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At least 811 records · Page 45

Effects of short-interval reburns in the boreal forest on soil bacterial communities compared to long-interval reburns

Abstract Increasing fire frequency in some biomes is leading to fires burning in close succession, triggering rapid vegetation change and altering soil properties. We studied the effects of short-interval (SI) reburns on soil bacterial communities of the boreal forest of northwestern Canada using paired sites (n = 44). Both sites in each pair had burned in a recent fire; one site had burned within the previous 20 years before the recent fire (SI reburn) and the other had not. Paired sites were closely matched in prefire ecosite characteristics, prefire tree species composition, and stand structure. We hypothesized that there would be a significant effect of short vs. long fire-free intervals on community composition and that richness would not be consistently different between paired sites. We found that Blastococcus sp. was consistently enriched in SI reburns, indicating its role as a strongly ‘pyrophilous’ bacterium. Caballeronia sordidicola was consistently depleted in SI reburns. The depletion of this endophytic diazotroph raises questions about whether this is contributing to—or merely reflects—poor conifer seedling recolonization post-fire at SI reburns. While SI reburns had no significant effect on richness, dissimilarity between short- and long-interval pairs was significantly correlated with difference in soil pH, and there were small significant changes in overall community composition.

54 ENVIRONMENTAL SCIENCES↗

LA100 Equity Strategies. Chapter 1: Justice as Recognition

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided and community-tailored strategies that aim to operationalize recognition and procedural justice. This chapter focuses on recognition justice, identifying and analyzing past and present social, cultural, and institutional barriers to affordable and clean energy for LA communities, as well as disparities in the distribution of energy system burdens and benefits. Acknowledging historical and structural factors behind current energy inequities is a first step in developing energy equity strategies for the Los Angeles Department of Water and Power (LADWP) to achieve distributional justice - the just and equitable distribution of energy benefits and burdens in LA's energy transition. Recognition, procedural, and distributional justice are the three tenets of energy justice around which the LA100 Equity Strategies project is organized. In the United States, theory and practice around justice have historically focused on unequal distribution of environmental benefits and burdens. The historical siting of hazardous infrastructure such as power plants and transportation corridors in communities of color and low-income communities has disproportionately concentrated negative environmental impacts in their neighborhoods. Those inequities are reproduced via programs, policies, and other efforts (e.g., zoning and regulations, rebates and incentives, lending, investment, and financing) that directly affect people's lives and livelihoods. In recent decades, energy justice scholars and activists broadened their analysis to examine how environmental inequities intersect with other forms of social difference in the distribution of energy benefits and burdens. This approach investigates how differences in class, race, gender, age, and abilities, among others, intersect to understand the social, cultural, and institutional processes that create and perpetuate energy inequities. The LA100 Equity Strategies project embraces this approach to developing a more just clean energy future for LA. Because recognizing and understanding past and existing inequities is vital to addressing them in ways that ensure an equitable energy transition for all Angelenos, this chapter focuses on identifying and analyzing the challenges and inequities of LA's past and existing energy system, including LADWP programs.

community↗

Polymer genome–based prediction of gas permeabilities in polymers

Abstract Predicting gas permeabilities of polymers a priori is a long-standing challenge within the membrane research community that has important applications for membrane process design and ultimately widespread adoption of membrane technology. From early attempts based on free volume and cohesive energy to more recent group contribution methods, the ability to predict membrane permeability has improved in terms of accuracy. However, these models usually stay “within the paper”, i.e. limited model details are provided to the wider community such that adoption of these predictive platforms is limited. In this work, we combined an advanced polymer chemical structure fingerprinting method with a large experimental database of gas permeabilities to provide unprecedented prediction precision over a large range of polymer classes. No prior knowledge of the polymer is needed for the prediction other than the repeating unit chemical formula. In addition, we have incorporated this model into the existing Polymer Genome project to make it open to the membrane research community.

Polymer Science↗

Functional Equivalence Acceptance Testing of FUN3D for Entry Descent and Landing Applications

The functional equivalence of the unstructured grid code FUN3D to the the structured grid code LAURA (Langley Aerothermodynamic Upwind Relaxation Algorithm) is documented for applications of interest to the Entry, Descent, and Landing (EDL) community. Examples from an existing suite of regression tests are used to demonstrate the functional equivalence, encompassing various thermochemical models and vehicle configurations. Algorithm modifications required for the node-based unstructured grid code (FUN3D) to reproduce functionality of the cell-centered structured code (LAURA) are also documented. Challenges associated with computation on tetrahedral grids versus computation on structured-grid derived hexahedral systems are discussed.

