Article states that microneedles are highly sought after for medicinal and cosmetic applications. However, the current manufacturing process for microneedles remains complicated, hindering its applicability to a broader variety of applications. This experimental study enables the shapes and mechanical properties of the microneedles to be predicted in advance for mass production and wide practical use for biomedical or cosmetic applications.

Article asserts that the foot is a vital organ, as it stabilizes the impact forces between the human skeletal system and the ground. The authors present an instep girth measurement algorithm, and they used a pixel per metric algorithm for measurement; these algorithms were accordingly integrated with the application.

Article states that thiol-ene/acrylate shape memory polymers (SMPs) have sufficient stiffness for facile insertion and precision placement and soften after exposure to physiological conditions to reduce the mechanical mismatch with body tissue; as a result, they have demonstrated excellent potential as substrates for various flexible bioelectronic devices, such as cochlear implants, nerve cuffs, cortical probes, plexus blankets, and spinal cord stimulators. Here, the authors report a new strategy for designing SMPs with enhanced shape recovery properties and lower moduli than previously reported SMPs under physiological conditions without sacrificing stiffness at room temperature by introducing a hydrophilic monomer.

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.