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Advances In very high resolution satellite imagery analysis for Monitoring human settlements

The high rate of urbanization, political conflicts and ensuing internal displacement of population, and increased poverty in the 20th century has resulted in rapid increase of informal settlements. These unplanned, unauthorized, and/or unstructured homes, known as informal settlements, shantytowns, barrios, or slums, pose several challenges to the nations, as these settlements are often located in most hazardous regions and lack basic services. Though several World Bank and United Nations sponsored studies stress the importance of poverty maps in designing better policies and interventions, mapping slums of the world is a daunting and challenging task. In this paper, we summarize our ongoing research on settlement mapping through the utilization of Very high resolution (VHR) remote sensing imagery. Most existing approaches used to classify VHR images are single instance (or pixel-based) learning algorithms, which are inadequate for analyzing VHR imagery, as single pixels do not contain sufficient contextual information (see Figure 1). However, much needed spatial contextual information can be captured via feature extraction and/or through newer machine learning algorithms in order to extract complex spatial patterns that distinguish informal settlements from formal ones. In recent years, we made significant progress in advancing the state of art in both directions. This paper summarizes these results.

Vatsavai, Raju↗

Nested active learning for efficient model contextualization and parameterization: pathway to generating simulated populations using multi-scale computational models

There is increasing interest in the use of mechanism-based multi-scale computational models (such as agent-based models (ABMs)) to generate simulated clinical populations in order to discover and evaluate potential diagnostic and therapeutic modalities. The description of the environment in which a biomedical simulation operates (model context) and parameterization of internal model rules (model content) requires the optimization of a large number of free parameters. In this work, we utilize a nested active learning (AL) workflow to efficiently parameterize and contextualize an ABM of systemic inflammation used to examine sepsis. Contextual parameter space was examined using four parameters external to the model’s rule set. The model’s internal parameterization, which represents gene expression and associated cellular behaviors, was explored through the augmentation or inhibition of signaling pathways for 12 signaling mediators associated with inflammation and wound healing. We have implemented a nested AL approach in which the clinically relevant (CR) model environment space for a given internal model parameterization is mapped using a small Artificial Neural Network (ANN). The outer AL level workflow is a larger ANN that uses AL to efficiently regress the volume and centroid location of the CR space given by a single internal parameterization. We have reduced the number of simulations required to efficiently map the CR parameter space of this model by approximately 99%. In addition, we have shown that more complex models with a larger number of variables may expect further improvements in efficiency.

97 MATHEMATICS AND COMPUTING↗

Introduction to Metadata and Ontologies: Everything You Always Wanted to Know About Metadata and Ontologies (But Were Afraid to Ask)

Metadata are contextual data about your experimental data. Metadata are the who, what, when, where, and why of these data. Metadata puts these data into context. In microbiome research, metadata includes information about the sample: when it was collected, where it was collected from, what kind of sample it is, and what were the properties of the environment or experimental condition from which the sample was taken. Information about sample processing is also metadata: methods used to extract and purify molecules (e.g., DNA) from the sample, type of DNA sequencing or other ’omics analyses done, and where the raw experimental data are located. This documentation includes information on the following topics: What are metadata? What kinds of metadata are there? Why are metadata important? Why should metadata be standardized? Why should metadata be machine readable? What is an ontology? Why are ontologies important? What are some examples of ontologies? The documentation also includes further resources on metadata guides and tools and tips for formatting metadata for maximum utility.

