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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗
NASA NTRS1984

Al-rich objects in ordinary chondrites - Related origin of carbonaceous and ordinary chondrites and their constituents

A description is given of 169 Al-rich objects (arbitrarily defined as having 10 wt pct or more of Al2O3) from 24 ordinary chondrites of types 3 and 4, five regolith breccias containing unequilibrated material, the unique meteorite Kakangari, and a few ordinary chondrites of types 5 and 6. On the basis of shape and texture, the Al-rich objects are divided into chondrules (round, with igneous textures), irregularly shaped inclusions (similar to type F and spinel-rich complex Ca-Al-rich inclusions), and fragments (probably fragments of Al-rich chondrules and inclusions). For descriptive purposes, the Al-rich chondrules are further subdivided into compositional subgroups, although they are entirely transitional.

Bischoff, A.↗
DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Outcomes of WPEC SG47 on "Use of Shielding Integral Benchmark Archive and Database for Nuclear Data Validation"

The Working Party on International Nuclear Data Evaluation Co-operation Subgroup 47 (WPECSG47) entitled "Use of Shielding Integral Benchmark Archive and Database for Nuclear Data Validation" was organised from 2019 and 2022 with the objectives to promote more systematic and wider use of shielding benchmark experiments in nuclear data (ND) and transport code validation and development, to provide feedback on the Shielding Integral Benchmark Archive and Database (SINBAD), and to promote its further development in coordination with the Expert Group on Physics of Reactor Systems (EGPRS). Altogether 9 meetings, the large majority (8) held remotely, were organised during the past 3 years to discuss the experience on the use of SINBAD, evaluation of new benchmarks and improvements to be contributed to the database which was severely neglected and lacking maintenance over the past ← 10+ years. Several proposals for new or updated benchmark evaluation were presented and discussed, such as FNG copper, LLNL pulsed spheres, CIAE iron sphere, KFK 1977 gamma measurements, Rez Fe sphere, ASPIS, ORNL Oxygen broomstick, TIARA and others. Complementing the database with new features was also discussed, for example providing the nuclear data sensitivity profiles more systematically would facilitate and better guide the use of data. Information on the geometry, (radiation source) and materials available in CAD format is expected to allow an easier and less error prone reference for computational model preparation and a potential input to CAD based workflows. Inputs for various transport codes and other benchmark data from participants have been shared via the NEA GitLab which could hopefully in the future evolve and form a bases for critically checked and validated benchmark data. Future development of SINBAD will be monitored by EGPRS and the newly created SINBAD Task Force.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Prototypes of Nonrelativistic Spin Splitting and Polarization in Symmetry Broken Antiferromagnets

Antiferromagnets that break both space-time reversal and translation-spin-rotation symmetries were recently predicted [L.-D. Yuan, Z. Wang, J.-W. Luo, E. I. Rashba, and A. Zunger, Phys. Rev. B 102, 014422 (2020)] to possess splitting between the otherwise spin-degenerate energy bands even without the relativistic spin-orbit coupling (SOC). Here, we point out that such nonrelativistic spin splitting (NRSS)—in particular, “spin splitting type 4” (SST-4) symmetry-broken antiferromagnets—can be divided into subgroups having distinct patterns of spin splitting and spin textures, depending on additional auxiliary symmetries of spin interconversion and polarity. These SST-4 subgroups include the 𝛼-type (no spin-interconverting symmetry) having spin splitting at the Brillouin zone center, as well as the 𝛽 subgroup in which a rotation symmetry is applied and determines the alternating spin texture and the 𝛾 subgroup having exclusively reflection spin-interconverting symmetry. Unlike ferrimagnets, the 𝛼-type compounds are shown to have tiny net magnetization at finite temperature and thus avoid the adverse effect of the stray field. The 𝛼 and 𝛽 subgroups can be either polar or nonpolar, whereas the 𝛾 subgroup is polar only, providing a basis for possible switching by external fields. The combination of NRSS-enabling and auxiliary symmetries is used here as a filter for identifying previously synthesized compounds as specific prototypes. Their characteristic splitting and spin polarization are calculated by density functional theory to the benefit of potential future experimental testing. Interesting results are as follows: (i) SOC-independent NRSS can exceed the magnitude of the SOC-induced Rashba and Dresselhaus spin splitting in semiconductors. (ii) Examples of predicted 𝛼-type insulating compounds include BiCrO 3 (nonpolar) and Mn 2 ⁢ScSbO 6 (polar), the latter having spin splitting of 158 meV and 160 meV in the valence and conduction bands, respectively. (iii) The 𝛽-type (Cu 2 ⁢Y 2 ⁢O 5 and FeF 2 ) and 𝛾-type compounds (Mn 4 ⁢Nb 2 ⁢O 9 and FeScO 3 ) are distinguished both by their auxiliary symmetries and polarity. The spin textures of 𝛾-type compounds are mirror reflected with spin degeneracy of the wave vectors on that mirror. These observations will likely broaden the experimental playing field of NRSS physics significantly.

