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Cooperative Research and Development Agreement With Georgetown University Report: National Institutes of Health, National Center for Advancing Translational Sciences Clinical and Translational Science Award

Oak Ridge National Laboratory (ORNL) is participating with Georgetown University (GU) as a subrecipient in response to the National Institutes of Health (NIH), National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Award (CTSA) (U54 Clinical Trial Optional) funding opportunity announcement. This Cooperative Research and Development Agreement is put in to place to facilitate the development and implementation of clinical interventions that demonstrably improve human health is currently a complex, recursive, and inefficient process that leads to delays of years or decades before discoveries in biomedical research result in health benefits for patients and communities. NCATS conducts and supports research in the science of translation, to discover the mechanistic and operational principles of the intervention development and dissemination process, thereby providing the scientific foundation for improvements in translational efficiency that will accelerate the realization of interventions that improve human health. Under NCATS’ leadership, the CTSA Program supports a national network of medical research institutions called hubs. GU is the lead institution in one of the NIH hubs that was created as a result of a previous NIH CTSA. The missions of the GU have historically included the advancement of health through research in the clinical and biomedical sciences, the education of future leaders in medical and nursing practice and academia, and the provision of compassionate and scientifically competent patient care and service to the Washington, DC community and the nation. GU is the lead institution for the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS), a multi-institutional partnership of medical research institutions forged from a desire to promote clinical research and translational science. Through multiple collaborations among these institutions, GHUCCTS is transforming clinical research and translational science in order to bring new scientific advances to health care. Oak Ridge National Laboratory is the Department of Energy's (DOE) largest science and energy laboratory. Managed since April 2000 by a partnership of the University of Tennessee and Battelle, ORNL was established in 1943 as a part of the secret Manhattan Project to pioneer a method for producing and separating plutonium. During the 1950s and 1960s, ORNL became an international center for the study of nuclear energy and related research in the physical and life sciences. With the creation of DOE in the 1970s, ORNL's mission broadened to include a variety of energy technologies and strategies. Today the laboratory supports the nation with a peacetime science and technology mission that is just as important as, but very different from, its role during the Manhattan Project. ORNL is home to the world's premier center for high performance supercomputing to enable scientific discovery. ORNL has extensive expertise in various areas of computer science that are uniquely situated to support GU. Additionally, ORNL’s leading computational user facilities present a unique opportunity to leverage the largest scale machines for open science in support of the stated mission of the NCATS CTSA. ORNL's partnership with GU will offer unparalleled opportunity in data analytics, deep-learning, artificial intelligence, and urban dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Orthologs of human circulating miRNAs associated with hepatocellular carcinoma are elevated in mouse plasma months before tumour detection

Research examining the potential for circulating miRNA to serve as markers for preneoplastic lesions or early-stage hepatocellular carcinoma (HCC) is hindered by the difficulties of obtaining samples from asymptomatic individuals. As a surrogate for human samples, we identified hub miRNAs in gene co-expression networks using HCC-bearing C3H mice. We confirmed 38 hub miRNAs as associated with HCC in F2 hybrid mice derived from radiogenic HCC susceptible and resistant founders. When compared to a panel of 12 circulating miRNAs associated with human HCC, two had no mouse ortholog and 7 of the remaining 10 miRNAs overlapped with the 38 mouse HCC hub miRNAs. Using small RNA sequencing data generated from serially collected plasma samples in F2 mice, we examined the temporal levels of these 7 circulating miRNAs and found that the levels of 4 human circulating markers, miR-122-5p, miR-100-5p, miR-34a-5p and miR-365-3p increased linearly as the time approaching HCC detection neared, suggesting a correlation of miRNA levels with oncogenic progression. Estimation of change points in the kinetics of the 4 circulating miRNAs suggested the changes started 17.5 to 6.8 months prior to HCC detection. These data establish these 4 circulating miRNAs as potential sentinels for preneoplastic lesions or early-stage HCC.

