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At least 649 records · Page 36

A functional microbiome catalogue crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

59 BASIC BIOLOGICAL SCIENCES↗

Radiation-induced alteration of apatite on the surface of Mars: first in situ observations with SuperCam Raman onboard Perseverance

Abstract Planetary exploration relies considerably on mineral characterization to advance our understanding of the solar system, the planets and their evolution. Thus, we must understand past and present processes that can alter materials exposed on the surface, affecting space mission data. Here, we analyze the first dataset monitoring the evolution of a known mineral target in situ on the Martian surface, brought there as a SuperCam calibration target onboard the Perseverance rover. We used Raman spectroscopy to monitor the crystalline state of a synthetic apatite sample over the first 950 Martian days (sols) of the Mars2020 mission. We note significant variations in the Raman spectra acquired on this target, specifically a decrease in the relative contribution of the Raman signal to the total signal. These observations are consistent with the results of a UV-irradiation test performed in the laboratory under conditions mimicking ambient Martian conditions. We conclude that the observed evolution reflects an alteration of the material, specifically the creation of electronic defects, due to its exposure to the Martian environment and, in particular, UV irradiation. This ongoing process of alteration of the Martian surface needs to be taken into account for mineralogical space mission data analysis.

Science & Technology - Other Topics↗

Direct flue gas capture for algae cultivation and subsequent valorization: evaluating life cycle emissions and costs

Algae cultivation and processing is an important pathway under discussion within the broader CO 2 capture and utilization umbrella. Here, we discuss the results of a life-cycle analysis and techno-economic analysis of a pilot-scale photobioreactor that uses flue gas directly from natural gas or biogas combustion at 3–5% CO 2 concentration. The system requires minimal freshwater use as it has been successfully run with industrial wastewater and has a much smaller areal footprint compared with open pond cultivation. Introducing the flue gas directly to the photobioreactor avoids the need for CO 2 separation and pressurization, which is undertaken in many other algae cultivation systems. For the end-use of the biomass, the default case assumes conversion of algae to liquid fuels via hydrothermal liquefaction. The results indicate that the pilot-scale system has a higher cost, and comparable greenhouse gas emissions compared to pond-based systems, especially as the grid is anticipated to evolve to a lower carbon intensity. The costs of algae biofuel production range from $\$12–16$ per GGE at the current pilot scale. Depending on whether the source of the carbon is fossil or biogenic, the net emissions are 68 g CO 2 e per MJ and −4 g CO 2 e per MJ respectively. If the marine algae species is used instead of the freshwater species, it offers an additional 16 g CO 2 e per MJ carbon fixation in the form of calcium carbonate. The findings point to broadly desirable trends in GHG emissions and costs, while the discussion aims to shed light on areas that could further improve the scalability of the system.

20 FOSSIL-FUELED POWER PLANTS↗

Streaming Readout and Data-Stream Processing With ERSAP

With the exponential growth in the volume and complexity of data generated at high-energy physics and nuclear physics research facilities, there is an imperative demand for innovative strategies to process this data in real or near-real-time. Given the surge in the requirement for high-performance computing, it becomes pivotal to reassess the adaptability of current data processing architectures in integrating new technologies and managing streaming data. This paper introduces the ERSAP framework, a modern solution that synergizes flow-based programming with the reactive actor model, paving the way for distributed, reactive, and high performance in data stream processing applications. Additionally, we unveil a novel algorithm focused on time-based clustering and event identification in data streams. The efficacy of this approach is further exemplified through the data-stream processing outcomes obtained from the recent beam tests of the EIC prototype calorimeter at DESY.

Vardan, Gyurjyan↗

NWChem: Past, present, and future

Specialized computational chemistry packages have permanently reshaped the landscape of chemical sciences by providing tools to support and guide the experimental effort and for prediction of chemical and materials properties. In this regard, a special role has been played by electronic structure packages where complex chemical and materials processes can be modeled using first-principle-driven methodologies. Over the last few decades, the rapid development of computing technologies and a tremendous increase in computational power has offered a unique chance to study complex chemical transformations using sophisticated and predictive many-body techniques to describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, a critical role has been played by novel parallel algorithms capable of taking advantage of computational resources to address polynomial scaling of electronic structure methods. NWChem was among the first electronic structure codes that focused on delivering scalable performance for electronic structure simulations. Herein, we briefly review the NWChem suite of computational codes including its history, design principles, parallel tools, current capabilities, outreach and outlook.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A WKB based preconditioner for the 1D Helmholtz wave equation

Frequency-domain full-wave solutions to the cold-plasma problem have become ubiquitous in the study of radio frequency power in fusion plasmas. However, recent efforts at extreme levels of geometric fidelity have revealed fundamental limits in the problem size that can be solved by typical sparse direct solver based methods. These limits are of particular importance in the 3D study of RF launchers, where the number of degrees of freedom required can exceed 100 million. In such cases, it would be advantageous to solve the system via iterative means, but due to the large null space of the curl-curl operator, the convergence properties of algorithms like GMRES are poor. Here we present a physics-based preconditioner in the form of a WKB solution and demonstrate the iterative solution to the frequency-domain Helmholtz problem in 1D for several cases ranging from satisfying the WKB approximation to strongly violating it.

