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At least 541 records · Page 30

Integrating biological knowledge for mechanistic inference in the host-associated microbiome

Advances in high-throughput technologies have enhanced our ability to describe microbial communities as they relate to human health and disease. Alongside the growth in sequencing data has come an influx of resources that synthesize knowledge surrounding microbial traits, functions, and metabolic potential with knowledge of how they may impact host pathways to influence disease phenotypes. These knowledge bases can enable the development of mechanistic explanations that may underlie correlations detected between microbial communities and disease. In this review, we survey existing resources and methodologies for the computational integration of broad classes of microbial and host knowledge. We evaluate these knowledge bases in their access methods, content, and source characteristics. We discuss challenges of the creation and utilization of knowledge bases including inconsistency of nomenclature assignment of taxa and metabolites across sources, whether the biological entities represented are rooted in ontologies or taxonomies, and how the structure and accessibility limit the diversity of applications and user types. We make this information available in a code and data repository at: https://github.com/lozuponelab/knowledge-source-mappings. Addressing these challenges will allow for the development of more effective tools for drawing from abundant knowledge to find new insights into microbial mechanisms in disease by fostering a systematic and unbiased exploration of existing information.

59 BASIC BIOLOGICAL SCIENCES↗

Bias Reduction in Short Records of Satellite Soil Moisture

Although surface soil moisture data from different sources (satellite retrievals, ground measurements, and land model integrations of observed meteorological forcing data) have been shown to contain consistent and useful information in their seasonal cycle and anomaly signals, they typically exhibit very different mean values and variability. These biases pose a severe obstacle to exploiting the useful information contained in satellite retrievals through data assimilation. A simple method of bias removal is to match the cumulative distribution functions (cdf) of the satellite and model data. However, accurate cdf estimation typically requires a long record of satellite data. We demonstrate here that by wing spatial sampling with a 2 degree moving window we can obtain local statistics based on a one-year satellite record that are a good approximation to those that would be derived from a much longer time series. This result should increase the usefulness of relatively short satellite data records.

Reichle, Rolf H.↗

Retrofits Convert Gas Vehicles into Hybrids

Successful space missions can rarely be attributed to a single thing. Rather, they are the result of a system of systems: integrated elements functioning effectively in their individual roles and together with related components, then those systems interacting with and supporting other systems to form a collaborative whole - from the spacecraft itself to the engineering and research teams that design and build it. An example is found in spacecraft power systems. Unlike a gas-powered car or a battery-powered laptop, most spacecraft are powered by multiple energy sources - such as photovoltaic panels, fuel cells, and batteries - working in tandem to ensure the spacecraft functions throughout the course of a mission. As with any system, the appropriate combination of elements and the method of their management are key to high performance and efficiency. One initiative at Glenn Research Center, the Hybrid Power Management (HPM) program, focused on joining new and mature technologies for optimal power systems applications in space and on Earth, with the goal not only to develop ultra-efficient space power systems, but to advance HPM to address global energy issues. The HPM program emerged from Glenn s long history of electric vehicle research dating back to the 1970s, including the NASA Hybrid Electric Transit Bus (HETB) project in the 1990s, which was the largest vehicle to use supercapacitor energy storage.

Source record↗

Integrated development facility for the calibration of low-energy charged particle flight instrumentation

The design of a low-energy ion facility for development and calibration of thermal ion instrumentation is examined. A directly heated cathode provides the electrons used to produce ions by impact ionization and an applied magnetic field increases the path length followed by the electrons. The electrostatic and variable geometry magnetic mirror configuration in the ion source is studied. The procedures for the charge neutralization of the beam and the configuration and function of the 1.4-m drift tube are analyzed. A microcomputer is utilized to control and monitor the beam energy and composition, and the mass- and angle-dependent response of the instrument under testing. The facility produces a high-quality ion beam with an adjustable range of energies up to 150 eV; the angular divergence and uniformity of the beam is obtained from two independent retarding potential analyzers. The procedures for calibrating the instrument being developed are described.

