Data management plan for the University of North Texas GenCyber Academy grant. The GenCyber Cybersecurity Program at the University of North Texas is part of the GenCyber program. The program is hosted by the Department of Computer Science and Engineering. The mission as part of the GenCyber program is to engage students at an early age in cybersecurity field and inspire them to become skilled cybersecurity professionals. This is provided by free summer cybersecurity camps for North Texas middle and high school students (7th-11th grade). The goals of the summer camps are to help students at an early age to understand correct and safe on-line behavior, increase students' interest in cybersecurity careers and improve diversity in the cybersecurity workforce of the nation.

Data management plan for the grant "2021 NCAE-C-002 University of North Texas."

Data management plan for the grant, "2023-GenCyber-University of North Texas."

Data management plan for the grant, "CAN23-161, Hierarchically structured ISRU derived composites."

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 "CAREER: A Prosthetic Elbow with Network of Soft and Modular Thermo-Active Actuators for Mobility Impaired Patients." This NSF Faculty Early Career Development (CAREER) project will develop novel networks of flexible Peltier-based soft actuators designed for rehabilitation.

Data management plan for the grant, "CAREER: Developing a Flexible Serverless Multimedia Streaming Cloud Platform."

Data management plan for the grant, "CAREER: Fundamental Limits of Cryptographic Primitives Through Network Information Theory." Research project studying the fundamental limits of a diverse array of cryptographic primitives through network information theory and coding tools. The project takes an information theoretic view of the investigation of the fundamental limits of cryptographic primitives. The project is expected to unveil theoretical and practical insights into cryptographic primitives, and enhance the understanding on their fundamental limits.

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, "CAREER: Reinventing Network-on-Chips of GPU-Accelerated Systems." Research seeking to reinvent on-chip networks for GPU-accelerated systems to remove a communication bottleneck. A major outcome of the project is a set of techniques that enable the development of effective and efficient network-on-chip architectures. Graphics processing units (GPUs) have rapidly evolved to become high-performance accelerators for data-parallel computing. To fully take advantage of the computing power of GPUs, on-chip networks need to provide timely data movement to satisfy the requests of data by the processing cores. Currently, there exists a big gap between the fast-growing processing power of the GPU processing cores and the slow-increasing on-chip network bandwidth. Because of this, GPU-accelerated systems are interconnect-dominated and the on-chip network becomes their performance bottleneck.

Data management plan for the grant, "CAREER: Shape Memory Polymers as Biomaterial." This CAREER projectaimsto elucidate the underlying mechanism of the plasticization-induced shape memory effect of thiol-enebased polymers. The model application for this material will be a heat shrink tubing that can shrink at bodily conditions (37° C and simulated body fluids) and can be used to seal colonic anastomosis. The specific three aims are to (1) Systematically investigate the effect of crosslink-density and chain extender length on theplasticization-induced shape memory effect of thiol-enebased polymers. Mechanical and thermomechanical measurements inside simulated body fluids will be used to assess shape memory properties and structure-property relationships. (2) Understand the relationship between material thickness, degree of shape-programming, and radial recovery forces of tube-shaped SMPs to determine optimal design parameters for sufficient shape recovery using the heat shrink tube model. (3) Demonstrate the functionality of a biomedical heat shrink tube that utilizes the plasticization-induced shape recovery through an ex vivo colon anastomosis model and quantify mechanical and sealing properties.

Data management plan for the grant, "CAREER: Understanding the Role of Nanoprecipitates in Advanced Metastable Titanium Alloys."

Data management plan for the grant "Charge Transport in Two-Dimensional Materials Based Integrated Flexible Energy System."

Data management plan for the grant, "Child Health and Human Development Extramural Research." This study will use the genome-edited human induced pluripotent stem cell (hiPSC) with NOTCH1 knockout to recapitulate the genetic variants of NOTCH1 mutation in the Hypoplastic left heart syndrome (HLHS). It will use advances in the vascularized cardiac organoid directly differentiated from hiPSCs to replay the development and function of cardiomyocytes, endothelial cells, smooth muscle cells, and other cardiac cells in a defined 3D cell culture model by stencil-based micropatterning. It will elucidate the pathogenesis of cardiovascular underdevelopment and dysfunction found in HLHS with NOTCH1 mutation via the NOTCHDELTA/JAG ligand-receptor binding and multicellular crosstalk by single-cell RNA-seq and proteomics analysis.

