University of Pittsburgh

NSF Awards · FY 2024 · 2024-09

To study the spread of disease or opinions, it has proven useful to consider a collection of interacting individuals as a mathematical structure called a graph. A graph consists of a set of nodes and a set of edges, each of which links a pair of nodes. PI will extend this framework to the study of neuronal activity. In the neuronal case, each node is a neuron, and edges between them represent the one-way or directed synaptic connections through which neurons interact. Moreover, to capture the different levels of activity that neurons exhibit, each node will be in one of three states, with state changes determined by interactions along edges. PI will develop novel mathematical methods to analyze the patterns of activity that emerge in such multi-state, directed graphs. These methods will allow the project team to study how activity spreads in networks of neurons, how this spread depends on the connection patterns in the network, and what properties characterize sets of nodes that are especially effective at spreading activity. The research results will generate novel predictions about the properties and function of networks of neurons in the brain, with a focus on the key networks that drive breathing and other essential, rhythmic behaviors. The project will train students, will generate openly available computer code, and will include public outreach through online videos and a summer math program for girls. Functional outputs from brain circuits driving certain critical, rhythmic behaviors require the widespread emergence of an elevated, bursting state of neuronal activity. The main goal of this project is to advance knowledge about how the localized initiation of activity can rapidly evolve into widespread bursting in synaptically coupled neuronal networks, exemplified by the respiratory brainstem circuit. The project team will achieve this goal by representing such networks as digraphs in which each node can assume one of three possible activity states – inactive, weakly active, and fully active or bursting -- with updates based on in-neighbors’ states. Little theory exists to characterize this multi-state bootstrap percolation framework, and we will develop new analytical approaches involving mean field and master equations, asymptotic and probabilistic estimates, and graph design based on combinatorial principles. The analysis will address differences between dynamics in this framework and that in bootstrap percolation with only two possible states per node, the impact of global graph properties on activity spread, and the characteristics of local initiation sites that result in especially effective activity propagation. Overall, the project will support a new interdisciplinary collaboration and the completed work, involving trainee mentorship and open sharing of code, will provide important insights and predictions about neuronal dynamics and interactions as well as a range of mathematical advances. This project is jointly funded by the Mathematical Biology Program in the Division of Mathematical Sciences and the Research Resources Cluster in the Division of Biological Infrastructure in the Directorate for Biological Sciences. 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

This award funds the research activities of Professor Daniel Boyanovsky at the University of Pittsburgh. Observations over the last two decades have unambiguously determined that 95% of the energy and matter content of our Universe is in the form of Dark Matter and Dark Energy, both of which require new theoretical frameworks for their understanding. The Standard Model of Particle Physics describes the fundamental particles and their interactions and has been experimentally confirmed to great accuracy with current accelerators, with the discovery in 2012 of the Higgs particle. Despite its successes the Standard Model does not explain either Dark Matter or Dark Energy. However, compelling extensions beyond it provide tantalizing hints for the possible explanation of Dark Matter in the form of a new particle, the axion, which, if it exists, also provides a possible explanation of aspects of the strong interactions. Under this grant award, Professor Boyanovsky, in collaboration with students will pursue research on fundamental non-equilibrium aspects of this Dark Matter candidate to complement current experimental searches for its existence. Recently it has been proposed that a similar type of particle may exist in novel materials, thus the study of its properties and observational avenues is truly interdisciplinary and promotes the progress of science in many ways. The project is also envisioned to have significant broader impacts across disciplines. Professor Boyanovsky will involve graduate students in the research program, thereby providing critical training for junior physicists and a broad and enriching educational experience. The results will be disseminated via public lectures and shared openly with the community. More technically, Professor Boyanovsky and students will implement non-equilibrium effective field theory and quantum master equation methods borrowed from quantum information and other branches of physics, to study the production, decay and thermalization of Dark Matter candidates during the Early Universe determining its abundance, and to explore the tantalizing possibility of realizing these particles in novel materials which may provide platforms for quantum information. 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 problem of real-time monitoring and detecting changes in the statistical properties of multi-stream data has many applications in science and engineering. These include monitoring public health for possible pandemic onset and recognizing abnormal events in multi-camera video surveillance. Often the data of interest is non-stationary, i.e., its statistical properties that change with time. Traditional change detection algorithms are not optimized to process non-stationary data. This project will develop algorithms that are provably robust against uncertainty in data distribution and easily implementable in practice. The algorithms will be further developed to apply in settings where privacy, energy efficiency, and high-dimensionality of data come into play. The developed algorithms will be applicable to solve a wide class of spatiotemporal change detection problems in public health and cyber-physical systems. The algorithms will be validated on several publicly available datasets and the code will be made publicly available. Students will have opportunities to participate in the research and efforts will be made to recruit participants from underrepresented groups. The algorithms developed in this project will be optimized to detect changes in the statistical properties of multi-stream non-stationary data with the minimum possible delay, subject to a constraint on the rate of false alarms. These quickest change detection algorithms will be designed to be robust against uncertainty in the distribution of data before and after the change. The project is divided into four technical thrusts. The first thrust will develop robust algorithms for quickest change detection when there are multiple streams of non-stationary data with unknown pre- and post-change distributions and the change can occur in any subset of the streams. The algorithms will also be designed to identify the affected stream, at the time the change is declared, and an alarm is raised. The algorithms will be based on the least favorable pair of distributions in the pre- and post-change uncertainty classes. Procedures to analytically characterize or numerically calculate the least favorable pair will also be provided. The second thrust will develop robust algorithms for non-stationary high-dimensional data. The algorithms will be based on the gradient of the logarithm of the density of the data which can be learned using deep neural networks. The third thrust will develop algorithms for data-efficient quickest change detection in non-stationary data. A data-efficient procedure utilizes adaptive sampling techniques to control the average number of observations used before the change. The fourth thrust will develop optimal algorithms for some special classes of non-stationary processes encountered in traffic safety, satellite safety, and public health applications. 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