Green, David↗

Study of vacuum ultraviolet emission in helium and helium/nitrogen mixtures

Helium is frequently used as a working medium for the generation of plasmas and is capable of energetic photon emissions. These energetic photon emissions are often attributed to the formation of helium excimer and subsequent photon emission. When the plasma device is exposed to another gas, such as nitrogen, this energetic photon emission can cause photoionization and further ionization wave penetration into the additional gas. Often ignored are the helium resonance emissions that are assumed to be radiation trapped and therefore not pertinent to photoionization. Here, experimental evidence for the presence of helium atomic emission in a pulsed discharge at ten’s of Torr is shown. Simulations of a discharge in similar conditions agree with the experimental measurements. In this context, the role of atomic and molecular helium light emission on photoionization of molecular nitrogen in an ionization wave is studied using a kinetic modeling approach that accounts for radiation dynamics in a developing low-temperature plasma. Three different mixtures of helium at a total pressure of 250 Torr are studied in simulation. Photoionization of the nitrogen molecule by vacuum ultraviolet helium emission is used as the only seed source ahead of the ionization front. It is found that even though radiation trapped, the atomic helium emission lines are the significant source of photoionization of nitrogen. The significant effect of radiation trapped photon emission on ionization wave dynamics demonstrates the need to consider these radiation dynamics in plasma reactors where self-absorbed radiation is ignored.

42 ENGINEERING↗

Effects of electron beam irradiation on CrMnV and CrMnTiV high entropy alloys: Nano-mechanical, structural, and thermodynamic perspectives

Beam exit windows are crucial components of any particle accelerator as they provide an interface between the beamline vacuum and target material at atmospheric media. For high beam power machines, special materials and designs are required to withstand high radiation and mechanical loads, while minimizing energy loss during transition and maximizing window lifetime. This research investigates the impact of electron beam exposure to bulk CrMnV and CrMnTiV high entropy alloys (HEAs) with the primary goal of identifying suitable candidate materials for the design of robust and durable exit window settings. The selection criteria include intrinsic characteristics, power dissipation, and mechanical responses. According to the thermodynamic calculations, both equiatomic CrMnV and the addition of 7% of Ti with equiatomic CrMnV yield solid-solutions phases. The structural and mechanical properties of CrMnV and CrMnTiV samples were tested using field emission scanning electron microscopy, atomic force microscopy, scanning electron microcopy with energy dispersive x-ray spectroscopy, x-ray diffraction, and nanoindentation before and after exposure to a dose of ~66 kGy from a 10 MeV e-beam accelerator. Despite exhibiting beam transmission characteristics comparable to Cr and V, the indentation hardness of HEAs exceeded that of the Cr and V samples by five to six times. The examination of the CrMnTiV irradiated samples revealed organized deformation patterns depicting new features, which we suspect twinning and twin boundaries due to the addition of Ti to CrMnV. Ti, a hexagonal-close-packed crystal structure, is commonly known for deformation twinning behavior.

36 MATERIALS SCIENCE↗

Progress in Fast Modular Reactor Conceptual Design

The Fast Modular Reactor (FMR) is a 100-MW(thermal) gas-cooled fast reactor being developed by General Atomics Electromagnetic System with the goal of developing a FMR for flexible and dispatchable power to the U.S. electricity market in the mid-2030s. The conceptual design aims to develop and verify simplified design features. These include an inert helium gas coolant, pellet-loaded fuel rods, installations with air cooling as ultimate heat sink, and small and passive heat removal systems. The goal is to ensure the development of a safe, maintainable, cost-effective, and distributed nuclear energy-generating station. The baseline technologies selected to achieve this goal are a helium coolant that is an inert gas with no chemical reaction with structural components, not activated, single phase, enabling high-temperature operation and a high thermal efficiency Brayton cycle; conventional uranium dioxide (UO 2 ) fuel, which is the most widely used and well-known fuel material, capable of high burnup (100 MWd/kg) and a long fuel life; and silicon carbide composite (SiGA®) cladding and internal structures that are chemically inert in the helium environment, exceptionally radiation tolerant, and being derisked by accident tolerant fuel technology development. Further, the reactor was specifically designed with passive safety features, including high-temperature in-core materials and a reactor vessel cooling system consisting of cooling panels of naturally circulating water. The passive safety of the core was confirmed for the depressurized loss-of–forced cooling accident, which showed the peak cladding temperature at ~1600°C during the transient, which is below the current design limit of 1800°C. The conceptual design of the FMR has been conducted for the reactor system, vessel system, generator and turbomachine, instrumentation and control, residual heat removal system, plant service system, and containment, as well as pre-application licensing documents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Spatiotemporally resolved measurements of electric field around a piezoelectric transformer using electric-field induced second harmonic (E-FISH) generation

