Category: Notable Grants

A crop’s traits and 3D structure (the shape and architecture of plants, including both above- and below-ground parts) are the attributes that chiefly influence crop growth and yield and provide critical evidence for plant phenotyping (the characterization assessment of plant traits). Crop yield predictions can be made by assessing 3D plant structures using crop sensing methods. However, crop sensing results at different scales are usually analyzed in isolation, which overlooks essential connections. Moreover, while root systems play a central role in plant functions, current methods mainly assess crops based on above-ground crop structure due to the difficulty of accessing roots. Current methods use satellites for remote sensing and drones for local sensing, enabling crop assessment at varying scales; however, it is difficult to integrate these observations effectively, and the information stream is formidable. The overarching objective of this project is to develop a novel AI infrastructure to integrate these observations to model and assess 3D crop structures at multiple scales and enhance below-ground sensing capabilities. Using this infrastructure, 3D crop structures can be estimated accurately at the individual, farm, and satellite scales, facilitating crop assessment and yield prediction. The project dramatically enhances and accelerates the ability of growers and agronomists to assess critical crop field structural variation for both above- and below-ground components, enabling large-scale crop management. This project also benefits students, from the high school to the Ph.D. level, by applying multi-scale 3D models of above- and below-ground crop structures to immersive education methods (Virtual Reality (VR), Augmented Reality (AR), and online learning), which are well-suited to solving the challenges of distance learning, especially for subjects like agriculture requiring field study. The multi-scale sensing system is also capable of estimating 3D landscape structures and large-scale crop structures and can be utilized in other areas, such as Arctic Sea ice modeling, forestry, and climate change studies. This project aims to connect a plant’s structural phenotypes below- and above-ground and link in-situ measurements to satellite sensing data, thus enabling non-destructive crop root sensing and root-system status estimation based on observation of plant growth above-ground while at the same time empowering satellite images to assess these factors to furnish more local and detailed information. This project establishes a method for 3D crop sensing of individual plants, crop fields, and satellite regions to provide multi-scale crop structural evidence for crop assessment and yield prediction. This project also develops a novel AI neural network to sense root structures and predict traits based on sensing above-ground plant structures.

This project investigates methods for satellite-based 3D sensing and nondestructive below-ground root sensing. Novel AI infrastructures are explored to address critical issues in computer vision and remote sensing, efficient integration of multi-scale sensing, 3D structure prediction, and spatial-temporal 4D inference. Such an approach can lower the ceiling for operational adoption of satellite and in-situ imagery assessments, based on a scientifically underpinned, multi-scale, 3D assessment workflow. In addition to its essential and practical implications for agriculture professionals, this project also explores novel AI solutions within computer vision and remote sensing. Crop structures are highly diverse, complicated, and changing phenomena. Therefore, agriculture presents an ideal research domain for investigating novel AI methods. This research advances AI by 1) largely improving the fusion effectiveness of various remote sensing modalities from sensors mounted on different devices, 2) significantly enhancing the learning capability by connecting sensing outputs expressed in multiple scales, 3) enabling 3D structure prediction for objects across different domains, and 4) providing future status prediction based on 4D spatial-temporal neural networks.

