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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Scanning Mobility Particle Sizer (SMPS)-Aerodynamic Particle Sizer (APS) Merged Size Distribution (mergedsmpsaps) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform designed to house instruments that measure many of these aerosol properties in situ. Currently, ARM operates at least four different instruments that measure a portion of the ambient aerosol size distribution. Most users are interested in the entire size distribution or a portion of the size distribution that extends across the measurement range of multiple instruments. However, merging these distributions is not trivial as the instruments employ different measurement principals and, in most cases, report data as a function of different representations of the aerosol diameter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1–4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Gene Amplification, Laboratory Evolution, and Biosensor Screening Reveal MucK as a Terephthalic Acid Transporter in Acinetobacter baylyi ADP1

Microbial terephthalic acid (TPA) catabolic pathways are conserved among the few bacteria known to turnover this xenobiotic aromatic compound. However, to date there are few reported cases in which this pathway has been successfully expressed in heterologous hosts to impart efficient utilization of TPA as a sole carbon source. In this work, we aimed to engineer TPA conversion in Acinetobacter baylyi ADP1 via the heterologous expression of catabolic and transporter genes from a native TPA-utilizing bacterium. Specifically, we obtained ADP1-derived strains capable of growing on TPA as the sole carbon source using chromosomal insertion and targeted amplification of the tph catabolic operon from Comamonas sp. E6. Adaptive laboratory evolution was then used to improve growth on this substrate. TPA consumption rates of the evolved strains, which retained multiple copies of the tph genes, were ~0.2 g/L/h (or ~1 g TPA/g cells/h), similar to that of Comamonas sp. E6 and almost 2-fold higher than that of Rhodococcus jostii RHA1, another native TPA-utilizing strain. To evaluate TPA transport in the evolved ADP1 strains, we engineered a TPA biosensor consisting of the transcription factor TphR and a fluorescent reporter. In combination with whole-genome sequencing, the TPA biosensor revealed that transport of TPA was not mediated by the heterologous proteins from Comamonas sp. E6. Instead, the endogenous ADP1 muconate transporter MucK, a member of the major facilitator superfamily, was responsible for TPA transport in several evolved strains in which MucK variants were found to enhance TPA uptake. Furthermore, the IclR-type transcriptional regulator DcaS was identified as a repressor of mucK expression. Overall, this work presents an unexpected function of a native protein identified through gene amplification, adaptive laboratory evolution, and a combination of screening methods. This study also provides a TPA biosensor for application in ADP1 and identifies transporter variants for use in metabolic engineering applications focused on plastic upcycling of polyesters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A phase 2 study of sorafenib combined with conventional therapies in refractory central nervous system leukemia

Background Patients with refractory central nervous system leukemia (CNSL) have a dismal prognosis and lack effective therapy. Case reports have shown that sorafenib is effective against brain metastases, including leukemia. Methods To explore the efficacy of sorafenib combined with conventional therapies for refractory CNSL, a phase 2 study was conducted. The primary end point was the complete remission rate (CRR) within 8 weeks of treatment. Secondary end points included the overall response rate (ORR), event‐free survival (EFS), overall survival (OS), and adverse events (AEs). Results Twenty‐six patients with refractory CNSL were enrolled; they included 17 with isolated CNSL, 7 with hematological relapse, and 2 with another extramedullary relapse. After 8 weeks of treatment, 21 patients achieved complete remission, 2 achieved partial remission, and 3 achieved no remission for a CRR of 80.8% (95% CI, 62.1%‐91.5%) and an ORR of 88.5% (95% CI, 71.0%‐96.0%). Twenty patients survived, and 6 died. The 2‐year EFS and OS rates were 75.0% (95% CI, 54.5%‐88.3%) and 76.9% (95% CI, 54.2%‐90.4%), respectively. Six patients experienced grade 3 or 4 treatment‐related AEs, including moderate chronic graft‐vs‐host disease (n = 3), grade 3 or 4 acute graft‐vs‐host disease (n = 2), and grade 3 skin rash (n = 1). No treatment‐related deaths occurred during the therapy of refractory CNSL. Conclusions Sorafenib combined with conventional therapies is effective and safe for refractory CNSL. Lay Summary Sorafenib combined with conventional therapies is effective and safe for refractory central nervous system leukemia.