59 BASIC BIOLOGICAL SCIENCES↗

Boninites from Cyprus Island as Mercury Lava Analogues

Mercurian meteorites have never been found on Earth. However, thanks to the NASA’s MESSENGER mission, some constraints on the geochemistry and mineralogy of Mercurian rocks are now available. Results from the Xand Gamma-ray Spectrometers onboard the MESSENGER mission suggest a surface composition with Mg/Si ratio within 0.33-0.67 and a Fe/Si ratio within 0.03-0.15, characterized by extremely reduced (IW -6) rocks. Experimental petrology studies show that the most appropriate Mercurian rock-type should be a Mg-rich, Fe-poor basalt, mainly composed of orthopyroxene and plagioclase. Visible/near-infrared (VNIR) spectroscopy of terrestrial basalts can help contextualize acquired MESSENGER spectra. The most Mg-rich, Al-poor regions on Mercury, are suggested to be orthopyroxene-rich lavas analogous to terrestrial boninites and/or komatiites. At present, there are no studies on the geochemistry and mineralogy of boninites for their possible association with Mercurian material. In addition, there are still no information about the VNIR spectral properties of boninitic material. In this work, we investigate the VNIR and Raman spectroscopy and X-Ray Fluorescence (XRF) of a series of boninitic pillow lavas that were collected on the Upper Pillow Lavas unit of the Troodos Massif, located on the island of Cyprus. Data are then discussed in order to reveal potential classification as Mercury analog.

Nicola Mari↗

Contextualizing Non-Powered Dam Site Selection for Archimedes Screw Turbines: A Methodology for Responsible Archimedes Screw Turbine Conversion at Existing Dams

Non-powered dams represent 97% of dams in the United States and their energy generation potential has not been fully realized. The use of an Archimedes screw turbine to generate power at non-powered dams offers a dual benefit; producing electricity, and acting as downstream fish passage, helping to reconnect previously separated ecosystems. In this study, we assess the technical, environmental, social, and economic feasibility of generating power at non-powered U.S. dam sites using Archimedes screw turbines by integrating mechanical constraints, social impact metrics, proximity to infrastructure, and environmental sensitivity data. Results account for future precipitation predictions and show, between 2024 and 2050, the number of sites where Archimedes screw turbines are viable decreases by one site, but overall generation capacity increases due to increased flow rates across persisting locations. Our analysis identified 82 non-powered dam sites with a mean generation capacity of 49 kW that meet the mechanical requirements for Archimedes screw turbine technology in 2024. Our analysis presents a framework for considering social, environmental, and economic impacts of specific turbine technologies to convert non-powered dams to generate power.

Archimedes screw turbine↗

University Data Management Pilot Utilizing the Nuclear Research Data System

Background In 2022, the Office of Science and Technology Policy (OSTP) issued a memo that significantly reshaped the landscape of access to federally funded research. The memo mandated that all taxpayer-funded research be made available to the public without delay upon publication, without an embargo period, superseding the 2013 OSTP public access policy. This public access policy promotes transparency and the democratization of knowledge, ensuring that the fruits of scientific endeavors funded by federal agencies could be immediately accessed and built upon by scientists, educators, students, and the public at large. To implement the requirements of the OSTP guidance and DOE Public Access Plan, the Office of Nuclear Energy (NE) has implemented public access plan guidance and has identified several areas where better data management practices would further expand public access to important nuclear energy related scientific data, reports, and other technical products. Significant NE supported efforts are already underway for data management and public access to important nuclear energy related data.1 2 To address gaps in data management practices, and improve retention and accessibility of data, NE is actively exploring enhanced data management options utilizing its high-performance computing resources administered by its Nuclear Scientific User Facility Program. A newly piloted system, the Nuclear Research Data System (NRDS) acts as a portal for data collection and dissemination. Nuclear Energy University Program Research and Development Portfolio According to Web of Science, NEUP has produced 2,345 journal publication that have been cited more than 61,000 times3 and countless conference proceedings. These publications are publicly available through OSTI.gov and in the open literature. Additional scientific and technical products including project milestones that are not publications and NEUP project final reports are vetted through OSTI.gov and released once reviewed and approved by DOE. Since 2009, NEUP has awarded close to 1,000 different R&D projects in technical areas across the NE research programs. As of June 2023, 512 NEUP reports are publicly available on OSTI. The underlying data for projects is still held at universities, and data transfer, co-location, and dissemination has not occurred in a systematic way. NEUP data is currently accessible through myriad university-based data repositories, or through direct requests to PIs. The program identified this patchwork of repositories, or often lack of publicly available data, as a significant barrier to an organized, accessible, and comprehensive solution to sharing data with the larger nuclear energy community. Approach The goal of this pilot project is to establish a pathway to a consolidated long-term repository for NEUP project data. To accomplish this goal, the pilot strives to accomplish the following objectives: Establish data collection standards, including a standard set of required supplementary information to contextualize and support raw data files. Work with the HPC group collect and upload information and to modify the NRDS system, as needed, to support a standardized approach. Resolve potential barriers to successful roll out of an expanded data collection strategy, including modifying data management plan guidelines and establishing a document and data release process that accounts for potential intellectual property and/or export control concerns. Results Overall, the pilot was successful in collecting 8,982 raw and processes data files, 220 reports, 56 calibration files, and 5,931 other supplementary documents. Supplementary documents included experimental plans, methods, journal publications and conference proceedings, milestone reports, and final reports. Figure 2 shows the number of data sets and supplementary project information provided by each project. Projects has significantly different input, depending on experimental data produced and completeness of the datasets provided.