Biological tissues, such as skin, muscle, cartilage, and bone are composed of nano/microfibers embedded in a matrix. The fiber arrangement varies over complex tissue geometries to efficiently bear load and regulate deformation. Reproducing such fiber arrangements can lead to more robust and biocompatible medical implants and advanced biomimetic robots that are as adaptive and agile as animals. However, given the small fiber diameter, it can take more than 100km nano/microfibers to fill up a 1ml volume. No existing technology can handle such fiber lengths while controlling spatially varying fiber arrangement. This award supports the investigation of a new technology, aerodynamic fiber deposition, to address this challenge. Aerodynamic fiber deposition uses airflow to focus fibers into a small deposition spot and control the fiber arrangement within the spot. Spatially varying fiber arrangement is achieved by changing fiber arrangement as the deposition spot moves. High throughput is achieved as airflow can manipulate thousands of fibers simultaneously. The research can lead to biomimetic materials that rival the performance of biological tissues, thus enabling its utility in a wide range of medical and robotic devices. The project will also support the participation of underrepresented groups in research and develop related workshops for early science and engineering education. The project will address a fundamental challenge in nano/microfiber manufacturing. 3D printing techniques such as direct ink writing can precisely control fiber arrangements but cannot handle long fiber lengths and throughput remains low. Fiber spinning technologies such as electrospinning and centrifugal spinning can manufacture nano/microfibers with a high throughput but have limited control over the fiber arrangement. Aerodynamic fiber deposition combines the high throughput of established nano/microfiber spinning technologies and a spot-wise deposition like 3D printing to control the spatially varying nano/microfiber arrangements. This research will integrate an electric field and an air jet to achieve a deposition spot smaller than 1cm and will characterize how the deposition spot size affects the resolvable spatial variation in fiber arrangements. The fibers will be embedded into an elastomeric matrix to study how the spatially varying fiber arrangement affects the inhomogeneous mechanical properties. This research will lay the foundation for designing biomimetic fiber-reinforced soft materials using aerodynamic fiber deposition and adapting the technology to applications that require different throughput and resolution. 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

This award is a request for a $20,000 travel grant to support students attending or participating in the 2024 Embedded Systems Week (ESWEEK), which will be held at the Sheraton Raleigh Hotel in Raleigh, NC, USA, from September 29 to October 4, 2024. ESWEEK is the leading event in the embedded systems field. Its conferences have traditionally been very selective, with acceptance rates typically in the 25-30% range. ESWEEK is normally attended by over 300 participants, where conferences and symposia traditionally have high rates of student attendance and participation. Students attend the workshops and talks, and they participate by presenting papers that they have authored, where each accepted paper is accompanied by a poster presented in a separate poster sessions. Most of the students have been Ph.D. candidates doing research relevant to the conferences, symposia and workshops. Special preference given to US citizens and permanent residents as well as under-represented groups. The support requested in this proposal will subsidize the cost for students to attend and will be used to increase participation of students, including minority and underrepresented students. The proposal describes how the allocation of the 20 travel awards will be distributed among students without a paper, and those students from underrepresented groups, as well as students from a 4-year college or university. 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 innate immune system is the first line of defense against pathogens, allowing cells to recognize when they are infected and mount responses. Because these immune responses can also be dangerous to the cell, it is critical for organisms to distinguish between pathogen infection and commonplace bacterial exposure (e.g. to the environmental microbes around us or to our own microbiomes). This distinction is particularly challenging for organisms that eat bacteria, as they constantly inhabit microbe-rich environments and bring microbes into their own bodies. This project brings together a cross-disciplinary team of scientists to investigate innate immune responses in three different organisms that eat bacteria: 1) sponges, one of the earliest branches on the animal tree of life; 2) choanoflagellates, the closest living relatives of animals; and 3) amoebae, a more distant relative. Because these organisms span the evolutionary transition between multicellular animals and their unicellular cousins, similarities among these organisms can illuminate the origins of animal innate immune systems, as well as reveal novel strategies for antibacterial defense. Outreach components of this project include a four-week, summer, pre-college program for students from urban, public, Pittsburgh high schools. Students will conduct hands-on experiments investigating sponge immune responses to bacteria, which they will present at their schools and to the public at the Carnegie Science Center. This project will test the hypothesis that organisms with high-levels of microbial exposure may disproportionately rely on ‘effector-triggered immunity’ (ETI) to monitor for pathogen activity. The proposed approach is to use the versatile pathogen Legionella pneumophila to elicit ETI in three species selected for their phylogenetic position and lifestyle - an amoeba, a choanoflagellate, and a sponge. L. pneumophila is a pathogen that can infect diverse protists and humans by injecting bacterial effector proteins into host cells. This pathogen therefore enables the use of the same bacterial strains and species for parallel investigations of host immune responses across diverged host species. The researchers have recently established a L. pneumophila infection model for sponges. Here, they will characterize the infection modalities, immune cell types, and cellular pathways involved in these infections. They will also attempt to extend this infection model to choanoflagellates (in addition to the well-established amoeba model) and use parallel, unbiased approaches to assess if these organisms elicit ETI in response to L. pneumophila’s global translation inhibition in host cells. 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 2024 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI’24) is a premier flagship conference sponsored by the Institute of Electrical and Electronics Engineers (IEEE) Engineering in Medicine and Biology Society (EMBS), focusing on informatics and computing in healthcare and life sciences. BHI’24 will take place from November 10 to 13, 2024, in Houston, Texas. The theme of BHI’24 is “Deep Medicine and AI for Health.” It will provide a unique platform for cross-disciplinary researchers to showcase their research on big data analytics and machine learning addressing challenges in biomedicine. An important mission of BHI’24 is to promote the participation and engagement of undergraduate and graduate students, especially women and students from under-represented groups. The NSF Student Travel Award will support this goal by providing travel awards to qualified students, especially encouraging students from under-represented groups and those who lack funds to attend the conference. With NSF support, the investigator expects to provide travel awards to approximately 20 student participants to encourage their attendance at BHI’24. The conference will offer student awardees opportunities to present their research, expand their knowledge, network with world-class researchers, and broaden their collaborations. Additionally, participants will have access to keynote speeches from world-renowned researchers, career and technology panels, special sessions, workshops, and tutorials. The investigator will particularly promote diversity and equity by aiming to allocate at least 25% of the awards for students from under-represented groups (women, African American, Hispanic, economically disadvantaged, and others) and first-time attendees to the conference. 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

