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PARAGON 2 - KM2209 - Iron Uptake Timecourse Incubations
<p>This dataset contains measurements of rates of dissolved iron (Fe) uptake collected during the PARAGON 2 expedition (KM2209) in the North Pacific Subtropical Gyre. Measurements come from time-course incubation experiments initiated with whole seawater collected at 150 m using trace metal clean techniques and modified with various additions of organic carbon, iron, and/or nitrogen. Rates of iron uptake were measured at multiple time points for each experimental biological replicate by subsampling 250 mL aliquots from polycarbonate incubation bottles into new polycarbonate bottles and spiking with a final concentration of 0.4 nmol L⁻¹ ⁵⁵FeCl₃ with a specific activity of 2.74 Ci mmol⁻¹ of Fe (Perkin Elmer). A killed blank measurement was made for each experimental treatment by spiking an additional 250 mL aliquot with a final concentration of 1% glutaraldehyde prior to spiking with ⁵⁵FeCl₃. All aliquots were then incubated in the dark at in situ temperature for 8-10 hours. Incubations were terminated by filtering the entire 250 mL aliquot for each sample through a 0.2 µm polycarbonate filter. In order to remove extracellularly bound Fe, filters were rinsed 3 times with an oxalate wash according to Tang and Morel (2006) followed by three rinses with 0.2 µm filtered seawater. Filters were then transferred to high density polyethylene scintillation vials and submerged in 10 mL of Ultima Gold LLT scintillation cocktail (Perkin Elmer). Radioactivity incorporated into microbial biomass was measured on a TriCarb 4910TR scintillation counter. Values reported are blank-corrected but have not been adjusted for isotope dilution resulting from unlabeled iron present in situ. Timestamp is in UTC.</p>
PARAGON 2 - KM2209 - Particulate Carbon and Nitrogen Timecourse Incubations
<p>This dataset contains measurements of particulate carbon and nitrogen concentrations collected during the PARAGON 2 expedition (KM2209) in the North Pacific Subtropical Gyre. Measurements come from time-course incubation experiments initiated with whole seawater collected at 150 m using trace metal clean techniques and modified with various additions of organic carbon, iron, and/or nitrogen. Samples for measurements of particulate carbon and nitrogen concentrations were collected at multiple time points for each experimental biological replicate by filtering 4 L of seawater from polycarbonate incubation bottles onto pre-combusted 25 mm glass fiber filters (GF/F, Whatman) under positive pressure. Filters were then transferred to polystyrene Petri dishes lined with pre-combusted aluminum foil and stored at -20°C until analysis onshore. Filters were then analyzed by high temperature combustion using an Exeter CE-440 Elemental Analyzer according to Grabowski et al. (2019). Particulate carbon concentrations are measurements of total particulate carbon, including both organic and inorganic carbon. Timestamp is in UTC.</p>
PARAGON 2 - KM2209 - Total Organic Carbon Timecourse Incubations
<p>This dataset contains measurements of total organic carbon concentrations (TOC) collected during the PARAGON 2 expedition (KM2209) in the North Pacific Subtropical Gyre. Measurements come from time-course incubation experiments initiated with whole seawater collected at 150 m using trace metal clean techniques and modified with various additions of organic carbon, iron, and/or nitrogen. Samples for measurements of TOC concentrations were collected at multiple time points for each experimental biological replicate by aliquoting 40 mL of whole seawater from polycarbonate incubation bottles into pre-combusted borosilicate vials. Samples were acidified with 27 µL of 12N HCl (Optima grade, Fisher), capped with Teflon-lined silicone septa lids, and stored in the dark at room temperature until analysis on shore. Total organic carbon concentrations were determined by high temperature combustion on a modified Shimadzu TOC analyzer according to Carlson et al. (2010). Timestamp is in UTC.</p>
PARAGON 2 - KM2209 - Leucine Incorporation Timecourse Incubations
