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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Iron rescues glucose-mediated photosynthesis repression during lipid accumulation in the green alga Chromochloris zofingiensis

Energy status and nutrients regulate photosynthetic protein expression. The unicellular green alga Chromochloris zofingiensis switches off photosynthesis in the presence of exogenous glucose (+Glc) in a process that depends on hexokinase (HXK1). Here, we show that this response requires that cells lack sufficient iron (–Fe). Cells grown in –Fe+Glc accumulate triacylglycerol (TAG) while losing photosynthesis and thylakoid membranes. However, cells with an iron supplement (+Fe+Glc) maintain photosynthesis and thylakoids while still accumulating TAG. Proteomic analysis shows that known photosynthetic proteins are most depleted in heterotrophy, alongside hundreds of uncharacterized, conserved proteins. Photosynthesis repression is associated with enzyme and transporter regulation that redirects iron resources to (a) respiratory instead of photosynthetic complexes and (b) a ferredoxin-dependent desaturase pathway supporting TAG accumulation rather than thylakoid lipid synthesis. Combining insights from diverse organisms from green algae to vascular plants, we show how iron and trophic constraints on metabolism aid gene discovery for photosynthesis and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Influence of intrinsic and extrinsic attributes on neonate survival in an invasive large mammal

Abstract Understanding factors influencing survival of neonates for wild species is important for successful management, particularly for determining drivers of population dynamics. Wild pigs ( Sus scrofa ) are invasive and populations are rapidly increasing in part due to high reproductive capacity. Survival of adults is generally high, however, survival of piglets, and particularly neonates, is largely unknown. We located neonates at the natal nest and quantified survival in relation to individual and maternal biological attributes, and environmental variables. During 2017–2020, we captured 50 neonates from 13 litters and documented 28 mortalities (56%) over six weeks. Survival was positively influenced by pelage coloration, likely as a form of camouflage from predators. Male neonates had higher survival. They were born larger than females, which could be beneficial for thermoregulation and competition for milk. Neonates born to larger sows had lower survival. Sow size was positively correlated with litter size, and this finding may reflect the increased nutritional demands of sustaining large litters, or difficulties in defending more neonates against predators. Neonates born in warmer months had higher survival than those born in cooler months. Neonates are inefficient thermoregulators, thus being born in warmer months could be beneficial for maintaining homeostasis as well as access to more food resources. These are the largest and most complete data for neonate wild pig survival and will inform population models for the development of management strategies to reduce negative impacts of this destructive invasive species on native ecosystems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Improving Sanitation and Health in Rural Alaska

In rural Alaskan communities personal health is threatened by energy costs and limited access to clean water, wastewater management, and adequate nutrition. Fuel-­‐based energy systems are significant factors in determining local accessibility to clean water, sanitation and food. Increasing fuel costs induce a scarcity of access and impact residents' health. The University of Alaska Fairbanks (UAF) School of Natural Resources and Agricultural Sciences (SNRAS), NASA's Ames Research Center, and USDA Agricultural Research Service (ARS) have joined forces to develop high‐efficiency, low­‐energy consuming techniques for water treatment and food production in rural circumpolar communities. Methods intended for exploration of space and establishment of settlements on the Moon or Mars will ultimately benefit Earth's communities in the circumpolar north. The initial phase of collaboration is completed. Researchers from NASA Ames Research Center and SNRAS, funded by the USDA­‐ARS, tested a simple, reliable, low-energy sewage treatment system to recycle wastewater for use in food production and other reuse options in communities. The system extracted up to 70% of the water from sewage and rejected up to 92% of ions in the sewage with no carryover of toxic effects. Biological testing showed that plant growth using recovered water in the nutrient solution was equivalent to that using high‐purity distilled water. With successful demonstration that the low energy consuming wastewater treatment system can provide safe water for communities and food production, the team is ready to move forward to a full‐scale production testbed. The SNRAS/NASA team (including Alaska students) will design a prototype to match water processing rates and food production to meet rural community sanitation needs and nutritional preferences. This system would be operated in Fairbanks at the University of Alaska through SNRAS. Long­‐term performance will be validated and operational needs of the system determined. The testbed will be a part of the university education and operator training program. The "Forgotten Alaska" has long awaited this technology to augment the traditional

