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Data for the COVID newcomers project
Open the record for dataset details and reuse information.
Data and code supporting the project "Mapping global coldspots of veterinary capacity"
<p>The folder "data" includes 1) the dataset "vets_observed.rda", which reports the locations of veterinarians, 2) the dataset "vets_national.csv", which reports the national estimates of veterinarians, 3) the dataset "vet_schools.csv", which reports the list of veterinary schools per country, along with the range of veterinary graduates per year, 4) the dataset "faostat_livestock_2019.csv", which reports the number and species of animals raised for food per country, and 5) the raster "obs_all_r.tif" which is the rasterized version of the "vets_observed.rda" dataset at the resolution of 10x10 km.</p> <p>The folder "scripts" includes the R and python code used for assembling the dataset of the locations of veterinarians and for performing all the analyses.</p>
Global Assessment of Agricultural Drought Characteristics Based on scPDSI under CMIP6 Projections
<p><strong><span><span><span>《CMIP6 预测下基于 scPDSI 的全球农业干旱特征评估</span></span></span></strong><span><span>》论文数据及代码 </span><span>。</span></span></p>
raw data related to project "Circulating biomarkers as predictors of gender-specific response to Immune Checkpoint Inhibitors in melanoma and non-small-cell lung cancer patients"
<p><strong>Sex-related differences in serum biomarker levels predict the activity and efficacy of Immune Checkpoint Inhibitors in advanced melanoma and Non-Small Cell Lung Cancer patients.</strong></p> <p><strong>Abstract </strong></p> <p><strong>Background:</strong> Immune Checkpoint Inhibitors (ICIs) lead to durable response and a significant increase in long-term survival in patients with advanced malignant melanoma (MM) and Non-Small Cell Lung Cancer (NSCLC). The identification of serum cytokines that can predict their activity and efficacy, and their sex interaction, could improve treatment personalization. </p> <p><strong>Methods: </strong>In this prospective study, we enrolled immunotherapy-naïve patients affected by advanced MM and NSCLC treated with ICIs. The primary endpoint was to dissect the potential sex correlations between serum cytokines (IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, GM-CSF, MCP-1, TNF-ɑ, IP-10, VEGF, sPD-L1) and the overall response rate (ORR). Secondly, we analyzed biomarker changes during treatment related to ORR, disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Blood samples, collected at baseline and during treatment until disease progression (PD) or up to 2 years, were analyzed using Luminex xMAP or ELLA based technology. </p> <p>Three Luminex xMAP assays and two ELLA microfluidic cartridges were used to screen 28 immune-related biomarkers in 38 paired serum and citrate-theophylline-adenosine-dipyridamole (CTAD) plasma samples collected from 10 advanced melanoma or non-small cell lung cancer (NSCLC) patients at different time points during immunotherapy.</p> <p><strong>Results</strong>: Serum samples from 161 patients (98 males/63 females; 92 MM/69 NSCLC) were analyzed for treatment response. At baseline, IL-6 was significantly lower in females (F) <em>versus</em> males (M); lower levels of IL-4 in F and of IL-6 in both sexes significantly correlated with a better ORR, while higher IL-4 and TNF-ɑ values were predictive of a lower probability of ORR in F <em>versus</em> M. One hundred and sixty-five patients were evaluable for survival analysis: at multiple Cox regression, an increased risk of PD was observed in F with higher baseline values of IL-4, sPD-L1 and IL-10, while higher IL-6 was a negative predictor in males. In males, higher levels of GM-CSF predict a longer survival, whereas higher IL-1β predicts a shorter survival. Regardless of sex, high baseline IL-8 values were associated with an increased risk of both PD and death, and high IL-6 levels only with shorter OS. </p> <p>Twenty-three of 28 biomarkers were detected both in serum and plasma by at least one of the assays, including IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12p70, GM-CSF, IFN-γ, TNF-α, VEGF, IP-10, MCP-1, eotaxin, fractalkine, G-CSF, IFN-α, IL-1RA, IL-13, IL-17A, MIP-1β and sPD-L1. Conversely, FGF-2 and IL-1α were not detected in both matrices; GRO-α factor and EGF were detected only in serum and MIP-1α only in plasma. sPD-L1, MCP-1, IFN-γ, IL-8, MIP-1β and VEGF were, respectively, 1.15-, 1.44-, 1.83-, 2.43-, 2.82-, 6.72-fold higher in serum, whereas IL-10, IL-4, IL-2 and IL-5 were 1.05-, 1.19-, 1.92- and 2.17-fold higher, respectively, in plasma. IP-10 levels were higher in plasma but, as well as for VEGF, the bias serum versus plasma varied depending on the assay used (IP-10: −5.7% to −145%; VEGF: 115% to 165%). No significant differences were found for the remaining nine analyzed cytokines.</p> <p><strong>Conclusions</strong></p> <p>Serum IL-1β, IL-4, IL-6, IL-10, GM-CSF, TNFɑ, and sPDL1 had a significant independent sex-related predictive impact on ORR, PFS and OS in melanoma and NSCLC patients treated with ICIs. These results will potentially pave the way for new ICI combinations, designed according to baseline and early changes of these cytokines and stratified by sex. </p> <p>The cytokine and sPD-L1 levels may differ between serum and plasma samples collected from cancer patients treated with immunotherapy, and the results obtained can be influenced by the different characteristics of the tested assays.</p>
