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Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Fuel Ethanol Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 View History; U ...

2

Crude Oil Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

3

Lubricants Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

4

Propane/Propylene Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

5

Naphtha for Petrochemical Feedstock Use Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

6

Asphalt and Road Oil Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 View History; U ...

7

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: 2007 2008 2009 2010 2011 2012 View History; U.S. 1,665,345 ...

8

Motor Gasoline Blending Components Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

9

Ethane/Ethylene Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

10

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

11

Unfinished Oils - Naphthas and Lighter Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

12

Unfinished Oils - Heavy Gas Oils Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

13

Residual Fuel Oil Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

14

Normal Butane/Butylene Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

15

,"Crude Oil and Petroleum Products Total Stocks Stocks by Type"  

U.S. Energy Information Administration (EIA) Indexed Site

Total Stocks Stocks by Type" Total Stocks Stocks by Type" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description","# Of Series","Frequency","Latest Data for" ,"Data 1","Crude Oil and Petroleum Products Total Stocks Stocks by Type",6,"Monthly","9/2013","1/15/1956" ,"Release Date:","11/27/2013" ,"Next Release Date:","Last Week of December 2013" ,"Excel File Name:","pet_stoc_typ_a_ep00_sae_mbbl_m.xls" ,"Available from Web Page:","http://www.eia.gov/dnav/pet/pet_stoc_typ_a_ep00_sae_mbbl_m.htm" ,"Source:","Energy Information Administration" ,"For Help, Contact:","infoctr@eia.gov"

16

Crude Oil and Petroleum Products Total Stocks Stocks by Type  

U.S. Energy Information Administration (EIA) Indexed Site

Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Propane/Propylene Normal Butane/Butylene Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Comp. (MGBC) MGBC - Reformulated MGBC - Reformulated, RBOB MGBC - Reformulated, RBOB w/ Alcohol MGBC - Reformulated, RBOB w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Conventional Other Aviation Gasoline Blending Comp. Finished Motor Gasoline Reformulated Gasoline Reformulated Gasoline Blended w/ Fuel Ethanol Reformulated Gasoline, Other Conventional Gasoline Conventional Gasoline Blended Fuel Ethanol Conventional Gasoline Blended Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater 500 ppm Sulfur Residual Fuel Oil Residual F.O., than 1.00% Sulfur Petrochemical Feedstocks Naphtha for Petro. Feedstock Use Other Oils for Petro. Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products Period-Unit: Monthly-Thousand Barrels Annual-Thousand Barrels

17

Crude Oil Total Stocks Stocks by Type - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

18

U.S. Total Stocks  

Annual Energy Outlook 2012 (EIA)

Show Data By: Product Stock Type Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Crude Oil and Petroleum Products 1,806,501 1,817,459 1,817,679 1,817,508 1,820,533...

19

Stocks of Total Motor Gasoline  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

20

Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

West Coast (PADD 5) Total Stocks  

U.S. Energy Information Administration (EIA)

Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; Crude Oil and Petroleum Products: 148,209: 144,699: 141,778: 140,755: 140,174: 142,146: 1981 ...

22

Reformulated GTAB Gasoline Blending Components Total Stocks Stocks ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

23

Gulf Coast (PADD 3) Total Stocks  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

24

Lubricants Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

25

U.S. Propane Total Stocks  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: U.S. inventories of propane benefited from a late pre-season build that pushed inventories to over 65 million barrels by early November 2000, the second highest peak pre-heating season level since 1986. Although propane inventories were expected to remain within the normal range for the duration of the 2000-01 heating season, cold weather in November and December, along with recently high natural gas prices that discouraged propane production from gas processing, resulted in stocks falling below the normal range by the end of December. However, if the weather remains seasonally normal, and the recent decline in natural gas prices holds, EIA expects the propane inventory drawdown to slow. This is reflected in the data for January 19, which showed a draw of only 2.1 million barrels, compared to more than twice that

26

Propane/Propylene Natural Gas Processing Plant Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

27

Residual Fuel Oil Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: Jan-13 Feb-13 Mar-13 Apr-13 May-13 Jun-13 View History; U ...

28

U.S. Crude Oil and Petroleum Products Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Area: Feb-13 Mar-13 Apr-13 May-13 Jun-13 Jul-13 View History; Total Stocks: 1,790,732: 1,793,174: 1,806,501: 1,817,459: 1,817,679: 1,817,508: 1956-2013 ...

29

West Coast (PADD 5) CBOB Gasoline Blending Components Stocks by Type  

U.S. Energy Information Administration (EIA)

Stock Type: Area: 2007 2008 2009 2010 2011 2012 View History; Total Stocks: 1,769: 2,651: 3,784: 4,085: 3,756: 5,082: 2005-2012: Refinery: 1,001: 1,018: 1,022: 824 ...

30

Kerosene Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

31

Isobutane/Butylene Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

32

Crude Oil Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

33

Stocks of Kerosene-Type Jet Fuel  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

34

Petroleum Coke Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

35

Stocks of Total Crude Oil and Petroleum Products (Excl. SPR)  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

36

East Coast (PADD 1) Total Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

37

Stocks of Total Crude Oil and Petroleum Products (Including SPR)  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

38

Midwest (PADD 2) Total Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

39

Stocks of Total Motor Gasoline - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

40

Kerosene-Type Jet Fuel Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Low Total OECD Oil Stocks* Keep Market Balance Tight  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: This chart illustrates why EIA sees crude oil prices staying relatively high. It shows global inventories, as measured by OECD petroleum stocks. EIA sees a tenuous supply/demand balance over the remainder of 2001. Global inventories remain low, and need to recover to more adequate levels of forward demand coverage in order to avoid continued price volatility. The most recent data show OECD inventories remaining at very low levels. Low inventories increase the potential for price volatility throughout 2001. Inventories are a good measure of the supply/demand balance that affects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. OECD inventories illustrate the changes in the world petroleum

42

Pentanes Plus Pipeline Stocks by Type - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Stock Type: Download Series History: Definitions, Sources & Notes: Show Data By: Product: Stock Type: Area: 2007 2008 2009 2010 2011 2012 View History; U.S. 1,219 ...

43

Normal Butane/Butylene Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

44

U.S. Motor Gasoline Blending Components Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

45

East Coast (PADD 1) Crude Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

46

East Coast (PADD 1) Liquefied Petroleum Gases Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

47

Stocks by Type - Rocky Mountain (PADD 4) CBOB Gasoline Blending ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

48

Rocky Mountain (PADD 4) Crude Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

49

U.S. Renewable Diesel Fuel Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

50

Residuum Refinery Stocks by Type - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

51

U.S. Asphalt and Road Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

52

Crude Oil Non-SPR Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

53

Conventional Gasoline Blended Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

54

U.S. Crude Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

55

Ethane/Ethylene Natural Gas Processing Plant Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

56

MTBE Pipeline Stocks by Type - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

57

Crude Oil Tank Farms and Pipelines Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

58

Asphalt and Road Oil Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

59

Crude Oil Strategic Petroleum Reserve Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

60

Crude Oil Alaskan in Transit Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Crude Oil and Petroleum Products Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

62

U.S. Ethane/Ethylene Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

63

Refinery Grade Butane Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

64

Isobutane/Butylene Bulk Terminal Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

65

U.S. Refinery Grade Butane Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

66

Midwest (PADD 2) Refinery Grade Butane Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

67

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Earned FY2008 2,550,203 FY2009 39,646,446 FY2010 64,874,187 FY2011 66,253,207 FY2012...

68

U.S. Total Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

69

Do Innovations Really Pay Off? Total Stock Market Returns to Innovation  

Science Conference Proceedings (OSTI)

Critics often decry an earnings-focused short-term orientation of management that eschews spending on risky, long-term projects such as innovation to boost a firm's stock price. Such critics assume that stock markets react positively to announcements ... Keywords: Fama-French 3-factor model, event study, high-tech marketing, innovation, market returns

Ashish Sood; Gerard J. Tellis

2009-05-01T23:59:59.000Z

70

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Number: Number: Contract Type: Total Estimated Contract Cost: Performance Period Total Fee Earned FY2008 $2,550,203 FY2009 $39,646,446 FY2010 $64,874,187 FY2011 $66,253,207 FY2012 $41,492,503 FY2013 $0 FY2014 FY2015 FY2016 FY2017 FY2018 Cumulative Fee Earned $214,816,546 Fee Available $2,550,203 Minimum Fee $77,931,569 $69,660,249 Savannah River Nuclear Solutions LLC $458,687,779 $0 Maximum Fee Fee Information $88,851,963 EM Contractor Fee Site: Savannah River Site Office, Aiken, SC Contract Name: Management & Operating Contract September 2013 DE-AC09-08SR22470

71

U.S. Kerosene-Type Jet Fuel Stocks at Refineries (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Kerosene-Type Jet Fuel Stocks at Refineries (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1993: 13,255: 14,640: 14,907: 15,583: 14,878 ...

72

U.S. Total Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

History; Total Crude Oil and Petroleum Products (Incl. SPR) 1,793,174: 1,806,501: 1,817,459: 1,817,679: 1,817,508: 1,820,533: 1956-2013:

73

U.S. Total Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA) Indexed Site

Area: U.S. PADD 1 New England Central Atlantic Lower Atlantic PADD 2 Cushing, Oklahoma PADD 3 PADD 4 PADD 5 PADD's 4 & 5 Period: Weekly Monthly Annual Area: U.S. PADD 1 New England Central Atlantic Lower Atlantic PADD 2 Cushing, Oklahoma PADD 3 PADD 4 PADD 5 PADD's 4 & 5 Period: Weekly Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 11/08/13 11/15/13 11/22/13 11/29/13 12/06/13 12/13/13 View History Total Crude Oil and Petroleum Products (Incl. SPR) 1,806,930 1,795,196 1,793,557 1,786,470 1,781,747 1,769,150 1990-2013 Total Crude Oil and Petroleum Products (Excl. SPR) 1,110,961 1,099,227 1,097,588 1,090,501 1,085,778 1,073,181 1990-2013 Crude Oil (Including SPR) 1,084,057 1,084,432 1,087,385 1,081,800 1,071,215 1,068,274 1982-2013 Commercial Crude Oil

74

Stocks of Propane/Propylene  

U.S. Energy Information Administration (EIA)

Stocks held at natural gas processing plants are included in "Other Oils" and in totals. All stock levels are as of the end of the period.

75

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: The most recent data show OECD inventories remaining at very low levels. EIA expects inventories to remain low through the coming year. This increases the potential for price volatility through the rest of the winter, and into the next gasoline season. Inventories are a good measure of the supply/demand balance that affects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. As global oil production changed relative to demand, the world moved from a period of over-supply in 1998 to one of under-supply in 1999 and 2000. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in

76

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

The most recent data show OECD inventories remaining at very low The most recent data show OECD inventories remaining at very low levels. EIA expects inventories to remain low through the coming year. This increases the potential for price volatility through the winter, and even extending to the next gasoline season. Inventories are a good measure of the supply/demand balance that effects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. As global oil production changed relative to demand, the world moved from a period of over-supply in 1998 to one of under-supply in 1999 and 2000. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in

77

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: The most recent data show OECD inventories remaining at very low levels. EIA expects inventories to remain low through the coming year. This increases the potential for price volatility through the winter, and even extending to the next gasoline season. Inventories are a good measure of the supply/demand balance that effects prices. A large over-supply (production greater than demand) will put downward pressure on prices, while under-supply will push prices upward. As global oil production changed relative to demand, the world moved from a period of over-supply in 1998 to one of under-supply in 1999 and 2000. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in

78

Total OECD Oil Stocks*  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: As global production changed relative to demand, the world moved from a period of "over supply" in 1998 to one of "under supply" in 1999 and 2000. Inventories are a good means of seeing the imbalance between petroleum production and demand. For example, when production exceeds demand, inventories rise. A large over supply will put downward pressure on prices, while under supply will cause prices to rise. OECD inventories illustrate the changes in the world petroleum balance. OECD inventories rose to high levels during 1997 and 1998 when production exceeded demand and prices dropped to around $10 per barrel in December 1998. However, when demand exceeded production in 1999 and early 2000, inventories fell to the low levels seen above, and prices rose to $35 per

79

Total OECD Oil Stocks  

Gasoline and Diesel Fuel Update (EIA)

5 Notes: OECD oil inventory levels are not expected to rise sufficiently during the rest of the year to match the average levels seen prior to the wide swings since 1995. This...

80

U.S. Crude Oil Stocks by Type - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Rocky Mountain (PADD 4) Asphalt and Road Oil Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

82

Residual F.O. - 0.31 to 1.00% Sulfur Refinery Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

83

U.S. Reformulated RBOB Gasoline Blending Components Stocks by Type  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Crude oil stocks in the ...

84

How different types of restaurants behaved differently through the recent recession an analysis of stock market and financial ratios.  

E-Print Network (OSTI)

??This study attempted to identify, quantify, and explain the possible impact the recession had on restaurant stock performance in comparison with the S&P 500 index… (more)

Wang, Xiaofan

2012-01-01T23:59:59.000Z

85

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Total Energy Consumption in U.S. Households by Type of Housing Unit, 2001 RSE Column Factor: Total ... where the end use is electric air-conditioning, ...

86

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Census Division Total South...

87

STOCK AND DISTRIBUTION OF TOTAL AND CORN-DERIVED SOIL ORGANIC CARBON IN AGGREGATE AND PRIMARY PARTICLE FRACTIONS FOR DIFFERENT LAND USE AND SOIL MANAGEMENT PRACTICES  

Science Conference Proceedings (OSTI)

Land use, soil management, and cropping systems affect stock, distribution, and residence time of soil organic carbon (SOC). Therefore, SOC stock and its depth distribution and association with primary and secondary particles were assessed in long-term experiments at the North Appalachian Experimental Watersheds near Coshocton, Ohio, through *13C techniques. These measurements were made for five land use and soil management treatments: (1) secondary forest, (2) meadow converted from no-till (NT) corn since 1988, (3) continuous NT corn since 1970, (4) continuous NT corn-soybean in rotation with ryegrass since 1984, and (5) conventional plow till (PT) corn since 1984. Soil samples to 70-cm depth were obtained in 2002 in all treatments. Significant differences in soil properties were observed among land use treatments for 0 to 5-cm depth. The SOC concentration (g C kg*1 of soil) in the 0 to 5-cm layer was 44.0 in forest, 24.0 in meadow, 26.1 in NT corn, 19.5 in NT corn-soybean, and 11.1 i n PT corn. The fraction of total C in corn residue converted to SOC was 11.9% for NT corn, 10.6% for NT corn-soybean, and 8.3% for PT corn. The proportion of SOC derived from corn residue was 96% for NT corn in the 0 to 5-cm layer, and it decreased gradually with depth and was 50% in PT corn. The mean SOC sequestration rate on conversion from PT to NT was 280 kg C ha*1 y*1. The SOC concentration decreased with reduction in aggregate size, and macro-aggregates contained 15 to 35% more SOC concentration than microaggregates. In comparison with forest, the magnitude of SOC depletion in the 0 to 30-cm layer was 15.5 Mg C/ha (24.0%) in meadow, 12.7 Mg C/ha (19.8%) in NT corn, 17.3 Mg C/ha (26.8%) in NT corn-soybean, and 23.3 Mg C/ha (35.1%) in PT corn. The SOC had a long turnover time when located deeper in the subsoil.

Puget, P; Lal, Rattan; Izaurralde, R Cesar C.; Post, M; Owens, Lloyd

2005-04-01T23:59:59.000Z

88

U.S. Total Stocks  

U.S. Energy Information Administration (EIA) Indexed Site

Crude Oil and Petroleum Products Crude Oil and Petroleum Products 1,665,345 1,736,739 1,776,375 1,794,099 1,750,087 1,807,777 1956-2012 Crude Oil 983,046 1,027,663 1,051,795 1,059,975 1,026,630 1,060,764 1913-2012 All Oils (Excluding Crude Oil) 682,299 709,076 724,580 734,124 723,457 747,013 1993-2012 Pentanes Plus 10,278 13,775 10,481 12,510 17,596 12,739 1981-2012 Liquefied Petroleum Gases 95,592 113,134 102,147 108,272 111,778 140,529 1967-2012 Ethane/Ethylene 14,869 27,591 20,970 24,323 22,892 35,396 1967-2012 Propane/Propylene 52,007 55,408 50,140 49,241 54,978 67,991 1967-2012 Normal Butane/Butylene 21,862 23,031 24,149 27,652 26,779 28,574 1981-2012 Isobutane/Butylene 6,854 7,104 6,888 7,056 7,129 8,568 1981-2012 Other Hydrocarbons 29 20 41 42 2009-2012

89

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Division Total West Mountain Pacific Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

90

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

(millions) Census Division Total South Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC13.7...

91

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Census Division Total Midwest Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC12.7...

92

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Census Division Total Northeast Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC11.7...

93

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Census Division Total South Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

94

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

(millions) Census Division Total West Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC14.7...

95

Total  

Gasoline and Diesel Fuel Update (EIA)

Total Total .............. 16,164,874 5,967,376 22,132,249 2,972,552 280,370 167,519 18,711,808 1993 Total .............. 16,691,139 6,034,504 22,725,642 3,103,014 413,971 226,743 18,981,915 1994 Total .............. 17,351,060 6,229,645 23,580,706 3,230,667 412,178 228,336 19,709,525 1995 Total .............. 17,282,032 6,461,596 23,743,628 3,565,023 388,392 283,739 19,506,474 1996 Total .............. 17,680,777 6,370,888 24,051,665 3,510,330 518,425 272,117 19,750,793 Alabama Total......... 570,907 11,394 582,301 22,601 27,006 1,853 530,841 Onshore ................ 209,839 11,394 221,233 22,601 16,762 1,593 180,277 State Offshore....... 209,013 0 209,013 0 10,244 260 198,509 Federal Offshore... 152,055 0 152,055 0 0 0 152,055 Alaska Total ............ 183,747 3,189,837 3,373,584 2,885,686 0 7,070 480,828 Onshore ................ 64,751 3,182,782

96

U.S. Crude Oil and Petroleum Products Stocks by Type  

U.S. Energy Information Administration (EIA) Indexed Site

Product: Crude Oil and Petroleum Products Crude Oil All Oils (Excluding Crude Oil) Pentanes Plus Liquefied Petroleum Gases Ethane/Ethylene Ethylene Propane/Propylene Propylene (Nonfuel Use) Normal Butane/Butylene Refinery Grade Butane Isobutane/Butylene Other Hydrocarbons Oxygenates (excluding Fuel Ethanol) MTBE Other Oxygenates Renewables (including Fuel Ethanol) Fuel Ethanol Renewable Diesel Fuel Other Renewable Fuels Unfinished Oils Unfinished Oils, Naphthas & Lighter Unfinished Oils, Kerosene & Light Gas Unfinished Oils, Heavy Gas Oils Residuum Motor Gasoline Blending Comp. (MGBC) MGBC - Reformulated MGBC - Reformulated, RBOB MGBC - Reformulated, RBOB w/ Alcohol MGBC - Reformulated, RBOB w/ Ether MGBC - Reformulated, GTAB MGBC - Conventional MGBC - Conventional, CBOB MGBC - Conventional, GTAB MGBC - Conventional Other Aviation Gasoline Blending Comp. Finished Motor Gasoline Reformulated Gasoline Reformulated Gasoline Blended w/ Fuel Ethanol Reformulated Gasoline, Other Conventional Gasoline Conventional Gasoline Blended Fuel Ethanol Conventional Gasoline Blended Fuel Ethanol, Ed55 and Lower Conventional Other Gasoline Finished Aviation Gasoline Kerosene-Type Jet Fuel Kerosene Distillate Fuel Oil Distillate F.O., 15 ppm Sulfur and under Distillate F.O., Greater than 15 to 500 ppm Sulfur Distillate F.O., Greater 500 ppm Sulfur Residual Fuel Oil Residual F.O., than 1.00% Sulfur Petrochemical Feedstocks Naphtha for Petro. Feedstock Use Other Oils for Petro. Feedstock Use Special Naphthas Lubricants Waxes Petroleum Coke Asphalt and Road Oil Miscellaneous Products

97

Total............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Total................................................................... Total................................................................... 111.1 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546

98

Total...................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Single-Family Units Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Single-Family Units Detached Type of Housing Unit Table HC2.7 Air Conditioning Usage Indicators by Type of Housing Unit, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators Attached 2 to 4 Units 5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business

99

Total...................  

Gasoline and Diesel Fuel Update (EIA)

4,690,065 52,331,397 2,802,751 4,409,699 7,526,898 209,616 1993 Total................... 4,956,445 52,535,411 2,861,569 4,464,906 7,981,433 209,666 1994 Total................... 4,847,702 53,392,557 2,895,013 4,533,905 8,167,033 202,940 1995 Total................... 4,850,318 54,322,179 3,031,077 4,636,500 8,579,585 209,398 1996 Total................... 5,241,414 55,263,673 3,158,244 4,720,227 8,870,422 206,049 Alabama ...................... 56,522 766,322 29,000 62,064 201,414 2,512 Alaska.......................... 16,179 81,348 27,315 12,732 75,616 202 Arizona ........................ 27,709 689,597 28,987 49,693 26,979 534 Arkansas ..................... 46,289 539,952 31,006 67,293 141,300 1,488 California ..................... 473,310 8,969,308 235,068 408,294 693,539 36,613 Colorado...................... 110,924 1,147,743

100

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Q Q Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions) Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.2 Living Space Characteristics by Owner-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Million U.S. Housing Units Owner- Occupied Housing Units (millions) Type of Owner-Occupied Housing Unit Housing Units (millions)

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
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101

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Q Q Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005 2 to 4 Units 5 or More Units Mobile Homes Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing Units Renter- Occupied Housing Units (millions) Type of Renter-Occupied Housing Unit U.S. Housing Units (millions Single-Family Units Apartments in Buildings With-- Living Space Characteristics Detached Attached Table HC4.2 Living Space Characteristics by Renter-Occupied Housing Units, 2005

102

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

5.6 5.6 17.7 7.9 Personal Computers Do Not Use a Personal Computer.................................. 35.5 8.1 5.6 2.5 Use a Personal Computer.............................................. 75.6 17.5 12.1 5.4 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 14.1 10.0 4.0 Laptop Model............................................................. 16.9 3.4 2.1 1.3 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 3.4 2.5 0.9 2 to 15 Hours............................................................. 29.1 7.0 4.8 2.3 16 to 40 Hours........................................................... 13.5 2.8 2.1 0.7 41 to 167 Hours......................................................... 6.3

103

Total.......................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer ................... 35.5 6.4 2.2 4.2 Use a Personal Computer................................ 75.6 17.8 5.3 12.5 Number of Desktop PCs 1.................................................................. 50.3 11.0 3.4 7.6 2.................................................................. 16.2 4.4 1.3 3.1 3 or More..................................................... 9.0 2.5 0.7 1.8 Number of Laptop PCs 1.................................................................. 22.5 5.4 1.5 3.9 2.................................................................. 4.0 1.1 0.3 0.8 3 or More..................................................... 0.7 0.3 Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)...........................

104

Total.................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

... ... 111.1 20.6 15.1 5.5 Do Not Have Cooling Equipment................................. 17.8 4.0 2.4 1.7 Have Cooling Equipment............................................. 93.3 16.5 12.8 3.8 Use Cooling Equipment............................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it............................. 1.9 0.3 Q Q Type of Air-Conditioning Equipment 1, 2 Central System.......................................................... 65.9 6.0 5.2 0.8 Without a Heat Pump.............................................. 53.5 5.5 4.8 0.7 With a Heat Pump................................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................... 28.9 10.7 7.6 3.1 1 Unit.......................................................................

105

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 10.3 3.1 7.3 Have Cooling Equipment............................................ 93.3 13.9 4.5 9.4 Use Cooling Equipment............................................. 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it............................ 1.9 1.0 Q 0.8 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump............................................. 53.5 8.7 3.2 5.5 With a Heat Pump................................................. 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit..................................................................... 14.5 2.9 0.5 2.4 2 Units...................................................................

106

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................ 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................ 1.9 0.5 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................. 12.3 9.0 6.7 1.4 0.9 Window/Wall Units.................................................. 28.9 8.0 3.4 1.7 2.9 1 Unit.....................................................................

107

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Personal Computers Personal Computers Do Not Use a Personal Computer.................................. 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer.............................................. 75.6 26.6 14.5 4.1 7.9 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 20.5 11.0 3.4 6.1 Laptop Model............................................................. 16.9 6.1 3.5 0.7 1.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.0 2.6 1.0 1.3 2 to 15 Hours............................................................. 29.1 10.3 5.9 1.6 2.9 16 to 40 Hours........................................................... 13.5 4.1 2.3 0.6 1.2 41 to 167 Hours.........................................................

108

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.4 2.2 4.2 Use a Personal Computer.............................................. 75.6 17.8 5.3 12.5 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 13.7 4.2 9.5 Laptop Model............................................................. 16.9 4.1 1.1 3.0 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.9 0.9 2.0 2 to 15 Hours............................................................. 29.1 6.6 2.0 4.6 16 to 40 Hours........................................................... 13.5 3.4 0.9 2.5 41 to 167 Hours......................................................... 6.3

109

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 2.1 1.8 0.3 Have Cooling Equipment............................................ 93.3 23.5 16.0 7.5 Use Cooling Equipment............................................. 91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it............................ 1.9 Q Q Q Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 17.3 11.3 6.0 Without a Heat Pump............................................. 53.5 16.2 10.6 5.6 With a Heat Pump................................................. 12.3 1.1 0.8 0.4 Window/Wall Units.................................................. 28.9 6.6 4.9 1.7 1 Unit..................................................................... 14.5 4.1 2.9 1.2 2 Units...................................................................

110

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

25.6 25.6 40.7 24.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.9 1.0 500 to 999........................................................... 23.8 4.6 3.9 9.0 6.3 1,000 to 1,499..................................................... 20.8 2.8 4.4 8.6 5.0 1,500 to 1,999..................................................... 15.4 1.9 3.5 6.0 4.0 2,000 to 2,499..................................................... 12.2 2.3 3.2 4.1 2.6 2,500 to 2,999..................................................... 10.3 2.2 2.7 3.0 2.4 3,000 to 3,499..................................................... 6.7 1.6 2.1 2.1 0.9 3,500 to 3,999..................................................... 5.2 1.1 1.7 1.5 0.9 4,000 or More.....................................................

111

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 1.0 0.2 0.8 500 to 999........................................................... 23.8 6.3 1.4 4.9 1,000 to 1,499..................................................... 20.8 5.0 1.6 3.4 1,500 to 1,999..................................................... 15.4 4.0 1.4 2.6 2,000 to 2,499..................................................... 12.2 2.6 0.9 1.7 2,500 to 2,999..................................................... 10.3 2.4 0.9 1.4 3,000 to 3,499..................................................... 6.7 0.9 0.3 0.6 3,500 to 3,999..................................................... 5.2 0.9 0.4 0.5 4,000 or More.....................................................

112

Total.........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Floorspace (Square Feet) Floorspace (Square Feet) Total Floorspace 2 Fewer than 500.................................................. 3.2 Q 0.8 0.9 0.8 0.5 500 to 999.......................................................... 23.8 1.5 5.4 5.5 6.1 5.3 1,000 to 1,499.................................................... 20.8 1.4 4.0 5.2 5.0 5.2 1,500 to 1,999.................................................... 15.4 1.4 3.1 3.5 3.6 3.8 2,000 to 2,499.................................................... 12.2 1.4 3.2 3.0 2.3 2.3 2,500 to 2,999.................................................... 10.3 1.5 2.3 2.7 2.1 1.7 3,000 to 3,499.................................................... 6.7 1.0 2.0 1.7 1.0 1.0 3,500 to 3,999.................................................... 5.2 0.8 1.5 1.5 0.7 0.7 4,000 or More.....................................................

113

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

. . 111.1 20.6 15.1 5.5 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.5 0.4 500 to 999........................................................... 23.8 4.6 3.6 1.1 1,000 to 1,499..................................................... 20.8 2.8 2.2 0.6 1,500 to 1,999..................................................... 15.4 1.9 1.4 0.5 2,000 to 2,499..................................................... 12.2 2.3 1.7 0.5 2,500 to 2,999..................................................... 10.3 2.2 1.7 0.6 3,000 to 3,499..................................................... 6.7 1.6 1.0 0.6 3,500 to 3,999..................................................... 5.2 1.1 0.9 0.3 4,000 or More.....................................................

114

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 7.0 8.0 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.4 Q Q 0.5 500 to 999........................................................... 23.8 2.5 1.5 2.1 3.7 1,000 to 1,499..................................................... 20.8 1.1 2.0 1.5 2.5 1,500 to 1,999..................................................... 15.4 0.5 1.2 1.2 1.9 2,000 to 2,499..................................................... 12.2 0.7 0.5 0.8 1.4 2,500 to 2,999..................................................... 10.3 0.5 0.5 0.4 1.1 3,000 to 3,499..................................................... 6.7 0.3 Q 0.4 0.3 3,500 to 3,999..................................................... 5.2 Q Q Q Q 4,000 or More.....................................................

115

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

.. .. 111.1 24.5 1,090 902 341 872 780 441 Total Floorspace (Square Feet) Fewer than 500...................................... 3.1 2.3 403 360 165 366 348 93 500 to 999.............................................. 22.2 14.4 763 660 277 730 646 303 1,000 to 1,499........................................ 19.1 5.8 1,223 1,130 496 1,187 1,086 696 1,500 to 1,999........................................ 14.4 1.0 1,700 1,422 412 1,698 1,544 1,348 2,000 to 2,499........................................ 12.7 0.4 2,139 1,598 Q Q Q Q 2,500 to 2,999........................................ 10.1 Q Q Q Q Q Q Q 3,000 or More......................................... 29.6 0.3 Q Q Q Q Q Q Heated Floorspace (Square Feet) None...................................................... 3.6 1.8 1,048 0 Q 827 0 407 Fewer than 500......................................