Biddle, A. P.↗

Nuclear Thermal Propulsion (NTP) Fission Product and Source Term Analysis

Nuclear thermal propulsion (NTP) is an in-space propulsion technology that uses a nuclear reactor to directly heat a propellant to provide high thrust, at higher efficiencies than achievable with conventional chemical propulsion systems. Due to the ability of NTP rockets to efficiently provide high thrust, this technology has been proposed for long duration space missions such as crewed missions to Mars and beyond. A primary hurdle for NTP technology development is the demonstration of an integrated reactor engine system to verify its functionality and performance. This primarily requires the manufacture and testing of candidate reactor and engine technologies to demonstrate the proposed design enables desired performance and exhibits acceptable response under all known operation modes. A major component in this testing is fission product accumulation, since after operation radioactive isotopes can be produced and pose radiological dose concerns. This paper explains the background behind fission product analysis and the methodology used to evaluate current reactor designs and identify the amount of fission products present and their radiological impact. Results of multiple thrust level engines at different time periods are discussed and highlight the need for additional experimental testing to confirm fractional release levels of fission products out of the system. Benchmarking of models and future paths of analysis are also discussed.

Fission↗

Nuclear Thermal Propulsion (NTP) Fission Product and Source Term Analysis

Nuclear thermal propulsion (NTP) is an in-space propulsion technology that uses a nuclear reactor to directly heat a propellant to provide high thrust, at higher efficiencies than achievable with conventional chemical propulsion systems. Due to the ability of NTP rockets to efficiently provide high thrust, this technology has been proposed for long duration space missions such as crewed missions to Mars and beyond. A primary hurdle for NTP technology development is the demonstration of an integrated reactor engine system to verify its functionality and performance. This primarily requires the manufacture and testing of candidate reactor and engine technologies to demonstrate the proposed design enables desired performance and exhibits acceptable response under all known operation modes. A major component in this testing is fission product accumulation, since after operation radioactive isotopes can be produced and pose radiological dose concerns. This paper explains the background behind fission product analysis and the methodology used to evaluate current reactor designs and identify the amount of fission products present and their radiological impact. Results of multiple thrust level engines at different time periods are discussed and highlight the need for additional experimental testing to confirm fractional release levels of fission products out of the system. Benchmarking of models and future paths of analysis are also discussed.

Nuclear Thermal Propulsion↗

Proton discrimination in CLYC for fast neutron spectroscopy

The Cs 2 LiYCl 6 :Ce (CLYC) elpasolite scintillator is known for its response to fast and thermal neutrons along with good γ-ray energy resolution. While the 35 Cl(n,p) reaction has been identified as a potential means for CLYC-based fast neutron spectroscopy in the absence of time-of-flight (TOF), previous efforts to functionalize CLYC as a fast neutron spectrometer have been thwarted by the inability to isolate proton interactions from 6 Li(n,α) and 35 Cl(n,α) signals. This work introduces a new approach to particle discrimination in CLYC for fission spectrum neutrons using a multi-gate charge integration algorithm that provides excellent separation between protons and heavier charged particles. Neutron TOF data were collected using a 252 Cf source, an array of EJ-309 organic liquid scintillators, and a 6 Li-enriched CLYC scintillator outfitted with fast electronics. Modal waveforms were constructed corresponding to the different reaction channels, revealing significant differences in the pulse characteristics of protons and heavier charged particles at ultrafast, fast, and intermediate time scales. These findings informed the design of a pulse shape discrimination algorithm, which was validated using the TOF data. This study also proposes an iterative subtraction method to mitigate contributions from confounding reaction channels in proton and heavier charged particle pulse height spectra, opening the door for CLYC-based fast neutron and γ-ray spectroscopy while preserving sensitivity to thermal neutron capture signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Massive νs through the CNN lens: interpreting the field-level neutrino mass information in weak lensing

Modern cosmological surveys probe the Universe deep into the nonlinear regime, where massive neutrinos suppress cosmic structure. Traditional cosmological analyses, which use the 2-point correlation function to extract information, are no longer optimal in the nonlinear regime, and there is thus much interest in extracting beyond-2-point information to improve constraints on neutrino mass. Quantifying and interpreting the beyond-2-point information is thus a pressing task. We study the field-level information in weak lensing convergence maps using convolution neural networks. We find that the network performance increases as higher source redshifts and smaller scales are considered — investigating up to a source redshift of 2.5 and ℓ max ≃ 10 4 — verifying that massive neutrinos leave a distinct effect on weak lensing. However, the performance of the network significantly drops after scaling out the 2-point information from the maps, implying that most of the field-level information can be found in the 2-point correlation function alone. We quantify these findings in terms of the likelihood ratio and also use Integrated Gradient saliency maps to interpret which parts of the map the network is learning the most from. We find that, in the absence of noise, the network extracts a similar amount of information from the most overdense and underdense regions. However, upon adding noise, the information in underdense regions is distorted as noise disproportionately washes out void-like structures.

