Data management plan for the grant, "Conference: Dynamical Systems and Fractal Geometry."

Data management plan for a grant seeking to analyze existing support structures for transfer students in Chemistry between the University of North Texas and Dallas College.

Data management plan for the grant "Formation of cotton bast fiber as a means to modulate carbon capture and increase bio-product utilization."

Data management plan for the grant, "A Laser Microdissection System to Enhance Agricultural and Food Research in the North Texas and Southern Oklahoma Region."

Data management plan for the research grant "Generating pathogen- / pest-resistant non-GMO cotton through targeted genome editing of oxylipin signaling pathways."

Data management plan for the grant, "Collaborative Research: Conference: Texas-Oklahoma Representations and Automorphic forms (TORA)."

Data management plan for the grant, "Non-Genetic Inheritance of Hypoxia Tolerance in Fishes: Dynamics and Mechanisms." Research quantifying the inheritance of tolerance to low oxygen in a model fish and then determine the tolerance mechanisms, at organismal to molecular levels, that are passed on from parents to their offspring. The investigators will not only focus on conventional, well-studied genetic mechanisms for inheritance, but will explore so-called “epigenetic” forms of inheritance that may transfer parental characteristics for only a generation or two. Such “temporary inheritance” might actually require less energy and be more beneficial to a species than the more permanent form of genetic inheritance. This project will quantify non-genetic inheritance of hypoxia tolerance in zebrafish as a model organism and then identify underlying mechanisms, at organismal to molecular levels, in parents and in their progeny. Specifically, this project will quantify non-genetically inherited traits that allow hypoxia tolerance, determine “wash-in” and “wash-out” (i.e., the dynamics) of hypoxia-tolerant phenotypes across multiple generations, and establish epigenetic mechanism(s) of non-genetic inheritance in subsequent generations. The information provided by this project will allow biologists to better predict, and perhaps even mitigate, the negative consequences of future episodes of low oxygen in rivers and lakes.

Data management plan for the grant "Expanding A Bilingual Trauma-Based Behavioral Health Workforce in Integrated Health Settings."

Data management plan for the grant, "Fatty Acid Amide Hydrolases and Chemical Communication in Plants." Research seeking to understand how an evolutionarily-conserved group of plant enzymes utilizes chemical signals to regulate growth and to influence their microbial environment. Specific research aims include the discovery of new enzymes and their substrate molecules that act as communication signals. Broader applications of this research may offer new strategies to enhance agricultural outputs by manipulating plant-microbe interactions in crop and soil systems.

Data management plan for the grant, "Novel regulators of Slo2 potassium channels"

Data management plan for the grant, "Quantitative PCR Primer Development for Early Detection of Invasive Species."

Data management plan for the grant, "Southwest Local Algebra Meeting 2023." No data will be collected or reported for this grant.

Data management plan for the grant, "Encapsulated perovskite in NiO nanotube for topological meta-photonic devices." Research studying meta-photonic devices with high absorption and topological photonic devices using encapsulated perovskites in NiO nanotubes. The goal is to achieve high-efficiency solar cells and electrically pumped laser in perovskite/NiO nanotubes patterned in the graded photonic super-crystal. The success of this project will lead to high-efficiency integrated lasers and solar cell devices. It also enhances the abilities in the education arena by enriching program offerings in nanotechnology, clean-energy, and photonics technology.

Data management plan for the grant "Development of Novel Approaches to Earth-abundant Methane Catalysis." Research on catalytic cycles for C–H activation and functionalization of light alkanes based on the CMD (concerted metalation deprotonation) mechanism will be modeled for Earth-abundant metal dicarboxylates and related complexes. The impact of inner and outer coordination sphere effects upon catalytic cycles for light alkane functionalization will be assessed using computational chemistry techniques. The aforementioned studies will be leveraged to identify promising, synthetically feasible lead catalysts for experimental collaborators.

Data management plan for the grant, "MRI: Acquisition of a High Performance Hybrid Computer Cluster for Computational Modeling." Research grant for the purchase, installation, and operation of a new high-performance computing (HPC) resource, called CRUNTCH4, to be deployed at the University of North Texas’ (UNT) Center for Advanced Scientific Computing and Modeling (CASCaM). This much needed HPC resource combines different computing architectures and significant amounts of data storage, all connected via a high-speed communications fabric. This computing resource will provide the means for CASCaM investigators to continue research on a broad range of topics including quantum chemistry, materials design, biomolecular simulations, machine-learning based chemical discovery, and bioinformatics, among others.

