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Risk-Informed Condition Evaluation of Solar-centered Energy Generation and Distribution Networks through Bayesian Learning and Inference

We develop a methodology based on Bayesian inference over Probabilistic Graphical Models (PGMs) to understand and quantify risk in solar-centered grids using targeted measurements and learned system behavior. Being non-prescriptive but, rather, able to infer system behavior and, ultimately, address risk queries from data, our machine learning-type paradigm is tailored for diverse topologies and threat scenarios often associated with distributed energy generation and photovoltaic distributed energy resources (PV-DERs) in particular. We describe algorithmic processes for: (i) learning the structure of PGMs that result from attack-prone PV-DER-proliferated distribution systems, (ii) quantifying cause-effect relationships, and (iii) evaluating risk queries based on diverse evidence. The contributions are illustrated on a residential grid subject to output impairment attacks on its PV-DER infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unravelling biogeochemical drivers of methylmercury production in an Arctic fen soil and a bog soil

Arctic tundra soils store a globally significant amount of mercury (Hg), which could be transformed to the neurotoxic methylmercury (MeHg) upon warming and thus poses serious threats to the Arctic ecosystem. However, our knowledge of the biogeochemical drivers of MeHg production is limited in these soils. Using substrate addition (acetate and sulfate) and selective microbial inhibition approaches, we investigated the geochemical drivers and dominant microbial methylators in 60-day microcosm incubations with two tundra soils: a circumneutral fen soil and an acidic bog soil, collected near Nome, Alaska, United States. Results showed that increasing acetate concentration had negligible influences on MeHg production in both soils. However, inhibition of sulfate-reducing bacteria (SRB) completely stalled MeHg production in the fen soil in the first 15 days, whereas addition of sulfate in the low-sulfate bog soil increased MeHg production by 5-fold, suggesting prominent roles of SRB in Hg(II) methylation. Without the addition of sulfate in the bog soil or when sulfate was depleted in the fen soil (after 15 days), both SRB and methanogens contributed to MeHg production. Analysis of microbial community composition confirmed the presence of several phyla known to harbor microorganisms associated with Hg(II) methylation in the soils. Lastly, the observations suggest that SRB and methanogens were mainly responsible for Hg(II) methylation in these tundra soils, although their relative contributions depended on the availability of sulfate and possibly syntrophic metabolisms between SRB and methanogens.

54 ENVIRONMENTAL SCIENCES↗

SoK: What does it Mean to Benchmark Database Forensics?

Relational Database Management Systems are the backbone of modern enterprises and public-sector services, and are thus frequent targets of security incidents, insider threats, and thorough regulatory audits. Consequently, databases have become key sources of digital evidence, requiring investigators to reconstruct past activity from audit logs, transaction logs, and backups. Although benchmarking frameworks such as those developed by the Transaction Processing Performance Council (TPC) are widely used to evaluate database performance, they do not capture forensic requirements such as evidentiary completeness, tamper-evidence, chain of custody, or regulatory compliance under GDPR and CCPA. This survey examines the emerging domain of forensic database benchmarking. We gathered prior research on database forensics, secure logging, and tamper-evident data structures; we analyze modern forensic-ready features in commercial and open-source systems (SQL Server Ledger, Oracle Blockchain Tables, PostgreSQL pgAudit, Db2 Audit, Aurora Database Activity Streams, Oracle Real Application Security and IBM Guardium) and assess why existing benchmarks are insufficient. We propose forensic workloads, metrics, and methodologies that incorporate adversarial stressors, deleted-record recovery, and backup analysis. We also identify open research problems and call for a community-driven forensic benchmark suite. The result is an idea for evaluating not only database performance but also forensic soundness, bridging the gap between system engineering, compliance, and digital investigations.