This award supports research on understanding and predicting the evolution of the backward erosion piping (BEP) phenomenon in geotechnical flood protection infrastructure. BEP is a type of internal erosion mechanism, where soil in a permeable sand layer that resides underneath the cohesive foundation of river levees progressively erodes. BEP has been found to be the present in nearly one third of all recorded failures of water retaining structures. Moreover, flood risk is expected to increase across many parts of the United States as a result of climate change, causing the expected yearly flood damage to increase significantly. This research project will develop novel modeling and computational capabilities for the prediction of BEP, with the goal of providing a fundamental understanding of the interrelationships between soil characteristics, hydraulic conditions, infrastructure geometry and the evolution of erosion. The research team will also carry out educational and outreach activities in the Pennsylvania and Tennessee regions, to share results from the research with the wider public. A strong focus will be to use Augmented Reality-based tools to create novel learning activities to educate K-12, undergraduate students and the public on topics related to flood protection and hazard mitigation. The technical goal of this research is to mechanistically understand and characterize the relationship between hydraulic conditions in flood protection infrastructure systems and the time-dependent evolution of BEP. The research objectives to achieve the technical goal are: (1) the definition of a stochastic multiphase model of BEP evolution; (2) model-enabled discovery of fundamental erosion mechanics; and (3) characterization of the fundamental relationships between system properties, soil characteristics, and backward erosion potential. A stochastic multiphase computational model will be devised by leveraging and building on the Dual Random Lattice Modeling approach. The computational model will be exercised to gain mechanistic understanding of BEP through the idea of a numerical laboratory, where the model outcomes along with multiscale experimental evidence are used together to update the constitutive model form and the associated theoretical model that conceptualizes the constitutive form. 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

Social media use has transformed adolescents’ interpersonal interactions, with important implications for body image. The majority of U.S. teen girls experience body image concerns, which include body dissatisfaction, body shame, and self-objectification. Body image concerns can negatively impact adolescent development, with increased risk for mental health symptoms and low self-esteem. Social media use likely exacerbates body image concerns for many adolescent girls, but the mechanisms are not yet well understood. The overarching goal of this NSF CAREER project is to understand how, when, and for whom specific social media experiences affect body image, in a diverse sample of adolescent girls. In the context of heightened public discourse regarding adolescent social media use, we expect the findings of this study to have broad impacts for science and society. Overall, this project has the potential to provide transformative insights into adolescent social media use and body image, as well as in-depth research training for the next generation of developmental scientists. During a developmental period characterized by heightened self-consciousness and need for peer approval, social media apps provide adolescents with an unprecedented context for self-presentation and social comparison. In recent years, a growing body of research has documented connections between specific social media experiences and body image concerns. However, most of this work has focused on adult women rather than adolescent girls, without attention to unique adolescent developmental processes. This project utilizes a longitudinal, multi-method approach to investigate how specific appearance-related social media experiences affect body image concerns among adolescent girls via a combination of 1) eye-tracking methods to assess attention to social media stimuli, 2) longitudinal surveys of social media experiences and body image concerns, and 3) ecological momentary assessments, in which adolescents are prompted to report real-time experiences related to social media and body image in their daily lives. Guided by developmental and social psychological theories and methods, this project examines whether specific social media experiences predict body image concerns over both short-term (i.e., hourly) and longer-term (18 months) periods in a diverse sample of adolescent girls. Based on prior research and theory, this project focuses on cognitive, behavioral, interpersonal, and emotional risk factors related to social media use. 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

