G-DaM: A Distributed Data Storage with Blockchain Framework for Management of Groundwater Quality Data (open access)

G-DaM: A Distributed Data Storage with Blockchain Framework for Management of Groundwater Quality Data

Authors discuss their use of a distributed and decentralized architecture to store the statistics, perform double hashing, and implement access control through smart contracts to forecast groundwater availability. Their work demonstrates a modern and innovative approach combining Distributed Data Storage and Blockchain technologies to overcome traditional data sharing, and centralized storage, while addressing blockchain limitations.
Date: November 11, 2022
Creator: Vangipuram, Sukrutha L. T.; Mohanty, Saraju P.; Kougianos, Elias & Ray, Chittaranjan
System: The UNT Digital Library
Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations (open access)

Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations

Article provides a general reweighting framework based on anisotropic diffusion maps for manifold learning that takes into account that the learning data set is sampled from a biased probability distribution. The authors show that their proposed framework can be used in many manifold learning techniques on data from both standard and enhanced sampling simulations.
Date: November 11, 2022
Creator: Rydzewski, Jakub; Chen, Ming; Ghosh, Tushar K. & Valsson, Omar
System: The UNT Digital Library
Seeking Mental Health Support Among College Students in Video-Based Social Media: Content and Statistical Analysis of YouTube Videos (open access)

Seeking Mental Health Support Among College Students in Video-Based Social Media: Content and Statistical Analysis of YouTube Videos

This article presents a study that aims to identify strategies for using video-based social media to combat stigmatized diseases, such as mental health, among college students. The authors identify effective strategies for designing video-based social media content for supporting college students’ mental health. Results show that the videos where individuals share their personal stories, as well as experiential knowledge (ie, tips and advice), engaged more viewers in both the short term and long term. Individuals’ videos on YouTube showed the potential to support college students' mental health in unique ways, such as providing social support, validating experience, and sharing the positive experience of help-seeking.
Date: November 11, 2021
Creator: Choi, Bogeum; Kim, Heejun & Huh-Yoo, Jina
System: The UNT Digital Library