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At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

A Rapid Assessment of a Lunar Surface Laboratory Module

Johnson Space Center has piloted an innovation team known as the Forge to perform rapid turnaround, concurrent engineering studies. The Forge is intended to be able to pull together a team of strategically selected domain experts to innovatively solve a specified problem within a short period of time. The Forge’s inaugural project was the development of a Lunar Surface Laboratory Module concept. The lab module is intended as an option for the NASA Lunar Architecture Team and may allow for increased science productivity and return on investment than with only the Surface Habitat. The Forge team developed two concepts, a stationary laboratory and a mobile laboratory. Human factors evaluations have been conducted to determine the acceptability of the resulting design concepts. The human factors evaluations conducted include a card sort evaluation of the laboratories by science discipline and the System Usability Scale (SUS). The card sort focused subject matter expert expectations for the relative positioning of the laboratory functional areas, determining whether a given lab area should be adjacent to, or separated from, another. The SUS focused on layout efficiency. Both used human factors personnel and both life and physical scientists as subject matter experts. Each of these evaluations will focus primarily on objective data with limited subjective comments, reducing the time required for processing responses. The results of the card sort and SUS evaluations and their implications will be discussed. Based on the evaluation data, an overall acceptability of the Lunar Surface Laboratory Module produced by the Forge study can be determined. Lessons learned and recommendations for future use of human factors rapid assessment processes in early design trades will also be provided.

Forge↗

NASA NTRSDate not supplied

Rapid Assessment of a Lunar Surface Laboratory Module

Johnson Space Center has piloted an innovation team known as the Forge to perform rapid turnaround, concurrent engineering studies. The Forge is intended to be able to pull together a team of strategically selected domain experts to innovatively solve a specified problem within a short period of time. The Forge’s inaugural project was the development of a Lunar Surface Laboratory Module concept. The lab module is intended as an option for the NASA Lunar Architecture Team and may allow for increased science productivity and return on investment than with only the Surface Habitat. The Forge team developed two concepts, a stationary laboratory and a mobile laboratory. Human factors evaluations have been conducted to determine the acceptability of the resulting design concepts. The human factors evaluations conducted include a card sort evaluation of the laboratories by science discipline and the System Usability Scale (SUS). The card sort is focused subject matter expert expectations for the relative positioning of the laboratory functional areas, determining whether a given lab area should be adjacent to, or separated from, another. The SUS will focus on layout efficiency. Both will use human factors personnel and both life and physical scientists as subject matter experts. Each of these evaluations will focus primarily on objective data with limited subjective comments, reducing the time required for processing responses. The results of the card sort and SUS evaluations and their implications will be discussed. Based on the evaluation data, an overall acceptability of the Lunar Surface Laboratory Module produced by the Forge study can be determined. Lessons learned and recommendations for future use of human factors rapid assessment processes in early design trades will also be provided.

Human Factors↗

DOE OSTI2019

Parallel storage system with burst buffer appliance for storage of partitioned key-value store across a plurality of storage tiers

Parallel storage systems are provided with a burst buffer appliance for storage of a partitioned key-value store across a plurality of storage tiers. The burst buffer appliance is configured to store key-value data on first and second storage tiers comprising respective disjoint subsets of storage. One or more servers in the partitioned key-value store provide (i) an interface between one or more local key-value stores and one or more additional storage architectures, and/or (ii) a key value interface that provides access to at least one hardware key-value store. The local key-values are optionally sorted both locally by the local store and globally by the overall MDHIM framework. The local and global sorting can be leveraged to provide batch input/output (IO) operations that aggregate multiple requests into batch operations on one or more sorted ranges.

Bent, John M.↗

DOE OSTI2022

Metal sorter

A material sorting system sorts materials utilizing a vision system that implements a machine learning system in order to identify or classify each of the materials, which are then sorted into separate groups based on such an identification or classification determining that the materials are composed of either wrought aluminum, extruded aluminum, or cast aluminum.