antiferromagnets↗
DOE OSTI2021

Multiscale X-ray phase contrast imaging of human cartilage for investigating osteoarthritis formation

The evolution of cartilage degeneration is still not fully understood, partly due to its thinness, low radio-opacity and therefore lack of adequately resolving imaging techniques. X-ray phase-contrast imaging (X-PCI) offers increased sensitivity with respect to standard radiography and CT allowing an enhanced visibility of adjoining, low density structures with an almost histological image resolution. This study examined the feasibility of X-PCI for high-resolution (sub-) micrometer analysis of different stages in tissue degeneration of human cartilage samples and compare it to histology and transmission electron microscopy. Ten 10%-formalin preserved healthy and moderately degenerated osteochondral samples, post-mortem extracted from human knee joints, were examined using four different X-PCI tomographic set-ups using synchrotron radiation the European Synchrotron Radiation Facility (France) and the Swiss Light Source (Switzerland). Volumetric datasets were acquired with voxel sizes between 0.7 × 0.7 × 0.7 and 0.1 × 0.1 × 0.1 µm 3 . Data were reconstructed by a filtered back-projection algorithm, post-processed by ImageJ, the WEKA machine learning pixel classification tool and VGStudio max. For correlation, osteochondral samples were processed for histology and transmission electron microscopy. X-PCI provides a three-dimensional visualization of healthy and moderately degenerated cartilage samples down to a (sub-)cellular level with good correlation to histologic and transmission electron microscopy images. X-PCI is able to resolve the three layers and the architectural organization of cartilage including changes in chondrocyte cell morphology, chondrocyte subgroup distribution and (re-)organization as well as its subtle matrix structures. X-PCI captures comprehensive cartilage tissue transformation in its environment and might serve as a tissue-preserving, staining-free and volumetric virtual histology tool for examining and chronicling cartilage behavior in basic research/laboratory experiments of cartilage disease evolution.

3D analysis↗
NASA NTRS1994

Rare Earth Garnet Selective Emitter

Thin film Ho-YAG and Er-YAG emitters with a platinum substrate exhibit high spectral emittance in the emission band (epsilon(sub lambda) approx. = 0.75, sup 4)|(sub 15/2) - (sup 4)|(sub 13/2),for Er-YAG and epsilon(sub lambda) approx. = 0.65, (sup 5)|(sub 7) - (sup 5)|(sub 8) for Ho-YAG) at 1500 K. In addition, low out-of-band spectral emittance, epsilon(sub lambda) less than 0.2, suggest these materials would be excellent candidates for high efficiency selective emitters in thermophotovoltaic (TPV) systems operating at moderate temperatures (1200-1500 K). Spectral emittance measurements of the thin films were made (1.2 less than lambda less than 3.0 microns) and compared to the theoretical emittances calculated using measured values of the spectral extinction coefficient. In this paper we present the results for a new class of rare earth ion selective emitters. These emitters are thin sections (less than 1 mm) of yttrium aluminum garnet (YAG) single crystal with a rare earth substitutional impurity. Selective emitters in the near IR are of special interest for thermophotovoltaic (TPV) energy conversion. The most promising solid selective emitters for use in a TPV system are rare earth oxides. Early spectral emittance work on rare earth oxides showed strong emission bands in the infrared (0.9 - 3 microns). However, the emittance outside the emission band was also significant and the efficiency of these emitters was low. Recent improvements in efficiency have been made with emitters fabricated from fine (5 - 10 microns) rare earth oxide fibers similar to the Welsbach mantle used in gas lanterns. However, the rare earth garnet emitters are more rugged than the mantle type emitters. A thin film selective emitter on a low emissivity substrate such as gold, platinum etc., is rugged and easily adapted to a wide variety of thermal sources. The garnet structure and its many subgroups have been successfully used as hosts for rare earth ions, introduced as substitutional impurities, in the development of solid state laser crystals. Doping, dependent on the particular ion and crystal structure, may be as high as 100 at. % (complete substitution of yttrium ion with the rare earth ion). These materials have high melting points, 1940 C for YAG (Yttrium Aluminum Garnet), and low emissivity in the near infrared making them excellent candidates for a thin film selective emitter. As previously stated, the spectral emittance of a rare earth emitter is characterized by one or more well defined emission bands. Outside the emission band the emittance(absorptance) is much lower. Therefore, it is expected that emission outside the band for a thin film selective emitter will be dominated by the emitter substrate. For an efficient emitter (power in the emission band/total emitted power) the substrate must have low emittance, epsilon(sub S). This paper presents normal spectral emittance, epsilon(sub lambda), measurements of holmium(Ho) and erbium (Er) doped YAG thin film selective emitters at (1500 K), and compares those results with the theoretical spectral emittance.