Lenard, Ben↗

GIF Supercritical Water Cooled Reactor: Proliferation Resistance and Physical Protection White Paper

This report is part of a series of six white papers, prepared jointly by the Proliferation Resistance and Physical Protection Working Group (PRPPWG) and the six System Steering Committees (SSCs) and provisional System Steering Committees (pSSCs). This publication is an update to a similar series published in 2011 presenting the status of Proliferation Resistance & Physical Protection (PR&PP) characteristics for each of the six systems selected by the Generation IV International Forum (GIF) for further research and development, namely: the Sodium-cooled fast Reactor (SFR), the Very high temperature reactor (VHTR), the gas-cooled fast reactor (GFR), the Molten salt reactor (MSR) and the Supercritical water–cooled reactor (SCWR). This white paper represents the status of Proliferation Resistance and Physical Protection (PR&PP) characteristics for the Supercritical Water-cooled Fast reactor (SCFR) reference designs selected by the Generation IV International Forum (GIF) SCWR System Steering Committee (SSC). The intent is to generate preliminary information about the PR&PP features of the SCWR reactor technology and to provide insights for optimizing their PR&PP performance for the benefit of SCWR system designers. It updates the SCWR analysis published in the 2011 report “Proliferation Resistance and Physical Protection of the Six Generation IV Nuclear Energy Systems”, prepared Jointly by the Proliferation Resistance and Physical Protection Working Group (PRPPWG) and the System Steering Committees and provisional System Steering Committees of the Generation IV International Forum, taking into account the evolution of both the systems, the GIF R&D activities, and an increased understanding of the PR&PP features. The white paper, prepared jointly by the GIF PRPPWG and the GIF SCWR SSC, follows the highlevel paradigm of the GIF PR&PP Evaluation Methodology to investigate the PR&PP features of the eight proposed GIF SCWR designs. Two small modular reactors, the Canadian SSR and the Canada/China/Europe ECC-SMART are also mentioned. An overview of the fuel cycles for the GIF designs are provided. For PR, the document analyses and discusses the proliferation resistance aspects in terms of robustness against State-based threats associated with diversion of materials, misuse of facilities, breakout scenarios, and production in clandestine facilities. Similarly, for PP, the document discusses the robustness against theft of material and sabotage by non-State actors. The document follows a common template adopted by all the white papers in the updated series.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Spruce, Joseph P.↗

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because it can aid in both cybersecurity analysis and the evaluation of other cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

cyber-physical systems↗

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because they can aid in both cybersecurity analysis and the evaluation of cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

alfalfa↗

Potential of VIIRS Time Series Data for Aiding the USDA Forest Service Early Warning System for Forest Health Threats: A Gypsy Moth Defoliation Case Study