Golshan, Malika [University of California, Berkele↗

Precision luminosity measurement in proton–proton collisions at $\sqrt{s}$ = 13 TeV in 2015 and 2016 at CMS

The measurement of the luminosity recorded by the CMS detector installed at LHC interaction point 5, using proton–proton collisions at √s = 13 TeV in 2015 and 2016, is reported. The absolute luminosity scale is measured for individual bunch crossings using beam-separation scans (the van der Meer method), with a relative precision of 1.3 and 1.0% in 2015 and 2016, respectively. The dominant sources of uncertainty are related to residual differences between the measured beam positions and the ones provided by the operational settings of the LHC magnets, the factorizability of the proton bunch spatial density functions in the coordinates transverse to the beam direction, and the modeling of the effect of electromagnetic interactions among protons in the colliding bunches. When applying the van der Meer calibration to the entire run periods, the integrated luminosities when CMS was fully operational are 2.27 and 36.3 fb -1 in 2015 and 2016, with a relative precision of 1.6 and 1.2%, respectively. These are among the most precise luminosity measurements at bunched-beam hadron colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Thermal Energy Delivery System Design Basis Report

Nuclear power plants operate most efficiently and economically when they are operating at some constant power output. However, with the current dynamics of the grid, including the introduction and growth of renewable energy sources such as wind and solar, nuclear generation facilities across the U.S. are finding it difficult to keep their power supply constant and provide for baseload generation capacities. As a result, most nuclear plants are finding it hard to compete with other generation fuel sources, most notably, natural gas. Finding a solution to this intermittent power supply dynamic could help U.S. nuclear power plants economically compete with other generation fuel sources such as natural gas, wind, and solar. The Thermal Energy Delivery System (TEDS) at the INL aims to investigate alternative solutions to this dilemma. The TEDS design focuses on the delivery of thermal energy to different systems throughout the Dynamic Energy Transport and Integration laboratory (DETAIL). Its strategy revolves around allowing the system to operate at full generation output while storing any surplus energy for later use and/or additional function.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

X-ray-selected M dwarfs and the diffuse X-ray background

A systematic optical identification program was carried out for serendipitous X-ray sources discovered by the Einstein Observatory. A total of 104 were detected above the threshold flux of 3 x 10 to the -13th ergs/sq cm per sec in the 114 sq deg survey region; 11 of these 104 sources are dM stars. Including X-ray-selected M dwarfs from the LMC survey, the Medium Sensitivity Survey, and the Einstein Deep Survey, a dwarf M star composite X-ray spectrum was constructed; the best-fit thermal model yields kT = 1.3 + or - 0.3 keV, consistent with typical active star spectra. An M dwarf X-ray luminosity function was also constructed and it is concluded that the integrated contribution to the diffuse soft (0.28-1.0 keV) X-ray background from such stars is less than 10 percent, a factor of more than about 2 lower than previous estimates. This result is consistent with a limit on the dwarf M star contribution derived from a spectral decomposition of the observed X-ray background spectrum.

Caillault, J.-P.↗

Evaluation of Performance of Five Parallel Biological Water Proce

The objective of the work entitled Molecular Characterization of Eubacteria in a Biological Water Processor was to gain an understanding of the microbial diversity and species stability of the consortia that inhabit an anoxic bioreactor and to correlate those factors with functional performance, mechanical reliability, and stability. The evaluation was divided into four studies. During Study 1, replicate biological water processor (BWP) systems were operated to evaluate variability in the microbial diversity over time as a function of the initial consortia used for inoculation of the BWP reactors. Study 2 was designed to investigate the impact of an inoculum source on BWP performance. Study 3 was a modification of Study 2 where the impact of inoculum on BWP performance from inoculation until steady state operations was monitored. In Study 4, the reactors were divided into three different operational periods, based on the operational periods of the integrated water recovery test at the Johnson Space Center (JSC) in 2001.