Funder: National Science Foundation 

Amount: $549,928 

PI: Guoyu Lu, College of Engineering 

Coastal marshes provide a suite of vital functions that support natural and human communities. Humans frequently take for granted and exploit these ecosystem services without fully understanding the ecological feedbacks, linkages, and interdependencies of these processes to the wider ecosystem. As demands on coastal ecosystem services have risen, marshes have experienced substantial loss due to direct and indirect impacts from human activity. The rapidly changing coastal ecosystems of Louisiana provide a natural experiment for understanding how coastal change alters ecosystem function. This project is developing new metrics and tools to assess food web variability and test hypotheses on biodiversity and ecosystem function in coastal Louisiana. The research is determining how changing habitat configuration alters the distribution of energy across the seascape in a multitrophic system. This work is engaging students from the University of Louisiana Lafayette and Dillard University in placed-based learning by immersing them in the research and local restoration efforts to address land loss and preserve critical ecosystem services. Students are developing a deeper understanding of the complex issues facing coastal regions through formal course work, directed field work, and outreach. Students are interacting with stakeholders and managers who are currently battling coastal change. Their directed research projects are documenting changes in coastal habitat and coupling this knowledge with the consequences to ecosystems and the people who depend on them. By participating in the project students are emerging with knowledge and training that is making them into informed citizens and capable stewards of the future of our coastal ecosystems, while also preparing them for careers in STEM. The project is supporting two graduate students and a post-doc. The transformation and movement of energy through a food web are key links between biodiversity and ecosystem function. A major hurdle to testing biodiversity ecosystem function theory is a limited ability to assess food web variability in space and time. This research is quantifying changing seascape structure, species diversity, and food web structure to better understand the relationship between biodiversity and energy flow through ecosystems. The project uses cutting edge tools and metrics to test hypotheses on how the distribution, abundance, and diversity of key species are altered by ecosystem change and how this affects function. The hypotheses driving the research are: 1) habitat is a more important indirect driver of trophic structure than a direct change to primary trophic pathways; and 2) horizontal and vertical diversity increases with habitat resource index. Stable isotope analysis is characterizing energy flow through the food web. Changes in horizontal and vertical diversity in a multitrophic system are being quantified using aerial surveys and field sampling. To assess the spatial and temporal change in food web resources, the project is combining results from stable isotope analysis and drone-based remote sensing technology to generate consumer specific energetic seascape maps (E-scapes) and trophic niche metrics. In combination these new metrics are providing insight into species’ responses to changing food web function across the seascape and through time.

Funder: National Science Foundation 

Amount: $688,849 

PI: Jimmy Nelson, Franklin College of Arts and Sciences, Department of Marine Sciences 

Georgia has a rich agricultural history in fresh produce, owing to its long growing season. Creation of value-added markets would provide a valuable source of income to growers during times where fresh produce is not actively being grown and harvested. In rural areas where farms are primarily located, many entrepreneurs lack accessibility to appropriate business development resources and thus opportunities to break into value-added markets are limited. The proposed Value-addition Institute for Business Expansion (VIBE), an Agriculture Innovation Center (AIC), located at the University of Georgia (UGA) – Department of Food Science and Technology (FST) aims to support food businesses based in rural communities of GA to commercialize new value-added foods. The proposed AIC will provide technical assistance on food product development, scaled-up processing and access to mini-grants to producers throughout Georgia to enable them to take the steps necessary to commercialize their products. The AIC aims to do this by accomplishing the following objectives: (1) Perform a needs assessment in rural, distressed communities in Georgia, (2) Establish a Georgia-specific network of providers for business development services, (3) Build capacity for farmers seeking to enter value-added markets, (4) Develop multiplatform training materials and workshops related to process and product development, and (5) Administer mini-grants to producers to facilitate access to services and support required to start a new business or scale up an existing business. Georgia currently has a significant number of resources devoted to building and running a business, as evidenced by letters from our key partners, but there is a gap in programs specifically related to process and product development of foods that will bridge initial business development steps with production runs and marketing. Center personnel will evaluate the product prototype and work with clients to identify equipment capable of replicating the process and operating at the desired scale, with consideration to product characteristics (quality and safety) and cost analysis. Mini-grants will be distributed through a competitive application process. In addition to those companies who receive mini grants, we plan to provide consultation services to ~20 companies per year, evenly split between PD Casulli and co-PD Mis Solval. Preference will be given to rural communities in Georgia with high levels of distress.