This report details one of three experiments performed during FY 2007 for the NASA RPC (Rapid Prototyping Capability) at Stennis Space Center. This RPC experiment assesses the potential of VIIRS (Visible/Infrared Imager/Radiometer Suite) and MODIS (Moderate Resolution Imaging Spectroradiometer) data for detecting and monitoring forest defoliation from the non-native Eurasian gypsy moth (Lymantria dispar). The intent of the RPC experiment was to assess the degree to which VIIRS data can provide forest disturbance monitoring information as an input to a forest threat EWS (Early Warning System) as compared to the level of information that can be obtained from MODIS data. The USDA Forest Service (USFS) plans to use MODIS products for generating broad-scaled, regional monitoring products as input to an EWS for forest health threat assessment. NASA SSC is helping the USFS to evaluate and integrate currently available satellite remote sensing technologies and data products for the EWS, including the use of MODIS products for regional monitoring of forest disturbance. Gypsy moth defoliation of the mid-Appalachian highland region was selected as a case study. Gypsy moth is one of eight major forest insect threats listed in the Healthy Forest Restoration Act (HFRA) of 2003; the gypsy moth threatens eastern U.S. hardwood forests, which are also a concern highlighted in the HFRA of 2003. This region was selected for the project because extensive gypsy moth defoliation occurred there over multiple years during the MODIS operational period. This RPC experiment is relevant to several nationally important mapping applications, including agricultural efficiency, coastal management, ecological forecasting, disaster management, and carbon management. In this experiment, MODIS data and VIIRS data simulated from MODIS were assessed for their ability to contribute broad, regional geospatial information on gypsy moth defoliation. Landsat and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data were used to assess the quality of gypsy moth defoliation mapping products derived from MODIS data and from simulated VIIRS data. The project focused on use of data from MODIS Terra as opposed to MODIS Aqua mainly because only MODIS Terra data was collected during 2000 and 2001-years with comparatively high amounts of gypsy moth defoliation within the study area. The project assessed the quality of VIIRS data simulation products. Hyperion data was employed to assess the quality of MODIS-based VIIRS simulation datasets using image correlation analysis techniques. The ART (Application Research Toolbox) software was used for data simulation. Correlation analysis between MODIS-simulated VIIRS data and Hyperion-simulated VIIRS data for red, NIR (near-infrared), and NDVI (Normalized Difference Vegetation Index) image data products collectively indicate that useful, effective VIIRS simulations can be produced using Hyperion and MODIS data sources. The r(exp 2) for red, NIR, and NDVI products were 0.56, 0.63, and 0.62, respectively, indicating a moderately high correlation between the 2 data sources. Temporal decorrelation from different data acquisition times and image misregistration may have lowered correlation results. The RPC experiment also generated MODIS-based time series data products using the TSPT (Time Series Product Tool) software. Time series of simulated VIIRS NDVI products were produced at approximately 400-meter resolution GSD (Ground Sampling Distance) at nadir for comparison to MODIS NDVI products at either 250- or 500-meter GSD. The project also computed MODIS (MOD02) NDMI (Normalized Difference Moisture Index) products at 500-meter GSD for comparison to NDVI-based products. For each year during 2000-2006, MODIS and VIIRS (simulated from MOD02) time series were computed during the peak gypsy moth defoliation time frame in the study area (approximately June 10 through July 27). Gypsy moth defoliation mapping products from simated VIIRS and MOD02 time series were produced using multiple methods, including image classification and change detection via image differencing. The latter enabled an automated defoliation detection product computed using percent change in maximum NDVI for a peak defoliation period during 2001 compared to maximum NDVI across the entire 2000-2006 time frame. Final gypsy moth defoliation mapping products were assessed for accuracy using randomly sampled locations found on available geospatial reference data (Landsat and ASTER data in conjunction with defoliation map data from the USFS). Extensive gypsy moth defoliation patches were evident on screen displays of multitemporal color composites derived from MODIS data and from simulated VIIRS vegetation index data. Such defoliation was particularly evident for 2001, although widespread denuded forests were also seen for 2000 and 2003. These visualizations were validated using aforementioned reference data. Defoliation patches were visible on displays of MODIS-based NDVI and NDMI data. The viewing of apparent defoliation patches on all of these products necessitated adoption of a specialized temporal data processing method (e.g., maximum NDVI during the peak defoliation time frame). The frequency of cloud cover necessitated this approach. Multitemporal simulated VIIRS and MODIS Terra data both produced effective general classifications of defoliated forest versus other land cover. For 2001, the MOD02-simulated VIIRS 400-meter NDVI classification produced a similar yet slightly lower overall accuracy (87.28 percent with 0.72 Kappa) than the MOD02 250-meter NDVI classification (88.44 percent with 0.75 Kappa). The MOD13 250-meter NDVI classification had a lower overall accuracy (79.13 percent) and a much lower Kappa (0.46). The report discusses accuracy assessment results in much more detail, comparing overall classification and individual class accuracy statistics for simulated VIIRS 400-meter NDVI, MOD02 250-meter NDVI, MOD02-500 meter NDVI, MOD13 250-meter NDVI, and MOD02 500-meter NDMI classifications. Automated defoliation detection products from simulated VIIRS and MOD02 data for 2001 also yielded similar, relatively high overall classification accuracy (85.55 percent for the VIIRS 400-meter NDVI versus 87.28 percent for the MOD02 250-meter NDVI). In contrast, the USFS aerial sketch map of gypsy moth defoliation showed a lower overall classification accuracy at 73.64 percent. The overall classification Kappa values were also similar for the VIIRS (approximately 0.67 Kappa) versus the MOD02 (approximately 0.72 Kappa) automated defoliation detection product, which were much higher than the values exhibited by the USFS sketch map product (overall Kappa of approximately 0.47). The report provides additional details on the accuracy of automated gypsy moth defoliation detection products compared with USFS sketch maps. The results suggest that VIIRS data can be effectively simulated from MODIS data and that VIIRS data will produce gypsy moth defoliation mapping products that are similar to MODIS-based products. The results of the RPC experiment indicate that VIIRS and MODIS data products have good potential for integration into the forest threat EWS. The accuracy assessment was performed only for 2001 because of time constraints and a relative scarcity of cloud-free Landsat and ASTER data for the peak defoliation period of the other years in the 2000-2006 time series. Additional work should be performed to assess the accuracy of gypsy moth defoliation detection products for additional years.The study area (mid-Appalachian highlands) and application (gypsy moth forest defoliation) are not necessarily representative of all forested regions and of all forest threat disturbance agents. Additional work should be performed on other inland and coastal regions as well as for other major forest threats.

