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  1. Microstructural evolution in a precipitate-hardened (Fe0.3Ni0.3Mn0.3Cr0.1)94Ti2Al4 multi-principal element alloy during high-pressure torsion

    Multi-principal element alloys demonstrate high strength, thermal stability, and irradiation resistance, making them excellent candidate materials for applications in nuclear reactors and other harsh environments. Some studies have examined the use of high-pressure torsion to strengthen MPEAs through grain size reduction and strain hardening. However, no studies have investigated the effect of HPT on secondary phases (precipitates) within an MPEA. Two alloys, (Fe0.3Ni0.3Mn0.3Cr0.1)94Ti2Al4 containing Ni(Ti, Al) B2 phase, and CrFe σ phase, and single-phase Fe0.3Ni0.3Mn0.3Cr0.1, were fabricated by casting and heat treatment. Both alloys were then processed with HPT to study microstructural evolution. Scanning electron microscopy (SEM) and transmission electronmore » microscopy (TEM) were used to characterize the alloys before and after HPT processing. HPT processing produced a nanocrystalline structure in both alloys, but (Fe0.3Ni0.3Mn0.3Cr0.1)94Ti2Al4 exhibited a significantly smaller grain size and higher dislocation density than Fe0.3Ni0.3Mn0.3Cr0.1, with corresponding higher hardness. Before HPT, the (Fe0.3Ni0.3Mn0.3Cr0.1)94Ti2Al4 alloy consisted of large grain (~ 400 μm) and precipitates, including B2 of ~ 38 μm average size, B2 of ~ 0.7 μm average size, and small amounts of σ of ~ 1.5 μm average size. After HPT, the larger B2 precipitates were decreased in size and volume fraction, while the smaller B2 precipitates were completely dissolved; the σ precipitates appeared unaffected by HPT, likely due to their much higher hardness. Finally, observation of the B2 precipitate distribution along radial distance indicates that the strain caused the precipitates to fracture at intermediate strain (γ = 125) and dissolve at high strain (γ = 280).« less
  2. Survival and behavior of Mojave desert tortoises head-started with and without outdoor rearing

    Mojave desert tortoise (Gopherus agassizii) populations in some regions have declined by >50% since 2004, prompting the need for more research on ways to recover populations. One possible recovery tool is head-starting (i.e., the act of protecting and raising juvenile tortoises to sizes that increase survival upon release); however, head-starting can have high start-up and maintenance costs that can limit its feasibility. Strategies that reduce cost and rearing duration may foster broader and more effective use. We released and radio-tracked 60 juvenile tortoises in the Mojave National Preserve in California, USA, that had been reared under 2 treatments: those rearedmore » 1 year indoors after hatching, then 1 year outdoors (combo) and those reared just 1 year indoors (indoor-only). We tested whether indoor-only rearing alone could be a more efficient means of producing robust head-started tortoises. We examined the behavior, movement, and survival of tortoises after release into the wild from 2020 to 2021 to determine whether these outcomes differed between husbandry treatments. Combo tortoises tended to perform settling behaviors (mean ± 1 SE days to building first burrow = 6.7 ± 0.8, entering dormancy = 23.3 ± 2.1, and emerging from dormancy = 189.6 ± 4.4) earlier than indoor-only tortoises (7.4 ± 0.9, 31.5 ± 2.6, and 193.9 ± 5.9, respectively), but this difference was not significant, suggesting the rearing method did not greatly alter settling behavior. Indoor-only tortoises dispersed at least twice as far from their release site (156.2 ± 26.3 m compared with 77.3 ± 20.6 m for combo tortoises), had larger mean use areas (3.7 ± 0.1 ha compared with 2.8 ± 0.3 ha for combo tortoises for 95% Brownian bridge movement model estimates), and greater variability in their movements than combo tortoises (daily average step length post-emergence: 4.3 ± 0.2 m compared with 2.8 ± 0.1 m for combo tortoises). Despite differences in their movements, indoor-only and combo tortoises had similar survival rates over the study, 51% versus 42%, respectively, during a period of extreme drought in 2021. The similarity in survival between groups gives head-starting practitioners freedom in their rearing methods. The indoor-only group had lower site fidelity, which should be considered when this is an undesirable trait for released tortoises.« less
  3. Impacts of non-residential solar on residential adoption decisions

    Household decisions to adopt rooftop solar photovoltaics are partly driven by social influence. Previous research on solar adoption influence has focused on influence among residential peers. Here, we expand the framework of solar adoption influence by exploring the influence of non-residential installations on residential adoption decisions. We use staggered differences-in-differences to estimate non-residential influence effects using a large data sample of residential adoptions. We also critically evaluate prevailing frameworks for solar adoption influence. We find that non-residential installations are associated with accelerated residential adoption rates, on the order of 0.4 additional residential adoptions per quarter per non-residential installation. We showmore » that non-residential systems exert a continuous, long-term influence on residential adoption decisions. We explore separate results and influence mechanisms for solar installed on commercial buildings, government buildings, and houses of worship. The results suggest that non-residential solar adopters could serve as partners in policies to “seed” residential adoption in underserved communities.« less
  4. Co-occurrence of native white-tailed deer and invasive wild pigs: Evidence for competition?