When a piezoelectric transformer (PT) is actuated at its second harmonic frequency by a low input voltage, the generated electric field at the distal end can be sufficient to breakdown the surrounding gas, making them attractive power sources for non-equilibrium plasma generation. Understanding the potential and electric fields produced in the surrounding medium by the PT is important for effectively designing and using PT plasma devices. In this work, the spatiotemporally resolved characteristics of the electric field generated by a PT operating in open air have been investigated using the femtosecond electric field-induced second harmonic generation (E-FISH) method. Here, electric field components were determined by simultaneously conducting E-FISH measurements with the incident laser polarized in two orthogonal directions relative to the PT crystal. Results of this work demonstrate the spatial distribution of electric field around the PT’s output distal end and how it evolves as a function of time. Notably, the strongest electric field appears on the face of the PT’s distal surface, near the top and bottom edges and decreases by approximately 70% over 3 mm. The time delay between the PT’s input voltage and measured electric field indicates that there is an about 0.45 phase difference between the PT’s input voltage and output signal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Parallel simulation via SPPARKS of on-lattice kinetic and Metropolis Monte Carlo models for materials processing

Abstract SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

36 MATERIALS SCIENCE↗

Geographic patterns of genomic diversity and structure in the C4 grass Panicum hallii across its natural distribution

Abstract Geographic patterns of within-species genomic diversity are shaped by evolutionary processes, life history and historical and contemporary factors. New genomic approaches can be used to infer the influence of such factors on the current distribution of infraspecific lineages. In this study, we evaluated the genomic and morphological diversity as well as the genetic structure of the C4 grass Panicum hallii across its complex natural distribution in North America. We sampled extensively across the natural range of P. hallii in Mexico and the USA to generate double-digestion restriction-associated DNA (ddRAD) sequence data for 423 individuals from 118 localities. We used these individuals to study the divergence between the two varieties of P. hallii, P. hallii var. filipes and P. hallii var. hallii as well as the genetic diversity and structure within these groups. We also examined the possibility of admixture in the geographically sympatric zone shared by both varieties, and assessed distribution shifts related with past climatic fluctuations. There is strong genetic and morphological divergence between the varieties and consistent genetic structure defining seven genetic clusters that follow major ecoregions across the range. South Texas constitutes a hotspot of genetic diversity with the co-occurrence of all genetic clusters and admixture between the two varieties. It is likely a recolonization and convergence point of populations that previously diverged in isolation during fragmentation events following glaciation periods.

54 ENVIRONMENTAL SCIENCES↗

Spatio-temporal differences in leaf physiology are associated with fire, not drought, in a clonally integrated shrub

Abstract In highly disturbed environments, clonality facilitates plant survival via resprouting after disturbance, resource sharing among interconnected stems and vegetative reproduction. These traits likely contribute to the encroachment of deep-rooted clonal shrubs in tallgrass prairie. Clonal shrubs have access to deep soil water and are typically thought of as relatively insensitive to environmental variability. However, how leaf physiological traits differ among stems within individual clonal shrubs (hereafter ‘intra-clonal’) in response to extreme environmental variation (i.e. drought or fire) is unclear. Accounting for intra-clonal differences among stems in response to disturbance is needed to more accurately parameterize models that predict the effects of shrub encroachment on ecosystem processes. We assessed intra-clonal leaf-level physiology of the most dominant encroaching shrub in Kansas tallgrass prairie, Cornus drummondii, in response to precipitation and fire. We compared leaf gas exchange rates from the periphery to centre within shrub clones during a wet (2015) and extremely dry (2018) year. We also compared leaf physiology between recently burned shrubs (resprouts) with unburned shrubs in 2018. Resprouts had higher gas exchange rates and leaf nitrogen content than unburned shrubs, suggesting increased rates of carbon gain can contribute to recovery after fire. In areas recently burned, resprouts had higher gas exchange rates in the centre of the shrub than the periphery. In unburned areas, leaf physiology remained constant across the growing season within clonal shrubs (2015 and 2018). Results suggest single measurements within a shrub are likely sufficient to parameterize models to understand the effects of shrub encroachment on ecosystem carbon and water cycles, but model parameterization may require additional complexity in the context of fire.