Kumar, Nalin↗

DOE OSTI2020

The application of flow cytometry for kelp meiospore isolation

The goal of this study was to evaluate flow-cytometric techniques for isolating individual kelp meiospores into 96-welled plates. Previously reported low success rates for sorting tens of thousands of meiospores at a time have been improved by technological developments, specifically, the low nozzle pressure of the commercially available, JSAN (Bay Bioscience Co. Ltd) instrument. We monitored growth and gametophyte development post-sorting for 10 months. Our data demonstrate that successful kelp meiospore isolations of up to 76% viability can be achieved with flow-cytometry. This method can save time as compared to traditional, manual isolations using pipettes and improves confidence that self-fertilized individuals will not contaminate specific crosses of resulting gametophytes. Our results highlight a new application for the flow cytometer to produce clonal kelp gametophytes with direct applications for germplasm and culture collection development.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

A systematic analytical framework for multi-source municipal solid waste characterization for energy recovery

Advancing municipal solid waste (MSW) management from disposal-oriented practices toward circular, value-driven systems requires standardized methodologies capable of identifying material composition and resource recoverable potential at the point of generation. Despite extensive research, MSW characterization remains fragmented due to inconsistences in sampling methodologies, waste sorting categories, and temporal coverage across previous studies which limit cross-site comparability, reproducibility, and constrain the reliable evaluation of potential resource recovery pathways. This lack of consistency has hindered the development of a unified framework for MSW characterization and resource assessment. This study introduces a standardized, field-validated protocol for MSW sampling and composition analysis that ensures consistent, traceable data across diverse waste sources. The protocol integrates randomized spatial sampling, systematic material sorting, and controlled subsampling for multi-site and multi-season field campaigns. Validation included MSW collection from residential, grocery, restaurant, and school MSW streams across five U.S. states, including Maryland, Idaho, Virginia, Ohio, and Mississippi, to demonstrate the protocol’s ability to identify source-based composition patterns relevant to resource recovery applications. Grocery and restaurant streams were dominated by food waste and high-moisture organics, while school waste contained higher paper content and residential waste showed greater heterogeneity. Aggregation into energy-relevant fractions highlighted practical recovery pathways via anaerobic digestion or gasification, supporting data-driven planning, policy, and circular economy strategies for sustainable waste management across waste sources.

09 BIOMASS FUELS↗

DOE OSTI2013

Urban Mining: Quality and quantity of recyclable and recoverable material mechanically and physically extractable from residual waste

Highlights: • Material recycling and recovery from residual waste by physical and mechanical process has been investigated. • About 6% of recyclable can be extracted by NIR and 2-3Dimension selector. • Another 2% of construction materials can be extracted by adopting modified soil washing process. • Extracted material quality is quite high even some residual heavy metal have been detected by leaching test. - Abstract: The mechanically sorted dry fraction (MSDF) and Fines (<20 mm) arising from the mechanical biological treatment of residual municipal solid waste (RMSW) contains respectively about 11% w/w each of recyclable and recoverable materials. Processing a large sample of MSDF in an existing full-scale mechanical sorting facility equipped with near infrared and 2-3 dimensional selectors led to the extraction of about 6% w/w of recyclables with respect to the RMSW weight. Maximum selection efficiency was achieved for metals, about 98% w/w, whereas it was lower for Waste Electrical and Electronic Equipment (WEEE), about 2% w/w. After a simulated lab scale soil washing treatment it was possible to extract about 2% w/w of inert exploitable substances recoverable as construction materials, with respect to the amount of RMSW. The passing curve showed that inert materials were mainly sand with a particle size ranging from 0.063 to 2 mm. Leaching tests showed quite low heavy metal concentrations with the exception of the particles retained by the 0.5 mm sieve. A minimum pollutant concentration was in the leachate from the 10 and 20 mm particle size fractions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

An optimized method for mouse liver sinusoidal endothelial cell isolation

The objective of the present study was to develop an accurate and reproducible method for liver sinusoidal endothelial cell (LSEC) isolation in mice. Non-parenchymal cells were isolated using a modified two-step collagenase digestion combined with Optiprep density gradient centrifugation. LSEC were further purified using two prevalent methods, short-term selective adherence and CD146+ magnetic-activated cell sorting (MACS), and compared in terms of cell yield, viability and purity to our purification technique using CD11b cell depletion combined with long-term selective adherence. LSEC purification using our technique allowed to obtain 7.07±3.80 million LSEC per liver, while CD146+ MACS and short-term selective adherence yielded 2.94±1.28 and 0.99±0.66 million LSEC, respectively. Purity of the final cell preparation reached 95.10±2.58% when using our method. In contrast, CD146+ MACS and short-term selective adherence gave purities of 86.75±3.26% and 47.95±9.82%, respectively. Similarly, contamination by non-LSEC was the lowest when purification was performed using our technique, with a proportion of contaminating macrophages of only 1.87±0.77%. Further, isolated cells analysed by scanning electron microscopy presented typical LSEC fenestrations organized in sieve plates, demonstrating that the technique allowed to isolate bona fide LSEC. In conclusion, we described a reliable and reproducible technique for the isolation of high yields of pure LSEC in mice. This protocol provides an efficient method to prepare LSEC for studying their biological functions. - Highlights: • This protocol provides an efficient method to prepare primary mouse LSEC for studying their biological functions. • The liver cell dispersion step was improved by performing a retrograde cannulation of the liver. • The cell yield and the purity obtained were higher than comparative techniques in mice. • Contaminating macrophages were removed by introducing a CD11b- magnetic –activated cell sorting step.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Visible/near-infrared spectral diversity from in situ observations of the Bagnold Dune Field sands in Gale Crater, Mars