<p>This dataset contains measurements of rates of leucine incorporation as a measure of bacterial production collected during the PARAGON 2 expedition (KM2209) in the North Pacific Subtropical Gyre. Measurements come from time-course incubation experiments initiated with whole seawater collected at 150 m using trace metal clean techniques and modified with various additions of organic carbon, iron, and/or nitrogen. Rates of leucine incorporation were measured at multiple time points for each experimental biological replicate by subsampling 1 mL aliquots from polycarbonate incubation bottles into 2 mL microcentrifuge tubes (Axygen) and spiking with a final concentration of 20 nmol L⁻¹ leucine with a ³H specific activity of 53.3 Ci mmol⁻¹ of leucine (Perkin Elmer). A killed blank measurement was made for each experimental biological replicate by spiking an additional 1 mL aliquot with 100 µL of 100% (w/v) ice-cold trichloroacetic acid (TCA) prior to spiking with ³H-leucine. All aliquots were then incubated in the dark at in situ temperature for 4-6 hours after which live incubations were terminated with the addition of 100 µL of 100% (w/v) ice-cold TCA. Samples were processed at sea using the centrifugation method of Smith and Azam (1992), and radioactivity incorporated into bacterial protein was measured on a TriCarb 4910TR scintillation counter using Ultima Gold LLT scintillation cocktail (Perkin Elmer). Values reported are the blank-corrected averages of technical triplicate measurements from each sample. Timestamp is in UTC.</p>
A biodiversity dataset graph: Biological Associations in TaxonWorks hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 hash://md5/686007de79cc2a49ab23fd3debe56e3f
<p>The intended use of this archive is to facilitate (meta-)analysis of Biological Associations captured in TaxonWorks [1]. TaxonWorks is an integrated web-based workbench for taxonomists and biodiversity scientists. It allows you to capture, organize, and enrich your data; share it with collaborators; and package it for analysis and publication. </p> <p>This dataset provides versioned snapshots of the TaxonWorks network as tracked by Preston [2,3,4] during 2024-05-07 using:</p> <pre><code>preston track -u https://sfg.taxonworks.org</code></pre> <p>. In addition, this dataset provides a processed version of the biological associations using the "preston tw-stream" command as generated by the following bash script:</p> <pre><code>#!/bin/bash # # Generates GloBI interaction JSON Lines from provided provenance log as generated by preston tw-stream. # /usr/local/bin/preston cat hash://sha256/c1b081afa6ea0f60570c24cca85c4d9acd91eeefe36b9cacd1fe53b6893ea154\ | /usr/local/bin/preston tw-stream </code></pre> <p><br>The script itself was executed using:</p> <pre><code>cat transform.sh | preston bash </code></pre> <p>The execution of this transform.sh script (with content id hash://sha256/6dfe3c4ebf877bed73aebbe88c7d388bf894c569578ed7b28ca68e57a6afe43b), as well as their results, is captured within this datasets also. A rdf/quads formatted machine readable version of the workflow execution description can be found via:</p> <pre><code>preston cat hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 </code></pre> <p>And, the resulting JSON Lines file has content id (or signature) hash://sha256/4c2b8642251ced5985660d63c565efa6e5a9bf3d12b3b0c0d9ac577905f5e897 and is also included as interactions.json to facilitate access. </p> <p>The first json record can be generated using:</p> <pre><code>preston cat hash://sha256/4c2b8642251ced5985660d63c565efa6e5a9bf3d12b3b0c0d9ac577905f5e897\ | head -n1\ | jq . </code></pre> <p>or, provided that the interactions.json has content id starting with hash://sha256/4c2b86...</p> <pre><code>cat interactions.json\ | head -n1\ | jq . </code></pre> <p>This produces the following (formatted) json object:</p> <pre><code>{<br> "http://www.w3.org/ns/prov#wasDerivedFrom": "hash://sha256/fdbf13dc5f3d9c5afbc03db62699e2ce2724c499b7d91d8b0bf31e39409b153a",<br> "http://www.w3.org/1999/02/22-rdf-syntax-ns#type": "application/vnd.taxonworks+json",<br> "referenceId": "https://sfg.taxonworks.org/api/v1/sources/213218",<br> "interactionId": "https://sfg.taxonworks.org/api/v1/biological_associations/227664",<br> "taxonRootsResolved": 2,<br> "referenceResolved": true,<br> "referenceCitation": "@article{213218,\n author = {Monzen, Kota},\n journal = {Annual Report of the Gakugei Faculty of the Iwate University},\n pages = {24-38},\n title = {Revision of the Japanese gall wasps with the descriptions of new genus, subgenus, species and subspecies (II). Cynipidae (Cynipinae) Hymenoptera.