116

Total...................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

2,033 2,033 1,618 1,031 791 630 401 Total Floorspace (Square Feet) Fewer than 500............................................... 3.2 357 336 113 188 177 59 500 to 999....................................................... 23.8 733 667 308 343 312 144 1,000 to 1,499................................................. 20.8 1,157 1,086 625 435 409 235 1,500 to 1,999................................................. 15.4 1,592 1,441 906 595 539 339 2,000 to 2,499................................................. 12.2 2,052 1,733 1,072 765 646 400 2,500 to 2,999................................................. 10.3 2,523 2,010 1,346 939 748 501 3,000 to 3,499................................................. 6.7 3,020 2,185 1,401 1,177 851 546 3,500 to 3,999................................................. 5.2 3,549 2,509 1,508

117

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 19.0 22.7 22.3 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 2.1 0.6 Q 0.4 500 to 999........................................................... 23.8 13.6 3.7 3.2 3.2 1,000 to 1,499..................................................... 20.8 9.5 3.7 3.4 4.2 1,500 to 1,999..................................................... 15.4 6.6 2.7 2.5 3.6 2,000 to 2,499..................................................... 12.2 5.0 2.1 2.8 2.4 2,500 to 2,999..................................................... 10.3 3.7 1.8 2.8 2.1 3,000 to 3,499..................................................... 6.7 2.0 1.4 1.7 1.6 3,500 to 3,999..................................................... 5.2 1.6 0.8 1.5 1.4 4,000 or More.....................................................

118

Total..........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.7 0.7 21.7 6.9 12.1 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................................... 3.2 0.9 0.6 Q Q 500 to 999........................................................... 23.8 9.0 4.2 1.5 3.2 1,000 to 1,499..................................................... 20.8 8.6 4.7 1.5 2.5 1,500 to 1,999..................................................... 15.4 6.0 2.9 1.2 1.9 2,000 to 2,499..................................................... 12.2 4.1 2.1 0.7 1.3 2,500 to 2,999..................................................... 10.3 3.0 1.8 0.5 0.7 3,000 to 3,499..................................................... 6.7 2.1 1.2 0.5 0.4 3,500 to 3,999..................................................... 5.2 1.5 0.8 0.3 0.4 4,000 or More.....................................................

119

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500................................... 3.2 1.9 0.9 Q Q Q 1.3 2.3 500 to 999........................................... 23.8 10.5 7.3 3.3 1.4 1.2 6.6 12.9 1,000 to 1,499..................................... 20.8 5.8 7.0 3.8 2.2 2.0 3.9 8.9 1,500 to 1,999..................................... 15.4 3.1 4.2 3.4 2.0 2.7 1.9 5.0 2,000 to 2,499..................................... 12.2 1.7 2.7 2.9 1.8 3.2 1.1 2.8 2,500 to 2,999..................................... 10.3 1.2 2.2 2.3 1.7 2.9 0.6 2.0 3,000 to 3,499..................................... 6.7 0.9 1.4 1.5 1.0 1.9 0.4 1.4 3,500 to 3,999..................................... 5.2 0.8 1.2 1.0 0.8 1.5 0.4 1.3 4,000 or More...................................... 13.3 0.9 1.9 2.2 2.0 6.4 0.6 1.9 Heated Floorspace

120

Total...........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500.................................... 3.2 0.7 Q 0.3 0.3 0.7 0.6 0.3 Q 500 to 999........................................... 23.8 2.7 1.4 2.2 2.8 5.5 5.1 3.0 1.1 1,000 to 1,499..................................... 20.8 2.3 1.4 2.4 2.5 3.5 3.5 3.6 1.6 1,500 to 1,999..................................... 15.4 1.8 1.4 2.2 2.0 2.4 2.4 2.1 1.2 2,000 to 2,499..................................... 12.2 1.4 0.9 1.8 1.4 2.2 2.1 1.6 0.8 2,500 to 2,999..................................... 10.3 1.6 0.9 1.1 1.1 1.5 1.5 1.7 0.8 3,000 to 3,499..................................... 6.7 1.0 0.5 0.8 0.8 1.2 0.8 0.9 0.8 3,500 to 3,999..................................... 5.2 1.1 0.3 0.7 0.7 0.4 0.5 1.0 0.5 4,000 or More...................................... 13.3

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Total................................................  

U.S. Energy Information Administration (EIA) Indexed Site

.. .. 111.1 86.6 2,522 1,970 1,310 1,812 1,475 821 1,055 944 554 Total Floorspace (Square Feet) Fewer than 500............................. 3.2 0.9 261 336 162 Q Q Q 334 260 Q 500 to 999.................................... 23.8 9.4 670 683 320 705 666 274 811 721 363 1,000 to 1,499.............................. 20.8 15.0 1,121 1,083 622 1,129 1,052 535 1,228 1,090 676 1,500 to 1,999.............................. 15.4 14.4 1,574 1,450 945 1,628 1,327 629 1,712 1,489 808 2,000 to 2,499.............................. 12.2 11.9 2,039 1,731 1,055 2,143 1,813 1,152 Q Q Q 2,500 to 2,999.............................. 10.3 10.1 2,519 2,004 1,357 2,492 2,103 1,096 Q Q Q 3,000 or 3,499.............................. 6.7 6.6 3,014 2,175 1,438 3,047 2,079 1,108 N N N 3,500 to 3,999.............................. 5.2 5.1 3,549 2,505 1,518 Q Q Q N N N 4,000 or More...............................

122

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Personal Computers Do Not Use a Personal Computer ........... 35.5 17.1 10.8 4.2 1.8 1.6 10.3 20.6 Use a Personal Computer......................... 75.6 9.6 18.0 16.4 11.3 20.3 6.4 17.9 Number of Desktop PCs 1.......................................................... 50.3 8.3 14.2 11.4 7.2 9.2 5.3 14.2 2.......................................................... 16.2 0.9 2.6 3.7 2.9 6.2 0.8 2.6 3 or More............................................. 9.0 0.4 1.2 1.3 1.2 5.0 0.3 1.1 Number of Laptop PCs 1.......................................................... 22.5 2.2 4.6 4.5 2.9 8.3 1.4 4.0 2.......................................................... 4.0 Q 0.4 0.6 0.4 2.4 Q 0.5 3 or More............................................. 0.7 Q Q Q Q 0.4 Q Q Type of Monitor Used on Most-Used PC Desk-top

123

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

20.6 20.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer ........... 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer......................... 75.6 13.7 17.5 26.6 17.8 Number of Desktop PCs 1.......................................................... 50.3 9.3 11.9 18.2 11.0 2.......................................................... 16.2 2.9 3.5 5.5 4.4 3 or More............................................. 9.0 1.5 2.1 2.9 2.5 Number of Laptop PCs 1.......................................................... 22.5 4.7 4.6 7.7 5.4 2.......................................................... 4.0 0.6 0.9 1.5 1.1 3 or More............................................. 0.7 Q Q Q 0.3 Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 7.9 11.4 15.4 10.2 Flat-panel LCD.................................

124

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer.................................. 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer.............................................. 75.6 30.3 12.5 18.1 14.7 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 22.9 9.8 14.1 11.9 Laptop Model............................................................. 16.9 7.4 2.7 4.0 2.9 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 5.7 1.8 2.9 3.2 2 to 15 Hours............................................................. 29.1 11.9 5.1 6.5 5.7 16 to 40 Hours........................................................... 13.5 5.5 2.5 3.3 2.2 41 to 167 Hours.........................................................

125

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

47.1 47.1 19.0 22.7 22.3 Personal Computers Do Not Use a Personal Computer ........... 35.5 16.9 6.5 4.6 7.6 Use a Personal Computer......................... 75.6 30.3 12.5 18.1 14.7 Number of Desktop PCs 1.......................................................... 50.3 21.1 8.3 10.7 10.1 2.......................................................... 16.2 6.2 2.8 4.1 3.0 3 or More............................................. 9.0 2.9 1.4 3.2 1.6 Number of Laptop PCs 1.......................................................... 22.5 9.1 3.6 6.0 3.8 2.......................................................... 4.0 1.5 0.6 1.3 0.7 3 or More............................................. 0.7 0.3 Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 17.7 7.5 10.2 9.6 Flat-panel LCD.................................

126

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.7 0.7 21.7 6.9 12.1 Personal Computers Do Not Use a Personal Computer ........... 35.5 14.2 7.2 2.8 4.2 Use a Personal Computer......................... 75.6 26.6 14.5 4.1 7.9 Number of Desktop PCs 1.......................................................... 50.3 18.2 10.0 2.9 5.3 2.......................................................... 16.2 5.5 3.0 0.7 1.8 3 or More............................................. 9.0 2.9 1.5 0.5 0.8 Number of Laptop PCs 1.......................................................... 22.5 7.7 4.3 1.1 2.4 2.......................................................... 4.0 1.5 0.9 Q 0.4 3 or More............................................. 0.7 Q Q Q Q Type of Monitor Used on Most-Used PC Desk-top CRT (Standard Monitor)................... 45.0 15.4 7.9 2.8 4.8 Flat-panel LCD.................................

127

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment............................... Do Not Have Cooling Equipment............................... 17.8 8.5 2.7 2.6 4.0 Have Cooling Equipment............................................ 93.3 38.6 16.2 20.1 18.4 Use Cooling Equipment............................................. 91.4 37.8 15.9 19.8 18.0 Have Equipment But Do Not Use it............................ 1.9 0.9 0.3 0.3 0.4 Type of Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 25.8 10.9 16.6 12.5 Without a Heat Pump............................................. 53.5 21.2 9.7 13.7 8.9 With a Heat Pump................................................. 12.3 4.6 1.2 2.8 3.6 Window/Wall Units.................................................. 28.9 13.4 5.6 3.9 6.1 1 Unit.....................................................................

128

Total..................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

78.1 78.1 64.1 4.2 1.8 2.3 5.7 Do Not Have Cooling Equipment..................... 17.8 11.3 9.3 0.6 Q 0.4 0.9 Have Cooling Equipment................................. 93.3 66.8 54.7 3.6 1.7 1.9 4.8 Use Cooling Equipment.................................. 91.4 65.8 54.0 3.6 1.7 1.9 4.7 Have Equipment But Do Not Use it................. 1.9 1.1 0.8 Q N Q Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 51.7 43.9 2.5 0.7 1.6 3.1 Without a Heat Pump.................................. 53.5 41.1 34.8 2.1 0.5 1.2 2.6 With a Heat Pump....................................... 12.3 10.6 9.1 0.4 Q 0.3 0.6 Window/Wall Units....................................... 28.9 16.5 12.0 1.3 1.0 0.4 1.7 1 Unit.......................................................... 14.5 7.2 5.4 0.5 0.2 Q 0.9 2 Units.........................................................

129

Total.........................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

..... ..... 111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer...................................... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer.................................................. 75.6 4.2 5.0 5.3 9.0 Most-Used Personal Computer Type of PC Desk-top Model............................................................. 58.6 3.2 3.9 4.0 6.7 Laptop Model................................................................. 16.9 1.0 1.1 1.3 2.4 Hours Turned on Per Week Less than 2 Hours......................................................... 13.6 0.7 0.9 0.9 1.4 2 to 15 Hours................................................................. 29.1 1.7 2.1 1.9 3.4 16 to 40 Hours............................................................... 13.5 0.9 0.9 0.9 1.8 41 to 167 Hours.............................................................

130

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

25.6 25.6 40.7 24.2 Personal Computers Do Not Use a Personal Computer.................................. 35.5 6.9 8.1 14.2 6.4 Use a Personal Computer.............................................. 75.6 13.7 17.5 26.6 17.8 Most-Used Personal Computer Type of PC Desk-top Model......................................................... 58.6 10.4 14.1 20.5 13.7 Laptop Model............................................................. 16.9 3.3 3.4 6.1 4.1 Hours Turned on Per Week Less than 2 Hours..................................................... 13.6 2.4 3.4 5.0 2.9 2 to 15 Hours............................................................. 29.1 5.2 7.0 10.3 6.6 16 to 40 Hours........................................................... 13.5 3.1 2.8 4.1 3.4 41 to 167 Hours.........................................................

131

Total..................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

33.0 33.0 8.0 3.4 5.9 14.4 1.2 Do Not Have Cooling Equipment..................... 17.8 6.5 1.6 0.9 1.3 2.4 0.2 Have Cooling Equipment................................. 93.3 26.5 6.5 2.5 4.6 12.0 1.0 Use Cooling Equipment.................................. 91.4 25.7 6.3 2.5 4.4 11.7 0.8 Have Equipment But Do Not Use it................. 1.9 0.8 Q Q 0.2 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 14.1 3.6 1.5 2.1 6.4 0.6 Without a Heat Pump.................................. 53.5 12.4 3.1 1.3 1.8 5.7 0.6 With a Heat Pump....................................... 12.3 1.7 0.6 Q 0.3 0.6 Q Window/Wall Units....................................... 28.9 12.4 2.9 1.0 2.5 5.6 0.4 1 Unit.......................................................... 14.5 7.3 1.2 0.5 1.4 3.9 0.2 2 Units.........................................................

132

Stocks of Residual Fuel Oil  

U.S. Energy Information Administration (EIA)

All stock levels are as of the end of the period. Data may not add to total due to independent rounding. Weekly data for RBOB with Ether, RBOB with Alcohol, ...

133

Total..................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

. . 111.1 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Do Not Have Cooling Equipment..................... 17.8 3.9 1.8 2.2 2.1 3.1 2.6 1.7 0.4 Have Cooling Equipment................................. 93.3 10.8 5.6 10.3 10.4 15.8 16.0 15.6 8.8 Use Cooling Equipment.................................. 91.4 10.6 5.5 10.3 10.3 15.3 15.7 15.3 8.6 Have Equipment But Do Not Use it................. 1.9 Q Q Q Q 0.6 0.4 0.3 Q Type of Air-Conditioning Equipment 1, 2 Central System.............................................. 65.9 3.7 2.6 6.1 6.8 11.2 13.2 13.9 8.2 Without a Heat Pump.................................. 53.5 3.6 2.3 5.5 5.8 9.5 10.1 10.3 6.4 With a Heat Pump....................................... 12.3 Q 0.3 0.6 1.0 1.7 3.1 3.6 1.7 Window/Wall Units....................................... 28.9 7.3 3.2 4.5 3.7 4.8 3.0 1.9 0.7 1 Unit..........................................................

134

Total..............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment................ Do Not Have Cooling Equipment................ 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment.............................. 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Type of Air-Conditioning Equipment 1, 2 Central System.......................................... 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit...................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units....................................................

135

Table CE1-4c. Total Energy Consumption in U.S. Households by Type ...  

U.S. Energy Information Administration (EIA)

Table CE1-4c. Total Energy Consumption in U.S. Households by Type of Housing Unit, 1997 ... where the end use is electric air-conditioning, ...

136

Baldrige Stock Studies  

Science Conference Proceedings (OSTI)

Baldrige Stock Studies. From 1994 through 2004, the Baldrige Performance Excellence Program conducted studies around ...

2013-06-27T23:59:59.000Z

137

Stock mechanics: theory of conservation of total energy and predictions of coming short-term fluctuations of Dow Jones Industrials Average (DJIA)  

E-Print Network (OSTI)

Predicting absolute magnitude of fluctuations of price, even if their sign remains unknown, is important for risk analysis and for option prices. In the present work, we display our predictions about absolute magnitude of daily fluctuations of the Dow Jones Industrials Average (DJIA), utilizing the original theory of conservation of total energy, for the coming 500 days.

Tuncay, C

2006-01-01T23:59:59.000Z

138

Second NIST Stock Investment Study "Quality Stocks" Yield ...  

Science Conference Proceedings (OSTI)

... Study Finds "Quality Stocks" Yield Big Payoff Second NIST Stock Investment Study February 1996 A second NIST stock investment study (the first ...

2013-09-11T23:59:59.000Z

139

A quantum mechanical model for the relationship between stock price and stock ownership  

SciTech Connect

The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schroedinger type equation.

Cotfas, Liviu-Adrian [Faculty of Economic Cybernetics, Statistics and Informatics, Academy of Economic Studies, 6 Piata Romana, 010374 Bucharest (Romania)

2012-11-01T23:59:59.000Z

140

A quantum mechanical model for the relationship between stock price and stock ownership  

E-Print Network (OSTI)

The trade of a fixed stock can be regarded as the basic process that measures its momentary price. The stock price is exactly known only at the time of sale when the stock is between traders, that is, only in the case when the owner is unknown. We show that the stock price can be better described by a function indicating at any moment of time the probabilities for the possible values of price if a transaction takes place. This more general description contains partial information on the stock price, but it also contains partial information on the stock owner. By following the analogy with quantum mechanics, we assume that the time evolution of the function describing the stock price can be described by a Schrodinger type equation.

Liviu-Adrian Cotfas

2012-07-14T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

cutting stock problem  

Science Conference Proceedings (OSTI)

NIST. cutting stock problem. (classic problem). Definition: Find the best arrangement of shapes on rectangles to minimize ...

2013-08-23T23:59:59.000Z

142

Game Analysis of the Evolution of Artificial Stock Market  

Science Conference Proceedings (OSTI)

In this paper, we build the participators’ logistic model of the game model in artificial stock market. The participators are three types: flexible agent, semi-flexible agent and rigidity agent. Then, we set up the game model in artificial stock ... Keywords: Artificial stock market, Game model, Agent

She Zhenyu; Yan Bo

2010-12-01T23:59:59.000Z

143

FY12 -TOTAL AWARDS BY SPONSOR TYPE AND UNIT Unit Federal Industry International Private Foundation Local Government TotalOther Private State  

E-Print Network (OSTI)

FY12 - TOTAL AWARDS BY SPONSOR TYPE AND UNIT Unit Federal Industry International Private Foundation to an identified unit (or units)---typically to the employee's academic department(s). Colleges/Schools COLLEGE and Administrative Units VP FOR RESEARCH UNITS $ 15,456,303 $ 856,884 $ 0 $ 35,000 $ 100,129 $ 2,755,103 $ 2

Arnold, Jonathan

144

U.S. Propane Total Stocks  

Gasoline and Diesel Fuel Update (EIA)

6 Notes: U.S. inventories of propane benefited from a late pre-season build that pushed inventories to over 65 million barrels by early November 2000, the second highest peak...

145

U.S. Propane Total Stocks  

Gasoline and Diesel Fuel Update (EIA)

7 Notes: U.S. inventories of propane benefited from a late pre-season build that pushed inventories to over 65 million barrels by early November 2000, the second highest peak...

146

Ending Stocks - Total Fuel Ethanol & Oxygenates  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: See Definitions ...

147

Information flow between composite stock index and individual stocks  

E-Print Network (OSTI)

We investigate the strength and the direction of information transfer in the U.S. stock market between the composite stock price index of stock market and prices of individual stocks using the transfer entropy. Through the directionality of the information transfer, we find that individual stocks are influenced by the index of the market.

Kwon, Okyu

2007-01-01T23:59:59.000Z

148

Stocks of Fuel Ethanol  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

149

stocked inventory.PDF  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

08 08 AUDIT REPORT STOCKED INVENTORY AT THE SAVANNAH RIVER SITE U.S. DEPARTMENT OF ENERGY OFFICE OF INSPECTOR GENERAL OFFICE OF AUDIT SERVICES JUNE 2001 MEMORANDUM FOR THE SECRETARY FROM: Gregory H. Friedman (Signed) Inspector General SUBJECT: INFORMATION: Audit Report on "Stocked Inventory at the Savannah River Site" BACKGROUND The Department of Energy's (Department) management and operating contractor at the Savannah River Site, Westinghouse Savannah River Company (Westinghouse), is responsible for managing the majority of the Department's missions and associated stocked inventory at the site. As of March 2001, Westinghouse maintained about

150

Japanese coastal fishery stocks.  

E-Print Network (OSTI)

In United Nations Convention on the Law of the Sea (UNCLOS), it was enshrined that "States shall take measures which are designed, on the best scientific evidence available to the States concerned, to maintain or restore populations of harvested species at levels which can produce the maximum sustainable yield (MSY)". However considering the current status of scientific knowledge for the fishery target species in Japan, it is practical that MSY can be defined as the optimal yield under the proper fishery stock management (Japanese Fishery Agency 2012). In Japan, the allowable biological catch (ABC) is estimated for important coastal fishery stocks. The threshold level of stock (Blimit: the minimum stock biomass to ensure an appropriate amount of recruitment) is defined and if the biomass is above Blimit, ABC is calculated based on various reference points which ensure sustainable yields. If the biomass is below Blimit, tighter ABC is set to recover the stock. If the stock biomass is extremely low (below Bban), fishing moratorium or similar measure will be recommended.

Minoru Kanaiwa; Minoru Kanaiwa

2012-01-01T23:59:59.000Z

151

Low Gasoline Stocks Indicate Increased Odds of Spring Volatility  

Gasoline and Diesel Fuel Update (EIA)

We cannot just focus on distillate. Gasoline will likely be our next We cannot just focus on distillate. Gasoline will likely be our next major concern. Gasoline stock levels have fallen well below the typical band for this time of year, primarily for the same reason distillate stocks fell to low levels -- namely relatively low production due to low margins. At the end of January, total gasoline inventories were almost 13 million barrels (6%) below the low end of the normal band. While gasoline stocks are generally not as important a supply source to the gasoline market this time of year as are distillate stocks to the distillate market, gasoline stocks still are needed. Gasoline stocks are usually used to help meet gasoline demand during February and March as refiners go through maintenance and turnarounds, but we do not have the

152

U.S. Total Propane (Consumer Grade) Prices by Sales Type  

U.S. Energy Information Administration (EIA) Indexed Site

Area: U.S. East Coast (PADD 1) New England (PADD 1A) Central Atlantic (PADD 1B) Lower Atlantic (PADD 1C) Midwest (PADD 2) Gulf Coast (PADD 3) Rocky Mountain (PADD 4) West Coast (PADD 5) Period: Monthly Annual Area: U.S. East Coast (PADD 1) New England (PADD 1A) Central Atlantic (PADD 1B) Lower Atlantic (PADD 1C) Midwest (PADD 2) Gulf Coast (PADD 3) Rocky Mountain (PADD 4) West Coast (PADD 5) Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Sales Type Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History Sales to End Users, Average - - - - - - 1993-2013 Residential - - - - - - 1993-2013 Commercial/Institutional - - - - - - 1993-2013 Industrial - - - - - - 1993-2013 Through Retail Outlets - - - - - - 1993-2013 Petro-Chemical - - - - - - 1994-2013 Other End Users - - - - - - 1993-2013 Sales for Resale

153

Distillate Stocks Expected  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: So let's get to what you want to know. What do we expect this upcoming winter? When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain towards the lower end of the normal range. We are forecasting about an 11 million barrel build between the end of July 2001 and the end of November 2001, slightly more than the average over the past 5 years (10 million barrels), but less than the average of the last 10 years (15 ½ million barrels). If, however, economic incentives are high enough, distillate stocks could build more, resulting in a higher distillate stock level heading into the winter. Of course, the reverse is true as well, if for example, the distillate fuel refining spread declines substantially. Since 1994,

154

PAD District III Stocks  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: PADD 3 (the Gulf Coast) inventories, at the end of July, stood at 33.5 million barrels and are well above the normal range for this time of year. Since we have a few months more to go until the beginning of the heating season, there is still time for the plentiful stocks in the Gulf Coast to find their way up into the Midwest. Thus, even though propane stocks in the Midwest are low, this could easily not be the case by the beginning of the heating season. One slight area of concern, however, is that the Texas Eastern Pipeline (TET) is experiencing brine problems due to heavy rains and record stock builds. To help alleviate the problem, some chemical companies are shifting their propane out of TET to other storage facilities. At this time we don't feel that this will negatively affect the propane market this

155

PADD 3 Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

All stock levels are as of the end of the period. Data may not add to total due to independent rounding. Weekly data for RBOB with Ether, RBOB with Alcohol, ...

156

Stocks of Propane/Propylene - Energy Information Administration  

U.S. Energy Information Administration (EIA)

All stock levels are as of the end of the period. Data may not add to total due to independent rounding. Weekly data for RBOB with Ether, RBOB with Alcohol, ...

157

Cushing, Oklahoma Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

All stock levels are as of the end of the period. Data may not add to total due to independent rounding. Weekly data for RBOB with Ether, RBOB with Alcohol, ...

158

Value-Added Stock Loan Participation Program | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Value-Added Stock Loan Participation Program Value-Added Stock Loan Participation Program Value-Added Stock Loan Participation Program < Back Eligibility Agricultural Savings Category Bioenergy Solar Buying & Making Electricity Wind Maximum Rebate RFA provides up to 45% of the loan up to $40,000 of loan principal Program Info Start Date 1994 State Minnesota Program Type State Loan Program Provider Minnesota Department of Agriculture The Value-Added Stock Loan Participation Program was created in 1994 and is designed to help farmers finance the purchase of stock in certain types of cooperative, limited liability company, or limited liability partnership that will produce a "value-added agricultural product." This may include wind energy and anaerobic-digestion cooperatives if they meet the

159

Property:StockSymbol | Open Energy Information  

Open Energy Info (EERE)

StockSymbol StockSymbol Jump to: navigation, search This is a property of type String. Pages using the property "StockSymbol" Showing 25 pages using this property. (previous 25) (next 25) A A.O. Smith + AOS + AAON + AAON + Alterra Power + MGMXF + Ameresco, Inc. + AMRC + Applied Materials + AMAT + Archer Daniels Midland + ADM + Autodesk + ADSK + C China Integrated Energy + CBEH + E EEMAP, Inc. + N/A + EnerNOC + ENOC + Evergreen Solar, Inc. + ESLR + ExxonMobil + XOM + G General Electric + GE + Geothermal Resources Council + Geothermal Resources Council + Goodwill Instrument + TPE 2423 + GreenShift Corporation + GERS.OB + Gulfsands Petroleum + AIM:GPX + H Helix Wind Corp. + HLXW + I ICF International + NASDAQ:ICFI + J Johnson Controls + JCI + M Molycorp Inc. + MCP +

160

Results of Baldrige Winners' Common Stock Comparison ...  

Science Conference Proceedings (OSTI)

... Results of Baldrige Winners' Common Stock Comparison Third NIST Stock Investment Study February 1997 Methodology: A hypothetical sum was ...

2013-09-11T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Table 7.6 Coal Stocks by Sector, End of Year 1949-2011 ...  

U.S. Energy Information Administration (EIA)

Table 7.6 Coal Stocks by Sector, End of Year 1949-2011 (Million Short Tons) Year: Producers and Distributors: Consumers: Total: Residential

162

Jim Stock | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Jim Stock Jim Stock About Us Jim Stock - Member - White House Council of Economic Advisers James H. Stock is a member of the Council of Economic Advisers and is responsible for offering the President objective advice on the formulation of economic policy. Stock was previously the Chief Economist for the Council of Economic Advisers. He is on leave from Harvard University where he is the Harold Hitchings Burbank Professor of Political Economy in the Department of Economics, with a dual appointment in the Harvard Kennedy School. Dr. Stock served as Chair of the Harvard Economics Department from 2006 to 2009 and has been a professor at Harvard continuously since 1983, with the exception of a two-year appointment at UC Berkeley from 1990 to 1991. His research focuses on macroeconomic forecasting, monetary policy, and

163

Stocks of Distillate Fuel Oil  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

164

Stocks of Crude Oil, Commercial  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

165

Stock Mechanics: a classical approach  

E-Print Network (OSTI)

New theoretical approaches about forecasting stock markets are proposed. A mathematization of the stock market in terms of arithmetical relations is given, where some simple (non-differential, non-fractal) expressions are also suggested as general stock price formuli in closed forms which are able to generate a variety of possible price movements in time. A kind of mechanics is submitted to cover the price movements in terms of classical concepts. Where utilizing stock mechanics to grow the portfolios in real markets is also proven.

Tuncay, C

2005-01-01T23:59:59.000Z

166

Stock Market and Consumption: Evidence from China  

E-Print Network (OSTI)

A. 1992. Understanding Consumption. Cambridge, UK: CambridgeStock market wealth and consumption. The Journal of Economic139–146. Stock Market and Consumption: Evidence from China

Hau, Leslie C

2011-01-01T23:59:59.000Z

167

Average Stock Levels: Crude Market & Propane  

U.S. Energy Information Administration (EIA)

This graph shows that propane was not alone in experiencing excess supply in 1998 and extraordinary stock builds. Note that the graph shows average stock levels ...

168

Buildings Stock Load Control  

E-Print Network (OSTI)

Researchers and practitioners have proposed a variety of solutions to reduce electricity consumption and curtail peak demand. This research focuses on electricity demand control by applying some strategies in existing building to reduce it during the extreme climate period. The first part of this paper presents the objectives of the study: ? to restrict the startup polluting manufacturing units (power station), ? to limit the environmental impacts (greenhouse emission), ? to reduce the transport and distribution electricity infrastructures The second part presents the approach used to rise the objectives : ? To aggregat the individual loads and to analyze the impact of different strategies from load shedding to reduce peak power demand by: ? Developing models of tertiary buildings stocks (Schools, offices, Shops, hotels); ? Making simulations for different load shedding strategies to calculate potential peak power saving. The third part is dedicated to the description of the developed models: An assembly of the various blocks of the library of simbad and simulink permit to model building. Finally the last part prensents the study results: Graphs and tables to see the load shedding strategies impacts.

Joutey, H. A.; Vaezi-Nejad, H.; Clemoncon, B.; Rosenstein, F.

2006-01-01T23:59:59.000Z

169

Table 38. Coal Stocks at Coke Plants by Census Division  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Stocks at Coke Plants by Census Division Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Table 38. Coal Stocks at Coke Plants by Census Division (thousand short tons) U.S. Energy Information Administration | Quarterly Coal Report, April - June 2013 Census Division June 30, 2013 March 31, 2013 June 30, 2012 Percent Change (June 30) 2013 versus 2012 Middle Atlantic w w w w East North Central 1,313 1,177 1,326 -1.0 South Atlantic w w w w East South Central w w w w U.S. Total 2,500 2,207 2,295 8.9 w = Data withheld to avoid disclosure. Note: Total may not equal sum of components because of independent rounding. Source: U.S. Energy Information Administration (EIA), Form EIA-5, 'Quarterly Coal Consumption and Quality Report - Coke Plants.'

