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At least 379 records · Page 21

Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey. II. Anisotropic Large-scale Coherence in Hot Gas, Galaxies, and Dark Matter

Statistics that capture the directional dependence of the baryon distribution in the cosmic web enable unique tests of cosmology and astrophysical feedback. We use constrained oriented stacking of thermal Sunyaev–Zel’dovich (tSZ) maps to measure the anisotropic distribution of hot gas 2.5–40 Mpc away from galaxy clusters embedded in massive filaments and superclusters. The cluster selection and orientation (at a scale of ∼15 Mpc) use Dark Energy Survey (DES) Year 3 data, while expanded tSZ maps from the Atacama Cosmology Telescope Data Release 6 enable a ∼3× more significant measurement of the extended gas compared to the technique’s proof-of-concept. Decomposing stacks into cosine multipoles of order m , we detect a dipole ( m = 1) and quadrupole ( m = 2) at 8σ–10σ, as well as evidence for m = 4 signal at up to 6σ, indicating sensitivity to late-time non-Gaussianity. We compare to Cardinal simulations with spherical gas models pasted onto dark matter halos. The fiducial tSZ data can discriminate between two models that deplete pressure differently in low-mass halos (mimicking astrophysical feedback), preferring higher average pressure in extended structures. However, uncertainty in the amount of cosmic infrared background contamination reduces the constraining power. Additionally, we apply the technique to DES galaxy density and weak lensing to study for the first time their oriented relationships with tSZ. In the tSZ-to-lensing relation, averaged on 7.5 Mpc (transverse) scales, we observe dependence on redshift but not shape or radial distance. Thus, on large scales, the superclustering of gas pressure, galaxies, and total matter is coherent in shape and extent.

79 ASTRONOMY AND ASTROPHYSICS↗

A new database website for nuclear level densities

We introduce a new open-access, web-based database (http://nld.ascsn.net), Current Archive of Nuclear Density of Levels (CANDL), that hosts experimental nuclear level density (NLD) datasets from a variety of techniques and energy ranges. Built using the Dash framework in Python, the database is designed to be interactive and user-friendly, allowing researchers to search, visualize, fit, and export NLD data with minimal effort. This resource includes data extracted from evaporation spectra, Oslo method variants, and other experimental techniques that cover excitation energies beyond the neutron resonance region. The database supports on-the-fly fitting with two widely-used phenomenological models—the Constant Temperature (CT) model and the Back-Shifted Fermi Gas (BSFG) model—selected for their simplicity and computational efficiency. Future versions aim to include additional datasets and model types, as well as easy-to-use interfaces to data science techniques. Here, this platform offers a vital tool for the nuclear physics, astrophysics, medicine, and reactor design communities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Effects of PFOS on the behavior, growth, emergence, and predation susceptibility of larval mosquitoes ( Culex quinquefasciatus )

Per-/polyfluoroalkyl substances (PFAS) have been commonly used over several decades for a variety of products and are very persistent in the environment. However, not much is known about their direct effects on aquatic invertebrates and their ecosystems. We examined the survival, behavior, development, and predation susceptibility of mosquito larvae Culex quinquefasciatus exposed to concentrations of perfluorooctanesulfonic acid (PFOS) ranging from 0.02 to 453.7 µg/L. PFOS exposure resulted in reduced larval survival, with a 48 hour LC50 (concentration with 50 % mortality) of 255.99 µg/L. PFOS exposure also resulted in reduced developmental success and slower maturation to adulthood (and thus slower emergence from the water) compared to control larvae. PFOS also resulted in delays in reaction to prodding stimuli, which were meant to simulate a predator attack, and longer reactions to prodding. Larvae exposed to PFOS also spent more time at the bottom of the water column, rather than at the surface where respiration takes place. Effects of larval mosquito PFOS exposure on predation by unexposed damselfly naiads (genus Ischnura) were not detected. Overall, this research suggests that PFOS impacts mosquito larvae survival, behavior, development, and adult emergence, which could have important implications for food webs or public health given the role of mosquitos as disease vectors.