Lowe, Roland A.↗
NASA NTRS2011

A Model of Reduced Kinetics for Alkane Oxidation Using Constituents and Species for N-Heptane

The reduction of elementary or skeletal oxidation kinetics to a subgroup of tractable reactions for inclusion in turbulent combustion codes has been the subject of numerous studies. The skeletal mechanism is obtained from the elementary mechanism by removing from it reactions that are considered negligible for the intent of the specific study considered. As of now, there are many chemical reduction methodologies. A methodology for deriving a reduced kinetic mechanism for alkane oxidation is described and applied to n-heptane. The model is based on partitioning the species of the skeletal kinetic mechanism into lights, defined as those having a carbon number smaller than 3, and heavies, which are the complement of the species ensemble. For modeling purposes, the heavy species are mathematically decomposed into constituents, which are similar but not identical to groups in the group additivity theory. From analysis of the LLNL (Lawrence Livermore National Laboratory) skeletal mechanism in conjunction with CHEMKIN II, it is shown that a similarity variable can be formed such that the appropriately non-dimensionalized global constituent molar density exhibits a self-similar behavior over a very wide range of equivalence ratios, initial pressures and initial temperatures that is of interest for predicting n-heptane oxidation. Furthermore, the oxygen and water molar densities are shown to display a quasi-linear behavior with respect to the similarity variable. The light species ensemble is partitioned into quasi-steady and unsteady species. The reduced model is based on concepts consistent with those of Large Eddy Simulation (LES) in which functional forms are used to replace the small scales eliminated through filtering of the governing equations; in LES, these small scales are unimportant as far as the overwhelming part of dynamic energy is concerned. Here, the scales thought unimportant for recovering the thermodynamic energy are removed. The concept is tested by using tabular information from the LLNL skeletal mechanism in conjunction with CHEMKIN II utilized as surrogate ideal functions replacing the necessary functional forms. The test reveals that the similarity concept is indeed justified and that the combustion temperature is well predicted, but that the ignition time is over-predicted, a fact traced to neglecting a detailed description of the processes leading to the heavies chemical decomposition. To palliate this deficiency, functional modeling is incorporated into this conceptual reduction in addition to the modeling the evolution of the global constituent molar density, the enthalpy evolution of the heavies, the contribution to the reaction rate of the unsteady lights from other light species and from the heavies, the molar density evolution of oxygen and water, and the mole fractions of the quasisteady light species. The model is compact in that there are only nine species-related progress variables. Results are presented showing the performance of the model for predicting the temperature and species evolution. The model reproduces the ignition time over a wide range of equivalence ratios, initial pressure, and initial temperature.

Harstad, Kenneth G.↗
DOE OSTI2021

Discrete theta angles, symmetries and anomalies

Gauge theories in various dimensions often admit discrete theta angles, that arise from gauging a global symmetry with an additional symmetry protected topological (SPT) phase. We discuss how the global symmetry and ’t Hooft anomaly depends on the discrete theta angles by coupling the gauge theory to a topological quantum field theory (TQFT). We observe that gauging an Abelian subgroup symmetry, that participates in symmetry extension, with an additional SPT phase leads to a new theory with an emergent Abelian symmetry that also participates in a symmetry extension. The symmetry extension of the gauge theory is controlled by the discrete theta angle which comes from the SPT phase. We find that discrete theta angles can lead to two-group symmetry in 4d 4 d QCD with SU(N),SU(N)/\mathbb{Z}_k S U ( N ) , S U ( N ) / ℤ k or SO(N) S O ( N ) gauge groups as well as various 3d 3 d and 2d 2 d gauge theories.

