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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess

The nature of the Fermi γ-ray Galactic Center Excess (GCE) has remained a persistent mystery for over a decade. Although the excess is broadly compatible with emission expected due to dark matter annihilation, an explanation in terms of a population of unresolved astrophysical point sources e.g., millisecond pulsars, remains viable. The effort to uncover the origin of the GCE is hampered in particular by an incomplete understanding of diffuse emission of Galactic origin. This can lead to spurious features that make it difficult to robustly differentiate smooth emission, as expected for a dark matter origin, from more “clumpy” emission expected from a population of relatively bright, unresolved point sources. Here, we use recent advancements in the field of simulation-based inference, in particular density estimation techniques using normalizing flows, in order to characterize the contribution of modeled components, including unresolved point source populations, to the GCE. Compared to traditional techniques based on the statistical distribution of photon counts, our machine learning-based method is able to utilize more of the information contained in a given model of the Galactic Center emission, and in particular can perform posterior parameter estimation while accounting for pixel-to-pixel spatial correlations in the γ-ray map. This makes the method demonstrably more resilient to certain forms of model misspecification. On application to Fermi data, the method generically attributes a smaller fraction of the GCE flux to unresolved point sources when compared to traditional approaches. We nevertheless infer such a contribution to make up a non-negligible fraction of the GCE across all analysis variations considered, with at least $38^{+9}_{-19}$% of the excess attributed to unresolved point sources in our baseline analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Observing signals of spectral features in the cosmic-ray positrons and electrons from Milky Way pulsars

The Alpha Magnetic Spectrometer (AMS-02) has provided unprecedented precision measurements of the electron and positron cosmic-ray fluxes and the positron fraction spectrum. At the higher energies, sources as energetic local pulsars, may contribute to both cosmic-ray species. The discreteness of the source population, can result in features both on the positron fraction measurement and in the respective electron and positron spectra. For the latter, those would coincide in energy and would contrast predictions of smooth spectra as from particle dark matter. In this work, using a library of pulsar population models for the local part of the Milky Way, we perform a power-spectrum analysis on the cosmic-ray positron fraction. We also develop a technique to cross-correlate the electron and positron fluxes. We show that both such analyses, can be used to search statistically for the presence of spectral wiggles in the cosmic-ray data. For a significant fraction of our pulsar simulations, those techniques are already sensitive enough to give a signal for the presence of those features above the regular noise, with forthcoming observations making them even more sensitive. Lastly, by cross-correlating the AMS-02 electron and positron spectra, we find an intriguing first hint for a positive correlation between them, of the kind expected by a population of local pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

New determination of the millisecond pulsar gamma-ray luminosity function and implications for the Galactic Center gamma-ray excess

It has been suggested that the Galactic Center gamma-ray excess (GCE) could be produced by a large number of centrally located millisecond pulsars. The fact that no such pulsar population has been detected implies that these sources must be very faint and very numerous. Here, in this study, we use the contents of Fermi’s recently released Third Pulsar Catalog (3PC) to measure the luminosity function of the millisecond pulsars in the Milky Way’s disk. We find that this source population exhibits a luminosity function with a mean γ -ray luminosity of ⟨ L γ ⟩ ∼ 6 × 10 32 erg / s (integrated above 0.1 GeV). If the GCE were generated by millisecond pulsars with the same luminosity function, we find that ∼ 20 such sources from the inner Galaxy population should have already been detected by Fermi and included in the 3PC. Given the lack of such observed sources, we exclude the hypothesis that the GCE is generated by pulsars with the same luminosity function as those in the Galactic disk with a significance of 3.4 σ . We conclude that either less than 39% of the GCE is generated by pulsars, or that the millisecond pulsars in the inner Galaxy are at least 5 times less luminous on average than those found in the Galactic disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Water dynamics in pristine and porous Ti 3 C 2 T x MXene as probed by quasielastic neutron scattering