Funder: U.S. Department of Agriculture 

Amount: $978,545 

PI: Kaitlyn Casulli, College of Agricultural and Environmental Sciences 

A manufactured product is the end of a long chain of interwoven manufacturing steps that may span geography, industries, and manufacturing processes. Each step may be optimized, yet for a step there may be uncertainty about the larger context of its contribution that if known during production would allow for greater efficiencies, better quality, and improved productivity. If a global system analysis and optimization could, in addition, be conducted cooperatively with each step during production, the end product and overall production would greatly benefit. Advances in hybrid distributed control and optimization, in highly networked cyber-physical systems, and in artificial intelligence and machine learning have opened new opportunities in cyber-enabled manufacturing. This Future Manufacturing Research Grant (FMRG) CyberManufacturing project connects and coordinates the ensemble of various manufacturing processes, operating at different manufacturing stages under a cyber-coordinated close-knit system, defined by an analytical framework, known as STREAM, a multi-stage distributed future manufacturing system. This project provides a public online repository that hosts the STREAM data, models, simulators, controllers, analytics, and empirical studies, and that facilitates sharing research experiences about STREAM with the research and industry communities. The project creates new outreach and workforce development activities for K-12, undergraduate and graduate students, as well as working professionals in the field of manufacturing. These research results will be included in the university curriculum for advanced manufacturing, architecture design, machine learning, simulation, and system control and optimization. This project is an interdisciplinary research project with three interconnected research tasks: (1) STREAM architecture design and implementation. There is a novel bridging middleware architecture to enable seamless machine interoperability, and software- and hardware-based accelerators will be built to enable efficient communication and computing in cyber-manufacturing systems. (2) STREAM modeling and quality control. There is a novel multi-layer functional graphical model to address the high-dimensional functional dependencies over STREAM machines and a spatial-temporal iterative learning control method to achieve an accurate and efficient process quality control. (3) STREAM simulation and production control. To handle the multi-level dynamic process interactions in the system that collectively meet process quality, cost, and resource constraints, there are coordinated, high-fidelity multi-resolution simulators, assisting with the hybrid control of STREAM production. These research tasks are validated in an open-source additive manufacturing testbed for the manufacture of high energy/power density supercapacitors. The modeling and analysis methodologies form a rigorous basis for continuous improvement of quality, manufacturability, and productivity of future multi-stage and distributed manufacturing systems.

Funder: National Science Foundation 

Amount: $2,333,085 

PI: Hongyue Sun, Franklin College of Arts and Sciences, Department of Statistics 

Seasonal influenza viruses cause significant disease burden. While seasonal influenza vaccines are available, these are often poorly efficacious due to mismatch with circulating virus strains, particularly in the populations at greatest risk of complications from infection, including the elderly, infant, and immunocompromised. Influenza A viruses (IAV) also pose a pandemic risk for which seasonal influenza vaccines provide no cross protection. In 2018, the National Institute of Allergy and Infectious Diseases (NIAID) released a strategic plan for developing a universal influenza vaccine and subsequently released the FOA PA-18-859, “Advancing Research Needed to Develop a Universal Influenza Vaccine.” The long-term goal of this proposal is to develop a universal influenza vaccine. We hypothesize that a flu vaccine composed of broadly cross-reactive B-and T-epitopes covalently linked to an immune adjuvant will elicit potent immune responses and protect against diverse influenza A virus infections and associated disease. This expectation is supported by our prior studies which demonstrated a fully multi- component vaccine composed of tumor associated glycopeptide B- and CTL-epitope, a peptide CD4 T cell epitope and a TLR2 agonist (Pam3CysSK4) elicited robust immune responses and protected against a stringent tumor challenge in a murine cancer model. We will chemically synthesize multi-component vaccines that are composed of conserved peptide antigens derived from IAV and an adjuvant such as Pam3CysSK4 or monophosphoryl lipid A (Aim 1). In addition, we will employ an enzymatic glycan remodeling strategy to modify recombinant hemagglutinin (rHA), which is used as a licensed flu vaccine, with various TLR agonists and DC targeting moieties (Aim 2). It is expected that the self-adjuvanting rHA vaccines will enhance antigenicity of conserved but poorly immunogenic stalk domain thereby providing heterologous protection. We will also explore whether covalent attachment of immune-potentiators to recombinant neuramidase (rHA) can enhance its immunogenicity and provide broad protection (Aim 3). The

immunogenicity and efficacy of the vaccine candidates will be evaluated in murine and ferret vaccination and challenge models, using innovative approaches and antigen probes to assess polyfunctional T cell responses and geminal center (GC) B cell response. This research is significant as it directly addresses multiple NIAID priorities in their strategic plan for developing a universal influenza vaccine. The results of these studies could have a significant impact as the universal influenza vaccines developed should be suitable for advancement to pre-clinical studies. Moreover, the adjuvants and approaches developed in this proposal will be applicable to other vaccines and study of the host response to influenza infection, and will have broader impacts beyond universal influenza vaccine development.