60 APPLIED LIFE SCIENCES↗

Mapping the immunogenic landscape of near-native HIV-1 envelope trimers in non-human primates

The induction of broad and potent immunity by vaccines is the key focus of research efforts aimed at protecting against HIV-1 infection. Soluble native-like HIV-1 envelope glycoproteins have shown promise as vaccine candidates as they can induce potent autologous neutralizing responses in rabbits and non-human primates. In this study, monoclonal antibodies were isolated and characterized from rhesus macaques immunized with the BG505 SOSIP.664 trimer to better understand vaccine-induced antibody responses. Our studies reveal a diverse landscape of antibodies recognizing immunodominant strain-specific epitopes and non-neutralizing neo-epitopes. Additionally, we isolated a subset of mAbs against an epitope cluster at the gp120-gp41 interface that recognize the highly conserved fusion peptide and the glycan at position 88 and have characteristics akin to several human-derived broadly neutralizing antibodies.

59 BASIC BIOLOGICAL SCIENCES↗

GCAM v4.3 SSP-RCP-GCM Output Products

Supplemental dataset to: Graham N.T., M.I. Hejazi, M. Chen, E. Davies, J.A. Edmonds, S.H. Kim, and S. Turner, et al. 2020. "Humans drive future water scarcity changes across all Shared Socioeconomic Pathways." Environmental Research Letters 15, no. 1:Article No. 014007. PNNL-SA-151297. doi:10.1088/1748-9326/ab639b This analysis makes deterministic classifications of how, when water resources are limited and constrained, the human and climate systems interact. The relative effects of both systems on water scarcity are quantified at global and basin scales across 15 global futures that include five different socioeconomic conditions (the Shared Socioeconomic Pathways, SSPs) and four different climatic conditions (the Representative Concentration Pathways, RCPs). These 15 scenarios are used to first analyze a 'Human Alone' component by isolating the human impact on future scarcity. This is accomplished by holding all climate variables to their 2005 levels while altering socioeconomic growth and technological change. General circulation model (GCM) derived climate impacts for five models are applied to establish 75 'Human and Climate' scenarios which allows for the quantification of climate impacts. Climatic impacts to water supply, agricultural productivity and change, hydropower availability, and building energy demands are applied from 5 different bias-corrected GCMs to make a suite of 75 climate runs. By subtracting the human derived impacts from the 'Human Alone' scenarios, from the 'Human and Climate' scenarios the climate impact is isolated. First, the drivers of future water scarcity are evaluated by isolating the impacts that both humans and climate have while accounting for feedbacks between humans, energy, and land. Secondly, the simultaneous impacts that human and climate systems have on water scarcity are analyzed by determining whether each system is increasing or decreasing scarcity in all global water basins. Below we describe the GCAM model, the scenario components, climate derived impacts, and the calculations of scarcity changes and attribution. This study uses the global change assessment model (GCAM), with inclusions of water constraints to both renewable and nonrenewable sources of water, to investigate the relative contributions of climate and human systems on water scarcity regionally and globally under a wide range of scenarios. GCAM links socioeconomics, the energy system, land-use change, climate, and the water sector. GCAM is a market-equilibrium model that allows for prices to be adjusted within each time step to ensure that the supply and demand of goods and services remains equilibrated at each time step allowing for simultaneous market clearing across sectors. This study accounts for a limited supply of water by employing cost resource curves across all 235 basins that follow a logit formulation to determine the share of each water source (renewable surface water, nonrenewable groundwater, and desalinated water) needed to meet the water demands within all basins. As depletion of various water sources increases the extraction price increases, which leads to compounding price increases on the goods and services that require higher-priced water sources.

99 GENERAL AND MISCELLANEOUS↗

Crowd cluster data in the USA for analysis of human response to COVID-19 events and policies

We provide data on daily social contact intensity of clusters of people at different types of Points of Interest (POI) by zip code in Florida and California. This data is obtained by aggregating fine-scaled details of interactions of people at the spatial resolution of 10 m, which is then normalized as a social contact index. We also provide the distribution of cluster sizes and average time spent in a cluster by POI type. This data will help researchers perform fine-scaled, privacy-preserving analysis of human interaction patterns to understand the drivers of the COVID-19 epidemic spread and mitigation. Current mobility datasets either provide coarse-level metrics of social distancing, such as radius of gyration at the county or province level, or traffic at a finer scale, neither of which is a direct measure of contacts between people. We use anonymized, de-identified, and privacy-enhanced location-based services (LBS) data from opted-in cell phone apps, suitably reweighted to correct for geographic heterogeneities, and identify clusters of people at non-sensitive public areas to estimate fine-scaled contacts.