    Understanding whether invasive and native species compete for shared resources where they co-occur is essential for mitigating the negative impacts of invasive species on native ecosystems. Here, we examined how the presence and density of an invasive species, wild pigs (Sus scrofa), affect native white-tailed deer (Odocoileus virginianus; hereafter, deer) on the Savannah River Site, SC, USA. We examined potential changes in deer areas of use, temporal overlap, and occupancy to evaluate the effects of wild pig occurrence and density on deer space use, diel activity, and co-occurrence with wild pigs across 9 months during 2018 and 2019. Wild pigmore » density had the strongest effect on deer space use in high- and moderate-use areas. Declines in deer space use in response to wild pig density were most pronounced in March and October 2018 and April 2019 for females, while male space use declined in response to wild pig density in October and December 2018. Both species were largely nocturnal with high overlap in diel activity across months. Deer occupancy responses to wild pig density varied across months, with negative responses in May and October 2018 and positive responses in July 2018 and April 2019. Deer and wild pigs co-occurred at 30%–59% of camera stations across months, with broadscale co-occurrence patterns being unaffected by changes in shared cover or wild pig occurrence. Overall, our results suggest that deer make fine-scale behavioral adjustments to avoid wild pigs, providing evidence that competition is likely occurring even where wild pig density is relatively low. Such fine-scale behavioral plasticity in deer appears to mitigate the costs of competition with wild pigs and may be a mechanism enabling long-term co-existence of deer and wild pigs. Our study provides novel insight on the complexities of spatiotemporal relationships between invasive wild pigs and native deer and suggests that the negative effects of interactions between deer and wild pigs may be more pronounced when deer life history needs are particularly demanding. In areas where eradication of invasive wild pigs may be impossible, maintaining low wild pig densities may help mitigate, but may not eliminate, the negative effects of wild pigs on deer.« less
  5. Two (or more) for one: Identifying classes of household energy- and water-saving measures to understand the potential for positive spillover

    A key component of behavior-based energy conservation programs is the identification of target behaviors. A common approach is to target behaviors with the greatest energy-saving potential. The concept of behavioral spillover introduces further considerations, namely that adoption of one energy-saving behavior may increase (or decrease) the likelihood of other energy-saving behaviors. This research aimed to identify and describe household energy- and water-saving measure classes within which positive spillover is likely to occur (e.g., adoption of energy-efficient appliances may correlate with adoption of water-efficient appliances), and explore demographic and psychographic predictors of each. Nearly 1,000 households in a California city weremore » surveyed and asked to report whether they had adopted 75 different energy- and/or water-saving measures. Principal Component Analysis and Network Analysis based on correlations between adoption of these diverse measures revealed and characterized eight water-energy-saving measure classes: Water Conservation, Energy Conservation, Maintenance and Management, Efficient Appliance, Advanced Efficiency, Efficient Irrigation, Green Gardening, and Green Landscaping. Understanding these measure classes can help guide behavior-based energy program developers in selecting target behaviors and designing interventions.« less
  6. The Ahr2-Dependent wfikkn1 Gene Influences Zebrafish Transcriptome, Proteome, and Behavior