Chen, Xiaoxia↗
DOE OSTI2024

Enhancing the Range and Reliability of the Spacer Layer Imaging Method

The spacer layer imaging method (SLIM) is widely used to measure the thickness of additive and lubricant films, in lubricant development and evaluation, and for fundamental research into elastohydrodynamic lubrication and tribofilm formation mechanisms. The film thickness measurement, as implemented on several popular tribometers, provides powerful, non-destructive in-situ mapping of film topography with nanometre-scale height sensitivity. However, the results can be highly sensitive to experimental procedure, machine condition, and image analysis, in some cases reporting unphysical film thickness trends. The prevailing image analysis techniques make it challenging to interrogate these errors, often hiding their multivariate nonlinear behaviour from the user by spatial averaging. Herein, several common ‘silent errors’ in the SLIM measurement, including colour matching to incorrect fringe orders, and colour drift due to the optical properties of the system or film itself, are discussed, with examples. A robust suite of novel a priori and a posteriori methods to address these issues, and to improve the accuracy and reliability of the measurement, are also presented, including a novel, computationally inexpensive circle-finding algorithm for automated image processing. In combination, these methods allow reliable mapping of films up to at least 800 nm in thickness, representing a significant milestone for the utility of SLIM applied to elastohydrodynamic contact.

EHL film geometry↗
DOE OSTI2023

Natural gas odorants: A scoping review of health effects

Organosulfur compounds are intentionally added to natural gas as malodorants with the intent of short-term nasal inhalation to aid in leak detection. Regulatory exposure limits have not been established for all commonly used natural gas odorants, and recent community-level exposure events and growing evidence of indoor natural gas leakage have raised concerns associated with natural gas odorant exposures. We conducted a scoping review of peer-reviewed scientific publications on human exposures and animal toxicological studies of natural gas odorants to assess toxicological profiles, exposure potential, health effects and regulatory guidelines associated with commonly used natural gas odorants. We identified only 22 studies which met inclusion criteria for full review. Overall, there is limited evidence of both transient nonspecific health symptoms and clinically diagnosed causative neurotoxic effects associated with prolonged odorant exposures. Across seven community-level exposure events and two occupational case reports, consistent symptom patterns included: headache, ocular irritation, nose and throat irritation, respiratory complaints such as shortness of breath and asthma attacks, and skin irritation and rash. Of these, respiratory inflammation and asthma exacerbations are the most debilitating, whereas the high prevalence of ocular and dermatologic symptoms suggest a non-inhalation route of exposure. The limited evidence available raises the possibility that organosulfur odorants may pose health risks at exposures much lower than presently understood, though additional dose-response studies are needed to disentangle specific toxicologic effects from nonspecific responses to noxious organosulfur odors. Numerous recommendations are provided including more transparent and prescriptive natural gas odorant use practices.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2021

Lessons Learned—Fluoride Exposure and Response

Laboratory research can expose workers to a wide variety of chemical hazards. Researchers must not only take personal responsibility for their safety but also inevitably rely on coworkers to also work safely. The foundations for protocols, requirements, and behaviors come from our history and lessons learned from others. For that reason, here, a recent incident is examined in which a researcher suffered hydrofluoric acid (HF) burns while working with an inorganic digestion mixture of aqueous HF (8%) and nitric acid (HNO 3 , 58%). HF education is critical for workers because delays in treatment, improper treatment, and delay of symptoms are all factors in unfavorable outcomes in case reports. Furthermore, while the potential severity of the incident was elevated due to bypassed engineered controls and lack of proper personal protective equipment, only minor injuries were sustained. We discuss the results of a causal analysis of the incident that revealed areas of improvement in protocols, personal protective equipment, and emergency response that could help prevent similar accidents from occurring. We also present simple improvements that anyone can implement to reduce the potential consequences of an accident, based upon our lessons learned.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Emergence of Fermi arcs due to magnetic splitting in an antiferromagnet

The Fermi surface plays an important role in controlling the electronic, transport and thermodynamic properties of materials. As the Fermi surface consists of closed contours in the momentum space for well-defined energy bands, disconnected sections known as Fermi arcs can be signatures of unusual electronic states, such as a pseudogap. Another way to obtain Fermi arcs is to break either the time-reversal symmetry or the inversion symmetry of a three-dimensional Dirac semimetal, which results in formation of pairs of Weyl nodes that have opposite chirality, and their projections are connected by Fermi arcs at the bulk boundary. Here, we present experimental evidence that pairs of hole- and electron-like Fermi arcs emerge below the Neel temperature (TN) in the antiferromagnetic state of cubic NdBi due to a new magnetic splitting effect. The observed magnetic splitting is unusual, as it creates bands of opposing curvature, which change with temperature and follow the antiferromagnetic order parameter. This is different from previous theoretically considered and experimentally reported cases of magnetic splitting, such as traditional Zeeman and Rashba, in which the curvature of the bands is preserved. Therefore, our findings demonstrate a type of magnetic band splitting in the presence of a long-range antiferromagnetic order that is not readily explained by existing theoretical ideas.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Orbital selective band re-normalization induced Lifshitz transition in TiSe 2

