University of Texas at San Antonio

NSF Awards · FY 2024 · 2024-10

Consumer-level virtual reality goggles are not accessible for many persons with balance impairments, such as elderly persons, persons with multiple sclerosis, Parkinson's, or diabetes. Currently, people with balance impairments cannot benefit from many immersive virtual reality benefits, such as education, physical fitness, rehabilitation, and entertainment. The team's previous work studied how audio, visuals, and vibrations can improve balance while in virtual reality in controlled laboratory settings with simplified virtual reality environments, where they found that audio was the most effective. This project aims to expand the research beyond laboratory settings because typical use of virtual reality occurs at home with complex virtual reality environments with much more intense audio, visual, and vibration stimulation. To address the additional complexities of being outside the lab with much stronger stimulation, the team will develop specialized audio intended to improve balance in any virtual environment. If virtual reality imbalance issues can be resolved, persons with balance impairments can more readily benefit from virtual reality. This project investigates approaches to enable adaptive auditory feedback techniques to improve balance in virtual reality use at home, which includes commercial virtual reality experiences with strong stimuli. Based on the team's preliminary studies, the central hypothesis is that adaptive auditory feedback can improve balance during virtual reality use at home more effectively than the current state of the art, which uses a static, 'one size fits all' approach to feedback. The work will seek the following novel contributions: 1) adaptive auditory feedback techniques to improve balance in VR; 2) automatic, real-time balance prediction with low-cost sensors, some of which are already integrated into commercial virtual reality systems; 3) controlled laboratory and at-home studies, providing generalizable understanding and computational models of balance in virtual reality in the presence of strong stimuli; 4) insight into the potentially lasting effects of virtual reality-based auditory feedback on balance after virtual reality exposure. Ultimately, this project will result in datasets and open-source tools that will make virtual reality more accessible for persons with balance impairments, which could improve their quality of life. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

The United States (U.S.) transportation sector remains a cornerstone of the economy, contributing over 8% to the country's Gross Domestic Product (GDP). Electrification efforts are transforming this sector, aiming to enhance mobility efficiency, reduce operating and maintenance costs, and cut greenhouse gas emissions. These efforts also seek to boost energy independence and security while significantly contributing to employment, particularly in technology and innovation fields. This shift has already placed more than 2.5 million Electric Vehicles (EVs) on U.S. roads, supported by over 70 thousand charging stations nationwide. To manage this advanced and complex cyberinfrastructure (CI), EV operators and vendors rely on cloud-based EV Management Stations (EVMS), crucial for provisioning services such as charging, billing, and authentication. However, the critical nature of EVMS has made them targets for malicious attacks, often state-sponsored, exploiting rarely investigated vulnerabilities. In response, this project establishes a collaborative ecosystem among academia, industry, and the public sector to bolster the resilience of the EV CI. It aims to develop proactive methodologies to identify and analyze Internet-connected EVMS and their software, thoroughly exploring and mitigating related vulnerabilities. This initiative connects several diverse Minority Serving Institutions (MSIs) within the established ecosystem, fostering joint research and providing enriching training opportunities. Through workshops, capstones, curricula material, virtual hands-on labs, professional development, and mentorship programs, the project enhances cross-disciplinary capacities at MSIs and beyond, driving forward the future of resilient, electrified transportation. In this context, this project serves NSF's mission in promoting the progress of science and securing national defense related to this ever-evolving CI. The project pioneers advanced fingerprinting techniques employing automated web scraping, recursive unsupervised learning algorithms, and pattern matching methodologies to identify and cluster Internet-scale EVMS. The primary objective is to detect deployed configurations and their interconnections, while retrieving critical artifacts, such as firmware binaries and compiled software, for comprehensive vulnerability analysis and disclosure. Leveraging robust industry connections, the project acquires auxiliary artifacts, including EVMS source code, through advanced supply chain reconnaissance and reverse engineering methods. This initiative also devises and implements an advanced digital forensic methodology rooted in ensemble techniques and machine learning classifiers. It integrates static analysis, file system forensics, memory forensics using volatility frameworks, data carving with custom heuristics, offensive security tactics, behavioral analysis through dynamic instrumentation, and virtualization methodologies such as hypervisor introspection to meticulously analyze the security posture of EVMS firmware and web endpoints. Furthermore, the project exploits state-of-the-art innovations in Large Language Models (LLMs) to automatically identify vulnerabilities in EVMS source code and suggest tailored and sound code fixes. This is accomplished by creating an unprecedented instruction-based training dataset using supervised fine-tuning, reinforcement learning, and transfer learning techniques. Additionally, the project establishes a large-scale data and threat repository to index discovered threat models, associated vulnerabilities, and retrieved EVMS artifacts. Accessible via RESTful APIs and web-based interfaces, this repository democratizes knowledge by making the harvested EVMS assets available at large, significantly empowering EVMS-centric threat situational awareness while fostering advanced research and development. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

