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At least 1,279 records · Page 71

Phylodynamic Inference across Epidemic Scales

Within-host genetic diversity and large transmission bottlenecks confound phylodynamic inference of epidemiological dynamics. Conventional phylodynamic approaches assume that nodes in a time-scaled pathogen phylogeny correspond closely to the time of transmission between hosts that are ancestral to the sample. However, when hosts harbor diverse pathogen populations, node times can substantially pre-date infection times. Imperfect bottlenecks can cause lineages sampled in different individuals to coalesce in unexpected patterns. To address realistic violations of standard phylodynamic assumptions we developed a new inference approach based on a multi-scale coalescent model, accounting for nonlinear epidemiological dynamics, heterogeneous sampling through time, non-negligible genetic diversity of pathogens within hosts, and imperfect transmission bottlenecks. We apply this method to HIV-1 and Ebola virus (EBOV) outbreak sequence data, illustrating how and when conventional phylodynamic inference may give misleading results. Within-host diversity of HIV-1 causes substantial upwards bias in the number of infected hosts using conventional coalescent models, but estimates using the multi-scale model have greater consistency with reported number of diagnoses through time. In contrast, we find that within-host diversity of EBOV has little influence on estimated numbers of infected hosts or reproduction numbers, and estimates are highly consistent with the reported number of diagnoses through time. The multi-scale coalescent also enables estimation of within-host effective population size using single sequences from a random sample of patients. We find within-host population genetic diversity of HIV-1 p17 to be 2Nμ=0.012 (95% CI 0.0066–0.023), which is lower than estimates based on HIV envelope serial sequencing of individual patients.

59 BASIC BIOLOGICAL SCIENCES↗

Communications Network

The Multi-Compatible Network Interface Unit (MCNIU) is intended to connect the space station's communications and tracking, guidance and navigation, life support, electric power, payload data, hand controls, display consoles and other systems, and also communicate with diverse processors. Honeywell is now marketing MCNIU commercially. It has applicability in certain military operations or civil control centers. It has nongovernment utility among large companies, universities and research organizations that transfer large amounts of data among workstations and computers. *This product is no longer commercially available.

Source record↗

Data-driven analysis and prediction of stable phases for high-entropy alloy design

High-entropy alloys (HEAs) represent a promising class of materials with exceptional structural and functional properties. However, their design and optimization pose challenges due to the large composition-phase space coupled with the complex and diverse nature of the phase formation dynamics. In this study, a data-driven approach that utilizes machine learning (ML) techniques to predict HEA phases and their composition-dependent phases is proposed. By employing a comprehensive dataset comprising 5692 experimental records encompassing 50 elements and 11 phase categories, we compare the performance of various ML models. Our analysis identifies the most influential features for accurate phase prediction. Furthermore, the class imbalance is addressed by employing data augmentation methods, raising the number of records to 1500 in each category, and ensuring a balanced representation of phase categories. The results show that XGBoost and Random Forest consistently outperform the other models, achieving 86% accuracy in predicting all phases. Additionally, this work provides an extensive analysis of HEA phase formers, showing the contributions of elements and features to the presence of specific phases. We also examine the impact of including different phases on ML model accuracy and feature significance. Notably, the findings underscore the need for ML model selection based on specific applications and desired predictions, as feature importance varies across models and phases. This study significantly advances the understanding of HEA phase formation, enabling targeted alloy design and fostering progress in the field of materials science.

36 MATERIALS SCIENCE↗

Building and testing correlations for the estimation of one‐electron reduction potentials of a diverse set of organic molecules

We describe and evaluate a method for computationally predicting reduction potentials of a diverse group of organic molecules by linearly correlating calculated lowest unoccupied molecular orbital energies with ground state reduction potentials measured in acetonitrile. The approach is shown to provide a unique combination of extreme computational simplicity and excellent accuracy across a diverse range of organic structures and a wide window of reduction potentials. A disparate set of molecules (74 compounds belonging to six distinct structural families, comprised of molecules containing C, H, N, O, F, Cl, and Br, with functional groups including esters, ketones, halides, nitriles, quinones, alkenes, arenes, heteroarenes, and pyridinium and higher benzologs, all containing conjugated pi systems, spanning a 3.5‐V range of reduction potentials) was used to build the correlations. This methodology was found to be computationally inexpensive compared with other approaches and to permit the useful prediction of reduction potentials of additional molecules of diverse structural types not included in the families used to determine the correlation parameters. The effects of varying the basis set used in the B3LYP electronic structure calculations and including solvent (compared with calculations in gas phase) were also examined. It was found that the inclusion of a continuum solvent model in the calculations was required for accurate results, particularly when including cationic species in the correlations (although when only neutral molecules were examined, reasonable results could even be obtained in vacuo ). Several of the best correlations were used to predict the reduction potentials of seven much larger and structurally diverse chromophores that were not included in the correlation data set. Strong correlations ( r 2 values > 0.99) with very good predictive abilities (root mean square deviation < 60 mV) were found. This extremely simple and computationally efficient entirely closed‐shell methodology is proven robust and useful for the design of new molecules capable of participating in redox processes, including electron transfer reactions. Copyright © 2015 John Wiley & Sons, Ltd.