170

Stocks of Total Crude Oil and Petroleum Products (Including SPR)  

U.S. Energy Information Administration (EIA)

Weekly data for RBOB with Ether, RBOB with Alcohol, and Reformulated GTAB Motor Gasoline Blending Components are discontinued as of the week ending June 4, ...

171

Total Imports  

U.S. Energy Information Administration (EIA) Indexed Site

Data Series: Imports - Total Imports - Crude Oil Imports - Crude Oil, Commercial Imports - by SPR Imports - into SPR by Others Imports - Total Products Imports - Total Motor Gasoline Imports - Finished Motor Gasoline Imports - Reformulated Gasoline Imports - Reformulated Gasoline Blended w/ Fuel Ethanol Imports - Other Reformulated Gasoline Imports - Conventional Gasoline Imports - Conv. Gasoline Blended w/ Fuel Ethanol Imports - Conv. Gasoline Blended w/ Fuel Ethanol, Ed55 & Ed55 Imports - Other Conventional Gasoline Imports - Motor Gasoline Blend. Components Imports - Motor Gasoline Blend. Components, RBOB Imports - Motor Gasoline Blend. Components, RBOB w/ Ether Imports - Motor Gasoline Blend. Components, RBOB w/ Alcohol Imports - Motor Gasoline Blend. Components, CBOB Imports - Motor Gasoline Blend. Components, GTAB Imports - Motor Gasoline Blend. Components, Other Imports - Fuel Ethanol Imports - Kerosene-Type Jet Fuel Imports - Distillate Fuel Oil Imports - Distillate F.O., 15 ppm Sulfur and Under Imports - Distillate F.O., > 15 ppm to 500 ppm Sulfur Imports - Distillate F.O., > 500 ppm to 2000 ppm Sulfur Imports - Distillate F.O., > 2000 ppm Sulfur Imports - Residual Fuel Oil Imports - Propane/Propylene Imports - Other Other Oils Imports - Kerosene Imports - NGPLs/LRGs (Excluding Propane/Propylene) Exports - Total Crude Oil and Products Exports - Crude Oil Exports - Products Exports - Finished Motor Gasoline Exports - Kerosene-Type Jet Fuel Exports - Distillate Fuel Oil Exports - Residual Fuel Oil Exports - Propane/Propylene Exports - Other Oils Net Imports - Total Crude Oil and Products Net Imports - Crude Oil Net Imports - Petroleum Products Period: Weekly 4-Week Avg.

172

Stock Market and Consumption: Evidence from China  

E-Print Network (OSTI)

9] Funke, Norbert. 2004. Is there a stock market wealth e?ect in emerging markets? Economics Letters, 83, 417–21. [10]C. 1990. Has the stock market crash reduced consumer spend-

Hau, Leslie C

2011-01-01T23:59:59.000Z

173

Distillate Stocks Expected to Remain Low  

Gasoline and Diesel Fuel Update (EIA)

8 Notes: When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year. - Stocks...

174

Essays on predictability of stock returns  

E-Print Network (OSTI)

This thesis consists of three chapters exploring predictability of stock returns. In the first chapter, I suggest a new approach to analysis of stock return predictability. Instead of relying on predictive regressions, I ...

Rytchkov, Oleg

2007-01-01T23:59:59.000Z

175

Political Cycles and the Stock Market  

E-Print Network (OSTI)

forecast the stock market as controls for business cycle ?uctuations. After controlling for the dividend-price

Santa-Clara, Pedro; Valkanov, Rossen

2000-01-01T23:59:59.000Z

176

Stocking rate effects on intensive-early stocked Flint Hills bluestem range  

E-Print Network (OSTI)

Stocking rate effects on intensive-early stocked Flint Hills bluestem range CLENTON E. OWENSBY, ROBERT COCHRAN, AND ED F. SMITH Stocking rate effects on intensive-early stocked Kansas Flint Hills range- lands is limited to the first 2 1/ 2 months of the growing season in the Kansas Flint Hills. Grazing

Owensby, Clenton E.

177

Forecast Technical Document Growing Stock Volume  

E-Print Network (OSTI)

Forecast Technical Document Growing Stock Volume Forecasts A document describing how growing stock (`standing') volume is handled in the 2011 Production Forecast. Tom Jenkins Robert Matthews Ewan Mackie Lesley Halsall #12;PF2011 ­ Growing stock volume forecasts Background A forecast of standing volume (or

178

EQUUS Total Return Inc | Open Energy Information  

Open Energy Info (EERE)

EQUUS Total Return Inc EQUUS Total Return Inc Jump to: navigation, search Name EQUUS Total Return Inc Place Houston, Texas Product A business development company and VC investor that trades as a closed-end fund. EQUUS is managed by MCC Global NV, a Frankfurt stock exchange listed management and merchant banking group. Coordinates 29.76045°, -95.369784° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.76045,"lon":-95.369784,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

179

Low Stocks Mean Tight Markets  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Like those for other petroleum products, gasoline inventories have been running below normal. As of the latest weekly data, stocks are about 5% lower than the low end of the normal range for this time of year. Behind all of the low product inventories are low crude oil inventories. Recall that the crude market tightened in 1999 when OPEC cut back production. Demand was greater than supply and inventories were used to make up the difference. They have not yet recovered. Crude oil inventories are running about 7% below the low end of the normal range for this time of year. After last week's very large stock draw, it appears inventories are the lowest that they have been since December 1975. The U.S. inventory data will be an important price barometer to

180

Distillate Stocks Expected to Remain Low  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: When EIA's demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year. - Stocks are beginning at very low levels. The September 1 distillate fuel stock level (112 million barrels) is nearly 20% less than last year, and about 15% below the 10 year average for end of August levels. - But stocks on the East Coast, at 39.8 million barrels, are 39% behind year-ago levels, and about a similar percentage below end-of-August 10-year average levels. Over the last 10 years, the average stock build from the end of August through the end of November has been about 10 million barrels. We are forecasting about a 12 million barrel build, which does not reach the normal band. Forecast stocks peak at the end of November at 127 million

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

WILD RICE SALAD RECIPE 1 quart water, chicken stock or vegetable stock  

E-Print Network (OSTI)

WILD RICE SALAD RECIPE 1 quart water, chicken stock or vegetable stock 1 cup wild rice, rinsed Sea ground pepper to taste 4 tablespoons extra virgin olive oil 2 tablespoons buttermilk or plain low-fat

Blanchette, Robert A.

182

How Predictable Is The Chinese Stock Market?.  

E-Print Network (OSTI)

?? We analyze return predictability for the Chinese stock market, including the aggregate market portfolio and the components of the aggregate market, such as portfolios… (more)

Jiang, Fuwei

2011-01-01T23:59:59.000Z

183

Low Stocks Set Stage for Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

left heating oil markets in a vulnerable position. Stocks began the winter of 199900 well above average. They deteriorated somewhat as low margins kept refiners from continuing...

184

Stocks of Motor Gasoline Blending Components  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

185

Stocks of Motor Gasoline Blending Components, CBOB  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

186

Integer Solutions to Cutting Stock Problems  

E-Print Network (OSTI)

ting Stock Problem (CSP) that can be described as follows: find the most ... two integer linear programming models for the one-dimensional CSP differing in.

187

Models for the two-dimensional two-stage cutting stock problem with multiple stock size  

Science Conference Proceedings (OSTI)

We consider a Two-Dimensional Cutting Stock Problem (2DCSP) where stock of different sizes is available, and a set of rectangular items has to be obtained through two-stage guillotine cuts. We propose and computationally compare three Mixed-Integer Programming ... Keywords: Computational experiments, Cutting stock problem, Mixed-integer programming models

Fabio Furini, Enrico Malaguti

2013-08-01T23:59:59.000Z

188

Intensive-Early Stocking and Season-Long Stocking of Kansas Flint Hills Range  

E-Print Network (OSTI)

Intensive-Early Stocking and Season-Long Stocking of Kansas Flint Hills Range ED F. SMITH AND CLENTON E. OWENSBY Highlight: Native Flint Hills bluestem range was stocked at twice the normal rate, 1 gains during the latter half of the growing season on Kansas Flint Hills range are barely one-half those

Owensby, Clenton E.

189

Shandong Jinjing Science Technology Stock Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Shandong Jinjing Science Technology Stock Co Ltd Shandong Jinjing Science Technology Stock Co Ltd Jump to: navigation, search Name Shandong Jinjing Science & Technology Stock Co Ltd Place Zibo, Shandong Province, China Zip 255200 Sector Solar Product Zibo-based glass producer. The firm makes low-iron super white glass for use in solar modules. Coordinates 36.799999°, 118.050003° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":36.799999,"lon":118.050003,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

190

Iowa Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

Notes: Distillate stocks located in the Northeast Heating Oil Reserve are not included. Stocks are reported as of the last day of the month.

191

Oregon Refinery, Bulk Terminal, and Natural Gas Plant Stocks ...  

U.S. Energy Information Administration (EIA)

Notes: Distillate stocks located in the Northeast Heating Oil Reserve are not included. Stocks are reported as of the last day of the month.

192

Kentucky Refinery, Bulk Terminal, and Natural Gas Plant Stocks ...  

U.S. Energy Information Administration (EIA)

Notes: Distillate stocks located in the Northeast Heating Oil Reserve are not included. Stocks are reported as of the last day of the month.

193

Information Efficiency Comparison Between Shanghai and Hongkong Stock Markets.  

E-Print Network (OSTI)

??This thesis starts with the introduction of Shanghai stock market, Hong Kong stock market and efficient market hypothesis. It then tries to compare the information… (more)

Qu, Huan

2008-01-01T23:59:59.000Z

194

A quantum model for the stock market  

E-Print Network (OSTI)

Beginning with several basic hypotheses of quantum mechanics, we give a new quantum model in econophysics. In this model, we define wave functions and operators of the stock market to establish the Schr\\"odinger equation for the stock price. Based on this theoretical framework, an example of a driven infinite quantum well is considered, in which we use a cosine distribution to simulate the state of stock price in equilibrium. After adding an external field into the Hamiltonian to analytically calculate the wave function, the distribution and the average value of the rate of return are shown.

Chao Zhang; Lu Huang

2010-09-24T23:59:59.000Z

195

Distillate Stocks Expected to Remain Low  

U.S. Energy Information Administration (EIA)

When EIA’s demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year.

196

Ohio Distillate Fuel Oil Stocks at Refineries, Bulk Terminals, and ...  

U.S. Energy Information Administration (EIA)

Ohio Distillate Fuel Oil Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

197

Wisconsin Propane and Propylene Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Wisconsin Propane and Propylene Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

198

Michigan Finished Motor Gasoline Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Michigan Finished Motor Gasoline Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

199

An efficient CMAC neural network for stock index forecasting  

Science Conference Proceedings (OSTI)

Stock index forecasting is one of the major activities of financial firms and private investors in making investment decisions. Although many techniques have been developed for predicting stock index, building an efficient stock index forecasting model ... Keywords: Back-propagation neural network, Cerebellar model articulation controller, Neural network, Stock index forecasting, Support vector regression

Chi-Jie Lu; Jui-Yu Wu

2011-11-01T23:59:59.000Z

200

Long-term Stock Market Forecasting using Gaussian Processes  

E-Print Network (OSTI)

Address3 email4 Abstract5 Forecasting stock market prices is an attractive topic to researchers from6 to analyze18 and forecast stock prices and index changes. The accuracy of these techniques is still an19-term predictions in stock prices.32 33 1.2 Motivation34 In stock market, investors need long-term forecasting

de Freitas, Nando

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Alaska Prices, Sales Volumes & Stocks - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

Prices, Sales Volumes & Stocks by State Area: Period: Download Series History: Definitions, Sources ...

202

Colorado Propane and Propylene Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Colorado Propane and Propylene Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

203

Colorado Finished Motor Gasoline Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

Colorado Finished Motor Gasoline Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

204

South Dakota Distillate Fuel Oil Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

South Dakota Distillate Fuel Oil Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

205

South Dakota Propane and Propylene Stocks at Refineries, Bulk ...  

U.S. Energy Information Administration (EIA)

South Dakota Propane and Propylene Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

206

national total  

U.S. Energy Information Administration (EIA)

AC Argentina AR Aruba AA Bahamas, The BF Barbados BB Belize BH Bolivia BL Brazil BR Cayman Islands CJ ... World Total ww NA--Table Posted: December 8, ...

207

Macroeconomic determinants of the stock market movements: empirical evidence from the Saudi stock market.  

E-Print Network (OSTI)

??This dissertation investigates the long run and short run relationships between Saudi stock market returns and eight macroeconomic variables. We investigate the ability of these… (more)

Alshogeathri, Mofleh Ali Mofleh

2011-01-01T23:59:59.000Z

208

Wuhan Linuo Solar Energy Group Stock Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Solar Energy Group Stock Co Ltd Solar Energy Group Stock Co Ltd Jump to: navigation, search Name Wuhan Linuo Solar Energy Group Stock Co Ltd Place Wuhan, Hubei Province, China Zip 430015 Sector Solar Product String representation "Develop, manufa ... istry painting." is too long. Coordinates 30.572399°, 114.279121° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":30.572399,"lon":114.279121,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

209

Restaurant Industry Stock Price Forecasting Model Utilizing Artificial Neural Networks to Combine Fundamental and Technical Analysis.  

E-Print Network (OSTI)

??Stock price forecasting is a classic problem facing analysts. Forcasting models have been developed for predicting individual stocks and stock indices around the world and… (more)

Dravenstott, Ronald W.

2012-01-01T23:59:59.000Z

210

Towards a Very Low Energy Building Stock: Modeling the US Commercial...  

NLE Websites -- All DOE Office Websites (Extended Search)

Towards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning Title Towards a Very Low Energy Building Stock:...

211

U.S. Crude Oil Stocks  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: U.S. crude oil stocks stood at about 289 million barrels on September 8, according to EIA's latest survey. This puts them about 24 million barrels below the level seen at the same time last year. Current market conditions do not suggest much improvement in the near term. We probably ended last month (August 2000) with the lowest level for end-of-August crude oil stocks (289 million barrels) in the United States since 1976, when crude oil inputs to refineries were about 2 million barrels per day less than today. However, by EIA data, we have seen (at least slightly) lower crude stocks in recent months, including an end-December 1999 level of 284 million barrels. The American Petroleum Institute (API), which also surveys petroleum supply and demand

212

A bottom-up engineering estimate of the aggregate heating andcooling loads of the entire U.S. building stock  

SciTech Connect

A recently completed project for the U.S. Department of Energy's (DOE) Office of Building Equipment combined DOE-2 results for a large set of prototypical commercial and residential buildings with data from the Energy Information Administration (EIA) residential and commercial energy consumption surveys (RECS, CBECS) to estimate the total heating and cooling loads in U.S. buildings attributable to different shell components such as windows, roofs, walls, etc., internal processes, and space-conditioning systems. This information is useful for estimating the national conservation potentials for DOE's research and market transformation activities in building energy efficiency. The prototypical building descriptions and DOE-2 input files were developed from 1986 to 1992 to provide benchmark hourly building loads for the Gas Research Institute (GRI) and include 112 single-family, 66 multi-family, and 481 commercial building prototypes. The DOE study consisted of two distinct tasks : (1) perform DOE-2 simulations for the prototypical buildings and develop methods to extract the heating and cooling loads attributable to the different building components; and (2) estimate the number of buildings or floor area represented by each prototypical building based on EIA survey information. These building stock data were then multiplied by the simulated component loads to derive aggregated totals by region, vintage, and building type. The heating and cooling energy consumption of the national building stock estimated by this bottom-up engineering approach was found to agree reasonably well with estimates from other sources, although significant differences were found for certain end-uses. The main added value from this study, however, is the insight it provides about the contributing factors behind this energy consumption, and what energy savings can be expected from efficiency improvements for different building components by region, vintage, and building type.

Huang, Yu Joe; Brodrick, Jim

2000-08-01T23:59:59.000Z

213

Supply/Demand Forecasts Begin to Show Stock Rebuilding  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: During 1999, we saw stock draws during the summer months, when we normally see stock builds, and very large stock draws during the winter of 1999/2000. Normally, crude oil production exceeds product demand in the spring and summer, and stocks build. These stocks are subsequently drawn down during the fourth and first quarters (dark blue areas). When the market is in balance, the stock builds equal the draws. During 2000, stocks have gradually built, but following the large stock draws of 1999, inventories needed to have been built more to get back to normal levels. As we look ahead using EIA's base case assumptions for OPEC production, non-OPEC production, and demand, we expect a more seasonal pattern for the next 3 quarters. But since we are beginning the year with

214

Low Distillate Stocks Set Stage for Price Volatility  

U.S. Energy Information Administration (EIA)

This distillate price spike is a classic response to a local supply and demand imbalance that began as a result of low distillate stocks. Low distillate stocks in the ...

215

U.S. Distillate Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Slide 5 of 27. Distillate Stocks. This slide shows the average U.S. distillate stock pattern -- building in the summer and fall, then being drawn down through the ...

216

Jiangsu FAW Foundry Stock Co Ltd | Open Energy Information  

Open Energy Info (EERE)

FAW Foundry Stock Co Ltd Jump to: navigation, search Name Jiangsu FAW Foundry Stock Co Ltd Place Wuxi, Jiangsu Province, China Sector Wind energy Product Wuxi-based JV set up...

217

Policy Consequences of Better Stock Estimates in Pacific Halibut Fisheries  

E-Print Network (OSTI)

the effect of halibut price, stock biomass, on the amount ofbiomass over time. The measurement equa- equation tions include a priceprice The is catch in determined equation area storage describes the effect of effort and stock biomass

Berck, Peter; Johns, Grace

1985-01-01T23:59:59.000Z

218

Fear and its implications for stock markets  

E-Print Network (OSTI)

The value of stocks indices, and other assets, are examples of stochastic processes that drop and raise in unpredictable ways. In this paper, we discuss certain asymmetries in short term price movements that can not be attributed to a long term increasing trend. These empirical asymmetries predict that price drops in stock indices on a relatively short time scale are more common than the corresponding price raises, and we present several empirical examples of such asymmetries. Furthermore, a simple model is introduced with the aim of explaining these facts. The prime idea is to introduce occasional, short periods of dropping stock prices that are synchronized for all stocks of the index. These collective negative price movements are imagined to be triggered by external factors in our society that create fear for the future among the investors. In the model this is parameterized by a ``fear factor'' defining how often such events take place. It is demonstrated that such a simple fear factor model can reproduce...

Simonsen, I; Jensen, M H; Donangelo, R; Sneppen, K; Simonsen, Ingve; Ahlgren, Peter Toke Heden; Jensen, Mogens H.; Donangelo, Raul; Sneppen, Kim

2006-01-01T23:59:59.000Z

219

A new Loan-Stock Financial Instrument  

E-Print Network (OSTI)

A new financial instrument (a new kind of a loan) is introduced. The loan-stock instrument (LSI) combines fixed rate instruments (loans, etc.) with other financial instruments that have higher volatilities and returns (stocks, mutual funds, currencies, derivatives, options, etc.). This new loan depends on the value of underlying security (for example, stock) in such a way that when underlying security increases, the value of loan decreases and backwards. The procedure to create a risk free portfolio and a technique to fairly price the LSI is described. The philosophy behind this procedure is quite similar to the Black-Scholes formalism in option theory. Creation of the risk free portfolio is possible because the change in the underlying security offsets the change in the value of the loan (or the amount that the borrower has to repay). The new financial instrument takes an advantage of the fact that on average the stock market grows in time. It is beneficial for both the borrower and the lender. The LSI is more attractive for the borrower than the traditional loan is due to the decrease in the amount that has to be repaid. This attractiveness constitutes the benefit for the lender in terms of the market share among the borrowers. In addition, the lender can charge the extra premium.

Alexander Morozovsky; Rajan Narasimhan; Yuri Kholodenko

2000-07-01T23:59:59.000Z

220

Ohio Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Distillate stocks ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Michigan Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Distillate stocks ...

222

Idaho Refinery, Bulk Terminal, and Natural Gas Plant Stocks of ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Distillate stocks ...

223

Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence  

E-Print Network (OSTI)

Using Neural Networks to Forecast Stock Market Prices Ramon Lawrence Department of Computer Science on the application of neural networks in forecasting stock market prices. With their ability to discover patterns. Section 3 covers current analytical and computer methods used to forecast stock market prices

Lawrence, Ramon

224

Do Firms Choose Their Stock Liquidity? A Study of Innovative Firms and Their Stock Liquidity ?  

E-Print Network (OSTI)

We ask whether firms can choose, or at least influence, their stock liquidity. We analyze a sample of firms that, we hypothesize, will value stock liquidity more than other firms – innovative firms that primarily hold intangible assets and expect to raise capital from the stock market. Consistent with their reliance on equity markets, we find that innovative firms have higher liquidity and that they take a variety of actions (e.g., frequent earnings guidance, stock splits etc) that help keep their stock more liquid. Maintaining liquidity appears to be less of a concern when innovative firms have greater access to other sources of capital. Given their low leverage, there is greater reliance on monitoring by large equity-holders and incentive contracts to help resolve agency issues, rather than banks or other creditors: consistent with the greater institutional ownership, higher likelihood of blockholders, and more incentivized CEO compensation contracts in these firms. The marginal impact on firm value (Tobin’s Q) of a plausibly exogenous increase in liquidity (e.g., following decimalization of stock prices) is greater for innovative firms, especially when CEOs have strong incentive contracts. Innovative activity tends to increase in the wake of such liquidity enhancements.

Nishant Dass; Vikram N; Steven Chong Xiao; Nikunj Kapadia; Simi Kedia; Pete Kyle; Er Ljungqvist

2012-01-01T23:59:59.000Z

225

Tebian Electric Apparatus Stock Co Ltd TBEA | Open Energy Information  

Open Energy Info (EERE)

Tebian Electric Apparatus Stock Co Ltd TBEA Tebian Electric Apparatus Stock Co Ltd TBEA Jump to: navigation, search Name Tebian Electric Apparatus Stock Co Ltd (TBEA) Place Changji, Xinjiang Autonomous Region, China Zip 831100 Sector Solar Product TBEA makes transformer products and aluminium foil, and also solar energy equipment. References Tebian Electric Apparatus Stock Co Ltd (TBEA)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Tebian Electric Apparatus Stock Co Ltd (TBEA) is a company located in Changji, Xinjiang Autonomous Region, China . References ↑ "Tebian Electric Apparatus Stock Co Ltd (TBEA)" Retrieved from "http://en.openei.org/w/index.php?title=Tebian_Electric_Apparatus_Stock_Co_Ltd_TBEA&oldid=352059

226

NATIONAL ENERGY POLICY Taking Stock A  

NLE Websites -- All DOE Office Websites (Extended Search)

Taking Stock Taking Stock A merica's current energy challeng- es can be met with rapidly im- proving technology, dedicated leadership, and a comprehensive approach to our energy needs. Our challenge is clear-we must use tech- nology to reduce demand for energy, re- pair and maintain our energy infrastruc- ture, and increase energy supply. Today, the United States remains the world's undisput- ed technological leader; but recent events have demonstrated that we have yet to inte- grate 21st-century technology into an ener- gy plan that is focused on wise energy use, production, efficiency, and conservation. Prices today for gasoline, heating oil, and natural gas are dramatically higher than they were only a year ago. In Califor- nia, homeowners, farmers, and businesses face soaring electricity prices, rolling

227

Maximum entropy distribution of stock price fluctuations  

E-Print Network (OSTI)

The principle of absence of arbitrage opportunities allows obtaining the distribution of stock price fluctuations by maximizing its information entropy. This leads to a physical description of the underlying dynamics as a random walk characterized by a stochastic diffusion coefficient and constrained to a given value of the expected volatility, taking in this way into account the information provided by the existence of an option market. This model is validated by a comprehensive comparison with observed distributions of both price return and diffusion coefficient. Expected volatility is the only parameter in the model and can be obtained by analysing option prices. We give an analytic formulation of the probability density function for price returns which can be used to extract expected volatility from stock option data. This distribution is of high practical interest since it should be preferred to a Gaussian when dealing with the problem of pricing derivative financial contracts.

Bartiromo, Rosario

2011-01-01T23:59:59.000Z

228

Transfer Entropy Analysis of the Stock Market  

E-Print Network (OSTI)

In terms of transfer entropy, we investigated the strength and the direction of information transfer in the US stock market. Through the directionality of the information transfer, the more influential company between the correlated ones can be found and also the market leading companies are selected. Our entropy analysis shows that the companies related with energy industries such as oil, gas, and electricity influence the whole market.

Baek, S K; Kwon, O; Moon, H T; Baek, Seung Ki; Jung, Woo-Sung; Kwon, Okyu; Moon, Hie-Tae

2005-01-01T23:59:59.000Z

229

Kokanee Stock Status and Contribution of Cabinet Gorge Hatchery, Lake Pend Oreille, Idaho, Final Report.  

DOE Green Energy (OSTI)

Lake Pend Oreille once provided the most popular kokanee Oncorhynchus nerka fishery in northern Idaho. A dramatic decline in the population occurred from the mid-1960s to 1970s. Restoration efforts included construction of the Cabinet Gorge Fish Hatchery to supplement the wild population and restore the fishery. In this study, hatchery-reared age 0 kokanee were stocked into Lake Pend Oreille from 1986 through 1992. Seven experimental stocking strategies for kokanee were tested using five locations and two time periods (early May through early June or late July). In 1985, the age 3 and older kokanee totaled about 0.35 million, but rose to 0.78 million in 1986, was stable, was then followed by a decline in 1990 to 0.53 million, then improved to 1.75 million in 1992. Much of the annual variation in total numbers of kokanee, ranging from 4.5 million to 10.2 million, was due to hatchery stockings of age 0 fish. Standing stocks of kokanee remained stable and ranged from 8 to 10 kg/hectare de spite dramatic changes in density due to age 0 fish. Prior to this study (1985), standing stocks were substantially higher (mean = 13.6 kg/hectare), indicating that the population may be operating below carrying capacity. The authors found survival of age 0 hatchery kokanee by each release season to range from 3% in 1986 to 39% in 1992, while the mean from 1987 through 1992 was 23%. They found significant (P=0.05) differences in survival between years, but they could not detect differences between stocking locations (P>0.71). Their analysis of survival between time (early vs late) and location was weak and inconclusive because after 1989 they had fewer fish to stock and could not repeat testing of some release strategies. They believe some of the variation in survival between release groups each year was due to the length of time between release in the lake and trawling.

Paragamian, Vaugh L.

1994-07-01T23:59:59.000Z

230

Last-Minute Energy Saving Stocking Stuffers | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Last-Minute Energy Saving Stocking Stuffers Last-Minute Energy Saving Stocking Stuffers Last-Minute Energy Saving Stocking Stuffers December 23, 2013 - 12:13pm Addthis There are all sorts of small energy-efficient presents available for stuffing stockings this year. | Photo courtesy of ©iStockphoto.com/DNY59 There are all sorts of small energy-efficient presents available for stuffing stockings this year. | Photo courtesy of ©iStockphoto.com/DNY59 Christina Stowers Communications Specialist in the Office of Weatherization and Intergovernmental Program How can I participate? Keep an eye out for these small, energy saving gifts as you do your last minute shopping this year. Looking for some last minute stocking stuffers to complement the holiday gifts you've purchased for your loved ones? We covered a few

231

Low Distillate Stocks Set Stage for Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

Along with the recent rise in crude oil prices, low stocks of Along with the recent rise in crude oil prices, low stocks of distillate fuels left markets in a vulnerable position. As we went into our two biggest distillate demand months, January and February, U.S. distillate stocks were very low -- particularly on the East and Gulf Coasts. The East Coast is the primary heating oil region, and it depends heavily on production from the Gulf Coast as well. Distillate stocks in the U.S. and Europe were in surplus supply as recently as October, but distillate stocks did not build as they usually do during the late fall, and declined more sharply than usual in December. December stocks closed well below the normal range. The unusual drawdown, in contrast to the more normal building pattern, resulted in distillate inventory levels about 3 million barrels lower than the very low

232

Distillate Stocks Are Important Part of Northeast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

1 of 15 1 of 15 Notes: Why do stocks matter in the Northeast? Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 5 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666 MB/D of stocks, covering almost 36% of demand for that month. PADD 1 refineries meet about 25% of demand during January and February, and other PADDs -- mostly PADD 3 -- supply 45-50% of the regionÂ’s needs. Imports generally supply about as much as stocks during the peak months, with most of the product coming from Canada, the Virgin Islands and Venezuela. Percentages do not tell the whole story. Stocks supply close to 300

233

The investigation of the market disequilibrium in the stock market.  

E-Print Network (OSTI)

??This thesis investigated stock market disequilibrium focusing on two topics: the impact of multiple market makers on the market disequilibrium at the market microstructure level,… (more)

Park, Jin Suk

2013-01-01T23:59:59.000Z

234

NIST 2002 Stock Study of Malcolm Baldrige National Quality ...  

Science Conference Proceedings (OSTI)

... Stock Purchases. December 2, 2002 Close. Price, $ Invested, Price, $ Value, % Change. 11/2/92. CitiGroup (AT&T Universal Card Services). 44.125 ...

2011-07-14T23:59:59.000Z

235

Stocks of Reformulated Gasoline - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

236

Table 3.4 Petroleum Stocks (Million Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration / Monthly Energy Review October 2013 47 Table 3.4 Petroleum Stocks (Million Barrels) Crude Oila Distillate

237

Stocks of Distillate Fuel Oil 15 ppm Sulfur and Under  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

238

PADD 1 Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

239

Stocks of SPR Crude Oil - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

240

Stocks of Distillate Fuel Oil - Energy Information Administration  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Midwest (PADD 2) Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

242

Jefferson Lab Science Series - The Physics of Stock Car Racing...  