AI/ML projects
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Global Mean Sea-Level Rise Projections to 2150 and 2300 (PROTECT)
<p>Full-track projections of global mean sea-level rise from PROTECT. Please check the deliverable text for details regarding these data.</p>
Effort and capture of Feral Cat Eradication Project on Socorro Island
<p>Datos mensuales de captura y esfuerzo del proyecto de erradicación de gato feral en Isla Socorro.</p> <ul> <li>Enero: <a href="https://mail.google.com/mail/u/0/#advanced-search/subject=Enero&subset=all&has=%22enero+del+2022%22&attach=true&within=1d&sizeoperator=s_sl&sizeunit=s_smb&query=subject%3AEnero+del+2022+has%3Aattachment">18 febrero 2022</a></li> <li>Febrero: <a href="https://mail.google.com/mail/u/0/#advanced-search/from=braulio.rojas%40islas.org.mx&to=ciencia.datos%40islas.org.mx&subject=Base+de+datos+febrero+2022&subset=all&has=(has%3Aattachment+OR+has%3Adrive)&within=1d&sizeoperator=s_sl&sizeunit=s_smb">4 marzo 2022</a></li> <li>Marzo: <a href="https://mail.google.com/mail/u/0/#advanced-search/subset=all&has=%22Aqu%C3%AD+marzo+del+2022%22&attach=true&within=1d&sizeoperator=s_sl&sizeunit=s_smb">8 abril 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener"> ✔️</a></li> <li>Abril: <a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">6 de junio 2022 ✔️</a></li> <li>Mayo 2022: <a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">6 de junio 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Junio 2022: <a href="https://mail.google.com/mail/u/0/#advanced-search/subject=Bases+de+datos+Junio+y+Julio&subset=cat_gatos%2Fsocorro&has=junio+2022&within=1d&sizeoperator=s_sl&sizeunit=s_smb&query=label%3Agatos-socorro+junio+2022" target="_blank" rel="noopener">4 agosto 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Julio: <a href="https://mail.google.com/mail/u/0/#advanced-search/subject=Bases+de+datos+Junio+y+Julio&subset=cat_gatos%2Fsocorro&has=junio+2022&within=1d&sizeoperator=s_sl&sizeunit=s_smb&query=label%3Agatos-socorro+junio+2022" target="_blank" rel="noopener">4 agosto 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Agosto: <a href="https://mail.google.com/mail/u/0/?tab=rm&ogbl#search/base+de+datos+%22agosto,+septiembre+y+octubre%22+2022+from:javier.gongora@islas.org.mx" target="_blank" rel="noopener">21 noviembre 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Septiembre: <a href="https://mail.google.com/mail/u/0/?tab=rm&ogbl#search/base+de+datos+%22agosto,+septiembre+y+octubre%22+2022+from:javier.gongora@islas.org.mx" target="_blank" rel="noopener">21 noviembre 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Octubre: <a href="https://mail.google.com/mail/u/0/?tab=rm&ogbl#search/base+de+datos+%22agosto,+septiembre+y+octubre%22+2022+from:javier.gongora@islas.org.mx" target="_blank" rel="noopener">21 noviembre 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Noviembre: <a href="https://mail.google.com/mail/u/0/?tab=rm&ogbl#search/%22Base+de+datos+Noviembre%22+after:2022+before:2023" target="_blank" rel="noopener">1 diciembre 2022 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> <li>Diciembre 2022: <a href="https://mail.google.com/mail/u/0/#search/subject:(Bases+de+datos)+%22diciembre+del+2022%22+has:attachment" target="_blank" rel="noopener">24 febrero 2023 </a><a href="https://mail.google.com/mail/u/0/#search/subject%3A+Re%3A+%22Bases+de+datos+abril%2C+mayo%22" target="_blank" rel="noopener">✔️</a></li> </ul>
The Cost of Build Tool Downgrades: An Empirical Study of the Kubernetes Project
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UJA_OPEN_Antibiotics Data SOIL O-LIVE PROJECT 2024 RP1
<p>Database with Antibiotics Data within the frame of the WP2 Diagnosis phase in SOIL O-LIVE PROJECT</p>
UJA_UNIPA_CNR_UAG_ELGO-D_NSA-M_HMU_OPEN_Soil Parameters Data SOIL O-LIVE PROJECT 2024 RP1
<p>Database with Soil Parameters Data within the frame of the WP2 Diagnosis phase in SOIL O-LIVE PROJECT</p>
Figure 6 in Taxonomy and distribution of Icelandic Fauveliopsidae (Annelida) collected during the BIOICE project
Figure 6. Fauveliopsis olgae Hartmann-Schröder, 1983. SEM micrographs, BIOICE sample 3260 (IINH40707). (a) Complete specimen, dorsolateral view. (b) Anterior region, detail, dorsolateral view (framed in (a)). (c) Median region chaetigers, left lateral view. (d) Pyriform interramal papilla. (e) Posterior region chaetigers, lateral view. (f) Posterior body end, dorsolateral view (framed in (a)). Abbreviations: A – acicular chaeta; a – thin acicular chaeta; AR – anterior body region; c – capillary chaeta; CH – chaetiger; gp – genital papilla; imp – integumental micropapillae; irp – interramal papilla; isb – intersegmental border; MR – median body region; pyg – pygidium.