An algebraic set is a collection of points that satisfy constraints imposed by a collection of multivariable polynomial equations. Algebraic sets defined on real numbers naturally arise in electrical engineering, computer vision, and modeling of biochemical reaction networks. Put another way, algebraic sets are geometric objects that are cut out by polynomial equations: These sets provide a rich language for modeling and computation, as well as a clear framework for algorithm design. The boundary of what is efficiently computable and what is intractable for computations over real algebraic sets is currently hazy. Moreover, even in the cases in which we have a fast algorithm for processing a collection of real algebraic sets, its numerical stability aspects are typically unclear. This proposal aims to develop a practical and clarifying theory: We aim to delineate hard and easy problems in computational real algebra in a way that guides numerical computations. The project has the potential to impact the accuracy of 3D reconstruction, the stability of power-flow networks, and the modeling of biochemical reaction networks. The project will also train undergraduate and graduate students in theoretical computer science. The proposal will address several structural and algorithmic questions. The first problem is to design an algorithm for finding a complex zero of a sparse system of polynomial equations that is average-case polynomial time. The second problem is understanding the relation between description complexity and geometric complexity of a real algebraic set. We will specifically focus on Kushnirenko's conjecture and test our findings against the conjectures arising from systems biology. Kushnirenko's conjecture, in simple terms, asserts that the number of connected pieces of a real algebraic set is a polynomial function of the number of terms that appear in its defining equations. The third problem is to design algorithms that separate the polynomial systems with many real zeros from the ones with few real zeros, and this is motivated by applications in power flow network design. The last problem to be addressed is the design and analysis of preconditioners for algebraic sets in general, and 3D reconstruction in particular. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

The National Institutes of Health note that heat and poor air quality in urban areas are the cause of significant illness and death in the US every year, with heat slated to increase dramatically in the future due to global warming. Many cities in the American southwest are already suffering from the combined impacts of rising temperatures and increased air pollution, the latter due to wildfires and drought, with drought causing increased air-borne dust due to the drying of an already arid landscape. Exacerbating this problem is the fact that the scientific understanding of the urban heat island phenomenon is incomplete. Various attempts have been tried to mitigate the problem; but most are ad-hoc and not based on scientific evidence, especially when heat and air pollution co-exist in increasingly complex urban environments that contain a mix of surfaces, waste heat from buildings and other infrastructure, heavily traveled roadways, and other sources of heat and air pollution. The premise of this planning process is to discover if the urban heat island effect is driven solely by surface characteristics or if it can be reinforced by local variations in atmospheric pollution. Air quality issues and climate change are often studied separately even though the chemical and physical processes that occur in the atmosphere are factors in both. This Civic Innovation Challenge (CIVIC) planning process brings together a science team with local city government entities to better understand the problem and the potential coupling of heat and air pollution in the city of San Antonio, Texas with San Antonio serving as a pilot for the co-design of a science/research-based, implementable, scalable, and sustainable solution that addresses, in one study, heat and air quality in an urban environment. It will also identify effective solutions that can be used for mitigation approaches that can improve San Antonio resident resilience to these problems. The science team and city planners from four departments of the San Antonio city government will work together to co-design a plan for better understanding the atmospheric system in a complex urban environment and determine the cause(s) and locations of dangerous hot spots in cities. The team will investigate and quantitatively measure characteristics of the city of San Antonio to both examine the interaction between air pollution and heat and determine the effectiveness of already implemented ways that the city and its residents are trying to reduce surface and air temperatures, such as deploying “cool pavement” surfaces and increasing city tree canopy and green space. In addition to measuring the concentration of atmospheric pollutants and the temperature of the air and surfaces, the team will survey and interview residents to see if they have insights beyond those coming out of the scientific literature. Broader impacts of the work are results that are intended to be scalable and sustainable and provide fact-based evidence to allow communities to use their resources more efficiently to improve their local environmental conditions. Any outcomes that result in the decrease of urban/city air and surface temperatures and air pollution will increase community health and well-being.   