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hybrid · semantic + lexical · 323 datasets ranked · 0.80s

Structuretabular19composite6modal2
Depthcataloged296measured27
Licenseopen315non commercial4share alike3unknown1
Accessopen323
Formatcsv305zip56pdf53xlsx34tsv20
Sourcezenodo320zenodo-bio3
clear
1-20 of 323sortrelevancemeasured firstqualitysize
tabular

Dataset Priming against Salmonella enterica affects differentially haemocyte sub-populations in Armadillidium vulgare

0.00

Pailler, Louis

207 rows × 1 cols · 22 KB · csv

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1 text

These datasets were collected using a total of 585 Armadillidium vulgare females. The objective of this study was to measure survival after immune priming with Salmonella enterica , using different doses and inactivation methods, and to characterise the underlying cellular mechanisms using flow cytometry. Survival analysis according to S. enterica method of inactivation and dosage Survival after injection of a lethal dose of live S. enterica was measured after immune priming using bacteria inactivated by heat (HK) or paraformaldehyde (PFA) and two different doses (10^3 and 10^6). This allowed to collect the Dataset_survival.csv, analysed using the Script_survival_analysis.R. Dataset_survival.csv: Ind: individual identification Treatment: priming treatment that females received. C : control females, no priming injection. PBS : females primed with sterile PBS. PFA3 / PFA6 : females primed with 10^3 or 10^6 PFA-inactivated S. enterica . HK3 / HK6 : females primed with 10^3 or 10^6 heat-inactivated S. enterica . Repl: experimental replicate Status: 1 = dead, 0 = live Survival : Time at death. 168 indicates living females at the end of the experiment Time: Time elapsed between the two injections. T24 : 24hours. T7 : 7 days Haemocyte sub-populations analysis according to priming treatment Following the survival experiment, and because the A. vulgare primed with PFA6 inactivated S. enterica exhibited the highest survival rates against LD50 infection, this inactivated method and dosage were used to examine the haemocyte sub-populations of A. vulgare mounting immune priming. Haemolymph was sampled from all females (C, PBS, PFA6) either 2 days (2D-PP) or 6 days (6D-PP) after the initial priming injection, or 2 days after the LD50 injection (2D-LD50). Distinct sets of females were used for each time point. This allowed to generate the Dataset_cytometry.csv, analysed using the Script_cytometry_pca_analysis.R. Principal Component Analysis (PCA) for each observation time allowed to extract projection values of the four PCs for each individual (Dataset_pca_ind_coord.csv). Dataset_cytometry.csv: Ind: individual identification Treatment: priming treatment that females received. C: control females, no priming injection. PBS: females primed with sterile PBS. PFA6: 10^6 PFA-inactivated S. enterica . Repl: experimental replicate Box: experimental box Exp: experimental day Time: Sampling time. 2D-PP: 2-days after priming. 6D-PP: 6-days after the priming injection. 2D-LD50: 2 days after the LD50 infection. P1_percent: Percentage of the first population. P1_FSCA: Cell diameter (size) of the first population. P1_SSCA: Internal complexity (internal granularity) of the first population. Viab_P1: Viability of the first population. P2_percent: Percentage of the second population. P2_FSCA: Cell diameter (size) of the second population. P2_SSCA: Internal complexity (internal granularity) of the second population. Viab_P2: Viability of the second population. Dataset_pca_ind_coord .csv: Ind: individual identification Treatment: priming treatment that females received. C: control females, no priming injection. PBS: females primed with sterile PBS. PFA6: 10^6 PFA-inactivated S. enterica . Repl: experimental replicate Box: experimental box Exp: experimental day Time: Sampling time. 2D-PP: 2-days after priming. 6D-PP: 6-days after the priming injection. 2D-LD50: 2 days after the lethal dose infection. Dim.1: projection values on the first principal component (PC1) for each individual. Dim.2: projection values on the second principal component (PC2) for each individual. Dim.3: projection values on the third principal component (PC3) for each individual. Dim.4: projection values on the fourth principal component (PC4) for each individual.

