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NASA NTRSDate not supplied

Overview of the Inaugural Space Health Impacts for the NASA Experience (SHINE) Training Program – Virtual Space Radiation Curriculum

The Space Radiation Element part of NASA Human Research Program initiated a virtual, annual space radiation curriculum. The SHINE space radiation curriculum aims to educate participants not only in the scientific aspects of space radiation but also in the agency’s risk management strategies. SHINE combines weekly seminars by speakers from NASA, other government agencies, academia, and industry, with networking sessions designed to foster collaboration between participants and interactions with NASA scientists. A total of 59 applications were received from which 25 participants were selected. The 25 participants, with citizenship from a total of 8 countries, are composed of 5 graduate students, 4 postdocs, 11 scientists and 5 professors/medical doctors. Participants have a wide range of expertise including molecular and cellular biology, microbiology, botany, physiology, engineering, physics, aerospace medicine, planetary science, biostatistics, and modeling. The inaugural course ran weekly from February 2023 to August 2023 and was comprised of lectures, less formal coffee hours and office hours. The topics covered ranged from space environments to health effects to granting opportunities. The second annual SHINE training program is scheduled from February to August 2024. In addition, a separate competitive practicum session, to allow participants to gain hands-on radiation experience, will be held Fall 2024 at the NASA Space Radiation Laboratory (NSRL).

Janice A. Zawask↗

NASA NTRSDate not supplied

Overview of The Inaugural Space Health Impacts for the NASA Experience (SHINE) Training Program – Virtual Space Radiation Curriculum

The Space Radiation Element of the NASA Human Research Program initiated a virtual, annual space radiation curriculum. The Space Health Impacts for the NASA Experience (SHINE) space radiation didactic curriculum aims to educate participants not only in the scientific aspects of space radiation but also in the agency’s risk management strategies. SHINE combines weekly seminars by speakers from NASA, other government agencies, academia, and industry, with networking sessions designed to foster collaboration between participants and interactions with NASA scientists and HRP funded investigators. The inaugural course ran weekly from February 2023 to August 2023 and was comprised of lectures, less formal coffee hours and office hours. The SHINE topics ranged from space environments to health effects and countermeasure to granting opportunities. Participants developed beam time proposals for real, proposed, or potential experiments at the NASA Space Radiation Laboratory (NSRL) at the Brookhaven National Laboratory. For the 2023 course, a total of 59 applications were received from which 25 participants were selected. Selected participants were citizens from 8 countries and comprised 5 graduate students, 4 postdocs, 11 scientists and 5 professors/medical doctors. Participants had a wide range of expertise including molecular and cellular biology, microbiology, botany, physiology, engineering, physics, aerospace medicine, planetary science, biostatistics, and modeling. The second annual SHINE training program is scheduled from February to August 2024. In addition, a separate SHINE space radiation practicum session, to allow participants to gain hands-on radiation experience, will be held Fall 2024 at the NSRL.

Radiation↗

NASA NTRSDate not supplied

Overview of The Inaugural Space Health Impacts for the NASA Experience (SHINE) Training Program - Virtual Space Radiation Curriculum

SHINE↗

DOE OSTI2012

Automated imaging system for single molecules

There is provided a high throughput automated single molecule image collection and processing system that requires minimal initial user input. The unique features embodied in the present disclosure allow automated collection and initial processing of optical images of single molecules and their assemblies. Correct focus may be automatically maintained while images are collected. Uneven illumination in fluorescence microscopy is accounted for, and an overall robust imaging operation is provided yielding individual images prepared for further processing in external systems. Embodiments described herein are useful in studies of any macromolecules such as DNA, RNA, peptides and proteins. The automated image collection and processing system and method of same may be implemented and deployed over a computer network, and may be ergonomically optimized to facilitate user interaction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

Data Science for Public Policy: Of the people, for the people, by the people 2.0 ?