Despite the well-established need for action on urban heat island impacts and the fact that research has shown that urban heat exacerbates air pollution, the feedback loops and how air pollution can worsen urban heat island intensity is not well known. This planning process and the follow-on proposal will adopt a new framing and assess the potential bi-directional interactions between urban heat islands and air quality. The CIVIC science and San Antonio city team will work together to investigate the causes of urban heat and poor air quality as well as the intra-urban variations in each. The results will involve the implementation of science-backed solutions that are targeted to mitigate heat and pollution drivers. The collective goal of the planning process and follow-on project is to improve understanding of the urban environment to enable implementation of effective strategies that can successfully mitigate urban environmental heat and air pollution hazards. The joint science and San Antonio city team will collect air temperature, relative humidity, air pollutant concentrations (ozone, particulate matter, and carbon dioxide among others), land surface temperature, and aerosol optical depth. They will also engage San Antonio city residents to find out their experience living with, and attempting to, mitigate San Antonio heat and negative air quality. The resulting information will provide food for discussion among CIVIC team members on the effectiveness of already employed heat mitigation efforts and possible new approaches. It will also illuminate whether there is bi-directional interaction between air pollution and heat. Results of the planning process are identification and co-design of the most promising heat/air pollution mitigation and installation strategies targeting key locations in the city that can increase community resilience to climate change. To achieve effective heat and air pollution mitigation strategies urban heat and atmospheric quality data will be collected and combined with remote sensing satellite data on surface and atmospheric conditions. This planning process will both improve understanding of how community-based efforts can be designed to improve living conditions in urban centers and catalyze needed policy changes. The process will also foster and strengthen collaboration between researchers and community stakeholders, develop new collaborations and partnerships, refine the research vision to enable submission of a successful follow-on proposal that will implement the community vision and provide data to address research questions and develop evaluation methods and measures for the follow-on project. Through this approach, the project team feels the activities and anticipated outcomes can be replicated in other similar urban communities facing similar challenges. This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. This project was funded by the NSF Directorate for Geosciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The neuromorphic commons (THOR) project aims to accelerate the pace of research innovation by creating a new and unparalleled large-scale neuromorphic computing resource, providing unique opportunities for cooperation in research collaborations and tool development. By lowering the barriers to access neuromorphic infrastructure through collaborations with two prominent neuromorphic companies, and by providing open-source software frameworks and benchmarks, THOR will drive research advancements in multiple application domains. THOR will catalyze a transformation in algorithm design, hardware/software co-design paradigms, and neuromorphic applications, similar in scale to the impact seen when high-performance computing systems became accessible to the engineering research community. The THOR project involves researchers from the University of Texas at San Antonio, the University of Tennessee Knoxville, the University of California San Diego, and Harvard University. The project aims to develop and deploy large-scale neuromorphic computing research infrastructure which will provide community access to heterogeneous neuromorphic computing hardware systems through close-knit partnership with industry. THOR offers i) remote access to large-scale neuromorphic systems; ii) open-source hardware/software co-design frameworks and tools; iii) common benchmarks and competitions; and iv) rapid algorithm development by providing access to a collection of learning modules, network models, and example frameworks. THOR will enable a richer understanding of computational models, algorithms, neuromorphic hardware, and engineered test cases, supporting research in neuroscience and a wide range of application domains that benefit from bioinspired processing. THOR team will develop training and educational materials that will cover the fundamentals of neuromorphic learning algorithms and systems, in partnership with industry and the neuromorphic community. All the resources will be available through open-platforms to researchers and K-12 students, facilitating integration into both undergraduate and graduate curricula. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Ground based telescopes with adaptive optics (AO) have now provided direct imaging (DI) detections of about 20 extrasolar gas giant planets. Targets are usually selected based on system properties like age and distance, and these surveys have low yields, about 1%. These detections do not directly measure a planet’s mass and often poorly measure its orbit. This program takes a different approach to exoplanet imaging discovery and characterization, to remedy these aspects. DI survey targets are selected from among young, nearby stars based on their accelerations across the sky, indicating they are being gravitationally pulled by a dimmer companion. The search is expected to discover new exoplanets via two world-class ground-based AO systems located in Hawaii and – due to the selection criterion – measure their masses and constrain their orbits. This project will start a collaborative partnership with Maunakea Visitor’s Center, providing funding for new exhibits that highlight the knowledge about extrasolar planets revealed from Maunakea and the cultural and biological significance of Maunakea. It will support an astronomy-related internship to a student in Hawaii in the Akamai Workforce Initiative. Local to one PI’s institution, the project supports and expands the San Antonio Teachers Training Astronomy Academy, providing effective science education professional development for Texas high school teachers who predominately teach economically disadvantaged and underrepresented minority groups. The dynamical evidence for a companion from precision astrometry is contained in the Hipparcos-Gaia Catalogue of Accelerations (HGCA): i.e., stars showing an astrometric acceleration. The project uses the Subaru Coronagraphic Extreme Adaptive Optics Project (SCExAO) coupled with the CHARIS integral field spectrograph in the near-infrared (near-IR) to discover the perturbing bodies. For the brightest planets and brown dwarfs, analogues to jovian planets, it will also obtain follow-up thermal IR imaging with NIRC2 camera on the Keck II Telescope. The new dynamical code orvara simultaneously constrains the planet’s masses and orbits from these data. The planetary atmospheres are analyzed via empirical libraries and new atmospheric models. These discoveries anchor models of substellar formation and evolution from the largest brown dwarfs to jovian exoplanets. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Small businesses form the backbone of the U.S. economy, yet significant disparities exist in access to capital and entrepreneurial opportunities for various demographic groups. This project seeks to advance national prosperity and welfare by dismantling systemic obstacles that prevent equitable participation in entrepreneurial activities. By developing novel research tools to examine underlying market frictions and facilitate inclusive funding opportunities, the project holds promise for empowering underserved communities, unlocking untapped economic potential, and creating a more level playing field for all aspiring entrepreneurs nationwide. The project establishes two interconnected research infrastructures with a cross-country scope: (1) The Small Business Lender Preference and Perception (SBLPP) database, consolidating survey data on nearly 9,300 U.S. community banks and credit unions regarding their lending preferences, market perceptions, and institutional strengths and (2) FundMatch, an online platform using SBLPP data to match entrepreneurs with lenders aligned to their financing needs and preferences, reducing search frictions. FundMatch enables field experiments identifying and addressing demand-side barriers like borrower discouragement. This researcher-entrepreneur-lender nexus yields actionable insights to foster inclusive entrepreneurial ecosystems and drive equitable economic development across regions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Today’s schools are experiencing increasing cultural and linguistic diversity and facing the challenge of meeting the learning needs of culturally and linguistically diverse children, such as Latinx learners in dual language immersion programs. This project will support bilingual students by recognizing and incorporating their cultural heritage into science education. Further, it will advance the understanding of how integrating Indigenous knowledge with Western science in dual language immersion programs can improve science identity and education for Latinx youth in middle schools, many of whom are also of Indigenous heritage. The project will also evaluate the impact of this curriculum on students and teachers, fostering a more inclusive and holistic approach to learning. Digital media and curricular materials developed through this collaboration will be widely available, making this innovative curriculum accessible to dual language classrooms across the U.S. Ultimately, this work seeks to enhance science education accessibility for marginalized students, particularly Latinx youth, and support their representation and engagement in STEM fields. The project team will support 11 middle school teachers and 2,500 students across southern states providing them with resources that acknowledge and incorporate multiple epistemologies of indigenous communities. The research team will employ qualitative methods, including thematic, content, and ethnographic analyses of meetings with Indigenous collaborators, the curricular development process, professional learning for teachers, teaching practices, and student artifacts. Assessment and evaluation plans to involve examining how teachers adapt their instruction to include Indigenous knowledge and measuring the curriculum's impact on student engagement and achievement in STEM. Further dissemination of the digital curriculum can increase the