open·CC-BY-NC-4.0·Zenodo·0% null·completeSource
modal

Intensivkapazitäten und COVID-19-Intensivbettenbelegung in Deutschland

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Robert Koch-Institut

9 files · 197 KB · csv, pdf, zip

Der Datensatz "Intensivkapazitäten und COVID-19-Intensivbettenbelegung in Deutschland" des Robert Koch-Instituts dokumentiert die tägliche intensivmedizinische Versorgungslage seit der COVID-19-Pandemie. Basierend auf Meldungen aller intensivbettenführenden Krankenhäuser in Deutschland erfasst das DIVI-Intensivregister Echtzeitdaten zu belegten und freien Intensivbetten. Die Erhebung differenziert nach Altersgruppen, Regionen und Versorgungsstufen. COVID-19-Fälle auf Intensivstationen werden gesondert ausgewiesen. Die Daten stehen aggregiert auf Bundes-, Landes- und Kreisebene zur Verfügung. Damit bildet der Datensatz eine Grundlage für die Überwachung von Kapazitäten, die Koordination von Behandlungskapazitäten und politische Entscheidungsprozesse während der Pandemie und darüber hinaus.

open·CC-BY-4.0·Zenodo·completeSource
tabular

A global dataset of immigration flow composition by age, sex and educational attainment

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Yıldız, Dilek · Abel, Guy

123,090 rows × 6 cols · 6.8 MB · csv

5 categorical · 1 numeric

Estimates and R codes of immigration flow proportions by age, sex and education of 199 countries between 1990-1995 to 2015-2020 based on methods presented in Yildiz and Abel (2026). Version v2: Updated R scripts to extend the range of Random Forest models considered in the main SL algorithm and to include a more diverse SL algorithm, and revised output table. Immigration composition by SL provides the results by the Super Learner model with six columns for each of the data dimensions: iso3c: Destination ISO three letter country code period: Five-year periods age: Five-year ge groups sex education: Educational attainment prop: Proportion of immigration flow.

open·CC-BY-4.0·Zenodo·0% null·completeSource
tabular

TRASYS Metamodels and M2M/M2T Transformation Specifications for Continuous Traceability Management

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Morales Trujillo, Leticia · García García, Julián Alberto · Domínguez Mayo, Francisco José · et al.

11 rows × 3 cols · 1.1 KB · csv, png

3 categorical

This package provides the TRASYS validation and verification metamodel diagrams together with concise specifications of the model-to-model and model-to-text transformations documented in the doctoral thesis Continuous Traceability Management in Assisted Reproduction Processes. The materials describe the derivation of a preliminary verification model from a validation model and the generation of traceability-rule and data-structure code from the verification model. No clinical data, personal data, production code, Enterprise Architect project files, credentials, or proprietary artifacts are included.

open·CC-BY-4.0·Zenodo·0% null·completeSource
tabular

2024-04-08 Partial Solar Eclipse ESID#204

0.00

Winter, Henry · Severino, MaryKay · Volunteer Scientist

7 rows × 11 cols · 985 B · csv, pdf, zip

11 categorical

These are audio recordings taken by an Eclipse Soundscapes (ES) Data Collector during the week of the April 08, 2024 Partial 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: 29.523398 Longitude: -95.803043 Local Eclipse Type: Partial Solar Eclipse Solar Eclipse Eclipse Percent (%): 94.47 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): 17:18:47 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] N/A Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 18:38:58 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] N/A Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:00:03 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# 204]. 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.

open·CC-BY-4.0·Zenodo·60% null·completeSource
tabular

Explore Wales: A Geospatial Dataset of Heritage and Visitor Locations

0.00

Williams, Aled

206 rows × 8 cols · 40 KB · csv

4 numeric · 3 text · 1 categorical

This dataset provides a structured geospatial and descriptive record of locations of heritage, cultural, historical, natural, and visitor interest across Wales, combining thematic categories, geographic coordinates, projected coordinates, and concise contextual notes. Each entry represents a distinct location selected for its heritage, cultural, historical, natural, industrial, educational, or tourism significance. The dataset is designed to support spatial analysis, cultural and historical geography, tourism studies, and applications in optimisation, routing, and graph-based modelling. Each record includes: unique location identifier and name, thematic category, WGS 84 latitude and longitude (EPSG:4326), WGS 84 / UTM Zone 30N projected eastings and northings (EPSG:32630), a concise contextual note describing the location and its significance. Coordinates are provided in WGS 84 / UTM Zone 30N (EPSG:32630) to enable replicable planar distance calculations, optimisation modelling, clustering, and spatial analysis. The dataset covers a wide range of heritage, cultural, historical, natural, and visitor locations across Wales. It is designed as a compact, analysis-ready resource rather than a comprehensive inventory of every place of interest in Wales. The dataset and accompanying documentation are provided as CSV and Markdown files.