Spruce, Joseph P.↗

A review of privacy in energy applications

As the distribution system continues to experience an increase in distributed energy resource (DER) and electric vehicle (EV) penetration, so does the need for new solutions that can help grid operators manage and leverage their capabilities. This will undoubtedly lead to new operational schemes and business opportunities that will transform the traditional consumer into a prosumer who will be more actively engaged in grid operations. Although the field is still under active development, many of the potential use cases presented in literature or industry are built upon edge computing, two-way communications, and other innovative computational constructs to attain their goals. However, at their core, many use cases assume a great level of data access to aid with the decision-making process, an assumption that may need to be revised to ensure fair and equitable operational processes are maintained. This may be particularly true as edge resources are predicted to participate in retail-side, many-to-many, or peer-to-peer markets and thus may lead to financial impacts if data access considerations are ignored. The need to revise data access mechanisms can be further justified by the introduction of new participants into the operational process, who do not have the same level of trust, nor the incentives to focus on energy delivery as their primary objective. At the same time, more consumers are becoming aware of their own data, and the potential impacts of its abuse. To help solution developers better understand these risks, this report has been developed to offer an initial introduction to the topic of privacy. This is achieved by 1) Highlighting the need for privacy-aware solutions; 2) Encouraging system designers to be inquisitive about the status quo; 3) Documenting the existing threat space; 4) Presenting and evaluating tools that may be helpful towards enabling better privacy postures; and 5) Making recommendations to encourage the adoption of better practices. From a technical perspective, the report focuses on evaluating two potential techniques by applying them to the Transactive Energy Space. Based on the obtained results, it can be established that differential privacy (DP) methods may have limited applicability when highly correlated, time-series data records need to be protected. However, DP may be a powerful tool when it is used to aggregate and analyze mid-size and large-size data sets in a more traditional statistical environment. The second tool under evaluation is threshold cryptography, which can guarantee complete secrecy (and thus privacy) but requires the establishment of key management procedures and dedicated communication channels for key coordination. Therefore, due to its increased computational overhead, the use of threshold cryptography must be weighted using a cost/benefit analysis on a per-application basis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Establishment of a reverse transcription real-time quantitative PCR method for Getah virus detection and its application for epidemiological investigation in Shandong, China

Getah virus (GETV) is a mosquito-borne, single-stranded, positive-sense RNA virus belonging to the genus Alphavirus of the family Togaviridae . Natural infections of GETV have been identified in a variety of vertebrate species, with pathogenicity mainly in swine, horses, bovines, and foxes. The increasing spectrum of infection and the characteristic causing abortions in pregnant animals pose a serious threat to public health and the livestock economy. Therefore, there is an urgent need to establish a method that can be used for epidemiological investigation in multiple animals. In this study, a real-time reverse transcription fluorescent quantitative PCR (RT-qPCR) method combined with plaque assay was established for GETV with specific primers designed for the highly conserved region of GETV Nsp1 gene. The results showed that after optimizing the condition of RT-qPCR reaction, the minimum detection limit of the assay established in this study was 7.73 PFU/mL, and there was a good linear relationship between viral load and Cq value with a correlation coefficient ( R 2 ) of 0.998. Moreover, the method has good specificity, sensitivity, and repeatability. The established RT-qPCR is 100-fold more sensitive than the conventional RT-PCR. The best cutoff value for the method was determined to be 37.59 by receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) was 0.956. Meanwhile, we collected 2,847 serum specimens from swine, horses, bovines, sheep, and 17,080 mosquito specimens in Shandong Province in 2022. The positive detection rates by RT-qPCR were 1%, 1%, 0.2%, 0%, and 3%, respectively. In conclusion, the method was used for epidemiological investigation, which has extensive application prospects.