Food web dynamics↗

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

54 ENVIRONMENTAL SCIENCES↗

BIPSPI+: Mining Type-Specific Datasets of Protein Complexes to Improve Protein Binding Site Prediction

Computational approaches for predicting protein-protein interfaces are extremely useful for understanding and modelling the quaternary structure of protein assemblies. In particular, partner-specific binding site prediction methods allow delineating the specific residues that compose the interface of protein complexes. In recent years, new machine learning and other algorithmic approaches have been proposed to solve this problem. However, little effort has been made in finding better training datasets to improve the performance of these methods. With the aim of vindicating the importance of the training set compilation procedure, in this work we present BIPSPI+, a new version of our original server trained on carefully curated datasets that outperforms our original predictor. We show how prediction performance can be improved by selecting specific datasets that better describe particular types of protein interactions and interfaces (e.g. homo/hetero). In addition, our upgraded web server offers a new set of functionalities such as the sequence-structure prediction mode, hetero- or homo-complex specialization and the guided docking tool that allows to compute 3D quaternary structure poses using the predicted interfaces. BIPSPI+ is freely available at https://bipspi.cnb.csic.es.

59 BASIC BIOLOGICAL SCIENCES↗

Soil compartments (bulk soil, litter, root and rhizosphere) as main drivers of soil protistan communities distribution in forests with different nitrogen deposition

Protists, in particular bacterivores, are essential players in the rhizosphere; thus, how their interactions with bacteria and fungi affect plant productivity and soil nutrient cycles warrants more attention. Using next-generation sequencing of the 18 S rRNA gene, we investigated the distribution of two major protistan phyla, Cercozoa and Endomyxa, across four seasons, and four soil compartments - rhizosphere, root, soil and litter. The sampling was replicated in two forests in Norway and the Czech Republic, in order to test our results across biogeographic scales. Compartment had a major influence in shaping protistan communities, over and above spatial distance and seasonal variation. Protistan diversity was highest in the bulk soil while lowest in the roots, suggesting that the plants select for restricted assemblages of protists. Accordingly, only the root compartment harboured a subset of the bulk soil protistan diversity. In addition, protistan communities showed markedly different distributions according to their feeding modes, with opposite patterns for bacterivores versus omnivores and eukaryvores. The small bacterivorous flagellates (mostly Glissomonadida) were more abundant in roots, while the larger amoeboid eukaryvores (e.g. some of the Cryomonadida and vampyrellids) dominated in soil and in the rhizosphere, and the omnivores (e.g. Euglyphida and part of the Cercomonadida), also large and mostly amoeboid, were more abundant in litter. The current view of the soil microbiome is mostly focused on bacteria and fungi: this detailed study on the community distribution of protists according to their feeding modes reveals the essential role they play in each of the soil compartments, an essential precondition for a detailed understanding of the soil food web and nutrient cycling in forest.

59 BASIC BIOLOGICAL SCIENCES↗

Meeting report: The first soil viral workshop 2022

Soil viral ecology is a growing research field; however, the state of knowledge still lags behind that of aquatic systems. Therefore, to facilitate progress, the first Soil Viral Workshop was held to encourage international scientific discussion and collaboration, suggest guidelines for future research, and establish soil viral research as a concrete research area. The workshop took place at Søminestationen, Denmark, between 15 and 17th of June 2022. The meeting was primarily held in person, but the sessions were also streamed online. The workshop was attended by 23 researchers from ten different countries and from a wide range of subfields and career stages. Eleven talks were presented, followed by discussions revolving around three major topics: viral genomics, virus-host interactions, and viruses in the soil food web. The main take-home messages and suggestions from the discussions are summarized in this report.

09 BIOMASS FUELS↗

A cloud platform for atomic pair distribution function analysis: PDFitc

A cloud web platform for analysis and interpretation of atomic pair distribution function (PDF) data ( PDFitc ) is described. The platform is able to host applications for PDF analysis to help researchers study the local and nanoscale structure of nanostructured materials. The applications are designed to be powerful and easy to use and can, and will, be extended over time through community adoption and development. The currently available PDF analysis applications, structureMining, spacegroupMining and similarityMapping , are described. In the first and second the user uploads a single PDF and the application returns a list of best-fit candidate structures, and the most likely space group of the underlying structure, respectively. In the third, the user can upload a set of measured or calculated PDFs and the application returns a matrix of Pearson correlations, allowing assessment of the similarity between different data sets. structureMining is presented here as an example to show the easy-to-use workflow on PDFitc . In the future, as well as using the PDFitc applications for data analysis, it is hoped that the community will contribute their own codes and software to the platform.