Hsin, Po-Shen↗
NASA NTRS1993

The Third Annual NASA Science Internet User Working Group Conference

The NASA Science Internet (NSI) User Support Office (USO) sponsored the Third Annual NSI User Working Group (NSIUWG) Conference March 30 through April 3, 1992, in Greenbelt, MD. Approximately 130 NSI users attended to learn more about the NSI, hear from projects which use NSI, and receive updates about new networking technologies and services. This report contains material relevant to the conference; copies of the agenda, meeting summaries, presentations, and descriptions of exhibitors. Plenary sessions featured a variety of speakers, including NSI project management, scientists, and NSI user project managers whose projects and applications effectively use NSI, and notable citizens of the larger Internet community. The conference also included exhibits of advanced networking applications; tutorials on internetworking, computer security, and networking technologies; and user subgroup meetings on the future direction of the conference, networking, and user services and applications.

Lev, Brian S.↗
NASA NTRS2014

Heterogenous Oxygen Isotopic Composition of a Complex Wark-Lovering Rim and the Margin of a Refractory Inclusion from Leoville

Wark-Lovering (WL) rims [1] surrounding many refractory inclusions represent marker events in the early evolution of the Solar System in which many inclusions were exposed to changes in pressure [2], temperature [3], and isotopic reservoirs [4-7]. The effects of these events can be complex, not only producing mineralogical variability of WL rims [2], but also leading to mineralogical [8-10] and isotopic [7, 11, 12] changes within inclusion interiors. Extreme oxygen isotopic heterogeneity measured in CAIs has been explained by mixing between distinct oxygen gas reservoirs in the nebula [13]. Some WL rims contain relatively simple mineral layering and/or are isotopically homogeneous [14, 15]. As part of a larger effort to document and understand the modifications observed in some CAIs, an inclusion (L6) with a complex WL rim from Leoville, a member of the reduced CV3 subgroup was studied. Initial study of the textures and mineral chemistry was presented by [16]. Here we present NanoSIMS oxygen isotopic measurements to complement these petrologic observations.

Simon, J. I.↗
NASA NTRS2001

Clinical and echocardiographic characteristics of papillary fibroelastomas: a retrospective and prospective study in 162 patients

BACKGROUND: Cardiac papillary fibroelastoma (CPF) is a primary cardiac neoplasm that is increasingly detected by echocardiography. The clinical manifestations of this entity are not well described. METHODS AND RESULTS: In a 16-year period, we identified patients with CPF from our pathology and echocardiography databases. A total of 162 patients had pathologically confirmed CPF. Echocardiography was performed in 141 patients with 158 CPFs, and 48 patients had CPFs that were not visible by echocardiography (<0.2 cm), leaving an echocardiographic subgroup of 93 patients with 110 CPFs. An additional 45 patients with a presumed diagnosis of CPF were identified. The mean age of the patients was 60+/-16 years of age, and 46.1% were male. Echocardiographically, the mean size of the CPFs was 9+/-4.6 mm; 82.7% occurred on valves (aortic more than mitral), 43.6% were mobile, and 91.4% were single. During a follow-up period of 11+/-22 months, 23 of 26 patients with a prospective diagnosis of CPF that was confirmed by pathological examination had symptoms that could be attributable to embolization. In the group of 45 patients with a presumed diagnosis of CPF, 3 patients had symptoms that were likely due to embolization (incidence, 6.6%) during a follow-up period of 552+/-706 days. CONCLUSIONS: CPFs are generally small and single, occur most often on valvular surfaces, and may be mobile, resulting in embolization. Because of the potential for embolic events, symptomatic patients, patients undergoing cardiac surgery for other lesions, and those with highly mobile and large CPFs should be considered for surgical excision.

