Mendeley Data Showcase

Uncalibrated and calibrated sensor data used in Frischmon, et. al. "Evaluating machine learning model performance in a two-step colocation process for TVOC and BTEX sensor calibration." The uncalibrated data contains all sensor inputs used to build the calibration models. The calibrated data contains the concentrations predicted from the calibration models. Please note the data was time-averaged (median) to 15-min intervals prior to publication. The first hour of data collection was also removed prior to publication, as the metal oxide sensors require a warm-up period to reach operating temperatures. File name key: {modelname}_colocation_calibrated: The predicted concentrations by a given calibration model during colocation colocation_raw: The raw secondary standard sensor data collected during colocation harmonization_secondary-standard: The raw secondary standard sensor data collected during harmonization harmonization_harmonized: The harmonized sensor data collected during harmonization by field sensors harmonized_raw: The raw sensor data collected during harmonization by field sensors {model_name}_field_harmonized-and-calibrated: The predicted field concentrations by a given calibration model field_raw: The raw sensor data collected in the field Units: VOC concentration- ppb BTEX concentration- ppb NO2 concentration- ppb Uncalibrated sensor data does not have units, as it is an uncalibrated sensor signal.

This dataset contains Raman spectroscopy data for layered double hydroxides (LDH), including turmeric-functionalised variants. The data support the structural and physicochemical analysis of the materials. The dataset was prepared for the peer review process of the manuscript “Composite Nanoarchitectonics with Turmeric-Functionalised Layered Double Hydroxide/Poly(3-hydroxyoctanoate) as Bioactive Coatings for Bone and Nerve Regeneration” and includes only Raman spectroscopy results. The research was supported by the National Science Centre, Poland (UMO-2022/45/B/ST8/02557; DEC-2024/08/X/ST11/00571).

This dataset provides informative data on reproductive, familial, and lifestyle factors related to BC among women in Western Indonesia. The medical records of women with BC and women without breast or ovarian cancer at a national referral hospital and a regional hospital in West Sumatra, Indonesia, were reviewed. The data were collected from 250 women with histopathologically confirmed BC and 250 women without BC. The reproductive variables included age (<50 years; ≥50 years), age at menarche (7–11 years; 12–13 years; >13 years), age at menopause (<50 years; ≥50 years), age at first pregnancy (<20 years; 20–29 years; ≥30 years), parity (nulliparous; primiparous; multiparous), breastfeeding duration (<12 months; ≥12 months), oral contraceptive use (<12 months; ≥12 months), hormone replacement therapy (yes; no), and marital status (single/widowed; married). The familial variables included family history of BC among first-degree and second-degree relatives. The lifestyle variables included alcohol consumption, smoking, BMI, high-fat diet, high-calorie diet, and physical activity.

The results of studies on the physicochemical, morphological, mechanical, strcutral and biological analysis of composites based on poly(3-hydroxybutyrate), MXeneas and cannabinadiol intended for nerve tisue regeneration. The work was supported by the National Science Centre, Poland, under the research project Assessment of the biomedical potential of new conductive composites in the context of their use in peripheral nerve regeneration”, no. DEC-2024/08/X/ST11/00571.

This repository contains the reproducibility materials for the development and content-validity evaluation of the Scientific-Forensic Evaluation Guide for Psychological Autopsy (GECP-AP). It includes an anonymized expert-panel dataset, public analysis scripts, derived outputs, and supporting documentation used to reproduce the reported content-validity analyses. The public dataset has been de-identified and minimized for sharing and therefore does not include restricted-source files. Restricted materials are not part of this deposit. The repository is intended to support transparency, reproducibility, and secondary methodological appraisal of the GECP-AP study.

The results of comprehensive physicochemical, morphological, structural, and biological analyses of hydrogel composites based on silk fibroin, N-acetylcysteine-modified chitosan, and hydroxyapatite are presented. The materials were developed via enzyme-mediated crosslinking and evaluated in terms of their potential application in subchondral bone regeneration. The work was supported by the National Science Centre, Poland, under the research project “Hierarchical approaches for osteochondral tissue engineering”, no. UMO-2022/45/B/ST8/02557.

An SEM-NCA Approach to the Impact of Bank Affection on Bank Customer Retention and Loyalty: The Mediating Role of Satisfaction and Trust a study in Peru context

**Code for the paper ‘Projected impacts of extreme heat stress on China’s economy: A high-resolution coupling of biometeorological modeling and multi-regional input-output analysis’** **Abstract:** Our study develops a multi‑model integrated assessment framework, based on five high‑resolution CMIP6 climate models, the Liljegren physical model, a localized exposure‑response function and the AMRIO multi‑regional input‑output model, to systematically investigate the spatiotemporal patterns of future heat stress risk in China, the mechanisms of labor loss, and the resulting cascading economic effects along industrial chains under the SSP585 high‑emission scenario. The multi‑model ensemble simulation of WBGT during the historical period shows excellent overall performance (R>0.95), with the 50‑km‑resolution HadGEM3‑GC31‑HM model exhibiting the optimal performance. Future extreme heat stress risk in China, as represented by the 95th percentile of WBGT, is projected to increase significantly, with outdoor WBGT daily maximum values in South China exceeding 34 °C. Heat stress intensification follows a distinct NW-SE gradient, with larger increases in the northwest and northeast regions (1.8–2.0 °C) and smaller increases along the southeast coast (1.0–1.2 °C). This spatial heterogeneity is physically driven by the nonlinear humidity response to warming, modulated by regional topography. Future labor loss risk is the product of spatial coupling between climate stress and socioeconomic vulnerability, and two types of highly vulnerable regions are identified: “development‑lagged” and “transition‑stressed”. Under the no‑intervention scenario, national total industrial value-added loss is projected to increase from 2.7% of GDP in 2017 to 4.7% of GDP in 2050, with a growth rate exceeding that of GDP. The transport and warehousing sector, as a critical “loss transmission node”, exhibits extremely high loss rates (reaching 12.62% in Northeast China), significantly amplifying systemic risk through a positive feedback loop. The uncertainty ranges of all simulations exhibit pronounced asymmetry, with the upper bound (107–145%) dominated by parameters of socioeconomic system resilience, the importance of which is on a par with climate forcing itself. The code can be run in the following sequence once the prerequisite data files are prepared. This is provided for reference only: - **R1–6** Read, clean, and save meteorological, population and economic data - **CW1–6** Calculate historical and future, indoor and outdoor WBGT data, and generate ensemble - **V1–2** Historical validation of WBGT data - **CA** Calculate air‑conditioning penetration based on future meteorological, population and economic data - **CL1–5** Simulate labor productivity loss with air‑conditioning penetration incorporated - **CE1–2** Organize the MRIO table and simulate economic losses using the AMRIO model - **P1–9** Produce figures

Compared with other land use types, mountain meadows in the Longzhong Loess Plateau have stable carbon sequestration

This dataset was used in an evaluation pipeline for neural rendering methods that focuses on geometric accuracy, along with a benchmark comprising 19 diverse scenes containing objects from YCB dataset. Our approach enables a systematic assessment of reconstruction methods in terms of surface and shape fidelity, complementing traditional visual metrics.