Cao, Xinyu↗

Electronic Interactions Between the Receptor-Binding Domain of Omicron Variants and Angiotensin-Converting Enzyme 2: A Novel Amino Acid–Amino Acid Bond Pair Concept

SARS-CoV-2 remains a severe threat to worldwide public health, particularly as the virus continues to evolve and diversify into variants of concern (VOCs). Among these VOCs, Omicron variants exhibit unique phenotypic traits, such as immune evasion, transmissibility, and severity, due to numerous spike protein mutations and the rapid subvariant evolution. These Omicron subvariants have more than 15 mutations in the receptor-binding domain (RBD), a region of the SARS-CoV-2 spike protein that is important for recognition and binding with the angiotensin-converting enzyme 2 (ACE2) human receptor. To address the impact of these high numbers of Omicron mutations on the binding process, we have developed a novel method to precisely quantify amino acid interactions via the amino acid–amino acid bond pair (AABP). We applied this concept to investigate the interface interactions of the RBD–ACE2 complex in four Omicron Variants (BA.1, BA.2, BA.5, and XBB.1.16) with its Wild Type counterpart. Based on the AABP analysis, we have identified all the sites that are affected by mutation and have provided evidence that unmutated sites are also impacted by mutation. We have calculated that the binding between RBD and ACE2 is strongest in OV BA.1, followed by OV BA.2, WT, OV BA.5, and OV XBB.1.16. We also present the partial charge values for all 311 residues across these five models. Our analysis provides a detailed understanding of changes caused by mutation in each Omicron interface complex.

Biochemistry & Molecular Biology↗

Energy Master Planning: Identifying Framing Constraints that Scope Your Technology Options

This paper addresses the framing constraints for building and community energy projects that must be considered when energy master planning (EMP) is conducted. The constraints cover emissions, sustainability, resilience, regulations and directives, and regional and local limitations such as available energy types, local conditions, and project requirements. The paper reflects development results from participants in an International Energy Agency project on energy master planning and in a U.S. Department of Defense project on technology integration to achieve resilient, low-energy use military installations. It identifies a comprehensive list of framing constraints categorized into locational threats, locational resources, energy and water distribution and storage systems, building and facility, indoor environmental, and equipment in buildings and district systems constraints. In addition, it identifies limits for these constraints that exist in seven participating countries. Some framing constraints can profoundly impact technology selection while others impact the installation of technologies (as in hardening) and have little to no impact on technology selection. Furthermore, framing constraints can be assessed in different ways and there are resources available to help EMP stakeholders evaluate them. Finally, a case is made that identifying and applying framing constraints early in EMP can bring efficiencies and better focus to the EMP process. We come to the conclusion that (1) for holistic energy planning, it is essential to identify and assess the framing constraints that bound an optimized EMP solution, (2) framing constraints limits should be evaluated as either hard or soft or promising technologies may fall out of an EMP analysis, (3) to maintain consistent quality in the EMP process, the identification of framing constraints and their limits, and perhaps their evaluation, should be standardized, (4) a standardized approach could establish a baseline that can be used, built upon, and improved, (5) as automated EMP tools are improved or developed, the resources in this paper could possibly contribute to their interworkings relative to technology screening, and (6) continued climate change and resulting aggressive goal setting will likely drive a continued and strong emphasis on EMP.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Modeling Approach to Support Changeability Analysis and Management of Earth Observation Portfolios

