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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 649 records · Page 36

Biogenic manganese oxide nanoparticle formation by a multimeric multicopper oxidase Mnx

Bacteria that produce Mn oxides are extraordinarily skilled engineers of nanomaterials that contribute significantly to global biogeochemical cycles. Their enzyme-based reaction mechanisms may be genetically tailored for environmental remediation applications or bioenergy production. However, significant challenges exist for structural characterization of the enzymes responsible for biomineralization. The active Mn oxidase, Mnx, in Bacillus sp. PL-12 is a complex composed of a multicopper oxidase (MCO), MnxG, and two accessory proteins MnxE and MnxF. MnxG shares sequence similarity with other, structurally characterized MCOs. However, MnxE and MnxF have no similarity to any characterized proteins. The ~200 kDa complex has been recalcitrant to crystallization, so its structure is unknown. In this study, native mass spectrometry defines the subunit topology and copper binding of the Mnx complex, while high resolution electron microscopy visualizes the protein and nascent Mn oxide minerals. Furthermore, these data provide critical structural information for conceptualizing how Mnx produces nanoparticulate Mn oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measuring the value of microgrids: a benefit–cost framework

This study examines the costs and benefits of microgrids under a variety of business models. Many factors complicate a utility-planning benefit–cost framework when evaluating microgrids. For the purposes of this paper, a ‘microgrid’ is a group of interconnected resources and loads sharing a (usually) single point of interconnection with a larger grid, and capable of balancing load and resources when disconnected from the grid, through dispatch of resources and demand control and/or response. Economically, a microgrid can be examined from a variety of perspectives, and the picture is more complex than for typical utility investments. It is Electric Power Research Institute’s intent to provide unbiased and independent analysis of technology applications, examining economic questions from the perspectives of electricity end-consumers and society as a whole. Among the first steps is determining the point of view the analysis is to assume and narrowing down the set of economic questions to be addressed. Since the nature and major purpose of a microgrid is presumably to provide its internal customers with enhanced reliability and resilience, it is important to ask the question of perspective: For whom is the microgrid an economical choice, and compared with what?

Roark, Jeffrey↗

Detection and diversity of fungal nitric oxide reductase genes ( p450nor ) in agricultural soils

Members of the Fungi convert nitrate (NO 3 - ) and nitrite (NO 2 - ) to gaseous nitrous oxide (N 2 O) (denitrification), but the fungal contributions to N-loss from soil remain uncertain. Cultivation-based methodologies that include antibiotics to selectively assess fungal activities have limitations and complementary molecular approaches to assign denitrification potential to fungi are desirable. Microcosms established with soils from two representative U.S. Midwest agricultural regions produced N 2 O from added NO 3 - or NO 2 - in the presence of antibiotics to inhibit bacteria. Cultivation efforts yielded 214 fungal isolates belonging to at least 15 distinct morphological groups, of which 151 produced N 2 O from NO 2 - . Novel PCR primers targeting the p450nor gene that encodes the nitric oxide (NO) reductase responsible for N 2 O production in fungi yielded 26 novel p450nor amplicons from DNA of 37 isolates and 23 amplicons from environmental DNA obtained from two agricultural soils. The sequences shared 54-98% amino acid identity to reference P450nor sequences within the phylum Ascomycota , and expand the known fungal P450nor sequence diversity. p450nor was detected in all fungal isolates that produced N 2 O from nitrite, whereas nirK (encoding the NO-forming nitrite reductase) was amplified in only 13-74% of the N 2 O-forming isolates using two separate nirK primer sets. Altogether, our findings demonstrate the value of p450nor -targeted PCR to complement existing approaches to assess the fungal contributions to denitrification and N 2 O formation.

59 BASIC BIOLOGICAL SCIENCES↗

DataShare Recon Assistant Tool (DSRAT) v.1.0.x

SAND2023-06798O DataShare Recon Assistant Tool (DSRAT) software is used for capturing recon data and information in an emergency response situation on an Android device. Users can capture images, video, item description and spectra information in DSRAT and upload it to DataShare, which is a multi-server application that shares data in real-time to all nodes on the network. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Gilbert, Christina↗

Market Evolution: Wholesale Electricity Market Design for 21st Century Power Systems