Data collection↗

Integrated fluorescence light microscopy-guided cryo-focused ion beam-milling for in situ montage cryo-ET

Cryogenic-electron tomography (cryo-ET) permits the in situ visualization of biological macromolecules at the molecular level. Owing to the variable thickness of cells, tissues and organisms, frozen specimens may need to be thinned by cryo-focused ion beam (FIB) milling to produce thin (<500 nm) cryo-lamellae suitable for cryo-ET. Locating regions of interest remains a challenge because untargeted milling can lead to inadvertent ablation and removal of regions of interest. Correlative light and electron microscopy, combined with cryo-FIB milling, can guide the identification of labeled targets in the cellular milieu. Multiple transfers between cryo-imaging instruments, cumbersome correlation algorithms, limited accuracy and low throughput have hindered the routine adoption of cryo-FIB milling within a multimodal correlative workflow for in situ structural biology. Here, in this study, we present a workflow for 3D correlative cryo-fluorescence light microscopy-FIB-ET that streamlines fluorescence light microscopy-guided FIB milling, improving throughput while preserving both structural and contextual information. The complete integration of hardware and software described here minimizes sample contamination from cross-platform exchanges and greatly enhances the efficiency of 3D targeting in cryo-milling. We then describe procedures for implementing montage parallel array cryo-ET (MPACT), which can be easily adapted to any modern life-science transmission electron microscope. MPACT supports high-throughput cryo-ET acquisitions (10 tilt series in 1.5 h) for structure determination and comprehensive contextual understanding of macromolecules within their native surroundings. A complete session from sample preparation to MPACT data processing takes 5−7 d for an individual experienced in both cryo-EM and cryo-FIB milling.

Yang, Jie E. [Univ. of Wisconsin, Madison, WI (Uni↗

The HydroBio Dataset: a new data resource for evaluating existing and potential hydropower capacity and freshwater biodiversity in the conterminous United States

Hydropower is a critical source of affordable and reliable electricity and energy system stability services in the United States. Opportunities to expand US hydropower production include retrofitting existing non-powered dams to produce power, retrofitting existing hydropower dams to improve efficiency or increase capacity, or constructing new hydropower infrastructure on currently unregulated river reaches. We created the HydroBio Dataset, which summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin scale in the conterminous US to contextualize existing and potential grid contributions with the freshwater ecosystems in which dams are situated. We demonstrate a use-case of this dataset by rescaling and comparing potential non-powered dam nominal capacity to rarity-threat-weighted freshwater species richness for sub-basins where both types of data exist. On average, normalized freshwater biodiversity exceeded normalized potential non-powered dam nominal capacity in these sub-basins. Potential non-powered dam nominal capacity was concentrated in sub-basins in the Upper Mississippi and Ohio hydrologic regions while freshwater biodiversity was concentrated in the South Atlantic-Gulf, Ohio, and Tennessee hydrologic regions. Additionally, non-powered dams and existing hydropower dams are located in sub-basins with similar indices of freshwater biodiversity. The HydroBio Dataset adds an additional ecological dimension of context to our understanding of current and potential future US hydropower capabilities and is a valuable decision support tool for stakeholders tasked with balancing gains in services to the US power grid with the public and environmental benefits of freshwater ecosystems.

