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  • How Far Can Label-Free Learning Go? Unsupervised Android Malware Detection under Contamination and Shift, with Evidence from 126,000 Behavioral Traces
    Android Malware detection using Unsupervised learning.
  • Green Finance, Energy Transition and Employment Stability across Career Stages: Evidence from China’s Green Credit Policy and a Heterogeneous-Agent Model
    Green Finance, Energy Transition and Employment Stability across Career Stages: Evidence from China’s Green Credit Policy and a Heterogeneous-Agent Model
  • Synthetic media URL normalization fixtures for Spotify, Instagram and Twitter/X
    Original deterministic synthetic conformance fixtures for the FunDownloader Link API. The dataset contains 362 accepted and rejected URL examples for Spotify tracks/playlists, Instagram posts/reels and Twitter/X status links. Each JSON Lines record includes a case identifier, platform, input URL, expected acceptance, expected canonical URL and construction rule. Identifiers are synthetic; no platform content was fetched or verified. No media, personal records or Spotify metadata are included. The corpus covers tracking removal, hostname aliases, path aliases, trailing slashes, unsupported hosts/schemes, malformed identifiers and oversized input. Expected labels follow explicit construction rules rather than parser output. All 362 records were checked against the implementation. This is a contract-specific fixture set, not an independent or exhaustive benchmark of platform URL standards, content existence or content rights. Generated with AI assistance and checked programmatically. Files: fixtures.jsonl, generate.mjs, manifest.json and README.md. Related implementation and documentation: https://fundownloader.online/developers . Project: https://fundownloader.online .
  • Entry speed and peak deceleration in the 17-0-5 curved sprint test: anonymised data and analysis code
    Anonymised data and Python code supporting the article "Peak deceleration cannot be interpreted without entry speed: a mechanical normalisation to detect real changes in football players" (Journal of Biomechanics, submitted). The dataset contains 248 repetitions of the 17-0-5 CS Test performed by 44 professional male football players from two clubs, recorded with 10 Hz GNSS (Catapult Vector S7). Each row is one repetition, with anonymised player and club codes, session, repetition number, entry speed (km/h), peak deceleration (m/s2), age, height, body mass and maximal sprint speed. The script S3_analysis.py reproduces every result reported in the article; S3_README.txt describes the variables and how to run it.
  • Air-Stable Nickel Oxide Nanosheets as a Model Platform for Decoupling Structure-Activity Relation in Oxygen Evolving Electrocatalysts
    Data repository for the "Air-Stable Nickel Oxide Nanosheets as a Model Platform for Decoupling Structure-Activity Relation in Oxygen Evolving Electrocatalysts"
  • Replication Code for Climate Change Emotions Network Analysis in Ukraine
    R code for all analyses conducted in R in the study “Emotional Responses to the Climate Crisis in Ukraine: Network Analysis and Demographic Differences”. The script covers sample description and correlations, two-way MANOVA, network estimation with EBICglasso, centrality, bootstrapped edge accuracy and stability, community detection, robustness checks for unequal group sizes, Network Comparison Tests with a power simulation, and sensitivity analyses controlling for general distress. Descriptive statistics and reliability coefficients were computed in JASP. Data 1.csv is part of the survey data collected by I. Kryazh and V. Baranov (https://doi.org/10.17632/zpcmxspz5p.1) and is provided here for reproducibility. It contains age in years and depressive symptoms (CES-D) for the 306 respondents, matched to data.csv by respondent number.