60 APPLIED LIFE SCIENCES↗

Conventional and Next Generation Treatment Technologies for PFAS - 20067

In 2016, the United States Environmental Protection Agency (USEPA) established a Health Advisory Limit (HAL) for perfluorooctanoic acid (PFOA) and perfluorooctane sulfonic acid (PFOS) (individually and the summation) of 70 nanograms per liter (ng/L) based on developing toxicological information. These two compounds are among several thousand per- and polyfluoroalkyl substances (PFAS). Due to a multitude of commercially beneficial physical and chemical properties, the availability of PFAS-relevant and practical water treatment technologies is limited. The use of conventional adsorbents, such as activated carbon (AC) and anion exchange (AIX) resins, have become a 'de facto' interim measure to immediately address drinking water above this criterion. However, these adsorbents can have marginal long-term efficiency and are relatively unproven against the diversity of polyfluorinated compounds. Additionally, geochemical and/or co-contaminant competition can significantly impede adsorption based PFAS removal. These challenges may be addressed using engineered filtration, such as reverse osmosis or nanofiltration (RO/NF); however, for larger flow systems RO/NF may have unacceptable reject ratios as high as 35% and the capital cost may preclude these technologies. Extending these technologies to natural waters, which have various degrees of geochemical and co-contaminant competition, often requires a treatment train, combining conventional adsorbents or engineered filtration with pretreatment and more innovative and emerging remediation solutions for PFAS. Conventional and Next Generation water treatment technologies for PFAS generally employ one of three mechanisms (adsorption, separation, or destruction). These mechanisms include many types of technologies for both municipal drinking water and extracted natural water applications. The previously mentioned AC, AIX, and RO/NF are commercially available technologies that are actively being deployed for PFAS treatment. Research and development around these technologies is focused on optimization, and ultimate destruction of PFAS is achieved through incineration. Next Generation water treatment technologies include PFAS-specific flocculants, foam fractionation, novel AIX resins, new engineered adsorptive media, electrochemical treatment, sonolysis, and photolysis, radiation, and plasma (forms of advanced reductive processes [ARP]). Research and development around these technologies is focused on proof of concept and assimilation to real world applications. As the PFAS-relevant destructive technologies (such as incineration, electrochemical treatment, sonolysis, and ARP) are energy intensive, the state of the practice for PFAS water treatment is to focus adsorption/separation based technologies on reducing and concentrating the volume of water requiring destructive treatment. This enables more flexibility with respect to circulation frequency, residence time, and more control over energy usage. Water treatment for PFAS presently requires multiple technologies (i.e. a treatment train) to protect human health in a cost-conscious manner. An investment in research and development to explore new technologies is part of a key initiative for efficient protection of human health. This presentation attempts to review PFAS-relevant water treatment technologies and provide perspective as to their status with respect to applicability and commercial relevance. (authors)

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Cities Are Concentrators of Complex, MultiSectoral Interactions Within the Human-Earth System

Cities are concentrators of complex, multi-sectoral interactions. As keystones in the interconnected human-Earth system, cities have an outsized impact on the Earth system. We describe a multi-lens framework for organizing our understanding of the complexity of urban systems and scientific research on urban systems, which may be useful for natural system scientists exploring the ways their work can be made more actionable. We then describe four critical dimensions along which improvements are needed to advance the urban research that addresses urgent climate challenges: (a) solutions-oriented research, (b) equity-centered assessments which rely on fine-scale human and ecological data, (c) co-production of knowledge, and (d) better integration of human and natural systems occurring through theory, observation, and modeling.