Data management plan for the grant, "LLELA Quail Program: Quail in the Park Cities? Restoring a functional quail population to a small rangeland system in the Dallas Metroplex."

Data management plan for the grant, "NSFDEB-NERC: Collaborative Research: Wildlife corridors: do they work and who benefits?" Research on the impact of wildlife corridors using genetics as the measure of effectiveness. The study will use 20 independent landscapes to quantify how corridor traits affect gene flow, and will use non-flying mammals as focal species because they are strongly affected by fragmentation. The research team hypothesizes (1) a strong non-linear decline in success (gene flow) with corridor length, reflecting the skewed distribution of dispersal distances within species; (2) success will drop steeply as corridor width falls below a threshold, with the threshold determined by species traits; and (3) species that are bigger, are habitat specialists, or have greater dispersal abilities (relative to brain size or reproductive rate) will benefit more from corridors. Testing these hypotheses will allow generalization to a wide range of mammal species not included in this project. It will use highly flexible Random Forest models to answer the overarching question: What landscape traits (e.g., corridor width, degree of human disturbance) and species traits (mobility, affinity to particular land cover types) are associated with effective corridors?

Data management plan for the grant, "Graduate Research Fellowship Program (GRFP): Landscape genetics of wild turkey (Meleagris gallopavo) in Texas."

Data management plan for the grant "IRES Track II - Cape Horn ASIs: Climate change and disease ecology at the southern end of the Americas." Research giving students the opportunity to be trained in quantitative experimental design and work as part of a multinational research collaboration to study infectious disease emergence in one of the few remaining pristine places on Earth. The Cape Horn Biosphere Reserve (CHBR) off the southern tip of South America protects pristine ecosystem is perfect for this type of graduate student training. The CHBR is part of the sub-Antarctic Magellanic ecoregion, which is globally significant because it houses the worlds southernmost forest biome, contains numerous endemic species, is remote, and is relatively free of anthropogenic impacts. The research questions themselves will be flexible, but organized thematically. Specifically, this IRES Track-II will focus on the merging molecular genetic analysis using a mobile next generation sequencing lab with mist netting and arthropod trapping to investigate the impacts of wildlife disease on local biodiversity and community structure. Secondarily, eDNA and traditional wildlife disease monitoring approaches will be applied to understand the potential for zoonosis and understanding ecological factors that contribute to, or inhibit, zoonosis. Resultantly, participation in this program …

Data management plan for the grant, "Complexity Synchronization: Information Transmission among Complex Systems."

Data management plan for the research grant, "Collaborative Research: Using Uncertainty Quantification and Validated Computational Models to Analyze Pumping Performance of Valveless, Tubular Hearts." This project will develop a computational model of the essential features of the circulatory system: the electrical activity of the heart, muscle contractions of the tube walls, and the fluid-structure interactions of the heart walls and blood within. This computational framework aims to be faithful to that of a real, model animal (tunicate, or sea squirt). The model will then be analyzed with mathematical tools to determine the physical limits of the pumping system. Results of this project will improve the understanding of human heart development at the earliest stages. Also, it will point to how the large, multi-chambered hearts of vertebrates could have evolved from smaller structures.

Data management plan for the research grant, "Using uncertainty quantification and machine learning techniques to study the evolution of odor capture." This research proposes the application of uncertainty quantification (UQ) and machine learning (ML) to a CFD model of odor capture to understand the role of hair-array morphology, kinematics, and fluid environment in odor capture. The combination of CFD modeling and UQ&ML techniques can map out the performance space under which these chemosensory hair arrays operate and the relative sensitivity of each parameter of odor capture to construct a global, quantitative understanding of how parameters control odor-capture performance. Furthermore, this analysis can eliminate parameters that have no influence on odor capture, extracting the root principles of odor capture and providing a more efficient way to construct bioinspired devices for chemical detection. This work is of interest to the Army for extracting design principles that can be used for biomimetic and/or bioinspired devices for sensing hazardous chemicals in the environment (e.g. explosives).

Data management plan for the grant, "Development of advanced biocatalyst tools and resources to enable biogas-based biomanufacturing."

Data management plan for the grant "Elucidating Cyclic Fatty Acid Biosynthesis and Compartmentalization to Improve Cottonseed Value." Cotton is an important oilseed crop in the U.S. economy. Cotton seed and other vegetative tissues produce unusual chemicals called cyclic fatty acids that have wide-ranging potential uses from high-value industrial properties to nutrition-oriented uses. This project focuses on identifying genes that contribute to the production and storage of these high value bioproducts.