97 MATHEMATICS AND COMPUTING↗

CERES : a cryo-EM re-refinement system for continuous improvement of deposited models

The field of electron cryomicroscopy (cryo-EM) has advanced quickly in recent years as the result of numerous technological and methodological developments. This has led to an increase in the number of atomic structures determined using this method. Recently, several tools for the analysis of cryo-EM data and models have been developed within the Phenix software package, such as phenix.real_space_refine for the refinement of atomic models against real-space maps. Also, new validation metrics have been developed for low-resolution cryo-EM models. To understand the quality of deposited cryo-EM structures and how they might be improved, models deposited in the Protein Data Bank that have map resolutions of better than 5 Å were automatically re-refined using current versions of Phenix tools. The results are available on a publicly accessible web page (https://cci.lbl.gov/ceres). The implementation of a Cryo-EM Re-refinement System ( CERES ) for the improvement of models deposited in the wwPDB, and the results of the re-refinements, are described. Based on these results, contents are proposed for a `cryo-EM Table 1', which summarizes experimental details and validation metrics in a similar way to `Table 1' in crystallography. The consistent use of robust metrics for the evaluation of cryo-EM models and data should accompany every structure deposition and be reported in scientific publications.

59 BASIC BIOLOGICAL SCIENCES↗

A Genome-Scale Atlas Reveals Complex Interplay of Transcription and Translation in an Archaeon

The scale of post-transcriptional regulation and the implications of its interplay with other forms of regulation in environmental acclimation are underexplored for organisms of the domain Archaea. Here, we have investigated the scale of post-transcriptional regulation in the extremely halophilic archaeon Halobacterium salinarum NRC-1 by integrating the transcriptome-wide locations of transcript processing sites (TPSs) and SmAP1 binding, the genome-wide locations of antisense RNAs (asRNAs), and the consequences of RNase_2099C knockout on the differential expression of all genes. This integrated analysis has discovered that 54% of all protein-coding genes in the genome of this haloarchaeon are likely targeted by multiple mechanisms for putative post-transcriptional processing and regulation, with about 20% of genes likely being regulated by combinatorial schemes involving SmAP1, asRNAs, and RNase_2099C. Comparative analysis of mRNA levels (transcriptome sequencing [RNA-Seq]) and protein levels (sequential window acquisition of all theoretical fragment ion spectra mass spectrometry [SWATH-MS]) for 2,579 genes over four phases of batch culture growth in complex medium generated additional evidence for the conditional post-transcriptional regulation of 7% of all protein-coding genes. We demonstrate that post-transcriptional regulation may act to fine-tune specialized and rapid acclimation to stressful environments, e.g., as a switch to turn on gas vesicle biogenesis to promote vertical relocation under anoxic conditions and modulate the frequency of transposition by insertion sequence (IS) elements of the IS200/IS605, IS4, and ISH3 families. Findings from this study are provided as an atlas in a public Web resource (https://halodata.systemsbiology.net).

59 BASIC BIOLOGICAL SCIENCES↗

Remarkably coherent population structure for a dominant Antarctic Chlorobium species

Background: In Antarctica, summer sunlight enables phototrophic microorganisms to drive primary production, thereby “feeding” ecosystems to enable their persistence through the long, dark winter months. In Ace Lake, a stratified marine-derived system in the Vestfold Hills of East Antarctica, a Chlorobium species of green sulphur bacteria (GSB) is the dominant phototroph, although its seasonal abundance changes more than 100-fold. Here, we analysed 413 Gb of Antarctic metagenome data including 59 Chlorobium metagenome-assembled genomes (MAGs) from Ace Lake and nearby stratified marine basins to determine how genome variation and population structure across a 7-year period impacted ecosystem function. Results: A single species, Candidatus Chlorobium antarcticum (most similar to Chlorobium phaeovibrioides DSM265) prevails in all three aquatic systems and harbours very little genomic variation (≥ 99% average nucleotide identity). A notable feature of variation that did exist related to the genomic capacity to biosynthesize cobalamin. The abundance of phylotypes with this capacity changed seasonally ~ 2-fold, consistent with the population balancing the value of a bolstered photosynthetic capacity in summer against an energetic cost in winter. The very high GSB concentration (> 10 8 cells ml –1 in Ace Lake) and seasonal cycle of cell lysis likely make Ca. Chlorobium antarcticum a major provider of cobalamin to the food web. Analysis of Ca. Chlorobium antarcticum viruses revealed the species to be infected by generalist (rather than specialist) viruses with a broad host range (e.g., infecting Gammaproteobacteria) that were present in diverse Antarctic lakes. The marked seasonal decrease in Ca. Chlorobium antarcticum abundance may restrict specialist viruses from establishing effective lifecycles, whereas generalist viruses may augment their proliferation using other hosts. Conclusion: The factors shaping Antarctic microbial communities are gradually being defined. In addition to the cold, the annual variation in sunlight hours dictates which phototrophic species can grow and the extent to which they contribute to ecosystem processes. The Chlorobium population studied was inferred to provide cobalamin, in addition to carbon, nitrogen, hydrogen, and sulphur cycling, as critical ecosystem services. The specific Antarctic environmental factors and major ecosystem benefits afforded by this GSB likely explain why such a coherent population structure has developed in this Chlorobium species.

