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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Ecohydrological decoupling under changing disturbances and climate

Terrestrial disturbances are increasing in frequency and severity, perturbing the hydrologic cycle by altering vegetation-mediated water use and microclimate. Changes in the hydrological cycle alter vegetation succession, which is additionally influenced by changing climate and atmospheric CO 2 . Here, the interacting drivers and feedbacks between disturbances, climate, and vegetation cause uncertainty regarding the sustainable provision of freshwater through streamflow. Here we synthesize the literature on post-disturbance ecohydrological coupling, in particular, including the mechanistic relationship between vegetation and streamflow, under changing disturbance regimes, atmospheric CO 2 , and climate. Disturbance can cause decoupling between transpiration and streamflow by altering the connectivity, size, availability, and spatial distribution of their source pools. Decoupling increases when soil moisture is low due to reduced connectivity, and when soil moisture is high and Q and T are independent. Successional trajectories regulate the physiological and physical features influencing influence the dynamics of source water partitioning. Changing climate and disturbance regimes can alter succession and prolong decoupling, with potential moderation by CO 2 . Increasing rates, severity, and spread of disturbances along with warming could promote greater decoupling globally. From this review emerges a framework of testable hypotheses that identify the critical processes regulating ecohydrological coupling and provides a roadmap for future research. Accurate prediction of post-disturbance coupling and subsequent water availability for human consumption requires understanding the degree of hydraulic connectivity between source water pools for transpiration and streamflow and their response to succession under changing disturbance and climate regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Pharmacological Profiling of a Brugia malayi Muscarinic Acetylcholine Receptor as a Putative Antiparasitic Target

The diversification of anthelmintic targets and mechanisms of action will help ensure the sustainable control of nematode infections in response to the growing threat of drug resistance. G protein-coupled receptors (GPCRs) are established drug targets in human medicine but remain unexploited as anthelmintic substrates despite their important roles in nematode neuromuscular and physiological processes. Bottlenecks in exploring the druggability of parasitic nematode GPCRs include a limited helminth genetic toolkit and difficulties establishing functional heterologous expression. In an effort to address some of these challenges, we profile the function and pharmacology of muscarinic acetylcholine receptors in the human parasite Brugia malayi, an etiological agent of human lymphatic filariasis. While acetylcholine-gated ion channels are intensely studied as targets of existing anthelmintics, comparatively little is known about metabotropic receptor contributions to parasite cholinergic signaling. Using multivariate phenotypic assays in microfilariae and adults, we show that nicotinic and muscarinic compounds disparately affect parasite fitness traits. We identify a putative G protein-linked acetylcholine receptor of B. malayi (Bma-GAR-3) that is highly expressed across intramammalian life stages and adapt spatial RNA in situ hybridization to map receptor transcripts to critical parasite tissues. Tissue-specific expression of Bma-gar-3 in Caenorhabditis elegans (body wall muscle, sensory neurons, and pharynx) enabled receptor deorphanization and pharmacological profiling in a nematode physiological context. Finally, we developed an image-based feeding assay as a reporter of pharyngeal activity to facilitate GPCR screening in parasitized strains. We expect that these receptor characterization approaches and improved knowledge of GARs as putative drug targets will further advance the study of GPCR biology across medically important nematodes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Proteomic characterization of Mycobacterium tuberculosis subjected to carbon starvation