Biodiversity↗

Learning from Correlated Events for Equipment Relation Inference in Buildings

Modern buildings produce thousands of data streams, and the ability to automatically infer the physical context of such data is the key to enabling building analytics at scale. As acquiring this contextual information is currently a time-consuming and error-prone manual process, in this study we make the first attempt at automatically inferring one important contextual aspect of the equipment in buildings — how each equipment is functionally connected with another. The main insight behind our solution is that functionally connected equipment is exposed to the same events in the physical world, creating correlated changes in the time series data of both equipment. Because events are of indeterminate length in time series, however, identifying them requires solving a non-polynomial combinatorial data segmentation problem. We present a solution that first extracts latent events from the sensory time series data, and then sifts out coincident events with a customized correlation procedure to identify the relationship between equipment.We evaluated our approach on data collected from over 1,000 pieces of equipment from 5 commercial buildings of various sizes located in different geographical regions in the US. Results show that this approach achieves 94.38% accuracy in relation inference, compared to 85.49% by the best baseline.

Relation inference, smart buildings, time series a↗

Demand for off-grid desalination technology in small-island communities — Can interfacial solar vapor generation be the answer?

The demand for an off-grid desalination technology and the feasibility of using interfacial solar vapor generation (ISVG) to address the problem were evaluated within the context of Bungin Island. Bungin Island is a small-island community in Indonesia facing water scarcity. By conducting interviews with households there, we found that households located on the exterior portion of the island faced the greatest challenges to water access. For example, only 17% of exterior households had piped water access, whereas 67% central households had piped water access. Similar inequities for exterior households were also found with respect to the cost of getting additional water. Thus, we determined that an off-grid desalination technology is best suited for solving the water access problems for the most vulnerable communities in small islands. Further, ISVG technologies that draw on the radiative energy in sunlight to achieve desalination are promising in increasing water access by offering a floating off-grid devices on water near exterior households, passive operation, low capital investment, and simple maintenance. These findings stress the importance of understanding how contextual factors shape barriers to water access and provide a road map on how to begin incorporating these factors into the development of a more sustainable desalination technology.

42 ENGINEERING↗

Interactive Streamline Exploration and Manipulation Using Deformation

Occlusion presents a major challenge in visualizing three-dimensional flow fields with streamlines. Displaying too many streamlines at once makes it difficult to locate interesting regions, but displaying too few streamlines risks missing important features. A more ideal streamline exploration model is to allow the viewer to freely move across the field that has been populated with interesting streamlines and pull away the streamlines that cause occlusion so that the viewer can inspect the hidden ones in detail. In this paper, we present a streamline deformation algorithm that supports such user-driven interaction with three-dimensional flow fields. We define a view-dependent focus+context technique that moves the streamlines occluding the focus area using a novel displacement model. To preserve the context surrounding the user-chosen focus area, we propose two shape models to define the transition zone for the surrounding streamlines, and the displacement of the contextual streamlines is solved interactively with a goal of preserving their shapes as much as possible. Based on our deformation model, we design an interactive streamline exploration tool using a lens metaphor. Our system runs interactively so that users can move their focus and examine the flow field freely.

flow visualization, focus+context, streamline, def↗

The Influence of Real-World Wind Turbine Deployments on Local to Mesoscale Climate

