Yu, Hongzheng

3 files · 1006 KB · zip

Data and code for "The Argument of Perigee as a First-Order Control on Tidal Heating Asymmetry in Coupled Eccentricity-Obliquity Regimes"

Bittnar, Petr · Padevět, Pavel

13 files · 1.7 MB · zip

Measured data from experimental tests on concrete specimens with passive confinement during uniaxial compression testing -- various ages, various concrete mixes, and various levels of passive confinement. The data is stored in 13 datasets.

Budzinski, Lisa · Beenken, Anne Elisabeth · Sempert, Toni · et al.

9 rows × 1 cols · 743 B · csv, docx, zip

1 categorical

We have investigated an IgG4-RD (IgG4-RD) cohort by our multi-parameter microbiota flow cytometry approach to characterise the microbiota on single-cell level for attributes of the disease. The microbiota is isolated from stool samples and stained according to the published protocol for (a) host immunoglobulins IgA1, IgA2, IgM, IgG and (b) agglutinin binding to mannose, galactose or N-Acetyl-glucosamine surface sugar moieties. For all samples we also determined the microbiome composition by 16S rRNA (V3-V4) sequencing on the illumina MiSeq platform. We provide the raw .fcs and FASTQ files of 40 IgG4-RD patients. For comparison we additionally analysed 36 healthy donors. All .fcs files were generated on BD Influx®. The metadata is collected in the provided meta.csv. The staining parameters are summarized in provided panel.csv.

Saha, Sudipto · Raghava, Gajendra

1 files · 186 KB · zip

VICMpred: SVM-Based Prediction of Functional Proteins of Gram-Negative Bacteria Using Amino Acid Patterns and Composition VICMpred is a computational web server developed for predicting the major functional classes of Gram-negative bacterial proteins from amino acid sequences. The tool classifies Gram-negative bacterial proteins into four broad functional categories: virulence factors, information molecules, cellular process proteins, and metabolism-related proteins. VICMpred uses support vector machine-based models trained on amino acid composition, dipeptide composition, and class-specific tetrapeptide patterns. Web Server: https://webs.iiitd.edu.in/raghava/vicmpred/ Citation Saha, S., and Raghava, G. P. S. VICMpred: An SVM-based method for the prediction of functional proteins of Gram-negative bacteria using amino acid patterns and composition. Genomics, Proteomics & Bioinformatics, 4(1), 42-47, 2006. https://doi.org/10.1016/S1672-0229(06)60015-6 About the Research Functional annotation of proteins is one of the major challenges in the post-genomic era. Due to the rapid growth of protein sequence databases, experimental functional characterization of every newly discovered protein is not practical. Traditional methods such as BLAST, FASTA, and PSI-BLAST depend on sequence similarity. However, proteins with similar functions may show poor sequence similarity, making direct function prediction difficult. VICMpred was developed as a direct function prediction method for Gram-negative bacterial proteins. Instead of only predicting subcellular localization, it predicts broad biological functions directly from protein sequence features. Data Compilation: The final dataset contained 670 non-redundant Gram-negative bacterial proteins. These included 255 cellular process proteins, 60 information molecules, 285 metabolism proteins, and 70 virulence factors. Methodology: VICMpred uses support vector machine-based models trained on amino acid composition, dipeptide composition, PSI-BLAST similarity search, class-specific tetrapeptide patterns, and hybrid combinations of these features.

Bilén, Frida · Nahavandizadeh, Nasim · Larsson, Moa · et al.

6 files · 13 MB · zip

NMR datas (raw and processed)

Zahid, R · Lázaro, A · Moreno‐Alcántar, G · et al.