Méndez‐Hernández, Dalvin D.↗

Software and Hardware Systems in the Safety Control Systems of Nuclear Power Plants

Fundamentally new software and hardware systems for lower level automation in the safety monitoring and control systems of nuclear power plants are examined. More than a hundred software-hardware systems employing software and hardware from different manufacturers have been developed and introduced in this area. Design and functional solutions based on specific software-hardware systems are presented and comparative data on the apparatus and the use of the diversity principle are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Crystal misorientation correlates with hardness in tooth enamels

The multi-scale hierarchical structure of tooth enamel enables it to withstand a lifetime of damage without catastrophic failure. While many previous studies have investigated structure-function relationships in enamel, the effects of crystal misorientation on mechanical performance have not been assessed. To address this issue, in the present study, we review previously published polarization-dependent imaging contrast (PIC) maps of mouse and human enamel, and parrotfish enameloid, in which crystal orientations were measured and displayed in every 60-nm-pixel. By combining those previous results with the PIC maps of sheep enamel presented here we discovered that, in all enamel(oid)s, adjacent crystals are slightly misoriented, with misorientation angles in the 0°-30° range, and mean 2°-8°. Within this limited range, misorientation is positively correlated with literature hardness values, demonstrating an important structure-property relation, not previously identified. At greater misorientation angles 8°30°, this correlation is expected to reverse direction, but data from different non-enamel systems, with more diverse crystal misorientations, are required to determine if and where this occurs.

36 MATERIALS SCIENCE↗

The challenge of assessing social dimensions of avoided deforestation: Examples from Cambodia

Reduced Emissions from Deforestation and Forest Degradation in developing countries (REDD +) has moved to the central stage of the climate change debate by being promoted as a significant, cheap, and quick win-win strategy to reduce greenhouse gas emissions and thereby mitigate climate change. In order to be successful in reducing emissions while providing the projected social and environmental co-benefits, REDD + needs to overcome key challenges of insecure forest tenure and inequity in the distribution of benefits. Such challenges threaten to affect the livelihoods and well-being in the local communities and in turn the effectiveness of REDD+. While REDD + programs will affect the participating communities, there is limited knowledge as to what social impacts these projects may bring to the local population. Similarly, assessment of these social dimensions has received little attention until recently, and is consequently out of sync with the realities of REDD + projects. The present paper aims to shed light on the methodological and contextual challenges in the assessment of the social dimensions of REDD+. Some of the main social concerns of REDD + are outlined with an emphasis on the uniqueness and complexity of REDD + interventions. Recently proposed approaches to assess social impacts in REDD + are critically assessed in terms of the diversity of frameworks proposed, choice of social indicators, and data collection requirements. Specifically, these methodological implications are further discussed in the light of the social dimensions and the prescribed regulations of REDD + in a Cambodian context. - Highlights: Black-Right-Pointing-Pointer Insecure tenure and inequitable benefit sharing are main social concerns in REDD +. Black-Right-Pointing-Pointer Two guides to social assessments in REDD + are critically reviewed. Black-Right-Pointing-Pointer Mismatch between social assessment requirements and the reality of REDD + is analyzed. Black-Right-Pointing-Pointer Concrete, topical examples from Cambodian REDD + are used. Black-Right-Pointing-Pointer Support the claim to add qualitative assessment of social dimensions in REDD +.