Paired simulations are conducted using the Weather Research and Forecasting model applied at convection permitting resolution in order to determine the impact of wind turbines (WTs) on the local to mesoscale climate. Using actual WT locations and a model of the effect of the WT rotor on the flow field, it is shown that while the presence of WT changes wind speeds (WSs) and near-surface air temperature in 4-km grid cells in which WTs are located, the impact at larger scales on near-surface air temperature, specific humidity, the fluxes of latent and sensible heat, boundary layer heights, and precipitation is not significant in any season other than summer. During summer, the maximum pairwise difference in grid cell mean temperatures is 0.5 K and the maximum increase in near-surface specific humidity is 0.4 g/kg. However, a spatial average of the mean seasonal perturbation of air temperature by WT gives a net impact of <0.1 K. Precipitation probability is also not significantly impacted in any season other than summer. In the summer the presence of WT is associated with a small decrease in precipitation probability and a decrease in season total precipitation of -2.6%. The finding of minor magnitude, but significant impacts, during summer should be used to contextualize results of substantial climate impacts from WT arrays deployed in the U.S. Central Plains based on short-term simulations conducted for the summer season.

54 ENVIRONMENTAL SCIENCES↗

Electricity Transmission, Pipelines, and National Trails: An Analysis of Current and Potential Intersections on Federal Lands in the Eastern United States, Alaska, and Hawaii

As has been noted in many reports and publications, acquiring new or expanded rights-of-way for transmission is a challenging process, because numerous land use and land ownership constraints must be overcome to develop pathways suitable for energy transmission infrastructure. In the eastern U.S., more than twenty federally protected national trails (some of which are thousands of miles long, and cross many states) pose a potential obstacle to the development of new or expanded electricity transmission capacity. However, the scope of this potential problem is not well-documented, and there is no baseline information available that could allow all stakeholders to study routing scenarios that could mitigate impacts on national trails. This report, Electricity Transmission, Pipelines, and National Trails: An Analysis of Current and Potential Intersections on Federal Lands in the Eastern United States, was prepared by the Environmental Science Division of Argonne National Laboratory (Argonne). Argonne was tasked by DOE to analyze the “footprint” of the current network of National Historic and Scenic Trails and the electricity transmission system in the 37 eastern contiguous states, Alaska, and Hawaii; assess the extent to which national trails are affected by electrical transmission; and investigate the extent to which national trails and other sensitive land use types may be affected in the near future by planned transmission lines. Pipelines are secondary to transmission lines for analysis, but are also within the analysis scope in connection with the overall directives of Section 368 of the Energy Policy Act of 2005, and because of the potential for electrical transmission lines being collocated with pipelines. Based on Platts electrical transmission line data, a total of 101 existing intersections with national trails on federal land were found, and 20 proposed intersections. Transmission lines and pipelines are proposed in Alaska; however there are no locations that intersect national trails. Source data did not indicate any planned transmission lines or pipelines in Hawaii. A map atlas provides more detailed mapping of the topics investigated in this study, and the accompanying GIS database provides the baseline information for further investigating locations of interest. In many cases the locations of proposed transmission lines are not accurately mapped (or a specific route may not yet be determined), and accordingly the specific crossing locations are speculative. However since both national trails and electrical transmission lines are long linear systems, the characteristics of the crossings reported in this study are expected to be similar to both observed characteristics of the existing infrastructure provided in this report, and of the new infrastructure if these proposed projects are built. More focused study of these siting challenges is expected to mitigate some of potential impacts by choosing routes that minimize or eliminate them. The current study primarily addresses a set of screening-level characterizations that provide insights into how the National Trail System may influence the siting of energy transport facilities in the states identified under Section 368(b) of the Energy Policy Act of 2005. As such, it initializes gathering and beginning analysis of the primary environmental and energy data, and maps the contextual relationships between an important national environmental asset and how this asset intersects with energy planning activities. Thus the current study sets the stage for more in-depth analyses and data development activities that begin to solve key transmission siting constraints. Our recommendations for future work incorporate two major areas: (1) database development and analytics and (2) modeling and scenario analysis for energy planning. These recommendations provide a path forward to address key issues originally developed under the Energy Policy Act of 2005 that are now being carried forward under the President’s Climate Action Plan.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

How Frequent Will the Rarest Daily Rainfall Records of Hurricane Ida’s Remnants Be in the Future?