1 files · 82 KB · tar

Synthetic nanozymes have emerged as promising alternatives to natural enzymes for catalytic and therapeutic applications, yet their limited stability, aqueous compatibility, and catalytic scope impede broader utilization. Here, we report a mild, one-step sol-gel synthesis that yields ultrasmall, water-stable octa-amino silsesquioxanes functioning as metal-free nanozymes. These minimalistic nanostructures exhibit aldolase-like organocatalytic activity in water and enable dynamic, stimuli-responsive modulation of catalysis through reversible supramolecular aggregation and disaggregation triggered by specific chemical inputs, thus forming a multifunctional platform for tunable catalysis and biomedical applications. Structural simplicity, stability, and functional versatility together permit tunable, enzyme-like catalysis in water without auxiliary surfactants or phase-transfer additives. Furthermore, the nanozymes display high biocompatibility and efficient cellular internalization, enabling their use in living cells, for instance, as intracellular prodrug activators via retro-aldol activation of a doxorubicin prodrug in human glioblastoma and metastatic melanoma cells, resulting in selective cytotoxicity. This system provides a cost-effective, sustainable, and scalable platform for water-compatible, metal-free organocatalysis that bridges abiotic catalysis and biological function. These findings demonstrate how rationally designed silsesquioxane frameworks can emulate natural enzyme reactivity while integrating adaptive, stimuli-responsive behavior, broadening the applicability of synthetic nanozymes to catalytic and therapeutic contexts.

Li, Zhiyao · Wang, Ningbo · Zhong, Jiahao

6 files · 48 MB · docx, zip

GIFT-BDS is a regional ionospheric total electron content (TEC) and TEC-gradient dataset over China derived from BeiDou geostationary Earth orbit (GEO) observations and a dense ground-based GNSS receiver network. The dataset is designed to provide high-resolution observations of ionospheric TEC variability and horizontal TEC-gradient structures over China and adjacent regions. The versioned release covers the period from 19 July 2024 to 31 December 2025, corresponding to DOY 201 of 2024 to DOY 365 of 2025. The geographical coverage is 15°N-50°N and 95°E-135°E. The dataset is provided in daily NetCDF files and contains two product levels. Level-1 products provide observation-level GEO-derived slant TEC (STEC) and rate of TEC index (ROTI) records for individual receiver-GEO satellite lines of sight, with a temporal resolution of 30 s. Level-2 products provide gridded regional TEC and TEC-gradient variables, including VTEC, VTEC t , ROTI, GIX, GIX std , GIX x , GIX y , GIX t,x , and GIX t,y , with a temporal resolution of 15 min. IPP-based variables are provided on a 1° × 1° grid, while inter-IPP-gradient variables are provided on a 0.25° × 0.25° grid. The main processing steps include observation screening, cycle-slip and data-gap detection, continuous-arc segmentation, carrier-to-code leveling, satellite and receiver DCB correction, IPP calculation, inter-IPP pair selection, gradient estimation, and gridding. Quality control is applied before release. Missing values may occur because of station outages, data gaps, quality-control exclusions, or insufficient valid samples within a grid cell. Users should check the NetCDF variable attributes, including units and fill values, before analysis. The dataset is suitable for regional ionospheric studies, TEC-gradient monitoring, space-weather-related analyses, and investigations of ionospheric effects on GNSS positioning applications.

Guastamacchia, Carlo · Piersanti, Roberto · Giardini, Francesco · et al.

3 files · 31 KB · zip

This dataset contains the results of the research presented in: https://doi.org/10.48550/arXiv.2604.00881 In particular, it includes the output of electrophysiology, passive mechanics, and electromechanics simulations performed on a biventricular geometry of a murine heart. The same simulations were run on multiple fiber fields obtained by applying a smoothing procedure to the experimental fiber field, using different regularization radii. The dataset contains the following data: Fiber fields corresponding to regularization radii of 0.0 mm, 0.1 mm, 0.25 mm, 0.5 mm, 1.0 mm, and 1.5 mm. Volume-pressure curves from passive inflation tests. Activation time maps obtained by solving the eikonal problem. Displacement fields from the full electromechanical model. The simulations were run on a mesh with an average edge length of 0.15 mm.