Funder: National Institutes of Health 

Amount: $3,294,848 

PI: Geert-Jan Boons, Franklin College of Arts and Sciences Department of Chemistry 

With support from the Chemical Structure, Dynamics, and Mechanisms A (CSDM-A) program in the Division of Chemistry, Melanie Reber of the University of Georgia is developing methods capable of measuring transient changes in the absorption spectra of molecules in the gas phase. Gas phase measurements, specifically in a molecular beam, allow for detailed study of the role of vibrations in excited state processes with a direct comparison to theoretical predictions. Molecular beams provide a cold and controlled environment for generating and studying small molecules but require high detection sensitivity due to the low number densities. Reber and her students will use optical enhancement cavities to increase the detection sensitivity of ultrafast transient absorption spectroscopy. Their discoveries could lead to a more complete understanding of conical intersections in vibrational excited states of organic molecules and radicals. As part of the educational component, Dr. Reber will explore how the use of art and music in teaching science impacts student learning and retention of students from all backgrounds. The students involved in the project will gain highly technical training in lasers, optics, and electronics relevant to a range of high technology fields including quantum technologies. To broaden participation and awareness of the interdisciplinary fields of physical chemistry and quantum science, Reber will teach a class for incoming first-year undergraduate students to introduce them to the science, technology, and application of quantum science. The project will look at the molecular dynamics around conical intersections with both ultrafast time resolution and high spectral resolution for a detailed characterization of the dynamics. This includes the development of new instrumental techniques that study ultrafast dynamics of molecules in the gas phase with both ultrafast time resolution and high-resolution detection. The team uses ultrafast frequency comb fiber lasers in the visible and infrared spectral regions and couples them to external optical enhancement cavities to increase the signal. This enables study of dilute species in molecular beams with ultrafast transient absorption spectroscopy. Dual comb detection techniques will be developed to provide quantum-state resolution on the absorption spectra of the resultant species. The overarching objective is to study conical intersections in excited electronic states and conical intersections between vibrational states, such as Jahn-Teller interactions. This study aims to provide a detailed description of the dynamics in the gas phase for direct comparison with theory and a more complete picture of the quantum effects in the dynamics.

Funder: National Science Foundation

Amount: $675,000

PI: Melanie Reber, Franklin College of Arts and Sciences, Department of Chemistry

With the support of the Chemical Synthesis program in the Division of Chemistry, Christopher Newton of the University of Georgia is designing novel molecular “building blocks” that improve the reactivity and versatility of molecular addition reactions. These addition reactions enable the rapid construction of complex organic molecules through the joining of two simpler fragments and this research aims to address long-standing challenges in the field that have limited its applications. The targeted reactions are expected to lead to a diverse set of cyclic structures containing carbon, oxygen, and nitrogen atoms. Detailed studies of the mechanisms underpinning these transformations will also be undertaken, helping to facilitate future discoveries. The outcomes of this research stand to have broad scientific and societal impacts including in the pharmaceutical, material, and agrochemical industries. The funded research will also support the training of a diverse body of undergraduate and graduate students in state-of-the-art chemistry techniques, helping to strengthen the future STEM (science, technology, engineering and mathematics) workforce in the United States. In addition, Dr. Newton and his team will work to create and disseminate free, open-access chemistry educational tools to reduce barriers and broaden engagement in STEM. Finally, this award will support an outreach program, in collaboration with local high school teachers, to provide hands-on laboratory experience and career guidance to the greater Athens, GA community. The overarching goal of the research program under the guidance of Christopher Newton is to develop novel, pericyclic-based strategies for the convergent synthesis of high-value complex ring systems. This study aims to tailor the reactivity of cycloaddition reactions, including the venerable Diels-Alder reaction, through the use of atypical, high oxidation state building blocks. The joining of these novel fragments leads to products of increased complexity and functionality when compared to current state-of-the-art approaches. The research plan has three distinct objectives: (i) development of the first general family of cross-coupling active Diels-Alder dienes, (ii) a one-step Diels-Alder/ring expansion route to 7- and 8-membered hetero- and carbocyclic motifs, and (iii) development of a novel, highly reactive class of aza-dienophiles. Success in these endeavors is anticipated to provide efficient access to a plethora of highly functionalized, biologically active polycyclic molecules, while also furthering fundamental understanding of structure and reactivity in this important area of reaction modality.