ABSTRACT Mycobacterium tuberculosis(Mtb) is the causative agent of tuberculosis (TB), the leading cause of infectious disease-related deaths worldwide. TB infections present on a spectrum from active to latent disease. In the human host,Mtbfaces hostile environments, such as nutrient deprivation, hypoxia, and low pH. Under these conditions,Mtbcan enter a dormant, but viable, state characterized by a lack of cell replication and increased resistance to antibiotics. DormantMtbposes a major challenge to curing infections and eradicating TB globally. We subjectedMtbmc 2 6020 (ΔlysAand ΔpanCD), a double auxotrophic strain, to carbon starvation (CS), a culture condition that induces growth stasis and mimics environmental conditions associated with dormancyin vivo. We provide a detailed analysis of the proteome in CS compared to replicating samples. We observed extensive proteomic reprogramming, with 36% of identified proteins significantly altered in CS. Many enzymes involved in oxidative phosphorylation and lipid metabolism were retained or more abundant in CS. The cell wall biosynthetic machinery was present in CS, although numerous changes in the abundance of peptidoglycan, arabinogalactan, and mycolic acid biosynthetic enzymes likely result in pronounced remodeling of the cell wall. Many clinically approved anti-TB drugs target cell wall biosynthesis, and we found that these enzymes were largely retained in CS. Lastly, we compared our results to those of other dormancy models and propose that CS produces a physiologically distinct state of stasis compared to hypoxia inMtb. IMPORTANCE Tuberculosis is a devastating human disease that kills over 1.2 million people a year. This disease is caused by the bacterial pathogenMycobacterium tuberculosis(Mtb).Mtbexcels at surviving in the human host by entering a non-replicating, dormant state. The current work investigated the proteomic changes thatMtbundergoes in response to carbon starvation, a culture condition that models dormancy. The authors found broad effects of carbon starvation on the proteome, with the relative abundance of 37% of proteins significantly altered. Protein changes related to cell wall biosynthesis, metabolism, and drug susceptibility are discussed. Proteins associated with a carbon starvation phenotype are identified, and results are compared to other dormancy models, including hypoxia.

Microbiology↗
DOE OSTI2019

guideline36_conformance_test 0.1

The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) has established a set of standardized high performance sequences of operation for Heating, Ventilation and Air Conditioning (HVAC) systems in buildings through their "Guideline 36". In order to achieve the intended performance, these sequences must be translated and programmed accurately in the Building Automation System (BAS) controllers. Standardizing these sequences will allow for a more efficient product delivery mechanism where the sequences are programmed and tested centrally by each manufacturer, and then distributed to their dealers/engineering contractors. This approach would minimize the need for each installer to re-interpret and program the sequences, reduces risk of errors, and reduces the time required for commissioning in the field. To achieve this goal, a performance validation method is needed to provide independent confirmation that each manufacturer has programmed the Guideline 36 sequences accurately. A standardized method of test would also avoid the need for manual interpretation (and the associated human variability) that is required with typical functional testing approaches by automating the inputs and the range of expected responses. This software "guideline36_conformance_test" has been developed to conduct standardized, repeatable and manufacturer independent tests to validate that a BAS controller has been programmed in conformance with Guideline 36. Manufacturers would provide the controller (or the control program) and the software would run a suite of tests by setting a set of inputs to the controller and verifying the output signals from the controller matches the expected output as set by Guideline 36.

Pritoni, Marco↗
DOE OSTI2019

Energy Transitions Towards Low Carbon Resilience: Evaluation of Disaster-Triggered Local and Regional Cases

Following numerous global scientific studies and major international agreements, the decarbonization of energy systems is an apparent and pressing concern. The consequence of continued emission growth tied to rising global average temperatures is difficult to predict, but against a background of other natural and human-induced disasters, may create a situation, from a positive perspective, where each disaster event triggers “build back better” responses designed to speed the transition toward low carbon, resilience-oriented energy systems. This article examines the potential for disaster-triggered responses in communities, at various local and regional levels, in four industrial economies in the Asia Pacific region: Japan, China, Australia, and the USA. Seven case studies were evaluated against a set of criteria that exemplify the key aspects of resilient energy systems. The research results suggest that a new space of innovation does emerge in post-disaster situations at a range of local and regional scales. The greatest potential benefit and opportunity for significant gains, however, appears to manifest at the small community level, and the ultimate challenge relates to how to mainstream local innovations into state and national level transformation on energy systems so as to enhance resilience and promote rapid decarbonization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Quantifying Carbon Cycle Extremes and Attributing Their Causes Under Climate and Land Use and Land Cover Change From 1850 to 2300