MXenes are a novel class of two-dimensional (2D) materials whose applications in energy-storage systems have attracted substantial attention. Still, the rate performance of these materials is often diminished by sheet restacking, which is attenuated via controlled etching in H 2 SO 4 solution. With this process, micropores are formed in MXene sheets that allow transport across 2D layers. As a result, the intercalation and diffusivity of ions are facilitated resulting in improved capacitance retention at high charge-discharge rates. In the present work, we used quasielastic neutron scattering to evaluate the potential changes in water dynamics as a consequence of this mechanism by assessing the behavior of weakly and strongly confined water populations in pristine and porous MXenes. First, we have found that the porous sample accommodates a noticeably higher content of both water populations. Additionally, the fraction of mobile molecules is higher either under strong or weak confinement. Interestingly, regardless of the abundance of weakly confined water in the porous sample, no considerable changes in the dynamical behavior were detected in comparison with the dynamics measured in the pristine material. Finally, for the strongly confined populations of water, our results show that water is able to permeate the micropores introduced by etching and perform unlocalized motions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Novel Machine Learning Workflow to Classify Mobile Home Parks at Scale

Understanding the built environment is essential to the overall study of population dynamics, grid infrastructure, emergency response, among others. In the United States there are multiple classifications for buildings within the built environment such as residential, signifying family homes while commercial buildings consist of apartments or larger structures which are multi-purpose. While there is a high level of understanding of where these aforementioned structures are located, there is a third class of structures, mobile home parks (MHP) which have been under-represented in the literature despite there being an estimated 2.7 million of them within the United States. Research has shown that individuals who reside in MHP are at higher risk to extreme events due to their location and structural integrity of residence. Attention must now turn to identifying MHP at scale to help first responders and policy makers understand where these at risk populations reside. To address for this gap, we develop a novel methodology to infer MHP at scale based off morphologies derived at a building level. Here, we show that across 3 million buildings in 6 states within the United States it is possible to identify MHP with 83% accuracy. This novel approach to identify MHP from other structures within the built environment using a machine learning approach provides a new tool to leverage in relation to helping at-risk populations.

Stipek, Clinton [Oak Ridge National Laboratory (OR↗
DOE OSTI2020

Effects of social structure and management on risk of disease establishment in wild pigs

Contact heterogeneity among hosts determines invasion and spreading dynamics of infectious disease, thus its characterization is essential for identifying effective disease control strategies. Yet, little is known about the factors shaping contact networks in many 28 wildlife species and how wildlife management actions might affect contact networks. Wild pigs in North America are an invasive, socially-structured species that pose a health concern for domestic swine given their ability to transmit numerous devastating diseases 2 such as African swine fever (ASF). Using proximity loggers and GPS data from 48 wild pigs in Florida and South Carolina, USA, we employed a probabilistic framework to estimate weighted contact networks. We determined the effects of sex, social group, and spatial distribution (monthly home range overlap and distance) on wild pig contact. We also estimated the impacts of management-induced perturbations on contact and inferred their effects on ASF establishment in wild pigs with simulation. Social group membership was the primary factor influencing contacts. Between-group contacts depended primarily on space use characteristics, with fewer contacts among groups separated by >2 km and no contacts among groups >4 km apart within a month. Modeling ASF dynamics on the contact network demonstrated that indirect contacts resulting from baiting (a typical method of attracting wild pigs or game species to a site to enhance recreational hunting) increased the risk of disease establishment by ~33% relative to direct contact. Low-intensity population reduction (<5.9% of the population) had no detectable impact on contact structure but reduced predicted ASF establishment risk relative to no population reduction. Here, we demonstrate an approach for understanding the relative role of spatial, social, and individual-level characteristics in shaping contact networks and predicting their effects on disease establishment risk, thus providing insight for optimizing disease control in spatially- and socially-structured wildlife species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optimizing invader suppression to restore native species: Leveraging species traits to overcome collateral damage

Strategies to control ongoing biological invasions are often developed by modelling the invasive species' population and aiming to reduce its abundance. However, if the ultimate objective is to protect and restore native species, focussing solely on the invader may not be optimal because it does not account for (i) species interactions that can cause the invader's impacts to depend nonlinearly on its abundance, (ii) collateral damages to native species incurred due to nonspecific removal methods or (iii) native-invader trait differences. Here, to identify an invader suppression strategy that maximizes average native population size, we applied optimal control theory to a two-species model of a native species threatened by an invasive competitor. We examined trade-offs between iterative physical removals that selectively target invaders and intensifiable chemical control that is nonselective but has higher efficacy. We found that while iterative removals were capable of supporting large native populations when applied continuously, cost could be prohibitively high. In contrast, when favourable native-invader trait differences enabled native species to re-establish more quickly than invaders, intensifiable methods could achieve substantial restoration benefits at lower cost by focussing removal effort into periodic, high-efficacy events. In a metapopulation, removals that rotated among spatial patches were optimal when the native species had higher dispersal, whereas synchronous removals were preferred when native recovery was initiated locally and the invader could disperse. For a case study in Hawaiian streams, we compared how effective two alternative methods of removing invasive live-bearing fishes (poeciliids) might be at restoring the endemic freshwater goby Sicyopterus stimpsoni. We found that rotenone (a piscicidal chemical) offered superior benefits when the control budget was small and efficacy was high, but that electrofishing (use of electricity to manually collect target fish) was better with larger budgets and in many lower-efficacy scenarios. Synthesis and applications. Our findings demonstrate that, by accounting for species interactions and collateral damage, invasive species control strategies can be optimized in light of species traits. Choices about the timing, locations and types of removal events present opportunities to increase the efficiency with which invasive species suppression benefits native species.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Genotype–environment associations across spatial scales reveal the importance of putative adaptive genetic variation in divergence

