Xu, Tao

3 files · 100 MB · rar, xlsx

The deepmd_data dataset comprises energy data for 375,781 structures and force data for more than 45 million atoms, generated from six hierarchical active learning iterations. The init directory stores the non-periodic molecular configurations established at the initialization stage. The iter directories contain structures labeled by both AIMD and DPMD-FP methods for each iteration. Each folder is named according to the scheme of solvent molecule index followed by lithium salt designation. The finetuned_data folder contains SEI reaction simulation data used for fine-tuning the MLFFs. Comprehensive details regarding the solvent molecules are available in the solvent_with_smiles.xlsx file.

Yuezong Wang · Yu Niu · Jiqiang Chen

2 files · 100 MB · rar, zip

This dataset contains raw experimental images, video sequences of real test samples, simulated microscopic image data from the manuscript " A robust method for microscopic 3D shape restoration via shape-from-focus" , as well as focal volume datasets collected before vibration simulation, after vibration simulation, and post anti-vibration processing. All provided data enable the validation of conclusions and reproducibility of experimental results obtained via the computational pipeline proposed in this paper.

Daugavietis, Jānis

6 files · 3.3 GB · jpeg, rardeclared

Skala Bünte, Süki Vagonu Hallē [2026.07.08.] Koncerta beigu telefona foto/ video. SKALA BÜNTE X SÜKI FACE2FACE https://fb.me/e/7dycfN2gI Details Event by John Dow Vagonu Hall Public · Anyone on or off Facebook 8TH OF JULY VAGONU HALLE TWO BANDS TWO BACKLINES MOSHPIT IN THE MIDDLE ONCE IN A LIFETIME FACE2FACE MASSACRE PROVIDED BY SKALA BÜNTE & SÜKI 🔪🔪🔪 DOORS 19:00 7€

Murilo Coelho · de Sousa Amâncio, Francisco Dione · Paixao, Matheus · et al.

3 files · 742 KB · rardeclared

This repository contains the replication package for the paper "More Productive, but at What Cost? Understanding How GenAI Shapes Developers' Work Across the SPACE Dimensions", accepted at the 40th Brazilian Symposium on Software Engineering (SBES 2026), São Paulo, Brazil. The package includes: (i) the complete survey instrument and sanitized participant responses; (ii) qualitative coding artifacts, including the codebook, category consolidation, and classification analysis; (iii) inter-rater reliability materials (Cohen's Kappa = 0.81); (iv) quantitative datasets and statistical analysis outputs (SPACE composite scores, Cronbach's alpha, Kruskal-Wallis, Mann-Whitney U, and Dunn's post-hoc tests); and (v) supporting literature review material. All participant data were anonymized prior to disclosure. The survey materials are in Portuguese, the language of data collection.

Abbas, Syed Hassan

1 files · 86 MB · rardeclared

Abbas H, et al. "GenixRL- " The VUS were extracted from CLinVar database (downloaded [Date: August 2025]) and scored using the GenixRL framework. This dataset provides the foundation for the VUS reclassification analysis presented in the main manuscript. The dataset is provided as a single compressed CSV file: GenixRL_VUS_Scored.csv.gz Key Coulmn Descriptions: [Variant Identifier Columns, e.g., CHROM, POS, REF, ALT]: Standard genomic coordinates for each variant. SYMBOL: The official gene symbol. GenixRL_Score: The continuous pathogenicity score generated by GenixRL, ranging from 0 (most likely benign) to 1 (most likely pathogenic). GenixRL_Classification: The tiered classification based on the manuscript's thresholds: 'Likely Benign': Score < 0.53 'Likely Pathogenic': Score >= 0.53 and < 0.709 'High-Confidence Pathogenic': Score >= 0.709 [Other relevant columns]: The file also includes intermediate scores from other predictors and allele frequencies used for validation.

Cao, Shiyuan · Li, Yaning

8 files · 18 MB · csv, rardeclared

This repository provides the supporting materials for the manuscript "A Confidence-Guided Sports Multi-Object Tracking Method via Jersey Semantic Fusion." The archived materials include evaluation summaries, final tracking outputs, environment records, dataset mapping files, protocol reproduction materials, intermediate summary files, and revision evidence used to support the reported SportsMOT validation results. The reported formal results were obtained from the real detector, real frame-level semantic feature extraction, confidence partitioning, cascaded association, and TrackEval evaluation pipeline. The original public benchmark datasets, including SportsMOT, TeamTrack, SoccerNet Tracking, MOT17, and MOT20, are not redistributed in this repository and should be obtained from their original providers.

