18 Search Results

Healthcare facilities (HCFs) in low- and middle-income countries frequently lack water, sanitation and hygiene (WASH) services that are adequate to implement infection prevention and control (IPC) practices, decrease healthcare-associated infections and antimicrobial resistance, and provide quality healthcare. The Water and Sanitation for Health Facility Improvement Tool (WASH FIT), initially published in 2017 and updated in 2018, is a risk-based, continuous improvement framework. The tool aims to improve WASH and related facility management and may contribute to quality of care (QoC) efforts. To date, there is no guidance available on how to monitor and evaluate the use of this tool normore » is there rigorous evidence on its effectiveness. We developed a conceptual WASH FIT evaluation framework by drawing from the broader WASH, health systems strengthening, and QoC evidence base. This framework provides a common basis to plan, implement, monitor, and evaluate potential inputs, outputs, outcomes, and impacts from applying WASH FIT. Routine use of the tool, coupled with WASH infrastructure improvements as guided by the tool, can lead to better IPC practices, and may support improvements in occupational safety, QoC, global health security, and ultimately progress towards achieving Sustainable Development Goals 3 (good health and well-being) and 6 (clean water and sanitation).« less

With the need for improving existing nuclear data evaluations, (e.g., ENDF/B-VIII.0 and JEFF-3.3 releases) the first step was to evaluate the standards for use in such a library. This new standards evaluation made use of improved experimental data and some developments in the methodology of analysis and evaluation. In addition to the work on the traditional standards, this work produced the extension of some energy ranges and includes new reactions that are called reference cross sections. Since the effort extends beyond the traditional standards, it is called the neutron data standards evaluation. This international effort has produced new evaluations ofmore » the following cross section standards: the H(n,n), ⁶Li(n,t), ¹⁰B(n,α), ¹⁰B(n,α₁γ), ^natC(n,n), Au(n,γ), ²³⁵U(n,f) and ²³⁸U(n,f). Also in the evaluation process the ²³⁸U(n,γ) and ²³⁹Pu(n,f) cross sections that are not standards were evaluated. Evaluations were also obtained for data that are not traditional standards: the Maxwellian spectrum averaged cross section for the Au(n,γ) cross section at 30 keV; reference cross sections for prompt γ-ray production in fast neutron-induced reactions; reference cross sections for very high energy fission cross sections; the ²⁵²Cf spontaneous fission neutron spectrum and the ²³⁵U prompt fission neutron spectrum induced by thermal incident neutrons; and the thermal neutron constants. The data and covariance matrices of the uncertainties were obtained directly from the evaluation procedure.« less

Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principles that could be applied to assessing the effectiveness of data visualizations in a more rapid and generalizable manner. One possibility for such a tool is a model of visual saliency for data visualizations. Visual saliency models are typically based on the properties of the human visual cortex and predict which areas of a scene havemore » visual features (e.g. color, luminance, edges) that are likely to draw a viewer's attention. While these models can accurately predict where viewers will look in a natural scene, they typically do not perform well for abstract data visualizations. In this paper, we discuss the reasons for the poor performance of existing saliency models when applied to data visualizations. We introduce the Data Visualization Saliency (DVS) model, a saliency model tailored to address some of these weaknesses, and we test the performance of the DVS model and existing saliency models by comparing the saliency maps produced by the models to eye tracking data obtained from human viewers. In conclusion, we describe how modified saliency models could be used as general tools for assessing the effectiveness of visualizations, including the strengths and weaknesses of this approach.« less

A complete B(E2)↑ evaluation and compilation for even-even nuclei has been presented. The present paper is a continuation of P.H. Stelson and L. Grodzins, and S. Raman et al. nuclear data evaluations and was motivated by a large number of new measurements. It extends the list of evaluated nuclides from 328 to 452, includes an extended list of nuclear reaction kinematics parameters and comprehensive shell model analysis. Evaluation policies for analysis of experimental data have been discussed and conclusions are given. Moreover, future plans for B(E2)↑ systematics and experimental technique analyses of even-even nuclei are outlined.