},\n volume = {6},\n year = {1954}\n}\n",<br> "interactionTypeId": "gid://taxon-works/BiologicalRelationship/69",<br> "interactionTypeName": "gall",<br> "sourceTaxonName": "Neuroterus hakonensis",<br> "sourceTaxonId": "gid://taxon-works/TaxonName/1174121",<br> "sourceTaxonRank": "species",<br> "sourceTaxonAuthorship": "Ashmead, 1904",<br> "sourceTaxonPath": "Root | Cynipidae | Neuroterus | Neuroterus hakonensis",<br> "sourceTaxonPathIds": "gid://taxon-works/TaxonName/623170 | gid://taxon-works/TaxonName/1170060 | gid://taxon-works/TaxonName/1170097 | gid://taxon-works/TaxonName/1174121",<br> "sourceTaxonPathNames": "nomenclatural rank | family | genus | species",<br> "targetTaxonName": "Quercus",<br> "targetTaxonId": "gid://taxon-works/TaxonName/1173543",<br> "targetTaxonRank": "genus",<br> "targetTaxonAuthorship": "",<br> "targetTaxonPath": "Root | Fagaceae | Quercus",<br> "targetTaxonPathIds": "gid://taxon-works/TaxonName/623170 | gid://taxon-works/TaxonName/1173542 | gid://taxon-works/TaxonName/1173543",<br> "targetTaxonPathNames": "nomenclatural rank | family | genus"<br>}<br></code></pre> <p>In this example, a claim is made that, according to https://sfg.taxonworks.org/api/v1/sources/213218 [6] Neuroterus hakonensis (a gall wasp) has a primary host in the genus of Quercus (oak tree). </p> <p>In total, 237,068 such claims can be found in the generated resource with alias interactions.json and content id starting with hash://sha256/4c2b86... .</p> <p>In addition, the archive preston.tar.gz to allow for batch download. The archive contains three types of files: index files, provenance logs and data files. In addition, index files have been individually included in this dataset publication to facilitate remote access. Index files provide a way to links provenance files in time to establish a versioning mechanism. Provenance files describe how, when, what and where the TaxonWorks content was retrieved. For more information, please visit https://preston.guoda.bio or https://doi.org/10.5281/zenodo.1410543 . </p> <p>To retrieve and verify the downloaded TaxonWorks biodiversity dataset graph, download preston.tar.gz. Then, extract the archive into a "data" folder. Alternatively, you can use the preston[2] command-line tool to "clone" this dataset using:</p> <pre><code>java -jar preston.jar clone --remote https://zenodo.org/record/11151783/files </code></pre> <p>After that, verify the index of the archive by reproducing the following provenance log history:</p> <pre><code> java -jar preston.jar history --log tsv</code></pre> <p>to be:</p> <pre><code>hash://sha256/e4a47c067d6c125da60c9a1b92b5eecdea539cb8666cd3aed99db347ae5b8ed0 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/c1b081afa6ea0f60570c24cca85c4d9acd91eeefe36b9cacd1fe53b6893ea154 </code><br><code>hash://sha256/c1b081afa6ea0f60570c24cca85c4d9acd91eeefe36b9cacd1fe53b6893ea154 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/ab7550368905e7c919e70a306efbb97719a1edbba2cfe4c4515f635ebc0be4bb hash://sha256/a4d651aac5220487835e6178511886e98b845b2d98cb7c5447fb2b042e0654d2 http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/ab7550368905e7c919e70a306efbb97719a1edbba2cfe4c4515f635ebc0be4bb</code><br><code>hash://sha256/ab7550368905e7c919e70a306efbb97719a1edbba2cfe4c4515f635ebc0be4bb http://www.w3.org/ns/prov#wasDerivedFrom hash://sha256/ff5e709305e593c87711e897b6341b94e775e2f312aa6d4ae5ed6120babd6f5e urn:uuid:0659a54f-b713-4f86-a917-5be166a14110 http://purl.org/pav/hasVersion hash://sha256/ff5e709305e593c87711e897b6341b94e775e2f312aa6d4ae5ed6120babd6f5e </code></pre> <p><br>To check the integrity of the extracted archive, confirm that each line produce by the command "preston verify" produces lines as shown below, with each line including "CONTENT_PRESENT_VALID_HASH". Depending on hardware capacity, this may take a while.