Plant Growth↗
NASA NTRS2018

In-space Biomanufacturing Using CO2 with Methylobacterium Extorquens

Long duration missions to deep space will require new approaches for supplying astronauts. In-space microbial manufacturing could generate many important compounds (such as nutrients, pharmaceuticals and fuels) but there are significant barriers to deploying reliable bioproduction platforms to space. These include ensuring adequate production and proper purification of the desired product, especially in the unique radiation and microgravity environment. Here we are focused on developing methods and technologies to feed microbial factories using the resources available in space. CO2, found in abundance in spacecraft cabins and the Mars atmosphere, can be sequestered and converted into bioproducts. While autotrophic organisms can use CO2 directly, they are generally slow growing and have less-developed biotechnology toolkits. Therefore we are developing an alternative paradigm in which CO2 is first reduced to more energetic carbon compounds that can support more rapid growth of workhorse biotechnology platforms (E. coli, S. cerevisiae, P. pastoris).Various technologies exist or are being developed to convert CO2. For example, the Sabatier system currently installed on the ISS, reacts CO2 and H2 to generate CH4 and H2O. This methane could be consumed by engineered methanotrophic bacteria. Alternatively, electrochemical systems can convert CO2 into formate (CHO2) which could be consumed by formatotrophic bacteria. In either case, synthetic biology techniques allow these microbes to serve as reprogrammable biofactories capable of producing a vast number or products.

Synthetic biology; Formate metabolism↗
DOE OSTI2020

A genome resource for green millet Setaria viridis enables discovery of agronomically valuable loci

Abstract Wild and weedy relatives of domesticated crops harbor genetic variants that can advance agricultural biotechnology. Here we provide a genome resource for the wild plant green millet ( Setaria viridis ), a model species for studies of C 4 grasses, and use the resource to probe domestication genes in the close crop relative foxtail millet ( Setaria italica ). We produced a platinum-quality genome assembly of S. viridis and de novo assemblies for 598 wild accessions and exploited these assemblies to identify loci underlying three traits: response to climate, a ‘loss of shattering’ trait that permits mechanical harvest and leaf angle, a predictor of yield in many grass crops. With CRISPR–Cas9 genome editing, we validated Less Shattering1 ( SvLes1 ) as a gene whose product controls seed shattering. In S. italica , this gene was rendered nonfunctional by a retrotransposon insertion in the domesticated loss-of-shattering allele SiLes1-TE (transposable element). This resource will enhance the utility of S. viridis for dissection of complex traits and biotechnological improvement of panicoid crops.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Brain Connectivity Workshop Series Report

The National Institutes of Health (NIH) BRAIN Initiative aims to accelerate development and application of technologies that show how individual brain cells in complex neural circuits interact at the speed of thought and action. Complete wiring diagrams of the mammalian brain will revolutionize the capabilities of researchers to formulate and test models of how activity within brain circuits drives coordinated function and behavior. A top priority for the BRAIN Initiative, motivated by the strategic guidance of the BRAIN 2.0 Working Group report, is to muster the resources and foster the collaborations needed to generate these wiring diagrams at the level of long-range projections (“projectomes”) and synapses (“connectomes”) in whole mammalian brains, including those from rodents, humans, and other large-brained mammals. Achieving the scale and resolution necessary to characterize and use these projectomes and connectomes will not only push the boundaries of current imaging and computational capabilities to generate faster, cheaper, and more scalable technologies, but also drive broad innovation in data science, artificial intelligence, and machine learning.