Earth observing (EO) mission portfolios provide data on many geophysical parameters that collectively inform our understanding of the Earth system. To observe large-scale climate trends, it is important to collect data on many parameters over time. However, gaps may occur between missions due to formulation complexity, development delays, and uncertain events in operations. These gaps may impact the ability to provide sustained measurements. Developing a balanced EO mission portfolio is key to supporting study of the Earth system. Yet, decision-making at the portfolio level is a complex task because missions often address multiple parameters. Currently, the likelihood of data gaps is often assessed for an individual parameter, but decisions and events can impact data collection for many parameters. This poster introduces a modeling approach that supports management of the many parameter impacts of decisions and uncertain events. The approach provides a foundation for analyzing changeability in EO mission portfolios. Changeability analysis provides insight into a portfolio’s sensitivity to changes caused by decisions or uncertain events. The model is developed to analyze two aspects of changeability, robustness and flexibility, in EO mission portfolios. In context of these portfolios, the authors define robustness as a portfolio’s ability to provide sustained measurements despite future uncertainties, and they define flexibility as the availability of decision alternatives that contribute to parameter coverage at little detriment to the rest of the portfolio. The proposed model characterizes a portfolio’s sensitivity to change by capturing mission-parameter interconnectivity and redundancy in parameter coverage. The model can be analyzed to identify events that can create substantial gaps, thereby revealing focus areas for mitigation efforts. The model can also be analyzed to identify gap mitigation decisions that may improve parameter coverage with little detriment to the rest of the portfolio, thereby revealing favorable pathways for portfolio improvement. Developing a process for identifying these threats and opportunities will be the focus of future work. A parallel poster proposes a standard for visualizing and communicating portfolio-level impacts of decisions and uncertain events.

Lindsey Jacobson↗

Elevated Temperature Effects on Protein Turnover Dynamics in Arabidopsis thaliana Seedlings Revealed by 15 N-Stable Isotope Labeling and ProteinTurnover Algorithm

Global warming poses a threat to plant survival, impacting growth and agricultural yield. Protein turnover, a critical regulatory mechanism balancing protein synthesis and degradation, is crucial for the cellular response to environmental changes. We investigated the effects of elevated temperature on proteome dynamics in Arabidopsis thaliana seedlings using 15 N-stable isotope labeling and ultra-performance liquid chromatography-high resolution mass spectrometry, coupled with the ProteinTurnover algorithm. Analyzing different cellular fractions from plants grown under 22 °C and 30 °C growth conditions, we found significant changes in the turnover rates of 571 proteins, with a median 1.4-fold increase, indicating accelerated protein dynamics under thermal stress. Notably, soluble root fraction proteins exhibited smaller turnover changes, suggesting tissue-specific adaptations. Significant turnover alterations occurred with redox signaling, stress response, protein folding, secondary metabolism, and photorespiration, indicating complex responses enhancing plant thermal resilience. Conversely, proteins involved in carbohydrate metabolism and mitochondrial ATP synthesis showed minimal changes, highlighting their stability. This analysis highlights the intricate balance between proteome stability and adaptability, advancing our understanding of plant responses to heat stress and supporting the development of improved thermotolerant crops.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The MSP 2001 Mars Environmental Compatibility Assessment (MECA)