Many caregivers of pre-school aged children find family math programs burdensome, which decreases engagement, sustainability, and ultimately the success of the programs. This is particularly the case for families that face opportunity gaps in math education. This project aims to test whether two low-touch, high-benefit family math programs improve family math engagement and preschool-aged children's math skills. Both programs are tailored to each family's daily routines, do not require specific materials, and provide examples of real families doing math. One of these programs additionally aligns its content to the child's math skills. The project will provide foundational knowledge about effective ways to increase and sustain family math engagement. These studies have the potential to decrease the burden for families, and increase the benefits of math programs on children's immediate and long-term math outcomes, which are critical for later math achievement and entering STEM careers. Using an experimental design, this project examines the impacts of two family-math programs in 160 4-year-olds and their parents. The first condition will deploy the "Math Made 4 Me" intervention, which is designed to support math via typical family routines. The second condition will deploy an enhanced version of the "Math Made 4 Me" intervention, "Math Made 4 Me Plus," which simultaneously tailors this support to each family's typical routines and to the child's math skills. An active control condition provides families with supports to develop children's social-cognitive skills. The project aims to address: 1) whether receiving the "Math Made 4 Me" or "Math Made 4 Me Plus" interventions increase family math engagement and children's math skills relative to receiving the control condition; and 2) whether receiving the "Math Made 4 Me +Plus" increases family math engagement and children's math skills beyond the potential impact of the "Math Made 4 Me" intervention. The project will collect survey and observational data from families and direct assessments of skills in children at three time points: pre-test, recent post-test (2 weeks after program completion) and delayed post-test (3 months after program completion). These family math programs leverage the important role that everyday routines play in math development and have the potential to: a) decrease the burden for families; and b) result in more successful and sustained positive math outcomes for preschoolers, which are critical for later math achievement and entering STEM careers. This project is supported by NSF's EDU Core Research (ECR) program. The ECR program emphasizes basic research in STEM education that generates fundamental knowledge in the field. The program invests in key areas crucial that are essential, broad and have long-term impact: STEM learning and STEM learning environments, broadening participation in STEM, and developing the STEM workforce. 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

The 16th International Workshop on Bio-Design Automation (IWBDA) 2024 takes place in Boston from September 16th to September 20th and will bring together researchers from electronic design automation (the practice of using computer software to build complex electronics) and synthetic biology (the forward design of novel biological systems using engineering principles). The goal of IWBDA is to make biology more easily, robustly, reliably, and predictably engineered and therefore, tackle challenges in biology and medicine, leading to advances in disease diagnosis, treatment and prevention. This award provides travel assistance for ten undergraduate and graduate students to attend this workshop to present research, participate in a computer programming competition, and network with a large community of industrial and academic researchers. These participants will go on to form the foundation of the field in the future. Specifically these students will join a wide variety of researchers (120+) from electronic design automation and synthetic biology in a unique context which does not exist elsewhere. They will have access to between twelve and fifteen technical talks over two days, two invited lectures, ten to twenty posters, multiple group discussion sessions, and a featured student programming competition (BDAthlon). 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

Girls interact with advanced technologies every day, and yet only 20 percent of computer science degrees in the United States are awarded to women. This number has further decreased over the years, and when broken out by ethnicity, is much lower for racially minoritized girls. This issue is not solely due to lack of access, but due to the approaches used in computing education technology and pedagogy. These approaches can limit creative and joyful learning opportunities that are meaningful to the learning context in ways that would empower girls to understand and express their own identities with technology. This project focuses on robotics education for middle school girls from backgrounds which have been historically excluded in the field of computer science, with the goal of developing girls’ skills to use and create new technologies, and construct positive STEM identities. The project extends culturally-responsive computing pedagogies through exploration of co-creation, where youth are empowered as creators of a robotics technology, and simultaneously engage in reflective dialogue with the AI-enhanced robots they have created. Learners will be able to directly ideate on the societal implications of their technological creation and develop their skills to positively impact their community. Researchers will carry out design-based research, including three iterations of co-design and program deployment with a total of 140 girls, in collaboration with two community partners, one serves a majority Black population, and one a more racially diverse group. This project will contribute: 1) Co-creative technology design principles and how design choices can facilitate Culturally Responsive Computing, 2) Sensing and modeling of the dynamic collaborative context, and 3) An understanding of how the resulting principles, outcomes, and implementation guidelines might differ depending on the cultural backgrounds of the participants. A mixed-method design will be employed, utilizing the co-design and deployment data, and pairing quantitative learning analytics of log and interaction data with a qualitative coding of participant artifacts and interviews. Curriculum, technologies, and professional development materials from this project will be made available for public use, and workshops will be conducted that both provide specific instruction on the program and facilitate general knowledge sharing on how to create and sustain empowering informal learning programs. This Integrating Research and Practice project is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences. This project is also partially funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. 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 award funds the research activities of Professors Ayres Freitas and Adam Leibovich at the University of Pittsburgh. This research will contribute to developing improved theoretical tools and calculational methods for the robust interpretation of results from current and future physics experiments. To test our current understanding of the Universe, it may be necessary to identify a potentially small new physics signal on top of large backgrounds. This requires a detailed understanding of the properties and interactions of known particles and advanced techniques for calculating precise predictions for experimental observations. As part of this research, a wide variety of phenomena will be investigated, from sub-atomic particles to gravity to cosmology. Research in this area advances the national interest by expanding our knowledge of fundamental physical laws and providing opportunities for junior scientists to engage in cutting-edge calculations using cutting-edge analysis tools. Indeed, the broader impacts of this research program include the training and professional development of several PhD students and a postdoc. Professors Freitas and Leibovich will also work closely with colleagues in high-energy experiments and in astrophysics research groups in order to ensure that their work can be incorporated in new search and analysis techniques. They will also help to organize workshops and summer schools to disseminate results from modern research to a larger audience of students and junior researchers. More technically, this research program can be divided into four main parts: (1) The development of calculational techniques for higher-order electroweak corrections to precision studies at the ongoing Large Hadron Collider (LHC) and at planned future e+e- colliders; (2) An investigation of several jet observables using fragmentation functions to a jet (FFJ) and Soft-Collinear Effective Theory; (3) Studies that compare the experimental constraints on effective neutrino and Higgs interactions to direct searches for new physics particles that could mediate these interactions, thus exploring the complementarity between the LHC, neutrino-beam experiments, and future e+e- colliders; and (4) Calculations of precise gravitational wave physics using effective field theory techniques, in particular the memory effect in binary systems with large mass ratios. 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