Abstract Identifying areas of high evolutionary potential is a judicious strategy for developing conservation priorities in the face of environmental change. For wide‐ranging species occupying heterogeneous environments, the evolutionary forces that shape distinct populations can vary spatially. Here, we investigate patterns of genomic variation and genotype–environment associations in the hermit thrush ( Catharus guttatus ), a North American songbird, at broad (across the breeding range) and narrow spatial scales (at a hybrid zone). We begin by building a genoscape or map of genetic variation across the breeding range and find five distinct genetic clusters within the species, with the greatest variation occurring in the western portion of the range. Genotype–environment association analyses indicate higher allelic turnover in the west than in the east, with measures of temperature surfacing as key predictors of putative adaptive genomic variation rangewide. Since broad patterns detected across a species' range represent the aggregate of many locally adapted populations, we investigate whether our broadscale analysis is consistent with a finer scale analysis. We find that top rangewide temperature‐associated loci vary in their clinal patterns (e.g., steep clines vs. fixed allele frequencies) across a hybrid zone in British Columbia, suggesting that the environmental predictors and the associated candidate loci identified in the rangewide analysis are of variable importance in this particular region. However, two candidate loci exhibit strong concordance with the temperature gradient in British Columbia, suggesting a potential role for temperature‐related barriers to gene flow and/or temperature‐driven ecological selection in maintaining putative local adaptation. This study demonstrates how patterns identified at the broad (macrogeographic) scale can be validated by investigating genotype–environment correlations at the local (microgeographic) scale. Furthermore, our results highlight the importance of considering the spatial distribution of putative adaptive variation when assessing population‐level sensitivity to climate change and other stressors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A genomic region associated with iteroparous spawning phenology is linked with age‐at‐maturity in female steelhead trout

Abstract Age‐at‐maturity and iteroparity are two life history variations of steelhead trout ( Oncorhynchus mykiss ) that are believed to increase population resilience and stability. While repeat‐spawning individuals are thought to have historically made up a substantial portion of the reproductive population in the Columbia River and the majority of females still attempt outmigration as kelts, return rates of repeat‐spawner are low throughout the basin and below 1% for the furthest migrating stocks. Notably, outmigrating adults exhibit variation in rematuration phenology, displaying either “consecutive” (reproduce immediately the following season) or “skip” (delay spawning for future seasons) spawning patterns. Here, we use low coverage whole genome sequencing of consecutive versus skip spawning female Columbia River steelhead from two populations to test for genomic differences between these two iteroparous phenotypes. We identified genomic regions on several chromosomes which were associated with the phenology of iteroparity, including a region on chromosome 25 containing two genes, estradiol receptor beta ( ER β) and glycoprotein hormone beta‐5 ( GPHB5 ), which, in mammals, are estrogen‐sensitive and expressed in reproductive tissues. Allele frequencies in this ER β/ GPHB5 region differed among female steelhead of different age at maturity, but not males. These genes also shared an island of linkage disequilibrium with the SIX6 gene, 600Kbp away on the same chromosome, a region of known association with age‐at‐maturity. These observations contribute to growing evidence that age‐at‐maturity and the phenology of iteroparity are determined by overlapping physiological processes and genetic pathways.