NLE Websites -- All DOE Office Websites (Extended Search)

Archive Next Video (Understanding Flight) Understanding Flight The Physics of Stock Car Racing from a NASCAR Champion's Perspective Dr. Scott Winters - Lawrence Livermore...

243

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of PADD 1...

244

Cushing, Oklahoma Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

245

Gulf Coast (PADD 3) Refinery Grade Butane Stocks at Bulk ...  

U.S. Energy Information Administration (EIA)

Gulf Coast (PADD 3) Refinery Grade Butane Stocks at Bulk Terminals (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 2005: 935: ...

246

Chapter 3. Fossil-Fuel Stocks for Electricity Generation  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration/Electric Power Monthly June 2012 69 Chapter 3. Fossil-Fuel Stocks for Electricity Generation

247

Stocks of Motor Gasoline RBOB with Alcohol Blending Components  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

248

Stocks of Finished Motor Gasoline - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

249

Stocks of All Other Motor Gasoline Blending Components  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

250

Distillate Stocks Are Important Part of East Coast Winter Supply  

U.S. Energy Information Administration (EIA)

One of the biggest stock draws we have seen was in January 1994, ... and if cold weather increases demand, resupply from these sources can take several weeks. ...

251

Stocks of Conventional Gasoline Blended with Fuel Ethanol  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

252

U.S. Propane Stocks - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Even if the near-record corn crop boosts dryer demand higher than expected, or 10 percent colder weather than normal occurs, stocks should be adequate for winter ...

253

5. Petroleum Stocks: Causes and Effects of Lower Inventories  

U.S. Energy Information Administration (EIA)

Energy Information Administration / Petroleum 1996: Issues and Trends 85 Stocks are needed to keep petroleum supplies moving smoothly from wellhead to ...

254

Hybrid Kansei-SOM model using risk management and company assessment for stock trading  

Science Conference Proceedings (OSTI)

Risk management and stock assessment are key methods for stock trading decisions. In this paper, we present a new stock trading method using Kansei evaluation integrated with a Self-Organizing Map model for improvement of a stock trading system. The ... Keywords: Hybrid intelligent trading system, Investment risk, Kansei evaluation, Risk management, Self-Organizing Map, Stock trading system

Hai V. Pham, Eric W. Cooper, Thang Cao, Katsuari Kamei

2014-01-01T23:59:59.000Z

255

Recent Trends in Crude Oil Stock Levels  

Gasoline and Diesel Fuel Update (EIA)

J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J J 0 280 300 320 340 360 380 400 420 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Average Range: 1993-1995 Recent Trends in Crude Oil Stock Levels by Aileen A. Bohn Energy Information Administration (EIA) data for March 1996 primary inventories of crude oil were the lowest recorded in almost 20 years. Crude oil inventories, which were generally on a downward trend since the beginning of 1995, fell below the average range in July 1995 and have yet to recover (Figure FE1). On September 27, 1996, crude oil stocks registered 303 million barrels, compared to a normal range of nearly 311 to 332 million barrels for September. 1 Low crude oil inventories can cause price volatility in crude oil markets. 2 When inventories are low, refiners resort to

256

Northern Gulf of Mexico Continental Shelf Stock  

E-Print Network (OSTI)

waters from 20 to 200m deep in the northern Gulf from the U.S.-Mexican border to the Florida Keys (Figure 1). Both “coastal ” and “offshore ” ecotypes of bottlenose dolphins occur in the Gulf of Mexico (Hersh and Duffield 1990; LeDuc and Curry 1998). The Continental Shelf Stock probably consists of a mixture of both the coastal and offshore ecotypes. The offshore and coastal ecotypes are genetically distinct using both mitochondrial and nuclear markers (Hoelzel et al. 1998). In the northwestern Atlantic, Torres et al. (2003) found a statistically significant break in the distribution of the ecotypes at 34 km from shore. The offshore ecotype was found exclusively seaward of 34km and in waters deeper than 34 m. Within 7.5km of shore, all animals were of the coastal ecotype. The continental shelf is much wider in the Gulf of Mexico so these results may not apply. The continental shelf stock range may extend into Mexican and Cuban territorial waters; however, there are no available estimates of either abundance or mortality from those countries. A stranded dolphin from the Florida Panhandle was rehabilitated and released over the shelf off western Florida, and traveled into the Atlantic Ocean (Wells et al. 1999). The bottlenose dolphins inhabiting waters <20m deep in

Bottlenose Dolphin (tursiops Truncatus Truncatus

2012-01-01T23:59:59.000Z

257

Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial Building Sector to Support Policy and Innovation Planning  

SciTech Connect

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

Coffey, Brian; Borgeson, Sam; Selkowitz, Stephen; Apte, Josh; Mathew, Paul; Haves, Philip

2009-07-01T23:59:59.000Z

258

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

04 294,316 FY2005 820,074 FY2006 799,449 FY2007 877,898 FY2008 866,608 FY2009 886,404 FY2010 800,314 FY2011 871,280 FY2012 824,517 FY2013 Cumulative Fee Paid 7,040,860...

259

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

16,237,181 FY2010 6,222,832 FY2011 59,831,257 FY2012 0 FY2013 0 FY2014 FY2015 FY2016 FY2017 FY2018 Cumulative Fee Paid 82,291,270 CH2MHill Plateau Remediation Company...

260

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

2010 19,332,431 FY2011 23,956,349 FY2012 19,099,251 FY2013 0 FY2014 FY2015 FY2016 FY2017 FY2018 FY2019 Cumulative Fee Paid 62,388,031 209,254,793 21,226,918 21,030,647 Fee...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Contractor: Contract Number: Contract Type: Total Estimated  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

13 0 FY2014 0 FY2015 0 FY2016 0 FY2017 0 FY2018 0 Cumulative Fee Paid 0 310,000 320,000 330,000 340,000 HPM Corporation DE-EM0002043 350,000 Firm Fixed Price Plus Award...

262

Table 2. U.S. Biodiesel Production, Sales, and Stocks  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Biodiesel Production, Sales, and Stocks U.S. Biodiesel Production, Sales, and Stocks (million gallons) Period 2011 January 35 22 9 17 4 February 40 27 13 17 1 March 60 41 17 19 2 April 71 47 22 21 2 May 77 50 27 23 2 June 81 62 24 19 (4)

263

Uranium Stocks in Slovenia for Nuclear Power Author: Matic Suhodolcan  

E-Print Network (OSTI)

Seminar Uranium Stocks in Slovenia for Nuclear Power Plant NEK Author: Matic Suhodolcan Supervisor and that reopening would make sense. We try to calculate the years of operating NEK only with uranium ore for reprocessing fuel. #12;Uranium Stocks in Slovenia for Slovenian Nuclear Power Plant NEK Matic Suhodolcan FMF 2

Prosen, TomaÂ?

264

Time Series Analysis and Forecasting in Stock Market Investments  

E-Print Network (OSTI)

Time Series Analysis and Forecasting in Stock Market Investments Ted Chi-Wei Fung Department and forecasting have been used as methods to help precisely on the task of stock market prediction by using past data. This paper will discuss three different models to create a time series analysis and forecast

Zanibbi, Richard

265

Paper Millionaires: How Valuable is Stock to a Stockholder Who is Restricted from Selling it?  

E-Print Network (OSTI)

this is because taking additional stock market risk helpsrisk of the restricted stock by taking o?setting positionsuse his illiquid stock as collateral for taking a net short

Kahl, Matthias; Liu, Jun; Longstaff, Francis A

2001-01-01T23:59:59.000Z

266

U.S. Atlantic and Gulf of Mexico Marine Mammal Stock Assessments -2012  

E-Print Network (OSTI)

iv U.S. Atlantic and Gulf of Mexico Marine Mammal Stock Assessments - 2012 Volume 1 Gordon T Atlantic Stock __________________________________104 Gulf Of Mexico Cetacean Species Sperm Whale (Physeter macrocephalus): Northern Gulf of Mexico Stock _______________________________112 Bryde's Whale (Balaenoptera

267

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Stocks are important in the Northeast because they are the nearest source of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of East Coast winter distillate supply. Over the last 10 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666,000 barrels per day of stocks, covering almost 36% of demand for that month. On average, stocks supply the East Coast with about 260,000 barrels per day on average in January and 280,000 barrels per day in February. Those supplies represent draws of about 8 million barrels in one month.

268

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Why do stocks matter in the Northeast? They are the nearest source of supply when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 10 years, they provided about 15% of supply during the peak winter months of January and February. One of the biggest stock draws we have seen was in January 1994, when a prolonged severe cold spell required 666 MB/D of stocks, covering almost 36% of demand for that month. Stocks supply the East Coast with about 260 MB/D on average in January and 280 MB/D in February. Those supplies represent draws of about 8 million barrels in one month. PADD 1 refineries meet about 25% of demand during January and

269

Distillate Stocks Are Important Part of Northeast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

The weather alone was not enough to cause the price spike. The low The weather alone was not enough to cause the price spike. The low stocks left the area vulnerable to sudden changes in the market, such as the weather change. Why do stocks matter in the Northeast? Stocks are normally an important part of PADD 1 winter distillate supply. Over the last 5 years, PADD 1 stocks provided about 15% of supply during the peak winter months of January and February. They are the closest source of supply to the consumer. PADD 1 depends on about 60% of its supply from distant sources such as the Gulf Coast or imports, which can take several weeks to travel to the Northeast. Even product from East Coast refineries, if capacity is available, may take a week before it is produced and delivered to the regions needing new supply. Thus, stocks must be able

270

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

Stocks are normally an important part of East Coast winter Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

271

Recovery May Require Holding Stocks Level in February and March  

Gasoline and Diesel Fuel Update (EIA)

have dropped back as new supplies are appearing, but we still have dropped back as new supplies are appearing, but we still have nearly a month of winter ahead of us. Stocks cannot drop much farther. February 4 stock levels were just above the lowest month-end levels ever seen for PADD 1, which occurred in April 1996. For stocks to recover to the low end of the normal range, they would have to stay level in February in March, when normally they would be used to meet demand. Keeping stocks level would require finding supply to substitute for the average stock drops of 290 thousand barrels per day (8 million barrels) in February and 210 thousand barrels per day (6 million barrels) in March. If all of that supply were to come from imports, we would have to see distillate imports into PADD 1 double from their average levels of 7

272

BOTTLENOSE DOLPHIN (Tursiops truncatus): Northern Gulf of Mexico Oceanic Stock  

E-Print Network (OSTI)

Thirty-eight stocks have been provisionally identified for Gulf of Mexico bottlenose dolphins (Waring et al. 2001). Gulf of Mexico inshore habitat has been separated into 33 bay, sound and estuarine stocks. Three northern Gulf of Mexico coastal stocks include nearshore waters from the shore to the 20 m isobath. The continental shelf stock encompasses waters from 20 to 200 m deep. The Gulf of Mexico oceanic stock encompasses the waters from the 200 m isobath to the seaward extent of the U.S. Exclusive Economic Zone (EEZ; Figure 1). Both “coastal/nearshore ” and “offshore ” ecotypes of bottlenose dolphins (Hersh and Duffield 1990) occur in the Gulf of Mexico (LeDuc and Curry 1998). The offshore and nearshore ecotypes are genetically distinct using both mitochondrial and nuclear markers (Hoelzel et al. 1998). In the northwestern Atlantic, Torres et al. (2003) found a statistically significant break in the distribution of the ecotypes at 34 km from shore. The offshore ecotype was found exclusively seaward of 34 km and in waters deeper than 34 m. Within 7.5 km of shore, all animals were of the coastal ecotype. If the distribution of ecotypes found by Torres et al. (2003) is similar in the northern Gulf of Mexico, the oceanic stock consists of the offshore ecoptype. Based on research currently being conducted on bottlenose dolphins in the Gulf of Mexico, as well as the western North Atlantic Ocean, the structure of these stocks is uncertain, but appears to be complex. The multi-disciplinary research programs conducted over the last two decades (e.g., Wells 1994) are beginning to shed light on stock structures of bottlenose dolphins, though additional analyses are needed before stock structures can be elaborated on in the Gulf of Mexico. As research is completed, it may be necessary to revise all the stocks of bottlenose dolphins in the Gulf of Mexico. POPULATION SIZE Estimates of abundance were derived through the application of distance sampling

Stock Definition; Geographic Range

2003-01-01T23:59:59.000Z

273

Summary Max Total Units  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Max Total Units Max Total Units *If All Splits, No Rack Units **If Only FW, AC Splits 1000 52 28 28 2000 87 59 35 3000 61 33 15 4000 61 33 15 Totals 261 153 93 ***Costs $1,957,500.00 $1,147,500.00 $697,500.00 Notes: added several refrigerants removed bins from analysis removed R-22 from list 1000lb, no Glycol, CO2 or ammonia Seawater R-404A only * includes seawater units ** no seawater units included *** Costs = (total units) X (estimate of $7500 per unit) 1000lb, air cooled split systems, fresh water Refrig Voltage Cond Unit IF-CU Combos 2 4 5 28 References Refrig Voltage C-U type Compressor HP R-404A 208/1/60 Hermetic SA 2.5 R-507 230/1/60 Hermetic MA 2.5 208/3/60 SemiHerm SA 1.5 230/3/60 SemiHerm MA 1.5 SemiHerm HA 1.5 1000lb, remote rack systems, fresh water Refrig/system Voltage Combos 12 2 24 References Refrig/system Voltage IF only

274

Weekly U.S. Ending Stocks of Total Gasoline (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

Year-Month Week 1 Week 2 Week 3 Week 4 Week 5; End Date Value End Date Value End Date Value End Date Value End Date Value; 1990-Jan: 01/05 : 210,982 : 01/12 : 215,395

275

Temporal changes in C and N stocks of restored prairie: implications for C sequestration strategies  

Science Conference Proceedings (OSTI)

The recovery of ecosystem C and N dynamics after disturbance can be a slow process. Chronosequence approaches offer unique opportunities to use space-for-time substitution to quantify the recovery of ecosystem C and N stocks and estimate the potential of restoration practices for C sequestration. We studied the distribution of C and N stocks in two chronosequences that included long-term cultivated lands, 3- to 26-year-old prairie restorations, and remnant prairie on two related soil series. Results from the two chronosequences did not vary significantly and were combined. Based on modeling predictions, the recovery rates of different ecosystem components varied greatly. Overall, C stocks recovered faster than N stocks, but both C and N stocks recovered more rapidly for aboveground vegetation than for any other ecosystem component. Aboveground C and N reached 95% of remnant levels in only 13 years and 21 years, respectively, after planting to native vegetation. Belowground plant C and N recovered several decades later, while microbial biomass C, soil organic C (SOC), and total soil N recovered on a century timescale. In the cultivated fields, SOC concentrations were depleted within the surface 25 cm, coinciding with the depth of plowing, but cultivation apparently led to redistribution of soil C, increasing SOC stocks deeper in the soil profile. The restoration of prairie vegetation was effective at rebuilding soil organic matter (SOM) in the surface soil. Accrual rates were maintained at 43 g C {center_dot} m{sup -2} {center_dot} yr{sup -1} and 3 g N {center_dot} m{sup -2} {center_dot} yr{sup -1} in the surface 0.16 Mg/m{sup 2} soil mass during the first 26 years of restoration and were predicted to reach 50% of their storage potential (3500 g C/m{sup 2}) in the first 100 years. We conclude that restoration of tallgrass prairie vegetation can restore SOM lost through cultivation and has the potential to sequester relatively large amounts of SOC over a sustained period of time. Whether restored prairies can retain the C apparently transferred to the subsoil by cultivation practices remains to be seen.

Matamala, Roser [Argonne National Laboratory (ANL); Jastrow, Julie D [ORNL; Miller, Raymond M [Argonne National Laboratory (ANL); Garten Jr, Charles T [ORNL

2008-10-01T23:59:59.000Z

276

Temporal changes in C and N stocks of restored prairie : implications for C sequestration strategies.  

SciTech Connect

The recovery of ecosystem C and N dynamics after disturbance can be a slow process. Chronosequence approaches offer unique opportunities to use space-for-time substitution to quantify the recovery of ecosystem C and N stocks and estimate the potential of restoration practices for C sequestration. We studied the distribution of C and N stocks in two chronosequences that included long-term cultivated lands, 3- to 26-year-old prairie restorations, and remnant prairie on two related soil series. Results from the two chronosequences did not vary significantly and were combined. Based on modeling predictions, the recovery rates of different ecosystem components varied greatly. Overall, C stocks recovered faster than N stocks, but both C and N stocks recovered more rapidly for aboveground vegetation than for any other ecosystem component. Aboveground C and N reached 95% of remnant levels in only 13 years and 21 years, respectively, after planting to native vegetation. Belowground plant C and N recovered several decades later, while microbial biomass C, soil organic C (SOC), and total soil N recovered on a century timescale. In the cultivated fields, SOC concentrations were depleted within the surface 25 cm, coinciding with the depth of plowing, but cultivation apparently led to redistribution of soil C, increasing SOC stocks deeper in the soil profile. The restoration of prairie vegetation was effective at rebuilding soil organic matter (SOM) in the surface soil. Accrual rates were maintained at 43 g C {center_dot} m{sup -2} {center_dot} yr{sup -1} and 3 g N {center_dot} m{sup -2} {center_dot} yr{sup -1} in the surface 0.16 Mg/m{sup 2} soil mass during the first 26 years of restoration and were predicted to reach 50% of their storage potential (3500 g C/m{sup 2}) in the first 100 years. We conclude that restoration of tallgrass prairie vegetation can restore SOM lost through cultivation and has the potential to sequester relatively large amounts of SOC over a sustained period of time. Whether restored prairies can retain the C apparently transferred to the subsoil by cultivation practices remains to be seen.

Matamala, R.; Jastrow, J. D.; Miller, R. M.; Garten, C. T.; Biosciences Division; ORNL

2008-09-01T23:59:59.000Z

277

A Quantum-like Approach to the Stock Market  

E-Print Network (OSTI)

Modern approaches to stock pricing in quantitative finance are typically founded on the 'Black-Scholes model' and the underlying 'random walk hypothesis'. Empirical data indicate that this hypothesis works well in stable situations but, in abrupt transitions such as during an economical crisis, the random walk model fails and alternative descriptions are needed. For this reason, several proposals have been recently forwarded which are based on the formalism of quantum mechanics. In this paper we apply the 'SCoP formalism', elaborated to provide an operational foundation of quantum mechanics, to the stock market. We argue that a stock market is an intrinsically contextual system where agents' decisions globally influence the market system and stocks prices, determining a nonclassical behavior. More specifically, we maintain that a given stock does not generally have a definite value, e.g., a price, but its value is actualized as a consequence of the contextual interactions in the trading process. This contextual influence is responsible of the non-Kolmogorovian quantum-like behavior of the market at a statistical level. Then, we propose a 'sphere model' within our 'hidden measurement formalism' that describes a buying/selling process of a stock and shows that it is intuitively reasonable to assume that the stock has not a definite price until it is traded. This result is relevant in our opinion since it provides a theoretical support to the use of quantum models in finance.

Diederik Aerts; Bart D'Hooghe; Sandro Sozzo

2011-10-24T23:59:59.000Z

278

Impaired fertility in T-stock female mice after superovulation  

Science Conference Proceedings (OSTI)

Superovulation of female mice with exogenous gonadotrophins is routinely used for increasing the number of eggs ovulated by each female in reproductive and developmental studies. We report an unusual effect of superovulation on fertilization in mice. In vivo matings of superovulated T-stock females with B6C3F1 males resulted in a 2-fold reduction (Pstock females had reached the metaphase stage of the first cleavage division versus 87% in B6C3F1 females (P stock males did not improve the reproductive performance of T-stock females. To investigate the possible cause(s) for the impaired fertilization and zygotic development, the experiments were repeated using in vitro fertilization. Under these conditions, the frequencies of fertilized eggs were not different in superovulated T-stock and B6C3F1 females (51.7% {+-} 6.0 and 64.5% {+-}3.8, P=0.10). There was a 7-fold increase in the frequencies of fertilized T-stock eggs that completed the first cell cycle of development after in vitro versus in vivo fertilization. These results rule out an intrinsic deficiency of the T-stock oocyte as the main reason for the impaired fertility after in vivo matings and suggest that superovulation of T-stock females induces a hostile oviductal and uterine environment with dramatic effects on fertilization and zygotic development.

Wyrobek, A J; Bishop, J B; Marchetti, F; Zudova, D

2003-12-05T23:59:59.000Z

279

Trading Puts and CDS on Stocks with Short Sale Ban  

E-Print Network (OSTI)

We focus on the short sale ban of 2008 to examine the interaction between price discovery in banned stocks and the trading of options and CDS. Within the sample of banned stocks with exchange traded options, stocks whose put-call ratios are in the top quintile underperform the middle group by 1.56 % and 2.84%, respectively, over the next two- and five-day returns. By contrast, the bottom quintile does not perform differently from the middle group. Within the sample of banned stocks with CDS traded and using their one-day percentage change in CDS spreads as a signal, we find cross-sectional predictability CDS signal for future stock returns. Again, the predictability is asymmetric, driven mostly by stocks with more positive percentage change in CDS spreads, and therefore more negative information according to the CDS market. Overall, our results confirm that in the presence of short sale ban, it takes time for the negative information contained in either the options market or the CDS market to get incorporated into stock prices.

Sophie Xiaoyan Ni; Jun Pan

2010-01-01T23:59:59.000Z

280

Annual Stock Assessment - CWT [Coded Wire Tag program] (USFWS), Annual Report 2007.  

DOE Green Energy (OSTI)

In 1989 the Bonneville Power Administration (BPA) began funding the evaluation of production groups of juvenile anadromous fish not being coded-wire tagged for other programs. These groups were the 'Missing Production Groups'. Production fish released by the U.S. Fish and Wildlife Service (FWS) without representative coded-wire tags during the 1980s are indicated as blank spaces on the survival graphs in this report. This program is now referred to as 'Annual Stock Assessment - CWT'. The objectives of the 'Annual Stock Assessment' program are to: (1) estimate the total survival of each production group, (2) estimate the contribution of each production group to fisheries, and (3) prepare an annual report for USFWS hatcheries in the Columbia River basin. Coded-wire tag recovery information will be used to evaluate the relative success of individual brood stocks. This information can also be used by salmon harvest managers to develop plans to allow the harvest of excess hatchery fish while protecting threatened, endangered, or other stocks of concern. All fish release information, including marked/unmarked ratios, is reported to the Pacific States Marine Fisheries Commission (PSMFC). Fish recovered in the various fisheries or at the hatcheries are sampled to recover coded-wire tags. This recovery information is also reported to PSMFC. This report has been prepared annually starting with the report labeled 'Annual Report 1994'. Although the current report has the title 'Annual Report 2007', it was written in fall of 2008 using data available from RMIS that same year, and submitted as final in January 2009. The main objective of the report is to evaluate survival of groups which have been tagged under this ongoing project.

Pastor, Stephen M. [U.S. Fish and Wildlife Service, Columbia River Fisheries Program Office

2009-07-21T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Compare All CBECS Activities: Total Energy Use  

U.S. Energy Information Administration (EIA) Indexed Site

Total Energy Use Total Energy Use Compare Activities by ... Total Energy Use Total Major Fuel Consumption by Building Type Commercial buildings in the U.S. used a total of approximately 5.7 quadrillion Btu of all major fuels (electricity, natural gas, fuel oil, and district steam or hot water) in 1999. Office buildings used the most total energy of all the building types, which was not a surprise since they were the most common commercial building type and had an above average energy intensity. Figure showing total major fuel consumption by building type. If you need assistance viewing this page, please call 202-586-8800. Major Fuel Consumption per Building by Building Type Because there were relatively few inpatient health care buildings and they tend to be large, energy intensive buildings, their energy consumption per building was far above that of any other building type.

282

The Neftemash closed joint-stock company  

Science Conference Proceedings (OSTI)

The Neftemash closed joint-stock company was created from the VNIIneftemash Scientific Production Association in the privatization process in the country. Members of the Neftemash Co. are listed. This group of members determined the basic activities of the Neftemash Co. as a multifunctional scientific production complex for designing and manufacturing modern equipment for oil and gas production and refining. By having highly qualified specialists, modern enterprises, test experience, and production capacity, this company is the leading organization in Russia and the Commonwealth of Independent States (CIS) for supplying oil and gas enterprises with petroleum equipment. The Neftemash Co. designs and produces drilling, geological prospecting, and petroleum production equipment and instrumentation. It designs oil and gas refining equipment and petrochemical equipment, equipment for processing coal and liquid fuels, including integrated automated production lines. It does fundamental and applied research in materials science, welding, and corrosion protection for oil and gas production and refining equipment. It designs ecologically safe equipment complexes for drilling wells and refining oil and gas. To a significant extent the petroleum industry in Russia was developed from the activity of the All-Union Scientific Research, Design, and Construction Institute for Petroleum Machinery. Equipment designed by the institute was used to explore, develop, and exploit oil and gas fields of western Siberia, the far north, and other petroleum regions of the country.

Umanchik, N.P.

1995-07-01T23:59:59.000Z

283

Table 2. U.S. Biodiesel Production, Sales, and Stocks  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Biodiesel Production, Sales, and Stocks" U.S. Biodiesel Production, Sales, and Stocks" "(million gallons)" "Period","B100 Production",,"Sales of B100",,"Sales of B100 Included in Biodiesel Blends",,"Ending Stocks of B100",,"B100 Stock Change" 2011 "January",35.355469,,21.760435,,9.397668,,16.705962,,3.900173 "February",40.342355,,27.263997,,13.027514,,17.367083,,0.661121 "March",59.59017,,40.879532,,16.804541,,19.178192,,1.811109 "April",71.0517,,47.320311,,21.819273,,21.000047,,1.821855 "May",77.196652,,49.520679,,27.20637,,23.448551,,2.448504 "June",81.39104,,61.776718,,23.965853,,19.302451,,-4.1461 "July",91.679738,,65.997152,,22.388332,,22.956565,,3.654114

284

The More Important Price Indicator This Year is Low Stocks  

Gasoline and Diesel Fuel Update (EIA)

6 of 6 6 of 6 Notes: Crude prices this year at the beginning of the second quarter are likely to be higher -- not lower -- as a result of the current shortfall in crude oil production relative to demand on top of low stocks. OECD stocks of crude oil and products plunged steeply in 1999. By year end, they were below the low levels at end December 1996 -- OPEC's stated target. This does not take into consideration the growth in demand that these stocks must help supply. EIA expects OECD stocks to stay very low throughout the year 2000. The projection shows end March levels remain well below those seen at the end of the first quarter 1996. The build during the summer will not be adequate to make up for the draws, resulting in a net draw of over 300 thousand barrels in an already tight market.

285

An Internet multicast system for the stock market  

Science Conference Proceedings (OSTI)

We are moving toward an international, 24-hour, distributed, electronic stock exchange. The exchange will use the global Internet, or internet technology. This system is a natural application of multicast because there are a large number of receivers ... Keywords: multicast

2001-08-01T23:59:59.000Z

286

Comparing Wealth Effects: The Stock Market versus the Housing Market  

E-Print Network (OSTI)

MAREKET VERSUS THE HOUSING MARKET By Karl E. Case John M.Article ? Comparing Wealth E?ects: The Stock Market versusthe Housing Market Karl E. Case ? John M. Quigley † Robert

Case, Karl E.; Quigley, John M.; Shiller, Robert J.

2005-01-01T23:59:59.000Z

287

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

9 9 Notes: Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

288

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

7 7 Notes: Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 MB/D in January and 280 MB/D in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak months,

289

Distillate Stocks Are Important Part of East Coast Winter Supply  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Stocks are normally an important part of East Coast winter distillate supply, since they are the nearest source when anything unexpected occurs, and they supply a significant portion of demand during the peak heating season. Over the last 10 years, stocks have provided about 15% of supply during the peak winter months of January and February. On average, stocks supply the East Coast with about 260 thousand barrels per day in January and 280 in February. Those supplies represent draws of about 8 million barrels in one month. In addition, East Coast refineries meet about 25% of demand during January and February, and other regions -- mostly the Gulf Coast -- supply 40-50% of the region's needs. Imports generally supply about as much as stocks during the peak

290

PADD 1 (East Coast) Heating Oil Stocks Low  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: The East Coast (PADD 1) is the primary heating oil region, and it depends heavily on production from the Gulf Coast (PADD 3) as well. The biggest decline in U.S. stocks has taken place in the heating oil markets of PADD 1 (East Coast), which consumed 86 percent of the nationÂ’s heating oil in 1998. It also is the region with the largest volume of heating oil stocks. PADD 1 was down over 8.4 million barrels on January 21 from the 5-year average stock level for end of January PADD 3, which supplies PADD 1, was down 4.6 million barrels from its 5-year January ending levels. During the week ending January 21, weather in New England was nearly 20% colder than normal for this time of year. This cold weather on top of low stocks was pushing prices up, with

291

NIST 2003 Stock Study of Malcolm Baldrige National Quality ...  

Science Conference Proceedings (OSTI)

... Stock Purchases. December 1, 2003 Close. Price, $ Invested, Price, $ Value, % Change. 1/3/94. Eastman Chemical. 45.125. 1000.00. 36.92. 818.17 ...

2010-10-05T23:59:59.000Z

292

East Coast (PADD 1) Normal Butane-Butylene Stock Change ...  

U.S. Energy Information Administration (EIA)

East Coast (PADD 1) Normal Butane-Butylene Stock Change (Thousand Barrels per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1981: 4-3: 1: ...

293

Midwest (PADD 2) Normal Butane-Butylene Stock Change (Thousand ...  

U.S. Energy Information Administration (EIA)

Midwest (PADD 2) Normal Butane-Butylene Stock Change (Thousand Barrels per Day) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1981-4-34-7: 14: ...

294

Distillate Stocks Are Important Part of Northeast Winter Supply  

U.S. Energy Information Administration (EIA)

... PADD 1 stocks provided about 15% of supply during the peak winter months of January and ... the Northeast saw the unusual heating oil and diesel price surges as a ...