54 ENVIRONMENTAL SCIENCES↗

Starch depletion in the xylem and phloem ray parenchyma of grapevine stems under drought

Abstract While nonstructural carbohydrate (NSC) storage can support long-lived woody plants during abiotic stress, the timing and extent of their use are less understood, as are the thresholds for cell mortality as NSCs and water supplies are consumed. Here, we combine physiological and imaging tools to study the response of Vitis riparia to a 6-week experimental drought. We focused on the spatial and temporal dynamics of starch consumption and cell viability in the xylem and phloem of the stem. Starch dynamics were further corroborated with enzymatic starch digestion and X-ray microcomputed tomography imaging. Starch depletion in the stems of droughted plants was detected after 2 weeks and continued over time. We observed distinct differences in starch content and cell viability in the xylem and phloem. By the end of the drought, nearly all the starch was consumed in the phloem ray parenchyma (98 % decrease), and there were almost no metabolically active cells in the phloem. In contrast, less starch was consumed in the xylem ray parenchyma (30 % decrease), and metabolically active cells remained in the ray and vessel-associated parenchyma in the xylem. Our data suggest that the higher proportion of living cells in the phloem and cambium, combined with smaller potential NSC storage area, rapidly depleted starch, which led to cell death. In contrast, the larger cross-sectional area of the xylem ray parenchyma with higher NSC storage and lower metabolically active cell populations depleted starch at a slower pace. Why NSC source-sink relationships between xylem and phloem do not allow for a more uniform depletion of starch in ray parenchyma over time is unclear. Our data help to pinpoint the proximate and ultimate causes of plant death during prolonged drought exposure and highlight the need to consider the influence of within-organ starch dynamics and cell mortality on abiotic stress response.

59 BASIC BIOLOGICAL SCIENCES↗

Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding

Abstract Motivation The vast expansion of sequence data generated from single organisms and microbiomes has precipitated the need for faster and more sensitive methods to assess evolutionary and functional relationships between proteins. Representing proteins as sets of short peptide sequences (kmers) has been used for rapid, accurate classification of proteins into functional categories; however, this approach employs an exact-match methodology and thus may be limited in terms of sensitivity and coverage. We have previously used similarity groupings, based on the chemical properties of amino acids, to form reduced character sets and recode proteins. This amino acid recoding (AAR) approach simplifies the construction of protein representations in the form of kmer vectors, which can link sequences with distant sequence similarity and provide accurate classification of problematic protein families. Results Here, we describe Snekmer, a software tool for recoding proteins into AAR kmer vectors and performing either (i) construction of supervised classification models trained on input protein families or (ii) clustering for de novo determination of protein families. We provide examples of the operation of the tool against a set of nitrogen cycling families originally collected using both standard hidden Markov models and a larger set of proteins from Uniprot and demonstrate that our method accurately differentiates these sequences in both operation modes. Availability and implementation Snekmer is written in Python using Snakemake. Code and data used in this article, along with tutorial notebooks, are available at http://github.com/PNNL-CompBio/Snekmer under an open-source BSD-3 license. Supplementary information Supplementary data are available at Bioinformatics Advances online.

59 BASIC BIOLOGICAL SCIENCES↗

Novel symmetry-preserving neural network model for phylogenetic inference

Abstract Motivation Scientists world-wide are putting together massive efforts to understand how the biodiversity that we see on Earth evolved from single-cell organisms at the origin of life and this diversification process is represented through the Tree of Life. Low sampling rates and high heterogeneity in the rate of evolution across sites and lineages produce a phenomenon denoted “long branch attraction” (LBA) in which long nonsister lineages are estimated to be sisters regardless of their true evolutionary relationship. LBA has been a pervasive problem in phylogenetic inference affecting different types of methodologies from distance-based to likelihood-based. Results Here, we present a novel neural network model that outperforms standard phylogenetic methods and other neural network implementations under LBA settings. Furthermore, unlike existing neural network models in phylogenetics, our model naturally accounts for the tree isomorphisms via permutation invariant functions which ultimately result in lower memory and allows the seamless extension to larger trees. Availability and implementation We implement our novel theory on an open-source publicly available GitHub repository: https://github.com/crsl4/nn-phylogenetics.

59 BASIC BIOLOGICAL SCIENCES↗