As part of the Bagnold Dune campaign conducted by Mars Science Laboratory rover Curiosity, visible/near–infrared reflectance spectra of dune sands were acquired using Mast Camera (Mastcam) multispectral imaging (445–1013 nm) and Chemistry and Camera (ChemCam) passive point spectroscopy (400–840 nm). By comparing spectra from pristine and rover–disturbed ripple crests and troughs within the dune field, and through analysis of sieved grain size fractions, constraints on mineral segregation from grain sorting could be determined. In general, the dune areas exhibited low relative reflectance, a weak ~530 nm absorption band, an absorption band near 620 nm, and a spectral downturn after ~685 nm consistent with olivine–bearing sands. The finest grain size fractions occurred within ripple troughs and in the subsurface and typically exhibited the strongest ~530 nm bands, highest relative reflectances, and weakest red/near–infrared ratios, consistent with a combination of crystalline and amorphous ferric materials. Coarser–grained samples were the darkest and bluest and exhibited weaker ~530 nm bands, lower relative reflectances, and stronger downturns in the near–infrared, consistent with greater proportions of mafic minerals such as olivine and pyroxene. These grains were typically segregated along ripple crests and among the upper surfaces of grain flows in disturbed sands. Sieved dune sands exhibited progressive decreases in reflectance with increasing grain size, as observed in laboratory spectra of olivine size separates. In conclusion, the continuum of spectral features observed between the coarse– and fine–grained dune sands suggests that mafic grains, ferric materials, and air fall dust mix in variable proportions depending on aeolian activity and grain sorting.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation and stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Abstract Physical blending is an effective strategy for tailoring polymeric materials to specific application requirements. However, physically blended mixed plastics waste adds additional barriers in mechanical or chemical recycling. This difficulty arises from the intricate requirement for meticulous sorting and separation of the various polymers in the inherent incompatibility of mixed polymers during recycling. To overcome this impediment, this work furthers the emerging single‐monomer – multiple‐materials approach through the design of a bifunctional monomer that can not only orthogonally polymerize into two different types of polymers – specifically lactone‐based polyester and CO 2 ‐based polycarbonate – but the resultant polymers and their mixture can also be depolymerized back to the single, original monomer when facilitated by catalysis. Specifically, the lactone/epoxide hybrid bifunctional monomer (BiL O ) undergoes ring‐opening polymerization through the lactone manifold to produce polyester, PE(BiL O ), and is also applied to ring‐opening copolymerization with CO 2 , via the epoxide manifold, to yield polycarbonate, PC(BiL O ). Remarkably, a one‐pot recycling process of a BiL O ‐derived PE/PC blend back to the constituent monomer BiL O in >99 % selectivity was achieved with a superbase catalyst at 150 °C, thereby effectively obviating the requirement for sorting and separation typically required for recycling of mixed polymers.

Shi, Changxia↗

DOE OSTI2024

Closed‐Loop Recycling of Mixed Plastics of Polyester and CO 2 ‐Based Polycarbonate to a Single Monomer

Chemistry↗

DOE OSTI2018

Economic analysis of forest residues supply chain options to produce enhanced-quality feedstocks

Not provided.

Biotechnology & Applied Microbiology↗

DOE OSTI2020

Sampling and resolution characteristics in reduced order models of shallow water equations: Intrusive vs nonintrusive

We investigate the sensitivity of reduced order models (ROMs) to training data spatial resolution as well as sampling rate. In particular, we consider proper orthogonal decomposition (POD), coupled with Galerkin projection (POD-GP), as an intrusive reduced order modeling technique. For non-intrusive ROMs, we consider two frameworks. The first is using dynamic mode decomposition (DMD), and the second is based on artificial neural networks (ANNs). For ANN, we utilized a residual deep neural network, and for DMD we have studied two versions of DMD approaches; one with hard thresholding and the other with sorted bases selection. Also, we highlight the differences between mean-subtracting the data (centering) and using the data without mean-subtraction. We tested these ROMs using a system of 2D shallow water equations for four different numerical experiments, adopting combinations of sampling rates and spatial resolutions. For these cases, we found that the DMD basis obtained with hard threshodling is sensitive to sampling rate. The sorted DMD algorithm helps to mitigate this problem and yields more stabilized and converging solution. Furthermore, we demonstrate that both DMD approaches without mean subtraction provide significantly more accurate results than DMD with mean-subtracting the data. On the other hand, POD is relatively insensitive to sampling rate and yields better representation of the flow field. Meanwhile, spatial resolution has little effect on both POD and DMD performances. Here, the numerical results reveal that an ANN on POD subspace (POD-ANN) performs remarkably better than POD-GP and DMD in capturing system dynamics, even with a small number of modes.