Ahmad, Mushtaq

2 files · 16 MB · zip

This archive is the public reproducibility package for the manuscript "HYPER-Z4c: A Paper-I Reproducible Constraint-Energy-Ledger Framework for Hyperboloidal Z4c Evolution and Direct Scri Waveform Extraction," prepared for submission to the Journal of Scientific Computing. The archive contains the manuscript source, Online Resource 1 source, publication figures, processed CSV/JSON validation records, waveform-level comparison summaries, metric-worldtube readiness audit records, figure-generation scripts, convergence-fit reproduction scripts, environment files, checksum manifests, and a one-command reproduction workflow. The package supports the methods-paper evidence for a stage-synchronous constraint-energy ledger for hyperboloidal Z4c evolution, scri-compatible SAT closure, full-discrete finite-part regularization, evolved-cut BMS waveform extraction, official SXS/SpECTRE Ext-CCE waveform-level comparison, and a separate CceR0207.h5 metric-worldtube input-readiness audit. The archive does not claim a completed same-spacetime HYPER-Z4c-to-SPECTRE-CCE binary-black-hole validation. The manuscript treats the official Ext-CCE waveform-level comparison and the metric-worldtube readiness audit as separate evidence categories. A matched same-spacetime worldtube-to-CCE comparison remains future work. A minimal reproduction workflow verifies the checksum manifest, runs archive smoke tests, recomputes headline convergence-fit quantities, and regenerates the main figures from the archived records.

De Alwis Watuthanthrige, Nethmi

6 files · 5.6 MB · zip

Beck, Edgar

1 files · 100 MB · zip

This dataset includes models and results of the SINFONY software v3.0.0, which is now complete: https://doi.org/10.5281/zenodo.8006567

The Paleobiology Database Community

4 files · 100 MB · zip

Comprehensive denormalized occurrence table built with the API of the Paleobiology Database ( http://paleobiodb.org/ ). Archived for the Chronosphere project by Ádám T. Kocsis. Downloaded on 2026-06-21 with the API call: https://paleobiodb.org/data1.2/occs/list.csv?datainfo&rowcount&all_records&show=class,classext,genus,subgenus,coll,coords,loc,paleoloc,strat,stratext,lith,env,ref,crmod,timebins,timecompare,refattr,entname,attr,ident,img,plant,abund,ecospace,taphonomy,etbasis,pres,prot,lithext,geo,methods,resgroup,refattr,ent Contents: pbdb_occs.rds : occurrence table in binary R data file. pbdb_parquet.zip : occurrence table, zipped parquet file pbdb_csv.zip : occurrence table, zipped csv file metadata.txt : The metadata of the download.

Kypridemos, Chris

91 files · 100 MB · zip

Input and simulation data files for the IMPACTncd England microsimulation model, including exposure distributions, disease burden estimates, mortality rates, population estimates and projections, other required inputs, population attributable fractions (PARFs), and compiled relative risk (RR) tables. Used with the IMPACTncdEngland R package (https://github.com/ChristK/IMPACTncd_Engl).

guo, na · pan, jiachen · li, tiantian · et al.

14 files · 100 MB · csv, rar, tsv

ADM_LSIR is a physics-inspired laparoscopic aerosol degradation dataset for aerosol-aware surgical image analysis and image restoration. The v1.0.0 release contains: - 21,916 clean clinical laparoscopic frames (clean/) - 9,562 real intraoperative aerosol-degraded frames (degraded/) - 36,052 simulated aerosol masks, including 19,701 smoke-like masks and 16,351 trajectory masks (mask/) - Blender simulation/cache materials (ADM_LSIR_Blender_simulation_files_v1.0.rar) - metadata_quality_report_v1.0.csv - recommended_splits_v1.0.csv - video_mapping_v1.0.csv - parts_manifest.txt - checksums_v1.0.tsv - release_manifest_v1.0.json All released clinical frames are de-identified and stored as lossless PNG files. Filenames use anonymized video identifiers, e.g., C-V##-####.png for clean frames and D-V##-####.png for degraded frames. The recommended split is defined at the source_video_id/public_video_label level to reduce leakage across frames from the same source video. The public video labels in video_mapping_v1.0.csv provide privacy-safe source-video identifiers (video1-video19). The Blender archive documents the smoke and trajectory mask simulation setup and supports reuse, but it is not a guaranteed exact per-mask reproduction package. The released pre-rendered mask library is the primary reusable dataset component. Source code for synthesis and quality screening is available at: https://github.com/SweetDeathh/ADM_LSIR

Tsugawa, Hiroshi

1 files · 100 MB · zip

The uploaded materials contained the source data and the source code to generate Figure 3 and Figure 4 of the manuscript showing ZT Scan DIA with MS-DIAL 5.6.