Demand for affordable, reliable, domestically sourced, and low-carbon electricity is on the rise. This growing demand is driven in part by evolving public policy priorities, especially reducing the health and environmental impacts of electricity service and expanding energy access to under-served customers. Consequently, variable renewable energy resources comprise an increasing share ofelectricity generation globally. At the same time, new opportunities for addressing the variability of renewables are being strengthened through advances in smart grids, communications, and technologies that enable dispatchable demand response and distributed generation to extend to the mass market. A key challenge of merging these opportunities is market design -- determining how to createincentives and compensate providers justly for attributes and performance that ensure a reliable and secure grid -- in a context that fully realizes the potential of a broad array of sources of flexibility in both the wholesale power and retail markets. This report reviews the suite of wholesale power market designs in use and under consideration to ensure adequacy, security, and flexibilityin a landscape of significant variable renewable energy. It also examines considerations needed to ensure that wholesale market designs are inclusive of emerging technologies, such as demand response, distributed generation, and storage.

21st Century Power Partnership↗

Fast timing with µRWELL-PICOSEC detector technology

The µWELL-PICOSEC detector, which is based on Resistive Micro-Well (µRWELL) technology, is a novel concept for fast timing gaseous detectors that can provide timing resolution in the tens of picosecond range, making it ideal candidate for time-of-flight (TOF) technology for particle identification (PID) in particle physics experiments as well as for future medical instrumentation. The µRWELL-PICOSEC concept is based on a Cerenkov radiator that produces Cerenkov photons from high energetic charged particles, a photocathode layer that converts the Cerenkov photons into primary electrons, a µRWELL amplification layer that multiply the electrons through amplification in a CF4-based gas mixture and a pad-segmentation anode readout coupled with fast timing electronics to provide fast signal. Beam tests were carried out at the CERN SPS H4 beamline in summer 2023 and 2024. Preliminary results show timing performance of the order of 23 ps achievable with µRWELL-PICOSEC prototype. and position scan of the 100-pads of a multi-channel prototype was also performed to study time response uniformity of large area detector. In this talk, after a brief overview of the PICOSEC technology, we will present recent results with different single channel µRWELL-PICOSEC prototype designs and also the position scan results of the 100-pads large prototype to study timing response uniformity for large area µRWELL-PICOSEC detector. Finally, we will discuss the ongoing R&D effort to further improve the timing resolution and allow good position capabilities through charge sharing for large area.

Gnanvo, Kondo↗

Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1°C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2°C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3°C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23°C(±0.12°C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

54 ENVIRONMENTAL SCIENCES↗

Fault-tolerant wait-free shared objects

A concurrent system consists of processes communicating via shared objects, such as shared variables, queues, etc. The concept of wait-freedom was introduced to cope with process failures: each process that accesses a wait-free object is guaranteed to get a response even if all the other processes crash. However, if a wait-free object 'crashes,' all the processes that access that object are prevented from making progress. In this paper, we introduce the concept of fault-tolerant wait-free objects, and study the problem of implementing them. We give a universal method to construct fault-tolerant wait-free objects, for all types of 'responsive' failures (including one in which faulty objects may 'lie'). In sharp contrast, we prove that many common and interesting types (such as queues, sets, and test&set) have no fault-tolerant wait-free implementations even under the most benign of the 'non-responsive' types of failure. We also introduce several concepts and techniques that are central to the design of fault-tolerant concurrent systems: the concepts of self-implementation and graceful degradation, and techniques to automatically increase the fault-tolerance of implementations. We prove matching lower bounds on the resource complexity of most of our algorithms.

Jayanti, Prasad↗

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Idris, Husni↗

Human Research Program Standard Measures in Analogs

To ensure that a minimal set of measures, relevant to human spaceflight risks, is consistently captured from subjects participating in spaceflight analog environments • The data from these measures will be placed in an archive managed by HRP and made available to studies via data sharing agreements • HRP Standard Measures will constitute a database for: – Providing context for data acquired by concurrent experiments – Supporting or developing hypotheses – Evaluating the effectiveness of various countermeasure profiles – Comparing population responses to various mission durations and scenarios