295

Low Distillate Stocks Set Stage for Price Volatility  

Gasoline and Diesel Fuel Update (EIA)

areas for a time, requiring unusual movement of stock from other areas. As buyers search for product, they bid prices up rapidly, which attracts product, but the time lag can...

296

U.S. Ending Stocks of Petroleum Coke (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Ending Stocks of Petroleum Coke (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9; 1980's: 4,502: ...

297

U.S. Petroleum Coke Stocks at Refineries (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Petroleum Coke Stocks at Refineries (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1993: 10,747: 11,072: 11,444: ...

298

Does stock market volatility with regime shifts signal the business cycle in Taiwan?  

Science Conference Proceedings (OSTI)

Using a Switching Regime ARCH (SWARCH) model and other time series models, this paper sets out to investigate the volatility of Taiwan's monthly stock market returns, with the empirical results demonstrating that our SWARCH-L specification ... Keywords: Markov switching, Taiwan, business cycle, e-finance, electronic finance, regime shifts, stock market volatility, stock markets, stock volatility

Yih-Wen Shyu; Kuangyu Hsia

2008-12-01T23:59:59.000Z

299

Design and implementation of fuzzy expert system for Tehran Stock Exchange portfolio recommendation  

Science Conference Proceedings (OSTI)

The key issue for decision making in stock trading is selection of the right stock at the right time. In order to select the superior stocks (alternatives) for investment, a finite number of alternatives have to be ranked considering several and sometimes ... Keywords: Fuzzy Delphi Method, Fuzzy expert system, Multiple Criteria Decision Making (MCDM), Portfolio recommendation, Tehran Stock Exchange (TSE)

Mehdi Fasanghari; Gholam Ali Montazer

2010-09-01T23:59:59.000Z

300

The stock index forecast based on dynamic recurrent neural network trained with GA  

E-Print Network (OSTI)

neural networks applied in forecasting stock price, at present, the most widely used neural network is BPThe stock index forecast based on dynamic recurrent neural network trained with GA Fang Yixian1In order to forecast the stock market more accurately, according to the dynamic property for the stock

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Genetic Stock Identification, Annual Report of Research 1986.  

DOE Green Energy (OSTI)

The results of the first year's investigation of a 5-year plan to demonstrate and develop a coastwide genetic stock identification (GSI) program are presented. The accomplishments under four specific objectives are outlined below: 1. Improved Efficiency through Direct Entry of Electrophoretic Data into the Computer. A program is described that was developed for direct computer entry o f raw data. This program eliminated the need for key- to-tape processing previously required for estimating compositions of mixed fisheries, and thereby permits immediate use of collected data in estimating compositions of stock mixtures. 2. Expand and Strengthen Oregon Coastal and British Columbia Baseline Data Set. Electrophoretic screening of approximately 105 loci of samples from 22 stocks resulted in complete data sets for 35 polymorphic and 19 monomorphic loci. These new data are part of the baseline information currently used in estimating mixed stock compositions. 3. Conduct a Pilot GSI Study of Mixed Stock Canadian Troll Fisheries off the West Coast of Vancouver Island. A predominance of lower Columbia River (fall run), Canadian, and Puget Sound stocks was observed for both 1984 and 1985 fisheries . Stocks other than Columbia River, Canadian, and Puget Sound contributed an estimated 13 and 5 % respectively, to the 1984 and 1985 fisheries . 4. Validation of GSI for Estimating Mixed Fishery Stock Composition. Baseline data from the Columbia River southward were used to simulate nor them and central California fisheries . These simulations provided estimates of accuracy and precision for mixed sample sizes ranging from 250 to 1,000 individuals. Sacramento River stocks had a heavier weighting in the central (89%) than in the northern (25%) fishery. Accuracy and precision increased for both fisheries as sample sizes increased and also were better for those estimates that were over 5%. Extrapolations from these estimates indicated that sample sizes of 2,320 and 2,869 would be required to fulfill coefficients of variation (SD/estimated contribution) of 20% with respective confidence intervals of 80 and 95% in stock groupings of the northern fishery. Similarly, sample sizes of 2,450 and 3,030 would be required in the central fishery. A concluding section noted that these investigations are part of an effort involving many agencies. The requirements for simulation preceding actual sampling of stock mixtures and for continued monitoring and development of baseline data sets were emphasized.

Milner, George B.

1986-12-01T23:59:59.000Z

302

Impaired fertility in T-stock female mice after superovulation  

SciTech Connect

Superovulation of female mice with exogenous gonadotrophins is routinely used for increasing the number of eggs ovulated by each female in reproductive and developmental studies. We report an unusual effect of superovulation on fertilization in mice. In vivo matings of superovulated T-stock females with B6C3F1 males resulted in a 2-fold reduction (P<0.001) in the frequencies of fertilized eggs compared to control B6C3F1 matings. In addition, {approx}22 hr after mating only 15% of fertilized eggs recovered in T-stock females had reached the metaphase stage of the first cleavage division versus 87% in B6C3F1 females (P < 0.0001). Matings with T-stock males did not improve the reproductive performance of T-stock females. To investigate the possible cause(s) for the impaired fertilization and zygotic development, the experiments were repeated using in vitro fertilization. Under these conditions, the frequencies of fertilized eggs were not different in superovulated T-stock and B6C3F1 females (51.7% {+-} 6.0 and 64.5% {+-}3.8, P=0.10). There was a 7-fold increase in the frequencies of fertilized T-stock eggs that completed the first cell cycle of development after in vitro versus in vivo fertilization. These results rule out an intrinsic deficiency of the T-stock oocyte as the main reason for the impaired fertility after in vivo matings and suggest that superovulation of T-stock females induces a hostile oviductal and uterine environment with dramatic effects on fertilization and zygotic development.

Wyrobek, A J; Bishop, J B; Marchetti, F; Zudova, D

2003-12-05T23:59:59.000Z

303

Long-run models of oil stock prices  

Science Conference Proceedings (OSTI)

The identification of the forces that drive oil stock prices is extremely important given the size of the Oil & Gas industry and its links with the energy sector and the environment. In the next decade oil companies will have to deal with international ... Keywords: C32, Cointegration, Energy, Environment, Hydrocarbon fuels, L71, Non-renewable resources, Oil companies, Oil stock prices, Q30, Q40, Vector error correction models

Alessandro Lanza; Matteo Manera; Margherita Grasso; Massimo Giovannini

2005-11-01T23:59:59.000Z

304

total energy | OpenEI  

Open Energy Info (EERE)

total energy total energy Dataset Summary Description This dataset comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 1, and contains only the reference case. The dataset uses quadrillion BTUs, and quantifies the energy prices using U.S. dollars. The data is broken down into total production, imports, exports, consumption, and prices for energy types. Source EIA Date Released April 26th, 2011 (3 years ago) Date Updated Unknown Keywords 2011 AEO consumption EIA export import production reference case total energy Data application/vnd.ms-excel icon AEO2011: Total Energy Supply, Disposition, and Price Summary - Reference Case (xls, 112.8 KiB) Quality Metrics Level of Review Peer Reviewed

305

UPDATING THE FREIGHT TRUCK STOCK ADJUSTMENT MODEL: 1997 VEHICLE INVENTORY AND USE SURVEY DATA  

NLE Websites -- All DOE Office Websites (Extended Search)

36 36 UPDATING THE FREIGHT TRUCK STOCK ADJUSTMENT MODEL: 1997 VEHICLE INVENTORY AND USE SURVEY DATA Stacy C. Davis November 2000 Prepared for the Energy Information Administration U.S. Department of Energy Prepared by the OAK RIDGE NATIONAL LABORATORY Oak Ridge, Tennessee 37831-6073 managed by UT-BATTELLE, LLC for the U.S. DEPARTMENT OF ENERGY under Contract No. DE-AC05-00OR22725 Updating the FTSAM: 1997 VIUS Data iii TABLE OF CONTENTS ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 OBJECTIVE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 VIUS DATA PREPARATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Table 1. Share of Trucks by Fuel Type and Truck Size -

306

U.S. Department of Energy Commercial Reference Building Models of the National Building Stock  

SciTech Connect

The U.S. Department of Energy (DOE) Building Technologies Program has set the aggressive goal of producing marketable net-zero energy buildings by 2025. This goal will require collaboration between the DOE laboratories and the building industry. We developed standard or reference energy models for the most common commercial buildings to serve as starting points for energy efficiency research. These models represent fairly realistic buildings and typical construction practices. Fifteen commercial building types and one multifamily residential building were determined by consensus between DOE, the National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory, and represent approximately two-thirds of the commercial building stock.

Deru, M.; Field, K.; Studer, D.; Benne, K.; Griffith, B.; Torcellini, P.; Liu, B.; Halverson, M.; Winiarski, D.; Rosenberg, M.; Yazdanian, M.; Huang, J.; Crawley, D.

2011-02-01T23:59:59.000Z

307

"ENDING STOCKS OF CRUDE OIL (excluding SPR)"  

U.S. Energy Information Administration (EIA) Indexed Site

ENDING STOCKS OF CRUDE OIL (excluding SPR)" ENDING STOCKS OF CRUDE OIL (excluding SPR)" "Sourcekey","WCESTP11","WCESTP11","WCESTP21","WCESTP21","WCESTP31","WCESTP31","WCESTP41","WCESTP41","WCESTP51","WCESTP51","WCESTUS1","WCESTUS1" "Date","Weekly East Coast (PADD 1) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly East Coast (PADD 1) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Midwest (PADD 2) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Midwest (PADD 2) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Gulf Coast (PADD 3) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Gulf Coast (PADD 3) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Rocky Mountain (PADD 4) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly Rocky Mountain (PADD 4) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly West Coast (PADD 5) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly West Coast (PADD 5) Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly U.S. Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)","Weekly U.S. Ending Stocks excluding SPR of Crude Oil (Thousand Barrels)"

308

The Impact of the Clean Air Act Amendments of 1990 on Electric Utilities and Coal Mines: Evidence from the Stock Market  

E-Print Network (OSTI)

In contrast, stock prices of coal mining companiesstudied. depress stock prices of several Eastern coal miningIn contrast, stock prices of practically all 12 coal mining

Kahn, Shulamit; Knittel, Christopher R.

2003-01-01T23:59:59.000Z

309

Distillate Stocks are Low - Especially on the East Coast  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Distillate stocks are normally built during the summer for use during the winter as shown by the normal band. Currently, stocks are very low for this time of year. This graph shows East Coast inventories, which at the end of August, were well below the normal band (over 9 million barrels or 19% below the low end of the band). The East Coast is about 31% lower than its 10-year average level for this time of year. We focus on the East Coast (PADD 1 ) because this a region in which heating oil is a major winter fuel. Furthermore, the East Coast consumes almost 2/3 of the nation's heating oil (high sulfur distillate). December 1999 was the turning point. Stocks were well within the normal range through November 1999, but in December, they dropped below the

310

Residential electricity demand: a suggested appliance stock equation  

Science Conference Proceedings (OSTI)

The author develops a simple appliance stock equation for estimating seasonal patterns of power demand elasticity. The equation relates an index of appliances (estimates of typical use) to marginal price per kWh, to income, to average price of alternative fuels, to climate (cooling degree days and heating degree days), to age of the household head, to family size, and to race. Price elasticity is -0.785 for the winter and 0.493 for the summer, with all estimates significant to 0.001. The appliance stock coefficient is 0.801 for the winter and 0.971 for the summer. The equation may be useful in studies that do not require elaborate disaggregation of appliance stock. 7 references, 2 tables.

Garbacz, C.

1984-04-01T23:59:59.000Z

311

Buildings","Total  

U.S. Energy Information Administration (EIA) Indexed Site

L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" L2. Floorspace Lit by Lighting Types (Non-Mall Buildings), 1999" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",61707,58693,49779,6496,37150,3058,5343,1913 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6750,5836,4878,757,3838,231,109,162 "5,001 to 10,000 ..............",7940,7166,5369,1044,4073,288,160,109 "10,001 to 25,000 .............",10534,9773,7783,1312,5712,358,633,232

312

Buildings","Total  

U.S. Energy Information Administration (EIA) Indexed Site

L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" L3. Floorspace Lit by Lighting Type (Non-Mall Buildings), 2003" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings* ...............",64783,62060,51342,5556,37918,4004,4950,2403 "Building Floorspace" "(Square Feet)" "1,001 to 5,000 ...............",6789,6038,4826,678,3932,206,76,124 "5,001 to 10,000 ..............",6585,6090,4974,739,3829,192,238,248 "10,001 to 25,000 .............",11535,11229,8618,1197,6525,454,506,289

313

Buildings","Total  

U.S. Energy Information Administration (EIA) Indexed Site

L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" L1. Floorspace Lit by Lighting Type for Non-Mall Buildings, 1995" ,"Floorspace (million square feet)" ,"Total (Lit or Unlit) in All Buildings","Total (Lit or Unlit) in Buildings With Any Lighting","Lighted Area Only","Area Lit by Each Type of Light" ,,,,"Incan- descent","Standard Fluor-escent","Compact Fluor- escent","High Intensity Discharge","Halogen" "All Buildings*",54068,51570,45773,6746,34910,1161,3725,779 "Building Floorspace" "(Square Feet)" "1,001 to 5,000",6272,5718,4824,986,3767,50,22,54 "5,001 to 10,000",7299,6667,5728,1240,4341,61,169,45 "10,001 to 25,000",10829,10350,8544,1495,6442,154,553,"Q"

314

A Note on Pricing Options on Defaultable Stocks  

E-Print Network (OSTI)

In this note, we develop stock option price approximations for a model which takes both the risk o default and the stochastic volatility into account. We also let the intensity of defaults be influenced by the volatility. We show that it might be possible to infer the risk neutral default intensity from the stock option prices. Our option price approximation has a rich implied volatility surface structure and fits the data implied volatility well. Our calibration exercise shows that an effective hazard rate from bonds issued by a company can be used to explain the implied volatility skew of the implied volatility of the option prices issued by the same company.

Bayraktar, Erhan

2007-01-01T23:59:59.000Z

315

Wisdom of Crowds Algorithm for Stock Market Predictions  

E-Print Network (OSTI)

In this paper we present a mathematical model for collaborative filtering implementation in stock market predictions. In popular literature collaborative filtering, also known as Wisdom of Crowds, assumes that group has a greater knowledge than the individual while each individual can improve group's performance by its specific information input. There are commercially available tools for collaborative stock market predictions and patent protected web-based software solutions. Mathematics that lies behind those algorithms is not disclosed in the literature, so the presented model and algorithmic implementation are the main contributions of this work.

Velic, Marko; Padavic, Ivan

2013-01-01T23:59:59.000Z

316

The Evolution of Aggregate Stock Ownership: A Unified Explanation  

E-Print Network (OSTI)

Since World War II, the fraction of stocks owned directly by households has decreased by more than 50 percentage points in the United States, the United Kingdom, and Sweden. We argue that tax policy is the driving force. Using data from eight countries, we show that tax-favored investors have replaced households as stockholders and that the fraction of household ownership decreases with measures of the effective marginal tax rate. We further show that the changes in stock ownership accelerate during the high-inflation period of the 1970s and the 1980s. These findings are important for policy considerations on effective taxation and for financial economics research on the longterm

Kristian Rydqvist; Joshua Spizman; Ilya Strebulaev

2008-01-01T23:59:59.000Z

317

Total Crude by Pipeline  

U.S. Energy Information Administration (EIA) Indexed Site

Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Product: Total Crude by All Transport Methods Domestic Crude by All Transport Methods Foreign Crude by All Transport Methods Total Crude by Pipeline Domestic Crude by Pipeline Foreign Crude by Pipeline Total Crude by Tanker Domestic Crude by Tanker Foreign Crude by Tanker Total Crude by Barge Domestic Crude by Barge Foreign Crude by Barge Total Crude by Tank Cars (Rail) Domestic Crude by Tank Cars (Rail) Foreign Crude by Tank Cars (Rail) Total Crude by Trucks Domestic Crude by Trucks Foreign Crude by Trucks Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: Product Area 2007 2008 2009 2010 2011 2012 View

318

Evolutionary multiobjective optimization approach for evolving ensemble of intelligent paradigms for stock market modeling  

Science Conference Proceedings (OSTI)

The use of intelligent systems for stock market predictions has been widely established. This paper introduces a genetic programming technique (called Multi-Expression programming) for the prediction of two stock indices. The performance is then compared ...

Ajith Abraham; Crina Grosan; Sang Yong Han; Alexander Gelbukh

2005-11-01T23:59:59.000Z

319

Practical Handbook of Soybean Processing and UtilizationChapter 13 Hydrogenation and Base Stock Formulation Procedures  

Science Conference Proceedings (OSTI)

Practical Handbook of Soybean Processing and Utilization Chapter 13 Hydrogenation and Base Stock Formulation Procedures Processing eChapters Processing Downloadable pdf of Chapter 13 Hydrogenation and Base Stock Formu

320

Analysis of Financial News Impact on Stock Based on a Statistical Learning Method with News Density  

Science Conference Proceedings (OSTI)

Since the investors often react to news and consequently make stock prices move, financial news has an impact on stock prices. However, the price adjustment process is a complex one. In this paper, a statistical learning methodology has been proposed ...

Feng Wang; Xiaodong Li; Chenxiao Dou

2011-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial...  

NLE Websites -- All DOE Office Websites (Extended Search)

Towards a Very Low Energy Building Stock: Modeling the U.S. Commercial Building Sector to Support Policy and Innovation Planning Title Towards a Very Low Energy Building Stock:...

322

Fuzzy-neural model with hybrid market indicators for stock forecasting  

Science Conference Proceedings (OSTI)

A number of research had been carried out to forecast stock price based on technical indicators, which rely purely on historical stock price data. Nevertheless, their performance is not always satisfactory. In this paper, the effect of using hybrid market ...

A. A. Adebiyi; C. K. Ayo; S. O. Otokiti

2011-07-01T23:59:59.000Z

323

Types of Radiation Exposure  

NLE Websites -- All DOE Office Websites (Extended Search)

External Irradiation Contamination Incorporation Biological Effects of Acute, Total Body Irradiation Managing Radiation Emergencies Procedure Demonstration Types of radiation...

324

Establishing relationships among patterns in stock market data  

Science Conference Proceedings (OSTI)

Similarities among subsequences are typically regarded as categorical features of sequential data. We introduce an algorithm for capturing the relationships among similar, contiguous subsequences. Two time series are considered to be similar during a ... Keywords: Financial applications, Knowledge discovery, Pattern mining, Stock market, Time series data

Dietmar H. Dorr; Anne M. Denton

2009-03-01T23:59:59.000Z

325

U.S. Ending Stocks of Fuel Ethanol (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Ending Stocks of Fuel Ethanol (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1993: 2,059: 1,946: 1,929: 2,152: 2,441: 2,627: 2,706 ...

326

Sense the Words: The Impact of Discussion Board Postings on the Stock Market  

Science Conference Proceedings (OSTI)

Some empirical studies claim that postings in the stock message board have a small but significant correlation on stock return. We study the effect of 2.85 million postings of 58 representative listed firms in HS300 index in China. Instead of considering ... Keywords: dicussion board, postings, word count, stock market

Tiejun Wang; Junwei Ma; Xin Liu; Qing Li

2012-10-01T23:59:59.000Z

327

A GA-weighted ANFIS model based on multiple stock market volatility causality for TAIEX forecasting  

Science Conference Proceedings (OSTI)

Stock market forecasting is important and interesting, because the successful prediction of stock prices may promise attractive benefits. The economy of Taiwan relies on international trade deeply, and the fluctuations of international stock markets ... Keywords: ANFIS, Genetic algorithm, Neural network, Weighted rule

Liang-Ying Wei

2013-02-01T23:59:59.000Z

328

Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning  

E-Print Network (OSTI)

Stock Price and Index Forecasting by Arbitrage Pricing Theory-Based Gaussian TFA Learning Kai Chun take advantage of those models. In literature, forecasting of stock prices within the framework Xu, (2002) "Stock price and index forecasting by arbitrage pricing theory-based gaussian TFA learning

Xu, Lei

329

The optimization of the stocks within coal power stations using the dynamic programming method  

Science Conference Proceedings (OSTI)

The purpose of this paper is to devise an economic and mathematical model for forecasting and optimizing the need of coal, for determining the current stock size and optimizing the supply-storage costs within a coal-fired power plant. The conditions ... Keywords: continuous flow production, dynamic programming method, energetic resources, optimization of the safety stock, power plants, stock analysis

Rascolean Ilie; Isac Claudia; Dura Codruta

2009-12-01T23:59:59.000Z

330

Support vector regression with chaos-based firefly algorithm for stock market price forecasting  

Science Conference Proceedings (OSTI)

Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box-Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market ... Keywords: Chaotic mapping, Firefly algorithm, Stock market price forecasting, Support vector regression

Ahmad Kazem; Ebrahim Sharifi; Farookh Khadeer Hussain; Morteza Saberi; Omar Khadeer Hussain

2013-02-01T23:59:59.000Z

331

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

332

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

333

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings*...

334

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings...

335

Differences of opinion and the cross-section of stock returns  

E-Print Network (OSTI)

We provide evidence that stocks with higher dispersion in analysts’ earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks, and stocks that have performed poorly over the past year. Interpreting dispersion in analysts ’ forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts’ forecasts proxies for risk.

Karl B. Diether; Christopher J. Malloy; Anna Scherbina

2001-01-01T23:59:59.000Z

336

Kokanee Stock Status and Contribution of Cabinet Gorge Hatchery, Lake Pend Oreille, Idaho, 1990 Annual Progress Report.  

DOE Green Energy (OSTI)

Rehabilitation of kokanee Oncorhynchus nerka in Lake Pend Oreille met with some success in 1990, but unexpected results have raised new questions. Estimated kokanee abundance during late August of 1990 was about 6.9 million fish. This is a decline of 19% from 1989, a continued decrease since 1988. The decreased population was attributed to low stocking of hatchery fry (7.3 million), lower wild fry survival in 1990 (1.5%), and exceptionally poor survival of fish ages 3+ and 4+. Average survival of the older fish was only 11% in 1990 compared to 72% in prior years. Compensatory survival was noted for kokanee ages 1+ and 2+, with an average of 81% in 1990 compared to 44% in 1989. Hatchery fry comprised 47% of the total kokanee fry recruitment in 1990 (80% of fry biomass). This contribution ranked third behind 1988 and 1989 since hatchery supplementation began in the 1970s. Survival of hatchery fry was 20%, the second highest since this investigation began. Findings of 1990 indicate a more comprehensive approach to managing kokanee must take into account predator stockings and predator/prey interaction. An unexpected low adult escapement was responsible for an egg-take of only 5.6 million eggs in 1990, 58% of the previous year, which will limit experimental stocking in 1991. Modification of the fish ladder at the Cabinet Gorge Fish Hatchery to improve adult escapement is strongly recommended to increase egg-take. 27 refs., 28 figs., 6 tabs.

Paragamian, Vaughn L.

1991-03-01T23:59:59.000Z

337

Hubei Shenzhou New Energy Power Generation Stock Co Ltd | Open Energy  

Open Energy Info (EERE)

Hubei Shenzhou New Energy Power Generation Stock Co Ltd Hubei Shenzhou New Energy Power Generation Stock Co Ltd Jump to: navigation, search Name Hubei Shenzhou New Energy Power Generation Stock Co Ltd Place Hubei Province, China Sector Biomass Product Hubei-based biomass power project developer. References Hubei Shenzhou New Energy Power Generation Stock Co Ltd[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Hubei Shenzhou New Energy Power Generation Stock Co Ltd is a company located in Hubei Province, China . References ↑ "Hubei Shenzhou New Energy Power Generation Stock Co Ltd" Retrieved from "http://en.openei.org/w/index.php?title=Hubei_Shenzhou_New_Energy_Power_Generation_Stock_Co_Ltd&oldid=346655

338

Connecticut Prices, Sales Volumes & Stocks  

Gasoline and Diesel Fuel Update (EIA)

- - - - - - 1986-2013 - - - - - - 1986-2013 Kerosene-Type Jet Fuel (Refiner Sales) W W W W W W 1984-2013 Kerosene (Refiner Sales) - W W - - NA 1984-2013 No. 1 Distillate (Refiner Sales) - - - - - - 1984-2013 No. 2 Distillate - - - - - - 1983-2013 No. 2 Fuel Oil (Residential) - - - - - - 1983-2013 No. 2 Diesel Fuel (Retail Outlets) - - - - - - 1994-2013 No. 4 Fuel Oil (Refiner Sales) W W W W W NA 1993-2013 Prime Supplier Sales Volumes (Thousand Gallons per Day) Motor Gasoline 3,969.5 4,012.0 3,982.9 4,034.9 3,938.4 3,955.8 1983-2013 Regular 3,431.9 3,470.2 3,458.0 3,486.5 3,382.7 3,432.7 1983-2013 Midgrade 62.5 64.9 67.3 73.9 67.8 57.4 1988-2013 Premium 475.0 476.9 457.6 474.5 487.9 465.7 1983-2013 Aviation Gasoline 2.7 4.1 3.0 6.1 3.4 3.5 1983-2013

339

Taking stock of renewables: NREL teaches farm and ranch appliations  

Science Conference Proceedings (OSTI)

NREL workshop leaders find a receptive audience for renewable energy technologies among farmers and ranchers. As an exhibitor/participant in Denver`s National Western Stock Show, the National Renewable Energy Laboratory (NREL) of Golden, Colorado sponsored an educational workshop to demonstrate applications of solar and wind energy on the farm and ranch, offering a very non-traditional energy approach to people who pride themselves in tradition. This article describes solar and wind energy applications to farms and ranches.

Marsh, M.G. [NREL, Golden, CO (United States)

1996-09-01T23:59:59.000Z

340

Duck Valley Resident Fish Stocking Program, 2000 Final Annual Report.  

DOE Green Energy (OSTI)

The Shoshone-Paiute Tribes fish-stocking program was begun in 1988 and is intended to provide a subsistence fishery for the tribal members. The program stocks catchable and fingerling size trout in Mt. View and Sheep Creek Reservoirs. Rainbow trout are purchased from only certified disease-free facilities to be stocked in our reservoirs. This project will help restore a fishery for tribal members that historically depended on wild salmon and steelhead in the Owyhee and Bruneau Rivers and their tributaries for their culture as well as for subsistence. This project is partial substitution for loss of anadromous fish production due to construction and operation of hydroelectric dams on the Columbia and Snake Rivers. Until anadromous fish can be returned to the Owyhee and Bruneau Rivers this project will continue indefinitely. As part of this project the Shoshone-Paiute Tribes will also receive income in the form of fees from non-tribal members who come to fish these reservoirs. Regular monitoring and evaluation of the fishery will include sampling for length/weight/condition and for signs of disease. A detailed Monitoring and evaluation plan has been put in place for this project. However due to budget limitations on this project only the fishery surveys and limited water quality work can be completed. A creel survey was initiated in 1998 and we are following the monitoring and evaluation schedule for this program (as budget allows) as well as managing the budget and personnel. This program has been very successful in the past decade and has provided enjoyment and sustenance for both tribal and non-tribal members. All biological data and stocking rates will be including in the Annual reports to Bonneville Power Administration (BPA).

Dodson, Guy; Pero, Vincent

2002-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Total Energy - Data - U.S. Energy Information Administration (EIA)  

U.S. Energy Information Administration (EIA)

Coal. Reserves, production, prices, employ- ment and productivity, distribution, stocks, imports and exports. Renewable & Alternative Fuels.

342

Method and apparatus for forming flues on tubular stock  

DOE Patents (OSTI)

The present invention is directed to a die mechanism utilized for forming flues on long, relatively narrow tubular stock. These flues are formed by displacing a die from within the tubular stock through perforations previously drilled through the tubular stock at selected locations. The drawing of the die upsets the material to form the flue of the desired configuration. The die is provided with a lubricating system which enables the lubricant to be dispensed uniformly about the entire periphery of the die in contact with the material being upset so as to assure the formation of the flues. Further, the lubricant is dispensed from within the die onto the peripheral surface of the latter at pressures in the range of about 2000 to 10,000 psi so as to assure the adequate lubrication of the die during the drawing operation. By injecting the lubricant at such high pressures, low viscosity liquid, such as water and/or alcohol, may be efficiently used as a lubricant and also provides a mechanism by which the lubricant may be evaporated from the surface of the flues at ambient conditions so as to negate the cleansing operations previously required prior to joining the flues to other conduit mechanisms by fusion welding and the like.

Beck, D.E.; Carson, C.

1979-12-21T23:59:59.000Z

343

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Survey: Energy End-Use Consumption Tables Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other...

344

Lake Roosevelt Fisheries Evaluation Program : Meadow Creek vs. Lake Whatcom Stock Kokanee Salmon Investigations in Lake Roosevelt Annual Report 2000-2001.  

DOE Green Energy (OSTI)

Lake Roosevelt has been stocked with Whatcom stock kokanee since 1989 to mitigate for anadromous salmon losses caused by the construction of Grand Coulee Dam. The primary objective of the hatchery plantings was to create a self-sustaining recreational fishery. Due to low return numbers, it was hypothesized a native stock of kokanee might perform better than the coastal Whatcom strain. Therefore, kokanee from Meadow Creek, a tributary of Kootenay Lake, British Columbia were selected as an alternative stock. Matched pair releases of Whatcom stock and Meadow Creek kokanee were made from Sherman Creek in late June 2000. Stock performance between Lake Whatcom and Meadow Creek kokanee was evaluated through three performance measures (1) returns to Sherman Creek, the primary egg collection facility, (2) returns to other tributaries, indicating availability for angler harvest, and (3) returns to the creel. A secondary objective was to evaluate the numbers collected at downstream fish passage facilities. Age 2 kokanee were collected during five passes through the reservoir, which included 89 tributaries between August 17th and November 7th, 2000. Sherman Creek was sampled once a week because it was the primary egg collection location. A total of 2,789 age 2 kokanee were collected, in which 2,658 (95%) were collected at Sherman Creek. Chi-square analysis indicated the Meadow Creek kokanee returned to Sherman Creek in significantly higher numbers compared to the Whatcom stock ({chi}{sup 2} = 734.4; P < 0.01). Reservoir wide recoveries indicated similar results ({chi}{sup 2} = 733.1; P < 0.01). No age 2 kokanee were collected during creel surveys. Age 3 kokanee are expected to recruit to the creel in 2001. No age 2 kokanee were collected at the fish passage facilities due to a 170 mm size restriction at the fish passage centers. Age 3 kokanee are expected to be collected at the fish passage centers during 2001. Stock performance cannot be properly evaluated until 2001, when age 3 kokanee are expected to return to Sherman Creek.

