Antagonism between substitutions in β-lactamase explains a path not taken in the evolution of bacterial drug resistance
Not Available
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
SEARCH · Engineering Papers
Results for “explainable”
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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Explaining the lack of power degradation of energy confinement in wide pedestal quiescent H-modes via transport modeling
Wide pedestal quiescent H (WPQH)-mode is an attractive scenario for future burning plasmas as they operate without ELMs. WPQH is characterized by formation of a wider and higher pedestal (than quiescent H-mode), and broadband fluctuations in the pedestal. Unlike conventional H-modes, where the energy confinement time reduces with increasing heating power, the WPQH plasmas reported in this paper do not show power degradation of the energy confinement. As the injected neutral beam power was increased, reduced core (ρ ≤ 0.45) transport calculated by transp, as well as increased core temperatures, pressure gradient and diamagnetic E × B shear rate were observed. The reduction in the heat transport and rapid decrease in the ion temperature gradient scale length suggest the formation of an ion internal transport barrier (ITB) that was accompanied by increased stored energy in the core. Quasilinear turbulent transport modeling using the trapped gyro Landau fluid (tglf) code was used to predict the ITB and its turbulence stability properties. By using profiles and equilibria produced by matching the transp transport fluxes with the tglf transport model within the tgyro transport solver, the energy confinement time captures the experimentally observed insensitivity to the increased PNBI. Linear stability analysis reveals that drift-wave instabilities in the core are stabilized by E × B shear, T i /T e ratio and Shafranov shift; the latter was found to have the strongest effect on the turbulence suppression at the highest heating level.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Regulation compliant AI for fusion: explainable image-based feedback control of divertor detachment in DIII-D tokamak
While artificial intelligence (AI) has been promising for fusion control, its inherent black-box nature will make compliant implementation in regulatory environments a challenge. This study implements and validates a real-time AI-enabled linear and interpretable control system for successful divertor detachment control with the DIII-D lower divertor camera. Using D 2 gas, we demonstrate successful feedback divertor detachment control with a mean absolute difference of 2% from the target for both detachment and reattachment. This automatic training and linear processing framework can be extended to any image-based diagnostic for future fusion reactors.
computer vision↗
Soil moisture thresholds explain a shift from light-limited to water-limited sap velocity in the Central Amazon during the 2015–16 El Niño drought
Transpiration is often considered to be light- but not water-limited in humid tropical rainforests due to abundant soil water, even during the dry seasons. The record-breaking 2015–16 El Niño drought provided a unique opportunity to examine whether transpiration is constrained by water under severe lack of rainfall. We measured sap velocity, soil water content, and meteorological variables in an old-growth upland forest in the Central Amazon throughout the 2015–16 drought. We found a rapid decline in sap velocity (-38 ± 21%, mean ± SD.) and in its temporal variability (-88%) during the drought compared to the wet season. Such changes were accompanied by a marked decline in soil moisture and an increase in temperature and vapor pressure deficit. Sap velocity was largely limited by net radiation during the wet and normal dry seasons; however, it shifted to be primarily limited by soil moisture during the drought. The threshold in which sap velocity became dominated by soil moisture was at 0.33 m 3 m -3 (around -150 kPa in soil matric potential), below which sap velocity dropped steeply. Our study provides evidence for a soil water threshold on transpiration in a moist tropical forest, suggesting a shift from light limitation to water limitation under future climate characterized by increased temperature and an increased frequency, intensity, duration and extent of extreme drought events.
54 ENVIRONMENTAL SCIENCES↗
Photosynthetic decline in aging perennial grass is not fully explained by leaf nitrogen
Abstract Aging in perennial plants is traditionally observed in terms of changes in end-of-season biomass; however, the driving phenological and physiological changes are poorly understood. We found that 3-year-old (mature) stands of the perennial grass Miscanthus×giganteus had 19–30% lower Anet than 1-year-old M.×giganteus (juvenile) stands; 10–34% lower maximum carboxylation rates of Rubisco and 34% lower light-saturated Anet (Asat). These changes could be related to nitrogen (N) limitations, as mature plants were larger and had 14–34% lower leaf N on an area basis (Na) than juveniles. However, N fertilization restored Na to juvenile levels but compensated only 50% of the observed decline in leaf photosynthesis with age. Comparison of leaf photosynthesis per unit of leaf N (PNUE) showed that mature stands had at least 26% lower PNUE than juvenile stands across all N fertilization rates, suggesting that other factors, besides N, may be limiting photosynthesis in mature stands. We hypothesize that sink limitations in mature stands could be causing feedback inhibition of photosynthesis which is associated with the age-related decline in photosynthesis.
