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At least 613 records · Page 34

Applications of GIS and remote sensing in public participation and stakeholder engagement for watershed management

The use of Geographic Information Systems (GIS) and remote sensing technologies for the development of water quality management programs and for post-implementation assessments has increased dramatically in the past decade. This increase in adoption has been made more accessible through the interfaces of many popular software tools used in the regulation and assessment of water quality. Customized applications of these tools will increase, as ease of access and affordability of directly monitored and remotely sensed datasets improve over time. Concurrently, there is a need for inclusive participatory engagement with stakeholders to achieve solutions to current watershed management challenges. This paper explores the potential of these GIS and remote sensing datasets, tools, models, and immersive engagement technologies from other domains, for improving public participation and stakeholder engagement throughout the watershed planning process. To do so, an initial review is presented about the use of GIS and remote sensing in watershed management and its role in impairment identification, model development, and planning and implementation. Then, ways in which GIS and remote sensing can be integrated with stakeholder engagement through (1) leveraging GIS and remote sensing datasets, and (2) stakeholder engagement approaches including outreach and education, modeler-led development, and stakeholder-led involvement and feedback, are discussed. Finally, future perspectives on the potential for transforming public participation and stakeholder engagement in the watershed management process through applications of GIS and remote sensing are presented.

54 ENVIRONMENTAL SCIENCES↗

2020 ETI Annual Summer School: Data Science and Engineering

The Consortium for Enabling Technologies & Innovation (ETI) was established in 2019 to address emerging technologies within the context of nuclear nonproliferation. ETI creates a research and education environment to support cross-cutting technologies across three core disciplines: 1) computer and engineering science research specifically in a form of machine learning and high performance computing (HPC), 2) advanced manufacturing, and 3) nuclear detection technologies. For outreach and development, ETI hosted the first of three summer schools from August 24-28, 2020 with the theme of “Data Science and Engineering”. The school was hosted in an on-line format and had over 200 participants. The recorded content is available on-line as a resource for students. The summer school had four modules: 1) Fundamentals of data Applications, 2) Computational Machine Learning, 3) Bayesian Modeling and Inference, and 4) Data Science for Safeguards. Modules contained both lectures as well as student exercises. Poll Everywhere was utilized in some modules as an on-line method to engage large groups of students. Upcoming ETI Summer Schools include Novel Instrumentation in 2021 and Advanced Manufacturing in 2022.

Biegalski, Steven R.↗

Foundation Models of Scientific Knowledge for Chemistry: Opportunities, Challenges and Lessons Learned

Foundation models pre-trained on large corpora demonstrate significant gains across many natural language processing tasks and domains e.g., law, healthcare, education, etc. However, only limited efforts have investigated the opportunities and limitations of applying these powerful models to science and security applications. In this work we develop foundation models of scientific knowledge for chemistry to augment scientists with the advanced ability to perceive and reason at scale previously unimagined. Specifically, we build large-scale (1.47B parameter) general-purpose models for chemistry that can be effectively used to perform a wide range of in-domain and out-of-domain tasks. Evaluating these models in a zero-shot setting, we analyze the effect of model and data scaling, knowledge depth, and temporality on model performance in context of model training efficiency. Our novel findings demonstrate that (1) model size significantly contributes to the task performance when evaluated in a zero-shot setting; (2) data quality (aka diversity) affects model performance more than data quantity; (3) similarly, unlike previous work (Luu et al., 2021) temporal order of the documents in the corpus boosts model performance only for specific tasks, e.g., SciQ; and (4) models pre-trained from scratch perform better on in-domain tasks than those tuned from general-purpose models like Open AI’s GPT-2.

Foundation Models, Chemistry↗

BOPTest As a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

Improving radiograph analysis throughput through transfer learning and object detection