The increasing atmospheric carbon dioxide (CO 2 ) mole fraction affects global climate through radiative (trapping longwave radiation) and physiological effects (reduction of plant transpiration). We use the simulations of the Community Earth System Model (CESM1-BGC) forced with Representative Concentration Pathway 8.5 to investigate climate-vegetation feedbacks from 1850 to the year 2300. Human-induced land use and land cover change (LULCC), through biogeochemical and biogeophysical processes, alter the climate and modify photosynthetic activity. The changing characteristics of extreme anomalies in photosynthesis, referred to as carbon cycle extremes, increase the uncertainty of terrestrial ecosystems to act as a net carbon sink. However, the role of LULCC in altering carbon cycle extremes under business-as-usual (continuously rising) CO 2 emissions is unknown. Here we show that LULCC magnifies the intensity, frequency, and extent of carbon cycle extremes, resulting in a net reduction in expected photosynthetic activity in the future. We found that large temporally contiguous negative carbon cycle extremes are due to a persistent decrease in soil moisture, which is triggered by declines in precipitation. With LULCC and global warming, vegetation exhibits increased vulnerability to hot and dry environmental conditions, increasing the frequency of fire events and resulting in considerable losses in photosynthetic activity. While most regions show strengthening of negative carbon cycle extremes, a few locations show a weakening effect driven by declining vegetation cover or benign climate conditions for photosynthesis. Increasing hot, dry, and fire-driven carbon cycle extremes are essential for improving carbon cycle modeling and estimation of ecosystem responses to LULCC and rising CO 2 mole fractions. Moreover, large aberrations in vegetation productivity represent potential and growing threats to human lives, wildlife, and food security.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Subseasonal Variability of U.S. Coastal Sea Level from MJO and ENSO Teleconnection Interference

Abstract Climate variability affects sea levels as certain climate modes can accelerate or decelerate the rising sea level trend, but subseasonal variability of coastal sea levels is underexplored. This study is the first to investigate how remote tropical forcing from the MJO and ENSO impact subseasonal U.S. coastal sea level variability. Here, composite analyses using tide gauge data from six coastal regions along the U.S. East and West Coasts reveal influences on sea level anomalies from both the MJO and ENSO. Tropical MJO deep convection forces a signal that results in U.S. coastal sea level anomalies that vary based on MJO phase. Further, ENSO is shown to modulate both the MJO sea level response and background state of the teleconnections. The sea level anomalies can be significantly enhanced or weakened by the MJO-associated anomaly along the East Coast due to constructive or destructive interference with the ENSO-associated anomaly, respectively. The West Coast anomaly is found to be dominated by ENSO. We examine physical mechanisms by which MJO and ENSO teleconnections impact coastal sea levels and find consistent relationships between low-level winds and sea level pressure that are spatially varying drivers of the variability. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts. Significance Statement Coastal flooding due to sea level rise is increasingly threatening communities, but natural fluctuations of coastal sea levels can exacerbate the human-caused sea level rise trend. This study assesses the role of tropical influences on coastal subseasonal (2 weeks–3 months) sea level heights. Further, we explore the mechanisms responsible, particularly for constructive interference of signals contributing to coastal flooding events. Subseasonal signals amplify or suppress the lower-frequency signals, resulting in higher or lower sea level heights than those expected from known climate modes (e.g., ENSO). Low-level onshore winds and reduced sea level pressure connected to the tropical phenomena are shown to be indicators of increased U.S. coastal sea levels, and vice versa. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

The crystal structure of methanogen McrD , a methyl‐coenzyme M reductase‐associated protein

Methyl‐coenzyme M reductase (MCR) is a multi‐subunit (α 2 β 2 γ 2 ) enzyme responsible for methane formation via its unique F 430 cofactor. The genes responsible for producing MCR ( mcrA , mcrB and mcrG ) are typically colocated with two other highly conserved genes mcrC and mcrD . We present here the high‐resolution crystal structure for McrD from a human gut methanogen Methanomassiliicoccus luminyensis strain B10. The structure reveals that McrD comprises a ferredoxin‐like domain assembled into an α + β barrel‐like dimer with conformational flexibility exhibited by a functional loop. The description of the M. luminyensis McrD crystal structure contributes to our understanding of this key conserved methanogen protein typically responsible for promoting MCR activity and the production of methane, a greenhouse gas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development of high-affinity nanobodies specific for Na V 1.4 and Na V 1.5 voltage-gated sodium channel isoforms