</p> <pre><code>java -jar preston.jar verify</code></pre> <p>Note that a copy of the java program "preston", preston.jar, is included in this publication. The program runs on java 8+ virtual machine using "java -jar preston.jar", or in short "preston". </p> <p>Files in this data publication:</p> <p>--- start of file descriptions ---</p> <p>-- description of archive and its contents (a rendition of this file) --<br>README</p> <p>-- biological associations indexed from TaxonWorks expressed in a GloBI [5] compatible JSON Lines file --<br>interactions.json</p> <p>-- first 10 biological associations indexed from TaxonWorks expressed in a GloBI [5] compatible JSON Lines file --<br>interactions-10.json</p> <p>-- executable java jar containing preston [2,3,4] v0.8.5-SNAPSHOT. --<br>preston.jar</p> <p>-- preston archive containing TaxonWorks data files, associated provenance logs and a provenance index --<br>preston.tar.gz</p> <p>-- individual provenance index files --</p> <p>1fed32bf78298d7ecc3d9f36d106f1d7d7773a8b9a5e47af6632f36c1f82adb5<br>29306c5c144c3d7fd21be344d8b6b554b6f6efa3b8f8f5c0b27cdf0e88785652<br>2a5de79372318317a382ea9a2cef069780b852b01210ef59e06b640a3539cb5a<br>d31ff1ef1dea88c5952181a4f30e7ea7862873aa5f66430451275aa6d08d329e<br>deb84d69224af488da585186f88cafc58e978db5f9897de624cc9b02c0c83742<br>e9c34683f1e826f68f841f3419bd5ee9c0fa18be04713a6fd3364f226c7c5f2f<br>f98d36a9dc7bd833c93b3b61130865628f7bc2f7bb0920e95afcd16fba3dc6a8<br>ffb41d48979ceb964fbfbeb68cb60b584b759950087fdcc012521b866249bc39</p> <p>--- end of file descriptions ---</p> <p>This work is funded in part by grant NSF OAC 1839201, NSF DBI 1901932, NSF DBI 1901926, and NSF DBI 2102006 from the National Science Foundation.<br> </p>
Mapping of a Mid-depth Salinity Maximum Intrusion south of New England in June 2021
<div> <div> <p>This dataset contains data from a process-oriented research cruise aboard the R/V Neil Armstrong from June 18th to July 2nd. The goal of this cruise was to map the three-dimensional structure of a mid-depth salinity maximum intrusion of warm salinity slope water extending onto the continental shelf south of New England. This was done through the use of Autonomous Underwater Vehicles (two REMUS 100 vehicles and one Tethys class AUV (Long Range AUV or LRAUV)), a towed Rockland Scientific Vertical Microstructure Profiler (VMP 250), and ship-board CTD and ADCP measurements. More details about the processing, data coverage, and usage can be found in the accompanying manuscript. This cruise took place on the shelf waters south of Cape Cod, MA, extending to the shelf break, with all of the data collected between 40°N to 41°N and 71.5°W to 70°W. Attached is a data map showing the location of all data included within this dataset. </p> </div> <div> <p> </p> </div> <div> <p>File Descriptions: </p> </div> <div> <p><strong>Datamap.jpg </strong></p> </div> <div> <p>A map of the locations of all data included within this dataset. </p> </div> <div> <p> </p> </div> <div> <p><strong>CTD_summer2021.mat </strong></p> </div> <div> <p>This file contains profiles from the ship-board CTD (SeaBird 911+). Raw data was processed and gridded into 1 decibar bins using standard procedures in Seasave V 7.26.7.121 (Look at cnv file header for details about processing). This file is organized as a structure, with each variable in the data being a different field called by dot notation and each row with the structure being a different CTD profile. Biooptical variables are not quality-controlled. </p> </div> <div> <ul> <li> <p>CTD.time: the time of each profile in the MATLAB datetime format (from the processed SeaBird header file) in GMT </p> </li> <li> <p>CTD.lon: degrees longitude of the profile (from the processed SeaBird header file) </p> </li> <li> <p>CTD.lat: degrees latitude of the profile (from the processed SeaBird header file) </p> </li> <li> <p>CTD.pres: the pressure in decibar at each location of the profile </p> </li> <li> <p>CTD.sal: the seawater practical salinity in psu </p> </li> <li> <p>CTD.temp: the seawater in-situ temperature in °C </p> </li> <li> <p>CTD.flor: seawater fluorescence in mg/ m3 </p> </li> <li> <p>CTD.depth: depth at each location within the profile in meters </p> </li> <li> <p>CTD.density: sigmatheta (the potential seawater density with respect to a reference pressure of 0 db) in kg.m3 minus 1,000kg/m3 </p> </li> </ul> </div> <div> <p> </p> </div> <div> <p><strong>CTD_Darter_MMMdd.mat and CTD_Edgar_MMMdd.mat </strong></p> </div> </div> <div> <div> <p>These files contain the data from the REMUS 100 missions, with Darter and Edgar