A Lifshitz transition is a sudden change in Fermi surface topology, often linked to quantum phenomena, with major impact on transport and sometimes superconductivity. Here we demonstrate a Lifshitz transition in TiSe 2 using micro–angle-resolved photoemission spectroscopy. At low temperatures an electron pocket appears at the Brillouin-zone center, whereas at higher temperatures spectral weight from a hole-like valence band dominates the Fermi level. Unlike previously reported cases typically driven by rigid band shifts, in TiSe 2 an orbital-selective strong band renormalization induces the crossover near 160 K. This mechanism naturally explains the longstanding resistivity anomaly of TiSe 2 , which peaks around 160 K. Our results clarify its puzzling transport behavior and open avenues to investigate how periodic lattice distortions interact with strong electronic correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world’s deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen’s antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Current challenges and future opportunities of phage therapy

ABSTRACT Antibiotic resistance is a major public health challenge worldwide, whose implications for global health might be devastating if novel antibacterial strategies are not quickly developed. As natural predators of bacteria, (bacterio)phages may play an essential role in escaping such a dreadful future. The rising problem of antibiotic resistance has revived the interest in phage therapy and important developments have been achieved over the last years. But where do we stand today and what can we expect from phage therapy in the future? This is the question we set to answer in this review. Here, we scour the outcomes of human phage therapy clinical trials and case reports, and address the major barriers that stand in the way of using phages in clinical settings. We particularly address the potential of phage resistance to hinder phage therapy and discuss future avenues to explore the full capacity of phage therapy.

Pires, Diana P.↗
DOE OSTI2020

A Critical Exploration of the Efficiency Impacts of Demand Response From HVAC in Commercial Buildings

Increasing quantities of renewable energy generation has yielded a need for greater energy storage capacity in power systems. Thermal storage in variable air volume (VAV) heating, ventilation, and air conditioning (HVAC) in commercial buildings has been identified as an inexpensive source of grid storage, but the true costs are not known. Recent literature explores the inefficiency associated with providing grid services from these HVAC-based demand response (DR) resources by employing a battery analogy to calculate round-trip efficiency (RTE). Results vary significantly across studies and in some cases reported efficiencies are strikingly low. This article has three objectives to address these prior results. First, we synthesize and expand on insights into existing literature by systematically exploring the potential causes for the discrepancies in results. We reinforce previous work indicating baseline modeling may drive differences across studies and deduce that control accuracy plays a role in the major differences between experiments and simulation. Second, we discuss why the RTE metric is problematic for DR applications, discuss another proposed metric, additional energy consumption (AEC), and propose an extension, which we call uninstructed energy consumption (UEC), to evaluate DR performance. Finally, we explore the merits of different metrics using experimental data and highlight UEC's reduced sensitivity to the characteristics of the DR signal than previously proposed metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Thermal Modeling and Limitations for Power Electronics Embedded in Medium-Voltage Cables

As next-generation energy technologies gain traction and power demand increases, the existing electrical infrastructure faces significant stress, prompting innovative solutions to enhance the grid's capacity and lifespan. This work explores the possibility of embedding medium-voltage (MV) power electronics directly inline with the cable, and the resulting thermal challenges. Since the majority of power distribution cables installed in the U.S. are passively cooled, the work focuses primarily on passive cooling, with an emphasis on the limitations of axial heat spreading within the cable. To date, literature on axial spreading of high incident heat loads on cables and cable environments is limited, typically reporting cases with <10 W of incident heat load. This work will explore the considerations, limits, and tradeoffs of cable-embedded heat loads significantly larger than the cable losses. Both external and internal effects are modeled analytically in nondimensional terms via a Biot number analysis, allowing fundamental limits and tradeoffs to be derived. The work culminates in the design and experimental validation of a cable-embedded thermal system capable of passively dissipating 300 W of heat from a coaxial SiC mosfet switch module over a length of 20 cm, thus validating the possibility of MV cable-embedded power electronics from a thermal standpoint.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Copy number variation in pituitary stalk interruption syndrome: A large case series of sporadic non‐syndromic patients and literature review

Abstract Abnormal hypothalamic/posterior pituitary development appears to be a major determinant of pituitary stalk interruption syndrome (PSIS). The observation of familial cases and associated congenital abnormalities suggests a genetic basis. Single‐gene mutations explain less than 5% of the cases, and whole exome sequencing has shown heterogeneous results. The present study aimed to assess copy number variation (CNV) using array‐based comparative genomic hybridization (aCGH) in patients with non‐syndromic PSIS and comprehensively review data from the literature on CNV analysis in congenital hypopituitarism (CH) patients. Twenty‐one patients with sporadic CH from our outpatient clinics presented with ectopic posterior pituitary (EPP) and no central nervous system abnormalities on magnetic resonance image (MRI) or any other malformations on physical examination at presentation were enrolled in the study. aCGH using a whole‐genome customized 400K oligonucleotide platform was performed in our patients. For the literature review, we searched for case reports of patients with CH and CNV detected by either karyotype or aCGH reported in PubMed up to November 2021. Thirty‐five distinct rare CNVs were observed in 18 patients (86%) and two of them (6%) were classified as pathogenic: one deletion of 1.8 Mb in chromosome 17 (17q12) and one deletion of 15 Mb in chromosome 18 (18p11.32p11.21), each one in a distinct patient. In the literature review, 67 pathogenic CNVs were published in 83 patients with CH, including the present study. Most of these patients had EPP (78% out of the 45 evaluated by sellar MRI) and were syndromic (70%). The most frequently affected chromosomes were X, 18, 20 and 1. Our study has found that CNV can be a mechanism of genetic abnormality in non‐syndromic patients with CH and EPP. In future studies, one or more genes in those CNVs, both pathogenic and variant of uncertain significance, may be considered as good candidate genes.