54 ENVIRONMENTAL SCIENCES↗

Large Language Models (LLMs) for Energy Systems Research

The integration of Large Language Models (LLMs) in energy systems research promises transformative results, as demonstrated in this work, particularly in the realms of information retrieval and legal document analysis. We have developed a chat-based interface, specifically designed to query an extensive corpus of technical reports from the National Renewable Energy Laboratory (NREL). This interface capitalizes on the natural language processing capabilities of LLMs, providing future consumers of NREL research with a user-friendly platform to access and extract valuable information from technical documents, thus enhancing the dissemination of research to the public. In addition to information retrieval, we have employed LLMs to extract renewable energy siting ordinances from a variety of legal documents, a task traditionally driven by significant human labor. This automated extraction not only supports the ongoing development of the high-impact NREL siting ordinance database but also ensures the database's accuracy and comprehensiveness. Crucially, we have augmented the performance of LLMs through the integration of a decision tree framework, resulting in a substantial improvement in extraction accuracy. Comparative analysis with manual efforts has shown that this approach not only rivals but also significantly surpasses human accuracy, heralding increased reliability in legal document analysis for energy systems research. To democratize access to these advancements and foster collaborative research, we introduce the "Energy Language Model" (ELM), an open-source software package. ELM encapsulates the methodologies and tools developed in this work, providing researchers and practitioners with a robust toolkit to conduct similar analyses within their respective domains. Through these contributions, this work underscores the immense potential of LLMs in revolutionizing energy systems research, improving accuracy, efficiency, and accessibility in the field.

automation↗

Transformative Impacts of Laser-Induced Breakdown Spectroscopy on Environmental and Biological Research at Oak Ridge National Laboratory

This manuscript will present an advancement of transformative research that has been conducted at Oak Ridge National Laboratory (ORNL) over a 25-year period (2000–2025) on a variety of environmental and biological matrices. These investigations derived a fundamental understanding of how elemental detection and analysis of these matrices led to the knowledge and discovery of natural processes in plants and the environment. Each project led to the initiation of a new research area which unearthed awesome and novel breakthroughs. Highlights are listed below: 1. The preliminary research at ORNL centered on the detection of aerosols utilizing Laser-induced Breakdown Spectroscopy (LIBS) technology. The Clean Air Act Amendment (CAAA) of 1990 highlighted the importance of identifying hazardous air pollutants (HAPs) due to their impact on environmental and human health, thereby underscoring the need to detect various toxic elements. Research in aerosol chemistry aimed to identify these harmful elements released by factories during periods of increased emissions in their manufacturing processes. LIBS emerged as the most effective method for real-time, in situ measurements of metal species in both gaseous and aerosol phases. 2. An understanding of the presence of total carbon in soils gives perspective on how to develop carbon sequestration strategies. The recognition that carbon sinks can evolve back to carbon sources to emit back to the atmosphere was an important consideration. Also, the concentration of carbon in soil indicates the health of land areas for growing crops successfully. 3. The direct detection of most of the elements in a wood sample in a single emission spectrum, without sample preparation, encouraged the research to use the LIBS technique for preservative treated wood coupled with use of multivariate statistical methodology. Additionally, it encouraged the researchers to try to differentiate natural woods from different parts of the country, and it was successfully demonstrated that LIBS coupled with MVA analysis could differentiate wood of different species from each other and of similar species grown in different environments based on their elemental spectra. This was a breakthrough since it revealed a systematic approach to connect elemental scarcity and abundance to either drought or typical rainfall conditions for the hardwood trees grown in specific areas. 4. Furthermore, the research progressed to reveal physiological and developmental processes contributing to biomass production such that the variation in leaf elemental composition increases our understanding of terrestrial nutrient cycles, as well as tracking the transfer of toxic elements from soils to living organisms. 5. Recently another breakthrough viz., ionomics initiated the correlation of elements to specific genes, uncovering the function that the element performed in the plant. More recently, this has been extended from plants to fungi as well as fungi growing in symbiotic relations with plants.

09 BIOMASS FUELS↗

Human Dimensions of Energy Systems Workshop - September 6-7, 2022: Findings and Next Steps

Advanced energy technologies and informed policies are necessary but not sufficient to accelerate the energy transition at the speed required to meet our shared climate and energy resilience goals. To fully understand and implement integrated energy systems, we need to be able to model and analyze the complete system-of-systems, including the behavior of people interacting with and being impacted by energy systems. The purpose of this workshop is: Understand how human behavior and decisions affect the performance of energy systems with a focus on resilience and human well-being; Identify opportunities to improve energy system design to explicitly consider human behavior and well-being; Enhance our capability to model and predict human actions. Develop the ability to stress test these integrated systems; Identify or develop requirements and tools for more robust system designs that can be used for human-in-the-loop exercises and training; Identify opportunities for joint research, joint appointments, and collaboration; and Guide internal investments and strategic hires.