being the two different REMUS 100 vehicles. </p> </div> <div> <ul> <li> <p>Conductivity: conductivity in mS/cm </p> </li> <li> <p>Depth: depth in meters </p> </li> <li> <p>Latitude: degrees latitude </p> </li> <li> <p>Longitude: degrees longitude </p> </li> <li> <p>Mission_number: the number of the REMUS mission </p> </li> <li> <p>Mission_time: time during the mission in seconds since midnight in GMT </p> </li> <li> <p>Salinity: the seawater practical salinity in psu </p> </li> <li> <p>Sound_speed: the sound speed in m/s </p> </li> <li> <p>Temperature: the seawater temperature in °C </p> </li> </ul> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p><strong>LRAUV_20210623T194917.mat and LRAUV_20210624T145829.mat </strong></p> </div> <div> <p>These files contain data from the Tethys Class LRAUV (Long Range AUV) missions. Each file contains 10 structure variables. </p> </div> </div> <div> <div> <ul> <li> <p>CTD_Seabird: structure containing the bin median temperature in °C and salinity in PSU. </p> </li> <li> <p>depth: the depth at each data point in meters. </p> </li> <li> <p>fix_residual_percent_distance_traveled: underwater dead-reckoned navigation error (based on GPS fix when on surface) as a percentage of distance traveled </p> </li> <li> <p>latitude: Latitude at each data point (not corrected for vehicle drift in underwater current) </p> </li> <li> <p>latitude_fix: latitude of GPS fix (vehicle surfaced) </p> </li> <li> <p>longitude: Longitude at each data point (not corrected for vehicle drift in underwater current) </p> </li> <li> <p>longitude_fix: longitude of GPS fix (vehicle surfaced) </p> </li> <li> <p>platform_battery_charge: The battery charge in ampere-hour </p> </li> <li> <p>time_fix: time in seconds since January 1, 1970 (epoch time) </p> </li> </ul> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p><strong>VMPtransact_YYYYMMdd.mat</strong></p> <p>Vertical Microstructure Profiler (Rockland Scientific VMP 250) </p> </div> <div> <p>These files contain the processed data for each Vertical Microstructure Profiler (Rockland Scientific VMP 250) transect, consisting of multiple profiles. Data has been gridded on a 1 decibar equidistant grid using standard procedures in Rockland Scientific’s processing software. Note: Bio-optical variables and dissipation rates have not been quality-controlled. </p> </div> <div> <ul> <li> <p>Time: Time in MATLAB datenum format (days since 0000-00-00 00:00:00) in GMT </p> </li> <li> <p>z: Pressure in decibar </p> </li> <li> <p>T: in-situ temperature in degC </p> </li> <li> <p>cnd: conductivity in mS/cm </p> </li> <li> <p>Chl: Chlorophyll from fluorescence in mg/ m3 </p> </li> <li> <p>turb: Turbidity in NTU </p> </li> <li> <p>eps: dissipation rate inferred from microstructure shear in m^2/s^3. (Note: Dissipation estimates come from standard fitting of microstructure data within a 1 decibar bin to a turbulence spectrum within Rockland Scientific’s standard processing. The dissipation data in the provided files has not been quality-controlled. </p> </li> </ul> </div> <div> <p> VMP-data was georeferenced by comparing the time stamps of VMP and processed ADCP files. </p> </div> <div> <p> </p> </div> <div> <p><strong>ADCP_ar50_wh300.mat </strong></p> </div> <div> <p>This file contains the data from the shipboard ADCP (Teledyne WH300 kHz). ADCP data was processed aboard using standard procedures in UHDAS/CODAS (University of Hawaii Technical Services Program, servicing UNOLS vessels (<a href="https://currents.soest.hawaii.edu/docs/adcp_doc/index.html" target="_blank" rel="noreferrer noopener">https://currents.soest.hawaii.edu/docs/adcp_doc/index.html). Vertical bin size is 2 m. </a>u: zonal (positive towards east) velocity component in m/s </p> <ul> <li> <p>v: meridional (positive towards north) component in m/s </p> </li> </ul> </div> </div> <div> <div> <ul> <li> <p>txy: time, longitude, and latitude of the velocity profiles. Time is in decimal days, with noon of Jan 1 being 0.5 decimal days and noon of January 20th being 19.5 decimal days of the reference year. For another example, 6am on June 18, 2021, is decimal day 168.25. All times are in GMT. </p> </li> <li> <p>refyear: The reference year from which the decimal days are calculated. </p> </li> <li> <p>depth: vertical coordinate of the velocity bin center </p> </li> <li> <p>pgood: percent good, a quality parameter showing the fraction of good pings within an ensemble average. </p> </li> <li> <p>spd_u: zonal ship speed in m/s </p> </li> <li> <p>spd_v: meridional ship speed in m/s </p> </li> <li> <p>tr_temp: ADCP transducer temperature in deg C </p> </li> <li> <p>amp: backscatter amplitude in relative units </p> </li> </ul> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p> </p> </div> <div> <p> </p> </div> </div>