  • Long-term stabilization of living bacterial formulations using a biodegradable chitosan-based composite hydrogel
    Maintaining the viability and functional stability of living microorganisms during prolonged storage and transport remains a major challenge. In this study, we evaluated the potential of immobilization in a carboxyethylchitosan-based gel for four different probiotic bacterial strains (E. faecium L3, E. fae-calis, B. subtilis, and E. coli ) over a storage period of up to 12 months at +22 °C and +4 °C. We measured bacterial growth curves, optical density values, titer values, and growth kinetics using seven kinetic models at time points of 0, 2, 4, 6, and 12 months. For each kinetic model, we determined the goodness-of-fit metrics (R2, RMSE, AIC) and estimated parameters (y0, ymax, µmax, λ). Bacterial cultivation was performed in a bioreactor, and the data analysis was conducted using the R programming language with the minpack.lm library. During the storage of liquid controls under both temperature regimes, a significant decrease in bacterial titer was observed, whereas the gel carrier maintained a high initial bacterial titer over one year. The observed increase in the B. subtilis titer to 1010 CFU/mL, compared to other strains (typically 107 CFU/mL), is apparently due to the production of chitinases and chitosanases, which allow the bacterium to utilize chitin and chitosan as carbon and energy sources. Over the 12-month observation period, the maximum specific growth rate (µmax) varied within ranges typical for the studied species; ymax values were higher in the immobilized samples, while the lag phase (λ) was shorter than in the controls. Overall, this research highlights the potential of natural polymer hydrogels as versatile platforms for probiotic storage and encapsulation.
  • Drivers of consumer food waste behavior: A comparative systematic review of Türkiye and New Zealand
    The study-level coding dataset, quality-appraisal records, search and screening documentation, and supplementary evidence files generated for the review titled "Drivers of consumer food waste behavior: A comparative systematic review of Türkiye and New Zealand".
  • Formal ergotropy versus Gaussian-accessible work in a nonlinear optomechanical quantum battery
    The archive includes the data and validation records underlying Figs. 2–5 and Tables 1–2, selected density matrices, and scripts for reproducing the figures and tables. Full density-matrix trajectories are not included in the archive.
  • Complete mitochondrial genomes of Echinometra mathaei with different spine colors and their phylogenetic implications
    The complete mitochondrial genome of the tropical sea urchin Echinometra mathaei (de Blainville, 1825) with three different spinal color phenotypes (brown, green and white) collected from the coastal waters of Sanya was sequenced. The length of mitochondrial genome of the brown-spined, the green-spined and the white-spined sea urchin is 15696 bp, 15696 bp and 15693 bp, respectively. The three genomes each contain 13 protein coding genes, 22 tRNA genes and 2 rRNA genes. Based on the 16 sequences with high similarity obtained from NCBI and all coding sequences of the three mitochondrial genome sequences, the base composition was analyzed, and the phylogenetic tree was constructed by maximum likelihood method. The results indicated that all three phenotypes exhibited a significant A+T bias, which is consistent with the general nucleotide composition patterns observed in sea urchins. The A-T skew values show that the brown-spined sea urchin is -0.0556, the green one is -0.0554, and the white one is -0.0563, indicating a slight asymmetry in the distribution of A/T between DNA strands. Phylogenetic analysis showed that the three phenotypes and two species of Echinometra genus formed a good monophyletic evolutionary clade, but there was a certain genetic differentiation among the three sea urchins. The genome sequence data that support the findings of this study are openly available in GenBank of NCBI at [https://www.ncbi.nlm.nih.gov] (https://www.ncbi.nlm.nih.gov/) under the accession no. PX252144 (brown-spined Echinometra mathaei) – PX252145 (green-spined E. mathaei) – PX252146 (white-spined E. mathaei). The raw genome sequence data has been publicly stored in the SRA database of the NCBI. The bioproject data numbers are PRJNA1312048 (brown-spined E. mathaei) – PRJNA1312050 (green-spined E. mathaei) – PRJNA1312056 (white-spined E. mathaei). The biosample data numbers are SAMN50847818 (brown-spined E. mathaei) – SAMN50847837 (green-spined E. mathaei) – SAMN50848074 (white-spined E. mathaei). The SRA data numbers are SRR35197848 (brown-spined E. mathaei) – SRR35197869 (green-spined E. mathaei) – SRR35197872 (white-spined E. mathaei).
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