McLellan, Holly J.; Scholz, Allan T.

2001-07-01T23:59:59.000Z

345

Performance Period Total Fee Paid  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Period Period Total Fee Paid 4/29/2012 - 9/30/2012 $418,348 10/1/2012 - 9/30/2013 $0 10/1/2013 - 9/30/2014 $0 10/1/2014 - 9/30/2015 $0 10/1/2015 - 9/30/2016 $0 Cumulative Fee Paid $418,348 Contract Type: Cost Plus Award Fee Contract Period: $116,769,139 November 2011 - September 2016 $475,395 $0 Fee Information Total Estimated Contract Cost $1,141,623 $1,140,948 $1,140,948 $5,039,862 $1,140,948 Maximum Fee $5,039,862 Minimum Fee Fee Available Portage, Inc. DE-DT0002936 EM Contractor Fee Site: MOAB Uranium Mill Tailings - MOAB, UT Contract Name: MOAB Uranium Mill Tailings Remedial Action Contract September 2013 Contractor: Contract Number:

346

U.S. Total Exports  

U.S. Energy Information Administration (EIA) Indexed Site

TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Kenai, AK Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to...

347

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to...

348

21 briefing pages total  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

briefing pages total p. 1 briefing pages total p. 1 Reservist Differential Briefing U.S. Office of Personnel Management December 11, 2009 p. 2 Agenda - Introduction of Speakers - Background - References/Tools - Overview of Reservist Differential Authority - Qualifying Active Duty Service and Military Orders - Understanding Military Leave and Earnings Statements p. 3 Background 5 U.S.C. 5538 (Section 751 of the Omnibus Appropriations Act, 2009, March 11, 2009) (Public Law 111-8) Law requires OPM to consult with DOD Law effective first day of first pay period on or after March 11, 2009 (March 15 for most executive branch employees) Number of affected employees unclear p. 4 Next Steps

349

Barge Truck Total  

U.S. Energy Information Administration (EIA) Indexed Site

Barge Barge Truck Total delivered cost per short ton Shipments with transportation rates over total shipments Total delivered cost per short ton Shipments with transportation rates over total shipments Year (nominal) (real) (real) (percent) (nominal) (real) (real) (percent) 2008 $6.26 $5.77 $36.50 15.8% 42.3% $6.12 $5.64 $36.36 15.5% 22.2% 2009 $6.23 $5.67 $52.71 10.8% 94.8% $4.90 $4.46 $33.18 13.5% 25.1% 2010 $6.41 $5.77 $50.83 11.4% 96.8% $6.20 $5.59 $36.26 15.4% 38.9% Annual Percent Change First to Last Year 1.2% 0.0% 18.0% - - 0.7% -0.4% -0.1% - - Latest 2 Years 2.9% 1.7% -3.6% - - 26.6% 25.2% 9.3% - - - = No data reported or value not applicable STB Data Source: The Surface Transportation Board's 900-Byte Carload Waybill Sample EIA Data Source: Form EIA-923 Power Plant Operations Report

350

Proposed Fidelity Option Line-Up Tier Fund Type Fund Category/Asset Class Proposed Investment Option  

E-Print Network (OSTI)

Fidelity BrokerageLink 3/1/11 #12;Proposed TIAA-CREF Option Line-Up Tier Fund Type Fund Category Fund TIAA-CREF Money Market Fund Fixed Income Fixed Annuity TIAA Traditional Annuity Intermediate Bond Stock Fund CREF Stock Variable Annuity Real Estate Real Estate Fund TIAA-CREF Real Estate Annuity IV

351

Stock price fluctuations and the mimetic behaviors of traders  

E-Print Network (OSTI)

We give a stochastic microscopic modelling of stock markets driven by continuous double auction. If we take into account the mimetic behavior of traders, when they place limit order, our virtual markets shows the power-law tail of the distribution of returns with the exponent outside the Levy stable region, the short memory of returns and the long memory of volatilities. The Hurst exponent of our model is asymptotically 1/2. An explanation is also given for the profile of the autocorrelation function, which is responsible for the value of the Hurst exponent.

Maskawa, J

2006-01-01T23:59:59.000Z

352

Spent fuel test project, Climax granitic stock, Nevada Test Site  

SciTech Connect

The Spent Fuel Test-Climax (SFT-C) is a test of dry geologic storage of spent nuclear reactor fuel. The SFT-C is located at a depth of 420 m in the Climax granitic stock at the Nevada Test Site. Eleven canisters of spent commercial PWR fuel assemblies are to be stored for 3 to 5 years. Additional heat is supplied by electrical heaters, and more than 800 channels of technical information are being recorded. The measurements include rock temperature, rock displacement and stress, joint motion, and monitoring of the ventilation air volume, temperature, and dewpoint.

Ramspott, L.D.

1980-10-24T23:59:59.000Z

353

Utah Distillate Fuel Oil, Greater than 15 to 500 ppm Sulfur Stocks ...  

U.S. Energy Information Administration (EIA)

Utah Distillate Fuel Oil, Greater than 15 to 500 ppm Sulfur Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)

354

Internal Evolution for Agent Cognition - Agent-Based Modelling of an Artificial Stock Market.  

E-Print Network (OSTI)

??Agent-Based Modeling (ABM) is a powerful simulation technique with applications in several fields, in particular social sciences. Artificial Stock Market (ASM), introduced by a group… (more)

Hassanzadeh, Morteza

2011-01-01T23:59:59.000Z

355

Two essays on the study of capital structure in Chinese stock market.  

E-Print Network (OSTI)

??This thesis contains two essays on the study of capital structure in Chinese stock market. The first essay tries to prove the validity of the… (more)

Cai, Jinghan (???)

2005-01-01T23:59:59.000Z

356

Financial liberalisation and the capital structure of firms listed on the Johannesburg stock exchange.  

E-Print Network (OSTI)

??This thesis examines the impact of financial liberalisation on the capital structure of non-financial firms listed on the Johannesburg Stock Exchange (JSE). The research hypotheses… (more)

Chipeta, Chimwemwe

2012-01-01T23:59:59.000Z

357

Stock market volatility and price discovery : three essays on the effect of macroeconomic information  

E-Print Network (OSTI)

Simple Microstructure Model of Price Determination . . 3.11Stock Market Volatility and Price Discovery: Three Essays onConstruction Spending PRICES CPI MONETARY POLICY FFR Source:

Rangel, Jose Gonzalo

2006-01-01T23:59:59.000Z

358

West Coast (PADD 5) Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

359

Catalytic conversion of C3+ alcohols to hydrocarbon blend-stock  

Catalytic conversion of C3+ alcohols to hydrocarbon blend-stock Note: The technology described above is an early stage opportunity. Licensing rights to this ...

360

East Coast (PADD 1) Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Rocky Mountain (PADD4) Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

362

Stocks of Crude Oil (Including SPR) - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

-No Data Reported; --= Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Notes: Stocks include those ...

363

Design Process for Restoring Stock Ride and Roll Characteristics to a Modified Vehicle.  

E-Print Network (OSTI)

??A design process for selection of suspension components for a hybrid vehicle has been proposed. A stock SUV was placed on a suspension parameter measurement… (more)

Roblin, Michael William

2007-01-01T23:59:59.000Z

364

The Role of Self-Efficacy in Stock-Market Participation and Financial Information-Seeking .  

E-Print Network (OSTI)

??This study of self-efficacy's (Bandura, 1977) effects on an individual's likelihood to invest in the stock market and seek financial information attempts to uncover some… (more)

[No author

2008-01-01T23:59:59.000Z

365

Stock market volatility and price discovery : three essays on the effect of macroeconomic information  

E-Print Network (OSTI)

of Macro Announcements: Real Time Price Discovery in Foreign93, 38–62. (2005): “Real Time Price Discovery in Stock, Bond

Rangel, Jose Gonzalo

2006-01-01T23:59:59.000Z

366

U.S. Total Exports  

Annual Energy Outlook 2012 (EIA)

NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to India Freeport, TX Sabine Pass, LA Total to Japan...

367

Crude Oil Stocks at Tank Farms & Pipelines  

Gasoline and Diesel Fuel Update (EIA)

Stocks at Tank Farms & Pipelines Stocks at Tank Farms & Pipelines (Thousand Barrels) Period: Monthly Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Area Apr-13 May-13 Jun-13 Jul-13 Aug-13 Sep-13 View History U.S. 263,633 264,749 252,781 242,174 232,837 248,898 1981-2013 East Coast (PADD 1) 2,000 1,635 1,585 1,793 1,507 2,033 1981-2013 Midwest (PADD 2) 100,842 101,525 99,186 89,116 84,420 84,878 1981-2013 Cushing, OK 49,237 50,172 48,671 40,459 34,809 33,017 2004-2013 Gulf Coast (PADD 3) 121,316 121,816 113,846 112,745 112,059 122,497 1981-2013 Rocky Mountain (PADD 4) 12,813 12,512 12,003 12,181 12,858 12,956 1981-2013 West Coast (PADD 5) 26,662 27,261 26,161 26,339 21,993 26,534 1981-2013

368

Total Sales of Kerosene  

U.S. Energy Information Administration (EIA) Indexed Site

End Use: Total Residential Commercial Industrial Farm All Other Period: End Use: Total Residential Commercial Industrial Farm All Other Period: Annual Download Series History Download Series History Definitions, Sources & Notes Definitions, Sources & Notes Show Data By: End Use Area 2007 2008 2009 2010 2011 2012 View History U.S. 492,702 218,736 269,010 305,508 187,656 81,102 1984-2012 East Coast (PADD 1) 353,765 159,323 198,762 237,397 142,189 63,075 1984-2012 New England (PADD 1A) 94,635 42,570 56,661 53,363 38,448 15,983 1984-2012 Connecticut 13,006 6,710 8,800 7,437 7,087 2,143 1984-2012 Maine 46,431 19,923 25,158 24,281 17,396 7,394 1984-2012 Massachusetts 7,913 3,510 5,332 6,300 2,866 1,291 1984-2012 New Hampshire 14,454 6,675 8,353 7,435 5,472 1,977 1984-2012

369

Types of Costs Types of Cost Estimates  

E-Print Network (OSTI)

· Types of Costs · Types of Cost Estimates · Methods to estimate capital costs MIN E 408: Mining the equipment for reclamation? Types of Costs #12;· Marginal Cost: ­ Change in total cost ­ Any production process involves fixed and variable costs. As production increases/expands, fixed costs are unchanged, so

Boisvert, Jeff

370

SolarTotal | Open Energy Information  

Open Energy Info (EERE)

SolarTotal SolarTotal Jump to: navigation, search Name SolarTotal Place Bemmel, Netherlands Zip 6681 LN Sector Solar Product The company sells and installs PV solar instalations Coordinates 51.894112°, 5.89881° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":51.894112,"lon":5.89881,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

371

An efficient fuzzy based neuro: genetic algorithm for stock market prediction  

Science Conference Proceedings (OSTI)

Stock market prediction is a complex and tedious task that involves the processing of large amounts of data, that are stored in ever growing databases. The vacillating nature of the stock market requires the use of data mining techniques like clustering ... Keywords: Kohonen network, clustering, data mining, genetic algorithms, machine learning, prediction

K. G. Srinivasa; K. R. Venugopal; L. M. Patnaik

2006-01-01T23:59:59.000Z

372

Use of Productivity and Susceptibility Indices to Determine Stock Vulnerability, with  

E-Print Network (OSTI)

of fish) should change as a function of spawning biomass of the stock or stock complex. The NS1 guidelines information. Control rules should be designed so that management actions become more conservative as biomass.5 are defined as high and low susceptibility, respectively. Biomass of Spawners: Analogous to fishing mortality

373

Stock Trading Using RSPOP: A Novel Rough Set-Based Neuro-Fuzzy Approach  

Science Conference Proceedings (OSTI)

This paper investigates the method of forecasting stock price difference on artificially generated price series data using neuro-fuzzy systems and neural networks. As trading profits is more important to an investor than statistical performance, this ... Keywords: Forecasting theory, fuzzy neural networks, rough set theory, stock market, time series

K. K. Ang; C. Quek

2006-09-01T23:59:59.000Z

374

Modelling the Stock Market using Twitter M. Sebastian A. WolframTH  

E-Print Network (OSTI)

to predict price trends immediately after the release of the article. He used press release articles rather et al. (Fung et al., 2002) who used pattern recognition methodologies to model stock price trends a major role in affecting the price of a company's stock. In today's information age, news can spread

Koehn, Philipp

375

Stock returns and the dispersion in earnings forecasts,” Working Paper No  

E-Print Network (OSTI)

Abstract: The efficient market hypothesis based on homogeneous expectations implies that future stock returns are unpredictable. However, the forecastability of stock returns has been well documented in a substantial literature. This paper introduces a new forecasting variable, dispersion in analysts ’ earnings forecasts. The implication from this finding is not only that we have another piece of evidence that stock returns are predictable, but also that alternative models should be used to explain movements of stock prices. Hence, this paper derives a relation between the dispersion in forecasts and future stock returns based on Harrison and Kreps (1978) and shows that the dispersion in forecasts exerts its own positive effect on demand in the market. Furthermore, this paper shows empirically that the dispersion in expectations has particularly strong predictive power for future stock returns at intermediate horizons (between 24 months and 43 months) and that it contains information about future stock returns aside from the information contained in other variables. In addition, the direction of predictive power from the dispersion for future stock returns is consistent with the derived relation from Harrison and Kreps (1978). This paper also shows that most of the movements in dispersion cannot be explained by other variables, such as common financial indicators, macroeconomic variables, market volatility, or non-economic events. Finally, Monte Carlo simulation shows that finite sample biases in long-horizon regressions using the dispersion do not seem so serious.

Cheolbeom Park

2001-01-01T23:59:59.000Z

376

Total Marketed Production ..............  

Gasoline and Diesel Fuel Update (EIA)

billion cubic feet per day) billion cubic feet per day) Total Marketed Production .............. 68.95 69.77 70.45 71.64 71.91 71.70 71.46 71.57 72.61 72.68 72.41 72.62 70.21 71.66 72.58 Alaska ......................................... 1.04 0.91 0.79 0.96 1.00 0.85 0.77 0.93 0.97 0.83 0.75 0.91 0.93 0.88 0.87 Federal GOM (a) ......................... 3.93 3.64 3.44 3.82 3.83 3.77 3.73 3.50 3.71 3.67 3.63 3.46 3.71 3.70 3.62 Lower 48 States (excl GOM) ...... 63.97 65.21 66.21 66.86 67.08 67.08 66.96 67.14 67.92 68.18 68.02 68.24 65.58 67.07 68.09 Total Dry Gas Production .............. 65.46 66.21 66.69 67.79 68.03 67.83 67.61 67.71 68.69 68.76 68.50 68.70 66.55 67.79 68.66 Gross Imports ................................ 8.48 7.60 7.80 7.95 8.27 7.59 7.96 7.91 7.89 7.17 7.61 7.73 7.96 7.93 7.60 Pipeline ........................................

377

Total Biofuels Consumption (2005 - 2009) Total annual biofuels...  

Open Energy Info (EERE)

Total Biofuels Consumption (2005 - 2009) Total annual biofuels consumption (Thousand Barrels Per Day) for 2005 - 2009 for over 230 countries and regions.      ...

378

Stocking of Offsite Waters for Hungry Horse Dam Mitigation Creston National Fish Hatchery, FY 2006 Annual Report.  

Science Conference Proceedings (OSTI)

A total of 350,000, M012 strain, westslope cutthroat trout (WCT) eggs were received from Montana Fish Wildlife & Parks (MFWP), Washoe Park State Fish Hatchery in June of 2005 to accomplish this fishery management objective. These eggs were incubated, hatched and reared entirely inside the hatchery nursery building using a protected well water supply. Fish grew according to schedule and survival was excellent. The hatchery achieved a 0.78 feed fed to pounds gained conversion ratio for this group of WCT. Not all of the progenies from this fish lot were used for Hungry Horse Dam Fishery Mitigation Implementation. Some were used for other regional fishery management projects. Westslope cutthroat trout were reared using approved fish culture techniques as recommended in the USFWS Fish Hatchery Management Handbook and also utilizing a regimen adapted for hatchery specific site conditions. The fish health for these WCT was very good. Survival from first feeding fry stage to stocking was 79%. The hatchery had an annual fish health inspection performed by the USFWS Bozeman Fish Health Center in mid March of 2006. This inspection found all fish lots at Creston to be disease free. The Montana State Fish Health Board has placed the hatchery under a limited quarantine since May of 2005 due to an epizootic of Furunculosis. This classification has allowed the Creston NFH to stock disease free fish in locations approved by regional fish managers. The hatchery has been working with the State Fish Pathologist to remove the limited quarantine classification from the facility. Although fish health for all station fish lots remains disease free, MFWP has asserted it will not remove the limited quarantine until the new influent water treatment system, including the ultraviolet disinfection unit, is running full time, year round. The USFWS is working to secure the additional funding necessary to operate the treatment building year round. Distribution of the WCT took place from March through June. The stocking locations on the Flathead Reservation and State managed waters were identified by Confederated Salish and Kootenai Tribe (CSKT) and MFWP fishery biologists. Post release survival and angler success is monitored routinely by CSKT and MFWP fishery technicians. Stocking numbers and locations vary annually based on the results of biological monitoring, creel evaluations and adaptive management decisions. A total of 99,126 WCT were stocked during nine distribution trips in management approved waters (see Table 1). The average size of WCT at stocking was 3.91-inches. A total of 101,600, Arlee strain, rainbow trout (RBT) eggs were received from the Ennis National Fish Hatchery, Ennis, Montana, in December of 2005 and 35,000 Kamloops strain eggs were received from Murray Springs SFH, Eureka, Montana, in March of 2006 to accomplish this fishery management objective. The RBT were reared using approved fish culture techniques as recommended in the USFWS Fish Hatchery Management Handbook. There was no fish health related problems associated with this lot of fish. Survival from swim up fry stage to stocking was 93% for the Arlee's and 79% for the Kamloops. The hatchery achieved a 0.68 feed fed to pounds gained conversion ratio for the Arlee and 0.97 for the Kamloops RBT. The excellent feed conversion ratio can be attributed to refined feeding techniques and the use of an extruded high performance fry feed made with premium fish meal and marine fish oil. The Arlee strain of rainbow trout is requested for this fishery mitigation objective because the chosen stocking locations are terminal basin reservoirs or lakes, habitat conditions prevent natural spawning runs and returns to the creel are more favorable then for native westslope cutthroat trout. MFWP also requested a fall plant of Kamloops strain RBT and they will be evaluated for performance and future fall stockings in Echo Lake. Post release survival and angler success is monitored routinely by the Confederated Salish and Kootenai Tribe (CSKT) and Montana Fish Wildlife & Parks (MFWP) fishery techn

Hooley, Sharon

2009-03-20T23:59:59.000Z

379

The Stock Market Reaction to Oil Price Changes  

E-Print Network (OSTI)

I explore the reaction of the stock market as a whole and of different industries to daily oil price changes. I find that the direction and magnitude of the market?s reaction to oil price changes depend on the magnitude of the price changes. Oil price changes most likely caused by supply shocks have a negative impact while oil price changes most likely caused by shifts in aggregate demand have a positive impact on the same day market returns. In addition to the returns of oil-intensive industries, returns of industries that do not use oil to any significant extent are also sensitive to oil price changes. Finally, I show that both the cost-side dependence and demand-side dependence on oil are important in explaining the sensitivity of industry returns to oil price changes. I am indebted to Louis Ederington. I am grateful for the helpful comments received from Chitru Fernando,

Sridhar Gogineni

2008-01-01T23:59:59.000Z

380

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Released: September, 2008 Released: September, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings* ........................... 3,037 115 397 384 52 1,143 22 354 64 148 357 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 386 19 43 18 11 93 7 137 8 12 38 5,001 to 10,000 .......................... 262 12 35 17 5 83 4 56 6 9 35 10,001 to 25,000 ........................ 407 20 46 44 8 151 3 53 9 19 54 25,001 to 50,000 ........................ 350 15 55 50 9 121 2 34 7 16 42 50,001 to 100,000 ...................... 405 16 57 65 7 158 2 29 6 18 45 100,001 to 200,000 .................... 483 16 62 80 5 195 1 24 Q 31 56 200,001 to 500,000 .................... 361 8 51 54 5 162 1 9 8 19 43 Over 500,000 ............................. 383 8 47 56 3 181 2 12 8 23 43 Principal Building Activity

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Figure 5.16 Petroleum Primary Stocks by Type, End of Year  

U.S. Energy Information Administration (EIA)

1949 1954 1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 0 500 1,000 1,500 2,000 Million Barrels (Cumulative) Petroleum Products SPRą Crude ...

382

Table 5.16 Petroleum Primary Stocks by Type, End of Year ...  

U.S. Energy Information Administration (EIA)

annual reports. - 1976-1980-U.S. Energy Information Administration (EIA), Energy Data Reports, Petroleum Statement, Annual, annual reports. - ...

383

Weekly East Coast (PADD 1) Ending Stocks of Kerosene-Type Jet Fuel ...  

U.S. Energy Information Administration (EIA)

9,977 : 04/20 : 9,525 : 04/27 : 8,585 : 2012-May: 05/04 : 8,884 : 05/11 : 8,607 : 05/18 : 10,044 : 05/25 : 10,075 : 2012-Jun: 06/01 : 9,465 : 06/08 : 10,058 : 06/15 :

384

Refining District Texas Gulf Coast Kerosene-Type Jet Fuel Stocks ...  

U.S. Energy Information Administration (EIA)

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1993: 3,029: 3,968: 3,482: 3,284: 3,543: 3,978: 3,501: 3,707: 2,993: 2,931: 3,003: 2,636: 1994: 3,924: 3,273 ...

385

Weekly U.S. Ending Stocks of Kerosene-Type Jet Fuel (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

Year-Month Week 1 Week 2 Week 3 Week 4 Week 5; End Date Value End Date Value End Date Value End Date Value End Date Value; 1982-Aug : 08/20 : 33,523 : 08/27

386

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

387

Total Space Heat-  

Gasoline and Diesel Fuel Update (EIA)

Revised: December, 2008 Revised: December, 2008 Total Space Heat- ing Cool- ing Venti- lation Water Heat- ing Light- ing Cook- ing Refrig- eration Office Equip- ment Com- puters Other All Buildings ............................. 91.0 33.0 7.2 6.1 7.0 18.7 2.7 5.3 1.0 2.2 7.9 Building Floorspace (Square Feet) 1,001 to 5,000 ........................... 99.0 30.7 6.7 2.7 7.1 13.9 7.1 19.9 1.1 1.7 8.2 5,001 to 10,000 .......................... 80.0 30.1 5.5 2.6 6.1 13.6 5.2 8.2 0.8 1.4 6.6 10,001 to 25,000 ........................ 71.0 28.2 4.5 4.1 4.1 14.5 2.3 4.5 0.8 1.6 6.5 25,001 to 50,000 ........................ 79.0 29.9 6.8 5.9 6.3 14.9 1.7 3.9 0.8 1.8 7.1 50,001 to 100,000 ...................... 88.7 31.6 7.6 7.6 6.5 19.6 1.7 3.4 0.7 2.0 8.1 100,001 to 200,000 .................... 104.2 39.1 8.2 8.9 7.9 22.9 1.1 2.9 Q 3.2 8.7 200,001 to 500,000 ....................

388

Determination of Total Petroleum Hydrocarbons (TPH) Using Total Carbon Analysis  

SciTech Connect

Several methods have been proposed to replace the Freon(TM)-extraction method to determine total petroleum hydrocarbon (TPH) content. For reasons of cost, sensitivity, precision, or simplicity, none of the replacement methods are feasible for analysis of radioactive samples at our facility. We have developed a method to measure total petroleum hydrocarbon content in aqueous sample matrixes using total organic carbon (total carbon) determination. The total carbon content (TC1) of the sample is measured using a total organic carbon analyzer. The sample is then contacted with a small volume of non-pokar solvent to extract the total petroleum hydrocarbons. The total carbon content of the resultant aqueous phase of the extracted sample (TC2) is measured. Total petroleum hydrocarbon content is calculated (TPH = TC1-TC2). The resultant data are consistent with results obtained using Freon(TM) extraction followed by infrared absorbance.

Ekechukwu, A.A.

2002-05-10T23:59:59.000Z

389

Columbia River Stock Identification Study; Validation of Genetic Method, 1980-1981 Final Report.  

DOE Green Energy (OSTI)

The reliability of a method for obtaining maximum likelihood estimate of component stocks in mixed populations of salmonids through the frequency of genetic variants in a mixed population and in potentially contributing stocks was tested in 1980. A data base of 10 polymorphic loci from 14 hatchery stocks of spring chinook salmon of the Columbia River was used to estimate proportions of these stocks in four different blind'' mixtures whose true composition was only revealed subsequent to obtaining estimates. The accuracy and precision of these blind tests have validated the genetic method as a valuable means for identifying components of stock mixtures. Properties of the genetic method were further examined by simulation studies using the pooled data of the four blind tests as a mixed fishery. Replicated tests with samples sizes between 100 and 1,000 indicated that actual standard deviations on estimated contributions were consistently lower than calculated standard deviations; this difference diminished as sample size increased. It is recommended that future applications of the method be preceded by simulation studies that will identify appropriate levels of sampling required for acceptable levels of accuracy and precision. Variables in such studies include the stocks involved, the loci used, and the genetic differentiation among stocks. 8 refs., 6 figs., 4 tabs.

Milner, George B.; Teel, David J.; Utter, Fred M. (Northwest and Alaska Fisheries Science Center, Coastal Zone and Estuarine Studies Division, Seattle, WA)

1981-06-01T23:59:59.000Z

390

U.S. Total Exports  

Gasoline and Diesel Fuel Update (EIA)

Babb, MT Havre, MT Port of Morgan, MT Pittsburg, NH Grand Island, NY Massena, NY Niagara Falls, NY Waddington, NY Sumas, WA Sweetgrass, MT Total to Chile Sabine Pass, LA Total to China Kenai, AK Sabine Pass, LA Total to India Freeport, TX Sabine Pass, LA Total to Japan Cameron, LA Kenai, AK Sabine Pass, LA Total to Mexico Douglas, AZ Nogales, AZ Calexico, CA Ogilby Mesa, CA Otay Mesa, CA Alamo, TX Clint, TX Del Rio, TX Eagle Pass, TX El Paso, TX Hidalgo, TX McAllen, TX Penitas, TX Rio Bravo, TX Roma, TX Total to Portugal Sabine Pass, LA Total to Russia Total to South Korea Freeport, TX Sabine Pass, LA Total to Spain Cameron, LA Sabine Pass, LA Total to United Kingdom Sabine Pass, LA Period: Monthly Annual

391

Combinatorial aspects of total positivity  

E-Print Network (OSTI)

In this thesis I study combinatorial aspects of an emerging field known as total positivity. The classical theory of total positivity concerns matrices in which all minors are nonnegative. While this theory was pioneered ...

Williams, Lauren Kiyomi

2005-01-01T23:59:59.000Z

392

Analysis of Realized Volatility in Two Trading Sessions of the Japanese Stock Market  

E-Print Network (OSTI)

We analyze realized volatilities constructed using high-frequency stock data on the Tokyo Stock Exchange. In order to avoid non-trading hours issue in volatility calculations we define two realized volatilities calculated separately in the two trading sessions of the Tokyo Stock Exchange, i.e. morning and afternoon sessions. After calculating the realized volatilities at various sampling frequencies we evaluate the bias from the microstructure noise as a function of sampling frequency. Taking into account of the bias to realized volatility we examine returns standardized by realized volatilities and confirm that price returns on the Tokyo Stock Exchange are described approximately by Gaussian time series with time-varying volatility, i.e. consistent with a mixture of distributions hypothesis.

Takaishi, Tetsuya; Zheng, Zeyu

2013-01-01T23:59:59.000Z

393

Disaster debris management and recovery of housing stock in San Francisco, CA  

E-Print Network (OSTI)

This thesis investigates the potential effects of a 7.2 magnitude earthquake in San Francisco City, particularly the implications on San Francisco's residential housing stock and impacts on the construction and demolition ...

Saiyed, Zahraa Nazim

2012-01-01T23:59:59.000Z

394

Distillate Stocks Expected to Remain Low - U.S. Energy Information ...  

U.S. Energy Information Administration (EIA)

When EIA’s demand forecast is combined with its outlook for production and net imports, distillate stocks are projected to remain low for the rest of the year.

395

,"U.S. Refinery, Bulk Terminal, and Natural Gas Plant Stocks...  

U.S. Energy Information Administration (EIA) Indexed Site

S1","MDGSXUS1","MRESXUS1","MPRSXUS1" "Date","U.S. Finished Motor Gasoline Stocks at Refineries, Bulk Terminals, and Natural Gas Plants (Thousand Barrels)","U.S. Reformulated Motor...

396

GG&A Hoofed Stock Price Year low high Comments 1971 97 ...  

Science Conference Proceedings (OSTI)

Page 1. GG&A Hoofed Stock Price Year low high Comments 1971 97–245 Bad year. 72 245–245 Light trading due to a heavy winter. ...