Willis, Stuart↗
DOE OSTI2023

Genetic variation associated with adult migration timing in lineages of Steelhead and Chinook Salmon in the Columbia River

Abstract With the discovery of a major effect region (GREB1L, ROCK1) for adult migration timing in genomes of both Chinook Salmon and Steelhead, several subsequent studies have investigated the effect size and distribution of early and late migration alleles among populations in the Columbia River. Here, we synthesize the results of these studies for the major lineages of Chinook Salmon and Steelhead that include highly distinct groups in the interior Columbia River that exhibit atypical life histories from most coastal lineage populations of these two species. Whole‐genome studies with high marker density have provided extensive insight into SNPs most associated with adult migration timing, and suites of markers for each species have been genotyped in large numbers of individuals to further validate phenotypic effects. For Steelhead, the largest phenotypic effect sizes have been observed in the coastal lineage (36% of variation for passage timing at Bonneville Dam; 43% of variation for tributary arrival timing) compared to the inland lineage (7.5% of variation for passage timing at Bonneville Dam; 8.4% of variation for tributary arrival timing) that overwinter in freshwater prior to spawning. For Chinook Salmon, large effect sizes have been observed in all three lineages for multiple adult migration phenotypes (Coastal lineage: percentage of variation of 27.9% for passage timing at Bonneville Dam, 28.7% for arrival timing for spawning; Interior ocean type: percentage of variation of 47.6% for passage timing at Bonneville Dam, 39.6% for tributary arrival timing, 77.9% for arrival timing for spawning; Interior stream type: percentage of variation of 35.3% for passage at Bonneville Dam, 9.8% for tributary arrival timing, 4.7% for arrival timing for spawning). Together, these results have extended our understanding of genetic variation associated with life history diversity in distinct populations of the Columbia River, however, much research remains necessary to determine the causal mechanism for this major effect region on migration timing in these species.

Narum, Shawn R.↗
DOE OSTI2022

Biomass yield improvement in switchgrass through genomic prediction of flowering time

The seasonal timing of the transition from vegetative to reproductive growth has a major impact on biomass accumulation in switchgrass. Late-flowering switchgrass cultivars produce greater biomass, a critical trait for sustainable bioenergy production. Genomic prediction (GP) may allow rapid selection of late-flowering individuals with reduced time and expense for field evaluations. To evaluate GP, two flowering time traits (heading date and anthesis date) were collected on 1532 genotypes from four breeding populations: Midwest, Gulf, Atlantic, and Hybrid. These were sequenced using genotype-by-sequencing (530,792 single-nucleotide polymorphisms). Predictive ability of single-trait and multi-trait models were evaluated by cross-validation, by prediction of a progeny trial (n = 122), and through prediction of yield performance in a parallel experiment (n = 52). Predictive ability was not improved by sharing information among breeding groups. Overall, multi-trait models provided an advantage during cross-validation, but a smaller advantage during progeny prediction. Within populations, GP resulted in lower per-cycle progress than previously reported field evaluations (3.1 vs. 5.0 day –1 cycle –1 ). However, GP cycles are potentially much faster than field evaluations. When directly predicting biomass yield, the Hybrid training population had a predictive ability of 0.54–0.63. This reinforces the strong linkage between biomass yields in swards and flowering time. Furthermore, these results highlight the value of GP for rapid yield improvement in switchgrass, particularly in a breeding program designed to share information between biomass yield trials and low-cost flowering time evaluations.

09 BIOMASS FUELS↗
DOE OSTI2024

Improving precision and accuracy of genetic mapping with genotyping‐by‐sequencing data in outcrossing species

Abstract Genotyping‐by‐sequencing (GBS) is a widely used strategy for obtaining large numbers of genetic markers in model and non‐model organisms. In crop plants, GBS‐derived marker datasets are frequently used to perform quantitative trait locus (QTL) mapping. In some plant species, however, high heterozygosity and complex genome structure mean that researchers must use care in handling GBS data to conduct QTL mapping most effectively. Such outbred crops include most of the perennial grass and tree species used for bioenergy. To identify strategies for increasing accuracy and precision of QTL mapping using GBS data in outbred crops, we conducted an empirical study of SNP‐calling and genetic map‐building pipeline parameters in a Miscanthus sinensis population, and a complementary simulation study to estimate the relationship between genome‐wide error rate, read depth, and marker number. The bioenergy grass Miscanthus is an obligate outcrossing species with a recent (diploidized) whole‐genome duplication. For the study of empirical M. sinensis data, we compared two SNP‐calling methods (one non‐reference‐based and one reference‐based), a series of depth filters (12×, 20×, 30×, and 40×) and two map‐construction methods (i.e., marker ordering: linkage‐only and order‐corrected based on a reference genome). We found that correcting the order of markers on a linkage map by using a high‐quality reference genome improved QTL precision (shorter confidence intervals). For typical GBS datasets of between 1000 and 5000 markers to build a genetic map for biparental populations, a depth filter set at 30× to 40× applied to outbred populations provided a genome‐wide genotype‐calling error rate of less than 1%, improved accuracy of QTL point estimates and minimized type I errors for identifying QTL. Based on these results, we recommend using a reference genome to correct the marker order of genetic maps and a robust genotype depth filter to improve QTL mapping for outbred crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Accuracy of self‐reported weight, height and body mass index among older people in Japan