Funder: National Science Foundation

Amount: $770,000

PI: Christopher Newton, Franklin College of Arts and Sciences, Department of Chemistry

Cilia are thread-like microtubule-based cell extensions which function in cell locomotion, fluid transport, and signaling. Many developmental disorders and diseases are caused by defects in ciliary function and assembly. To assemble cilia of a specific size and composition, cells have to transport hundreds of different proteins from the cell body into the organelle. Intraflagellar transport (IFT), a bidirectional motility of protein particles along ciliary microtubules, is assumed to be the major pathway for protein transport in cilia. IFT is required for ciliary assembly, maintenance, and signaling, however, it remains largely unknown which proteins are transported by IFT. It is also unclear where in the cilium cargoes are unloaded from IFT and whether the amount of protein transported by IFT is regulated. Because ciliary proteins are likely to be transported as single molecules or in small clusters, the analysis of their transport requires a highly sensitive imaging technique. Using Total Internal Reflection Fluorescence (TIRF) microscopy, we have established in vivo imaging of protein transport by IFT in cilia. We will analyze protein transport in cilia using the unicelluar model Chlamydomonas reinhardtii, which allows us to combine high resolution imaging in cilia with genetic manipulation and biochemical analysis of the organelle. We performed a comprehensive analysis of ciliary transport of the axonemal protein DRC4 and showed that DRC4-GFP depends on IFT for ciliary entry and distribution along the organelle. In Specific Aim 1, we will image distinct proteins selected from different ciliary compartments and substructures to determine how they interact with IFT to move into cilia. We will address the question of how IFT particles serve as carriers for many distinct proteins and how IFT transports proteins in the correct ratio into the organelle. We will test whether protein loading onto IFT particles depends on protein supply in the cell body and to which extent unloading of cargoes from IFT is spatially controlled. Our data show that the transport frequency of DRC4 is greatly increased when cilia grow, suggesting that the capacity of the IFT pathway can be modulated. The regulation of IFT is the focus of Specific Aim 2. We will analyze whether IFT particles isolated from growing and steady-state cilia are biochemically distinct and how cargo transport is affected in IFT mutants with small defects in the particle. The control of cargo influx is likely to be a prerequisite to establish a specific length of cilia, which is critical for its motile and signaling functions. We will analyze IFT and cargo transport in mutants with defects in ciliary length regulation such as long flagella 2 (lf2). LF2 encodes a widely conserved CDK-like kinase with an emerging role in disease. IFT is disturbed in lf2 cilia; we will test the hypothesis that LF2 kinase is a regulator of IFT, which when defective results in overloading of IFT particles. We noted that IFT proteins accumulate in mutants with structural defects in cilia, which might indicate a feedback mechanism on the IFT pathway which alerts the cell of incorrectly assembled cilia. We will test whether cells use the IFT pathway to monitor the correct size and structure of cilia.

Funder: National Institutes for Health

Amount: $2,522,709

PI: Karl Lechtreck, Franklin College of Arts and Sciences, Department of Cellular Biology