42 ENGINEERING↗
NASA NTRS2014

Investigation of Bio-Regenerative Life Support and Trash-to-Gas Experiment on a 4-Month Mars Simulation Mission

Future crewed missions to other planets or deep space locations will require regenerative Life Support Systems (LSS) as well as recycling processes for mission waste. Constant resupply of many commodity materials will not be a sustainable option for deep space missions, nor will stowing trash on board a vehicle or at a lunar or Martian outpost. The habitable volume will decline as the volume of waste increases. A complete regenerative environmentally controlled life support system (ECLSS) on an extra-terrestrial outpost will likely include physico-chemical and biological technologies, such as bioreactors and greenhouse modules. Physico-chemical LSS do not enable food production and bio-regenerative LSS are not stable enough to be used alone in space. Mission waste that cannot be recycled into the bio-regenerative ECLSS can include excess food, food packaging, clothing, tape, urine and fecal waste. This waste will be sent to a system for converting the trash into high value products. Two crew members on a 120 day Mars analog simulation, in collaboration with Kennedy Space Centers (KSC) Trash to Gas (TtG) project investigated a semi-closed loop system that treated non-edible biomass and other logistical waste for volume reduction and conversion into useful commodities. The purpose of this study is to show how plant growth affects the amount of resources required by the habitat and how spent plant material can be recycled. Real-time data was sent to the reactor at KSC in Florida for replicating the analog mission waste for laboratory operation. This paper discusses the 120 day mission plant growth activity, logistical and plant waste management, power and water consumption effects of the plant and logistical waste, and potential energy conversion techniques using KSCs TtG technology.

Trash-to-Gas↗
DOE OSTI2021

Progress Towards a Comprehensive Approach for Habitat Restoration in the Columbia Basin: Case Study in the Grande Ronde River

Abstract Despite immense resources directed towards habitat restoration, recovering fish populations remains a daunting and perplexing issue. In 2015, recommendations for a comprehensive approach to habitat restoration in the Columbia River basin were published in Fisheries, which included elements of landscape ecology and resilience, broad public support, governance for collaboration and integration, and capacity for learning and adaptation. Using the Grande Ronde River basin as a case study, we convened a working group consisting of local restoration practitioners, managers, and researchers involved in habitat restoration research, monitoring, and evaluation to assess progress towards meeting these recommendations. We concluded that partnerships and collaborations in governance have been formed and research using a landscape perspective has been integrated into decision making, but efforts would benefit from gaining broader public support, formalizing an adaptive management strategy, and defining objectives and indicators for biological and ecological diversity. Continued progress will require consistent policy and funding support from the broader region. We envision this self-assessment at the 5-year milestone would be helpful to other groups facing similar challenges.

White, Seth M. (ORCID:0000000349186865)↗
NASA NTRS2014

Investigation of Bio-Regenerative Life Support and Trash-To-Gas Experiment on a 4 Month Mars Simulation Mission

Future crewed missions to other planets or deep space locations will require regenerative Life Support Systems (LSS) as well as recycling processes for mission waste. Constant resupply of many commodity materials will not be a sustainable option for deep space missions, nor will storing trash on board a vehicle or at a lunar or Martian outpost. The habitable volume will decline as the volume of waste increases. A complete regenerative environmentally controlled life support system (ECLSS) on an extra-terrestrial outpost will likely include physico-chemical and biological technologies, such as bioreactors and greenhouse modules. Physico-chemical LSS do not enable food production and bio-regenerative LSS are not stable enough to be used alone in space. Mission waste that cannot be recycled into the bio-regenerative ECLSS can include excess food, food packaging, clothing, tape, urine and fecal waste. This waste will be sent to a system for converting the trash into the high value products. Two crew members on a 120 day Mars analog simulation, in collaboration with Kennedy Space Centers (KSC) Trash to Gas (TtG) project investigated a semi-closed loop system that treated non-edible biomass and other logistical waste for volume reduction and conversion into useful commodities. The purposes of this study are to show the how plant growth affects the amount of resources required by the habitat and how spent plant material can be recycled. Real-time data was sent to the reactor at KSC in Florida for replicating the analog mission waste for laboratory operation. This paper discusses the 120 day mission plant growth activity, logistical and plant waste management, power and water consumption effects of the plant and logistical waste, and potential energy conversion techniques using KSCs TtG reactor technology.