Clement, Gilles R.↗

UNCERTAINTY ANALYSIS FOR THE TECHA RIVER DOSIMETRY SYSTEM

Uncertainties in the doses estimated for the members of the Techa River Cohort (TRC) are being estimated with a two-dimensional Monte Carlo approach. In order to provide more accurate and precise estimates of individual dose (and thus more precise estimates of radiation risk) for the members of the TRC, a new dosimetric calculation system, the Techa River Dosimetry System-2009 (TRDS-2009) has been prepared. The deterministic version of the improved dosimetry system TRDS-2009D was basically completed in April 2009. Recent developments in evaluation of dose-response models in light of uncertain dose have highlighted the importance of different types of uncertainties in the development of individual dose estimates. These include uncertain parameters that may be either shared (common to some or all individuals) or unshared (a unique value for each person whose dose is to be estimated) within the dosimetric cohort. The nature of the type of uncertainty may be aleatory (random variability of true values due to stochastic processes) or epistemic (due to lack of complete knowledge about a unique quantity). Finally, there is a need to identify whether the structure of the errors is either related to measurement (the estimate differs from the true value by an error that is stochastically independent of the true value; frequently called classical uncertainty) or related to grouping (the true value varies from the estimate by an error that is random and is independent of the estimate; frequently called Berkson uncertainty). An approach has been developed that identifies the nature of the various input parameters and calculational methods incorporated in the Techa River Dosimetry System (based on the TRDS-2009D implementation), and a stochastic calculation model has been prepared to estimate the uncertainties in the dose estimates. This article reviews the concepts of uncertainty analysis, the equations, and input parameters, and then identifies the authors’ interpretations of their general nature. It presents the approach selected so that the stochastic, Monte-Carlo, implementation of the dosimetry system - TRDS-2009MC - provides useful information regarding the uncertainties of the doses.

uncertainty analysis, radiation dosimetry, Techa R↗

A Quartet of PIF bHLH Factors Provides a Transcriptionally Centered Signaling Hub That Regulates Seedling Morphogenesis through Differential Expression-Patterning of Shared Target Genes in Arabidopsis

Dark-grown seedlings exhibit skotomorphogenic development. Genetic and molecular evidence indicates that a quartet of Arabidopsis Phytochrome (phy)-Interacting bHLH Factors (PIF1, 3, 4, and 5) are critically necessary to maintaining this developmental state and that light activation of phy induces a switch to photomorphogenic development by inducing rapid degradation of the PIFs. Here, using integrated ChIP–seq and RNA–seq analyses, we have identified genes that are direct targets of PIF3 transcriptional regulation, exerted by sequence-specific binding to G-box (CACGTG) or PBE-box (CACATG) motifs in the target promoters genome-wide. In addition, expression analysis of selected genes in this set, in all triple pif-mutant combinations, provides evidence that the PIF quartet members collaborate to generate an expression pattern that is the product of a mosaic of differential transcriptional responsiveness of individual genes to the different PIFs and of differential regulatory activity of individual PIFs toward the different genes. Together with prior evidence that all four PIFs can bind to G-boxes, the data suggest that this collective activity may be exerted via shared occupancy of binding sites in target promoters.

59 BASIC BIOLOGICAL SCIENCES↗

Validating (d,p gamma) as a Surrogate for Neutron Capture

The r-process is responsible for creating roughly half of the elements heavier than iron. It has recently become understood that the rates at which neutron capture reactions proceed at late times in the r-process may dramatically affect the final abundance pattern. However, direct measurements of neutron capture reaction rates on exotic nuclei are exceptionally difficult, necessitating the development of indirect approaches such as the surrogate technique. The (d,pγ) reaction at low energies was identified as a promising surrogate for the (n,γ) reaction, as both reactions share many characteristics. We report on a program to validate (d,pγ) as a surrogate for (n,γ) using 95 Mo as a target. The experimental campaign includes direct measurements of the γ-ray intensities from the decay of excited states populated in the 95 Mo(n,γ) and 95 Mo(d,pγ) reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗

Strategic Energy Plan: Playa de Ponce, Ponce, Puerto Rico

Un Nuevo Amanecer Inc. (UNA), a community-based NGO (501C(3)), sought technical assistance through the U.S. Department of Energy's (DOE's) Energy Technology Innovation Partnership Project (ETIPP) to develop a strategic energy plan (SEP) for the community of Playa de Ponce on the south coast of Puerto Rico. A SEP helps communities identify energy goals and priority projects, and outline strategies and actions to build a shared path toward their energy vision. The primary goal of this SEP is to collaboratively explore pathways for the community's energy future. Researchers from the National Laboratory of the Rockies (NLR) engaged with the community for a period of seven months and facilitated a series of in-person community engagement workshops along with ETIPP regional partner Puerto Rico Hispanic Federation, UNA, and community leaders. The SEP workshops were held twice, March 18-20 and June 24-26, 2025. Through facilitated discussions, the community worked together to define and articulate a clear vision for its short-, medium-, and long-term energy goals. The workshops played a key role in identifying the specific strategies and priority projects that would best suit the needs of the community. The discussions outlined the community's energy aspirations, establishing a shared vision, setting goals, and outlining the priority actions needed to bring them to fruition. During the workshops, the community shared some of the most pressing energy challenges that they face on a regular basis, such as high energy costs that disproportionately impact an aging population and unreliable electricity during extreme weather events that result in frequent power outages. These issues have also exacerbated risks to public health and safety of the community. In response, UNA requested technical assistance through ETIPP to inform the development of a SEP tailored to Playa de Ponce to support its energy vision. This document explores four community-driven energy strategies aligned with that vision. Figure 1 shows the strategies outlined in this plan, which are categorized into three focus areas as identified by the community: energy reliability; safety and security; and stakeholder participation, education, and capacity building. This document serves as a shared roadmap for developing and implementing energy solutions that meet the needs of Playa de Ponce. It is intended to serve as a public resource for the community, UNA, and local authorities - providing tools, information and a shared foundation to inform future implementation efforts. This plan is intended to complement ongoing planning frameworks at the municipal, regional, and island-wide levels. As a living document, this SEP can evolve alongside Playa de Ponce's changing energy goals, while offering a framework to help them realize their energy vision.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

BioSentinel: Biosensors for Deep-Space Radiation Study

The BioSentinel mission will be deployed on NASA's Exploration Mission 1 (EM-1) in 2018. We will use the budding yeast, Saccharomyces cerevisiae, as a biosensor to study the effect of deep-space radiation on living cells. The BioSentinel mission will be the first investigation of a biological response to space radiation outside Low Earth Orbit (LEO) in over 40 years. Radiation can cause damage such as double stand breaks (DSBs) on DNA. The yeast cell was chosen for this mission because it is genetically controllable, shares homology with human cells in its DNA repair pathways, and can be stored in a desiccated state for long durations. Three yeast strains will be stored dry in multiple microfluidic cards: a wild type control strain, a mutant defective strain that cannot repair DSBs, and a biosensor strain that can only grow if it gets DSB-and-repair events occurring near a specific gene. Growth and metabolic activity of each strain will be measured by a 3-color LED optical detection system. Parallel experiments will be done on the International Space Station and on Earth so that we can compare the results to that of deep space. One of our main objectives is to characterize the microfluidic card activation sequence before the mission. To increase the sensitivity of yeast cells as biosensors, desiccated yeast in each card will be resuspended in a rehydration buffer. After several weeks, the rehydration buffer will be exchanged with a growth medium in order to measure yeast growth and metabolic activity. We are currently working on a time-course experiment to better understand the effects of the rehydration buffer on the response to ionizing radiation. We will resuspend the dried yeast in our rehydration medium over a period of time; then each week, we will measure the viability and ionizing radiation sensitivity of different yeast strains taken from this rehydration buffer. The data obtained in this study will be useful in finalizing the card activation sequence for this mission.

Yeast↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗

The packing problem of uncertain multicasts

Summary Multicast performs better than unicast in delivering the same content from a fixed single source to a set of destinations. Many efforts have been made to optimize such kind of deterministic multicast, such as minimizing the transmission cost of each multicast session. In practice, it is not necessary that the source of each multicast session has to be in a specific location, as long as certain constraints are satisfied. Accordingly, applications usually meet a novel multicast with uncertain sources, ie, uncertain multicast. That is, multiple nodes have the responsibility to act as the root node of a multicast session. Prior proposals have addressed an uncertain multicast by constructing the minimum cost forest. However, it is still unknown how to efficiently share the network resources, when a set of uncertain multicast occupies the network simultaneously. To tackle such a challenging issue, we present the packing problem of uncertain multicasts (MPU) to minimize the total transmission cost, under the constraint of link capacity. We prove that the MPU problem is NP‐hard. An intrinsic solution is constructing the minimum cost forest for each uncertain multicast individually. This method, however, is inefficient and may be infeasible because of the constraint of link capacity. Thus, we design 2 dedicated greedy methods, named priority‐based and adjusting congested link, to approximate the optimal solution. The comprehensive results indicate that both of our 2 methods can find a feasible solution for the MPU problem. Moreover, given a set of uncertain multicasts, the adjusting congested link method can generate a desired transmission structure for each uncertain multicast and achieve the least total cost when packing them.

Ren, Bangbang↗