open·CC-BY-4.0·Zenodo·0% null·completeSource
composite

2024-04-08 Total Solar Eclipse ESID#294

0.00

Winter, Henry · Severino, MaryKay · Volunteer Scientist

16 files · 31 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: 32.20485 Longitude: -97.65127 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): 17:20:54 Totality Start Time (UTC) (2nd Contact): [N/A if partial eclipse] 18:38:29 Eclipse Maximum Time [when the most possible amount of the Sun in blocked] (UTC): 18:40:14 Totality End Time (UTC) (3rd Contact): [N/A if partial eclipse] 18:42:00 Eclipse End Time (UTC) (4th Contact): [N/A if partial eclipse] 20:00:33 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# 294]. 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.

open·CC-BY-4.0·Zenodo·completeSource
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Low-Cost and Tough Pneumatic Artificial Muscle (LT-PAM): Design Files and Documentation

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Naniwa, Keisuke · Sugimoto, Yasuhiro · Nakanishi, Daisuke · et al.

8 rows × 9 cols · 957 B · csv

7 categorical · 2 numeric

This repository contains the complete open-source design files for the Low-Cost and Tough Pneumatic Artificial Muscle (LT-PAM) , a McKibben-type soft actuator designed for research and educational use in musculoskeletal and humanoid robotics. The repository includes: - STL files for 3D printing (end plugs and mounting holders) - CAD source files in Autodesk Inventor format (.ipt) - Editable bill of materials (CSV) listing every off-the-shelf component with supplier, part number, quantity, and cost - Assembly demonstration video - A README documenting each file together with the recommended print and assembly settings Key features: - Material cost: ~USD 5 per actuator - Simple and fast, crimp-based assembly (no adhesive in load-bearing connections) - Tensile capacity: 600-800 N (rupture); recommended working load ~400 N - Durability: contraction stroke varied by less than 3% over more than 9000 pressurization cycles, with no rupture or leakage - Reproducible in-house fabrication with small sample-to-sample variability This hardware is described in detail in the accompanying HardwareX article. This design was inspired by and builds upon the open McKibben artificial muscle fabrication recipe originally shared by the Ishikawa Group Laboratory. For the original recipe, see: https://ishikawa-lab.sakura.ne.jp/mckibben_eng All design files are released under the CERN Open Hardware Licence Version 2 - Permissive (CERN-OHL-P-2.0) , and documentation is released under Creative Commons Attribution 4.0 International (CC BY 4.0) .

open·CC-BY-4.0·Zenodo·6% null·completeSource
composite

Genomic, CRISPR, and structural datasets underlying Vibrio–phage interaction and defense system analysis

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Zhang, Song · Wang, Xiaoyu · Zhang, Jiayi · et al.

17 files · 1.4 MB · csv, xlsx, zip

This dataset contains raw and processed data underlying the study on Vibrio-phage interactions, including genome sequences, CRISPR arrays, spacer-protospacer mappings, defense system annotations, phylogenetic analyses, and structural modeling outputs. It also includes scripts used for analysis and figure generation. All raw sequencing reads are deposited in NCBI SRA and genome accession numbers are provided in Supplementary files.

open·CC-BY-4.0·Zenodo·completeSource
tabular

Data supporting: Seasonal variation in bait attractiveness among six Mediterranean pest ant populations: implications for toxic bait development

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ABRIL, SILVIA · Àlex, López Cerdà · Mara, Moreno-Gómez

360 rows × 1 cols · 8.5 KB · csv

1 text

This repository contains the raw data supporting the manuscript Seasonal variation in bait attractiveness among six Mediterranean pest ant populations: implications for toxic bait development , currently under peer review. The study evaluates seasonal variation in bait attractiveness among six Mediterranean pest ant species by comparing worker recruitment to three artificial bait formulations differing in macronutrient composition. Experiments were conducted under field conditions during autumn 2024 and spring 2025. Each row of the dataset represents one bait offered during one experimental replicate. The response variable corresponds to the number of worker ants feeding on that bait 90 minutes after bait placement.

open·CC-BY-4.0·Zenodo·0% null·completeSource
tabular

Dataset for: "Fluorination of Alkoxide Ligands: Neither too much, Nor too little for Optimal Ligand Field Strength"

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de Zwart, Felix · Gehr, Noah · Landis, Joel · et al.