The Mars Environmental Compatibility Assessment (MECA) will evaluate the Martian environment for soil and dust-related hazards to human exploration as part of the Mars Surveyor Program 2001 Lander. Sponsored by the Human Exploration and Development of Space (HEDS) enterprise, MECA's goal is to evaluate potential geochemical and environmental hazards that may confront future Martian explorers, and to guide HEDS scientists in the development of high fidelity Mars soil simulants. The integrated MECA payload contains a wet-chemistry laboratory, a microscopy station, an electrometer to characterize the electrostatics of the soil and its environment, and arrays of material patches to study the abrasive and adhesive properties of soil grains. The instrument will acquire soil samples with a robotic arm equipped with a camera. MECA will examine surface and subsurface soil and dust in order to characterize particle size, shape, hardness, and also physical characteristics that may provide clues to mineralogy. MECA will characterize soil/water mixtures with respect to pH, redox potential, total dissolved ions, and trace toxins. MECA will determine the nature of electrostatic charging associated with excavation of soil, and the influence of ionizing radiation on material properties. It will also observe natural dust accumulation on engineering materials. To accomplish these objectives, MECA is allocated a mass of 10 kg within an enclosure of 35 x 25 x 15 cm. The Wet Chemistry Laboratory (WCL) consists of four identical cells that will accept samples from surface and subsurface regions accessible to the Lander's robotic arm, mix them with water, and perform extensive analysis of the solution. Ion-selective electrodes and related sensors will evaluate total dissolved solids, redox potential, pH, and the concentration of many soluble ions and gases in wet Martian soil. These electrodes can detect potentially dangerous heavy-metal ions, emitted pathogenic gases, and the soil's corrosive potential. Experiments will include cyclic voltammetry and anodic stripping voltammetry. Complementary to the Viking experiments, the chemical laboratory will characterize the water-soil solution rather than emitted gases. Nonetheless, through analysis of dissolved gases it will be able to replicate many of the Viking observations related to oxidants. MECA's microscopy station combines optical and atomic-force microscopy (AFM) in an actively focused, controlled illumination environment to image particles from millimeters to nanometers in size. Careful selection of substrates allows controlled experiments in adhesion, abrasion, hardness, aggregation, magnetic and other properties. Special tools allow primitive manipulation (brushing and scraping) of samples. Soil particle properties including size, shape, color, hardness, adhesive potential (electrostatic and magnetic), will be determined using an array of sample receptacles and collection substrates. The simple, rugged atomic-force microscope will image in the submicron size range and has the capability of performing a particle-by-particle analysis of the dust and soil. On Earth, the earliest forms of life are preserved as microfossils. The atomic-force microscope will have the required resolution to image down to the scale of terrestrial microfossils and beyond. Mounted on the end of the robot arm, MECA's electrometer actually consists of four types of sensors: an electric field meter, several triboelectricity monitors, an ion gauge, and a thermometer. Tempered only by ultraviolet-light-induced ions and a low-voltage breakdown threshold, the dry, cold, dusty martian environment presents an imposing electrostatic hazard to both robots and humans. The field meter will measure the ambient field on nearby objects while the triboelectric sensors, using identical circuitry, will measure the charge accumulated on test substances as they are dragged through the soil by the arm. The ion chamber, open to the environment, will sense both charged dust and free ions in the air. Over and above the potential threat to electronics, the electrostatic environment holds one of the keys to transport of dust and, consequently, Martian meteorology. Viewed with the robot arm camera, the abrasion and adhesion plates are strategically placed to allow direct observation of the interaction between materials and soils on a macroscopic scale. Materials of graded hardness are placed directly under the robot arm scoop to sense wear and soil hardness. A second array, placed on the lander deck, is deployed after the dust plume of landing has settled. It can be manipulated in a primitive fashion by the arm, first having dirt deposited on it from the scoop and subsequently shaken clean. A third array will passively collect dust from the atmosphere. In addition to objectives related to human exploration, the MECA data set will be rich in information relevant to basic geology, paleoclimate, and exobiology issues. To understand both contemporaneous and ancient processes on Mars, the mineralogy, petrology, and reactivity of Martian surface materials should be constrained. The MECA experiment will shed light on these quantities through its combination of chemistry and microscopy. MECA will be capable of measuring the composition of ancient surface water environments, observing microscopic evidence of geological (and biological?) processes, inferring soil and dust transport, comminution and weathering mechanisms, and characterizing soil horizons that might be encountered during excavation.

Hecht, M. H.↗

Automated fault-management in a simulated spaceflight micro-world

BACKGROUND: As human spaceflight missions extend in duration and distance from Earth, a self-sufficient crew will bear far greater onboard responsibility and authority for mission success. This will increase the need for automated fault management (FM). Human factors issues in the use of such systems include maintenance of cognitive skill, situational awareness (SA), trust in automation, and workload. This study examine the human performance consequences of operator use of intelligent FM support in interaction with an autonomous, space-related, atmospheric control system. METHODS: An expert system representing a model-base reasoning agent supported operators at a low level of automation (LOA) by a computerized fault finding guide, at a medium LOA by an automated diagnosis and recovery advisory, and at a high LOA by automate diagnosis and recovery implementation, subject to operator approval or veto. Ten percent of the experimental trials involved complete failure of FM support. RESULTS: Benefits of automation were reflected in more accurate diagnoses, shorter fault identification time, and reduced subjective operator workload. Unexpectedly, fault identification times deteriorated more at the medium than at the high LOA during automation failure. Analyses of information sampling behavior showed that offloading operators from recovery implementation during reliable automation enabled operators at high LOA to engage in fault assessment activities CONCLUSIONS: The potential threat to SA imposed by high-level automation, in which decision advisories are automatically generated, need not inevitably be counteracted by choosing a lower LOA. Instead, freeing operator cognitive resources by automatic implementation of recover plans at a higher LOA can promote better fault comprehension, so long as the automation interface is designed to support efficient information sampling.