59 BASIC BIOLOGICAL SCIENCES↗
Ancient Rapid Radiation Explains Most Conflicts Among Gene Trees and Well-Supported Phylogenomic Trees of Nostocalean Cyanobacteria
Prokaryotic genomes are often considered to be mosaics of genes that do not necessarily share the same evolutionary history due to widespread horizontal gene transfers (HGTs). Consequently, representing evolutionary relationships of prokaryotes as bifurcating trees has long been controversial. However, studies reporting conflicts among gene trees derived from phylogenomic data sets have shown that these conflicts can be the result of artifacts or evolutionary processes other than HGT, such as incomplete lineage sorting, low phylogenetic signal, and systematic errors due to substitution model misspecification. Here, we present the results of an extensive exploration of phylogenetic conflicts in the cyanobacterial order Nostocales, for which previous studies have inferred strongly supported conflicting relationships when using different concatenated phylogenomic data sets. We found that most of these conflicts are concentrated in deep clusters of short internodes of the Nostocales phylogeny, where the great majority of individual genes have low resolving power. We then inferred phylogenetic networks to detect HGT events while also accounting for incomplete lineage sorting. Our results indicate that most conflicts among gene trees are likely due to incomplete lineage sorting linked to an ancient rapid radiation, rather than to HGTs. Moreover, the short internodes of this radiation fit the expectations of the anomaly zone, i.e., a region of the tree parameter space where a species tree is discordant with its most likely gene tree. In this work, we demonstrated that concatenation of different sets of loci can recover up to 17 distinct and well-supported relationships within the putative anomaly zone of Nostocales, corresponding to the observed conflicts among well-supported trees based on concatenated data sets from previous studies. Our findings highlight the important role of rapid radiations as a potential cause of strongly conflicting phylogenetic relationships when using phylogenomic data sets of bacteria. We propose that polytomies may be the most appropriate phylogenetic representation of these rapid radiations that are part of anomaly zones, especially when all possible genomic markers have been considered to infer these phylogenies.
59 BASIC BIOLOGICAL SCIENCES↗
Preserving isohydricity: vertical environmental variability explains Amazon forest water-use strategies
Abstract Increases in hydrological extremes, including drought, are expected for Amazon forests. A fundamental challenge for predicting forest responses lies in identifying ecological strategies which underlie such responses. Characterization of species-specific hydraulic strategies for regulating water-use, thought to be arrayed along an ‘isohydric–anisohydric’ spectrum, is a widely used approach. However, recent studies have questioned the usefulness of this classification scheme, because its metrics are strongly influenced by environments, and hence can lead to divergent classifications even within the same species. Here, we propose an alternative approach positing that individual hydraulic regulation strategies emerge from the interaction of environments with traits. Specifically, we hypothesize that the vertical forest profile represents a key gradient in drought-related environments (atmospheric vapor pressure deficit, soil water availability) that drives divergent tree water-use strategies for coordinated regulation of stomatal conductance (gs) and leaf water potentials (ΨL) with tree rooting depth, a proxy for water availability. Testing this hypothesis in a seasonal eastern Amazon forest in Brazil, we found that hydraulic strategies indeed depend on height-associated environments. Upper canopy trees, experiencing high vapor pressure deficit (VPD), but stable soil water access through deep rooting, exhibited isohydric strategies, defined by little seasonal change in the diurnal pattern of gs and steady seasonal minimum ΨL. In contrast, understory trees, exposed to less variable VPD but highly variable soil water availability, exhibited anisohydric strategies, with fluctuations in diurnal gs that increased in the dry season along with increasing variation in ΨL. Our finding that canopy height structures the coordination between drought-related environmental stressors and hydraulic traits provides a basis for preserving the applicability of the isohydric-to-anisohydric spectrum, which we show here may consistently emerge from environmental context. Our work highlights the importance of understanding how environmental heterogeneity structures forest responses to climate change, providing a mechanistic basis for improving models of tropical ecosystems.
Forestry↗
Boomerang mechanism explaining the excess radio background
We propose a boomerang mechanism for the explanation of the excess radio background detected by ARCADE 2. In an early stage of the Universe, at a temperature 𝑇 in the range ∼ 0.1 keV−1 MeV, a fraction of relic neutrinos is resonantly converted into dark neutrinos by mixing induced by a preexisting lepton asymmetry. Dark neutrinos decay much later into a dark-standard photon state and a dark fermion, with a lifetime longer than the age of the Universe, as required by a solution to the excess radio background. This scenario circumvents the upper bound on the neutrino magnetic moment but still implies a testable lower bound.