Data from Phenocam (PHE) measurements at Paris – Romainville (PAROMA) from 2023-09-26 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Paris – SIRTA (PASIRT) from 2023-04-26 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Heraklion – FORTH (HEFORT) from 2023-03-24 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Data from Phenocam (PHE) measurements at Berlin-Technical University of Berlin (BETUCC) from 2023-06-01 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
Calculation of parameter values based on observations for the herbaceous biomass plantation PFT representing Miscanthus in JSBACH3.2
<p>This dataset provides the calculation of parameter values and the observational data that was collected from literature used in these calculations for the re-implementation of a herbaceous biomass plantation (HBP) PFT representing Miscanthus in the dynamic global vegetation model (DGVM) JSBACH3.2 (Egerer et al. subm., Nützel et al. in prep.). The parameters included are the maximum rubisco capacity (Vmax) at 25°C, the PEPcase CO2 specificity (k) and specific leaf area (SLA). Some of the observed parameter values were already compiled in a dataset by Li et al. (2018). These observations were therefore re-used in this dataset (which is specified within the dataset sheets) and complemented with additional observed values from literature that has become available since then or was not included in the study by Li et al. (2018). A detailed methodology of the parameter calculations for JSBACH3.2 can be found on the first sheet of the dataset. </p>
Data from Phenocam (PHE) measurements at Berlin – Rothenburgstrasse (BEROTH) from 2023-01-01 to 2023-12-31 [RAW]
<p>Original phenocam images separated into near-infrared (NIR) and visible (VIS).</p>
ZooCor Corpus (fr-it)
<p>ZooCor is a bilingual (fr-it) specialized corpus, consisting of 350 texts concerning marine fauna and conservation biology. The ZooCor corpus covers a time window from 2000 to 2022. The partial metadata related to the subdomain of the threatened species of chelonids (marine turtles) are published. For further information on the entire corpus, please adress to silvia.zollo@uniparthenope.it. </p>
Digital image correlation measurement of linear elastic steel specimen
<p>The dataset comprises the axial and lateral displacements on the surface of a plate with a hole subjected to tensile load. The displacement data are measured by digital image correlation and the material is assumed to behave linear elastic. The material under investigation is a common low-carbon steel alloy of type S235. The displacement data are used for calibration of a linear elastic constitutive model using parametric physics-informed neural networks and finite elements. For that purpose, the dataset comprises both the raw experimental displacement data and displacement data interpolated onto a regular grid using linear interpolation, where the interpolation routine is provided as well.</p>
Data for At-home testing to characterize SARS-CoV-2 seroprevalence among children and adolescents
<div> <div>This repository contains the data used to reproduce *At-home testing to characterize SARS-CoV-2 seroprevalence among children and adolescents* by Ahmed et al.</div> </div>
Ice sheet surface elevation change from ablation stake measurements on bare ice in the western Greenland ablation zone during July 2016
<p>Measurements of ice surface elevation change from a network of twelve bamboo ablation stakes installed in the western Greenland ice sheet ablation zone (67.0496o N, 49.0201o W, 1215 m a.s.l.). Stakes were installed by drilling 3 m deep holes into the ice, inserting the bamboo stakes, and allowing them to freeze into the ice for 24 hours. Following the 24 hour freeze-in period, measurements of the distance from the top of the stake to its base were recorded at nominal 3 hour intervals continuously from 12:00 local time (UTC-2) on 6 July 2016 to 23:00 local time on 12 July 2016. Prior to each measurement, a 24×24 cm square wooden ablation board was placed at the base of the stake and oriented to true north. This board operated as a datum from which the stake height above the ice surface was measured.</p>