    The aryl hydrocarbon receptor (AHR) is required for vertebrate development and is also activated by exogenous chemicals, including polycyclic aromatic hydrocarbons (PAHs) and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). AHR activation is well-understood, but roles of downstream molecular signaling events are largely unknown. From previous transcriptomics in 48 h postfertilization (hpf) zebrafish exposed to several PAHs and TCDD, we found wfikkn1 was highly coexpressed with cyp1a (marker for AHR activation). Thus, we hypothesized wfikkn1’s role in AHR signaling, and showed that wfikkn1 expression was Ahr2 (zebrafish ortholog of human AHR)-dependent in developing zebrafish exposed to TCDD. To functionally characterize wfikkn1, we made a CRISPR-Cas9more » mutant line with a 16-bp deletion in wfikkn1’s exon, and exposed wildtype and mutants to dimethyl sulfoxide or TCDD. 48-hpf mRNA sequencing revealed over 700 genes that were differentially expressed (p < .05, log2FC > 1) between each pair of treatment combinations, suggesting an important role for wfikkn1 in altering both the 48-hpf transcriptome and TCDD-induced expression changes. Mass spectrometry-based proteomics of 48-hpf wildtype and mutants revealed 325 significant differentially expressed proteins. Functional enrichment demonstrated wfikkn1 was involved in skeletal muscle development and played a role in neurological pathways after TCDD exposure. Mutant zebrafish appeared morphologically normal but had significant behavior deficiencies at all life stages, and absence of Wfikkn1 did not significantly alter TCDD-induced behavior effects at all life stages. In conclusion, wfikkn1 did not appear to be significantly involved in TCDD’s overt toxicity but is likely a necessary functional member of the AHR signaling cascade.« less
  7. Accelerated screening of functional atomic impurities in halide perovskites using high-throughput computations and machine learning

    The pressing need for novel materials that can serve rising demands in solar cell and optoelectronic technologies makes the nexus of halide perovskites, high-throughput computations, and machine learning, very promising. Ever increasing amounts of data on the structure, fundamental properties, and device performance of halide perovskites provide opportunities for learning chemical rules and design principles that make these materials attractive, and applying them across wide chemical spaces. In this work, we show that impurity properties of halide perovskites computed using density functional theory (DFT) can be combined with machine learning (ML) to deliver predictive models and quick identification of optoelectronicallymore » active impurity atoms. Our computation lead to the largest reported dataset of the formation energies and charge transition levels of Pb-site impurities in methylammonium lead halide (MAPbX3) perovskites. Descriptors are defined to uniquely represent any impurity atom in any MAPbX3 compound and mapped to the computed impurity properties using regression techniques such as Gaussian process regression, neural networks, and random forests. We use the best optimized predictive models to make predictions for hundreds of impurities across 9 MAPbX3 compounds and create lists of dominating impurities, that is, impurities that can shift the equilibrium Fermi level in the perovskite as determined by native point defects. Finally, this accelerated screening powered by computations and machine learning can guide the identification of problematic impurities that may cause undesired recombination of charge carriers, as well as impurities that can be deliberately introduced to tune the perovskite conductivity and resulting photovoltaic absorption.« less
  8. Developing occupant archetypes within urban low-income housing: A case study in Mumbai, India

    Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural andmore » psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.« less
  9. Shifting temporal dynamics of human mobility in the United States

    In this paper we analyze the average hourly temporal dynamics of human mobility in the United States from 2019 to 2020. We discuss how large decreases in human mobility nonuniformly effect the daily temporal dynamics of aggregate human behavior. The data used are weekly activity patterns for POIs from 2019 to 2020 in the United States, provided by SafeGraph and made openly available to academic and research institutions. We use clustering methods to create metrics describing how human activity changes throughout the day/week at the county and national levels. In response to significant mobility reductions starting March 2020, daily temporalmore » patterns of human activity changed nonuniformly. Morning activity started later, and evening activity started earlier in 2020 compared to 2019, and temporal behavioral patterns on weekdays began to look more similar to weekends. The changes in daily temporal behavior persisted throughout the year even as total mobility levels recovered. The results provide insights on the changes in human behavior in response covid-19 policies and illustrate influences on social systems, health, and transportation networks.« less
  10. Influencing Activity of Bats by Dimly Lighting Wind Turbine Surfaces with Ultraviolet Light

    Wind energy producers need deployable devices for wind turbines that prevent bat fatalities. Based on the speculation that bats approach turbines after visually mistaking them for trees, we tested a potential light-based deterrence method. It is likely that the affected bats see ultraviolet (UV) light at low intensities. Here, we present the results of a multi-month experiment to cast dim, flickering UV light across wind turbine surfaces at night. Our objectives were to refine and test a practical system for dimly UV-illuminating turbines while testing whether the experimental UV treatment influenced the activity of bats, birds, and insects. We mountedmore » upward-facing UV light arrays on turbines and used thermal-imaging cameras to quantify the presence and activity of night-flying animals. The results demonstrated that the turbines can be lit to the highest reaches of the blades with “invisible” UV light, and the animal responses to such experimental treatment can be concurrently monitored. The UV treatment did not significantly change nighttime bat, insect, or bird activity at the wind turbine. Our findings show how observing flying animals with thermal cameras at night can help test emerging technologies intended to variably affect their behaviors around wind turbines.« less
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