Data management plan for the grant, "Ultra-High Temperature Stable Morphing Materials for Hypersonic Applications"

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 research grant, "Development of Combinatorial Processing Techniques for Accelerated Discovery of Complex Concentrated Alloy (or Multi-Principal Element Alloys) for Structural Applications"

Data management plan for the grant, "Project Communicate." The purpose of Project Communicate is to professionally prepare 27 special education teachers and 10 speech-language pathologists, including scholars from ethnically and racially diverse backgrounds, to be highly-qualified to demonstrate skills in promoting high expectations to improve student outcomes, providing individualized evidence-based practices for students with autism spectrum disorder, and providing culturally and linguistically responsive instruction. Scholars will participate in a master’s degree program in Special Education (Autism Intervention) or Speech-Language Pathology designed to include coursework, integrated and embedded supervised field experiences, and other professional development opportunities for developing knowledge and skills for working with students with ASD in school-based settings.

Data management plan for the grant, "Variable Conductor Radiator for CO2 Deposition in Deep Space Transit"

Data management plan for the grant, "The University of North Texas Industrial Assessment Center."

Data management plan for the grant, "REU Site: TaMaLe - Testing and Machine Learning for Context-Driven Systems: Research Experience for Undergraduates." TaMaLe (Testing and Machine Learning for Context-Driven Systems), a renewal Research Experience for Undergraduates (REU) Site at University of North Texas, engages 10 undergraduate students for 10 weeks with problems in the context-driven system domain. The students explore research problems to improve the reliability and security of context-driven systems. Context-driven systems, such as mobile apps, face constant streams of input from both users and context changes in their environments. Users interact with apps through touch and speech interfaces. These systems also respond to context events that occur in their environments such as changes to network connection, battery level, screen orientation, and more. The combined explosion of possible user events and context event sequences pose new challenges that require cost effective testing solutions. Students and mentors in this REU program work in small teams to develop and empirically evaluate new software testing techniques for context-driven systems using strategies such as reinforcement learning and combinatorial-based techniques.

Data management plan for the grant, "The North Texas-20". The North Texas-20 project builds upon its established work to redress unmet needs of our region, support for underserved communities, and contribute to psychology workforce diversification.

Data management plan for the grant, "Cancer Detection and Treatment Based on Low-Level Light Interaction with Biological Cells: Augmentation to Existing Human Performance Research Capabilities."

Data management plan for the grant, "Examination and Refinement of a Novel Treatment for Posttraumatic Stress Disorder: Processing of Positive Memories Technique (PPMT)." The study aims to examine effects of and targets underlying a novel technique for posttraumatic stress disorder focused on positive memories (Processing of Positive Memories Technique; PPMT). Specific aims include (1) examining PPMT’s effects; (2) examining mechanistic targets such as improved affect underlying PPMT’s effects; and (3) refining PPMT.

Data management plan for the grant, "Developing a High-Quality Academic Environment for Broadening Participation of Hispanic Students in Computing." The objectives of the grant are to Enhance the education quality and broadening the participation of Hispanic undergraduate students in Computing through new pedagogy adoption, cultural transformation, and offering guided research opportunity for students. The project is also going to study the cultural asset-based education for Hispanic students and to understand which cultural asset would be the most important impact factors for Hispanic education in computing.

Data management plan for the grant, "GenCyber Teachers Camp." The goal of the UNT GenCyber Teacher Camp is to increase the cybersecurity expertise of middle and high school Computer Science teachers so that they can introduce cybersecurity curriculum into their classrooms. We will recruit 20 teachers who teach Computer Science and STEM-related middle/high school courses. We will create modules that teachers can use to create positive environments for students and thus to motivate them to gain interest in cybersecurity.

Data management plan for the grant, "Improving Remote Breathalyzer Procedures used by Clinicians and Researchers to Remotely Monitor Alcohol Use."

Data management plan for the grant, "Piloting Deposit Contracts to Increase Accessibility of a Contingency Management Intervention to Reduce Problematic Drinking". The purpose of this study is to demonstrate the feasibility and/or effectiveness of deposit contracts as an intervention for problematic drinking.

Data management plan for the grant, "Capacity Building: Creating and Sustaining a Pathway for Engineering Majors to Become STEM Teachers." The project aims to serve a national need for building pathways for engineering students to become grade 6-12 STEM teachers in high-need schools. The project will develop a framework for recruitment, retention, and reshaping of graduate teacher certification specifically for engineering students to become STEM teachers. The effort is a collaboration between the College of Engineering and the College of Education at the University of North Texas, a Hispanic Serving Institution.

Data management plan for the grant, "UNT Gencyber Academy."

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, "Maternal Acetaminophen Use and Childhood Cancer."

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.

Data management plan for the grant, "Increasing students access to educational and experiential learning opportunities in agritourism." The project aims to develop an online course on agritourism within the sustainability framework, to be offered by the Department of Hospitality and Tourism Management (HTM) at the University of North Texas (UNT).

Data management plan for the grant, "Collaborative Research: Equitable Science Sensemaking: Helping Teacher Candidates Support Multiple Pathways for Learning"

Data management plan for the grant, "Enhancing Cybersecurity TKSs (Tasks, Knowledge, and Skills) for Cybersecurity Education and Workforce Development."