Gnoffo, Peter A.↗

Overview of NASARTI (NASA Radiation Track Image) Program: Highlights of the Model Improvement and the New Results

This presentation summarizes several years of research done by the co-authors developing the NASARTI (NASA Radiation Track Image) program and supporting it with scientific data. The goal of the program is to support NASA mission to achieve a safe space travel for humans despite the perils of space radiation. The program focuses on selected topics in radiation biology that were deemed important throughout this period of time, both for the NASA human space flight program and to academic radiation research. Besides scientific support to develop strategies protecting humans against an exposure to deep space radiation during space missions, and understanding health effects from space radiation on astronauts, other important ramifications of the ionizing radiation were studied with the applicability to greater human needs: understanding the origins of cancer, the impact on human genome, and the application of computer technology to biological research addressing the health of general population. The models under NASARTI project include: the general properties of ionizing radiation, such as particular track structure, the effects of radiation on human DNA, visualization and the statistical properties of DSBs (DNA double-strand breaks), DNA damage and repair pathways models and cell phenotypes, chromosomal aberrations, microscopy data analysis and the application to human tissue damage and cancer models. The development of the GUI and the interactive website, as deliverables to NASA operations teams and tools for a broader research community, is discussed. Most recent findings in the area of chromosomal aberrations and the application of the stochastic track structure are also presented.

Ponomarev, Artem L.↗

Improved representation of black carbon mixing structures suggests stronger direct radiative heating

Black carbon significantly influences the Earth system because of its strong solar radiation absorption. However, its direct radiative effect remains poorly understood in current climate models, partly because current climate models oversimplify the diverse structures formed when black carbon mixes with other atmospheric components. Here we show that incorporating more realistic, multi-mixing-structure representations of black carbon increases the direct radiative effect. We find that aged black carbon particles, with thicker coatings and higher embedded fractions, enhance the direct radiative effect more efficiently. Using machine learning alongside the Community Earth System Model, we show that the direct radiative effect at the top of the atmosphere in regions with heavy black carbon pollution is 31.6% greater when multi-mixing structures are considered. These findings highlight the importance of modeling complex mixing structures of particle-resolved black carbon to accurately capture their warming impacts on global atmosphere, particularly in highly polluted regions.

54 ENVIRONMENTAL SCIENCES↗

National Community Solar Partnership Technical Assistance: Together New Orleans [Slides]

This product is the outcome of a National Community Solar Partnership (NCSP) Technical Assistance (TA) request. TA is provided to NCSP members at no cost and upon request. Some TA, this project included, is later generalized and published to help educate the broader community, share findings, and provide best practices. Together New Orleans submitted a TA request to the NCSP aiming to obtain a third-party analysis on several rate compensation structures that could make project development more financially advantageous.

14 SOLAR ENERGY↗

A Case Study about Energy and Cost Impacts for Different Community Scenarios Using a Community-Scale Building Energy Modeling Tool

The United States building sector consumed approximately 75% of electricity in 2019. By implementing renewable energy technologies and control strategies into buildings, future buildings will serve as energy generators as well as consumers. To accommodate this transition, communications among buildings and between buildings and the grid could provide more possibilities to optimize the energy performance of buildings. This paper develops a community-scale building energy model tool and conducts a case study adopting behind-the-meter distributed energy resources, sharing energy in different buildings, and using different electricity tariff structures. Three scenarios are studied: (1) electricity only supplied by the grid, (2) photovoltaic (PV) panels installed on and available to some but not all buildings, and (3) a connected community. To consider the impacts of locations and energy tariffs, this paper selects four cities and three electricity tariffs to evaluate the energy and cost performances of these three scenarios. The results show that the PV panels in Scenario 2 reduce 25% to 33% of the community-level electricity consumption and 20% to 30% of the community-level electricity cost compared with Scenario 1 in all studied locations and energy tariffs. By considering power management in the connected community (Scenario 3), the electricity consumption and cost can be further reduced by 6% to 7% and 5% to 11%, respectively, compared with Scenario 2.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Architecting Ourselves: Schema to Facilitate Growth of the International Space Architecture Community