analyze↗

A perspective on iron (Fe) in the atmosphere: air quality, climate, and the ocean

As scientists engage in research motivated by climate change and the impacts of pollution on air, water, and human health, we increasingly recognize the need for the scientific community to improve communication and knowledge exchange across disciplines to address pressing and outstanding research questions holistically. Our professional paths have crossed because our research activities focus on the chemical reactivity of Fe-containing minerals in air and water, and at the air-sea interface. (Photo)chemical reactions driven by Fe can take place at the surface of the particles/droplets or within the condensed phase. The extent and rates of these reactions are influenced by water content and biogeochemical activity ubiquitous in these systems. One of these reactions is the production of reactive oxygen species (ROS) that cause damage to respiratory organs. Another is that the reactivity of Fe and organics in aerosol particles alter surficial physicochemical properties that impact aerosol-radiation and aerosol–cloud interactions. Also, upon deposition, aerosol particles influence ocean biogeochemical processes because micronutrients such as Fe or toxic elements such as copper become bioavailable. We provide a perspective on these topics and future research directions on the reactivity of Fe in atmospheric aerosol systems, from sources to short- and long-term impacts at the sinks with emphasis on needs to enhance the predictive power of atmospheric and ocean models.

54 ENVIRONMENTAL SCIENCES↗

U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗

Vertebrate and invertebrate competition for carrion in human‐impacted environments depends on abiotic factors

Abstract Human altered landscapes have caused declines in the diversity of wildlife where behaviorally plastic species (i.e., mesocarnivores and invasive species) tend to monopolize these areas and consume predictable and readily accessible food resources, such as human food waste and carrion. Increased consumption of carrion by vertebrates and invasive invertebrate species can alter population dynamics of native necrophagous insects relying on these resources. We tested the hypothesis that vertebrate scavengers and invasive species reduce blow fly (1) ability to use carrion and (2) reproduction in human‐impacted environments in central Texas, USA, with season, habitat (field and wooded landscapes), and carrion type (species of carrion and coat color) acting synergistically. Vertebrate scavengers in this habitat, of which 75% of the documented species were mesocarnivores and obligate scavengers, consumed 100% of carrion during the winter and 62% during summer despite having low species richness (2–5 species). Of the remaining carcasses available for arthropod activity during summer, the invasive red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), monopolized 34%, and blow flies (e.g., Lucilia eximia and Chrysomya rufifacies [Diptera: Calliphoridae]) were only able to colonize 25%. Approximately 90% of carrion that was utilized by blow flies was co‐colonized by fire ants, and subsequent production of adult blow flies experienced up to a ninefold reduction in production compared with carcasses that were not scavenged by vertebrates or fire ants. Our results demonstrate oviposition resources used by blow flies in environments altered by human activity are reduced significantly by vertebrate scavengers and an invasive ant species. Future research should determine whether competitive interactions between vertebrate and invasive ant competitors for access to carrion resources have population‐level impacts to blow flies in human‐mediated ecosystems, or whether blow flies are able to shift to other resources to maintain sustainable populations and continue providing ecosystem services, such as pollination.

54 ENVIRONMENTAL SCIENCES↗

Extending Imaging Volume in Soft X‐Ray Tomography

Soft X‐ray tomography offers rapid imaging of whole, single cells with a few tens of nanometers spatial resolution without fixation or labeling. Herein, this technique is limited to specimens about 10 μm thick, such that applications of soft X‐ray tomography of large human cells or multicellular specimens are not possible. A theoretical and experimental framework for soft X‐ray tomography that enables extension of imaging volumes to 18 μm‐thick specimens is developed. This approach, based on long depth of field and half‐acquisition tomography, is easily applicable to microscopes equipped with a full‐rotation specimen stage. This opens opportunities for imaging large human cells, such as those commonly seen in cancer research, as well as cell‐to‐cell interactions, where two or more cells occupy the same imaging volume.