impact of this project. Through the weaving of indigenous forms of scientific knowledge and Western science, the project team anticipates providing more spaces for participation in STEM and developing additional interest among historically marginalized Latinx youth toward STEM employment pathways. This collaborative project is funded by the EDU Racial Equity in STEM Education activity, which is supported by the Directorate for STEM Education (EDU). This activity supports research and practice projects that investigate how considerations of racial equity factor into the improvement of science, technology, engineering, and mathematics (STEM) education and workforce. Awarded projects seek to center the voices, knowledge, and experiences of the individuals, communities, and institutions most impacted by systemic inequities within the STEM enterprise. Programs across EDU contribute funds to the Racial Equity activity in recognition of the alignment of its projects with the collective research and development thrusts of the four divisions of the directorate. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

This doctoral dissertation research project investigates the significance and role of field schools in shaping of the discipline of primatology and the production of knowledge about primates. Field schools serve as important training grounds for future primatologists, offering valuable insights into how disciplinary practices and understandings are transmitted and transformed. By examining these crucial spaces of learning, this research contributes to an understanding of the dynamics involved in the creation and perpetuation of scientific knowledge. In addition to providing scientific training to a graduate student in anthropology, findings will be disseminated through academic publications, conference presentations, and public outreach efforts to enhance the public's understanding of the scientific process and the role of training in scientific disciplines. Research findings inform the development of inclusive, equitable, scientific training practices, benefiting both student experience and disciplinary standards. To expand understandings of the relationship between scientific training and disciplinary knowledge, the doctoral student employs an ethno-primatological approach. This combines primate behavioral observations with ethnographic techniques, in a comparative study of two field schools that train primatologists. The methods combine human and primate behavioral data with participant observation, interviews, surveys, and content analysis. The broader research contributes to science and technology studies, the science of scientific education, biological anthropology and primatology, and multispecies studies in cultural anthropology. This research is supported by the Cultural Anthropology, Science of Science: Discovery, Communication and Impact, and the Biological Anthropology programs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-07

Underground storage of carbon dioxide (CO2, a greenhouse gas) is a potential powerful tool to mitigate climate change. The storage must be permanent, safe, cost-effective, and environmentally sustainable. Carbon dioxide can be stored underground in a liquid-like state called supercritical fluid. Strong candidate places for storage of supercritical CO2 are saline formations, which are layers of porous and permeable rocks saturated with salty water. Under these conditions, the storage can be improved by an emulsion formed by supercritical carbon dioxide as the dispersed phase and the saline solution as a continuous phase; this emulsion must be stable for the CO2 to not escape back to the environment. This award will investigate the encapsulation of supercritical carbon dioxide by cellulose nanocrystals, which are non-toxic plant-based nanoparticles that have affinity to both carbon dioxide and water. The goal is to understand the mechanisms that might lead to stable carbon dioxide emulsions under extreme pressures found in underground reservoirs. Leveraging this understanding could lead to the development of other emulsion systems such as drug delivery systems, food products, and advanced materials. This award will provide research training and education of graduate and undergraduate students who will be trained in advanced characterization and computer simulation methods, contributing to the STEM workforce development. This award is a comprehensive computational and experimental investigation to elucidate the main mechanisms and energies associated with the stability of liquid carbon dioxide (CO2) dispersions in brine. It will determine the principles that may lead to CO2 drops coalescing into each other, or additional mechanisms that may detrimentally contribute to its release. Heptane and liquid carbon dioxide will be used as oil phases for all computational and experimental studies.The primary objectives are: 1) To develop a coarse-grained model of cellulose nanocrystals and use it to predict their aggregation state on a bulk aqueous phase, as well as the nanocrystal crust morphology on heptane/water and carbon dioxide/water interfaces, while corroborating predictions with advanced electron microscopy and scattering techniques, 2) To correlate predicted mechanical properties of interfaces with the large-scale organization of cellulose nanocrystals and corroborate findings with interfacial elasticity measurements, 3) To quantify cellulose nanocrystal adsorption energies on relevant interfaces, and 4) to predict droplet coalescence and coarsening as a model for emulsion stability of cellulose nanocrystal-stabilized heptane/water and carbon dioxide/water Pickering emulsions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.