This paper develops a conceptual model, adapted from the way research and development non-profits and universities tend to be organized, that could help amplify the reach and effectiveness of the international space architecture community. The model accommodates current activities and published positions, and increases involvement by allocating accountability for necessary professional and administrative activities. It coordinates messaging and other outreach functions to improve brand management. It increases sustainability by balancing volunteer workload. And it provides an open-ended structure that can be modified gracefully as needs, focus, and context evolve. Over the past 20 years, Space Architecture has attained some early signs of legitimacy as a discipline: an active, global community of practicing and publishing professionals; university degree programs; a draft undergraduate curriculum; and formal committee establishment within multiple professional organizations. However, the nascent field has few outlets for expression in built architecture, which exacerbates other challenges the field is experiencing in adolescence: obtaining recognition and inclusion as a unique contributor by the established aerospace profession; organizing and managing outreach by volunteers; striking a balance between setting admittance or performance credentials and attaining a critical mass of members; and knowing what to do, beyond sharing common interests, to actually increase the market demand for space architecture. This paper develops a conceptual model, adapted from the way research-anddevelopment non-profits and universities tend to be organized, that could help amplify the reach and effectiveness of the international space architecture community. The model accommodates current activities and published positions, and increases involvement by allocating accountability for necessary professional and administrative activities. It coordinates messaging and other outreach functions to improve brand management. It increases sustainability by balancing volunteer workload. And it provides an open-ended structure that can be modified gracefully as needs, focus, and context evolve. This organizational model is offered up for consideration, debate, and toughening by the space architecture community at large.

space architecure↗

Microbially mediated mechanisms underlie soil carbon accrual by conservation agriculture under decade-long warming

Increasing soil organic carbon (SOC) in croplands by switching from conventional to conservation management may be hampered by stimulated microbial decomposition under warming. Here, we test the interactive effects of agricultural management and warming on SOC persistence and underlying microbial mechanisms in a decade-long controlled experiment on a wheat-maize cropping system. Warming increased SOC content and accelerated fungal community temporal turnover under conservation agriculture (no tillage, chopped crop residue), but not under conventional agriculture (annual tillage, crop residue removed). Microbial carbon use efficiency (CUE) and growth increased linearly over time, with stronger positive warming effects after 5 years under conservation agriculture. According to structural equation models, these increases arose from greater carbon inputs from the crops, which indirectly controlled microbial CUE via changes in fungal communities. As a result, fungal necromass increased from 28 to 53%, emerging as the strongest predictor of SOC content. Collectively, our results demonstrate how management and climatic factors can interact to alter microbial community composition, physiology and functions and, in turn, SOC formation and accrual in croplands.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing the potential of deep learning for protein–ligand docking

The effects of ligand binding on protein structures and their in vivo functions carry numerous implications for modern biomedical research and biotechnology development efforts such as drug discovery. Although several deep learning (DL) methods and benchmarks designed for protein–ligand docking have recently been introduced, so far no previous works have systematically studied the behaviour of the latest docking and structure prediction methods within the broadly applicable context of: (1) using predicted (apo) protein structures for docking (for example, for applicability to new proteins); (2) binding multiple (cofactor) ligands concurrently to a given target protein (for example, for enzyme design); and (3) having no previous knowledge of binding pockets (for example, for generalization to unknown pockets). To enable a deeper understanding of the real-world utility of docking methods, we introduce PoseBench, a comprehensive benchmark for broadly applicable protein–ligand docking. PoseBench enables researchers to rigorously and systematically evaluate DL methods for apo-to-holo protein–ligand docking and protein–ligand structure prediction using both primary ligand and multiligand benchmark datasets, the latter of which we introduce to the DL community. Empirically, using PoseBench, we find that: (1) DL cofolding methods generally outperform comparable conventional and DL docking baseline algorithms, but popular methods such as AlphaFold 3 are still challenged by prediction targets with new protein–ligand binding poses; (2) certain DL cofolding methods are highly sensitive to their input multiple sequence alignments, whereas others are not; and (3) DL methods struggle to strike a balance between structural accuracy and chemical specificity when predicting new or multiligand protein targets.

Morehead, Alex [Lawrence Berkeley National Laborat↗

Scrambling Signal Modularity in Bottom-up Assembled Synthetic Pseudomonas Consortia Reveals Robust Information Transfer

There is immense potential in crafting synthetic microbial communities for application in human health, agriculture, the environment, and even biomanufacturing where an appropriately constructed consortium can be assembled with tremendous biosynthetic or degradative capabilities. In many of these cases, bacterial signaling serves as a form of intercellular information transfer that guides the collective’s behavior. Such communication is complex, as many signals, signal disruptors, microbial species, physical barriers, and spatiotemporal constraints may be involved. Here, in this work, we demonstrate that a multisignal pathway for molecular information transfer within a consortium of several Pseudomonas spp. can be scrambled (genetically and organizationally) while the original message is still effectively conveyed. Assembled from the bottom up, we have employed two types of signaling molecules (i) a redox active secondary metabolite (rhizospheric signal, phloroglucinol), and (ii) a bacterial quorum sensing signal (3-oxo-C12 acylhomoserine lactone, AI-1). These signals can be intraconverted and acted upon by designated community members. We show how the order in which the signals are received, transduced, and subsequently transmitted can be rearranged with minimal impact on the intended outcome. In the consortial context, we found this messaging structure can be remarkably robust. Inspired by rhizospheric molecular signaling mechanisms, this work provides a conceptual framework for designing signaling and information transfer processes within assembled communities.