Sikking, Maurits · Peisker, Fabian · Maatz, Henrike · et al.

1 files · 100 MB · zip

Project description: See related publication Code repository of the related publication: https://github.com/fpeisker303/IVIG_snRNA_project/ Methods use to generate the Single nuclear RNA sequencing data Endomyocardial biopsies (EMB) were taken from the right ventricular septum and collected via the internal jugular vein using a transcatheter bioptome (Cordis, Miami, FL., USA) at baseline before the IVIg treatment and at the standardized six-months follow-up timepoint of the original study (i.e., median 6.4 [5.9-7.3] months). EMB were evaluated regarding viral persistent and immunohistology markers of inflammation and fibrosis. Spare cardiac biopsies were stored at -80°C until preparation of snRNA sequencing. The isolation of cardiac nuclei and the 10x library preparation were performed at the Max Delbrück Center for Molecular Medicine following a published protocol (1) with adaptations to low-sized tissue pieces (2). In brief, 1-4-mg-sized flash-frozen cardiac biopsies were placed in a pre-cooled dish and an equally sized droplet of homogenization buffer (250 mM sucrose, 25 mM KCl, 5 mM MgCl 2 , 10 mM Tris-HCl, 1 μM DTT, 1× protease inhibitor, 0.4 U μl -1 RNaseIn, 0.2 U μl -1 SUPERaseIn and 0.1% Triton X-100 in nuclease-free water) was added. Buffer-encapsulated tissue pieces were sliced with a scalpel. The tissue pieces were then transferred to a 7-ml glass Dounce tissue grinder (Merck), and nuclei were isolated and stained with NucBlue Live ReadyProbes Reagent (Thermo Fisher Scientific). Hoechst + single nuclei were sorted via fluorescence-activated cell sorting (FACS) (BD Biosciences, FACSAria Fusion). Purity and integrity of nuclei were confirmed microscopically, and nuclei numbers were counted using a Countess II (Life Technologies) before processing with the Chromium Controller (10x Genomics) per the manufacturer's protocol. Single-nucleus 3' gene expression libraries were created using version 3.1 Chromium Single Cell Reagent Kits (10x Genomics) following the manufacturer's instructions. cDNA library quality control was performed using Bioanalyzer High Sensitivity DNA Analysis (Agilent Technologies) and a KAPA Library Quantification Kit. cDNA libraries were sequenced on an Illumina NovaSeq with a targeted read number of 30,000-50,000 reads per nucleus. Fastq files with sequencing results were processed using cellranger version 6.1.2 with the GRCh38-2020-A reference provided by 10x Genomics. References 1. Nadelmann ER, Gorham JM, Reichart D, Delaughter DM, Wakimoto H, Lindberg EL, et al. Isolation of Nuclei from Mammalian Cells and Tissues for Single-Nucleus Molecular Profiling. Curr Protoc. 2021;1(5):e132. 2. Maatz H, Lindberg EL, Adami E, López-Anguita N, Perdomo-Sabogal A, Cocera Ortega L, et al. The cellular and molecular cardiac tissue responses in human inflammatory cardiomyopathies after SARS-CoV-2 infection and COVID-19 vaccination. Nat Cardiovasc Res. 2025;4(3):330-45.