Following a stroke, hand dexterity does not recover fully for most patients, significantly reducing quality of life. Optimal and effective assessment and therapies for achieving hand dexterity are currently lacking due, in part, to limited scientific knowledge of human hand dexterity in health and disease. Hand dexterity hinges on multiple essential behavioral components embedded in a highly interactive neural circuit. How the behavioral components interact and how they are supported by descending neural pathways are still unclear. The long- term goal of this research is to build a predictive model and identify key behavioral and neural principles for designing targeted therapies to facilitate the reacquisition of hand dexterity to improve quality of life. The current objective of this project is to investigate behavioral and neural mechanisms of hand dexterity and its impairment and recovery after stroke. The central hypothesis is that three essential components of hand function, finger individuation, precision grip, and power grip, largely rely on three distinct control variables, flexibility, coordination, and strength, and separable descending pathways: direct- and indirect-corticospinal tract (CST), and reticulospinal tract (RST). The rationale for this project is that directly comparing different components of dexterity using kinematics/kinetics at the same levels of granularity, combined with the most advanced measures of descending neural pathway structure and function holds promise in a new model of hand dexterity. Two specific aims are proposed to test the central hypothesis: 1) characterize effect of stroke on individuation, precision grip, and power grip; and 2) determine if stroke-related disruption in the structure and function of three descending neural pathways are associated with three behavioral components. Under Aim 1, chronic stroke patients and healthy controls’ Individuation and Precision Grip will be directly compared using isometric forces recorded in high resolution at all ten fingertips in 3D, and their interaction with Power Grip will be examined. Under Aim 2, high-resolution tractography using diffusion-weighted MRI will be obtained to assess structural integrity of the three descending pathways. Transcranial magnetic stimulation (TMS) paired with peripheral nerve stimulation will be used to assess functional involvement of the three pathways using short-, long-, and extra-long interval modulation of Hoffmann-reflex. Under Aim3, a model will be built to map severity of impairment in behavioral measures to neurophysiological markers derived from Aim 1&2 to test the hypothesis that stroke survivors’ direct-, indirect-CST and RST measures will be predictive of individuation, precision grip, and power grip behaviors, respectively. The proposal is innovative because it reconceptualizes dexterity by, for the first time, directly assessing essential components of dexterity behaviors and descending pathways with cutting-edge techniques and builds a neural model from these findings. It is significant because findings from this project will guide the creation of sensitive clinical assessments and redefine therapeutic interventions for optimal hand rehabilitation after stroke to enhance patients’ quality of life.

Funder: National Institutes for Health

Amount: $2,736,478

PI: Jing Xu, Mary Frances Early College of Education

This project aims to optimize circularity, from the city up, transforming the linear consumption model of raw material extraction, production, use, and disposal that dominates the global economy. This linear model has led to serious unintended worldwide issues, from pollution to resource depletion. This project will reimagine how we design, from molecules and materials to buildings and communities. The newly updated and expanded Circularity Assessment Protocol (CAP) framework will be co-implemented with 11 cities. CAP integrates the open data tool Debris Tracker with data freely available, joining data from nearly 100 countries around the world. The new portal for this project will house the data from Phase I and Phase II communities aiming to foster global dialogue about community circularity and creating meaningful change. To increase circularity, the researchers will help communities address systemic and intersectional issues, including pollution burdens, lack of infrastructure, and lack of access to services. The project will further develop a platform for underrepresented voices through an existing podcast called Aquathread, produced and recorded at WUGA, the University of Georgia’s NPR affiliate. This research will continue to increase public scientific literacy and engagement with science and technology through the use of open data and free mobile citizen science apps; improve the well-being of individuals in society by reducing waste and improving the built environment; and develop a diverse, globally competitive workforce. All communities, partners, and the public will have access to project data, facilitating the use of science and technology to inform public policy and support decision-making. In contrast to the linear economy of “take, make, waste,” circular economy (CE) decouples economic growth from resource consumption. CE principles are based on the efficient use of resources and eliminating waste from product life cycles. This project will tackle the complex challenges that currently inhibit the circular economy’s growth by deeply integrating diverse disciplines through the researchers’ proven holistic systems framework. In Phase II, the newly updated and expanded Circularity Assessment Protocol (CAP) framework will be used to converge circularity across plastics (exploring polyfluoroalkyl substance-free alternatives), organic materials, and the built environment in 11 cities. In Phase I of this project, a circularity path was connected and converged across multiple materials and scales in two large metropolitan areas. Phase II will expand this work by training local implementation partners, and further developing a novel dynamic data and education portal. This portal will include city and metadata dashboards to facilitate inter- and intra-community dialogue to create systems change. Project partners include the Resilient Cities Network, a city-led network that brings together over 200 Chief Resilience Officers, practitioners, and researchers; the 2030 Districts Network of cities working to catalyze transformation in the built environment to mitigate the effects of climate change; Mississippi River Cities and Towns Initiative Mayors; and the Upper Midwest Association for Campus Sustainability (UMACS). This network of networks is the next step in expanding this project into a sustainable future as a continued resource and platform for sharing amongst cities around the world catalyzing change.

Funder: National Science Foundation

Amount: $5,000,000

PI: Jenna Jambeck, Institute for Resilient Infrastructure Systems