Abstract Gaining continued insights into the impact of global warming on the occurrence of hurricane-associated intense record downpours is essential for building climate resilient communities. This study investigates projected future changes in extreme rainfall over the Northeast United States, as represented by extreme daily amounts during Hurricane Ida in 2021. We used historical control simulations of Weather Research and Forecasting (WRF) Model generated from 40 years of weather events (1980–2014, 12 km) forced by the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis. These simulations are thermodynamically modified (2060–2100) via an imposed warming for the high-emission scenario of shared socioeconomic pathway (SSP585) from a range of general circulation models. Ground observations from the Global Historical Climatology Network (1950–2014) and WRF simulations (historical, 1980–2014, and future, 2060–2100) are integrated into a nonstationary generalized extreme value (GEV) framework to assess the frequency of Ida’s heaviest daily rain rates under the SSP585 scenario. Results show that Ida’s daily maximum rainfall recorded at different observation locations was higher than the single highest September daily maximum observed (1950–2014) for 5 out of 17 stations (∼30% of the stations). Ida-like extreme daily rain rates are projected to be, on average, more than 2 times more likely to occur at the end of the century in the simulations (with some regions as high as 5 times). This work demonstrates that integrating a high-resolution atmospheric model’s present-day and thermodynamically modified future simulations along with ground observations, within a nonstationary statistical framework, is crucial for understanding changing characteristics of extreme weather events. Significance Statement Daily scale extreme precipitation is expected to become more frequent and severe, as evidenced by observations and model simulations. While it is important to investigate how these intensifying heavy rainfall events affect current engineering standards, fewer studies have contextualized how warming impacts the most extreme rainfall from a single storm event relative to historical heavy downpours. In this study, we focused on the daily extreme rainfall associated with the extratropical transition of Hurricane Ida (2021), particularly over the northeastern United States—some of which exceeded the commonly used hydrologic design criteria for a 100-yr storm. Using a high-resolution atmospheric model simulation, we investigated how continued warming may influence the frequency of such daily rain rates. Under a high-emission scenario, these events are projected to become up to 5 times more likely at the end of the twenty-first century.

Dollan, Ishrat J↗

Microscopy Methods for Life Detection on Ocean Worlds

On Earth, light microscopy is commonly used in microbiology to identify organisms and observe their interactions with the environment; this makes it an attractive technique for in situ life detection methods on ocean worlds. As a standalone technique, brightfield microscopy, while able to provide important contextual information, has limited usefulness as a life detection technique because it is often challenging to differentiate between abiotic and biotic particles based solely on their size and shape, which may introduce risks of false positive or false negative interpretations. However, these risks can be reduced by combining brightfield microscopy with fluorescence microscopy to provide a method that correlate sample chemistry with sample morphology. In this work, we have used the Luminescence Imager for Exploration (LIfE), a brightfield and epifluorescence microscope with an integrated sample processing system (matured under the Concepts for Ocean worlds Life Detection Technology and Instrument Concepts of Europa Exploration programs) to develop methods that increase the fidelity of in situ microscopy life detection measurements through two main approaches. First, native fluorescence is excited in molecules that contain aromatic moieties such as proteins (using deep UV excitation), and energy carrying molecules and endogenous chromophores (using visible-light excitation), to correlate the location of these species with cell-like structural features (brightfield imaging). Second, fluorescent stains are used to selectively image cells and cell fragments by targeting proteins, lipids, and nucleic acids. We discuss the results of tests, obtained using ocean world analog samples, that have examined trades associated with implementing these methods autonomously in planetary missions, including the intrinsic properties of candidate fluorescence dyes and long-term storage and radiation stability.