Ekman, Axel↗

Enzymatic Laser-Induced Graphene Biosensor for Electrochemical Sensing of the Herbicide Glyphosate

Glyphosate is a globally applied herbicide yet it has been relatively undetectable in-field samples outside of gold-standard techniques. Its presumed nontoxicity toward humans has been contested by the International Agency for Research on Cancer, while it has been detected in farmers’ urine, surface waters and crop residues. Rapid, on-site detection of glyphosate is hindered by lack of field-deployable and easy-to-use sensors that circumvent sample transportation to limited laboratories that possess the equipment needed for detection. Herein, the flavoenzyme, glycine oxidase, immobilized on platinum-decorated laser-induced graphene (LIG) is used for selective detection of glyphosate as it is a substrate for GlyOx. The LIG platform provides a scaffold for enzyme attachment while maintaining the electronic and surface properties of graphene. The sensor exhibits a linear range of 10–260 µm, detection limit of 3.03 µm, and sensitivity of 0.991 nA µm -1 . The sensor shows minimal interference from the commonly used herbicides and insecticides: atrazine, 2,4-dichlorophenoxyacetic acid, dicamba, parathion-methyl, paraoxon-methyl, malathion, chlorpyrifos, thiamethoxam, clothianidin, and imidacloprid. Sensor function is further tested in complex river water and crop residue fluids, which validate this platform as a scalable, direct-write, and selective method of glyphosate detection for herbicide mapping and food analysis.

47 OTHER INSTRUMENTATION↗

Plant Summit 2019

The Plant Science Research Network organized the Plant Summit 2019, which took place February 10-13, 2019 at Biosphere 2 (Oracle, AZ). The Summit brought together plant scientists from many quarters, including stakeholders from academic institutions, government, nonprofits, and private industry with a broad range of experience in plant science research and education. Participants were guided through a facilitated workshop to review and assess the outcomes from previous PSRN workshops on cyberinfrastructure, postgraduate training, broadening participation, and future scenarios. An outcome of the Summit is the development of a report, “The Plant Science Decadal Vision (2020-2030): Reimagining the Potential of Plants for a Healthy Future.” The Decadal Vision frames societally vital, exciting and far-reaching research challenges as being necessary and deeply interwoven with human and technical resources. An Executive Summary of that report is provided.

59 BASIC BIOLOGICAL SCIENCES↗

Physiological Characterization of Language Comprehension

In this project, our goal was to develop methods that would allow us to make accurate predictions about individual differences in human cognition. Understanding such differences is important for maximizing human and human-system performance. There is a large body of research on individual differences in the academic literature. Unfortunately, it is often difficult to connect this literature to applied problems, where we must predict how specific people will perform or process information. In an effort to bridge this gap, we set out to answer the question: can we train a model to make predictions about which people understand which languages? We chose language processing as our domain of interest because of the well- characterized differences in neural processing that occur when people are presented with linguistic stimuli that they do or do not understand. Although our original plan to conduct several electroencephalography (EEG) studies was disrupted by the COVID-19 pandemic, we were able to collect data from one EEG study and a series of behavioral experiments in which data were collected online. The results of this project indicate that machine learning tools can make reasonably accurate predictions about an individual?s proficiency in different languages, using EEG data or behavioral data alone.

42 ENGINEERING↗

Instantiation of HCML Demonstrating Bayesian Predictive Modeling for Attentional Control

The research team developed models of Attentional Control (AC) that are unique to existing modeling approaches in the literature. The goal was to enable the research team to (1) make predictions about AC and human performance in real-world scenarios and (2) to make predictions about individual characteristics based on human data. First, the team developed a proof-of-concept approach for representing an experimental design and human subjects data in a Bayesian model, then demonstrated an ability to draw inferences about conditions of interest relevant to real-world scenarios. Ultimately, this effort was successful, and we were able to make reasonable (meaning supported by behavioral data) inferences about conditions of interest to develop a risk model for AC (where risk is defined as a mismatch between AC and attentional demand). The team additionally defined a path forward for a human-constrained machine learning (HCML) approach to make predictions about an individual's state based on performance data. The effort represents a successful first step in both modeling efforts and serves as a basis for future work activities. Numerous opportunities for future work have been defined.

97 MATHEMATICS AND COMPUTING↗