Biological and medical sciences↗

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗

Evolution of the SARS-CoV -2 proteome in three dimensions (3D) during the first 6 months of the COVID -19 pandemic

Understanding the molecular evolution of the SARS-CoV-2 virus as it continues to spread in communities around the globe is important for mitigation and future pandemic preparedness. Three-dimensional structures of SARS-CoV-2 proteins and those of other coronavirusess archived in the Protein Data Bank were used to analyze viral proteome evolution during the first 6 months of the COVID-19 pandemic. Analyses of spatial locations, chemical properties, and structural and energetic impacts of the observed amino acid changes in >48 000 viral isolates revealed how each one of 29 viral proteins have undergone amino acid changes. Catalytic residues in active sites and binding residues in protein–protein interfaces showed modest, but significant, numbers of substitutions, highlighting the mutational robustness of the viral proteome. Energetics calculations showed that the impact of substitutions on the thermodynamic stability of the proteome follows a universal bi-Gaussian distribution. Here detailed results are presented for potential drug discovery targets and the four structural proteins that comprise the virion, highlighting substitutions with the potential to impact protein structure, enzyme activity, and protein–protein and protein–nucleic acid interfaces. Characterizing the evolution of the virus in three dimensions provides testable insights into viral protein function and should aid in structure-based drug discovery efforts as well as the prospective identification of amino acid substitutions with potential for drug resistance.

59 BASIC BIOLOGICAL SCIENCES↗

Microanalysis of Primary Biological Particles from Model Grass over Its Life Cycle

Airborne biological aerosols are an integral part of the atmosphere–biosphere interface and significantly impact the environment and Earth’s climate. Primary biological particles such as fungal spores, bacteria, and fragments of plant debris are emitted directly from the biosphere into the atmosphere. The phyllosphere (aboveground plant surfaces) is one of the major habitats for different microbes. Here, atmospheric emissions of primary biological particles from model grass Brachypodium distachyon were monitored by online particle number concentration counting at eight principal growth stages starting from leaf development to senescence. Particles collected at each of the growth stages were then characterized using microspectroscopy techniques. Our findings indicate that the morphological and compositional characteristics of emitted biological particles are highly variable at the different growth stages. We identified fungal spores as the most abundant biological particles in the heading stage, while bacteria were most abundant in the flowering and fruit development stages. Understanding differences in the composition and morphology of biological particles during the plant life cycle provides more accurate and reliable insights on structural, functional, and biochemical properties of plant systems, as well as their interactions with microbial communities. This study also provides insights into Earth geoscience system models that represent primary biological particle emissions from the biosphere.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Event-modeled Risk Assessment Using Linked Diagrams

Event Modeling Risk Assessment using Linked Diagrams (EMRALD) is a software tool developed at INL for researching the capabilities of dynamic PRA (Probabilistic Risk Assessment). In order to promote the effective use of dynamic PRA by the general community, EMRALD focuses on the following key aspects: Simplifying the modeling process by providing a structure that corresponds to traditional PRA modeling methods Providing a user interface (UI) that makes it easy for the user to model and visualize complex interactions Allowing the user to couple with other analysis applications such as physics based simulations. This includes one-way communication for most applications and two-way loose coupling for customizable applications Providing the sequence and timing of events that lead to the specified outcomes when calculating results Traditional aspects of components with basic events, fault trees, and event trees are all captured in a dynamic framework of state diagrams, which are displayed.

Prescott, SteveR↗

DISCOverflow

Procedure for reverse engineering binary files and storing the result in a graph database structure for later analysis. This is achieved through the use of Python, angr, and OrientDB Community Edition.

Beckman, BryanR↗

Atomic-Scale Computational and Experimental Investigation of Twinning Mechanisms in HCP Systems

One of the major goals of the Materials Science and Engineering community is to achieve a fundamental understanding of how alloying affects the mechanical properties of structural materials. Titanium (Ti) and its alloys are particularly in demand due to their relatively lightweight, high strength and corrosion resistance. The low-temperature ductility of hexagonal close-packed (hcp) Ti known as α- Ti is linked to twinning. The addition of alloying elements can affect the deformation mechanisms leading to the change in macro-scale mechanical properties. To understand these effects, our objective is to study and quantify the energetics and kinetics of substitutional and interstitial solutes on the deformation mechanisms of hcp alloys.

36 MATERIALS SCIENCE↗