54 ENVIRONMENTAL SCIENCES↗

Standard methods for heat capacity measurements on a Quantum Design Physical Property Measurement System

The commercial availability of the Physical Property Measurement System (PPMS) by Quantum Design has significantly increased access to heat capacity measurements on a wide variety of materials. Although the PPMS can routinely measure the heat capacities of thermally conducting materials with high accuracy, specialized sample mounting techniques must be used for insulating powders, and the analysis of first order transitions also requires non-standard methods. The concern is that many users are not aware of these constraints when measuring the heat capacity of a diverse array of materials, and therefore, the heat capacity data reported in the literature can be unreliable. In this paper, we provide an extensive and critical review of the heat capacity data reported in the literature measured using the Quantum Design PPMS. The purpose is to provide a de facto standard for sample mounting and data analysis methods suitable for the reporting of accurate thermodynamic data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics

Modern microbial mats are potential analogues of some of Earth’s earliest ecosystems. Excellent examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our understanding of the functional genetic potential of these complex microbial ecosystems, we conducted for the first time shotgun metagenomic analyses. We assembled metagenomic nextgeneration sequencing data to classify the taxonomic and metabolic potential across diverse morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications using protein-coding and small subunit rRNA genes directly extracted from the metagenomes suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marine mats. However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas) marine systems appears to be distinct from each other. The metabolic potential (based on SEED subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are highly represented in Shark Bay and may have critical roles in overall ecosystem function in these modern microbial mats.

Ruvindy, Rendy↗

Capturing the genetic makeup of the active microbiome in situ

More than any other technology, nucleic acid sequencing has enabled microbial ecology studies to be complemented with the data volumes necessary to capture the extent of microbial diversity and dynamics in a wide range of environments. In order to truly understand and predict environmental processes, however, the distinction between active, inactive and dead microbial cells is critical. Also, experimental designs need to be sensitive toward varying population complexity and activity, and temporal as well as spatial scales of process rates. There are a number of approaches, including single-cell techniques, which were designed to study in situ microbial activity and that have been successively coupled to nucleic acid sequencing. The exciting new discoveries regarding in situ microbial activity provide evidence that future microbial ecology studies will indispensably rely on techniques that specifically capture members of the microbiome active in the environment. Herein, we review those currently used activity-based approaches that can be directly linked to shotgun nucleic acid sequencing, evaluate their relevance to ecology studies, and discuss future directions.

59 BASIC BIOLOGICAL SCIENCES↗

Static characterization of a highly optimized streak tube design incorporating a steering slot anode and an aberration-corrected Einzel lens

The BHx streak tube, under development at the Laboratory for Laser Energetics, incorporates a series of novel electron-optics elements to enable high fidelity measurements for high-energy-density physics experiments. The system is engineered to support a 25-mm active photocathode region compatible with sub-picosecond temporal resolution and with 70% internal photoelectron throughput. It exhibits negligible geometric distortion on a flat output screen, making it well suited for variety of measurements, such as ultrafast x-ray spectroscopy. Here, this paper presents characterization data from a prototype unit tested with an ultraviolet laser in a static deflection (non-swept) mode and shows good agreement with the predictions from numerical modeling, including focusing performance and geometric distortion measurements. Key design elements have been demonstrated and de-risked, laying the foundation for dynamic deflection testing. The anticipated improvements in data fidelity are expected to impact the fields as diverse as inertial confinement fusion, laboratory astrophysics, and materials science.

High energy density physics↗

EXTINCTION AND DUST GEOMETRY IN M83 H II REGIONS: AN HUBBLE SPACE TELESCOPE/WFC3 STUDY

We present Hubble Space Telescope/WFC3 narrow-band imaging of the starburst galaxy M83 targeting the hydrogen recombination lines (Hβ, Hα, and Paβ), which we use to investigate the dust extinction in the H II regions. We derive extinction maps with 6 pc spatial resolution from two combinations of hydrogen lines (Hα/Hβ and Hα/Paβ), and show that the longer wavelengths probe larger optical depths, with A{sub V} values larger by ≳1 mag than those derived from the shorter wavelengths. This difference leads to a factor ≳2 discrepancy in the extinction-corrected Hα luminosity, a significant effect when studying extragalactic H II regions. By comparing these observations to a series of simple models, we conclude that a large diversity of absorber/emitter geometric configurations can account for the data, implying a more complex physical structure than the classical foreground ''dust screen'' assumption. However, most data points are bracketed by the foreground screen and a model where dust and emitters are uniformly mixed. When averaged over large (≳100-200 pc) scales, the extinction becomes consistent with a ''dust screen'', suggesting that other geometries tend to be restricted to more local scales. Moreover, the extinction in any region can be described by a combination of the foreground screen and the uniform mixture model with weights of 1/3 and 2/3 in the center (≲2 kpc), respectively, and 2/3 and 1/3 for the rest of the disk. This simple prescription significantly improves the accuracy of the dust extinction corrections and can be especially useful for pixel-based analyses of galaxies similar to M83.