In this paper, we explore the role of data science in the public policy lifecycle. We posit policy documents (bills, acts, regulations and directives) as forms of social objects and present a methodology to understand interactions between prior context in professional and personal social networks to a given public policy document release. We employ natural language processing tools along with recent advances in semantic reasoning to formulate document-level proximity metrics which we use to predict the relevance (and impact) of the policy artifacts. These metrics serve as a measure of excitation between people and the public policy initiatives.

semantic reasoning↗

DOE OSTI2016

Computer systems for annotation of single molecule fragments

There are provided computer systems for visualizing and annotating single molecule images. Annotation systems in accordance with this disclosure allow a user to mark and annotate single molecules of interest and their restriction enzyme cut sites thereby determining the restriction fragments of single nucleic acid molecules. The markings and annotations may be automatically generated by the system in certain embodiments and they may be overlaid translucently onto the single molecule images. An image caching system may be implemented in the computer annotation systems to reduce image processing time. The annotation systems include one or more connectors connecting to one or more databases capable of storing single molecule data as well as other biomedical data. Such diverse array of data can be retrieved and used to validate the markings and annotations. The annotation systems may be implemented and deployed over a computer network. They may be ergonomically optimized to facilitate user interactions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Minority Serving Institutions Partnership Program (MSIPP) - 18108

The DOE-EM recognizes that successfully completing its legacy environmental cleanup mission will require maintaining a well-trained, technically skilled, and diverse workforce. Minority representation in critical science and engineering fields is an important part of EM's vision for the future workforce. The Minority Serving Institutions Partnership Program (MSIPP) has been created and designed to increase the numbers of minorities with science and engineering experience in areas important to the success of the DOE-EM mission. MSIPP will provide financial assistance for science, technology, engineering, and mathematics (STEM) activities at Minority Serving Institutions (MSI) engaged in research and related STEM efforts supporting EM's needs. The program offers research internship opportunities at DOE National Laboratories across the DOE complex. MSIPP also encourages research collaborations between MSI Universities and DOE National Laboratories by funding research in areas relevant to DOE-EM needs. Based on current DOE-EM missions, there are two research focus areas: Tank Waste and Site Restoration. Tank Waste includes priority areas of current DOE tank waste and waste processing approaches, alternative DOE tank waste processing options, and tank management and closure. Site Restoration research concentrates in the areas of Soil and Groundwater with priority areas of attenuation-based remedies for the subsurface, deep vadose zone, remediation of mercury and industrial contaminants, and advanced simulation capability for environmental management; and, in the areas of Deactivation and Decommissioning, with priority areas of unique sensor networks for remote monitoring of entombed facilities and tanks, interactions between radiological and chemical contaminants of concern to DOE and facility materials, incombustible fixatives and decontamination agents, acceptability of DeconGel and various contaminant mixtures and robotics, remote systems with plug-and-play interchangeable components, and models for facility decommissioning. This paper gives an overview of the opportunities available to MSI students and universities and outlines the progress this program has made since its inception, and the path forward to further enhance efforts to create a pipeline into the DOE-EM workforce. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2003

ISS Mini AERCam Radio Frequency (RF) Coverage Analysis Using iCAT Development Tool

The long-term goals of the National Aeronautics and Space Administration's (NASA's) Human Exploration and Development of Space (HEDS) enterprise may require the development of autonomous free-flier (FF) robotic devices to operate within the vicinity of low-Earth orbiting spacecraft to supplement human extravehicular activities (EVAs) in space. Future missions could require external visual inspection of the spacecraft that would be difficult, or dangerous, for humans to perform. Under some circumstance, it may be necessary to employ an un-tethered communications link between the FF and the users. The interactive coverage analysis tool (ICAT) is a software tool that has been developed to perform critical analysis of the communications link performance for a FF operating in the vicinity of the International Space Station (ISS) external environment. The tool allows users to interactively change multiple parameters of the communications link parameters to efficiently perform systems engineering trades on network performance. These trades can be directly translated into design and requirements specifications. This tool significantly reduces the development time in determining a communications network topology by allowing multiple parameters to be changed, and the results of link coverage to be statistically characterized and plotted interactively.

Bolen, Steve↗

DOE OSTI2022

Transcriptional networks underlying a primary ovarian insufficiency disorder in alligators naturally exposed to EDCs