Aim Weight and height are usually self‐reported in population‐based epidemiological surveys. While the accuracy of self‐reports has been extensively studied in younger populations, less is known in older populations. We investigated the accuracy of self‐reported weight, height and body mass (BMI) in an older cohort in Japan, where overweight/obesity and underweight coexist. Methods We used data from older Japanese adults (≥65 years) participating in the Japan Gerontological Evaluation Study in 2016 to 2017 (7357 men and 9271 women). Self‐report data were linked to objective data obtained from clinical examinations. Results The mean ± standard deviation (SD) age was 74.5 ± 5.8 years, mean ± SD weight, height and BMI were 55.7 ± 10.1 kg, 156.0 ± 8.9 cm and 22.8 ± 3.1, respectively. Results showed high intraclass correlation coefficients for self‐reported and measured values (0.97 for weight; 0.96 for height). While weight/height were overestimated among men (weight by 0.096 kg; height by 0.27 cm) and women (weight by 0.18 kg; height by 0.27 cm), BMI tended to be slightly underestimated (−0.034 kg/m 2 for men; −0.037 kg/m 2 for women). However, the absolute differences between self‐reported and measured values were not negligible; people had a higher risk for both under‐ and overestimation of their BMI category with increasing age. Lower education predicted BMI overestimation, whereas lower income predicted BMI underestimation. Conclusions Overall accuracy of self‐reported body habitus was higher in this cohort of older Japanese compared with previous reports. Nevertheless, misclassification of BMI due to the misreporting of their weight/height was more common among the oldest‐old, as well as those with lower education and income. Geriatr Gerontol Int 2020; 20: 803–810 .

Yazawa, Aki↗
DOE OSTI2025

Fate of Listeria monocytogenes Serotypes on Frozen Mixed Vegetables During Consumer‐Simulated Thawing and Storage

ABSTRACT Recent outbreaks and recalls associated with frozen vegetables in the United States and Europe have been linked to Listeria monocytogenes . This study aims to understand the extent to which frozen vegetables support the growth of L. monocytogenes once thawed and held at different temperatures. Six L. monocytogenes strains, two of each from serotypes 1/2a, 1/2b, and 4b, were individually inoculated onto frozen vegetables and stored at −18°C for 7 days. After 7 days, the vegetables were thawed and stored at 5°C or 10°C for up to 14 days or at 25°C for up to 7 days. L. monocytogenes was enumerated from the thawed vegetables throughout the storage period. Population data were fitted to the primary Baranyi model to estimate growth rates and lag phase durations; the secondary Ratkowsky square root model was used to model the relationship of the growth rates with storage temperature. Five of the L. monocytogenes strains survived and grew on the thawed vegetables (population increases of > 1 log CFU/g) stored at 5°C, and all six of the strains proliferated at 10°C and 25°C (population increases of > 3 log CFU/g after 14 days and > 4 log CFU/g after 7 days, respectively). A secondary model was successfully generated based on the growth rates of the six L. monocytogenes strains on the thawed vegetables ( r 2 = 0.8888, RMSE = 0.2057). Results from this study fill a data gap associated with L. monocytogenes survival on thawed vegetables and can be used to determine safe handling and storage practices for these products to protect public health.

Salazar, Joelle K. [Division of Food Processing Sc↗
DOE OSTI2025

Geographic, sectoral, and constituent characteristics of US off‐site manufacturing wastewater disposal