Winter, Henry · Severino, MaryKay · Volunteer Scientist

16 files · 100 MB · csv, pdf, zip

These are audio recordings taken by an Eclipse Soundscapes (ES) Data Collector during the week of the April 08, 2024 Total Solar Eclipse. It was decided to include only raw, unprocessed audio data files in each site-specific ZIP archive and in each Zenodo record. This decision was so that any researcher can independently verify, reproduce, and extend the analysis performed. As a result, some sites have WAV files with 0 bytes of data or timestamps outside the range of probable recording times. Procedures used by the Eclipse Soundscapes team to process audio data for its purposes are outlined in the Data Management reports located in the Eclipse Soundscapes Zenodo community. Data with 0 bytes of data were included for completeness. Data Site location information: Latitude: 44.46311 Longitude: -71.68203 Local Eclipse Type: Total Solar Eclipse Solar Eclipse Eclipse Percent (%): 100 WAV files Time & Date Settings: Set with Automated AudioMoth Time Chime (More information on TimeStamp Setting below) Data Collector Start Time Notes: N/A Included Data: Audio files in WAV format with the date and time in UTC within the file name: YYYYMMDD_HHMMSS meaning YearMonthDay_HourMinuteSecond For example, 20240411_141600.WAV means that this audio file starts on April 11, 2024 at 14:16:00 Coordinated Universal Time (UTC) CONFIG Text file: Includes AudioMoth device setting information, such as sample rate in Hertz (Hz), gain, firmware, etc. README.md: Markdown formatted file with information about the recording and recording site. file_list.csv: A machine and human file that gives the following information on each file in the record: File Name, File Type, Description, File Size in kilobytes, Name of Associated Data Dictionary with the file, calculated SHA-512 Hash of the file as a unique identifier to insure data integrity during transfer and compression. total_eclipse_data.csv: A machine and human readable file that gives the following information about the site where the audio data recording was taken: ESID#, Latitude, Longitude, Eclipse_type, CoveragePercent, Eclipse Start UTC (1st contact), Totality Start UTC (2nd contact), Totality End UTC (3rd Contact), Eclipse End UTC (4th Contact), Max Eclipse Time UTC License.txt: A human readable file that explains the terms and conditions under which the data can be used. AudioMoth_Operation_Manual.pdf: A human readable document that explains the use of an AudioMoth device. The document is current up to the time of the AudioMoth's use in the Eclipse Soundscapes project. file_list_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the file_list.csv file. CONFIG_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the CONFIG.TXT file. eclipse_data_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the total_eclipse_data.csv file. WAV_data_dict.csv: A machine and human data dictionary file that gives information on the variables contained within the *.WAV files. ES_Data_Management_Pre-Eclipse_Data_Infrastructure_Stage_0.pdf: PDF document that describes Stage 0 (Pre-Eclipse Infrastructure and Data Stewardship Planning) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Receipt_Sorting_and_Metadata_Organization_Stage_1.pdf: PDF document that describes Stage 1 (Receipt, Sorting, and Metadata Organization) of the Eclipse Soundscapes (ES) data lifecycle. ES_Data_Management_Data_Processing_Stage_2.pdf: PDF document that describes Stage 2 (Data Processing) of the Eclipse Soundscapes (ES) data Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio datalifecycle. ES_Data_Management_Data_Sharing_Stage_3.pdf: PDF document that describes Stage 3 (Public Data Sharing) of the Eclipse Soundscapes (ES) data lifecycle. Eclipse Information for this location: Eclipse Date: April 08, 2024 Eclipse Start Time (UTC) (1st Contact): 18:16:15 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] 19:28:56 Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 19:29:25 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] 19:29:53 Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:38:30 Audio Data Collection During Eclipse Week ES Data Collectors used AudioMoth devices to record audio data, known as soundscapes, over a 5-day period during the eclipse week: 2 days before the eclipse, the day of the eclipse, and 2 days after. The complete raw audio data collected by the Data Collector at the location mentioned above is provided here. This data may or may not cover the entire requested timeframe due to factors such as availability, technical issues, or other unforeseen circumstances. ES ID# Information: Each AudioMoth recording device was assigned a unique Eclipse Soundscapes Identification Number (ES ID#). This identifier connects the audio data, submitted via a MicroSD card, with the latitude and longitude information provided by the data collector through an online form. The ES team used the ES ID# to link the audio data with its corresponding location information and then uploaded this raw audio data and location details to Zenodo. This process ensures the anonymity of the ES Data Collectors while allowing them to easily search for and access their audio data on Zenodo. TimeStamp Information: The ES team and the Data Collectors took care to set the date and time on the AudioMoth recording devices using an AudioMoth time chime before deployment, ensuring that the recordings would have an automatic timestamp. However, participants also manually noted the