Quality of life as people age is heavily dependent on maintaining mobility. This research evaluates how walking patterns learned in one situation can generalize to another situation and how this ability changes with age. This is a significant issue for people with brain or body injuries that affect walking because rehabilitation techniques typically include training on treadmills or exoskeletons. The investigator will assess how walking patterns learned on a treadmill generalize to walking on the ground and whether that ability is modifiable, changes with age, and interacts with attentional demands. One broader impact of the work lies in its potential to improve rehabilitation tools, enhance mobility and reduce the risk of falls in the elderly. In addition, the project extends a Master’s-to-Ph.D. bridge program (MS2PhD BRIDGE) that increases participation of underrepresented minorities in STEM fields, ultimately fostering a diverse and skilled future workforce in cognitive science and bioengineering. This research identifies factors regulating the generalization of walking patterns in older adults, based on the hypothesis that aging increases generalization of motor learning due to reduced sensitivity to contextual cues and greater reliance on attentional resources. Researchers will compare electromyographic (EMG) changes and generalization of newly learned walking patterns during unassisted walking overground between young and older adults. The study employs innovative methods, such as motorized shoes and split-belt treadmills, to manipulate sensory and attentional demands. The findings are expected to reveal distinct age-specific contributions of subcortical vs. conscious strategies for generalization, advancing theoretical models of motor learning generalization and informing the design of age-specific rehabilitation interventions. This project was funded in part by support from the Perception Action and Cognition Program, Developmental Sciences Program, and Science of Learning and Augmented Intelligence Program in the Division of Behavioral and Cognitive Sciences and by the Disability and Rehabilitation Engineering Program in the Division of Chemical, Bioengineering, Environmental, and Transport Systems. 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

A growing body of research has examined parents’ efforts to support young children’s number and spatial math skill development in the home. Past research typically examines home math activities or parent talk about math and spatial concepts during the preschool years. However, during elementary school, it is unclear how parents balance greater academic rigor and homework assistance, increasing digital media use, and home math activities to support children’s continued math learning. This study examines children’s number and spatial math development in the context of families’ home math environments. The goal is to identify areas of stability and change in parental support of children’s math learning beginning in toddlerhood through first and second grades. Findings from this study will inform educators and parents about the home math practices that enhance math learning during early elementary school and the role of parents’ math engagement during child development. This project draws data from a longitudinal study of 30-month-old children (N = 280) and their parents and follows them into early elementary school. First, multi-method measurement of the home math environment (HME) will be collected in middle childhood. Second, associations between the first-grade home math environment and gains in math skills from first to second grade will be examined. Third, continuity in children’s number and spatial math skills from early childhood to middle childhood will be investigated. Fourth, this study will examine whether early childhood math skills and home environment uniquely predict middle childhood math skills. Children will complete assessments of math skills during two home visits in first and second grades. A combination of structured observations, surveys, and time diary interviews will measure children’s home math environment. The first and second grade data will be linked to early math skills and HME measures collected at ages 2 and 3 in the Parents Promoting Early Learning project (DRL-1920545). By identifying how early differences in number and spatial skills emerge, and the extent to which these foundational skills predict later math skills after the transition to school, this investigation will help inform future math interventions for young learners. This project is cofunded by NSF's DRK-12 and EDU Core Research (ECR) programs. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce 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 · 2024-08

With support from the Chemical Structure, Dynamics, and Mechanisms-A (CSDM-A) Program in the Division of Chemistry, Dr. Jessica Anna and her group at the University of Pennsylvania are investigating some of the earliest, and most important steps involved in the conversion of sunlight into energy. Solar energy conversion often begins with the transfer of energy or charge between two or more identical molecules that are packed together tightly. The close proximity and identical structures of the molecules make it very difficult to directly observe the first stages of the conversion process. In order to better understand these early events and how they affect solar energy conversion efficiency, Dr. Anna and her research team use sophisticated laser techniques to study pairs of molecules that represent more complicated systems. The team varies the relative distance and orientation of the two molecules in a well-defined way that allows them to distinguish changes caused by subtle differences in the way the two molecules interact with each other. The cutting-edge measurements they make provide new insight to aid in the design and development of new materials for solar energy conversion, including artificial photosynthetic complexes, photocatalysts, and organic photovoltaic materials. The project also involves educational and public outreach activities related to the research, including the development of new teaching modules for integration into graduate, undergraduate, and pre-college classrooms, as well as research opportunities and paid internships for undergraduates, pre-college students, and local area high school teachers. The teaching modules, research opportunities, and paid internships are designed to increase the participation of students in science, technology, engineering, and mathematics (STEM) fields, including underrepresented groups and first-generation college students. This project focuses on elucidating the interplay between exciton dynamics and charge transfer in a new family of pi-extended metallo-dipyrrin complexes. These systems have the potential to form excitonic states that undergo symmetry-breaking charge transfer, and therefore allow a systematic investigation of the interplay between energy- and charge-transfer processes. Dr. Anna and her students use pump-probe and coherent multidimensional spectroscopy in the visible and mid-IR spectral regions to study the different dipyrrin complexes and obtain a full characterization of the excited-state dynamics, structural rearrangement, and solvent reorganization involved in the symmetry-breaking charge transfer process. The research team uses a mixed spectral approach to probe the evolution of molecules in electronically excited states having charge-transfer character, harnessing the sensitivity of vibrational modes to the local electrostatic field. The team uses pump-probe spectroscopy to characterize population transfer and determine the branching ratios among different excited states in the dipyrrin complexes. The coherent multidimensional spectroscopy measurements provide more detailed information on the dynamics by alleviating spectral congestion, resolving vibrational modes in the excited state, and elucidating solvation dynamics and other relaxation processes. The comprehensive spectroscopic approach yields a deeper understanding of the combined role of intramolecular structural rearrangement and solvation dynamics in symmetry-breaking charge transfer processes that are important for solar energy conversion and other applications. 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