This study employs recent US Environmental Protection Agency off-site manufacturing wastewater disposal data and a socioenvironmental assessment tool for the United States to understand the characteristics of such disposal in terms of geography, major contributing sectors and pollutants, and environmental impacts. Environmental impact analyses of manufacturing are insufficient without encompassing the extended physical boundary of waste management. Our analysis reveals that off-site manufacturing wastewater disposal occurs disproportionately in populations residing in census tracts already negatively impacted by environmental hazards (impacted populations, or IPs) with 44% of transfers and 55% of Risk Screening Environmental Indicators (RSEI) Hazard going to these areas, compared to their national share of 37%. Disposal hazard is concentrated in a small number of populations, with a Gini coefficient of 0.99 for RSEI Hazard. Four manufacturing sub-sectors are significant generators: Chemicals, Fabricated Metals, Primary Metals, and Transportation Equipment, with Chemicals off-site wastewater disposal largely occurring in IPs. For individual contaminants, chromium compounds and chromium represent more than 85% of the hazard but less than 10% of transfers. We explore transfer distances and waste generation and disposal hotspots, finding that the Midwest hosts a disproportionate share of off-site wastewater disposal. Further, RSEI Hazard steeply rises at shorter distances and plateaus over distances >500 miles, revealing opportunities to reduce hazard by reducing 20–500-mile transfers. Our findings strongly support targeted mitigation strategies like process substitutions, control technologies, on-site recycling and treatment, and minimizing transfer distances. This article met the requirements for a gold-gold JIE data openness badge described at http://jie.click/badges.

Fuchs, Heidi [Lawrence Berkeley National Laborator↗
DOE OSTI2023

A common resequencing‐based genetic marker data set for global maize diversity

SUMMARY Maize ( Zea mays ssp. mays ) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole‐genome resequencing strategies, identifying millions of segregating single‐nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high‐confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering‐time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A large sequenced mutant library – valuable reverse genetic resource that covers 98% of sorghum genes

SUMMARY Mutant populations are crucial for functional genomics and discovering novel traits for crop breeding. Sorghum , a drought and heat‐tolerant C4 species, requires a vast, large‐scale, annotated, and sequenced mutant resource to enhance crop improvement through functional genomics research. Here, we report a sorghum large‐scale sequenced mutant population with 9.5 million ethyl methane sulfonate (EMS)‐induced mutations that covered 98% of sorghum's annotated genes using inbred line BTx623. Remarkably, a total of 610 320 mutations within the promoter and enhancer regions of 18 000 and 11 790 genes, respectively, can be leveraged for novel research of cis ‐regulatory elements. A comparison of the distribution of mutations in the large‐scale mutant library and sorghum association panel (SAP) provides insights into the influence of selection. EMS‐induced mutations appeared to be random across different regions of the genome without significant enrichment in different sections of a gene, including the 5′ UTR, gene body, and 3′‐UTR. In contrast, there were low variation density in the coding and UTR regions in the SAP. Based on the K a / K s value, the mutant library (~1) experienced little selection, unlike the SAP (0.40), which has been strongly selected through breeding. All mutation data are publicly searchable through SorbMutDB ( https://www.depts.ttu.edu/igcast/sorbmutdb.php ) and SorghumBase ( https://sorghumbase.org/ ). This current large‐scale sequence‐indexed sorghum mutant population is a crucial resource that enriched the sorghum gene pool with novel diversity and a highly valuable tool for the Poaceae family, that will advance plant biology research and crop breeding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Atomic-Level, Energy-Conversion Heat Transfer

Abstract Heat is stored in quanta of kinetic and potential energies in matter. The temperature represents the equilibrium and excited occupation (boson) of these energy conditions. Temporal and spatial temperature variations and heat transfer are associated with the kinetics of these equilibrium excitations. During energy-conversion (between electron and phonon systems), the occupancies deviate from equilibria, while holding atomic-scale, inelastic spectral energy transfer kinetics. Heat transfer physics reaches nonequilibrium energy excitations and kinetics among the principal carriers, phonon, electron (and holes and ions), fluid particle, and photon. This allows atomic-level tailoring of energetic materials and energy-conversion processes and their efficiencies. For example, modern thermal-electric harvesters have transformed broad-spectrum, high-entropy heat into a narrow spectrum of low-entropy emissions to efficiently generate thermal electricity. Phonoelectricity, in contrast, intervenes before a low-entropy population of nonequilibrium optical phonons becomes a high-entropy heat. In particular, the suggested phonovoltaic cell generates phonoelectricity by employing the nonequilibrium, low-entropy, and elevated temperature optical-phonon produced population—for example, by relaxing electrons, excited by an electric field. A phonovoltaic material has an ultranarrow electronic bandgap, such that the hot optical-phonon population can relax by producing electron-hole pairs (and power) instead of multiple acoustic phonons (and entropy). Examples of these quanta and spectral heat transfer are reviewed, contemplating a prospect for education and research in this field.

Engineering↗