Nie, Yong · Huang, Bo

1 files · 1.5 KB · rardeclared

BI tree

Nie, Yong · Huang, Bo

1 files · 9.1 KB · rardeclared

Alignments for phylogen

Rui, Jin · Cai, Chenfan

1 files · 3.7 MB · rardeclared

This dataset provides a paper-aligned 6-km grid-level perceived informality index for Southeast Asia. It is prepared as the data-release package associated with the manuscript "Unveiling the environmental drivers of urban informality in Southeast Asia through citizen science and explainable machine learning", intended for submission to npj Urban Sustainability. The release retains the ten countries used in the manuscript: Philippines, Indonesia, Vietnam, Cambodia, Myanmar, Thailand, Malaysia, Laos, Brunei and Timor-Leste. Singapore and unassigned grid cells from an earlier draft package were excluded to align the deposited data with the manuscript scope. The primary variable is informality_index, a min-max normalized 0-1 perceived informality index. Higher values indicate stronger predicted perceived urban informality. The original large-valued model output is retained as raw_informality_score for provenance, but informality_index should be used as the main manuscript-ready variable. Normalization was calculated over the retained ten-country grid cells. The package is organized into four main folders. The data/ folder contains the authoritative GeoPackage spatial layer, CSV exports, centroid-coordinate tables, administrative boundaries, country-level summary statistics and whole-dataset summary statistics. The docs/ folder contains a data dictionary, a methodology note and a processing log documenting how the release was generated. The figures/ folder contains quick-look visual summaries, including the informality-index histogram, country-level mean chart and spatial preview map. The checksums/ folder contains SHA-256 checksums for verifying file integrity. The GeoPackage file SEA_Perceived_Informality_6km_Grid.gpkg is the authoritative spatial dataset and includes grid geometries, country assignment, raw_informality_score and informality_index. The CSV files are provided for users who prefer tabular workflows or do not use GIS software. The centroid CSV includes approximate longitude and latitude for each grid cell centroid. Summary-statistics files report country-level and overall distributions of the normalized perceived informality index, with additional raw-score summaries retained for provenance. This release is intended to support reproducibility, spatial visualization and further research on perceived urban informality, environmental exposure and urban sustainability in Southeast Asia. Raw satellite imagery, Google Street View imagery and third-party geospatial layers are not redistributed in this package because they are subject to the access terms and licensing conditions of their original providers.

Haider, Haroon

1 files · 146 MB · rardeclared

This dataset provides global gridded soil nitrous oxide (N₂O) emissions for the period 1961-2019, distributed as a stack of annual NetCDF files ( N2O_soil_emissions_YYYY.nc ), one per year, giving 59 files in total. Each file resolves emissions on a regular 0.5° × 0.5° longitude-latitude mesh (720 longitude columns by 360 latitude rows) covering the full globe. Grid-cell centres are given by the lat (degrees_north) and lon (degrees_east) coordinate variables, with longitude running from -180° to +180°; the environmental-response field was rolled from its native 0-360° convention to -180-180° so that every layer shares this common grid. Ocean and other missing cells are flagged with a fill value of NaN . Within each annual file, emissions are stored as twelve monthly fields ( n2o_january through n2o_december ) together with an annual total ( n2o_annual ). The monthly fields report soil N₂O emission per grid cell in grams of N₂O-N per cell per month, and the annual field, expressed in grams of N₂O-N per cell per year, is the sum of the twelve monthly layers. Because the stored values are absolute per-cell masses rather than per-area fluxes, a regional or global total is obtained by summing cells directly and converting from grams to teragrams (dividing the summed grams by 1 × 10&sup1;²). Grid-cell emissions were computed as the product of a fertiliser-driven emission field, an environmental scaling term, and a mean precipitation modifier. Each file preserves the full provenance of this calculation through its global attributes, which record the dataset title, the reference year, the input and output units, the calculation string, the longitude-fix note, and a UTC creation timestamp, so that every layer can be traced back to its inputs and processing steps.

