Mendeley Data Showcase

The Knight Alzheimer Disease Research Center (ADRC) Data Freeze Ending 2025-03-31 is a longitudinal compilation of harmonized, processed research data collected from August 1, 1979 through March 31, 2025. This Data Freeze represents a fixed, versioned snapshot of curated datasets maintained by the ADRC and is intended to support reproducible secondary analyses under approved data use agreements. The Data Freeze includes data contributed by multiple ADRC Cores, including clinical assessments, cognitive testing, neuropsychological measures, neuroimaging data summaries, fluid biomarker data, neuropathology variables, and related research measures. Modules are compiled, quality controlled, and integrated according to ADRC Data Management and Sharing procedures prior to freeze finalization. This dataset reflects the full longitudinal structure of ADRC participant data available as of the official cutoff date (March 31, 2025). No data collected after this date are included in this release. Each subsequent Data Freeze constitutes a new versioned dataset with its own DOI. The purpose of this Data Freeze is to: 1. Provide a stable, citable dataset snapshot for approved secondary analyses 2. Support NIH Data Management and Sharing (DMS) policy compliance 3. Enable transparency, reproducibility, and longitudinal tracking of dataset versions This repository record provides metadata describing the Data Freeze and assigns a persistent DOI to this version. The underlying human subject data are stored in a secure Research Infrastructure Services (RIS) environment and are not publicly downloadable. Access to this dataset is controlled and requires submission of a formal data request through the Knight ADRC Request Center. Approved investigators must complete the appropriate Data Use Agreement prior to receiving access. Upon approval, access to the static dataset corresponding to this DOI will be granted through ADRC-managed secure infrastructure. Investigators using this Data Freeze must cite this dataset DOI in all resulting publications and acknowledge Knight ADRC funding as specified in the Data Use Agreement. This dataset was generated and curated by the Knight ADRC Data Management and Statistics Core in collaboration with contributing ADRC Cores. For information about submitting a data request, please visit: https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/submit-a-request/

CAD Files for the scientific paper "Low-cost instrumented tubular furnace for debinding and sintering of sinter-based metallic parts ": This repository includes the different parts to build a customized sintering system: Arduino Pilot box, Gaz analisis box, Sooling system, Filter system and finally the entire furnace (SG-1700) reproduced by the authors For each part in the assemblies, the manufacturing method is indicated. For example (please also see the Step_organization_exemple.png) : - (CNC) > Has to be machined - (3D print) > Has to be 3D printed If nothing is indicated, the parts have to be purchased. References are indicated in the original paper.

Replication Files for 'When Volatility Turns, Recessions Follow'

This dataset contains the quantitative analysis results of Short-Chain Fatty Acids (SCFAs) in serum and fecal samples from healthy controls and CKD patients. The analysis was performed using Gas Chromatography-Mass Spectrometry (GC-MS).

This dataset presents the zooarchaeological results from faunal remains recovered at the medieval mining site of Rocca San Silvestro (Campiglia Marittima, Tuscany, Italy), dating to the 13th–14th centuries AD. The material derives from a new research conducted in June–July 2023 and focuses on selected areas originally excavated between 1991 and 1993. The analyses were carried out within the international project “Pursuing Public Health in the Preindustrial World, 1100–1800”, funded by the Australian Research Council. The dataset includes 1,333 faunal remains from areas 4100, 4200, and 4700, organised into three sheets: Sheet 1 – Bones Records include the excavation year, associated archaeological period, stratigraphic unit (US), preservation state (good, medium, bad), anatomical element, side, taxonomic identification, degree of epiphyseal fusion, butchery evidence, burning and gnawing traces, biometrical measurements, pathologies, and other non-metric traits. Sheet 2 – Teeth This sheet documents loose and in-jaw teeth, including side, taxonomic identification, and associated dental measurements. Sheet 3 – Ribs and vertebrae Ribs and vertebrae are recorded separately, with notes on butchery, burning and gnawing evidence. Elements are further classified into medium-sized and large-sized categories.

This dataset contains raw measurements and analytical results from ripe oil palm fruit bunches sampled in three Ugandan districts: Kalangala (introduced hybrids), Bundibugyo, and Kanungu (indigenous genotypes). A total of 75 bunches were collected, georeferenced, and processed for oil extraction and compositional analysis. The raw data include detailed field and sample metadata such as genotype, cultivation scale, plant age, agronomic practices, and morphological traits, alongside oil extraction parameters including oil extraction rate and mass of stearin recovered. In addition, the dataset provides biochemical analyses covering carbohydrate content determined by the Anthrone method, fatty acid methyl ester (FAME) profiles for linolenic, linoleic, palmitic, stearic, and oleic acids using HPLC-UV, and beta-carotene concentration measured spectrophotometrically. All assays were performed in triplicate with analytical-grade reagents, and results are expressed in standardized units (mg/100 g, μg/g). Statistical outputs include raw values and processed data from non-parametric Kruskal-Wallis tests, comparing genotypes, districts, and age categories. Together, these data offer a comprehensive resource for evaluating oil palm diversity, nutritional composition, and biochemical quality across introduced and indigenous genotypes in Uganda.

This dataset comprises comprehensive measurements of fruit, seed, and quality traits in pumpkin landrace accessions, alongside biochemical analysis of total phenolic content (TPC). Structural fruit traits recorded include length, diameter, shape ratio (L/D), flesh thickness, flower scar diameter, weight, neck length, and volume. Quality traits encompass fruit shape, curvature, stem-end and blossom-end profiles, groove presence, skin color (primary/secondary, intensity), waxiness, surface warts, and flesh color. Seed traits were assessed for length, width, and color. Phenotypic diversity across sub-regions was characterized using descriptive statistics (mean, standard deviation, range, median, coefficient of variation), frequency distributions, and proportional analyses. Measurements were obtained with precision digital calipers (±0.01 mm) and calibrated digital bench scales (±0.1 g). Color determination followed the Royal Horticultural Society (RHS) colour chart (6th edition), with harmonized descriptors for consistency across landraces. Biochemical evaluation included quantification of total phenolic content (TPC) in pumpkin mesocarp extracts using the Folin–Ciocalteu colorimetric assay. Absorbance was measured at 765 nm with a UV-Vis spectrophotometer, and results expressed as gallic acid equivalents per kilogram of fresh weight (mg GAE/kg FW). This dataset provides a robust resource for studies on phenotypic diversity, trait correlations, and nutritional quality in pumpkins, supporting crop improvement, germplasm characterization, and sustainable production strategies.

Perceived self-efficacy on Advance Care Planning in Latin America: ACP-SE Latam validation

This dataset includes raw data from animal experiments (EF, FS), Western blot images, qPCR raw values, and statistical analyses for the study on LbGp effects on myocardial ischemia/reperfusion injury via ferroptosis.