Data management plan for the grant, "CAREER: Manufacturing of Mechanically Stable Nanoporous Ceramic Structures Via Selective Infiltration of Polymer Templates." This Faculty Early Career Development (CAREER) grant from the National Science Foundation supports fundamental research to elucidate a new strategy of manufacturing nanoporous ceramic structures with controllable structure and composition and programmable mechanical stability. The specific goal of this research is to discover processing-structure-property relationships in ceramic coatings and heterostructures by providing fundamental insights on the mechanism of liquid phase swelling-based infiltration of spin-coated polymer templates with inorganic precursors and defining the rules that control the resulting structure and, thus, access to various materials surfaces and interfaces.

Data management plan for the grant, "Developing a Biomanufacturing Platform for the Site-Selective Functionalization and Structural Diversification of Cytochalasan-Based Carbon Skeletons." This project will identify fungal enzymes that efficiently modify more than one substrate in a predictable way. Also, enzymes will be engineered to expand the range of substrates. A biomanufacturing platform to synthesize bioactive molecules at lower costs will be the end result. Fungi can synthesize small molecules with complex structures using a number of highly coordinated enzymes. These molecules are difficult to make synthetically, and they can aid in crop production or have beneficial human health effects. Cytochalasans are phytotoxic, cytotoxic and actin-binding natural products. Produced by fungi, over 400 variants have been described. The structural diversity is partly explained by the flexibility of the enzymes that introduce and modify functional groups. These enzymes structurally rearrange the core carbon skeleton in a site-selective manner, often on more than one substrate. Genome mining will be used to identify cytochalasan tailoring enzymes. Overproducing strains will be characterized chemically. Transcription factor over-expression will be investigated. Targeted gene knock-out will confirm the function and scope of the enzymes. The enzymes will be engineered to expand their substrate range. Synthetic biology and metabolic …

Data management plan for the grant, "REU Site: Interdisciplinary Research Experience on Accelerated Deep Learning through A Hardware-Software Collaborative Approach." This Research Experiences for Undergraduates (REU) Site Program at the University of North Texas will enhance the knowledge and research skills of a diverse cohort of undergraduate students through empowering, innovative, and interdisciplinary research experiences in developing Deep Learning applications and systems. The program aims to 1) expose undergraduate students to real-world and cutting-edge research focused on accelerated deep learning through combined hardware and software development; 2) encourage more undergraduate students to continue their academic careers and seek graduate degrees in computer science, computer engineering, and related disciplines; 3) develop research skills and improve communication and collaborative skills in undergraduate students.

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

Data management plan for the grant, "Predicting Criminal Activities in Darknet Markets: Advancing Knowledge and Tools for Activities Monitoring."

Data management plan for the grant, "Enhancing Techniques for Ontologies Mapping for the Cybersecurity Workforce Development Applications."

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 "IUCRC Phase I University of North Texas: Center for Electric, Connected and Autonomous Technologies for Mobility (eCAT)."

Data management plan for the grant "Self -powered Wireless Hybrid Density/Level Sensing with Differential Pressure Sensors for Safeguarding and Monitoring of Electrochemical Processing of Nuclear Spent Fuel."

Data management plan for the grant "Nuclear Safety Testing and Analysis Research (NSTAR) Fellowship Program at the University of North Texas." The proposed NSTAR fellowship program at UNT aims to reinforce the workforce in the nuclear energy safety community by engaging the selected fellowship students (fellows) with interdisciplinary education and research. The overarching theme and research focus of the proposed NSTAR program is acoustics-based non-destructive testing and analysis and nanoparticle processing for thermal management applications. An interdisciplinary research team will investigate these research areas with backgrounds in mechanical engineering, material science, and/or physics. The program will fully support two fellows over four years including full tuition and stipends.

Data management plan for the grant, "Exploring the Relative Risk Severity of Phishing Techniques on Individual Phishing Susceptibility: A Mixed Approach."

Data management plan for the grant, "CAREER: Liquid Crystal-Templated Sequential Infiltration Synthesis of Hybrid Organic/Inorganic Materials with Multidimensional Chiral Structures"

Data management plan for the grant, "3D Microscopy for High-throughput Phenotyping of Cotton Fibers."