Mendeley Data Showcase

The GoCJ dataset is comprised of multiple files, where each file contains the sizes of a specified number of jobs expressed in Million Instructions (MI), derived from workload behaviors observed in Google cluster traces. The name of each file indicates the number of jobs it contains; for example, GoCJ_Dataset_1000 includes 1000 jobs along with their associated SLA classes and arrival times. In this study, a modified version of the GoCJ dataset is employed. Each dataset file consists of three columns: (i) job length in terms of Million Instructions (MI), (ii) Service Level Agreement (SLA: {1, 2, 3}), representing different levels of priorities, and (iii) job arrival time, which captures realistic workload submission behavior. The experimental evaluation is conducted using the following dataset files: GoCJ_Dataset_1000.csv, GoCJ_Dataset_2000.csv, GoCJ_Dataset_3000.csv, GoCJ_Dataset_4000.csv, GoCJ_Dataset_5000.csv, and GoCJ_Dataset_6000.csv, enabling performance analysis under increasing workload scales.The file Original_Enhanced_Dataset.txt contains the 50 seed job sizes required as input for both the Java-based generator (EnhancedGoCJGenerator.java) and the Excel-based generator (GoCJ_Enhanced_Generator.xlsx) to reproduce datasets of any desired size while preserving the original workload distribution properties. Also the Java based generator java coding file is available online at : https://github.com/Mohsin-Nawaz/Enhanced_GoCJ-Java-Generator

The Grad-CAM visualizations for all images in the from the oral classification case study test set together with the corresponding original images and class labels (encoded in the lenames). This is part of the supporting information for the manuscript "Methodological Failures and Barriers to Reproducibility in AI-Based Dental Research" submitted to the Discover Applied Sciences Journal.

Full author list for the manuscript, "Development of a Core Outcome Set for Clinical Trials in Melasma."

This repository contains the processed computational outputs and manuscript-supporting files associated with the study "Directional Demand Substitution in Integrated Crop-Rotation and Fresh-Produce Logistics Planning: A Scenario-Based MILP Analysis." The deposited materials are organized to support inspection of the reported evidence in the manuscript. The package includes: - main scenario-block results built around a common no-substitution baseline; - reduced-network validation outputs for the 'fixed-price' and 'segmented' solution modes; - supplementary robustness and medium-instance outputs; - manuscript-supporting summary tables and final figure files. The scenario-result folders contain three types of CSV files: - 'scenario_summary.csv' for scenario-level economic outcomes and solver summaries; - 'scenario_crop_diagnostics.csv' for crop-level service and shortage diagnostics; - 'scenario_substitution_arc_diagnostics.csv' for substitution-flow summaries at the arc level. This is a data-oriented deposit. It provides the processed evidence underlying the reported tables, figures, and discussion in the manuscript. The public deposit does not include the full optimization source code.

Final vote results for inclusion or exclusion of outcomes in the core outcome set for clinical trials in melasma.

Research hypothesis: Gender-affirming hormone therapy improves transgender adults' mental health. Data extraction was performed for all the studies that met inclusion criteria, then entered into SRDR (Systematic Review Data Repository). The following headings: Sample characteristics: total sample size, number of FtM transgender participants, number of MtF transgender participants, mean age of the participants, age range of the participants, psychiatric comorbidities. Design details: study design, year of publication, authors of the study, aim of the study, follow up, duration of the follow up. Interventions/Arms: description of intervention, used dose of treatment, type of treatment administration, control group description Outcomes: description of mentioned measures Methodological quality: classification system, statistical analysis, limitations Inclusion criteria: • Transgender adults: male-to-female (MtF) and female-to-male (FtM) • Receipt of hormonal therapy • No prior medical history of gender-affirming surgeries (GAS) • Gender dysphoria or gender incongruence diagnosis (ICD/DSM protocols) • Studies published from the year 2000 onwards Exclusion criteria: • Pediatric population • Undergoing GAHT for less than 3 months Results were divided in a few categories: symptoms of depression, anxiety, gender dysphoria, general psychopathological symptoms and quality of life. Findings suggest that GAHT can have a positive impact on transgender adults' mental health.

This dataset contains 19,222 anonymized student records, designed for predicting academic performance using a multiclass classification approach (Grades: A, B, C, D, F). It was constructed using a Medallion Architecture data engineering pipeline, representing the final 'Gold Layer'. The dataset integrates 14 key features encompassing students' daily lifestyle habits (e.g., study hours, sleep duration, gaming hours), psychological indicators (e.g., stress levels, focus scores), and demographic/academic backgrounds. It is highly optimized and calibrated for advanced deep learning applications in Educational Data Mining (EDM).

Data and codebook necessary for replicating the analyses from the paper Eager but Afraid: Effects of Fear and Motivation on Exercise Intentions in People with Chronic Pain

Supplementary Table 1. Comorbidities of HS patients. P-values are adjusted for multiple comparisons by the Benjamini-Hochberg method.

This dataset contains longitudinal survey data from a field randomized controlled trial (RCT) designed to evaluate whether the impact of non-formal business education on women’s entrepreneurial activity depends on their level of prior formal education. The data was collected from women entrepreneurs in a Southern European country who were randomly assigned to either a treatment group or a delayed-treatment (waitlisted) control group. Data includes the STATA file with all relevant variables as long as the do file that someone can use to replicate the results of the paper "Non-Formal versus Formal Education in Strengthening Female Entrepreneurship"