NASA Discipline Cardiopulmonary↗
NASA NTRS2015

BioSentinel: Mission Development of a Radiation Biosensor to Gauge DNA Damage and Repair Beyond Low Earth Orbit on a 6U Nanosatellite

We are designing and developing a 6U (10 x 22 x 34 cm; 14 kg) nanosatellite as a secondary payload to fly aboard NASAs Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinels 12- to 18-month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. In order to understand the relative contributions of the space environments two dominant biological perturbations, reduced gravity and ionizing radiation, results from deep space will be directly compared to data obtained in LEO (on ISS) and on Earth. These data points will be available for validation of existing biological radiation damage and repair models, and for extrapolation to humans, to assist in mitigating risks during future long-term exploration missions beyond LEO. The BioSentinel Payload occupies 4U of the spacecraft and will utilize the monocellular eukaryotic organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from ambient space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. Yeast was selected because of 1) its similarity to cells in higher organisms, 2) the well-established history of strains engineered to measure DSB repair, 3) its spaceflight heritage, and 4) the wealth of available ground and flight reference data. The S. cerevisiae flight strain will include engineered genetic defects to prevent growth and division until a radiation-induced DSB activates the yeasts DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its successful repair. The yeast will be carried in the dry state within the 1-atm PL container in 18 separate fluidics cards with each card having 16 independent culture microwells, with integral microchannels and filters to supply nutrients and reagents, confine the yeast to the wells, and enable optical measurement. The measurement subsystem will monitor each subgroup of culture wells continuously for several weeks, optically tracking DSB-triggered cell growth and metabolism. BioSentinel will also include physical radiation sensors based on the TimePix sensor, as implemented by JSCs RadWorks group, which record individual radiation events including estimates of their linear-energy-transfer (LET) values. Radiation-dose and LET data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels.

Radiation Biosensor↗
NASA NTRS2015

BioSentinel: Mission Development of a Radiation Biosensor to Gauge DNA Damage and Repair Beyond Low Earth Orbit on a 6U Nanosatellite.

We are designing and developing a "6U" (10 x 22 x 34 cm; 14 kg) nanosatellite as a secondary payload to fly aboard NASA's Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinel's 12- to 18- month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. In order to understand the relative contributions of the space environment's two dominant biological perturbations, reduced gravity and ionizing radiation, results from deep space will be directly compared to data obtained in LEO (on ISS) and on Earth. These data points will be available for validation of existing biological radiation damage and repair models, and for extrapolation to humans, to assist in mitigating risks during future long-term exploration missions beyond LEO. The BioSentinel Payload occupies 4U of the spacecraft and will utilize the monocellular eukaryotic organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from ambient space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. Yeast was selected because of 1) its similarity to cells in higher organisms, 2) the well-established history of strains engineered to measure DSB repair, 3) its spaceflight heritage, and 4) the wealth of available ground and flight reference data. The S. cerevisiae flight strain will include engineered genetic defects to prevent growth and division until a radiation-induced DSB activates the yeast's DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its successful repair. The yeast will be carried in the dry state within the 1-atm P/L container in 18 separate fluidics cards with each card having 16 independent culture microwells, with integral microchannels and filters to supply nutrients and reagents, confine the yeast to the wells, and enable optical measurement. The measurement subsystem will monitor each subgroup of culture wells continuously for several weeks, optically tracking DSBtriggered cell growth and metabolism. BioSentinel will also include physical radiation sensors based on the TimePix sensor, as implemented by JSC's RadWorks group, which record individual radiation events including estimates of their linear-energytransfer (LET) values. Radiation-dose and LET data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels. The spacecraft bus will operate in a deep space environment with functions that include command and data handling, communications, power generation (via deployable solar panels) and storage, and attitude determination-and-control system with micropropulsion. Development of the BioSentinel spacecraft will mature and prove multiple nanosatellite advances in order to function well beyond LEO: Communications from distances of ≥ 500,000 km; Autonomous attitude control, momentum management, and safe mode of nanosatellites in deep space; Shielding-, hardening-, design-, and software-derived radiation tolerance for electronics; Reliable functionality for 12 - 18 months of key subsystems for biofluidics, memory, communications, power, etc.; Close integration of living biological radiation event monitors with miniature physical radiation spectrometers; Biological measurement of solar particle events beyond Earth orbit In addition to providing the first biological results from beyond LEO in over 4 decades, BioSentinel will provide an adaptable small-satellite instrument platform to perform a range of human-exploration-relevant measurements that characterize the biological consequences of multiple outer space environments. BioSentinel is being developed under NASA's Advanced Exploration Systems program.