61 rows × 6 cols · 3.9 KB · csv, zip

5 numeric · 1 text

Computational dataset for conformer analysis of Schrock catalyst as described in the related manuscript.

open·CC-BY-4.0·Zenodo·0% null·completeSource
tabular

On the impact of the turbulent grazing flow development on the acoustic response of an acoustic liner

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Paduano, Angelo · Scarano, Francesco · Casalino, Damiano · et al.

200 rows × 10 cols · 39 KB · csv, jpeg

10 numeric

The interaction between acoustic waves and turbulent grazing flow over an acoustic liner is investigated using Lattice-Boltzmann Very-Large-Eddy simulations. A single-degree-of-freedom liner with 11 streamwise-aligned cavities is studied in a grazing flow impedance tube. The conditions replicate reference experiments from the Federal University of Santa Catarina. The influence of grazing flow (with a centerline Mach number of 0.32), acoustic wave amplitude, frequency, and propagation direction relative to the mean flow is analysed. Impedance is computed using both direct (i.e. the in-situ method) and model-fitting inference (i.e. the mode-matching method) methods. The former reveals strong spatial variations; however, averaged values throughout the sample show minimal differences between upstream and downstream propagating waves, in contrast to what is obtained with the latter method. Flow analyses reveal that the orifices displace the flow away from the face sheet, with this effect amplified by acoustic waves and dependent on the wave propagation direction. Consequently, the boundary layer displacement thickness ($\delta^*$) increases along the streamwise direction compared to a smooth wall and exhibits localised humps downstream of each orifice. The growth of $\delta^*$ alters the flow dynamics within the orifices by weakening the shear layer at downstream positions. This influences the acoustic-induced mass flow rate through the orifices at equal Sound Pressure Level, suggesting that acoustic energy is dissipated differently along the liner. The asymmetry of the flow field experienced by the acoustic wave, depending on its propagation direction, highlights the need to consider a spatially evolving turbulent flow when studying the acoustic-flow interaction and measuring impedance.

open·CC-BY-4.0·Zenodo·0% null·completeSource
tabular

Materiálové vlastnosti recyklovaných polypropylenů z automobilového průmyslu

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Habr, Jiří · Novák, Jan · Behalek, Lubos · et al.

30 rows × 11 cols · 1.5 MB · csv, xlsx

11 categorical

Dataset projektu TAČR SS07020411 "Efektivní využití plastového odpadu v automobilovém průmyslu".

open·CC-BY-4.0·Zenodo·87% null·completeSource
tabular

Root anatomical traits modulate the assembly and nitrogen transformation potential of root-associated microbiomes in a temperate steppe

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Yuan, Guangyuan

72 rows × 13 cols · 6.0 KB · csv, fasta

11 numeric · 2 categorical

This dataset supports the findings of the manuscript "Root anatomical traits modulate the assembly and nitrogen transformation potential of root-associated microbiomes in a temperate steppe" (NPH-MS-2026-55667). It contains root traits data, bacterial 16S rRNA gene absolute abundances, functional genes relative abundances, DNA extraction metadata, and phylogenetic marker sequences for 37 plant species from a temperate steppe ecosystem. The dataset includes the following files: 1. root traits.csv - Root traits including average diameter (AD), specific root length (SRL), specific root area (SRA), root tissue density (RTD), root nitrogen content (RNC), root carbon content (RCC), carbon‑nitrogen ratio (RCN), cortex layer number (CLN), cortex thickness (CT), and the ratio of cortex thickness to root diameter (CTRD). The first column lists plant species names. 2. Absolute abundance of 16S rRNA gene.csv - Quantitative PCR (qPCR) derived absolute abundances of bacterial 16S rRNA gene copies (copies/ng DNA) across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 3. DNA extraction sample weight.csv - Fresh weight (grams) of root material used for DNA extraction for each sample, linked by SampleID to the abundance data. 4. DNA extraction concentration.csv - Qubit‑measured DNA concentrations (ng/μL) and the sample volume (μL) used for quality control, together with sample metadata. 5. 37species.fasta - DNA sequences of two chloroplast markers (matK and rbcL) for the 37 plant species included in the study. The sequences are in FASTA format with headers formatted as ">Species". These were used for host phylogeny construction and Pagel's &lambda; analyses. 6. Quantitative PCR results of functional gene.csv - Quantitative PCR (qPCR) derived relative abundances of bacterial 16S rRNA gene and functional genes across different root compartments (rhizosphere, rhizoplane, endosphere), host species, root orders, and cotyledon classes (monocot/dicot). 7. README.md - A detailed description of each file, column headers, abbreviations, units, and any missing value codings (NA). All data are provided to ensure transparency and reproducibility of the analyses. For methodological details, please refer to the Materials and Methods section of the associated publication. These data are under embargo until the associated research article is published. After that date, they will be freely available under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. During the embargo period, the metadata (title, authors, abstract) and the DOI remain publicly visible, but the data files are not accessible. For access requests before the embargo expires, please contact the corresponding author.