date and start time as a backup in case the time chime setup failed. The notes above indicate whether the WAV audio files for this site were timestamped manually or with the automated AudioMoth time chime. Common Timestamp Error: Some AudioMoth devices experienced a malfunction where the timestamp on audio files reverted to a date in 1970 or before, even after initially recording correctly. Despite this issue, the affected data was still included in this ES site's collected raw audio dataset. Latitude & Longitude Information: The latitude and longitude for each site was taken manually by data collectors and submitted to the ES team, either via a web form or on paper. It is shared in Decimal Degrees format. General Project Information: The Eclipse Soundscapes Project is a NASA Volunteer Science project funded by NASA Science Activation that is studying how eclipses affect life on Earth during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. Eclipse Soundscapes revisits an eclipse study from almost 100 years ago that showed that animals and insects are affected by solar eclipses! Like this study from 100 years ago, ES asked for the public's help. ES uses modern technology to continue to study how solar eclipses affect life on Earth! Eclipse Soundscapes is an enterprise of ARISA Lab, LLC and is supported by NASA award No. 80NSSC21M0008. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Aeronautics and Space Administration. Eclipse map/figure/table/predictions courtesy of Fred Espenak, NASA/Goddard Space Flight Center, from eclipse.gsfc.nasa.gov . Eclipse Data Version Definitions {1st digit = year, 2nd digit = Eclipse type (1=Total Solar Eclipse, 9=Annular Solar Eclipse, 0=Partial Solar Eclipse), 3rd digit is unused and in place for future use} 2023.9.0 = Week of October 14, 2023 Annular Eclipse Audio Data, Path of Annularity (Annular Eclipse) 2023.0.0 = Week of October 14, 2023 Annular Eclipse Audio Data, OFF the Path of Annularity (Partial Eclipse) 2024.1.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data, Path of Totality (Total Solar Eclipse) 2024.0.0 = Week of April 8, 2024 Total Solar Eclipse Audio Data , OFF the Path of Totality (Partial Solar Eclipse) *Please note that this dataset's version number is listed below. Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) (Archival Copy) This site-level record includes the Eclipse Soundscapes Data Collector Role Training and Implementation Resources Manual (2023-2024) . The manual documents the participant training, device setup procedures, metadata submission requirements, ES ID system, timestamp protocols, data return workflow, and public archiving processes used during the October 14, 2023 annular solar eclipse and the April 8, 2024 total solar eclipse. The manual is preserved for transparency and reproducibility and reflects the procedures under which this dataset was collected and processed. (DOI 10.5281/zenodo.18623442) Data Receipt, Processing, and Analysis Methods All programs supporting Stages 1–3 are openly available in the: Eclipse Soundscapes GitHub repository: https://github.com/ARISA-Lab-LLC/ESCSP Data Management Lifecycle The following section documents the relationship of this record to the full Eclipse Soundscapes (ES) data lifecycle, a multi-stage workflow designed to support large-scale participatory science, long-term data stewardship, open science, and scientific reuse. Each stage addressed a different operational need, beginning before eclipse deployment and continuing through validation, public archiving, and scientific analysis. Together, these stages transformed distributed volunteer-submitted audio recordings into structured, documented, publicly accessible NASA-funded research assets. Stage 0: Pre-Eclipse Infrastructure and Deployment Preparation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Pre-Eclipse Infrastructure and Deployment Preparation (Stage 0). Zenodo. https://doi.org/10.5281/zenodo.20413370 Stage 0 focused on building the operational foundation required to support geographically distributed eclipse data collection at national scale. This stage included AudioMoth device preparation, accessibility modifications, ES ID # assignment systems, metadata collection workflows, participant training materials, deployment logistics, and planning for downstream data stewardship and archival workflows. The 2023 annular eclipse served as both a scientific investigation and a large-scale operational beta test that informed improvements for the 2024 total solar eclipse campaign. Related Citations and Resources: Severino, M., & Kline, T. (2025, November 24). Eclipse Soundscapes Apprentice Role Curriculum: Solar Eclipses and Multi-Sensory Observing (Informal Education). Zenodo. https://doi.org/10.5281/zenodo.17703003 Severino, M., & Bauer, D. J. (2026). Eclipse Soundscapes Observer Role Training and Resources Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18633602< /li> Severino, M., Winter, H., & Bauer, D. J. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Stage 1: Receipt, Sorting, and Metadata Organization Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Receipt, Sorting, and Metadata Organization (Stage 1). Zenodo. https://doi.org/10.5281/zenodo.19471425 Stage 1 transformed returned participant materials into organized, traceable site-level records. This included receiving mailed microSD cards, consolidating participant-submitted metadata, reconciling handwritten and online records, organizing physical audio media by ES ID #, and deriving eclipse timing and coverage information using NASA eclipse prediction datasets. The outputs of Stage 1 established the structured metadata relationships required for downstream validation, processing, archiving, and analysis workflows. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). EPTT (Eclipse Phase Timing Tool) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-Eclipse-Phase-Timing-Tool /li> Espenak, F. (n.d.). Eclipse predictions by Fred Espenak, NASA's GSFC Eclipse Web Site. NASA Goddard Space Flight Center. http://eclipse.gsfc.nasa.gov/eclipse.html Stage 2: Data Processing and Validation Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Data Processing (Stage 2). Zenodo. https://doi.org/10.5281/zenodo.18683402 Stage 2 focused on centralized audio ingestion, validation, timestamp verification, metadata reconciliation, and preparation of datasets for analysis and public sharing. During this stage, returned audio recordings were processed using custom open-source tools developed by the ES team, including ES WAVES and ES AMES. The project implemented scalable infrastructure capable of processing large volumes of participant-submitted microSD cards while preserving all raw audio data without modification. Stage 2 established the validated dataset structure required for long-term preservation and scientific analysis. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). ES WAVES (Eclipse Soundscapes WAV Audio Validation & Extraction Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-WAV-Audio-Validation-Extraction-Suite Winter, H., & Goncalves, J. (2026). ES AMES (Eclipse Soundscapes AudioMoth Metadata Extractor Suite) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/ESCSP-ES-AMES-AudioMoth-Metadata-Extractor-Suite Stage 3: Public Data Sharing and Open Archiving Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Management: Public Audio Data Sharing (Stage 3). Zenodo. https://doi.org/10.5281/zenodo.18683437 Stage 3 transformed validated site-level datasets into publicly archived, DOI-assigned research records published through the Eclipse Soundscapes Zenodo Community. This stage included dataset packaging, metadata standardization, README generation, integrity verification, DOI assignment, and automated repository upload workflows using the Automated Zenodo Upload Software (AZUS). These workflows established the project's long-term open-science infrastructure and ensured that datasets remained findable, accessible, interoperable, reusable, and citable for future scientific and educational use. Related Citations and Resources: Winter, H., & Goncalves, J. (2026). AZUS (Automated Zenodo Upload Software) [Computer software]. GitHub. https://github.com/ARISA-Lab-LLC/AZUS-Automated-Zenodo-Upload-Software Stage 4: Scientific Analysis and Research Use Stage 4 involves the scientific analysis and interpretation of validated eclipse soundscape datasets. Analysis workflows utilized datasets verified during earlier stages to investigate eclipse-related environmental and animal vocalization changes across hundreds of recording sites. This stage also includes broader scientific interpretation, publication development, and continued reuse of Eclipse Soundscapes datasets and infrastructure for future research, education, and open-science applications. Related Citations and Resources: Pease, B., Gilbert, N., & Severino, M. (2026). Eclipse Soundscapes Preliminary Findings – How Eclipses Affect Nature as determined by Sound (Recorded Webinar). Zenodo. https://doi.org/10.5281/zenodo.18613979 Gilbert, N. A., Pease, B. S., Severino, M., & Winter, H. III. (2026). Photic niche explains avian behavioral responses to solar eclipses. Ecology and Evolution, 16(2), e73090. https://doi.org/10.1002/ece3.73090 Analysis code repository: https://github.com/BrentPease1/eclipse-traits Companion Zenodo record archiving structured analysis scripts and derived outputs: https://doi.org/10.5281/zenodo.15790879[r] Public Archiving, Privacy, and Data Transparency The Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023-2024) includes a detailed explanation of how Eclipse Soundscapes audio data are publicly archived on Zenodo, how participant privacy is protected through the ES ID system, and how transparency and traceability are maintained. It also outlines the criteria for determining which recordings are included in the public archive, as well as the distinction between publicly shared archival data and datasets used for ES-led scientific analyses. Participants and data users can consult this section for full documentation of the project's open science and privacy practices. Severino, M., & Winter, H. (2026). Eclipse Soundscapes Data Collector Role Training and Implementation Manual (2023–2024). Zenodo. https://doi.org/10.5281/zenodo.18623443 Citations Individual Site Citation: APA Citation (7th edition) Winter, H., Severino, M., & Volunteer Scientist. (2026). 2024 solar eclipse soundscapes audio data [Audio dataset, ES ID# 292]. Zenodo.{Insert DOI} Collected by volunteer scientists as part of the Eclipse Soundscapes Project. This project is supported by NASA award No. 80NSSC21M0008. Eclipse Community Citation Winter, H., Severino, M., & Volunteer Scientists. 2023 and 2024 solar eclipse soundscapes audio data [Collection of audio datasets]. Eclipse Soundscapes Community, Zenodo. https://zenodo.org/communities/eclipsesoundscapes/ Collected by volunteer scientists as part of the Eclipse Soundscapes Project This project is supported by NASA award No. 80NSSC21M0008.