With the projected growth in renewable energy and technology sectors along with their increasing reliance on critical minerals such as rare earth elements, yttrium, and manganese, identifying domestic sources of these critical minerals is essential. Large volumes of solid waste containing critical minerals are generated every year as a byproduct of acid mine drainage remediation. Within the United States, acid mine drainage remains an ongoing environmental issue. This research will examine the potential of adapting acid mine drainage remediation systems to produce critical minerals in economically viable concentrations. The research will support STEM education initiatives by providing training in the field and lab at both undergraduate and graduate levels, as well as hands-on activities in multiple introductory geoscience courses. This work will contribute to developing a more knowledgeable STEM workforce and a more efficient, economical, and environmentally sustainable approach for critical mineral recovery from unconventional domestic sources. The research will investigate the impact of a variety of biogeochemical conditions (such as pH, sulfate concentrations, and the presence of microbes) on rare earth elements and yttrium (REYs) uptake by hydrous manganese (Mn) oxide minerals in acid mine drainage remediation systems. With research comprising both laboratory and field experiments, the results will provide a comprehensive understanding of REY-hydrous Mn oxide mineral interactions. Multiple microcharacterization techniques (including advanced spectroscopic techniques such as synchrotron-based X-ray absorption spectroscopy) along with sequential extractions will provide a comprehensive understanding of REY sorption behaviors and mobilization. These results will help identify the optimal conditions for concentrating REYs in acid mine drainage remediation systems for the recovery of these critical minerals from unconventional domestic sources, while remediating harmful metal-laden acid mine drainage. 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

NSF Abstract for Public Dissemination – Professor Yiming Wang With the support of the Chemical Synthesis Program in the Division of Chemistry, Professor Yiming Wang at the University of Pittsburgh is studying the development of catalysts (additives that help to make a reaction proceed more efficiently and/or faster) based on iridium for the selective preparation of chemical compounds with well-defined configurations in three-dimensional space. This approach will use relatively simple chemical building blocks containing triple-bonded hydrocarbons, known as alkynes, as starting materials for the synthesis of products that contain new bonds to a variety of elements including sulfur, silicon, germanium, and tin, as well as molecular groupings that contain fluorine which are found in various pharmaceutical candidates. That substrates that are related to the products from these studies are valuable precursors to a range of other molecules makes this work relevant to several industries including those focused on polymers and materials, pharmaceuticals, and fine chemicals. In addition, the Wang group will also use the developed reactions for the chemical synthesis of several biologically active compounds that have been isolated from nature and thave the potential to be used as therapeutics. In addition to improving our ability to access complex molecules, the PI will broaden the teaching of metal-catalyzed reactions to students in both lecture and laboratory settings, as well as perform outreach to the broader community to disseminate the impact of transition metal catalysis on society with a focus on sustainability. Professor Yiming Wang’s lab will investigate the use of chiral, enantiopure phosphoramidite complexes of iridium for the C–H functionalization of alkynes at the propargylic position in an enantioselective manner. This approach will deliver highly enantioenriched propargylic thioethers, silanes, germanes, and stannanes along with several classes of compounds bearing fluorination. These studies will be broadly impactful on industries that make products ranging from polymers to medicines. This technology will also be applied to C–C bond formation and is expected to find utility in the enantioselective synthesis of a range of pyrrolizidine alkaloids, as well as cyclopropanes and heterocyclic compounds bearing multiple stereocenters. 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

The project will conduct research on the numerical solution of turbulent flows. Fluids transport and mix heat, chemical species, and contaminants. Accurate simulation of turbulent flow is essential for safety critical prediction and design in applications involving these and other effects. Turbulent flow prediction in science , engineering and industry requires the use of turbulence models. The research project has 3 objectives: increasing accuracy of these models, decreasing model complexity and exploring a promising algorithmic idea for computer solution of models. The proposed research also develops the expertise of graduate students in computational and applied mathematics while working on compelling problems addressing human needs. In their development into independent scientists, each student will develop their own research agenda and collaborate at points of contact among the problems studied. Modeling turbulence presents challenges at every level in every discipline it touches. 2-equation Unsteady Reynolds Averaged Navier-Stokes models are common in applications and also the ones with the most incomplete mathematical foundation. They have many calibration parameters, work acceptably for flows similar to the calibration data set and require users to have an intuition about which model predictions to accept and which to ignore. The project’s model analysis will address model accuracy, complexity and reliability. Even after modeling, greater computational resources are often required for their computational solution. In 1991 Ramshaw and Mesina proposed a non-obvious synthesis of penalty and artificial compression methods, resulting in a dispersive regularization of fluid motion. When the two effects were balanced, they reported a dramatic accuracy improvement over the most efficient current methods. The project will develop, improve and test the method based on a new analysis of energy flow. 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