Pavel E. Z. Klier↗

Microscopy Methods for Life Detection on Ocean Worlds

On Earth, light microscopy is commonly used in microbiology to identify organisms and observe their interactions with the environment; this makes it an attractive technique for in situ life detection methods on ocean worlds. As a standalone technique, brightfield microscopy, while able to provide important contextual information, has limited usefulness as a life detection technique because it is often challenging to differentiate between abiotic and biotic particles based solely on their size and shape, which may introduce risks of false positive or false negative interpretations. However, these risks can be reduced by combining brightfield microscopy with fluorescence microscopy to provide a method that correlate sample chemistry with sample morphology. In this work, we have used the Luminescence Imager for Exploration (LIfE), a brightfield and epifluorescence microscope with an integrated sample processing system (matured under the Concepts for Ocean worlds Life Detection Technology and Instrument Concepts of Europa Exploration programs) to develop methods that increase the fidelity of in situ microscopy life detection measurements through two main approaches. First, native fluorescence is excited in molecules that contain aromatic moieties such as proteins (using deep UV excitation), and energy carrying molecules and endogenous chromophores (using visible-light excitation), to correlate the location of these species with cell-like structural features (brightfield imaging). Second, fluorescent stains are used to selectively image cells and cell fragments by targeting proteins, lipids, and nucleic acids. We discuss the results of tests, obtained using ocean world analog samples, that have examined trades associated with implementing these methods autonomously in planetary missions, including the intrinsic properties of candidate fluorescence dyes and long-term storage and radiation stability.

Pavel E Z Klier↗

Market Survey 2020: Commercial Clinical Decision Support Systems and Wellness Tools

For long-duration, deep space exploration missions, current methods for managing and supporting crew health and medical conditions will be unsuitable. Communication and data transmission lags will necessitate the use of a sophisticated clinical decision support system (CDSS) that will tailor diagnosis and treatment guidance that is context-sensitive for anticipated astronaut health, wellness, and medical conditions. A variety of clinical decision support (CDS) and wellness tools (WT) are currently available in the commercial market and a broad-brush survey of this market can provide an initial impression of the current state of the art which, in turn, can inform the roadmap of NASA deep space CDSS development and associated requirements. Such a survey was undertaken during the first six months of 2020 using directed convenience sampling to obtain information provided by vendors on their websites; both commercially available CDS and WT (such as those used to track and monitor nutrition, exercise, and sleep) were included. Areas assessed were item type (e.g., software/application, device); primary purpose of the item (e.g., diagnostic support, nutrition tracking); additional purposes (if any); reported features, capabilities, and functionality; setting of use (e.g., inpatient, outpatient); intended user (e.g., clinician, patient); location and sources of data/information used or produced by the item; integration with patient electronic health record (EHR); compliance with interoperability ontologies and standards (e.g., Health Level 7 [HL7], Systematized Nomenclature of Medicine – Clinical Terminology [SNOMED-CT]); and whether the item is knowledge-based (derived from research findings) or non-knowledge-based (derived through artificial intelligence, machine learning, advanced probability and statistics), among others. Ninety-seven (97) vendor websites describing 196 CDS and 73 WT (269 total) were reviewed and coded. The primary purpose of the majority of CDS reviewed is diagnosis or diagnosis/treatment/drug decision support—targeted for clinician use— and the primary purpose of the majority of WT reviewed is the monitoring of different health metrics, most often through the use of a biosensor device (e.g., blood pressure)—targeted for patient use. Very few CDS or WT appear to comply with major international interoperability standards or can be integrated with a patient’s EHR data. None consider contextual factors, such as conditions of the physical environment (e.g., CO2 levels). The majority of CDS and WT reviewed are non-knowledge, cloud- or web-based applications or software. Forty-three (43) major findings were identified and the implications those findings have for NASA will be discussed. Example major findings include: CDS-WT capabilities range from diagnosis to treatment applications, CDS-WT may be wearable or non-wearable and are technologically advanced and only a few CDS-WT tools referenced compliance to ensure interoperability, among other findings. Recommendations will also be offered that will help to address ExMC Gap, Medical-701: Enhance medical capabilities within an exploration medical system.