Vega, Leticia M.↗

Optimizing and Exploring Untapped Micro-Hydro Hybrid Systems: a Multi-Objective Approach for Crystal Lake as a Large-Scale Energy Storage Solution

Increasing electricity demand and concerns about climate change and fossil fuel consumption have highlighted the importance of renewable energy resources and storage systems. This paper proposes a method for exploring untapped pumped hydro storage potentials to accommodate intermittent renewable energy generation profiles. Hourly measured data from 2022 in Benzie County, Michigan, United States, were gathered for system sizing and a thorough, realistic analysis. By employing the multi-objective grey wolf optimization algorithm, we formulated optimal sizing and energy-management strategies for three different scenarios. Unlike similar studies, the 3rd with triple objective functions (OFs) scenario aims to maximize both reliability and ecological OFs while minimizing the cost OF. It has shown promising results with multiple solutions, considering economic, environmental, and reliability factors. A case study conducted in Crystal Lake, Michigan, revealed that although Crystal Lake would function only as a micro-hydro power facility, it is a promising and huge storage unit with a substantial storage capacity of around 14.9734GWh. The system investigated is significant in the USA due to its rapid deployment capabilities, minimal construction requirements, and ease of integration with the distribution grid. The fuzzy logic method was employed to identify the best non-dominant solution among the other solutions. Furthermore, these outcomes include a notably low levelized cost of energy at 0.046147$/kWh, a robust index of reliability of 99.705%, and a significant reduction in CO₂ emissions amounting to 7.9142×10 3 tons/year, when considering the triple OFs. The paper’s methodology provides valuable insights for regions aiming to utilize renewable energy from untapped storage sources.

13 HYDRO ENERGY↗

Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

Objective: The growing availability of electronic health records (EHR) data opens opportunities for integrative analysis of multi-institutional EHR to produce generalizable knowledge. A key barrier to such integrative analyses is the lack of semantic interoperability across different institutions due to coding differences. We propose a Multiview Incomplete Knowledge Graph Integration (MIKGI) algorithm to integrate information from multiple sources with partially overlapping EHR concept codes to enable translations between healthcare systems. Methods: The MIKGI algorithm combines knowledge graph information from (i) embeddings trained from the co-occurrence patterns of medical codes within each EHR system and (ii) semantic embeddings of the textual strings of all medical codes obtained from the Self-Aligning Pretrained BERT (SAPBERT) algorithm. Due to the heterogeneity in the coding across healthcare systems, each EHR source provides partial coverage of the available codes. MIKGI synthesizes the incomplete knowledge graphs derived from these multi-source embeddings by minimizing a spherical loss function that combines the pairwise directional similarities of embeddings computed from all available sources. MIKGI outputs harmonized semantic embedding vectors for all EHR codes, which improves the quality of the embeddings and enables direct assessment of both similarity and relatedness between any pair of codes from multiple healthcare systems. Results: With EHR co-occurrence data from Veteran Affairs (VA) healthcare and Mass General Brigham (MGB), MIKGI algorithm produces high quality embeddings for a variety of downstream tasks including detecting known similar or related entity pairs and mapping VA local codes to the relevant EHR codes used at MGB. Based on the cosine similarity of the MIKGI trained embeddings, the AUC was 0.918 for detecting similar entity pairs and 0.809 for detecting related pairs. For cross-institutional medical code mapping, the top 1 and top 5 accuracy were 91.0% and 97.5% when mapping medication codes at VA to RxNorm medication codes at MGB; 59.1% and 75.8% when mapping VA local laboratory codes to LOINC hierarchy. When trained with 500 labels, the lab code mapping attained top 1 and 5 accuracy at 77.7% and 87.9%. MIKGI also attained best performance in selecting VA local lab codes for desired laboratory tests and COVID-19 related features for COVID EHR studies. Compared to existing methods, MIKGI attained the most robust performance with accuracy the highest or near the highest across all tasks. Conclusions: The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Zhou, Doudou↗

Event Driven Messaging with Role-Based Subscriptions

Event Driven Messaging with Role-Based Subscriptions (EDM-RBS) is a framework integrated into the Service Management Database (SMDB) to allow for role-based and subscription-based delivery of synchronous and asynchronous messages over JMS (Java Messaging Service), SMTP (Simple Mail Transfer Protocol), or SMS (Short Messaging Service). This allows for 24/7 operation with users in all parts of the world. The software classifies messages by triggering data type, application source, owner of data triggering event (mission), classification, sub-classification and various other secondary classifying tags. Messages are routed to applications or users based on subscription rules using a combination of the above message attributes. This program provides a framework for identifying connected users and their applications for targeted delivery of messages over JMS to the client applications the user is logged into. EDMRBS provides the ability to send notifications over e-mail or pager rather than having to rely on a live human to do it. It is implemented as an Oracle application that uses Oracle relational database management system intrinsic functions. It is configurable to use Oracle AQ JMS API or an external JMS provider for messaging. It fully integrates into the event-logging framework of SMDB (Subnet Management Database).