42 ENGINEERING↗

DOE OSTI2016

A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules

Here, we have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Hierarchical computation in the SPMD programming model

Large-scale parallel machines are programmed mainly with the single program, multiple data (SPMD) model of parallelism. While this model has advantages of scalability and simplicity, it does not fit well with divide-and-conquer parallelism or hierarchical machines that mix shared and distributed memory. In this paper, we define the recursive single program, multiple data model (RSPMD) that extends SPMD with a hierarchical team mechanism to support hierarchical algorithms and machines. We implement this model in the Titanium language and describe how to eliminate a class of deadlocks by ensuring alignment of collective operations. We present application case studies evaluating the RSPMD model, showing that it enables divide-and-conquer algorithms such as sorting to be elegantly expressed and that team collective operations increase performance of conjugate gradient by up to a factor of two. The model also facilitates optimizations for hierarchical machines, improving scalability of particle in cell by 8x and performance of sorting and a stencil code by up to 40% and 14%, respectively.

Kamil, A↗

DOE OSTI2021

Parameter inference from event ensembles and the top-quark mass

One of the key tasks of any particle collider is measurement. In practice, this is often done by fitting data to a simulation, which depends on many parameters. Sometimes, when the effects of varying different parameters are highly correlated, a large ensemble of data may be needed to resolve parameter-space degeneracies. An important example is measuring the top-quark mass, where other physical and unphysical parameters in the simulation must be profiled when fitting the top-quark mass parameter. We compare four different methodologies for top-quark mass measurement: a classical histogram fit similar to one commonly used in experiment augmented by soft-drop jet grooming; a 2D profile likelihood fit with a nuisance parameter; a machine-learning method called DCTR; and a linear regression approach, either using a least-squares fit or with a dense linearly-activated neural network. Despite the fact that individual events are totally uncorrelated, we find that the linear regression methods work most effectively when we input an ensemble of events sorted by mass, rather than training them on individual events. Although all methods provide robust extraction of the top-quark mass parameter, the linear network does marginally best and is remarkably simple. For the top study, we conclude that the Monte-Carlo-based uncertainty on current extractions of the top-quark mass from LHC data can be reduced significantly (by perhaps a factor of 2) using networks trained on sorted event ensembles. More generally, machine learning from ensembles for parameter estimation has broad potential for collider physics measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

TLR4 plays a crucial role in MSC-induced inhibition of NK cell function

Mesenchymal stem cells (MSC) are a kind of stromal cell within the tumor microenvironment. In our research, MSC derived from acute myeloid leukemia patients' bone marrow (AML-MSC) and lung cancer tissues (LC-MSC) as well as normal bone marrow-derived MSC (BM-MSC) cultured in conditioned medium of HeLa cells were found to have higher expressions of Toll-like receptor (TLR4) mRNA compared with BM-MSC. The sorted TLR4-positive MSC (TLR4+ MSC) differed in cytokine (interleukin-6, interleukin-8, and monocyte chemoattractant protein-1) secretion from those of unsorted MSC. MSC was reported to inhibit natural killer (NK) cell proliferation and function. In this research, we confirmed that TLR4+ MSC aggravate this suppression. Furthermore, when TLR4 in the sorted cells were stimulated by LPS or following blocked by antibody, the suppression on NK cell proliferation and cytotoxicity were more intensive or recovered respectively. Compared to unsorted MSC, NKG2D receptor expression on NK cells were also inhibited by TLR4+ MSC. These findings suggest that activation of TLR4 pathway is important for TLR4+ MSC and MSC to obstruct anti-tumor immunity by inhibiting NK cell function, which may provide a potential stroma-targeted tumor therapy. - Highlights: • TLR4+ MSC inhibit NK cell proliferation in vivo and in vitro. • TLR4+ MSC inhibit NKG2D expression on NK cells and NK cell cytotoxicity. • The distinguished cytokine expression of TLR4+ MSC may contribute to the inhibition on NK cell function.

60 APPLIED LIFE SCIENCES↗