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This dataset contains derived processed data, window manifests, model evaluation outputs, plotting figures, configuration files, and reproducibility scripts supporting a study on nonnegative remaining useful life (RUL) interval prediction for insulated-gate bipolar transistor (IGBT) prognostics under limited accelerated-aging data. The experiments use the public NASA IGBT accelerated-aging dataset and evaluate leave-one-device-out prediction, Deep Ensemble-TCN, Monte Carlo Dropout-TCN, GRU baselines, split conformal calibration, and device-wise conformal max calibration. This package does not redistribute the raw NASA source archive. The source data are publicly available from the NASA Open Data Portal: https://data.nasa.gov/dataset/insulated-gate-bipolar-transistor-igbt-accelerated-aging. NASA Open Data identifier: 7wwx-fk77. The included processed tables and result files support reproducibility of the manuscript tables, figures, and core interval-calibration comparisons.

This dataset contains 400 cherry tree leaf images collected from active farms in Uch-Korgon village (Kadamzhay District, Batken Region, Kyrgyzstan) using an iPhone 14. Images were captured across three separate farms in July, shortly after the June cherry harvest, from mature trees of at least ten years old. The dataset is organized into four classes, named in Uzbek as used by local growers: Sarik (leaf yellowing / chlorosis, 100 images), Teshik (shot-hole disease with perforations, 100 images), Chirish (brown rot with decaying tissue, 100 images), and Soglom (healthy leaf, 100 images). All images were captured under real outdoor farm conditions, naturally including variations in illumination, leaf orientation, shadows, occlusions, and background clutter. Each image was manually annotated using makesense.ai, with a bounding box drawn around the central leaf. Images were then cropped and standardized into square format at 224x224 pixels. This dataset is designed as a benchmark for evaluating few-shot and zero-shot learning methods in real-world, resource-constrained agricultural settings, and serves as a cross-lingual test case due to its Uzbek-language class labels.

This replication package contains the MATLAB and Dynare code, data files, auxiliary functions, and precomputed results needed to reproduce the main results and online appendix of “Persistent Global Growth Differences and Euro Area Adjustment: Real Activity, Trade and the Real Exchange Rate” by Adrian Ifrim, Robert Kollmann, Philipp Pfeiffer, Marco Ratto, and Werner Roeger (Journal of International Economics). The package includes a master script, Replication_RUN.m, which runs the different model specifications and generates the figures and results reported in the paper and online appendix. The code can either load the precomputed estimation and simulation results included in the package or re-estimate the models from scratch. Because full Bayesian estimation of the large-scale DSGE models is computationally intensive, the package includes saved results for fast replication. The replication files have been tested using MATLAB 2021b and Dynare 6.5. The folders contain auxiliary routines required by the replication code.

Replication material for the paper "Aggregate Demand Matters for Female Labour Force Participation". This replication package contains the data and Stata code required to reproduce all tables and figures presented in the paper. The paper examines female labour force participation through a macroeconomic lens, focusing on the role of aggregate demand. In line with the literature on hysteresis, we argue that growth in the level of demand expands employment opportunities and encourage women’s entry into the labour force, while demand contractions discourage participation. Using panel data for 21 OECD countries over the period 1960 to 2016, we show that sustained increases in autonomous demand are followed by durable rises in female labour force participation, whereas contractions generate similarly persistent declines. Long-run marginal effects, normalised by the treatment dosage, equal 0.133 for expansion episodes and 0.139 (in absolute value) for contraction episodes, corresponding to long-run elasticity-type measures of 0.22 and 0.23, respectively. The effects exhibit substantial heterogeneity across Varieties of Capitalism, with the long-run elasticity-type measure reaching 1.01 during expansion episodes in Mixed Market Economies. These results indicate that women’s participation is not determined solely by individual characteristics or social norms but is closely shaped by macroeconomic conditions. Strengthening demand may therefore be a powerful, and often overlooked, instrument for promoting female participation. The question is relevant today not only in view of fostering gender equality, but also of the demographic decline in mature economies: an increase in female labour force participation could provide significant additions to the labour supply, particularly in countries where it still is relatively low.

These are data for drivers of Bluegill population demographics in Iowa natural lakes collected in 2020-2025 and associated code.

The dataset includes conditioned and normalized vibration signals acquired directly at the root of each of the three blades of a rotating equipment with blades operating at 240 rpm. The blades have different health conditions; the cases considered are uncracked blades and cracked blades in one of three cross-sectional areas: root, middle, or tip. There are 10 experimental cases, with 7680 files each. The dataset was collected at a sampling rate of 1 kHz, with 500 samples per channel. The normalization was performed using the absolute maximum (Max Absolute) Scaling Method. The technique was implemented in Python using the scikit-learn (version 1.4) library.

Supplemental File for The efficacy and safety of oral minoxidil greater than 5 mg daily in hair loss disorders

This dataset contains processed, non-identifiable data and reproducibility materials for the manuscript "Network-based characterisation of latent co-testing patterns in antimicrobial susceptibility testing." Deposited materials include pairwise co-testing contingency tables, antibiotic metadata, pathogen cohort definitions, figure source data, analysis configuration files, and source code. The contingency tables capture joint observation of antimicrobial susceptibility results across antibiotic pairs, stratified by pathogen, specimen type, year, care setting, and ward type. These files support reconstruction of Jaccard, Dice, Cosine, and phi similarity matrices; FDR-filtered co-testing networks; Louvain community detection results; and all manuscript figures. Raw individual-level ARS surveillance records are excluded under data protection, surveillance governance, and data provider agreements. The deposited files contain no patient identifiers, laboratory identifiers, exact dates, free-text fields, or individual-level records.

This deidentified dataset contains the data used in all analyses reported in the associated manuscript. It includes 352 observations from 22 healthy young adults who completed a touchscreen reaching task across four sessions and four experimental conditions: dominant hand, non-dominant hand, dominant hand with cognitive load, and non-dominant hand with cognitive load. Each row represents one participant, session day, and experimental condition. Variables include participant ID, session day, hand condition, cognitive-load condition, throughput, movement time, motor error rate, and cognitive error count when applicable. No directly identifying information is included.

This dataset includes variables that reflect teachers' professional perceptions and their behavior regarding the use of artificial intelligence.