SIGN Fracture Care International partners with surgeons in low-resource hospitals worldwide to provide access to effective orthopedic care by donating educational materials and innovatively designed surgical implants. Over two decades, SIGN’s Online Surgical Database (SOSD) has grown to contain over 500,000 medical images, with radiographs holding the majority share. One challenge in working with hospitals worldwide is that both the radiographs uploaded to the SOSD and the data entry accompanying the uploads vary in quality. To improve the accuracy of data in the SOSD, we trained a model to detect surgical implants in radiographs. We first developed a tool to automatically detect radiographs, then trained an object detection model to determine the number and placement of surgical implants visible in the radiograph. Active learning was used to generate a training set containing 2,510 radiographs with screws, nails, and plates labeled by bounding boxes. Training a model to simultaneously recognize all three classes of implants gave a low average precision (AP) for the plate class, likely due to the low number of plate instances in our training set and the large variety of surgical plates used by SIGN-partnered surgeons. Applying standard image augmentation techniques to increase the plate count in our training set did not appreciably increase the AP of plate detection. To improve plate detection, we redrew the bounding boxes to account for correlations between the screw and plate classes. Training one model to detect nails and screws and a separate model to detect plates increased the AP of plate detection by 78.8 percentage points. The AP of each class was 80.7% for screws, 93.6% for nails, and 92.6% for plates; meanwhile, the sensitivity was 92% for screws, 86% for nails, and 81% for plates. We show that object detection methods can be used to detect surgical implants in radiographs of varying quality; however, the detection ability is dependent on the type of implant, and some implants, in our case plates, must be treated differently than others. Such tools can improve the throughput of radiograph analysis, assisting physicians and surgeons with the treatment of bone fractures.

60 APPLIED LIFE SCIENCES↗

spopt: a python package for solving spatial optimization problems in PySAL

Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated. Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others. To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions (Feng et al., 2021). Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr. Sergio J. Rey and Dr. Luc Anselin in 2005 (Rey et al., 2015, 2021; Rey & Anselin, 2007). The goal of developing spopt is to provide management and decision-making support to all relevant practitioners and to further promote the appropriate and meaningful application of spatial optimization models in practice.

97 MATHEMATICS AND COMPUTING↗

Willingness to Receive mHealth Services Among Patients with Diabetes on Chronic Follow-up in Public Hospitals in Eastern Ethiopia: Multicenter Mixed-Method Study

Background: Management of diabetes requires a long-term care strategy, including support for adherence to a healthy lifestyle and treatment. Exploring the willingness of patients with diabetes to receive mHealth services is essential for designing efficient and effective services. This study aimedto determine willingness to receive mHealth services and associated factors, as well as explore the barriers to receive mHealth services among patients with diabetes. Methods: A multicenter mixed-method study was employed from September 1 to November 30, 2022. For the quantitative part, a total of 365 patients with diabetes receiving chronic follow-up at three public hospitals were enrolled. Data were gathered using structured questionnaires administered by interviewers, entered into Epi-data version 4.6, and analyzed using Stata version 17. A binary and multivariable logistic regression model was computed to identify the associated factors. For qualitative, eight key informants and seven in-depth interviews were conducted. After verbatim transcription and translation, the data were thematically analyzed using ATLAS.ti V. 7.5. Results: Overall, 77.3% had access to a mobile phone, and 74.5% of them were willing to receive mHealth services. Higher odds of willingness to receive mHealth services were reported among patients with an age below 35 years [AOR = 4.11 (1.15– 14.71)], attended formal education [AOR = 2.63 (1.19– 5.77)], without comorbidity [AOR = 3.6 (1.54– 8.41)], < 1-hour travel to reach a health facility [AOR = 3.57 (1.03– 12.36)], answered unknown calls [AOR = 2.3 (1.04– 5.13)], and were satisfied with health-care provider service [AOR = 2.44 (1.04– 5.72)]. In the qualitative part, infrastructure, health facilities, socioeconomic factors, and patients’ behavioral factors were major identified barriers to receiving mHealth services. Conclusion: In this study, the willingness to receive mHealth services for those who have access to mobile phones increased. Additionally, the study highlighted common barriers to receiving mHealth services.

60 APPLIED LIFE SCIENCES↗

Engineering Precisely Controlled Negative and Zero Thermal Expansion Behaviors in Metal-Organic Frameworks

Positive thermal expansion can cause significant stress or even catastrophic device failure in applications where materials are placed in confined environments. At material interfaces such as coatings, thermal expansion effects can also lead to cracking and peeling behavior. The ability to impart controlled thermal expansion properties in an array of designs via additive manufacturing technologies would mitigate such problems and bring significant value to various materials science and engineering challenges. Negative thermal expansion materials are of interest for composite material applications whereby they can compensate for the behavior of a positive thermal expansion matrix. This Truman Fellowship LDRD research project presents complimentary experimental and molecular modeling results towards the fundamental understanding and development of metal-organic framework (MOF) materials with controlled thermal expansion properties. Design strategies for imparting precisely tailored negative, zero, and positive thermal expansion regimes in MOFs are studied and the implications of these design strategies for the use of MOFs as an emergent negative thermal expansion material class are examined. Challenges towards exploiting this nanoscale behavior at length scales relevant to composite material systems are introduced. ACKNOWLEDGEMENTS I will be forever grateful to the Truman Fellowship Selection Committee for providing me with the opportunity to pursue this research project. The unique opportunity to carry out this exciting scientific research with all of the resources and support that Sandia has to offer has been a truly rewarding experience. I would like to especially thank Yolanda Moreno for her endless assistance throughout my time as a Truman Fellow. It is hard to imagine a more supportive and stimulating scientific environment to carry out this research. I would also like to thank all of my colleagues and the individuals that have collaborated with me throughout this Fellowship, both internal and external to Sandia. Many of you appear as co-authors on the publications resulting from this LDRD, including especially fruitful collaborations with researchers at the Georgia Institute of Technology and the University of Amsterdam. I cannot express enough my gratitude for the significant role that you all played in shaping my educational experience and the success during my time at Sandia as a Truman Fellow.