Du, Yutong · Song, Junnian · Yao, Tianfu · et al.

11 files · 100 MB · xlsx, zip

HMLE-China is a spatially explicit, high-resolution, stage-resolved, multi-pollutant livestock emission inventory for mainland China in 2022. The dataset provides a comprehensive suite of GeoTIFF raster layers at a spatial resolution of 1 km, covering five major livestock species (beef cattle, dairy cows, swine, sheep/goats, and poultry), two production systems (extensive and intensive), four emission-related production stages (enteric fermentation, housing management, manure management, and energy use), and nine enivrionmental indicators of greenhouse gas, air pollutant, and water pollutant. In total, the dataset contains 985 GeoTIFF files, forming a nationally consistent, gridded emission inventory that enables full-chain environmental accounting of livestock production systems. Emissions are explicitly resolved by species, production system, and process stage, allowing detailed attribution of environmental burdens across heterogeneous livestock management practices. The inventory integrates multiple emission pathways, including direct biological emissions (e.g., enteric CH4 and manure-related CH4 and N2O), indirect nitrogen transformations (e.g., NH3 volatilization and downstream nitrogen emissions), energy-related emissions (coal, diesel, and electricity use), and nutrient-related pathways (nitrogen and phosphorus flows in both process-based and water-related compartments). This dataset is designed to support spatially explicit environmental assessment, policy analysis, and mitigation strategy development for livestock systems. It enables consistent evaluation of greenhouse gas emissions, air pollutants, and water pollutants within a unified multi-pollutant framework, facilitating integrated assessment of environmental trade-offs across production systems and regions. The dataset can be used for national-scale environmental footprint analysis, hotspot identification, life-cycle assessment, and climate-air-water co-benefit studies of livestock production systems.

Zhang, Xinmiao · Li, Zhuoran · Zhang, Dan

1 files · 100 MB · zip

This repository provides the data and full analysis pipeline used in the study.