79 ASTRONOMY AND ASTROPHYSICS↗

Fine-scale landscape characteristics, vegetation composition, and snowmelt timing control phenological heterogeneity across low-Arctic tundra landscapes in Western Alaska

The Arctic is warming at over twice the rate of the rest of the Earth, resulting in significant changes in vegetation seasonality that regulates annual carbon, water, and energy fluxes. However, a crucial knowledge gap exists regarding the intricate interplay among climate, permafrost, and vegetation that generates high phenology variability across extensive tundra landscapes. This oversight has led to significant discrepancies in phenological patterns observed across warming experiments, long-term ecological observations, and satellite and modeling studies, undermining our ability to understand and forecast plant responses to climate change in the Arctic. To address this problem, we assessed plant phenology across three low-Arctic tundra landscapes on the Seward Peninsula, Alaska, using a combination of in-situ phenocam observations and high-resolution PlanetScope CubeSat data. We examined the patterns and drivers of phenological diversity across the landscape by (1) quantifying phenological diversity among dominant plant function types (PFTs) and (2) modeling the interrelations between plant phenology and fine-scale landscape features, such as topography, snowmelt, and vegetation. Our findings reveal that both spring and fall phenology varied significantly across Arctic PFTs, accounting for about 25%–44% and 34%–59% of the landscape-scale variation in the start of spring [SOS] and start of fall [SOF], respectively. Deciduous tall shrubs (e.g. alder and willow) had a later SOS (~7 d behind the mean of other PFTs), but completed leaf expansion (within 2 weeks) considerably faster compared to other PFTs. We modeled the landscape-scale variation in SOS and SOF using Random Forest, which showed that plant phenology can be accurately captured by a suite of variables related to vegetation composition, topographic characteristics, and snowmelt timing (variance explained: 53%–68% for SOS and 59%–82% for SOF). Notably, snowmelt timing was a crucial determinant of SOS, a factor often neglected in most spring phenology models. Our study highlights the impact of fine-scale vegetation composition, snow seasonality, and landscape features on tundra phenological heterogeneity. Improved understanding of such considerable intra-site phenological variability and associated proximate controls across extensive Arctic landscapes offers critical insights for representation of tundra phenology in process models and associated impact assessments with climate change.

54 ENVIRONMENTAL SCIENCES↗

Genetic and Functional Diversity Help Explain Pathogenic, Weakly Pathogenic, and Commensal Lifestyles in the Genus Xanthomonas

The genus Xanthomonas has been primarily studied for pathogenic interactions with plants. However, besides host and tissue-specific pathogenic strains, this genus also comprises nonpathogenic strains isolated from a broad range of hosts, sometimes in association with pathogenic strains, and other environments, including rainwater. Based on their incapacity or limited capacity to cause symptoms on the host of isolation, nonpathogenic xanthomonads can be further characterized as commensal and weakly pathogenic. This study aimed to understand the diversity and evolution of nonpathogenic xanthomonads compared to their pathogenic counterparts based on their cooccurrence and phylogenetic relationship and to identify genomic traits that form the basis of a life history framework that groups xanthomonads by ecological strategies. We sequenced genomes of 83 strains spanning the genus phylogeny and identified eight novel species, indicating unexplored diversity. While some nonpathogenic species have experienced a recent loss of a type III secretion system, specifically the hrp2 cluster, we observed an apparent lack of association of the hrp2 cluster with lifestyles of diverse species. We performed association analysis on a large data set of 337 Xanthomonas strains to explain how xanthomonads may have established association with the plants across the continuum of lifestyles from commensals to weak pathogens to pathogens. Presence of distinct transcriptional regulators, distinct nutrient utilization and assimilation genes, transcriptional regulators, and chemotaxis genes may explain lifestyle-specific adaptations of xanthomonads.

59 BASIC BIOLOGICAL SCIENCES↗

A new constraint on galaxy–halo connections of [O ii ] emitters via HOD modelling with angular clustering and luminosity functions from the Subaru HSC survey