2013-02-19T23:59:59.000Z

397

International stock market linkages : are overnight returns on the U.S. Market informative?.  

E-Print Network (OSTI)

??Based on the theory of international stock market co-movements, this study shows that a profitable trading strategy can be developed. The U.S. market return is… (more)

An, Byeongung

2012-01-01T23:59:59.000Z

398

U.S. Refinery Grade Butane Stocks at Bulk Terminals (Thousand ...  

U.S. Energy Information Administration (EIA)

U.S. Refinery Grade Butane Stocks at Bulk Terminals (Thousand Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9; ...

399

U.S. Normal Butane-Butylene Stocks at Natural Gas Processing ...  

U.S. Energy Information Administration (EIA)

U.S. Normal Butane-Butylene Stocks at Natural Gas Processing Plants (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1993: ...

400

U.S. Refinery Grade Butane Stocks at Bulk Terminals (Thousand ...  

U.S. Energy Information Administration (EIA)

U.S. Refinery Grade Butane Stocks at Bulk Terminals (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 2005: 1,077: 999: 1,362: ...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

U.S. Ending Stocks of Normal Butane-Butylene (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Ending Stocks of Normal Butane-Butylene (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1981: 26,098: 24,979: 24,689: ...

402

Combining artificial neural networks and statistics for stock-market forecasting  

Science Conference Proceedings (OSTI)

We have developed a stock-market forecasting system based on artificial neural networks. The system has been trained with the Standard & Poor 500 composite indexes of past twenty years. Meanwhile, the system produces the forecasts and adjusts ...

Shaun-Inn Wu; Ruey-Pyng Lu

1993-03-01T23:59:59.000Z

403

More than just a school : an exploration in tractable neighborhood building stock  

E-Print Network (OSTI)

Shortages in land and resources are stiffling new construction and forcing the pursuit of alternate means to satisfy society's space needs within the existing building stock. Most existing buildings were not designed for ...

Stevermer, John Alton

1983-01-01T23:59:59.000Z

404

The Puzzle of Asymmetric Effects of Oil: New Results from International Stock Markets ?  

E-Print Network (OSTI)

Previous work has documented that oil price changes have nonlinear effects in the economy and in stock market returns. We show that the nonlinear effects are different depending on whether countries are energy dependent or not. While price soars seem to have a negative effect on the stock markets of oil energy dependent countries, they have a positive effect on the stock markets of oil exporting countries. Stock market returns are negatively affected by oil price volatility in energy dependent countries and positively in oil exporting countries. Moreover, we find bi-directional effects between oil price increases and some oil volatility measures that can be reinforced with volatility feedback. The asymmetric effects found in oil dependent and oil exporting countries seem to fit into the offset mechanism proposed in the literature where oil price shocks interact both with oil price volatility and the economy. The results are also consistent with the finding that oil exporting countries benefit economically from oil price hikes.

unknown authors

2011-01-01T23:59:59.000Z

405

Establishing a New Stock Market for Shareholder Value Oriented Firms in Korea  

E-Print Network (OSTI)

a reform, moreover, may give Korea the incentive and time toConference Program (Seoul, Korea 2002) sponsored by theVALUE*** (BIL. WON) OF * The Korea composite stock price

Choi, Stephen

2004-01-01T23:59:59.000Z

406

Total correlations and mutual information  

E-Print Network (OSTI)

In quantum information theory it is generally accepted that quantum mutual information is an information-theoretic measure of total correlations of a bipartite quantum state. We argue that there exist quantum states for which quantum mutual information cannot be considered as a measure of total correlations. Moreover, for these states we propose a different way of quantifying total correlations.

Zbigniew Walczak

2008-06-30T23:59:59.000Z

407

Recovering a time-homogeneous stock price process from perpetual option prices  

E-Print Network (OSTI)

It is well-known how to determine the price of perpetual American options if the underlying stock price is a time-homogeneous diffusion. In the present paper we consider the inverse problem, i.e. given prices of perpetual American options for different strikes we show how to construct a time-homogeneous model for the stock price which reproduces the given option prices.

Ekstrom, Erik

2009-01-01T23:59:59.000Z

408

Dynamic resource allocation in a multi-product make-to-stock production system  

Science Conference Proceedings (OSTI)

We consider optimal policies for a production facility in which several (K) products are made to stock in order to satisfy exogenous demand for each. The single machine version of this problem in which the facility manufactures at most ... Keywords: 68M20, 90B30, 90C39, Backordering, Dynamic programming, Dynamic resource allocation, Index heuristic, Lagrangian relaxation, Make-to-stock policy, Queueing control

D. J. Hodge; K. D. Glazebrook

2011-04-01T23:59:59.000Z

409

Listing Policy and Development of the Tokyo Stock Exchange in the Pre-War Period *  

E-Print Network (OSTI)

Recent studies have established that the Japanese stock market had a substantial size in the prewar period and played an important role in financing economic development. The pre-war stock market in Japan, however, did not achieve its size and status quickly. Indeed, the market capitalization stayed relatively small during the early years of the stock market development in Japan. This paper studies the pre-war development of the Tokyo Stock Exchange (TSE), and examines why the development was rather stagnant during the first 40 years and what led to its take-off in the late 1910s. The key to our explanation is the externality in listing shares: one firm’s decision to list on a stock exchange increases the attractiveness of the stock exchange to other firms by increasing the liquidity of the market. Such an externality suggests the possibility of multiple equilibria. The paper argues that a small change in the TSE’s listing policy in 1918 shifted the equilibrium from one with low number of listings and low liquidity to another one with high number of listings and high liquidity. The paper provides suggestive evidence from listing behavior of cotton spinning firms that shows the size of the market indeed mattered for their listing decision before 1918. The paper was prepared for the 18th Annual East Asian Seminar on Economics. We thank

Yasushi Hamao; Takeo Hoshi; Tetsuji Okazaki; Takatoshi Ito; Andrew Rose; Youngjae Lim; Masaya Sakuragawa

2007-01-01T23:59:59.000Z

410

Total...................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

15.2 15.2 7.8 1.0 1.2 3.3 1.9 For Two Housing Units............................. 0.9 Q N Q 0.6 N Heat Pump.................................................. 9.2 7.4 0.3 Q 0.7 0.5 Portable Electric Heater............................... 1.6 0.8 Q Q Q 0.3 Other Equipment......................................... 1.9 0.7 Q Q 0.7 Q Fuel Oil........................................................... 7.7 5.5 0.4 0.8 0.9 0.2 Steam or Hot Water System........................ 4.7 2.9 Q 0.7 0.8 N For One Housing Unit.............................. 3.3 2.9 Q Q Q N For Two Housing Units............................. 1.4 Q Q 0.5 0.8 N Central Warm-Air Furnace........................... 2.8 2.4 Q Q Q 0.2 Other Equipment......................................... 0.3 0.2 Q N Q N Wood..............................................................

411

Total...............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Do Not Have Cooling Equipment................. Do Not Have Cooling Equipment................. 17.8 5.3 4.7 2.8 1.9 3.1 3.6 7.5 Have Cooling Equipment.............................. 93.3 21.5 24.1 17.8 11.2 18.8 13.0 31.1 Use Cooling Equipment............................... 91.4 21.0 23.5 17.4 11.0 18.6 12.6 30.3 Have Equipment But Do Not Use it............. 1.9 0.5 0.6 0.4 Q Q 0.5 0.8 Air-Conditioning Equipment 1, 2 Central System............................................ 65.9 11.0 16.5 13.5 8.7 16.1 6.4 17.2 Without a Heat Pump.............................. 53.5 9.4 13.6 10.7 7.1 12.7 5.4 14.5 With a Heat Pump................................... 12.3 1.7 2.8 2.8 1.6 3.4 1.0 2.7 Window/Wall Units...................................... 28.9 10.5 8.1 4.5 2.7 3.1 6.7 14.1 1 Unit....................................................... 14.5 5.8 4.3 2.0 1.1 1.3 3.4 7.4 2 Units.....................................................

412

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.4 1.0 0.4 2 Times A Day...................................................... 24.6 5.8 3.5 2.3 Once a Day........................................................... 42.3 10.7 7.8 2.9 A Few Times Each Week...................................... 27.2 5.6 4.0 1.6 About Once a Week.............................................. 3.9 0.9 0.6 0.3 Less Than Once a Week....................................... 4.1 1.1 0.7 0.4 No Hot Meals Cooked........................................... 0.9 Q Q N Conventional Oven Use an Oven......................................................... 109.6 25.3 17.6 7.7 More Than Once a Day..................................... 8.9 1.3 0.8 0.5 Once a Day.......................................................

413

Total................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Do Not Have Space Heating Equipment....... 1.2 0.5 0.3 0.2 Q 0.2 0.3 0.6 Have Main Space Heating Equipment.......... 109.8 26.2 28.5 20.4 13.0 21.8 16.3 37.9 Use Main Space Heating Equipment............ 109.1 25.9 28.1 20.3 12.9 21.8 16.0 37.3 Have Equipment But Do Not Use It.............. 0.8 0.3 0.3 Q Q N 0.4 0.6 Main Heating Fuel and Equipment Natural Gas.................................................. 58.2 12.2 14.4 11.3 7.1 13.2 7.6 18.3 Central Warm-Air Furnace........................ 44.7 7.5 10.8 9.3 5.6 11.4 4.6 12.0 For One Housing Unit........................... 42.9 6.9 10.3 9.1 5.4 11.3 4.1 11.0 For Two Housing Units......................... 1.8 0.6 0.6 Q Q Q 0.4 0.9 Steam or Hot Water System..................... 8.2 2.4 2.5 1.0 1.0 1.3 1.5 3.6 For One Housing Unit...........................

414

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

25.6 25.6 40.7 24.2 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.7 Have Main Space Heating Equipment.................. 109.8 20.5 25.6 40.3 23.4 Use Main Space Heating Equipment.................... 109.1 20.5 25.6 40.1 22.9 Have Equipment But Do Not Use It...................... 0.8 N N Q 0.6 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 18.4 13.6 14.7 Central Warm-Air Furnace................................ 44.7 6.1 16.2 11.0 11.4 For One Housing Unit................................... 42.9 5.6 15.5 10.7 11.1 For Two Housing Units................................. 1.8 0.5 0.7 Q 0.3 Steam or Hot Water System............................. 8.2 4.9 1.6 1.0 0.6 For One Housing Unit................................... 5.1 3.2 1.1 0.4

415

Total...........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.6 0.6 15.1 5.5 Do Not Have Cooling Equipment............................. 17.8 4.0 2.4 1.7 Have Cooling Equipment.......................................... 93.3 16.5 12.8 3.8 Use Cooling Equipment........................................... 91.4 16.3 12.6 3.7 Have Equipment But Do Not Use it.......................... 1.9 0.3 Q Q Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 6.0 5.2 0.8 Without a Heat Pump........................................... 53.5 5.5 4.8 0.7 With a Heat Pump............................................... 12.3 0.5 0.4 Q Window/Wall Units.................................................. 28.9 10.7 7.6 3.1 1 Unit................................................................... 14.5 4.3 2.9 1.4 2 Units.................................................................

416

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 19.0 22.7 22.3 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.2 Q Have Main Space Heating Equipment.................. 109.8 46.3 18.9 22.5 22.1 Use Main Space Heating Equipment.................... 109.1 45.6 18.8 22.5 22.1 Have Equipment But Do Not Use It...................... 0.8 0.7 Q N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 27.0 11.9 14.9 4.3 Central Warm-Air Furnace................................ 44.7 19.8 8.6 12.8 3.6 For One Housing Unit................................... 42.9 18.8 8.3 12.3 3.5 For Two Housing Units................................. 1.8 1.0 0.3 0.4 Q Steam or Hot Water System............................. 8.2 4.4 2.1 1.4 0.3 For One Housing Unit................................... 5.1 2.1 1.6 1.0

417

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

15.1 15.1 5.5 Do Not Have Space Heating Equipment............... 1.2 Q Q Q Have Main Space Heating Equipment.................. 109.8 20.5 15.1 5.4 Use Main Space Heating Equipment.................... 109.1 20.5 15.1 5.4 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 11.4 9.1 2.3 Central Warm-Air Furnace................................ 44.7 6.1 5.3 0.8 For One Housing Unit................................... 42.9 5.6 4.9 0.7 For Two Housing Units................................. 1.8 0.5 0.4 Q Steam or Hot Water System............................. 8.2 4.9 3.6 1.3 For One Housing Unit................................... 5.1 3.2 2.2 1.0 For Two Housing Units.................................

418

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 1.2 1.0 0.2 2 Times A Day...................................................... 24.6 4.0 2.7 1.2 Once a Day........................................................... 42.3 7.9 5.4 2.5 A Few Times Each Week...................................... 27.2 6.0 4.8 1.2 About Once a Week.............................................. 3.9 0.6 0.5 Q Less Than Once a Week....................................... 4.1 0.6 0.4 Q No Hot Meals Cooked........................................... 0.9 0.3 Q Q Conventional Oven Use an Oven......................................................... 109.6 20.3 14.9 5.4 More Than Once a Day..................................... 8.9 1.4 1.2 0.3 Once a Day.......................................................

419

Total........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 24.5 1,090 902 341 872 780 441 Census Region and Division Northeast............................................. 20.6 6.7 1,247 1,032 Q 811 788 147 New England.................................... 5.5 1.9 1,365 1,127 Q 814 748 107 Middle Atlantic.................................. 15.1 4.8 1,182 978 Q 810 800 159 Midwest................................................ 25.6 4.6 1,349 1,133 506 895 810 346 East North Central............................ 17.7 3.2 1,483 1,239 560 968 842 351 West North Central........................... 7.9 1.4 913 789 329 751 745 337 South................................................... 40.7 7.8 881 752 572 942 873 797 South Atlantic................................... 21.7 4.9 875 707 522 1,035 934 926 East South Central........................... 6.9 0.7 Q Q Q 852 826 432 West South Central..........................

420

Total.................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

26.7 26.7 28.8 20.6 13.1 22.0 16.6 38.6 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day.............................. 8.2 2.9 2.5 1.3 0.5 1.0 2.4 4.6 2 Times A Day........................................... 24.6 6.5 7.0 4.3 3.2 3.6 4.8 10.3 Once a Day................................................ 42.3 8.8 9.8 8.7 5.1 10.0 5.0 12.9 A Few Times Each Week........................... 27.2 5.6 7.2 4.7 3.3 6.3 3.2 7.5 About Once a Week................................... 3.9 1.1 1.1 0.6 0.5 0.6 0.4 1.4 Less Than Once a Week............................ 4.1 1.3 1.0 0.9 0.5 0.4 0.7 1.4 No Hot Meals Cooked................................ 0.9 0.5 Q Q Q Q 0.2 0.5 Conventional Oven Use an Oven.............................................. 109.6 26.1 28.5 20.2 12.9 21.8 16.3 37.8 More Than Once a Day..........................

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Total..............................................  

U.S. Energy Information Administration (EIA) Indexed Site

111.1 86.6 2,720 1,970 1,310 1,941 1,475 821 1,059 944 554 Census Region and Division Northeast.................................... 20.6 13.9 3,224 2,173 836 2,219 1,619 583 903 830 Q New England.......................... 5.5 3.6 3,365 2,154 313 2,634 1,826 Q 951 940 Q Middle Atlantic........................ 15.1 10.3 3,167 2,181 1,049 2,188 1,603 582 Q Q Q Midwest...................................... 25.6 21.0 2,823 2,239 1,624 2,356 1,669 1,336 1,081 961 778 East North Central.................. 17.7 14.5 2,864 2,217 1,490 2,514 1,715 1,408 907 839 553 West North Central................. 7.9 6.4 2,729 2,289 1,924 1,806 1,510 1,085 1,299 1,113 1,059 South.......................................... 40.7 33.0 2,707 1,849 1,563 1,605 1,350 954 1,064 970 685 South Atlantic......................... 21.7 16.8 2,945 1,996 1,695 1,573 1,359 909 1,044 955

422

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Do Not Have Space Heating Equipment............... 1.2 0.7 Q 0.7 Have Main Space Heating Equipment.................. 109.8 23.4 7.5 16.0 Use Main Space Heating Equipment.................... 109.1 22.9 7.4 15.4 Have Equipment But Do Not Use It...................... 0.8 0.6 Q 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 14.7 4.6 10.1 Central Warm-Air Furnace................................ 44.7 11.4 4.0 7.4 For One Housing Unit................................... 42.9 11.1 3.8 7.3 For Two Housing Units................................. 1.8 0.3 Q Q Steam or Hot Water System............................. 8.2 0.6 0.3 0.3 For One Housing Unit................................... 5.1 0.4 0.2 0.1 For Two Housing Units.................................

423

Total.................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

49.2 49.2 15.1 15.6 11.1 7.0 5.2 8.0 Have Cooling Equipment............................... 93.3 31.3 15.1 15.6 11.1 7.0 5.2 8.0 Use Cooling Equipment................................ 91.4 30.4 14.6 15.4 11.1 6.9 5.2 7.9 Have Equipment But Do Not Use it............... 1.9 1.0 0.5 Q Q Q Q Q Do Not Have Cooling Equipment................... 17.8 17.8 N N N N N N Air-Conditioning Equipment 1, 2 Central System............................................. 65.9 3.9 15.1 15.6 11.1 7.0 5.2 8.0 Without a Heat Pump................................ 53.5 3.5 12.9 12.7 8.6 5.5 4.2 6.2 With a Heat Pump..................................... 12.3 0.4 2.2 2.9 2.5 1.5 1.0 1.8 Window/Wall Units........................................ 28.9 27.5 0.5 Q 0.3 Q Q Q 1 Unit......................................................... 14.5 13.5 0.3 Q Q Q N Q 2 Units.......................................................

424

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

7.1 7.1 7.0 8.0 12.1 Do Not Have Space Heating Equipment............... 1.2 Q Q Q 0.2 Have Main Space Heating Equipment.................. 109.8 7.1 6.8 7.9 11.9 Use Main Space Heating Equipment.................... 109.1 7.1 6.6 7.9 11.4 Have Equipment But Do Not Use It...................... 0.8 N Q N 0.5 Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 3.8 0.4 3.8 8.4 Central Warm-Air Furnace................................ 44.7 1.8 Q 3.1 6.0 For One Housing Unit................................... 42.9 1.5 Q 3.1 6.0 For Two Housing Units................................. 1.8 Q N Q Q Steam or Hot Water System............................. 8.2 1.9 Q Q 0.2 For One Housing Unit................................... 5.1 0.8 Q N Q For Two Housing Units.................................

425

Total........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

5.6 5.6 17.7 7.9 Do Not Have Space Heating Equipment............... 1.2 Q Q N Have Main Space Heating Equipment.................. 109.8 25.6 17.7 7.9 Use Main Space Heating Equipment.................... 109.1 25.6 17.7 7.9 Have Equipment But Do Not Use It...................... 0.8 N N N Main Heating Fuel and Equipment Natural Gas.......................................................... 58.2 18.4 13.1 5.3 Central Warm-Air Furnace................................ 44.7 16.2 11.6 4.7 For One Housing Unit................................... 42.9 15.5 11.0 4.5 For Two Housing Units................................. 1.8 0.7 0.6 Q Steam or Hot Water System............................. 8.2 1.6 1.2 0.4 For One Housing Unit................................... 5.1 1.1 0.9 Q For Two Housing Units.................................

426

Total...........................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

4.2 4.2 7.6 16.6 Do Not Have Cooling Equipment............................. 17.8 10.3 3.1 7.3 Have Cooling Equipment.......................................... 93.3 13.9 4.5 9.4 Use Cooling Equipment........................................... 91.4 12.9 4.3 8.5 Have Equipment But Do Not Use it.......................... 1.9 1.0 Q 0.8 Air-Conditioning Equipment 1, 2 Central System........................................................ 65.9 10.5 3.9 6.5 Without a Heat Pump........................................... 53.5 8.7 3.2 5.5 With a Heat Pump............................................... 12.3 1.7 0.7 1.0 Window/Wall Units.................................................. 28.9 3.6 0.6 3.0 1 Unit................................................................... 14.5 2.9 0.5 2.4 2 Units.................................................................

427

Total..............................................................  

U.S. Energy Information Administration (EIA) Indexed Site

,171 ,171 1,618 1,031 845 630 401 Census Region and Division Northeast................................................... 20.6 2,334 1,664 562 911 649 220 New England.......................................... 5.5 2,472 1,680 265 1,057 719 113 Middle Atlantic........................................ 15.1 2,284 1,658 670 864 627 254 Midwest...................................................... 25.6 2,421 1,927 1,360 981 781 551 East North Central.................................. 17.7 2,483 1,926 1,269 999 775 510 West North Central................................. 7.9 2,281 1,930 1,566 940 796 646 South.......................................................... 40.7 2,161 1,551 1,295 856 615 513 South Atlantic......................................... 21.7 2,243 1,607 1,359 896 642 543 East South Central.................................

428

Total.............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day......................................... 8.2 2.6 0.7 1.9 2 Times A Day...................................................... 24.6 6.6 2.0 4.6 Once a Day........................................................... 42.3 8.8 2.9 5.8 A Few Times Each Week...................................... 27.2 4.7 1.5 3.1 About Once a Week.............................................. 3.9 0.7 Q 0.6 Less Than Once a Week....................................... 4.1 0.7 0.3 0.4 No Hot Meals Cooked........................................... 0.9 0.2 Q Q Conventional Oven Use an Oven......................................................... 109.6 23.7 7.5 16.2 More Than Once a Day..................................... 8.9 1.7 0.4 1.3 Once a Day.......................................................

429

Total..............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

0.7 0.7 21.7 6.9 12.1 Do Not Have Cooling Equipment................................ 17.8 1.4 0.8 0.2 0.3 Have Cooling Equipment............................................. 93.3 39.3 20.9 6.7 11.8 Use Cooling Equipment.............................................. 91.4 38.9 20.7 6.6 11.7 Have Equipment But Do Not Use it............................. 1.9 0.5 Q Q Q Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 32.1 17.6 5.2 9.3 Without a Heat Pump.............................................. 53.5 23.2 10.9 3.8 8.4 With a Heat Pump................................................... 12.3 9.0 6.7 1.4 0.9 Window/Wall Units..................................................... 28.9 8.0 3.4 1.7 2.9 1 Unit......................................................................

430

Total....................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

14.7 14.7 7.4 12.5 12.5 18.9 18.6 17.3 9.2 Household Size 1 Person.......................................................... 30.0 4.6 2.5 3.7 3.2 5.4 5.5 3.7 1.6 2 Persons......................................................... 34.8 4.3 1.9 4.4 4.1 5.9 5.3 5.5 3.4 3 Persons......................................................... 18.4 2.5 1.3 1.7 1.9 2.9 3.5 2.8 1.6 4 Persons......................................................... 15.9 1.9 0.8 1.5 1.6 3.0 2.5 3.1 1.4 5 Persons......................................................... 7.9 0.8 0.4 1.0 1.1 1.2 1.1 1.5 0.9 6 or More Persons........................................... 4.1 0.5 0.3 0.3 0.6 0.5 0.7 0.8 0.4 2005 Annual Household Income Category Less than $9,999............................................. 9.9 1.9 1.1 1.3 0.9 1.7 1.3 1.1 0.5 $10,000 to $14,999..........................................

431

Total....................................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Cooking Appliances Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 3.7 1.6 1.4 1.5 2 Times A Day.............................................................. 24.6 10.8 4.1 4.3 5.5 Once a Day................................................................... 42.3 17.0 7.2 8.7 9.3 A Few Times Each Week............................................. 27.2 11.4 4.7 6.4 4.8 About Once a Week..................................................... 3.9 1.7 0.6 0.9 0.8 Less Than Once a Week.............................................. 4.1 2.2 0.6 0.8 0.5 No Hot Meals Cooked................................................... 0.9 0.4 Q Q Q Conventional Oven Use an Oven................................................................. 109.6 46.2 18.8

432

Total..............................................................................  

U.S. Energy Information Administration (EIA) Indexed Site

20.6 20.6 25.6 40.7 24.2 Do Not Have Cooling Equipment................................ 17.8 4.0 2.1 1.4 10.3 Have Cooling Equipment............................................. 93.3 16.5 23.5 39.3 13.9 Use Cooling Equipment.............................................. 91.4 16.3 23.4 38.9 12.9 Have Equipment But Do Not Use it............................. 1.9 0.3 Q 0.5 1.0 Air-Conditioning Equipment 1, 2 Central System........................................................... 65.9 6.0 17.3 32.1 10.5 Without a Heat Pump.............................................. 53.5 5.5 16.2 23.2 8.7 With a Heat Pump................................................... 12.3 0.5 1.1 9.0 1.7 Window/Wall Units..................................................... 28.9 10.7 6.6 8.0 3.6 1 Unit......................................................................

433

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

60,000 to 79,999 80,000 or More Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

434

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

Usage Indicators by U.S. Census Region, 2005 Million U.S. Housing Units Air Conditioning Usage Indicators U.S. Census Region Northeast Midwest South West Energy Information...

435

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC3.7...

436

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Homes Million U.S. Housing Units Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC4.7...

437

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

Self-Reported) City Town Suburbs Rural Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC8.7...

438

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

East North Central West North Central Energy Information Administration: 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Million U.S. Housing...

439

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Housing Units Home Electronics Usage Indicators Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005 Housing Units (millions) Energy Information...

440

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Housing Units Home Electronics Usage Indicators Table HC8.12 Home Electronics Usage Indicators by UrbanRural Location, 2005 Housing Units (millions) Energy Information...

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

7.0 7.7 6.6 Have Equipment But Do Not Use it... 1.9 Q N Q 0.6 Air-Conditioning Equipment 1, 2 Central System......

442

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

Air-Conditioning Equipment 1, 2 Central System... 65.9 47.5 4.0 2.8 7.9 3.7 Without a Heat Pump... 53.5...

443

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

91.4 23.4 15.9 7.5 Have Equipment But Do Not Use it... 1.9 Q Q Q Air-Conditioning Equipment 1, 2 Central System......

444

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

18.0 Have Equipment But Do Not Use it... 1.9 0.9 0.3 0.3 0.4 Air-Conditioning Equipment 1, 2 Central System......

445

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

m... 3.2 0.2 Q 0.1 Telephone and Office Equipment CellMobile Telephone... 84.8 14.9 11.1 3.9 Cordless...

446

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

m... 3.2 0.9 0.7 Q Telephone and Office Equipment CellMobile Telephone... 84.8 19.3 13.2 6.1 Cordless...

447

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Q 0.5 Q Q Monitor is Turned Off... 0.5 N Q Q Q Q N Q Use of Internet Have Access to Internet Yes... 66.9...

448

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Four Most Populated States New York Florida Texas California Million U.S. Housing Units Home Electronics Usage Indicators Table HC15.12 Home Electronics Usage Indicators by Four...

449

Total  

U.S. Energy Information Administration (EIA) Indexed Site

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

450

Total  

U.S. Energy Information Administration (EIA) Indexed Site

Normal ButaneButylene Other Liquids Oxygenates Fuel Ethanol MTBE Other Oxygenates Biomass-based Diesel Fuel Other Renewable Diesel Fuel Other Renewable Fuels Gasoline Blending...

451

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

111.1 7.1 7.0 8.0 12.1 Personal Computers Do Not Use a Personal Computer ... 35.5 3.0 2.0 2.7 3.1 Use a Personal Computer......

452

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

... 25.8 2.8 5.8 5.5 3.8 7.9 1.4 5.1 Use of Most-Used Ceiling Fan Used All Summer... 18.7 4.2 4.9 4.1 2.1 3.4 2.4 6.3...

453

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

Heating Characteristics Energy Information Administration 2005 Residential Energy Consumption Survey: Preliminary Housing Characteristics Tables Table HC5.4 Space Heating...

454

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

at All... 2.9 1.1 0.5 Q 0.4 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools......

455

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

3.3 Not Used at All... 2.9 0.7 0.5 Q Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

456

Total..........................................................  

U.S. Energy Information Administration (EIA) Indexed Site

3.6 Not Used at All... 2.9 0.8 0.3 0.4 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

457

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

1.1 Not Used at All... 2.9 0.4 Q 0.2 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools... 54.9...

458

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

at All... 2.9 1.4 0.4 0.4 0.7 Battery-Operated AppliancesTools Use Battery-Operated AppliancesTools......

459

Total..........................................................  

Gasoline and Diesel Fuel Update (EIA)

5 or More Units Mobile Homes Apartments in Buildings With-- Housing Units (millions) At Home Behavior Home Used for Business Yes......

460

Total..........................................................  

Annual Energy Outlook 2012 (EIA)

... 34.3 1.2 0.9 2.2 2.9 5.4 7.0 8.2 6.6 Adequacy of Insulation Well Insulated... 29.5 1.5 0.9 2.3 2.7 4.1...