Gider, Veysel · Ekinci, Serdar · Izci, Davut · et al.

1 files · 96 KB · rardeclared

Experimental dataset (616 Marsh-funnel flow-time and 252 mini-slump measurements; 22 in-house PCE formulations × 4 fly-ash replacement levels × 7 dosages, w/cm = 0.35) and the complete deterministic Python pipeline reproducing every numerical result, table and figure of the associated paper. See README.md for the column dictionary and reproduction instructions.

Meekes, Lisa · Tabaro, Francesco · Bexkens, Michiel · et al.

41 files · 8.2 GB · csv, fasta, pdfdeclared

This record contains the Python software for PEPTiGEN, a tool for generating tryptic peptides from prokaryotic gene sequences and their variants, and the associated antimicrobial resistance (AMR) peptide database. The database is provided as an SQL file and a CSV file containing all genes and predicted peptides. The README file contains explanation of the PEPTiGEN tool. The SQL database schema files contains both the database schema of the SQL database used in the PEPTiGEN analysis as the database schema of the AMR peptide datbase.

José Antonio, Alonso Viamonte · María Caridad, Rodríguez Pérez

1 files · 26 MB · rardeclared

Esta base de datos contempla los materiales suplementarios del artículo en evaluación en SciELO Preprints titulado: BAJO PESO AL NACER Y CRECIMIENTO FETAL EN JOVELLANOS, MATANZAS (2024-2025): AN&Aacute;LISIS EPIDEMIOL&Oacute;GICO.

Anonymous

3 files · 143 KB · rar, zipdeclared

This repository contains the dataset, source code and context information used in the controlled experiment on Artificial Intelligence-assisted Root Cause Analysis (RCA). The study evaluates the capability of three Large Language Models (GPT-5.5 Instant, Claude Sonnet 4.6, and Gemini 3.5 Flash) to diagnose performance bottlenecks in a Node.js/Express API under load, utilizing a grey-box approach. The models did not have access to the source code; instead, they performed inference exclusively by cross-referencing network metrics (generated by the k6 tool) with server infrastructure telemetry (CPU and Heap Memory consumption). The scenario documented in this dataset focuses on diagnosing an asynchronous passive wait bottleneck (simulating N+1 queries / blocking I/O). Context-and-problem.zip: contains all the information given to the evaluators scripts.rar: contains all the code/scripts used in the experiment raw-answers.rar: contains all the answers given by the evaluators

Shojaei, Mohamadamin

1 files · 370 KB · rardeclared

This study investigates the impact of post-2008 new-generation fiscal rules on the current account balance to evaluate their effectiveness in reducing economic vulnerability. To overcome the causal identification limitations of traditional methods and the ambiguity between policy non-enforcement and Ricardian equivalence, this paper employs the Generalized Synthetic Control Method (GSCM). The empirical analysis uses a balanced panel of 111 countries (2000-2019) to independently evaluate the Balanced Budget Rule (23 countries) and the Debt Rule (19 countries). To accurately differentiate competing theories, a first-stage model assesses the primary balance to confirm de facto enforcement. Findings reveal that the Balanced Budget Rule and Debt Rule improve the current account balance by 4.7 and 3.4 percentage points of GDP, respectively. Both rules significantly enhance the primary budget balance, confirming their actual implementation. These findings robustly support the Twin Deficits hypothesis, reject Ricardian equivalence, and are confirmed through extensive robustness checks.

Çelik, Ali İhsan

1 files · 69 MB · rardeclared

Impact, Abrasion, and Freeze-Thaw Resistance of GGBFS and Carbon Fiber-Reinforced Zeolite-Based Geopolymer Paving Blocks