Interactions between the endocrine system and environmental contaminants are responsible for impairing reproductive development and function. Despite the taxonomic diversity of affected species and attendant complexity inherent to natural systems, the underlying signaling pathways and cellular consequences are mostly studied in lab models. To resolve the genetic and endocrine pathways that mediate affected ovarian function in organisms exposed to endocrine disrupting contaminants in their natural environments, we assessed broad-scale transcriptional and steroidogenic responses to exogenous gonadotropin stimulation in juvenile alligators (Alligator missippiensis) originating from a lake with well-documented pollution (Lake Apopka, FL) and a nearby reference site (Lake Woodruff, FL). Here, we found that individuals from Lake Apopka are characterized by hyperandrogenism and display hyper-sensitive transcriptional responses to gonadotropin stimulation when compared to individuals from Lake Woodruff. Site-specific transcriptomic divergence appears to be driven by wholly distinct subsets of transcriptional regulators, indicating alterations to fundamental genetic pathways governing ovarian function. Consistent with broad-scale transcriptional differences, ovaries of Lake Apopka alligators displayed impediments to folliculogenesis, with larger germinal beds and decreased numbers of late-stage follicles. After resolving the ovarian transcriptome into clusters of co-expressed genes, most site-associated modules were correlated to ovarian follicule phenotypes across individuals. However, expression of two site-specific clusters were independent of ovarian cellular architecture and are hypothesized to represent alterations to cell-autonomous transcriptional programs. Collectively, our findings provide high resolution mapping of transcriptional patterns to specific reproductive function and advance our mechanistic understanding regarding impaired reproductive health in an established model of environmental endocrine disruption.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Modeling laser-driven ion acceleration with deep learning

Developments in machine learning promise to ameliorate some of the challenges of modeling complex physical systems through neural-network-based surrogate models. High-intensity, short-pulse lasers can be used to accelerate ions to mega-electronvolt energies, but to model such interactions requires computationally expensive techniques such as particle-in-cell simulations. Multilayer neural networks allow one to take a relatively sparse ensemble of simulations and generate a surrogate model that can be used to rapidly search the parameter space of interest. In this study, we created an ensemble of over 1,000 simulations modeling laser-driven ion acceleration and developed a surrogate to study the resulting parameter space. A neural-network-based approach allows for rapid feature discovery not possible for traditional parameter scans given the computational cost. A notable observation made during this study was the dependence of ion energy on the pre-plasma gradient length scale. While this methodology harbors great promise for ion acceleration, it has ready application to all topics in which large-scale parameter scans are restricted by significant computational cost or relatively large, but sparse, domains.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Multi-Sectoral Urban Interactions: Fundamental Science Needs to Inform Pathways to More Resilient Communities in a Changing Climate Multi-Sectoral Urban Interactions: Fundamental Science Needs to Inform Pathways to More Resilient Communities in a Changing Climate

Urban areas and the supply networks that support their resource use are inherently multisectoral systems composed of infrastructural, environmental, and socio-institutional components. These systems are vulnerable to accelerating and interacting stresses from climate change, population growth, resource scarcity, and land-use pressure at the same time as they have a major influence on regional and global systems. For instance, a majority of the world’s greenhouse gas emissions, food consumption, and economic activity can be attributed to urban areas. Urban areas are highly heterogenous, both across and within cities in terms of their socio-demographic, environmental, and infrastructural characteristics. This heterogeneity shapes how urban systems interact and co-evolve and contributes to different economic, environmental, and health outcomes for communities within urban areas. Urban heterogeneity also generates differential vulnerabilities to stressors and differential capacity for adapting to change. The evolution of urban space is thus critical in shaping how human societies respond to global change as they seek to improve resilience to stressors, support prosperous and equitable communities, and use natural resources in a sustainable manner. Developing fundamental scientific understanding of urban heterogeneity and system interactions across sectors and scales is critical for mapping the resilience, sustainability, and equity implications of alternative future pathways. On July 2021 the MSD Urban Systems Working Group organized this workshop to provide a venue for coordination and identification of shared objectives, research themes, and major knowledge gaps, as well as developing a shared strategy for addressing these gaps. This report summarizes the outcomes of this workshop.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1982

An optimization technique for lumped-distributed two ports

A frequency domain direct efficient analysis and an optimization technique of a large class of lumped-distributed networks containing active elements are presented. Sensitivity and Hessian matrix calculations are performed using truncated Taylor series expansion of two-port parameters of subnetworks. An interactive computer program was developed to demonstrate the application of the method. Examples of network optimizations are included to illustrate the powerfulness of the technique.