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461

Geology of the Source Physics Experiment Site, Climax Stock, Nevada National Security Site  

SciTech Connect

A test bed for a series of chemical explosives tests known as Source Physics Experiments (SPE) was constructed in granitic rock of the Climax stock, in northern Yucca Flat at the Nevada National Security Site in 2010-2011. These tests are sponsored by the U.S. Department of Energy, National Nuclear Security Administration's National Center for Nuclear Security. The test series is designed to study the generation and propagation of seismic waves, and will provide data that will improve the predictive capability of calculational models for detecting and characterizing underground explosions. Abundant geologic data are available for the area, primarily as a result of studies performed in conjunction with the three underground nuclear tests conducted in the Climax granite in the 1960s and a few later studies of various types. The SPE test bed was constructed at an elevation of approximately 1,524 meters (m), and consists of a 91.4-centimeter (cm) diameter source hole at its center, surrounded by two rings of three 20.3-cm diameter instrument holes. The inner ring of holes is positioned 10 m away from the source hole, and the outer ring of holes is positioned 20 m from the source hole. An initial 160-m deep core hole was drilled at the location of the source hole that provided information on the geology of the site and rock samples for later laboratory testing. A suite of geophysical logs was run in the core hole and all six instruments holes to obtain matrix and fracture properties. Detailed information on the character and density of fractures encountered was obtained from the borehole image logs run in the holes. A total of 2,488 fractures were identified in the seven boreholes, and these were ranked into six categories (0 through 5) on the basis of their degree of openness and continuity. The analysis presented here considered only the higher-ranked fractures (ranks 2 through 5), of which there were 1,215 (approximately 49 percent of all fractures identified from borehole image logs). The fractures were grouped into sets based on their orientation. The most ubiquitous fracture set (50 percent of all higher-ranked fractures) is a group of low-angle fractures (dips 0 to 30 degrees). Fractures with dips of 60 to 90 degrees account for 38 percent of high-ranked fractures, and the remaining 12 percent are fractures with moderate dips (30 to 60 degrees). The higher-angle fractures are further subdivided into three sets based on their dip direction: fractures of Set 1 dip to the north-northeast, fractures of Set 2 dip to the south-southwest, and Set 3 consists of high-angle fractures that dip to the southeast and strike northeast. The low-angle fractures (Set 4) dip eastward. Fracture frequency does not appear to change substantially with depth. True fracture spacing averages 0.9 to 1.2 m for high-angle Sets 1, 2, and 3, and 0.6 m for Set 4. Two significant faults were observed in the core, centered at the depths of 25.3 and 32.3 m. The upper of these two faults dips 80 degrees to the north-northeast and, thus, is related to the Set-1 fractures. The lower fault dips 79 degrees to the south-southwest and is related to SPE Set-2 fractures. Neither fault has an identifiable surface trace. Groundwater was encountered in all holes drilled on the SPE test bed, and the fluid level averaged about 15.2 to 18.3 m below ground surface. An informal study of variations in the fluid level in the holes conducted during various phases of construction of the test bed concluded that groundwater flow through the fractured granitic rocks is not uniform, and appears to be controlled by variations in the orientation and degree of interconnectedness of the fractures. It may also be possible that an aplite dike or quartz vein may be present in the test bed, which could act as a barrier to groundwater flow and, thus, could account for anisotropy seen in the groundwater recovery measurements.

Townsend, M., Prothro, L. B., Obi, C.

2012-03-15T23:59:59.000Z

462

Property:TotalValue | Open Energy Information  

Open Energy Info (EERE)

TotalValue TotalValue Jump to: navigation, search This is a property of type Number. Pages using the property "TotalValue" Showing 25 pages using this property. (previous 25) (next 25) 4 44 Tech Inc. Smart Grid Demonstration Project + 10,000,000 + A ALLETE Inc., d/b/a Minnesota Power Smart Grid Project + 3,088,007 + Amber Kinetics, Inc. Smart Grid Demonstration Project + 10,000,000 + American Transmission Company LLC II Smart Grid Project + 22,888,360 + American Transmission Company LLC Smart Grid Project + 2,661,650 + Atlantic City Electric Company Smart Grid Project + 37,400,000 + Avista Utilities Smart Grid Project + 40,000,000 + B Baltimore Gas and Electric Company Smart Grid Project + 451,814,234 + Battelle Memorial Institute, Pacific Northwest Division Smart Grid Demonstration Project + 177,642,503 +

463

Idle Operating Total Stream Day  

U.S. Energy Information Administration (EIA) Indexed Site

3 3 Idle Operating Total Stream Day Barrels per Idle Operating Total Calendar Day Barrels per Atmospheric Crude Oil Distillation Capacity Idle Operating Total Operable Refineries Number of State and PAD District a b b 11 10 1 1,293,200 1,265,200 28,000 1,361,700 1,329,700 32,000 ............................................................................................................................................... PAD District I 1 1 0 182,200 182,200 0 190,200 190,200 0 ................................................................................................................................................................................................................................................................................................ Delaware......................................

464

Lake Roosevelt Fisheries Evaluation Program; Meadow Creek vs. Lake Whatcom Stock Kokanee Salmon Investigations in Lake Roosevelt, Annual Report 2002.  

DOE Green Energy (OSTI)

Lake Whatcom, Washington kokanee have been stocked in Lake Roosevelt since 1987 with the primary objective of creating a self-sustaining fishery. Success has been limited by low recruitment to the fishery, low adult returns to hatcheries, and a skewed sex ratio. It was hypothesized that a stock native to the upper Columbia River might perform better than the coastal Lake Whatcom stock. Kokanee from Meadow Creek, a tributary of Kootenay Lake, British Columbia were selected as an alternative stock. Post smolts from each stock were released from Sherman Creek Hatchery in late June 2000 and repeated in 2001. Stock performance was evaluated using three measures; (1) number of returns to Sherman Creek, the primary egg collection facility, (2) the number of returns to 86 tributaries sampled and, (3) the number of returns to the creel. In two repeated experiments, neither Meadow Creek or Lake Whatcom kokanee appeared to be capable of providing a run of three-year old spawners to sustain stocking efforts. Less than 10 three-years olds from either stock were collected during the study period. Chi-square analysis indicated age two Meadow Creek kokanee returned to Sherman Creek and to other tributaries in significantly higher numbers when compared to the Lake Whatcom stock in both 2000 and 2001. However, preliminary data from the Spokane Tribe of Indians indicated that a large number of both stocks were precocial before they were stocked. The small number of hatchery three-year olds collected indicated that the current hatchery rearing and stocking methods will continue to produce a limited jacking run largely composed of precocious males and a small number of three-year olds. No kokanee from the study were collected during standard lake wide creel surveys. Supplemental creel data, including fishing derbies, test fisheries, and angler diaries, indicated anglers harvested two-year-old hatchery kokanee a month after release. The majority of the two-year old kokanee harvested were from a direct stock at the Fort Spokane boat launch. Only Lake Whatcom kokanee were stocked from the boat launch, therefore stock performance was not evaluated, however the high success of the stocking location will likely increase harvest of hatchery kokanee in the future. Despite low numbers of the targeted three-year olds, Meadow Creek kokanee should be stocked when possible to promote fish native to the upper Columbia River.

McLellan, Holly

2003-03-01T23:59:59.000Z

465

China Total Cloud Amount Trends  

NLE Websites -- All DOE Office Websites (Extended Search)

Trends in Total Cloud Amount Over China DOI: 10.3334CDIACcli.008 data Data image Graphics Investigator Dale P. Kaiser Carbon Dioxide Information Analysis Center, Environmental...

466

PADD 2 Stocks of Crude Oil and Petroleum Products  

U.S. Energy Information Administration (EIA)

History; Total Crude Oil and Petroleum Products (Incl. SPR) 279,627: 277,974: 280,607: 273,702: 274,961: 280,571: 1981-2013: Crude Oil (Including SPR) 117,512:

467

Cutting Stock with Bounded Open Stacks: a New Integer Linear ...  

E-Print Network (OSTI)

requirement: this number is called the pattern run length. In practice, to ..... number of distinct part types produced at any time (open stacks) does not exceed a.

468

Improving Robust Rolling Stock Circulation in Rapid Transit Networks  

E-Print Network (OSTI)

Aug 31, 2011 ... to undergo different types of maintenance checks and robustness ... of train services' RS assignment, empty trains, the optimal management of.

469

Stocks and Flows of U and Pu in a World with 3.6 TWe of Nuclear Power  

Science Conference Proceedings (OSTI)

Integrated energy, environment, and economics models project that worldwide electrical energy use will increase to ?12 TWe in 2100 and nuclear power may be required to provide 3.6 TWe at this time. If pulverized coal without carbon sequestration were employed instead, the resulting incremental long-term global temperature rise would be about 2/3 deg C. Calculations are presented of the stocks and flows of uranium and plutonium associated with the scenario where this energy is provided by nuclear power. If only light-water reactors (LWRs) are used, the scenario consumes about 33.4 Mt of mined uranium. Continuing to operate the reactors in place in 2100 through the end of their assumed 60 year lifetime raises this to 59 Mt, 4.7x the NEA/ IAEA Redbook estimate for total discovered + undiscovered uranium. The waste corresponds to about 86x the legally defined capacity of Yucca Mtn. A case is also considered where a transition is begun to fast-spectrum reactors in 2040, both for a “balanced” system of LWRs and transuranic (TRU) burners with conversion ration (CR) = 0.5, and for a system of breeders. In the latter case we find that CR = 1.21 is adequate to replace all LWRs with breeders by 2100, using solely TRU from LWRs to start up the reactors – assuming reprocessed fuel is available for use two years after its removal from the reactor. The stock of plutonium circulating in the fast reactor system in 2100 is comparable to that which would have been buried in the LWR-only case. One year of fueling corresponds to 2,000 – 6,000t of Pu. Fusion energy, if first brought on line in mid-century, could in principle replace fast reactors in this scenario.

Robert J. Goldston

2012-08-10T23:59:59.000Z

470

On the shortterm influence of oil price changes on stock markets in GCC countries: linear and nonlinear analyses  

E-Print Network (OSTI)

This paper examines the short-run relationships between oil prices and GCC stock markets. Since GCC countries are major world energy market players, their stock markets may be susceptible to oil price shocks. To account for the fact that stock markets may respond nonlinearly to oil price shocks, we have examined both linear and nonlinear relationships. Our findings show that there are significant links between the two variables in Qatar, Oman, and UAE. Thus, stock markets in these countries react positively to oil price

Mohamed El; Hedi Arouri; Julien Fouquau

2009-01-01T23:59:59.000Z

471

Total Energy Facilities Biomass Facility | Open Energy Information  

Open Energy Info (EERE)

Total Energy Facilities Biomass Facility Total Energy Facilities Biomass Facility Jump to: navigation, search Name Total Energy Facilities Biomass Facility Facility Total Energy Facilities Sector Biomass Facility Type Non-Fossil Waste Location Los Angeles County, California Coordinates 34.3871821°, -118.1122679° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":34.3871821,"lon":-118.1122679,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

472

U.S. Total Exports  

Annual Energy Outlook 2012 (EIA)

Springs, VT U.S. Pipeline Total from Mexico Ogilby, CA Otay Mesa, CA Galvan Ranch, TX LNG Imports from Algeria LNG Imports from Australia LNG Imports from Brunei LNG Imports...

473

Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Banks |  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Banks Feds Feed Families Wraps Up Successful Campaign to Stock Area Food Banks August 1, 2012 - 12:00pm Addthis EM’s Nevada Site Office took first place in the site-submitted category of DOE’s CANstruction Sculpture Contest for its entry, shown here, inspired by London’s Tower Bridge during the 2012 Summer Olympics. EM's Nevada Site Office took first place in the site-submitted category of DOE's CANstruction Sculpture Contest for its entry, shown here, inspired by London's Tower Bridge during the 2012 Summer Olympics. EM Office of Strategic Planning and Analysis Director Barry Gaffney throws the ball that sends Senior Advisor for Environmental Management David Huizenga into the dunk tank during an event to collect nonperishable food items for the DOE Feeds Families campaign.

474

DOE Completes Sale of Northeast Home Heating Oil Stocks | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Completes Sale of Northeast Home Heating Oil Stocks Completes Sale of Northeast Home Heating Oil Stocks DOE Completes Sale of Northeast Home Heating Oil Stocks February 10, 2011 - 12:00pm Addthis Washington, DC - The U.S. Department of Energy (DOE) today has awarded contracts to four companies who successfully bid for the purchase of 1,000,000 barrels of heating oil from the Northeast Home Heating Oil Reserve storage sites in Groton and New Haven, CT. Hess Groton Terminal, Groton, CT Shell Trading U.S. Company 150,000 barrels Sprague Energy Corp. 100,000 barrels Magellan New Haven Terminal, New Haven, CT Hess Corporation 300,000 barrels Morgan Stanley 450,000 barrels Today's sale was the second held as part of the Department's initiative to convert the 1,984,253 barrel heating oil reserve to cleaner burning

475

Window-Related Energy Consumption in the US Residential and Commercial Building Stock  

NLE Websites -- All DOE Office Websites (Extended Search)

Window-Related Energy Consumption in the US Window-Related Energy Consumption in the US Residential and Commercial Building Stock Joshua Apte and Dariush Arasteh, Lawrence Berkeley National Laboratory LBNL-60146 Abstract We present a simple spreadsheet-based tool for estimating window-related energy consumption in the United States. Using available data on the properties of the installed US window stock, we estimate that windows are responsible for 2.15 quadrillion Btu (Quads) of heating energy consumption and 1.48 Quads of cooling energy consumption annually. We develop estimates of average U-factor and SHGC for current window sales. We estimate that a complete replacement of the installed window stock with these products would result in energy savings of approximately 1.2 quads. We demonstrate

476

Coherence-based multivariate analysis of high frequency stock market values  

E-Print Network (OSTI)

The paper tackles the problem of deriving a topological structure among stock prices from high frequency historical values. Similar studies using low frequency data have already provided valuable insights. However, in those cases data need to be collected for a longer period and then they have to be detrended. An effective technique based on averaging a metric function on short subperiods of the observation horizon is suggested. Since a standard correlation-based metric is not capable of catching dependencies at different time instants, it is not expected to perform the best when dealing with high frequency data. Hence, the choice of a more suitable metric is discussed. In particular, a coherence-based metric is proposed, for it is able to detect any possible linear relation between two times series, even at different time instants. The averaging technique is employed to analyze a set of 100 high volume stocks of the New York Stock Exchange, observed during March 2008.

Donatello Materassi; Giacomo Innocenti

2008-05-18T23:59:59.000Z

477

EM Rockets Past Target for Donations to Stock Food Banks | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Rockets Past Target for Donations to Stock Food Banks Rockets Past Target for Donations to Stock Food Banks EM Rockets Past Target for Donations to Stock Food Banks November 13, 2012 - 12:00pm Addthis EMCBC Director Jack Craig, left to right, EM Executive Assistant Jillian Carter, who is EM's Feds Feed Families representative, and Senior Advisor for Environmental Management David Huizenga pause for a photo Nov. 8. Craig holds the "Teamwork Award" he and his staff received. EMCBC Director Jack Craig, left to right, EM Executive Assistant Jillian Carter, who is EM's Feds Feed Families representative, and Senior Advisor for Environmental Management David Huizenga pause for a photo Nov. 8. Craig holds the "Teamwork Award" he and his staff received. Savannah River Site Acquisition Operations Division Director David Hepner donated more than 1,000 pounds of food to the campaign.

478

DOE Accepts Bids for Northeast Home Heating Oil Stocks | Department of  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Accepts Bids for Northeast Home Heating Oil Stocks Accepts Bids for Northeast Home Heating Oil Stocks DOE Accepts Bids for Northeast Home Heating Oil Stocks February 3, 2011 - 12:00pm Addthis Washington, DC - The U.S. Department of Energy (DOE) today has awarded contracts to three companies who successfully bid for the purchase of 984,253 barrels of heating oil from the Northeast Home Heating Oil Reserve. Awardee Amount Morgan Stanley 500,000 barrels Shell Trading U.S. Company 250,000 barrels George E. Warren Corporation 234,253 barrels Today's sale was the first held as part of the Department's initiative to convert the current 1,984,253-barrel heating oil reserve to cleaner burning ultra low sulfur distillate. Contracts for the heating oil will be executed upon final payment to DOE; final payment is required no later than

479

Distillate Stocks on the East Coast Were Very Low Entering Last Winter  

Gasoline and Diesel Fuel Update (EIA)

4 4 Notes: So, what happened last winter? At last year's SHOPP conference, my renowned colleague, Joanne Shore, warned of the potential for high prices. At this time last year, distillate stocks were very low. This graph shows East Coast inventories, which at the end of July 2000, were well below the normal band. We focus on the East Coast (PADD 1) because this is a region in which heating oil is a major winter fuel. Furthermore, the East Coast consumes almost 2/3 of the nation's heating oil (high sulfur distillate). East Coast stocks were well below normal last year from July through December, but then actually increased in January, when they typically decline. In fact, the increase was only the 2nd time East Coast distillate stocks have increased in January since EIA has kept PADD level data (1981)!

480

Annual Coded Wire Tag Program; Oregon Stock Assessment, 2000 Annual Report.  

DOE Green Energy (OSTI)

This annual report is in fulfillment of contract obligations with Bonneville Power Administration which is the funding source for the Oregon Department of Fish and Wildlife's Annual Stock Assessment - Coded Wire Tag Program (ODFW) Project. Tule stock fall chinook were caught primarily in British Columbia and Washington ocean, and Columbia Basin fisheries. Up-river bright stock fall chinook contributed primarily to Alaska and British Columbia ocean commercial, Columbia Basin gillnet and freshwater sport fisheries. Contribution of Rogue stock fall chinook released in the lower Columbia River occurred primarily in Oregon ocean commercial, Columbia Basin gillnet and freshwater sport fisheries. Willamette stock spring chinook contributed primarily to Alaska and British Columbia ocean, and Columbia Basin sport fisheries. Willamette stock spring chinook released by CEDC contributed to similar ocean fisheries, but had much higher catch in Columbia Basin gillnet fisheries than the same stocks released in the Willamette Basin. Up-river stocks of spring chinook contributed almost exclusively to Columbia Basin fisheries. The up-river stocks of Columbia River summer steelhead contributed almost exclusively to the Columbia Basin gillnet and freshwater sport fisheries. Coho ocean fisheries from Washington to California were closed or very limited from 1994 through 1999 (1991 through 1996 broods). This has resulted in a lower percent of catch in Washington, Oregon and California ocean fisheries, and a higher percent of catch in Alaska and British Columbia ocean and Columbia Basin freshwater fisheries. Coho stocks released by ODFW below Bonneville Dam were caught mainly in Oregon, Washington, and British Columbia ocean, Columbia Gillnet and freshwater sport fisheries. Coho stocks released in the Klaskanine River and Youngs Bay area had similar ocean catch distributions, but a much higher percent catch in gillnet fisheries than the other coho releases. Ocean catch distribution of coho stocks released above Bonneville Dam was similar to the other coho groups. However, they had a higher percent catch in gillnet fisheries above Bonneville Dam than coho released below the dam. Survival rates of salmon and steelhead are influenced, not only by factors in the hatchery (disease, density, diet, size and time of release) but also by environmental factors in the river and ocean. These environmental factors are influenced by large scale oceanic and weather patterns such as El Nino. Changes in rearing conditions in the hatchery do impact survival, however, these can be offset by impacts caused by environmental factors. Coho salmon released in the Columbia River generally experience better survival rates when released later in the spring. However, for the 1990 brood year June releases of Columbia River coho had much lower survival than May releases, for all ODFW hatcheries. In general survival of ODFW Columbia River hatchery coho has declined to low levels in recent years. Preliminary results from the evaluation of Visual Implant Elastomer (VIE) tags showed tagging rate and pre-release tag retention improved from the first to second years of tagging. Tagging rate remained identical from 1999 to 2000 while pre-release tag retention dropped to 95%. Returning jack and adult salmon were sampled for CWT and VIE tags in the fall of 2000. Of 606 adults recovered at Sandy Fish Hatchery in 2000, only 1 or 0.2%, retained their VIE tag. Of 36 jacks recovered in 2000, 13 or 36.1% retained their VIE tag.

Lewis, Mark; Mallette, Christine; Murray, William

2002-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "type total stocks" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Evidence of Increment of Efficiency of the Mexican Stock Market Through the Analysis of its Variations  

E-Print Network (OSTI)

It is well known that there exist statistical and structural differences between the stock markets of developed and emerging countries. In this work, we present an analysis of the variations and autocorrelations of the Mexican Stock Market index (IPC) for different periods of its historical daily data, showing evidence that the Mexican Stock Market has been increasing its efficiency in recent times. We have analyzed the returns autocorrelation function (ACF) and used detrended fluctuation analysis (DFA) methods. We also analyze the volatility of the IPC and the Dow Jones Industrial Average (DJIA) and compare their evolution. The data samples analyzed here, correspond to daily values of the IPC and DJIA for the period 10/30/1978 to 02/28/2006.

Coronel-Brizio, H F; Huerta-Quintanilla, R; Rodriguez-Achach, M

2006-01-01T23:59:59.000Z

482

Table A39. Total Expenditures for Purchased Electricity and Steam  

U.S. Energy Information Administration (EIA) Indexed Site

9. Total Expenditures for Purchased Electricity and Steam" 9. Total Expenditures for Purchased Electricity and Steam" " by Type of Supplier, Census Region, Census Division, and" " Economic Characteristics of the Establishment, 1994" " (Estimates in Million Dollars)" ," Electricity",," Steam" ,,,,,"RSE" ,"Utility","Nonutility","Utility","Nonutility","Row" "Economic Characteristics(a)","Supplier(b)","Supplier(c)","Supplier(b)","Supplier(c)","Factors" ,"Total United States" "RSE Column Factors:",0.3,2,1.6,1.2

483

The economics of controlling stock pollutants: An efficient strategy for greenhouse gases  

SciTech Connect

Optimal control theory is applied to develop an efficient strategy to control stock pollutants such as greenhouse gases and hazardous waste. The optimal strategy suggests that, at any time, the marginal costs of abatement should be equated with the present value of the marginal damage of timely unabated emission. The optimal strategy calls for increasingly tight abatement over time as the pollutant stock accumulates. The optimal policy applied to greenhouse gases suggest moderate abatement efforts, at present, with the potential for much greater future efforts. 15 refs., 2 tabs.

Falk, I. (Harvard Univ., Cambridge, MA (United States)); Mendelsohn, R. (Yale Univ., New Haven, CT (United States))

1993-07-01T23:59:59.000Z

484

Asymptotic Behavior of the Stock Price Distribution Density and Implied Volatility in Stochastic Volatility Models  

Science Conference Proceedings (OSTI)

We study the asymptotic behavior of distribution densities arising in stock price models with stochastic volatility. The main objects of our interest in the present paper are the density of time averages of the squared volatility process and the density of the stock price process in the Stein-Stein and the Heston model. We find explicit formulas for leading terms in asymptotic expansions of these densities and give error estimates. As an application of our results, sharp asymptotic formulas for the implied volatility in the Stein-Stein and the Heston model are obtained.

Gulisashvili, Archil, E-mail: guli@math.ohiou.ed [Ohio University, Department of Mathematics (United States); Stein, Elias M., E-mail: stein@math.princeton.ed [Princeton University, Department of Mathematics (United States)

2010-06-15T23:59:59.000Z

485

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

15,763,807 Contractor: 93,591,118 Fee Available Contract Period: Contract Type: URSCH2M Oak Ridge, LLC (UCOR) DE-SC-0004645 April 29, 2011 - July 13, 2016 Contract...

486

Total Estimated Contract Cost: Performance Period Total Fee Paid  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Fee 0 May 2011 - September 2015 June 2013 Contractor: Contract Number: Contract Type: Idaho Treatment Group LLC DE-EM0001467 Cost Plus Award Fee Fee Information 419,202,975...

487

A comparative study of artificial neural networks, and decision trees for digital game content stocks price prediction  

Science Conference Proceedings (OSTI)

Precise prediction of stock prices is difficult chiefly because of the many intervening factors. Unpredictability is particularly notable in the aftermath of the global financial crisis. Data mining may however be used to discover highly correlated estimation ... Keywords: Artificial neural networks (ANN), C&RT, Decision tree, Stock price forecasting

Tsung-Sheng Chang

2011-11-01T23:59:59.000Z

488

Data mining investigation of co-movements on the Taiwan and China stock markets for future investment portfolio  

Science Conference Proceedings (OSTI)

On June 29, 2010, Taiwan signed an Economic Cooperation Framework Agreement (ECFA) with China as a major step to open markets between Taiwan and China. Thus, the ECFA will contribute by creating a closer relationship between China and Taiwan through ... Keywords: Association rules, Cluster analysis, Co-movements, Cross-national stock market, Data mining, Stock market investment portfolio

Shu-Hsien Liao; Shan-Yuan Chou

2013-04-01T23:59:59.000Z

489

Optimal production and rationing policies of a make-to-stock production system with batch demand and backordering  

Science Conference Proceedings (OSTI)

In this paper, we consider the stock rationing problem of a single-item make-to-stock production/inventory system with multiple demand classes. Demand arrives as a Poisson process with a randomly distributed batch size. It is assumed that the batch demand ... Keywords: Batch demand, Inventory, Markov decision process, Production, Rationing

Jianjun Xu; Shaoxiang Chen; Bing Lin; Rohit Bhatnagar

2010-05-01T23:59:59.000Z

490

Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over the Last Decade  

E-Print Network (OSTI)

Oil Prices, Stock Markets and Portfolio Investment: Evidence from Sector Analysis in Europe over This article extends the understanding of oil­stock market relationships over the last turbulent decade. Unlike returns to oil price changes differ greatly depending on the activity sector. In the out

Paris-Sud XI, Université de

491

Dynamic-radius species-conserving genetic algorithm for the financial forecasting of dow jones index stocks  

Science Conference Proceedings (OSTI)

This research uses a Niche Genetic Algorithm (NGA) called Dynamic-radius Species-conserving Genetic Algorithm (DSGA) to select stocks to purchase from the Dow Jones Index. DSGA uses a set of training data to produce a set of rules. These rules are then ... Keywords: Niche genetic algorithm, black-box investing, classification, financial forecasting, genetic algorithm, stock forecasting

Michael Scott Brown, Michael J. Pelosi, Henry Dirska

2013-07-01T23:59:59.000Z

492

Expert Stock Picker: The Wisdom of (Experts in) Crowds  

Science Conference Proceedings (OSTI)

The phrase "the wisdom of crowds" suggests that good verdicts can be achieved by averaging the opinions and insights of large, diverse groups of people who possess varied types of information. Online user-generated content enables researchers to view ... Keywords: Data Mining, Prediction Markets, Social Media, User-Generated Content, Wisdom Of Crowds

Shawndra Hill; Noah Ready-Campbell

2011-04-01T23:59:59.000Z

493

Compact Totally Disconnected Moufang Buildings  

E-Print Network (OSTI)

Let $\\Delta$ be a spherical building each of whose irreducible components is infinite, has rank at least 2 and satisfies the Moufang condition. We show that $\\Delta$ can be given the structure of a topological building that is compact and totally disconnected precisely when $\\Delta$ is the building at infinity of a locally finite affine building.

Grundhofer, T; Van Maldeghem, H; Weiss, R M

2010-01-01T23:59:59.000Z

494

Total Imports of Residual Fuel  

Annual Energy Outlook 2012 (EIA)

2007 2008 2009 2010 2011 2012 View History U.S. Total 135,676 127,682 120,936 133,646 119,888 93,672 1936-2012 PAD District 1 78,197 73,348 69,886 88,999 79,188 59,594 1981-2012...

495

Total China Investment Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Total China Investment Co Ltd Total China Investment Co Ltd Jump to: navigation, search Name Total (China) Investment Co. Ltd. Place Beijing, China Zip 100004 Product Total has been present in China for about 30 years through its activities of Exploration & Production, Gas & Power, Refining & Marketing, and Chemicals. Coordinates 39.90601°, 116.387909° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.90601,"lon":116.387909,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

496

U.S. Normal Butane-Butylene Stocks in Pipelines (Thousand Barrels)  

U.S. Energy Information Administration (EIA)

U.S. Normal Butane-Butylene Stocks in Pipelines (Thousand Barrels) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec; 1993: 1,901: 1,455: 1,356: 1,810: 2,062 ...

497

Corporate Investment, Book-to-Market, Firm Size and Stock Returns: Empirical Evidence  

E-Print Network (OSTI)

We examine the empirical relations among firm-level investment growth, market value of equity, bookto-market ratio (B/M), and stock returns. Under the widely used Fama and French (FF) methods, firms classified as big and low-B/M (B/L) significantly accelerate investment prior to the classification year. Their market values of equity rise and their leverage levels diminish. Firms classified as small and high-B/M (S/H) reduce investment and increase leverage. In other words, FF classification methods implicitly assign firms to portfolios conditional on past investment growth. Berk, Green, and Naik (BGN, 1999) offer a model and simulations consistent with such patterns in firm-level fundamentals. BGN’s model also predicts that systematic risk and expected equity returns evolve dynamically with firm-level investment, and that firm fundamentals such as B/M and firm size proxy for investment-related changes in risk. Consistent with BGN, we find that average raw returns vary across portfolios of stocks formed on the basis of past investment growth. We find weakened evidence of a value premium after categorizing stocks by investment growth. Investment growth also has explanatory power in cross-sectional and timeseries regressions of stock returns and appears to provide information similar to that of B/M.

Christopher W. Anderson; Luis Garcia-Feijóo

2002-01-01T23:59:59.000Z

498

Setting Safety-Stock Targets at Intel in the Presence of Forecast Bias  

Science Conference Proceedings (OSTI)

Inventory target setting within Intel's embedded devices group historically consisted of management-determined inventory targets that were uniformly applied across product families. Achieving and maintaining these inventory targets at the individual ... Keywords: applications, computer/electronic, forecasting, industries, inventory/production, multiechelon safety-stock optimization

Matthew P. Manary; Sean P. Willems

2008-03-01T23:59:59.000Z

499

Associations Between Management Forecast Accuracy and Pricing of IPOs in Athens Stock  

E-Print Network (OSTI)

1 Associations Between Management Forecast Accuracy and Pricing of IPOs in Athens Stock Exchange Dimitrios Gounopoulos* University of Surrey, U.K. This study examines the earnings forecast accuracy earnings forecast and pricing ofIPOs. It uses a unique data set of 208 IPOs, which were floated during

Jensen, Max

500

Stock mechanics: predicting recession in S&P500, DJIA, and NASDAQ  

E-Print Network (OSTI)

An original method, assuming potential and kinetic energy for prices and conservation of their sum is developed for forecasting exchanges. Connections with power law are shown. Semiempirical applications on S&P500, DJIA, and NASDAQ predict a coming recession in them. An emerging market, Istanbul Stock Exchange index ISE-100 is found involving a potential to continue to rise.

Tuncay, C

2005-01-01T23:59:59.000Z