Anonymous Authors

15 files · 2.2 GB · parquet, rar, torchdeclared

Economic losses caused by extreme climate are not confined to the locations where events occur, but can propagate across regions through physical and economic linkages. Yet existing climate-impact assessment methods remain poorly suited to tracing how shocks spread across space and reshape the geography of economic loss. Here we develop a mechanistically informed multi-scale spatiotemporal autoregressive graph neural network model to quantify spatially cascading climate impacts. The model couples scale-specific, physically structured spatiotemporal autoregressive processes through an adaptive gating mechanism, allowing heterogeneous cross-scale interactions to be learned from data. Model estimation is achieved through tailored graph convolutional neural networks that are mathematically equivalent to spatiotemporal autoregressive models, enabling scalability while preserving transparent parameter interpretation. Monte Carlo simulation experiments show that the model accurately recovers true parameters and distinguishes between scale-dependent processes. Applying the framework to extreme precipitation, we find that large-scale upwind-to-downwind cascades driven by atmospheric circulations dominate aggregated economic losses. A one-standard-deviation increase in log extreme precipitation is associated with a 0.19 percentage-point decline in economic growth rate at the large scale, with 62.3% of the loss arising from spatial cascades. These findings highlight the need for transboundary risk governance that incorporates spatial cascading into climate-extremes monitoring and early-warning. Description of the uploaded file Monte Carlo simulation code data_generator_factors.py: Data generation script for multi-scale Monte Carlo simulation experiments. sarnn_model.py:Implementation of the proposed MS-STARGNNs model architecture definition. train.py:Training pipeline script for the MS-STARGNNs model. Data and spatial weights matrices for empirical analysis global_panel_1deg_std.parquet:Standardized Large-scale (1°) datase; global_panel_2km_std.parquet:Standardized Small-scale (2 km) dataset. W_global_2km_knn8.pt:Small-scale spatial weights matrix based on 8-nearest neighbors (KNN8). W_Large-scale:A large-scale spatial weights matrix derived from moisture transport pathways (2005-2021) mapping_1deg_to_2km.parquet: Correspondence file mapping large-scale (1°) grid cells to small-scale (2km) grid cells. ipcc_region_mapping_coarse_8regions.parquet: Mapping file linking Large-scale grid cells to the 8 IPCC AR6 reference regions. ipcc_region_mapping_fine_8regions.parquet: Mapping file linking Small-scale grid cells to the 8 IPCC AR6 reference regions. Code model.py: Core architecture definitions for empirical analysis. Provides the base classes and computational layers engineered to handle real-world geospatial complexities. All subsequent training scripts import modules from this file. STARGNNs.py: Implementation of the single-scale baseline. Serves as a reference point for evaluating the efficacy of cross-scale feature fusion. MS-STARGNNs_fixed.py: Configuration script for the MS-STARGNNs model utilizing fixed autoregressive coefficients. MS-STARGNNs.py: Configuration script for the MS-STARGNNs model utilizing annually varying autoregressive coefficients. MS-STARGNNs_8 regions.py: Executes the MS-STARGNNs model with decoupled regional parameters, loading unique autoregressive weights and βvectors for each IPCC region. Implements null value handling for regions lacking observational data (e.g., Antarctica).

LiuLab_ShanghaiTech

3 files · 644 MB · rar, zipdeclared

October 18, 2025 (v1)DatasetOpen Demo data and result for paper Large-scale single-cell long-read genomics enables high-resolution microbiome profiling

Pignalberi, Alessio · Smirnov, Artem · Truhlik, Vladimir

2 files · 2.0 MB · rardeclared

# Swarm Plasma Density Products: Climatological Statistics and ISR Conjunction Datasets **Dataset type:** Processed scientific dataset for validation and inter-comparison of ESA Swarm plasma density products against incoherent scatter radar (ISR) observations **Related manuscript:** *ESA Swarm Satellites Plasma Density Products: Comparison and Validation against Incoherent Scatter Radars Observations* **Corresponding author:** Alessio Pignalberi, Istituto Nazionale di Geofisica e Vulcanologia (INGV), alessio.pignalberi@ingv.it ## Overview This dataset contains plain-text tabular files used to compare and validate plasma/electron density products from the ESA Swarm mission against independent observations from three incoherent scatter radar facilities: Jicamarca, Arecibo, and Millstone Hill. The dataset support two complementary analyses: 1. **Climatological statistical comparison**, in which Swarm products, ISR observations, and empirical model outputs are grouped into comparable geophysical conditions defined by ISR location, altitude range, magnetic local time, season, solar activity, and geomagnetic activity. 2. **Point-wise conjunction comparison**, in which Swarm measurements are matched to ISR measurements under strict spatial, temporal, and altitude coincidence criteria. The dataset is intended for reproducing the statistical analyses, residual distributions, and validation figures described in the associated manuscript, and for enabling further comparison of Swarm plasma density products under controlled geophysical conditions.