trash to gas↗
DOE OSTI2022

Enabling Technology - Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors

The project “Enabling Technology - Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors” focuses on developing transformational and disruptive food technologies, specifically in the area of alternative protein and meat production techniques. The impetus for developing alternative protein technologies include reducing intensive greenhouse gas emissions and energy/land/water usages associated with conventional meat production (animal agriculture). Additional rationales include providing alternatives to livestock rearing as a means of reducing antimicrobial resistance (most antibiotic and antimicrobial use occurs in food-producing animals), as well as the transmission of zoonotic diseases. The goal of this ARPA-E project was to research and develop novel and effective technologies to produce cell-cultured meat (also named in vitro meat, cultivated meat). Cell-cultured meat is an alternative protein or meat technology that involves directly growing muscle and fat tissues (which comprise meat) without using the full animal. This offers benefits in terms of animal welfare (elimination of animal slaughter), while also being projected to be more resource efficient in terms of metrics such as land use and greenhouse gas emissions, especially when compared to beef and lamb. Cell cultured meat additionally offers greater control over the cultivated cells, enabling more precise control over nutrition and taste. For example, cultured cells could be tuned to produce antioxidants such as carotenoids to improve human health. However, to date there are no scalable methods of producing cell-cultured meat cheaply at a large scale.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop

The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding. Although tempering- and order parameter-based techniques are commonly used for similar rare-event problems, the computational costs or the need for a priori knowledge about the system often present a challenge in their effective use. DDMD overcomes these challenges by adaptively learning from an ensemble of running MD simulations using generic contact maps as the raw input. DeepDriveMD enables on-the-fly learning of a low-dimensional latent representation and guides the simulation toward the undersampled regions while optimizing the resources to explore the relevant parts of the phase space. We showed that DDMD estimates the free energy landscape of the RNA stem-loop reasonably well at room temperature. Our simulation framework runs at a constant temperature without external biasing potential, hence preserving the information on transition rates, with a computational cost much lower than that of the simulations performed with external biasing potentials. Here, we also introduced a reweighting strategy for obtaining unbiased free energy surfaces and presented a qualitative analysis of the latent space. This analysis showed that the latent space captures the relevant slow degrees of freedom for the RNA folding problem of interest. Finally, throughout the manuscript, we outlined how different parameters are selected and optimized to adapt DDMD for this system. We believe this compendium of decision-making processes will help new users adapt this technique for the rare-event sampling problems of their interest.

Gupta, Ayush↗
DOE OSTI2024

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Low 13 C- 13 C abundances in abiotic ethane

Distinguishing biotic compounds from abiotic ones is important in resource geology, biogeochemistry, and the search for life in the universe. Stable isotopes have traditionally been used to discriminate the origins of organic materials, with particular focus on hydrocarbons. However, despite extensive efforts, unequivocal distinction of abiotic hydrocarbons remains challenging. Recent development of clumped-isotope analysis provides more robust information because it is independent of the stable isotopic composition of the starting material. Here, we report data from a 13 C- 13 C clumped-isotope analysis of ethane and demonstrate that the abiotically-synthesized ethane shows distinctively low 13 C- 13 C abundances compared to thermogenic ethane. A collision frequency model predicts the observed low 13 C- 13 C abundances (anti-clumping) in ethane produced from methyl radical recombination. In contrast, thermogenic ethane presumably exhibits near stochastic 13 C- 13 C distribution inherited from the biological precursor, which undergoes C-C bond cleavage/recombination during metabolism. Further, we find an exceptionally high 13 C- 13 C signature in ethane remaining after microbial oxidation. In summary, the approach distinguishes between thermogenic, microbially altered, and abiotic hydrocarbons. The 13 C- 13 C signature can provide an important step forward for discrimination of the origin of organic molecules on Earth and in extra-terrestrial environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Integrating environmental understanding into freshwater floatovoltaic deployment using an effects hierarchy and decision trees