Bui, Tung↗

Hydrogenerate: Open Source Python Tool To Estimate Hydropower Generation Time-series

Hydropower is one of the most mature forms of renewable energy generation. The United States (US) has almost 103 GW of installed, with 80 GW of conventional generation and 23 GW of pumped hydropower [1]. Moreover, the potential for future development on Non-Powered Dams is up to 10 GW. With the US setting its goals to become carbon neutral [2], more renewable energy in the form of hydropower needs to be integrated with the grid. Currently, there are no publicly available tool that can estimate the hydropower potential for existing hydropower dams or other non-powered dams. The HydroGenerate is an open-source python library that has the capability of estimating hydropower generation based on flow rate either provided by the user or received from United States Geological Survey (USGS) water data services. The tool calculates the efficiency as a function of flow based on the turbine type either selected by the user or estimated based on the “head” provided by the user.

Mitra, Bhaskar↗

A radioisotope - enabled reactive transport model for deep vadose zone carbon

In mountainous regions, which constitute the principle source of recharge to major rivers and regional aquifers, infiltration occurs through fractured, partially saturated, weathered bedrock that acts as a boundary layer between saturated aquifers and surface soil. Commonly this deep vadose zone (DVZ) is many meters thick, and yet its role in regulating the generation, retention and mobility of reactive solutes, including nutrients, contaminants and weathering products, is largely unknown. In particular, many of the key reactions that drive the formation of the weathered DVZ and the quality of water moving through it are redox processes, regulated by the availability of organic carbon and oxygen below the soil layer. The role of the DVZ is thus also poorly constrained in the context of carbon stocks and mobility, particularly in lithologies that are naturally high in organic carbon, such as shales. The overarching hypothesis of this study is that upland regions developed in geologic settings with abundant petrogenic carbon store and actively cycle carbon in the weathered DVZ below the soil and above the water table at rates that are significant and currently unconstrained. In order to quantify this cycling, the current study combines novel instrumentation techniques allowing new direct sampling of DVZ systems with advanced numerical reactive transport simulations of carbon transport and transformation. Critically, these simulations will explicitly treat the three isotopes of carbon (the abundant 12C, the stable rare 13C and the radioactive 14C) in a unified framework, thus clearly parsing between the contributions of modern surface derived carbon and lithologic carbon sources in integrated measurements of fluid and gas phase fluxes. This novel model capability will be applied to test the role of DVZ carbon cycling as a regulator of water quality and geological weathering in two complementary field sites both located in organic carbon rich shale lithologies. The first is the Eel River Critical Zone Observatory (ERCZO) in Mendocino County, California, and the second is the Lawrence Berkeley National Laboratory Watershed Function Scientific Focus Area (SFA) in the East River watershed, near Crested Butte, Colorado. At the ERCZO, a novel vadose zone monitoring system has been installed in a 20 m thick, partially saturated, weathered shale hillslope, and preliminary data already indicate substantial CO2 flux generated many meters below the soil surface. At the SFA field site, an instrumented hillslope transect indicates a more complex multi-dimensional fluid and solute transport regime, which will serve as a key test of the calibrated models. Collectively, this project will advance understanding of the cycling of carbon belowground and in relation to transport pathways across the poorly constrained DVZ characteristic of primary water recharge areas. The key product of this work will be enhanced isotope simulation capabilities that are robust and publicly available for application across a broad diversity of systems.

58 GEOSCIENCES↗

Criteria for the emergence and evolution of life in the solar system

It is proposed that there are at least 25 specific conditions or requirements which have to be fulfilled in order for life to appear and evolve in a planetary system such as ours. The criteria are grouped into five major general areas: (1) Planetary criteria relate to the physical properties of the planet as it is formed and as it becomes a cosmic body with the potential to provide an abode for life. (2) Chemical criteria concern the composition, availability of effective energy sources, and chemical constraints of the environment where reactions take place for the prebiological formation of biochemical compounds. (3) Protobiological criteria relate to the prebiologically synthesized oligomeric and polymeric biomolecules, how they interact cooperatively to form protobiological structures and functions, and self-assemble to give rise to a living system. (4) Evolutionary criteria are concerned with the processes responsible for the increase in complexity of organisms by genomic multiplication, symbiotic integration, and cellular differentiation, as well as with the negentropic ability of organisms to continuously recycle all the volatile biogenic elements. (5) Stellar criteria relate to the elemental composition mass, lifetime, and other features of Main Sequence stars which may be surrounded by planetary systems similar to our own.

Oro, J.↗