59 BASIC BIOLOGICAL SCIENCES↗

Ground Source Heat Pump Screening Tool and Related Resources

This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed to evaluate the feasibility, costs, and benefits of implementing GSHP systems in buildings across various U.S. climate zones. It is intended for use by building owners, HVAC system designers, and installers to support decision-making in residential and commercial applications, incorporating advanced modeling capabilities such as ground heat exchanger design. The included resources detail the tool's creation and use, covering topics such as innovative ground heat exchanger design methodologies, the development of an open library of g-functions for borehole configurations, and studies on GSHP performance and economic viability in retrofitting single-family homes.

15 GEOTHERMAL ENERGY↗

Directing Traffic in the Rhizosphere: How Phage and Fauna Shape the Flow and Fate of Root Carbon through Microbial Pathways

The rhizosphere, the portion of soil directly influenced by plant roots, is an area of great biological activity and intense carbon (C) cycling. Interactions among the residents of the rhizosphere, such as bacteria, fungi, viruses, and fauna, result in transformation and transfer C from root exudates and root debris to biomass and developing soil organic matter. The primary object of this research project was to explore the complex interactions controlling C flow in the rhizosphere and the response of these interactions to soil water conditions. We used stable isotope techniques combined with molecular analyses to observe the flow of C as it is fixed by plants from the atmosphere, deposited into the soil through plant roots, and exchanged through multiple pathways of the soil food web. This technical report summarizes the achievements of this project from field, greenhouse, and lab experiments.

54 ENVIRONMENTAL SCIENCES↗

Aquifer Injection Modeling (AIM) Toolbox User Guide

The Aquifer Injection Modeling Toolbox (“AIM Toolbox”) software was developed by the Pacific Northwest National Laboratory (PNNL) for the U.S. Environmental Protection Agency’s (EPA) to provide a collection of analytical solutions suitable for evaluating the potential extent of the area impacted by subsurface injection operations. Subsurface injection operations are regulated under the EPA’s Underground Injection Control (UIC) program and are typically related to oil/gas development, waste disposal, or subsurface mining or storage. The analytical algorithms provided in the AIM Toolbox each have different approaches/assumptions/focus with respect to the nature and processes in subsurface and the nature of the injection operations. Collectively the set of analysis algorithms provides a broader evaluation of the area that can potentially be impacted by an injection operation. By providing estimates for the injectate plume extent, the software supports technical aspects of planning, evaluation, and overseeing injection activities. That is, the results help assess when further regulatory controls (e.g., monitoring, reporting) may be required and, in the case of disposal into an underground source of drinking water, the extent of the impacted area would require exemption from protection under the Safe Drinking Water Act. The AIM Toolbox software is available as a single-page web application, providing an interface to provide the necessary inputs, and both chart and map panes for visualizing the results. This User Guide describes the AIM Toolbox software, information required, user interactions, and the underlying basis of the calculations.

54 ENVIRONMENTAL SCIENCES↗

Developing a Power Plant Suitability Model for the Energy Zones Mapping Tool

This report provides an example of designing, developing, and running a power plant suitability model in the Energy Zones Mapping Tool (EZMT), a public, web-based mapping tool with a large spatial database focused on energy infrastructure, energy resources, and related siting factors. The example focuses on natural gas combined cycle (NGCC) power plants, which have several unique and interesting characteristics. NGCC plants typically provide peaking power to the electrical grid. Such plants can be started or stopped relatively quickly and are often used to supplement base load plants (such as nuclear or coal) during times of peak electrical consumption or to counterbalance lulls in variable power generation (such as wind or solar). Due to these and other factors, NGCC plants have been projected to increase in number under energy planning studies such as Hadley et al. The scope of the Hadley et. al. study is the Eastern Interconnection (EI), the electrical transmission grid serving much of the United States and Canada east of the Rocky Mountains. Results in the study are organized according to 22 Multi-region National—North American Electricity and Environment Model (NEEM) regions within the EI. NGCC plants usually have lower water requirements than other thermoelectric power plants they may replace; therefore, they are expected to have an interesting role in reducing the overall water requirements of energy generation.