36 MATERIALS SCIENCE↗

Commercial PV Property Characterization: An Analysis of Solar Deployment Trends in Commercial Real Estate

The commercial rooftop solar energy market remains an under-developed sector. The market is estimated to contain 150 gigawatts of potential in the U.S. but it faces significant barriers to deployment to meet that potential, with an estimated 1.4 GW developed through 2017. This analysis focuses on of over 30,000 solar systems installed through 2017 and the properties on which they are located. The sample represents greater than 60% of the installed market at that time. The properties covered 20 states and almost 30 different types including industrial, warehouse, school/university, office, retail, and municipal/government and were compared to more than 2.4 million non-solar properties in the same geographies. The analysis finds overall commercial rooftop PV penetrations have only surpassed 1% recently across all property types with education properties (schools and universities) leading at over 6% penetration and with NJ and CA seeing the highest overall penetrations close to 2.5%. Also revealed were characteristics of those buildings, owners, and tenants and how solar penetrations change as those characteristics change. The research found clearly higher penetrations on owner-occupied larger (~9000 ft 2 ) buildings with fewer tenants indicating, potentially, areas for future customer acquisition for PV developers. Also investigated were differences of solar system characteristics on commercial buildings such as system installed prices, size, and percentages of third-party owned (TPO) systems. The research found a steady and substantial drop in installed prices over time, a drop in the percentage of TPO systems being installed, and a relatively steady trend of system size. This latter finding indicates that smaller systems remain difficult to develop.

14 SOLAR ENERGY↗

Conceptual Design of an Electron Accelerator for Bio-Solid Waste Treatment.

Several studies have identified electron beam (EB) irradiation of municipal wastewater and bio-solids as an effective and promising approach to the environmental remediation of the enormous quantities of human waste created by a growing world-wide population and increased urbanization. However, despite the technical success of experimental and pilot programs over the last several decades, the technique is still not in commercial use anywhere in the world. In addition, the report also identifies the need for “Financial and infrastructure participation from a utility for demonstration project” and “Education and awareness of safety of utilizing electron beam technology” as two additional roadblocks preventing technology adoption of EB treatment for bio-solids. In this concept design, we begin to address these barriers by working with Metropolitan Water Reclamation District of Greater Chicago (MWRD) and by the applying the latest accelerator technologies developed at Fermilab and within the DOE Office of Science laboratory complex.

43 PARTICLE ACCELERATORS↗

National QuarkNet Program

The agreement covers the joint administration of the National QuarkNet Program by Fermilab, on behalf of DOE, and Notre Dame, on behalf of the National Science Foundation. QuarkNet has established centers at universities and national laboratories conducting research in particle physics across the United States. Mentor physicists and physics teachers collaborate to bring cutting-edge physics to high school classrooms. QuarkNet offers research experiences for teachers and students, teacher workshops and sustained follow-up support. Through these activities, teachers enhance their knowledge and understanding of scientific research and transfer this experience to their classrooms, engaging students in both the substance and processes of contemporary physics research. The QuarkNet Program has been helping to improve science education in high schools across the U.S. and helping to develop America’s technological workforce.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Collaborative Research: The evolution of magnetic skeletons during 3D magnetic reconnection. Final Technical Report

The goals of this project were to investigate magnetic field evolution during 3D magnetic reconnection; begin development of an open source Python package for plasma research and education; advise students on research projects related to magnetic reconnection; and organize a conference session on diversity, equity, and inclusion in plasma physics. The principal investigator advanced an analytical theory to describe the ideal and non-ideal motion of the magnetic field lines that connect two magnetic null points; led development of the PlasmaPy package through version 0.2.0; directly advised two students; and is co-organizing a town hall on diversity, equity, and inclusion at a major plasma physics conference.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Case Study of a Skin Puncture Contaminated with 238Pu at Los Alamos National Laboratory