Many multidecadal atmospheric reanalysis products are available now, but their consistencies and reliability are far from perfect. In this work, atmospheric precipitable water (PW) from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), NCEP/Department of Energy (DOE), Modern Era Retrospective-Analysis for Research and Applications (MERRA), Japanese 55 year Reanalysis (JRA-55), JRA-25, ERA-Interim, ERA-40, Climate Forecast System Reanalysis (CFSR), and 20th Century Reanalysis version 2 is evaluated against homogenized radiosonde observations over China during 1979–2012 (1979–2001 for ERA-40). Results suggest that the PW biases in the reanalyses are within ~20% for most of northern and eastern China, butmore » the reanalyses underestimate the observed PW by 20%–40% over western China and by ~60% over the southwestern Tibetan Plateau. The newer-generation reanalyses (e.g., JRA25, JRA55, CFSR, and ERA-Interim) have smaller root-mean-sq uare error than the older-generation ones (NCEP/NCAR, NCEP/DOE, and ERA-40). Most of the reanalyses reproduce well the observed PW climatology and interannual variations over China. However, few reanalyses capture the observed long-term PW changes, primarily because they show spurious wet biases before about 2002. This deficiency results mainly from the discontinuities contained in reanalysis relative humidity fields in the middle-lower troposphere due to the wet bias in older radiosonde records that are assimilated into the reanalyses. An empirical orthogonal function (EOF) analysis revealed two leading modes that represent the long-term PW changes and El Niño–Southern Oscillation-related interannual variations with robust spatial patterns. The reanalysis products, especially the MERRA and JRA-25, roughly capture these EOF modes, which acco unt for over 50% of the total variance. The results show that even during the post-1979 satellite era, discontinuities in radiosonde data can still induce large spurious long-term changes in reanalysis PW and other related fields. Thus, more efforts are needed to remove spurious changes in input data for future long-term reanalyses.« less

More than 80% of the microbial genomes in GenBank are of ‘draft’ quality (12,553 draft vs. 2,679 finished, as of October, 2013). In this study, we have examined all the microbial DNA sequences available for complete, draft, and Sequence Read Archive genomes in GenBank as well as three other major public databases, and assigned quality scores for more than 30,000 prokaryotic genome sequences. Scores were assigned using four categories: the completeness of the assembly, the presence of full-length rRNA genes, tRNA composition and the presence of a set of 102 conserved genes in prokaryotes. Most (~88%) of the genomes hadmore » quality scores of 0.8 or better and can be safely used for standard comparative genomics analysis. We compared genomes across factors that may influence the score. We found that although sequencing depth coverage of over 100x did not ensure a better score, sequencing read length was a better indicator of sequencing quality. With few exceptions, most of the 30,000 genomes have nearly all the 102 essential genes. The score can be used to set thresholds for screening data when analyzing “all published genomes” and reference data is either not available or not applicable. The scores highlighted organisms for which commonly used tools do not perform well. This information can be used to improve tools and to serve a broad group of users as more diverse organisms are sequenced. Finally and unexpectedly, the comparison of predicted tRNAs across 15,000 high quality genomes showed that anticodons beginning with an ‘A’ (codons ending with a ‘U’) are almost non-existent, with the exception of one arginine codon (CGU); this has been noted previously in the literature for a few genomes, but not with the depth found here.« less

This paper examines a land surface solar radiation partitioning scheme, i.e., that of the Community Land Model version 4 (CLM4) with coupled carbon and nitrogen cycles. Taking advantage of a unique 30-year fraction of absorbed photosynthetically active radiation (FPAR) dataset derived from the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data set, multiple other remote sensing datasets, and site level observations, we evaluated the CLM4 FPAR ’s seasonal cycle, diurnal cycle, long-term trends and spatial patterns. These findings show that the model generally agrees with observations in the seasonal cycle, long-term trends, and spatial patterns,more » but does not reproduce the diurnal cycle. Discrepancies also exist in seasonality magnitudes, peak value months, and spatial heterogeneity. Here, we identify the discrepancy in the diurnal cycle as, due to, the absence of dependence on sun angle in the model. Implementation of sun angle dependence in a one-dimensional (1-D) model is proposed. The need for better relating of vegetation to climate in the model, indicated by long-term trends, is also noted. Evaluation of the CLM4 land surface solar radiation partitioning scheme using remote sensing and site level FPAR datasets provides targets for future development in its representation of this naturally complicated process.« less