Voltage-gated sodium channels, Na V s, are responsible for the rapid rise of action potentials in excitable tissues. Na V channel mutations have been implicated in several human genetic diseases, such as hypokalemic periodic paralysis, myotonia, and long-QT and Brugada syndromes. Here, we generated high-affinity anti-NaV nanobodies (Nbs), Nb17 and Nb82, that recognize the Na V 1.4 (skeletal muscle) and Na V 1.5 (cardiac muscle) channel isoforms. These Nbs were raised in llama (Lama glama) and selected from a phage display library for high affinity to the C-terminal (CT) region of Na V 1.4. The Nbs were expressed in Escherichia coli, purified, and biophysically characterized. Development of high-affinity Nbs specifically targeting a given human Na V isoform has been challenging because they usually show undesired crossreactivity for different Na V isoforms. Our results show, however, that Nb17 and Nb82 recognize the CTNa V 1.4 or CTNa V 1.5 over other CTNav isoforms. Kinetic experiments by biolayer interferometry determined that Nb17 and Nb82 bind to the CTNa V 1.4 and CTNa V 1.5 with high affinity (K D ~ 40–60 nM). In addition, as proof of concept, we show that Nb82 could detect Na V 1.4 and Na V 1.5 channels in mammalian cells and tissues by Western blot. Furthermore, human embryonic kidney cells expressing holo Na V 1.5 channels demonstrated a robust FRET-binding efficiency for Nb17 and Nb82. Our work lays the foundation for developing Nbs as anti-Na V reagents to capture Na V s from cell lysates and as molecular visualization agents for Na V s.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Urban Scaling as Validation for Predictions of Imperviousness From Population

Abstract Strategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Divergence in heritable life history traits suggests potential for local adaptation and trade‐offs associated with a coal ash disposal site

Abstract Globally, human activities have resulted in rapid environmental changes that present unique challenges for wildlife. However, investigations of local adaptation in response to simultaneous exposure to multiple anthropogenic selection pressures are rare and often generate conflicting results. We used an in situ reciprocal transplant design within a quantitative genetic framework to examine how adaptive evolution and phenotypic plasticity contribute to the persistence of an amphibian population inhabiting an environment characterized by high levels of multiple toxic trace elements. We found evidence of phenotypic divergence that is largely consistent with local adaptation to an environment contaminated with multiple chemical stressors, tied to potential trade‐offs in the absence of contaminants. Specifically, the population derived from the contaminated environment had a reduced risk of mortality and greater larval growth and in the contaminated environment, relative to offspring from the naïve population. Further, while survival in the uncontaminated environment was not compromised in offspring from the contaminant‐exposed population, they did show delayed development and reduced growth rates over larval development, relative to the naïve population. We found no evidence of reduced additive genetic variation in the contaminant‐exposed population, suggesting long‐term selection in a novel environment has not reduced the evolutionary potential of that population. We also saw little evidence that past selection in the ASH environment had reduced trait plasticity in the resident population. Maternal effects were prominent in early development, but we did not detect any trends suggesting these effects were associated with the maternal transfer of toxic trace elements. Our results demonstrate the potential for adaptation to multiple contaminants in a wild amphibian population, which may have facilitated long‐term persistence in a heavily impacted environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology

Abstract INTRODUCTION Factors responsible for the deposition of pathological tau in the brain are incompletely understood. This study links macroscale tau deposition in the human brain to cerebrospinal fluid (CSF) flow dynamics using resting‐state functional magnetic resonance imaging (rsfMRI). METHODS Low‐frequency (< 0.1 Hz) resting‐state global brain activity is coupled with CSF flow and potentially reflects CSF dynamics‐related clearance. We examined the correlation between rsfMRI measures of CSF inflow and global activity (gBOLD–CSF coupling) as a predictor, interacting with amyloid beta (Aβ), of tau and cortical thickness (dependent variables) across Alzheimer's Disease Neuroimaging Initiative (ADNI) participants from cognitively unimpaired through mild cognitive impairment (MCI) and Alzheimer's disease (AD). RESULTS Tau deposition in Aβ+ participants, accompanied by cortical thinning and cognitive decline, is associated with decreased gBOLD–CSF coupling. Tau mediates the relationship between coupling and thickness. DISCUSSION Findings suggest that resting‐state global brain activity and CSF movements comodulate Alzheimer's tau deposition, presumably related to CSF clearance. Highlights A non‐invasive functional magnetic resonance imaging (fMRI) assessment of a CSF clearance‐related process is carried out. Global brain activity is coupled with CSF inflow in human fMRI during resting state. Global fMRI–CSF coupling is correlated with tau in Alzheimer's disease (AD). This coupling measure is also associated with cortical thickness, mediated by tau.

Neurosciences & Neurology↗
DOE OSTI2026

Hierarchical semi-Markov models with duration-aware dynamics for activity sequences

Residential electricity demand at granular scales is driven by what people do and for how long. Accurately forecasting this demand for applications like microgrid management and demand response therefore requires generative models for activities that can produce realistic daily activity sequences, capturing both the timing and duration of human behavior. This paper develops a generative model of human activity sequences using nationally representative time-use diaries at a 10-min resolution. We use this model to quantify which demographic factors are most critical for improving predictive performance. We propose a hierarchical semi-Markov framework that addresses two key modeling challenges. First, a time-inhomogeneous Markov router learns the patterns of “which activity comes next.” Second, a semi-Markov hazard component explicitly models activity durations, capturing “how long” activities realistically last. To ensure statistical stability when data are sparse, the model pools information across related demographic groups and time blocks. The entire framework is trained and evaluated using survey design weights to ensure our findings are representative of the U.S. population. On a held-out test set, we demonstrate that explicitly modeling durations with the hazard component provides a substantial and statistically significant improvement over purely Markovian models. Furthermore, our analysis reveals a clear hierarchy of demographic factors: Sex, Day-Type, and Household Size provide the largest predictive gains, while Region and Season, though important for energy calculations, contribute little to predicting the activity sequence itself. The result is an interpretable and robust generator of synthetic activity traces, providing a high-fidelity foundation for downstream energy systems modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Volcanic Imprints in Last-Millennium Land Summer Temperatures in the Circum-North Atlantic Area

Summer cooling is one of the most direct consequences of explosive volcanic eruptions that can affect ecosystems and human societies. Recent studies revealed a multiyear cooling impact on hemispheric and global summer temperatures after tropical eruptions, yet the volcanic responses appear to vary on regional scales. Here, in this work, we revisit volcano-induced summer cooling in eastern Canada and northern and central Europe by applying superposed epoch analysis on CMIP6-PMIP4 simulations and millennial temperature reconstructions based on tree-ring density. We then examine potential causes modulating region-specific volcanic impact. While confirming that, on average, tropical eruptions over the last millennium have induced a longer cooling (>4 yr) than eruptions from extratropical Northern Hemisphere in all three North Atlantic regions, we show that the peak magnitude of cooling is stronger in eastern Canada. We also find that the detected volcanic temperature anomalies can be strongly affected by the selection and number of volcanic events and nonvolcanic signals embedded in the climate time series. This study highlights the risks of using highly noisy proxy records to investigate volcanic impacts, especially in regions with strong unforced climate variability. The CMIP6-PMIP4 simulations generally agree with the three reconstructions on the average response to tropical eruptions, but their performance is poorer regarding the production of significant cooling after extratropical eruptions. Our results further suggest that the particular sensitivity to tropical eruptions in eastern Canada is likely related to increased sea ice surrounding Quebec–Labrador associated with the positive Arctic Oscillation and North Atlantic Oscillation formed during the first posteruption winter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Dataset 1: A National and City Dataset on Human Factors in Pooled Rideshare, 2021