ABSTRACT Establishing a robust connection model between emission-line galaxies (ELGs) and their host dark haloes is of paramount importance in anticipation of upcoming redshift surveys. We propose a novel halo occupation distribution (HOD) framework that incorporates galaxy luminosity, a key observable reflecting ELG star-formation activity, into the galaxy occupation model. This innovation enables prediction of galaxy luminosity functions (LFs) and facilitates joint analyses using both angular correlation functions (ACFs) and LFs. Using physical information from luminosity, our model provides more robust constraints on the ELG–halo connection compared to methods relying solely on ACF and number density constraints. Our model was applied to $\rm [O\, {\small II}]$-emitting galaxies observed at two redshift slices at $z=1.193$ and 1.471 from the Subaru Hyper Suprime-Cam PDR2. Our model effectively reproduces observed ACFs and LFs observed in both redshift slices. Compared to the established Geach et al. HOD model, our approach offers a more nuanced depiction of ELG occupation across halo mass ranges, suggesting a more realistic representation of ELG environments. Our findings suggest that ELGs at $z\sim 1.4$ may evolve into Milky-Way-like galaxies, as their inferred halo masses evolve accordingly based on the extended Press–Schechter formalism, highlighting their role as potential building blocks in galaxy formation scenarios. By incorporating the LF as a constraint linking galaxy luminosity to halo properties, our HOD model provides a more precise understanding of ELG-host halo relationships. Furthermore, this approach facilitates the generation of high-quality ELG mock catalogues for future surveys. As the LF is a fundamental observable, our framework is potentially applicable to diverse galaxy populations, offering a versatile tool for analysing data from next-generation galaxy surveys.

Ishikawa, Shogo (ORCID:0000000221184211)↗

Large-scale Genetic Characterization of a Model Sulfate-Reducing Bacterium

ABSTRACTSulfate-reducing bacteria (SRB) are obligate anaerobes that can couple their growth to the reduction of sulfate. Despite the importance of SRB to global nutrient cycles and their damage to the petroleum industry, our molecular understanding of their physiology remains limited. To systematically provide new insights into SRB biology, we generated a randomly barcoded transposon mutant library in the model SRB Desulfovibrio vulgaris Hildenborough (DvH) and used this genome-wide resource to assay the importance of its genes under a range of metabolic and stress conditions. In addition to defining the essential gene set of DvH, we identified a conditional phenotype for 1,137 non-essential genes. Through examination of these conditional phenotypes, we were able to make a number of novel insights into our molecular understanding of DvH, including how this bacterium synthesizes vitamins. For example, we identified DVU0867 as an atypical L-aspartate decarboxylase required for the synthesis of pantothenic acid, provided the first experimental evidence that biotin synthesis in DvH occurs via a specialized acyl carrier protein and without methyl esters, and demonstrated that the uncharacterized dehydrogenase DVU0826:DVU0827 is necessary for the synthesis of pyridoxal phosphate. In addition, we used the mutant fitness data to identify genes involved in the assimilation of diverse nitrogen sources, and gained insights into the mechanism of inhibition of chlorate and molybdate. Our large-scale fitness dataset and RB-TnSeq mutant library are community-wide resources that can be used to generate further testable hypotheses into the gene functions of this environmentally and industrially important group of bacteria.

Trotter, Valentine V↗

Fluid-phase helium: Shock-compression experiments, quantum molecular dynamics simulations, and development of an equation of state

Helium (He) plays a critical role in numerous areas ranging from the study of celestial objects like brown dwarfs and gas giants to modern-day technologies like nuclear energy and rocket propulsion. For many of these applications, it is essential to have a reliable equation of state (EOS) for He that yields an accurate representation of its thermodynamic behavior. To help constrain and develop such EOS models, we have performed a series of shock-compression experiments on cryogenic liquid He to pressures exceeding 100 GPa using a magnetically accelerated flyer plate on Sandia National Laboratories' Z-machine. We have also performed quantum molecular dynamics simulations that are consistent with our shock measurements. None of the previously available EOSs agree with our experimental and simulation results, motivating the development of a fluid-phase He EOS that we present in this study. Here, we show that our EOS yields good agreement with published data that span temperatures and pressures encountered across a diverse array of applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Nonparametric reconstruction of the dark energy equation of state

A basic aim of ongoing and upcoming cosmological surveys is to unravel the mystery of dark energy. In the absence of a compelling theory to test, a natural approach is to better characterize the properties of dark energy in search of clues that can lead to a more fundamental understanding. One way to view this characterization is the improved determination of the redshift-dependence of the dark energy equation of state parameter, w(z). To do this requires a robust and bias-free method for reconstructing w(z) from data that does not rely on restrictive expansion schemes or assumed functional forms for w(z). We present a new nonparametric reconstruction method that solves for w(z) as a statistical inverse problem, based on a Gaussian process representation. This method reliably captures nontrivial behavior of w(z) and provides controlled error bounds. We demonstrate the power of the method on different sets of simulated supernova data; the approach can be easily extended to include diverse cosmological probes.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