DNA damage↗
NASA NTRS2014

On the Relationship between Cosmic Ray Exposure Ages and Petrography of CM Chondrites

Carbonaceous (C) chondrites are potentially the most primitive among chondrites because they mostly escaped thermal metamorphism that affected the other chondrite groups. C chondrites are chemically distinguished from other chondrites by their high Mg/Si ratios and refractory elements, and have experienced various degrees of aqueous alteration. They are subdivided into eight subgroups (CI, CM, CO, CV, CK, CR, CB and CH) based on major element and oxygen isotopic ratios. Their elemental ratios vary over a wide range, in contrast to those of ordinary and enstatite chondrites which are relatively uniform. It is critical to know how many separate bodies are represented by the C chondrites. In this study we defined 4 distinct cosmic-ray exposure (CRE) age groups of CMs and systematically characterized the petrography in each of the 4 CRE age groups to determine whether the groups have significant petrographic differences with such differences probably reflecting different parent body (asteroid) geological processing, or multiple original bodies. We have reported the results of a preliminary grouping at the NIPR Symp. in 2013 [3], however, we revised the grouping and here report our new results.

Takenouchi, A.↗
DOE OSTI2022

Distributed Energy Resource Cybersecurity Standards Development [Final Report]

Currently, the solar industry is operating with little application-specific guidance on how to protect and defend their systems from cyberattacks. This 3-year Department of Energy (DOE) Solar Energy Technologies Office-funded project helped advance the distributed energy resource (DER) cybersecurity state-of-the-art by (a) bolstering industry awareness of cybersecurity concepts, risks, and solutions through a webinar series and (b) developing recommendations for DER cybersecurity standards to improve the security performance of DER products and networks. Drafting DER standards is a lengthy, consensus-based process requiring effective leadership and stakeholder participation. This project was designed to reduce standard and guide writing times by creating well-researched recommendations that could act as a starting place for national and international standards development organizations. Working within the SunSpec/Sandia DER Cybersecurity Workgroup, the team produced guidance for DER cybersecurity certification, communication protocol standards, network architecture s, access control, and patching. The team also led subgroups within the IEEE P 1547.3 Guide for Cybersecurity of Distributed Energy Resources Interconnected with Electric Power Systems committee and pushed a draft to ballot in October 2021.

14 SOLAR ENERGY↗
DOE OSTI2023

The effect of ambient ozone exposure on three types of diabetes: a meta-analysis

Background: Ozone as an air pollutant is gradually becoming a threat to people's health. However, the effect of ozone exposure on risk of developing diabetes, a fast-growing global metabolic disease, remains controversial. Objective: To evaluate the impact of ambient ozone exposure on the incidence rate of type 1, type 2 and gestational diabetes mellitus. Method: We systematically searched PubMed, Web of Science, and Cochrane Library databases before July 9, 2022, to determine relevant literature. Data were extracted after quality evaluation according to the Newcastle Ottawa Scale (NOS) and the agency for healthcare research and quality (AHRQ) standards, and a meta-analysis was used to evaluate the correlation between ozone exposure and type 1 diabetes mellitus (T1D), type 2 diabetes mellitus (T2D), and gestational diabetes mellitus (GDM). The heterogeneity test, sensitivity analysis, and publication bias were performed using Stata 16.0. Results: Our search identified 667 studies from three databases, 19 of which were included in our analysis after removing duplicate and ineligible studies. Among the remaining studies, three were on T1D, five were on T2D, and eleven were on GDM. The result showed that ozone exposure was positively correlated with T2D [effect size (ES) = 1.06, 95% CI: 1.02, 1.11] and GDM [pooled odds ratio (OR) = 1.01, 95% CI: 1.00, 1.03]. Subgroup analysis demonstrated that ozone exposure in the first trimester of pregnancy might raise the risk of GDM. However, no significant association was observed between ozone exposure and T1D. Conclusion: Long-term exposure to ozone may increase the risk of T2D, and daily ozone exposure during pregnancy was a hazard factor for developing GDM. Decreasing ambient ozone pollution may reduce the burden of both diseases.

60 APPLIED LIFE SCIENCES↗