Iobst, K. W.↗

NASA NTRS1997

Characterizing the Relationships Among Lightning and Storm Parameters: Lightning as a Proxy Variable

We have gained important insights from prior studies that have suggested relationships between lightning and storm growth, decay, convective rain flux, vertical distribution of storm mass and echo volume in the region, and storm energetics. A study was initiated in the Summer of 1996 to determine how total (in-cloud plus ground) lightning observations might provide added knowledge to the forecaster in the determination and identification of severe thunderstorms and weather hazards in real-time. The Melbourne Weather Office was selected as a primary site to conduct this study because Melbourne is the only site in the world with continuous and open access to total lightning (LDAR) data and a Doppler (WSR-88D) radar. A Lightning Imaging Sensor Data Applications Demonstration (LISDAD) system was integrated into the forecaster's workstation during the Summer 1996 to allow the forecaster to interact in real-time with the multi-sensor data being displayed. LISDAD currently ingests LDAR data, the cloud-to-ground National Lightning Detection Network (NLDN) data, and the Melbourne radar data in f real-time. The interactive features provide the duty forecaster the ability to perform quick diagnostics on storm cells of interest. Upon selection of a storm cell, a pop-up box appears displaying the time-history of various storm parameters (e.g., maximum radar reflectivity, height of maximum reflectivity, echo-top height, NLDN and LDAR lightning flash rates, storm-based vertically integrated liquid water content). This product is archived to aid on detailed post-analysis.

Goodman, S. J.↗

NASA NTRS2015

Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

Knowledge domain↗

DOE OSTI2017

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identifi-cation or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level.

Acciarri, R↗

DOE OSTI2026

Regression Convolutional Neural Network for Energy Estimation in NOvA

Regression Convolutional Neural Network for Energy Estimation in NOvA" Abstract: "NOvA (NuMI Off-Axis $\nu_e$ Appearance) is a long baseline neutrino experiment designed to measure neutrino oscillations over a distance of 810 km. NOvA employs a near and far detector to observe $\nu_\mu$ disappearance and $\nu_e$ appearance of neutrinos produced by the NuMI beam at Fermilab. Energy reconstruction is critical for precise measurements of neutrino oscillation parameters and cross sections, which are functions of neutrino energy. Energy estimation remains difficult due to the complexity of detector response and final state particle kinematics. We present a regression-based convolutional neural network (CNN) method that reconstructs neutrino and lepton energies based on raw pixel inputs for NOvA. The trained model is able to reconstruct event energy for different interaction modes and complex final states containing leptons and hadrons. Studies of regression CNN networks show improved energy resolution and reduced sensitivity to calibration scale uncertainties relative to traditional kinematics-based energy reconstruction techniques. The results demonstrate the potential of the regression CNN method for neutrino physics analyses by improving on standard kinematics-based reconstruction.

Zhao, Larry [UC, Irvine (main)]↗

NASA NTRS2008

The Role of Trust and Interaction in Global Positioning System Related Accidents

The Global Positioning System (GPS) uses a network of satellites to calculate the position of a receiver over time. This technology has revolutionized a wide range of safety-critical industries and leisure applications. These systems provide diverse benefits; supplementing the users existing navigation skills and reducing the uncertainty that often characterizes many route planning tasks. GPS applications can also help to reduce workload by automating tasks that would otherwise require finite cognitive and perceptual resources. However, the operation of these systems has been identified as a contributory factor in a range of recent accidents. Users often come to rely on GPS applications and, therefore, fail to notice when they develop faults or when errors occur in the other systems that use the data from these systems. Further accidents can stem from the over confidence that arises when users assume automated warnings will be issued when they stray from an intended route. Unless greater attention is paid to the role of trust and interaction in GPS applications then there is a danger that we will see an increasing number of these failures as positioning technologies become integral in the functioning of increasing numbers of applications.

Johnson, Chris W.↗

DOE OSTI2019

A review of the behavior of radioiodine in the subsurface at two DOE sites

The 129 I isotope has a half-life of nearly 16 million years, creating a potential risk to receptors when 129I is present in groundwater and effective remedies are needed to mitigate its potential risk in the environment. This paper not only provides an in-depth review of various processes and reactions that control the fate and transport of iodine, but also describes how this information can be used for in situ management of iodine. The majority of the iodine fate and transport studies have been conducted at the US Department of Energy (DOE) Hanford and Savannah River sites, where radioisotopes of iodine were inadvertently released into the environment during weapons production. Site-specific remediation technologies are currently being evaluated as part of the DOE cleanup mission. The sites are markedly different in terms of climate (arid vs. sub-tropical), major geochemical parameters (pH ~ 7.5 vs. 4) and mineralogy (carbonate vs. Fe/Al oxide dominated), but they share the same network of processes and reactions that control iodine fate and transport. These include adsorption to minerals and sediments, interactions with organic matter, electron transfer reactions with minerals and microbes, and precipitation. In conclusion, this process-based network serves as basis for regional scale model calculations to predict plume spreading and/or dissipation, design efficient remediation techniques and conduct contamination management activities.

54 ENVIRONMENTAL SCIENCES↗