Long-duration energy storage (LDES) technologies provide numerous societal benefits, including enhancing grid stability, enabling greater use of renewable energy, and reducing the dependence on fossil fuels. LDES technologies transform intermittent renewable resources, such as solar and wind power, into dispatchable power sources. Among the available options for LDES are redox flow batteries (RFBs), which store energy electrochemically and feature significant operational flexibility, modularity, and cost advantages. Nonetheless, key challenges remain in developing energy carriers for RFBs, including cost and performance barriers stemming from fundamental limitations in their chemical properties. This research will focus on designing new chemical compounds, called biphasic charge carriers, that can store electric power, and link the fundamental chemical properties of these charge carriers to their function in small-scale working batteries. The goal is to develop a clear set of design principles for a new generation of batteries purpose-built for storing solar and wind power. This research project integrates hardware prototypes under active development by a startup company founded out of one of the participating laboratories, enabling further potential for societal impacts through commercialization and entrepreneurship. Additionally, a new training curriculum for undergraduate students will be developed to learn the fundamentals of electrochemistry and battery science. Work will be undertaken to deploy a series of educational outreach activities encompassing the development of low-cost hardware and software tools to support broader dissemination via the delivery of new laboratory courses at the participating universities, education research literature, and digital media. This project will develop design rules for inorganic charge carriers for redox flow batteries. The overarching objective is to overcome hurdles related to energy density and materials availability by developing redox-active molecules that store charge both as soluble units and in the solid phase. This feature opens opportunities to explore new RFB designs, beyond aqueous transition metal complexes, via the development of biphasic charge carriers, wherein soluble forms of a given molecule are used as mediators to shuttle charge to or from the solid form of the same molecule. The project encompasses hypothesis-driven studies directed at controlling molecular solubility across multiple charge states via ligand modification, alongside detailed investigations of charge transfer at interfaces between the electrode and the electrolyte and between the electrolyte and the solid-state charge carrier. Successful completion of this work will yield lab-scale biphasic battery systems with promising functional properties that can be fully rationalized from basic physical properties, entailing extensive opportunities for further 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 · 2024-08

Pathogenic bacteria have developed elaborate mechanism to defend themselves from high concentrations of toxic metal ions. These bacteria contain proteins that have high affinity to these metal ions, and in the presence of these metal ions initiate the generation of other proteins that rapidly remove the metal ion, convert them to less toxic redox states, or initiate other regulatory processes. This project will generate a holistic understanding of this sensing and transcription mechanism of a copper regulator in pathogenic bacterial cells. An understanding of the microscopic structural details of function is challenging given the absolute need to measure structural constraints and conformational changes that result upon interaction with metal ions as well as DNA. Measurement of such processes are often inaccessible to traditional structural techniques due to size of the full complexes, timescales of conformational changes, low solubility of the protein-DNA complex in the presence of metal ions, and the need to examine conformations at different ratios of the components (protein, DNA, and metal ions). This project will develop spin labeling strategies to be used in Electron Paramagnetic Resonance (EPR) Spectroscopy to shed light on the atomic level details of the conformational and structural adaptation that leads to protein function. Understanding the mechanistic details at an atomic-level detail enhances our ability to reduce this protective function in the cell, and thereby providing a new way to destroy pathogenic bacteria. Another centrally innovative aspect of this project is that the work will provide the wider biophysical community with new approaches to measure structural constraints. The project will train a diverse team of students at the interdisciplinary interface of Chemistry and Biophysics, promote access to EPR to four-year colleges, and create career awareness opportunities for K-12 students. More specifically, this NSF-BSF project will develop experimental EPR methodology and associated simulation methodology to elucidate the sensing and transcription mechanism of copper-inducible repressor, CopY. The CopY protein is a transcriptional regulator found in gram-positive bacteria such as Enterococcus and Streptococcus. CopY represses the transcription of metal regulatory proteins by binding to a specific DNA operon sequence. In the presence of Cu(I), the protein unbinds from DNA, thereby allowing RNA polymerase to access the promoter region to express proteins that remove toxic Cu(I) from the cell. Thus, the protein plays a crucial role in protecting the bacteria from toxic metal stress. The project will develop methods to improve the sensitivity of pulsed EPR distance measurement methods and generate orthogonal labeling schemes based on a novel site-directed spin label pioneered by the PI’s group; and elucidate the amplitude and nature of conformational changes in both protein and DNA that lead to the initiation of transcription. This collaborative US/Israel project is supported by the US National Science Foundation and the Israeli Binational Science Foundation. 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

The investigator pursues projects that combine questions in mathematical analysis, differential geometry, calculus of variations, materials science and engineering design. The key components are: (i) seeking to determine mechanical theories of thin multi-dimensional films with nonzero stored energy due to shape-formation processes such as growth or plasticity; (ii) the quest for regularity of solutions to a class of partial differential equations arising when the aforementioned prestrained films deform in order to release their energies; (iii) describing properties of “kirigamized” sheets, namely thin films with cuts of different geometries and distributions. Some of these projects are accessible to graduate students and contribute to their training. The related analytical projects include: (i) dimension reduction in nonlinear elasticity of prestrained materials, in function of the general prestrain given by a Riemannian metric, Gamma-convergence and rigidity estimates; (ii) convex integration and flexibility in the Holder regularity classes for the Monge-Ampere system and the k-Hessian system; and (iii) investigating structure and rectifiablity of geodesics in the kirigamized sheets in relation to the sheet’s deployment trajectory. 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