Abstract In an era of looming land scarcity and environmental degradation, the development of low carbon energy systems without adverse impacts on land and land-based resources is a global challenge. ‘Floatovoltaic’ energy systems—comprising floating photovoltaic (PV) panels over water—are an appealing source of low carbon energy as they spare land for other uses and attain greater electricity outputs compared to land-based systems. However, to date little is understood of the impacts of floatovoltaics on the hosting water body. Anticipating changes to water body processes, properties and services owing to floatovoltaic deployment represents a critical knowledge gap that may result in poor societal choices and water body governance. Here, we developed a theoretically-derived hierarchical effects framework for the assessment of floatovoltaic impacts on freshwater water bodies, emphasising ecological interactions. We describe how the presence of floatovoltaic systems may dramatically alter the air-water interface, with subsequent implications for surface meteorology, air-water fluxes and physical, chemical and biological properties of the recipient water body. We apply knowledge from this framework to delineate three response typologies—‘ magnitude’ , those for which the direction and magnitude of effect can be predicted; ‘ direction’ , those for which only the direction of effect can be predicted; and ‘ uncertain’ , those for which the response cannot be predicted—characterised by the relative importance of levels in the effects hierarchy. Illustrative decision trees are developed for an example water body response within each typology, specifically, evaporative water loss, cyanobacterial biomass, and phosphorus release from bed sediments, and implications for ecosystem services, including climate regulation, are discussed. Finally, the potential to use the new understanding of likely ecosystem perturbations to direct floatovoltaic design innovations and identify future research priorities is outlined, showcasing how inter-sectoral collaboration and environmental science can inform and optimise this low carbon, land-sparing renewable energy for ecosystem gains.

Environmental Sciences & Ecology↗
DOE OSTI2026

Learned adaptive properties for mitigation of weight perturbations in embedded spiking networks

Recent years have seen an increased importance of neural network inference in edge-based scenarios, which impose size and power constraints requiring novel computing devices. These same edge scenarios may require operating over long periods of time, or exposure to extreme environments, resulting in a drift of neural network weights that cause degraded performance. In searching for ways to develop neural network approaches that perform robustly under these conditions, we propose a biologically-inspired mechanism for the dynamic adaptation of within-neuron parameters that is guided by a global context signal carrying information about perturbations and variability in incoming stimuli. Specifically, we demonstrate that adaptive voltage thresholds or neuronal time constants, when informed by a global context signal, can enable network-level mechanisms to recover from perturbed synaptic weights. Consistent with prior literature, the context-modulated approach is effective for recurrent, but not feedforward networks, by modulating network level dynamics. We demonstrate this approach successfully recovers performance in image classification tasks and spatiotemporal tracking tasks under idealized and Gaussian noise as well as for realistic perturbations from a memristive device when exposed to ionizing radiation. Finally, we discuss how this approach enables the design of robust and energy-efficient neuromorphic systems that perform well, even in resource-constrained scenarios with extreme environments such as edge processing.

context modulation↗
DOE OSTI2021

Genome Assembly and Transcriptome of Colletotrichum sublineola CsGL1, a New Resource to Study Anthracnose Disease in Sorghum

Colletotrichum species are globally distributed and well known as members of a destructive phytopathogenic genus, causing the anthracnose disease in a wide variety of crops and fruits. Colletotrichum sublineola is the causal agent of the anthracnose disease in sorghum, causing losses of up to 50% in yield. Here, we used PacBio sequencing combined with RNA-seq to generate a chromosome-level assembly and annotation of the Colletotrichum sublineola strain CsGL1. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Biochemistry & Molecular Biology↗
DOE OSTI2022

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