20 FOSSIL-FUELED POWER PLANTS↗

Modeling Power Plant Siting Opportunities and Constraints in the Eastern Interconnection

The electrical transmission grid is a critical part of the U.S. national infrastructure, and its modernization is a U.S. Department of Energy (DOE) priority. We describe the Energy Zones Mapping Tool (EZMT), a unique, powerful, and public web-based system with multi-criteria decision analysis (MCDA) models for more than 20 power plant technologies and many other capabilities. Through a case study on natural gas combined cycle (NGCC) power plants in the Eastern Interconnection (EI), we provide an example of incorporating an EZMT MCDA model into a larger planning context, with projections of interconnection-level capacity expansion, thermoelectric power plant retirements, and water availability. Our results provide insights on candidate NGCC site distributions and the criteria influencing them. The case study provides both an efficient methodology for performing similar analyses and hundreds of candidate NGCC power plant sites that can be studied in more detail as potential project sites.

20 FOSSIL-FUELED POWER PLANTS↗

Aquifer Injection Modeling (AIM) Toolbox User Guide

The Aquifer Injection Modeling Toolbox (“AIM Toolbox”) software was developed by the Pacific Northwest National Laboratory (PNNL) for the U.S. Environmental Protection Agency’s (EPA) to provide a collection of analytical solutions suitable for evaluating the potential extent of the area impacted by subsurface injection operations. Subsurface injection operations are regulated under the EPA’s Underground Injection Control (UIC) program and are typically related to oil/gas development, waste disposal, or subsurface mining or storage. The analytical algorithms provided in the AIM Toolbox each have different approaches/assumptions/focus with respect to the nature and processes in subsurface and the nature of the injection operations. Collectively the set of analysis algorithms provides a broader evaluation of the area that can potentially be impacted by an injection operation. By providing estimates for the injectate plume extent, the software supports technical aspects of planning, evaluation, and overseeing injection activities. That is, the results help assess when further regulatory controls (e.g., monitoring, reporting) may be required and, in the case of disposal into an underground source of drinking water, the extent of the impacted area would require exemption from protection under the Safe Drinking Water Act. The AIM Toolbox software is available as a single-page web application, providing an interface to provide the necessary inputs, and both chart and map panes for visualizing the results. This User Guide describes the AIM Toolbox software, information required, user interactions, and the underlying basis of the calculations.

58 GEOSCIENCES↗

Automated Cloud Based Long Short-Term Memory Neural Network Based SWE Prediction

Snow derived water is a critical component of the US water supply. Measurements of the Snow Water Equivalent (SWE) and associated predictions of peak SWE and snowmelt onset are essential inputs for water management efforts. This paper aims to develop an integrated framework for real-time data ingestion, estimation, prediction and visualization of SWE based on daily snow datasets. In particular, we develop a data-driven approach for estimating and predicting SWE dynamics using the Long Short-Term Memory neural network (LSTM) method. Our approach uses historical datasets (precipitation, air temperature, SWE, and snow thickness) collected at NRCS Snow Telemetry (SNOTEL) stations to train the LSTM network and current year data to predict SWE behavior. The performance of our prediction was compared for different prediction dates and prediction training datasets. Our results suggest that the proposed LSTM network can be an efficient tool for forecasting the SWE timeseries, as well as Peak SWE and snowmelt timing. Results showed that the window size impacts the model performance (where the Nash Sutcliffe efficiency (NSE) ranged from 0.96 to 0.85 and the Rooted Mean Square Error (RMSE) ranged from 0.038 to 0.07) with an optimum number that should be calibrated for different stations and climate conditions. In addition, by implementing the LSTM prediction capability in a cloud based site-monitoring platform, we automate model-data integration. By making the data accessible through a graphical web interface and an underlying API which exposes both training and prediction capabilities. The associated results can be made easily accessible to a broad range of stakeholders.

54 ENVIRONMENTAL SCIENCES↗