open·CC-BY-4.0·zenodo-bio·6% null·completeSource
tabular

Microbiota study IgG4-RD AG Chang

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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.

open·CC-BY-4.0·zenodo-bio·0% null·completeSource
tabular

Datasets for "Refining simulated mineral dust composition through modified size distributions: dual validation with mineral-specific and elemental observations"

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Gómez Maqueo Anaya, Sofía · Dos Santos Souza, Eduardo José · Fomba, Khanneh Wadinga · et al.

116 rows × 16 cols · 7.0 KB · csv

11 categorical · 5 numeric

The dataset consists of three files: In-situ-NorthAfrica-compilation.csv : This file contains a compilation of in situ datasets used to produce the initial scatterplots comparing modeled and measured mineral mass fractions. All values are given as mass fraction percentages (%). The first column lists the authors associated with each published measurement. Elemental_CM-DUSTRISK-Praia.csv : This file includes the updated elemental mass concentration measurements used for comparison against the DUSTRISK2022 dataset. Measured total mass is reported in μg/m³, while elemental concentrations are given in ng/m³. The COSMO-MUSCAT outputs are identified by the prefix "CM" and are reported in μg/m³. "SD" denotes standard deviation. All variables ending in "_frac" represent mass fraction percentages (%). measurements_and-CM_compilation-JATAC2022.csv : This file contains measured elemental and the updated mineral mass fractions used for the results presented in the subsections 5.1.2 "Comparison with JATAC 2022" and 5.2.1 "JATAC 2022" . Particle size classes correspond to the MUSCAT size bins (see Table 1 of the associated manuscript) and are provided in separate columns following the format "X##", where X denotes the mineral or element and ## corresponds to MUSCAT bins (i.e., 01, 03, 09, or 26). Modeled values are provided in columns starting with "CM". The prefixes "CI025" and "CI975" denote the lower and upper confidence intervals, respectively.

open·CC-BY-4.0·Zenodo·61% null·completeSource
tabular

Dataset for manuscript: Ultra-conformal memristors for on-skin electronics

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Zamora, Esteban · Perez de Lara, David · Guidi, Luca · et al.

164 rows × 70 cols · 94 KB · csv, xlsx

70 numeric

Dataset corresponding to the figures of the article: Esteban Zamora-Amo, et al. "Ultra-Conformal memristors for on-skin electronics".

open·CC-BY-4.0·Zenodo·0% null·completeSource
modal

Dataset For "AUDIT TRANSPARANSI INFORMED CONSENT: ANALISIS KEPATUHAN KEBIJAKAN PRIVASI PLATFORM LAYANAN STREAMING VIDEO (OVER-THE-TOP) DI INDONESIA TERHADAP UU PDP NOMOR 27 TAHUN 2022"

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Putri Lenggo Genni · Tavasya Alia Anjani · Muhammad Fasha Asshofa

3 files · 2.8 MB · csv, pdf, xlsx

open·CC-BY-4.0·Zenodo·completeSource
tabular

Data for "Scalable high-fidelity and near-deterministic preparation of large photon-number states"

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Xiong, Mo · Xue, Ming

501 rows × 2 cols · 16 KB · csv

2 numeric

open·CC-BY-4.0·Zenodo·0% null·completeSource
tabular

Data for 'Distinct swimming behaviours in pupae of Aedes, Anopheles, and Culex mosquitoes'

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Drerup, Christian

8,000 rows × 9 cols · 511 KB · csv

5 numeric · 4 categorical

open·CC-BY-4.0·Zenodo·0% null·completeSource
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