Correa‐Silva, Silvia R.↗
DOE OSTI2022

Identification and distribution of pathogens coinfecting with Brucella spp., Coxiella burnetii and Rift Valley fever virus in humans, livestock and wildlife

Zoonotic diseases, such as brucellosis, Q fever and Rift Valley fever (RVF) caused by Brucella spp., Coxiella burnetii and RVF virus, respectively, can have devastating effects on human, livestock, and wildlife health and cause economic hardship due to morbidity and mortality in livestock. Coinfection with multiple pathogens can lead to more severe disease outcomes and altered transmission dynamics. These three pathogens can alter host immune responses likely leading to increased morbidity, mortality and pathogen transmission during coinfection. Developing countries, such as those commonly afflicted by outbreaks of brucellosis, Q fever and RVF, have high disease burden and thus common coinfections. A literature survey provided information on case reports and studies investigating coinfections involving the three focal diseases. Fifty five studies were collected demonstrating coinfections of Brucella spp., C. burnetii or RVFV with 50 different pathogens, of which 64% were zoonotic. While the literature search criteria involved ‘coinfection’, only 24/55 studies showed coinfections with direct pathogen detection methods (microbiology, PCR and antigen test), while the rest only reported detection of antibodies against multiple pathogens, which only indicate a history of co-exposure, not concurrent infection. These studies lack the ability to test whether coinfection leads to changes in morbidity, mortality or transmission dynamics. We describe considerations and methods for identifying ongoing coinfections to address this critical blind spot in disease risk management.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Application Experiences on a GPU-Accelerated Arm-based HPC Testbed

This paper assesses and reports the experience of ten teams working to port, validate, and benchmark several High Performance Computing applications on a novel GPU-accelerated Arm testbed system. The testbed consists of eight NVIDIA Arm HPC Developer Kit systems, each one equipped with a server-class Arm CPU from Ampere Computing and two data center GPUs from NVIDIA Corp. The systems are connected together using InfiniBand interconnect. The selected applications and mini-apps are written using several programming languages and use multiple accelerator-based programming models for GPUs such as CUDA, OpenACC, and OpenMP offloading. Working on application porting requires a robust and easy-to-access programming environment, including a variety of compilers and optimized scientific libraries. The goal of this work is to evaluate platform readiness and assess the effort required from developers to deploy well-established scientific workloads on current and future generation Arm-based GPU-accelerated HPC systems. The reported case studies demonstrate that the current level of maturity and diversity of software and tools is already adequate for large-scale production deployments.

Elwasif, Wael↗
DOE OSTI2023

Assessing the Influence of Climate on the Spatial Pattern of West Nile Virus Incidence in the United States

West Nile virus (WNV) is the leading cause of mosquito-borne disease in humans in the United States. Since the introduction of the disease in 1999, incidence levels have stabilized in many regions, allowing for analysis of climate conditions that shape the spatial structure of disease incidence. Our goal was to identify the seasonal climate variables that influence the spatial extent and magnitude of WNV incidence in humans. We developed a predictive model of contemporary mean annual WNV incidence using U.S. county-level case reports from 2005 to 2019 and seasonally averaged climate variables. We used a random forest model that had an out-of-sample model performance of R 2 =0.61. Our model accurately captured the V-shaped area of higher WNV incidence that extends from states on the Canadian border south through the middle of the Great Plains. It also captured a region of moderate WNV incidence in the southern Mississippi Valley. The highest levels of WNV incidence were in regions with dry and cold winters and wet and mild summers. The random forest model classified counties with average winter precipitation levels <23.3 mm/month as having incidence levels over 11 times greater than those of counties that are wetter. Among the climate predictors, winter precipitation, fall precipitation, and winter temperature were the three most important predictive variables. We consider which aspects of the WNV transmission cycle climate conditions may benefit the most and argued that dry and cold winters are climate conditions optimal for the mosquito species key to amplifying WNV transmission. Our statistical model may be useful in projecting shifts in WNV risk in response to climate change.

60 APPLIED LIFE SCIENCES↗