The University of Charleston (UC) is a private non-profit university with its main campus in Charleston, West Virginia. The university also has a location in Beckley, West Virginia, known as UC-Beckley.
The emergence of AI chatbots capable of simulating intimate interactions has created new forms of romantic engagement. This study investigates the psychological profiles that predict individuals’ likelihood of forming romantic connections with AI chatbots. A sample of 650 participants completed measures of the Big Five personality traits and two distinct dimensions of loneliness—emotional and social loneliness. Using latent profile analysis (LPA), we identified four distinct psychological profiles that differed significantly in their rates of AI romantic experience. Multiple logistic regression analyses revealed that higher openness, lower extraversion, and greater emotional loneliness significantly predicted AI-mediated romantic involvement, whereas social loneliness was not a significant factor. These findings suggest that emotional needs and exploratory personality traits, rather than generalized feelings of isolation, critically shape the appeal of AI chatbot relationships.
Climate change has dramatically altered the Arctic seas with significant decrease in sea ice extent and thickness and warming water temperature. The ecological impacts of such change have been described for many parts of the Arctic Ocean, but long-term records of biological indicators are still missing. Among those, photosynthetic and accessory pigments are one of the key tools that aid quantification of phytoplankton and sea–ice algae biomass and characterisation of community composition. To address this gap, we present the first pan-Arctic compilation of in situ algal pigment data obtained exclusively by High-Performance Liquid Chromatography (HPLC), containing 10 798 samples collected across 77 Arctic research cruises between 2000 and 2024. As a result of large-scale collaborative effort, this database covers both open water and sea–ice environments across coastal, shelf and open domains. The database (https://doi.org/10.11583/DTU.29445104, Heidemann et al., 2026) includes measures of up to 26 pigments, with 8 major marker/accessory pigments being considered in this study, namely Alloxanthin (Allo), 19'-Butanoyloxyfucoxanthin (But-fuco), Chlorophyll a (Chl a), Chlorophyll b (Chl b), Fucoxanthin (Fuco), 19'-Hexanoyloxyfucoxanthin (Hex-fuco), Peridinin (Peri), and Zeaxanthin (Zea). This publicly available database provides crucial data that can be used to assess phytoplankton dynamics, validating remote sensing observations and can serve as a resource for future Arctic ecological- and modelling studies.
This perspective paper explores cybersecurity and information security as critical dimensions of healthcare administration and organizational behavior within Applied Behavior Analysis (ABA) telehealth organizations. As digital platforms become central to clinical delivery, ABA therapists, highly skilled in behavioral science but often under-trained in cybersecurity, face increasing exposure to data breaches and compliance risks. Most security incidents in healthcare stem from preventable human factors such as cognitive overload, automation complacency, and inconsistent adherence to security protocols. Integrating behavioral principles with administrative governance can transform cybersecurity from a technical afterthought into a core element of professional and organizational competence. Embedding cybersecurity within organizational culture ensures sustainable protection of client data while advancing ethical, secure, and high-performing ABA telehealth systems.
Motivation: SNAPSHOT USA is an annual, multi-contributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained: SNAPSHOT USA 2024 contains 377,427 records of camera trap image sequence data and 3127 records of camera trap deployment metadata. Spatial Location and Grain: Data were collected across the United States of America in 49 states, 12 ecoregions and many ecosystems. Time Period and Grain: Data were collected between 1 August and 19 December in 2024. Major Taxa and Level of Measurement: The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format: SNAPSHOT USA 2024 comprises two.csv files. The original data can be found within the SNAPSHOT USA 2024 project on the Wildlife Insights platform.