The presentation describes the incident, evaluation, and treatment path of a plutonium contaminated skin puncture wound at Los Alamos National Laboratory. Treatment included chelation and excision. The post evaluation concluded that psychological harm was the most significant health effect in this particular case and that quick treatment was vital toward a positive outcome. Treatment efficacy declines rapidly with time. Additional wrriten materials were prepared for all radiation workers and their families to improve safety education.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Clean Cities Coalitions (2018 Activity Report)

Clean Cities coalition activities resulted in an energy use impact (EUI) of over 1 billion gasoline-gallons equivalent (GGE), comprised of net alternative fuels used and energy savings from efficiency projects, in 2018. Participation in vehicle and infrastructure development projects remained strong, as did alternative fuel use and resulting overall EUI. Clean Cities coalition activities reduce emissions as they impact energy use. Coalition-reported activities prevented 5 million carbon dioxide-equivalent tons of emissions (only greenhouse gas [GHG] emissions are reported here; criteria pollutants and other emissions are not included in this report). Coalitions were successful in securing project grant awards from numerous (non-DOE) outside sources. For other Federal, State, and local agencies and private sector foundations, see funding section on page 25. The 84 project grant awards in 2018 generated $251 million in funds from coalition members and project partners along with $1.9 million in DOE grant funds. Coalitions also collected $1.1 million in stakeholder dues and $2.9 million in operational funds from host organizations. In macro terms, this supplemental funding represents nearly a 7:1 leveraging of the $37.8 million that was included in the VTO Technology Integration budget in Fiscal Year 2018. Clean Cities coordinators spent nearly 121,000 hours pursuing their coalitions' goals in 2018. The average coordinator is quite experienced and has held his or her position for at least eight years. Coordinators logged more than 3,805 outreach, education, and training activities in 2018, which reached an estimated 35 million people.

33 ADVANCED PROPULSION SYSTEMS↗

Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era

The field of astronomy has arrived at a turning point in terms of size and complexity of both datasets and scientific collaboration. Commensurately, algorithms and statistical models have begun to adapt --- e.g., via the onset of artificial intelligence --- which itself presents new challenges and opportunities for growth. This white paper aims to offer guidance and ideas for how we can evolve our technical and collaborative frameworks to promote efficient algorithmic development and take advantage of opportunities for scientific discovery in the petabyte era. We discuss challenges for discovery in large and complex data sets; challenges and requirements for the next stage of development of statistical methodologies and algorithmic tool sets; how we might change our paradigms of collaboration and education; and the ethical implications of scientists' contributions to widely applicable algorithms and computational modeling. We start with six distinct recommendations that are supported by the commentary following them. This white paper is related to a larger corpus of effort that has taken place within and around the Petabytes to Science Workshops (https://petabytestoscience.github.io/).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Partial support of the Condensed Matter and Materials Research Committee. Final progress report

The Condensed Matter and Materials Research Committee (CMMRC) is one of five standing committees of the National Academies’ Board on Physics and Astronomy (BPA) and is charged with assisting the BPA in achieving its goals—monitoring the health of physics and astronomy, identifying important new developments at the scientific forefronts, fostering interactions with other fields, strengthening connections to technology, facilitating effective service to the nation, and enhancing education in physics. CMMRC carries out its functions in several ways – providing expert advice to the BPA in monitoring the health of condensed matter and materials research and providing perspective on issues that arise in those fields; assisting other National Academies’ boards in developing proposals and initiating studies that impact these fields; providing long-term stewardship of National Academies reports that it has played a role in initiating and that are of importance to the condensed matter and materials research communities, and providing a means for dialog with federal agencies on these and related fields.

36 MATERIALS SCIENCE↗

Support for the 2019 US-EU Transport Taskforce Workshop (Final Report)

This closeout report documents outcomes from the 2019 US-EU Transport Task Force workshop, which was partially supported by this award. This workshop was held March 18-21, 2019, at the AT&T Executive Education and Conference Center on the University of Texas, Austin Campus. There were 118 attendees at this meeting (22 of whom were students), drawn in roughly equal measure from national laboratories, universities, and private industry. Plenary talks were delivered by Prof. Fritz Wagner (reviewing the discovery and physics of the H-mode confinement regime) and Prof. James Callen (on the history of the TTF workshop, in recognition of TTF’s 30 anniversary in 2019).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