Mendeley Data Showcase

Urban dust acts as an effective environmental indicator of anthropogenic activities such as heavy metal pollution, reflecting the influence of industrial activities, traffic emissions, and port operations between others. Systematic sampling at different times and across urban locations with different land use categories is expected to capture the spatial and seasonal variability of heavy metal concentrations. This dataset consists of 96 urban dust samples collected at fixed locations at the Tampico conurbation (northeastern Mexico) during the dry and rainy seasons. Sampling sites were classified according to location type (e.g., school, bus stop, parking lot, residential, and industrial areas) to allow comparison among urban activities. Dust samples were collected using standardized surface collection procedures and analyzed for elemental composition by X-ray fluorescence (XRF) spectroscopy, enabling non-destructive multi-element detection. The data show the presence of Br, Cl, Cr, Fe, Mn, Ni, Pb, Rb, S, Sr, Ti, V, Y, Zn, and Zr, with concentrations reported in mg/kg. Interpretation of the data should consider seasonal effects, meteorological data, land-use classification, and proximity to emission sources such as industrial parks, ports, and high-traffic roads. The dataset can be used for urban contamination assessment, health risk evaluation, spatial analysis, and comparative studies in industrialized coastal cities. In the associated publication, statistical and spatial analyses including two baseline levels for future studies and regulatory comparisons was performed and discussed. To access the processed data, please contact Dr. Felipe Caballero at fcaballero@ipn.mx or MIA Mireya Ovando Rocha movando@utaltamira.edu.mx

Part II

This dataset contains the raw data supporting the research on the functional, nutritional, and chemical properties of Atole Agrio, a traditional Mexican fermented beverage made from purple corn (Zea mays L.). The data includes the physicochemical characterization, nutritional content, identification of bioactive compounds (total polyphenol content and monomeric anthocyanin content), antioxidant capacity (DPPH, ABTS assays), volatile compounds analysis, rheological properties, and sensory evaluation.

This dataset contains the anonymised raw data used in the study examining the effects of a single-session anodal tDCS over the left DLPFC on executive functions in elite badminton players.

This dataset supports the systematic literature review titled "AI-Driven Personalization of Gamification in Education: A Systematic Literature Review." It contains the complete data extraction, quality assessment scores, and coded analysis for all 75 included studies published between 2020 and 2025, retrieved from Scopus, Web of Science, and IEEE Xplore. The workbook includes: (1) search and screening records following PRISMA 2020 guidelines, (2) quality assessment scores across six criteria for each study, (3) full data extraction covering bibliographic information, AI techniques, gamification elements, learning outcomes, educational contexts, challenges, and proposed frameworks, and (4) coded summaries for each of the six research questions (RQ1–RQ6). This dataset enables full reproducibility of the review findings and supports secondary analyses by other researchers.

Major element compositions of Olivine and Fe-O-S melt (in wt%)

This dataset contains survey data examining the influence of online user-generated content (UGC) characteristics on tourist engagement, self-congruity, revisit intention, and destination brand evangelism in Vietnam. The study investigates how perceived informativeness, authenticity, vividness, and relevance of UGC affect engagement behavior and subsequent loyalty-related outcomes, while also incorporating travel constraints as a contextual factor. Data were collected from domestic and international tourists at major tourism destinations across Northern, Central, and Southern Vietnam between December 2025 and February 2026. A structured questionnaire using five-point Likert scales was administered on-site with the support of trained research assistants. A total of 1,500 tourists were approached, resulting in 1,347 valid responses after screening. The dataset includes raw survey responses, recoded variables, and processed outputs used for Partial Least Squares Structural Equation Modeling (PLS-SEM). The data can be used for replication studies, comparative tourism research, and further investigation into digital engagement, destination branding, and behavioral intention models in emerging tourism markets

What Drives Entrepreneurial Intentions in Colombian Female University Students? Evidence from Self-Efficacy, Resilience, and University Environment

Project FeederWatch is a citizen science project operated by the Cornell Lab of Ornithology and Birds Canada. Since November 1988, "FeederWatchers" (members of the public) have been following a standardized protocol for observing and reporting birds that visit supplemental feeding stations (bird feeders) in the US and Canada. This dataset contains raw data submitted to Project FeederWatch. The data are intended to be completely open access. The "FeederWatch Data Dictionary" file included with this dataset is critical for understanding fields and their contents. The dataset contains millions of records from > 60,000 count locations. Note that, due to the large file sizes, we have divided the dataset into multiple clusters of years. The FeederWatch season runs from November 1 through April each winter/spring (in the northern hemisphere). As such, the “2025” FeederWatch season includes data from November 1, 2024 – April 30, 2025, and the ‘PFW_birdobs_2021_2025’ file includes data from November 1, 2020 – April 30, 2025. For meaningful use of the data, please consult the data paper describing the FeederWatch dataset: Bonter, D.N. and E.I. Greig. 2021. Over 30 years of standardized bird counts at supplementary feeding stations in North America: A citizen science data report for Project FeederWatch. Frontiers in Ecology and Evolution 9: Article 619682 doi.org/10.3389/fevo.2021.619682 The dataset is scheduled for updates annually on or about June 1. Details about Project FeederWatch can be found on the project website: www.feederwatch.org. Data files are on the FeederWatch web site here: https://feederwatch.org/explore/raw-dataset-requests/ See documentation at https://feederwatch.org/explore/raw-dataset-requests/ for the latest details.

This dataset contains chemical (major and trace elements), isotopic (Sr and Nd) analyses on whole rock and minerals, noble gas (3He/4He, 20Ne and 40Ar/36Ar) and δ13C isotopic analyses performed on fluid inclusions in minerals from the whole stratigraphic sequence of the 79 CE eruption from Somma-Vesuvius, sampled at Cava Pozzelle.