market survey↗

NSA Site Science: Use of ARM Observations from Northern Alaska to Evaluate and Improve Prediction Capabilities

The Arctic is warming at a rate nearly double that of the rest of the planet, leading to profound changes in atmospheric, oceanic, and ice processes. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility has played a significant role in Arctic research, operating observatories in Alaska's North Slope for over 25 years. These observatories provide a rich, and wide-reaching dataset that offers insight into atmospheric processes in northern Alaska. This report details the results of a nine-year research project (2015–2024) supported by the DOE Atmospheric Systems Research (ASR) program, that leverages data from ARM’s deployment of observing facilities at Utqiaġvik (known as the North Slope of Alaska, or NSA, site) and Oliktok Point, Alaska. The project was conducted in two phases: - Phase 1 (2015–2019): Focused on understanding key atmospheric processes at Oliktok Point, including cloud formation, high-latitude precipitation, aerosol-cloud interactions, and cloud properties. - Phase 2 (2019–2024): Extended the research to the broader North Slope region, using data from both Oliktok Point and Utqiaġvik. Topics explored included surface energy budgets, atmospheric stability, ice nucleation processes, and microphysics in Arctic clouds. The project resulted in numerous research products, including 50 peer-reviewed publications and dissertations, 169 presentations, and 10 data products. These products cover a variety of topics, including: - Cloud Macro- and Microphysical Properties: Arctic clouds play a crucial role in energy transfer, and accurate representation in models is critical. The study explored cloud transitions, ice crystal shapes, and dual-wavelength radar data to understand ice crystal habits and size distributions. - Aerosol Properties and Processes: The team examined aerosol sources in the Arctic, including industrial emissions and natural sources. Observations showed significant spatial gradients in aerosol concentrations due to human activities and wildfire smoke. The influence of aerosols on cloud formation and the surface energy budget was also assessed. - Aerosol-Cloud Interactions: Research revealed that aerosols might suppress cloud ice production, affecting cloud radiative forcing and precipitation. The impact of local industrial emissions on cloud properties was also investigated. - Contextualizing the North Slope of Alaska in the context of the broader Arctic: To understand broader trends, the project evaluated large-scale circulation patterns and the influence of weather systems on the Arctic. Studies indicated that large-scale processes play a significant role in temperature patterns and the timing of snowmelt. - Advancing ARM Observational and Modeling Capabilities: The project developed new radar data products and advanced measurement techniques, including clutter mitigation and drizzle detection. Uncrewed aerial systems (UAS) and tethered balloon systems (TBS) were deployed to gather detailed atmospheric data. Additionally, the project supported 10 early career scientists, providing training and mentorship to undergraduate interns, graduate students, postdoctoral researchers, and early career researchers. These efforts contributed to the advancement of ARM research capabilities and fostered a new generation of scientists skilled in Arctic atmospheric research. Ultimately, this ASR-supported project has provided valuable insights into Arctic atmospheric processes and their broader climate implications. Recommendations for future work include continuing support for long-term observing at Arctic locations to foster additional research, further exploration of aerosol-cloud interactions and the potential impacts of enhanced industrialization of the Arctic, and expanded use of uncrewed systems to gather data in this remote and harsh environment. Additionally, the data products developed by this work, and the data products developed through the ARM infrastructure, leave a treasure-trove of additional information that should be explored for many years to come to gain additional insight into physical processes in the Arctic atmosphere that drive the rapid changes occurring in at high latitudes and their global impact.

58 GEOSCIENCES↗