Dataset 1: A National and City Dataset on Human Factors in Pooled Rideshare, 2021. Dataset Description: Pooled Rideshare Acceptance Survey - Phase 1 (2021, N = 5,385). This dataset captures responses from a nationally representative sample of 5,385 adults across the United States to understand public acceptance, preferences, and behavioral intentions related to pooled rideshare (PR) services. The primary objective of this research is to provide actionable insights to inform the design, deployment, and policy development of sustainable shared mobility systems. Data was collected via an online survey administered through a national panel provider. Participants ranged in age from 18 to 95 years, and representation from all U.S. regions. The survey instrument was designed to explore numerous dimensions related to PR adoption including demographic traits, current travel habits, rideshare familiarity, trust, safety, environmental attitudes, and user experience preferences. Both rideshare users and non-users were included, offering a diverse range of perspectives. - Phase_1_Final - The dataset includes survey items developed from literature reviews, and prior field studies. Each row represents an individual respondent, and each column corresponds to a variable such as willingness to use pooled rideshare, attitudes toward specific service features, and sociodemographic data. The data is available in both .CSV and .SAV formats. - Phase_1_Final_MapFile - The accompanying data dictionary explains all variable labels, response scales, and codes. An .XLSX format of the full survey instrument is also included to support interpretation and reuse of the dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Dataset 2: A National Dataset on Human Choices in Pooled Rideshare, 2022

Dataset 2: A National Dataset on Human Choices in Pooled Rideshare, 2022. Dataset Description: Pooled Rideshare Acceptance Survey - Phase 2 (2022, N = 2,884). This dataset captures responses from a nationally representative sample of 2,884 adults across the United States to understand choice behaviors between personal and pooled rideshare services. The primary objective of this research is to investigate choice behaviors in rideshare services and provide insights that inform service design, policymaking, and transportation planning, with the aim of encouraging pooled rideshare adoption and enhancing transportation network energy efficiency. Data was collected via an online survey administered through a national panel provider. Participants ranged in age from 18 to 94 years, and representation from all U.S. regions. The survey was designed with a focus on investigating the stated-preference between personal and pooled rideshare services. Each participant responded to 20 stated-preference questions, where they were presented with a hypothesized situation to choose between a personal rideshare option and a pooled rideshare option to complete a trip. The sociodemographic information and attitudes towards factors of pooled rideshare acceptance were also collected to support the comprehensive investigation of participants’ rideshare choice behaviors. - Phase_2_Final - Each row represents an individual respondent, and each column corresponds to a variable such as stated-preference scenario attributes, stated-preference scenario responses, attitudes toward specific service features, and sociodemographic data. The data is available in both .CSV and .SAV formats. - Phase_2_Final_MapFile - The accompanying data dictionary explains all variable labels, response scales, and codes. An .XLSX format of the full survey instrument is included to support interpretation and reuse of the dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Biophysical Screens Identify Fragments That Bind to the Viral DNA-Binding Proteins EBNA1 and LANA

The human gamma-herpesviruses Epstein–Barr virus (EBV) (HHV-4) and Kaposi’s sarcoma-associated herpesvirus (KSHV) (HHV-8) are responsible for a number of diseases, including various types of cancer. Epstein–Barr nuclear antigen 1 (EBNA1) from EBV and latency-associated nuclear antigen (LANA) from KSHV are viral-encoded DNA-binding proteins that are essential for the replication and maintenance of their respective viral genomes during latent, oncogenic infection. As such, EBNA1 and LANA are attractive targets for the development of small-molecule inhibitors. To this end, we performed a biophysical screen of EBNA1 and LANA using a fragment library by saturation transfer difference (STD)–NMR spectroscopy and surface plasmon resonance (SPR). We identified and validated a number of unique fragment hits that bind to EBNA1 or LANA. We also determined the high-resolution crystal structure of one fragment bound to EBNA1. Results from this screening cascade provide new chemical starting points for the further development of potent inhibitors for this class of viral proteins.

59 BASIC BIOLOGICAL SCIENCES↗