Dev, P. S. Bhupal [Washington Univ., St. Louis, MO↗
Explaining ( g − 2 ) μ , e , the KOTO anomaly, and the MiniBooNE excess in an extended Higgs model with sterile neutrinos
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Explaining g μ − 2 and R K ( * ) using the light mediators of U ( 1 ) T 3 R
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Self-generated cosmic-ray turbulence can explain the morphology of TeV halos
Observations have shown that spatially extended “TeV halos” are a common (and potentially generic) feature surrounding young and middle-aged pulsars. However, their morphology is not understood. They are larger than the “compact” region where the stellar remnant dominates the properties of the interstellar medium, but smaller than expected in models of cosmic-ray diffusion through the standard interstellar medium. Several explanations have been proposed, but all have shortcomings. In this work, we revisit a class of models where the cosmic-ray gradient produced by the central source induces a streaming stability that “self-confines” the cosmic-ray population. We find that previous studies significantly underpredicted the degree of cosmic-ray confinement and show that corrected models can significantly inhibit cosmic-ray diffusion throughout the TeV halo, especially when similar contributions from the coincident supernova remnant are included.
79 ASTRONOMY AND ASTROPHYSICS↗
Explaining the XENON1T Excess with Luminous Dark Matter
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72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Axion Emission Can Explain a New Hard X-Ray Excess from Nearby Isolated Neutron Stars
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79 ASTRONOMY AND ASTROPHYSICS↗
Explainable machine learning for hydrogen diffusion in metals and random binary alloys
Hydrogen diffusion in metals and alloys plays an important role in the discovery of new materials for fuel cell and energy storage technology. While analytic models use hand-selected features that have clear physical ties to hydrogen diffusion, they often lack accuracy when making quantitative predictions. Machine learning models are capable of making accurate predictions, but their inner workings are obscured, rendering it unclear which physical features are truly important. To develop interpretable machine learning models to predict the activation energies of hydrogen diffusion in metals and random binary alloys, we create a database for physical and chemical properties of the species and use it to fit six machine learning models. Our models achieve root-mean-squared errors between 98–119 meV on the testing data and accurately predict that elemental Ru has a large activation energy, while elemental Cr and Fe have small activation energies. By analyzing the feature importances of these fitted models, we identify relevant physical properties for predicting hydrogen diffusivity. While metrics for measuring the individual feature importances for machine learning models exist, correlations between the features lead to disagreement between models and limit the conclusions that can be drawn. Instead grouped feature importance, formed by combining the features via their correlations, agree across the six models and reveal that the two groups containing the packing factor and electronic specific heat are particularly significant for predicting hydrogen diffusion in metals and random binary alloys. In conclusion, this framework allows us to interpret machine learning models and enables rapid screening of new materials with the desired rates of hydrogen diffusion.
36 MATERIALS SCIENCE↗
Cooperative Interactions between Surface Terminations Explain Photocatalytic Water Splitting Activity on Sr Ti O 3
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71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Explaining Health Risk Behaviors in the U.S. with Social Deprivation at Local and Regional Levels
Health risk behaviors are precursors to many chronic health outcomes, and hence, they pose a challenge to public health. Social deprivation undoubtedly creates circumstances that limit access to healthy habits. Moreover, broad regional effects (weather patterns, political ideology, social norms), and local characteristics (cultural notions and barriers, urban places) also influence lifestyle choices and must be accounted for to truly understand the impact of social deprivation on risky behaviors. This research fills the knowledge gap in epidemiological modeling of health risk behaviors by leveraging machine learning to find associations between social deprivation and health risk behaviors, when adjusted by regional and local effects. Four health risk behaviors, namely, binge drinking, smoking, lack of sleep, and lack of physical activity from the CDC PLACES project are considered in a single framework to understand and compare the interplay between local/regional characteristics and seven measures of social deprivation. Our results indicate that local and/or regional factors rise to the top for three out of four risk behaviors (binge drinking, smoking and lack of sleep) out-competing social deprivation measures. Un-entangling the geographical effects reveals that poverty, educational attainment and non-employment are the three deprivation measures most significantly associated with all four health risk factors. The research thus indicates that public health policies to promote healthy lifestyle behaviors must seek to remedy social deprivation, but using socially and culturally sensitive interventions.
Gokhale, Swapna↗
How R Developers explain their Package Choice: A Survey
Background: Contemporary software development relies heavily on reusing already implemented functionality, usually in the form of packages. Aims: We aim to shed light on developers' preferences when selecting packages in R language. Method: To do that, we create and administer a survey to over 1000 developers who have added one of two common dataframe enhancement libraries in R to their projects: data.table or tidyr. We design a questionnaire using the Social Contagion Theory (SCT) following prior work on technology adoption and ensure that key dimensions affecting developer choice are considered. Results: Of the 1085 developers we contacted, 803 completed the survey asking them to prioritize various factors known to affect developer perceptions of package quality and to provide their background. Most developers self-identified as data scientists with two to five years of work experience. We found significant differences between the preferences of developers who chose data.table and tidyr. Surprisingly, package reputation based on easy-to-see measures, such as the number of stars on GitHub, was not an important factor for either group. Conclusions: Our findings demonstrate the inherently social nature of package adoption. They can help design future studies on how different populations of developers make decisions on which software packages to use in their projects. Finally, package developers and maintainers can benefit by better understanding the prime concerns of the users of their packages.
Malviya Thakur, Addi↗