The broader impact of this I-Corps project is the development of a tool to reduce damage when harvesting veins used for coronary artery bypass grafting surgery. Heart disease is the leading cause of death in the U.S., with approximately 700,000 deaths annually from various heart conditions. Patients with coronary artery disease can suffer from unexpected heart attacks unless the blockages are removed or bypassed. Heart surgery carries significant costs for materials and tools that are currently used to harvest veins in the leg for coronary artery bypass surgery. Physician assistants and cardiothoracic surgeons have identified several issues using the current electrocautery devices on the market due to device failure during operation, added costs for the tool, added surgical time if bleeding occurs, and potential damage to the vein graft that can lead to poor outcomes after surgery. This solution has the potential to introduce a technology to reduce costs, surgical time, and damage to veins during harvesting. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a method to mechanically cut and clip veins during endovascular vein harvesting. To treat coronary artery disease patients, physicians perform a surgical procedure to replace a patient's damaged blood vessel with a suitable graft that is harvested from elsewhere in the body. The most common blood vessel used is the great saphenous vein in the leg. Harvesting is currently performed with electrocauterization tools that can cause unnecessary harm to the patient and result in poor patient outcomes. Electrocautery has been observed to fail to effectively seal the larger blood vessels while harvesting, damage tissue, and fail to cut through side vein branches. This technology is a purely mechanical tool that can cut through a blood vessel while clamping the side branches of veins shut. The tool is designed to provide physicians with a simpler, safer tool for harvesting procedures, which ultimately benefits the patients undergoing these procedures. 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

In order to predict the future evolution of Earth’s climate, it is important to understand and quantify the processes that govern vertical mixing of heat and CO2 in the ocean, such as tides, internal waves and others. The degree to which the motion of small organisms such as zooplankton can contribute to this mixing is currently unknown, although several hypotheses have been forwarded that arrive at very different conclusions. The current project aims to improve the understanding of such biogenic mixing via a collaborative investigation that combines theoretical analysis with laboratory experiments and detailed computer simulations. In this way, the project results will enable more accurate predictions of future climate trends. The project will involve significant educational and outreach activities, including research by undergraduate and high school students. While it has been proposed that biologically generated turbulence plays an important role in oceanic turbulence, the range of zooplankton swimmer sizes that can contribute to such mixing is currently unknown. Recent research indicates that the minimum swimmer required depends on the nature of the flow field in which the swimmer moves, so that the capability of a swimmer to produce sustainable biogenic turbulence is not an inherent and static characteristic, but rather, it is modulated by the swimmer’s orientation in relation to the local shear and the intensity of the ambient hydrodynamic shear. The objective of the proposed research is to employ both laboratory experiments and direct numerical simulations (DNS) to reveal the minimum size and the corresponding biogenic turbulence production mechanism in a space spanned by the strength of the background shear, the orientation of the swimmer with regard to this shear, and the swimmer size. On this basis, models for the incorporation of these effects into ocean simulation tools will be developed. The experiments will use a unique system that can produce accurate on-demand migrations of zooplankton via phototaxis in a background shear in a controlled laboratory setting. The computational methodology is based on a well-validated immersed boundary method approach, and it employs an established squirmer model to represent the individual organisms. The proposed research will reveal how the swimmer’s agitation produces turbulence and dissipation. It will be the first systematic experimental and numerical study of biogenic turbulence considering both swimmer and background flow. Although the research is motivated by ocean flows, the insights gained from the project will deepen our understanding of how physical perturbations affect turbulent flows in general. 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

This grant supports research that intends to advance fundamental science needed to improve semiconductor microchip manufacturing, an enabling technology for automation, robotics, machine-learning, and other key drivers of the US economy. As microchip components shrink ever-smaller, national reports have identified a key barrier for their technological advancement, which is the robotic manipulation of the chips with near atomic-scale precision. This research seeks to eliminate this barrier by improving the scientific understanding of how microchip materials adhere to the manufacturing equipment in the presence of humidity. Humidity determines how microchips stick because it leads to tiny water bridges between the contacting bodies. These capillary bridges resist stretching and act like a glue keeping the contact together. Insights are generated through advanced experimental measurements on technology-relevant materials, combined with computer simulations, theory, and machine learning. The goal is to predict and control unwanted positional slipping, enabling the creation of the next generation of microchips with greater performance, better reliability, and lower cost. This is a collaboration between modeling by the German team and experiments by the US team. This project bolsters the current manufacturing workforce by (1) making all models and results publicly available using a free-to-use web application; (2) funding The Surface-Topography Challenge, an international open-science effort to better understand surface properties; and (3) training industry leaders via manufacturing-focused Centers at the University of Pittsburgh. It develops the next-generation manufacturing workforce by developing a project-based engineering unit for K-12 students. This project supports research that develops fundamental understanding of how adhesion in semiconductor manufacturing is controlled by a combination of chemistry, mechanical properties, and surface topography of the substrate surfaces. The existing scientific framework for capillary adhesion cannot adequately describe the performance of the wafer-handling equipment, which has complex multi-scale topography that evolves over time during high-volume manufacturing. The central hypothesis of this project is that the formation, deformation, and percolation of capillary bridges determines the adhesive force in humid environments and is controlled by topography at multiple length scales. To test this hypothesis, this research experimentally measures the co-evolution of adhesion and topography (down to the atomic scale) over time during tool use. These experiments are combined with physics-based and data-driven modeling to describe the behavior of the liquid capillaries during adhesion. Scientifically, the goal is to create a new class of humid-adhesion models that account for the complex, multi-scale topography of wafers and manufacturing equipment. Technologically, these experimentally validated, science-guided insights into the attributes of surfaces that control adhesion guide the development of high-performance and long-lifetime equipment for next-generation semiconductor manufacturing. 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.