Dataset for Towards improved online dissolution evaluation of Pt-alloy PEMFC electrocatalysts via electrochemical flow cell - ICP-MS setup upgrades
<p>Experimental data comprises raw data from ICP-MS (Inductively coupled plasma mass spectrometry) (i.e. time dependence of signal intensity for Co59 and Pt195) for different cell geometry and operating parameters. <br>Model data comprise of time- and space-dependent values of Pt ions concentration in the modelling cell and local velocity vectors.</p>
Dataset for "Impact of the flow-field distribution channel cross-section geometry on PEM fuel cell performance: stamped vs. milled channel"
<p>Experimental data comprises raw data from load curve characterisation of a PEM fuel cell used for the validation of the mathematical model. Model data comprise of space-dependent values of hydrogen and oxygen concentration, local current densities, gas pressures and gas velocities in the modelled cell. These data were used for the investigation of the effect of different geometric parameters of flow-field channels on the performance of a PEM fuel cell.</p>
Data from: mPRIME Study - Interaction of Insulin Resistance with Cognition, Lifestyle, and Mental Health
<p>The presented datasets were collected within the <em>m</em>PRIME study, a prospective, observational study of the H2020 project Prevention and Remediation of Insulin Multimorbidity in Europe (PRIME) (grant No. 847879). The study investigates the interaction of insulin resistance with cognition, lifestyle, and mental health by combining traditional methods with ambulatory assessment and sensor-based data collection. Recruitment took place between March 2021 and March 2023 at the University Hospital Frankfurt, Germany.</p> <p>The eligibility criteria for the study were as follows: Age above 18 years, no intake of antidiabetic medication, insulin or glucocorticoids, no existing type 1 diabetes mellitus or gestational diabetes, no diagnoses of bipolar I disorder, schizophrenia, organically caused mental disorders and substance dependence, no severe neurological disorders, no current pregnancy or breastfeeding, no non-correctable visual impairments, no participation in medication-related studies within the last 6 months, no use of weight-reducing medications or a diet within the last 3 months, sufficient proficiency in German to complete questionnaires and neuropsychological tests.</p> <p>All participants in the <em>m</em>PRIME study provided written informed consent. The study protocol and procedures were approved by the local ethics committee.</p> <p><strong>Study Design</strong></p> <p>Individuals completed a baseline assessment and a one-week ambulatory assessment. The baseline assessment included: socio-demographic information, blood samples, anthropometric measures, neuropsychological tests, and several questionnaires. In addition, individuals were introduced to smartphone-based ecological momentary assessment (EMA), food protocols, and the use of sensors (continuous glucose monitor, accelerometer). Food protocols and EMA were conducted on three consecutive days, including two weekdays and one weekend day (Thursday to Saturday or Sunday to Tuesday). Several times a day, individuals were prompted via their smartphone to complete a working memory task and answer questions about stress, affect, and food intake. The continuous glucose monitor and accelerometer were worn continuously for 1 week.</p> <p> </p>
Dataset of "Microporous electrode binders for anion exchange membrane water electrolyzers"
<p>Membranes made of SEBS/DABCO/PIM-1 blends were prepared and characterized. In the next step, the several blends were used as polymer binder's of the catalysts layers. Characterization of SEBS-DABCO/PIM-1 blends in the form of the catalyst layer revealed the significance of the catalyst layer porosity, which controls the permeation of gasses.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.