NASA Discipline Space Human Factors↗

Efficacy of Dried Plum to Countermeasure Simulated Spaceflight Exposure

Human exploration of the space environment has been a topic of interest for decades; however, the threat to physiological health posed by ionizing radiation and microgravity effects remains a concern. Previous research utilizing combined hindlimb unloading and irradiation to simulate spaceflight effects found that a dried plum diet can mitigate adverse effects of simulated spaceflight on skeletal health. Though the mechanism is not fully understood we believe this protective effect is due to its high antioxidant capacity and polyphenolic content. This study seeks to extend these findings to investigate if dried plum is an effective countermeasure in other tissues relating to aging and neurotoxicity. Male C57BL/6 J mice were assigned to one of eight groups (n = 10/group) and were fed either a controlled diet or dried plum diet, underwent normal loading or hindlimb unloading as well as exposure 2 Gy gamma radiation or sham exposure. At the end of the experiment, mice were euthanized, and RNA was extracted from brain and bone marrow tissue and PCR was employed to analyze significant changes in gene expression profiles. Analysis of five house-keeping genes revealed genes B2M (neurotoxicity) and GUSB (aging) to be the most stable genes across all treatments and were used to find the fold change within our genes of interest. Through this, and analysis via ANOVA, we were able to identify genes with significant altered expression levels within brain and bone marrow tissues related to neurotoxicity and aging. Considering previous research, we hypothesize that the dried plum diet’s antioxidative properties ameliorated the oxidative stress from irradiation and microgravity via altered levels of gene expression. Identified expression changes will provide insights into molecular mechanisms behind the observed protective effects. These findings present potential avenues for future interventions to alleviate negative impacts of spaceflight on astronaut health.

Faisal Ahmad↗

The Efficacy of Dried Plum to Counter Spaceflight Microgravity and Radiation

Human exploration of the space environment has been a topic of interest for decades; however, the threat to physiological health posed by ionizing radiation and microgravity effects remains a concern. Previous research utilizing combined hindlimb unloading and irradiation to simulate spaceflight effects found that a dried plum diet can mitigate adverse effects of simulated spaceflight on skeletal health. Though the mechanism is not fully understood we believe this protective effect is due to its high antioxidant capacity and polyphenolic content. This study seeks to extend these findings to investigate if dried plum is an effective countermeasure in other tissues relating to aging and neurotoxicity. Male C57BL/6 J mice were assigned to one of eight groups (n = 10/group) and were fed either a controlled diet or dried plum diet, underwent normal loading or hindlimb unloading as well as exposure 2 Gy gamma radiation or sham exposure. At the end of the experiment, mice were euthanized, and RNA was extracted from brain and bone marrow tissue and PCR was employed to analyze significant changes in gene expression profiles. Analysis of five house-keeping genes revealed genes B2M (neurotoxicity) and GUSB (aging) to be the most stable genes across all treatments and were used to find the fold change within our genes of interest. Through this, and analysis via ANOVA, we were able to identify genes with significant altered expression levels within brain and bone marrow tissues related to neurotoxicity and aging. Considering previous research, we hypothesize that the dried plum diet’s antioxidative properties ameliorated the oxidative stress from irradiation and microgravity via altered levels of gene expression. Identified expression changes will provide insights into molecular mechanisms behind the observed protective effects. These findings present potential avenues for future interventions to alleviate negative impacts of spaceflight on astronaut health.

Faisal Ahmad↗