Data management plan for the grant, "CICI: UCSS: Secure Containers in High-Performance Computing Infrastructure." Ensuring the security and privacy of high-performance computing (HPC) infrastructures is of utmost importance due to their handling of sensitive data and critical scientific computations. HPC infrastructures commonly employ containers, which provide lightweight and isolated environments for running applications. Nevertheless, containers in HPC infrastructures encounter security challenges, including insecure container images and vulnerabilities related to isolation. Existing container image scanners face a major challenge of low coverage, while current container runtimes struggle to ensure both security and performance for HPC workloads simultaneously. This project addresses these challenges by developing secure containers specifically tailored for HPC infrastructures. The project introduces innovative solutions, including the development of an efficient image vulnerability scanner and a secure container runtime.

Data management plan for the grant "Collaborative Research: CCRI: Planning: A Multilayer Network (MLN) Community Infrastructure for Data,Interaction,Visualization, and softwarE(MLN-DIVE)." Research relating to creating a community infrastructure for researchers using multilayer networks (MLN). This project uses a formally established network decoupling approach to perform various aggregate analysis (community, centrality, substructure detection, etc.) using individual layers and composing them. The broader impact of this planning project is to provide meaningful and appropriate analysis tools that are grounded in theory to a broad range of applications from different domains. The focus is on facilitating the mainstream use of multilayer network analysis in data analysis, research and teaching.

Data management plan for the grant, "Collaborative Research: CIF: Medium: Fundamental Limits of Cache-aided Multi-user Private Function Retrieval." This project is motivated by the need to efficiently execute complex queries on massive databases in a way that minimizes the use of communication resources while preserving the privacy of the entity that initiated the query. Such queries are functions of the data points that are stored at remote servers. This project develops a principled and holistic framework for the problem of privately retrieving, at distributed cache-aided nodes, the output of functions based on both data that is locally computed and data that is received from multiple servers.

Data management plan for the grant, "Collaborative Research: Combined Tribological and Bactericidal Effect of Bioinjectable Nanodiamonds on Biological Joints."

Data management plan for the grant, "Collaborative Research: CyberTraining: Pilot: Research Workforce Development for Deep Learning Systems in Advanced GPU Cyberinfrastructure." This project aims to develop a novel set of interactive training materials, including hands-on lecture modules, invited research talks from renowned researchers, and an interdisciplinary collaborative project in an intensive workshop, integrating a wide variety of advanced and inter-connected techniques employed by research workforce for deep learning (DL) systems in advanced GPU cyberinfrastructure (CI). Specifically, this project focuses on training seniors, graduate students, and researchers on how advanced GPU CI can be efficiently utilized and improved to enable high-performance DL systems for data-intensive DL applications in geoscience (GS) and computer science and engineering (CSE) research. The goal is to foster future CI users and contributors to adopt, develop, and improve advanced GPU CI for DL systems in their research.

Data management plan for the grant, "Collaborative Research: DMREF: AI-enabled Automated design of ultrastrong and ultraelastic metallic alloys"

Data management plan for the grant, "Collaborative Research: Engaging Blind and Visually Impaired Youth in Computer Science through Music Programming."

Data management for the grant, "Collaborative Research: Framework Implementations: CSSI: CANDY: Cyberinfrastructure for Accelerating Innovation in Network Dynamics." Research addressing the lack of a comprehensive cyberinfrastructure that supports innovative research challenges in large-scale, complex, dynamic networks by developing a novel platform, called CANDY (Cyberinfrastructure for Accelerating Innovation in Network Dynamics), based on efficient, scalable parallel algorithm design for dynamic networks and high-performance software development with performance optimization.

Data management plan for the grant, "Collaborative Research: IRES Track I: Wireless Federated Fog Computing for Remote Industry 4.0 Applications."

Data management plan for the grant "Collaborative Research: Microneedle‐mediated Adaptive Phototherapy (MAP) for Wound Healing."