COASTAL EU Project: oceanographic data from the marine sector of SW Messinia, Greece
<p><strong>COASTAL Project: Marine Data Set</strong></p> <p>In the framework of COASTAL Project (<a href="https://h2020-coastal.eu/">https://h2020-coastal.eu/</a>), EU-H2020 Grant Number 773782, the Institute of Oceanography/HCMR coordinates the Multi-Actor Lab for the SW Messinia case study.</p> <p><strong>Data set description</strong></p> <p>In this area (SW Messinia) five research cruises in three periods were conducted. Data presented here include:</p> <table> <tbody> <tr> <td> <p>Nutrients, chlorophyll, dissolved oxygen, carbon, nitrogen, phosphorus in water</p> </td> </tr> <tr> <td> <p>Metals, carbon, nitrogen, mineralogy in sediment</p> </td> </tr> <tr> <td> <p>Metals, carbon, nitrogen, mineralogy in sediment cores</p> </td> </tr> <tr> <td> <p>Particulate matter</p> </td> </tr> <tr> <td> <p>Hydrocarbons (PAHs, PCBs) in water</p> </td> </tr> <tr> <td> <p>Hydrocarbons (PAHs) in sediment</p> </td> </tr> <tr> <td> <p>Zooplankton biomass</p> </td> </tr> <tr> <td> <p>Zoobenthos taxonomic abundance</p> </td> </tr> </tbody> </table>
Area averaged Sentinel 2 vegetation Indices time series on NBS and control sites (Panaro River). Further details can be found in D4.5 of the OPERANDUM project.
<p>NBS interventions in OAL-IT (Panaro) aimed at the establishment of a dense deep rooted perennial vegetation on river embankments with the goal to improve the strength of the vadose zone and to reduce erosivity of the soil cover. Monitoring the vegetation cover at the NBS location over time shall provide information about vegetation growth and structure past the completion of the intervention and could give useful insights on the status and effectiveness of the NBS.</p> <p>Dataset includes area averaged Vegetation Indices calculated by a time series of Sentinel-2 multispectral data (10-20 m spatial resolution). Normalized Difference Vegetation Index, Inverted Red-Edge Chlorophyll Index and Red Position Index were calculated for the cloud free images available in the time period between January 2019 and December 2021 providing a total of 71 images covering the NBS site and a control site close to it. The analysis was focused on the evaluation of the temporal profile of Vegetation Indices that can provide metrics of the vigor and health of the vegetation in both the NSB and the standard vegetation (control area).</p>
High spatial resolution Fractional Vegetation Cover maps OAL-DE (Elbe river). Further details can be found in D4.5 of the OPERANDUM project.
<p>In order to reduce the risk posed by flooding, areas of woody vegetation have been removed along the riverbank of Elbe river in order to expedite the inflow and outflow of water from the main channel, and thus contribute to flattening the peak hydrographic response. Maintaining the effectiveness of this clearing requires that there is little or no regrowth of this woody vegetation. The NBS that have been implemented in OAL-Germany sees the use of various animals to graze these areas. NBS is devoted to prevent the re-growth of woody vegetation after an intervention which took place over a period from autumn 2014 to February 2015, when woody vegetation along the riverbank was cut back. Monitoring the effectiveness of the NBS is being performed by means of high spatial resolution remotely sensed data , i.e. Rapideye at 5 m spatial resolution. The preliminary analysis of this experiment consisted in the monitoring of the fractional vegetation cover over four of the seven NBS sites. </p> <p>The green fractional abundance (fc) was calculated by an algorithm based on scaling NDVI in-between the maximum and minimum NDVI values. A semi-empirical method based on the use of NDVI was used following Zeng et al, (2000), to calculate fc. </p> <p>The dataset contains layer stack of fractional abundance calculated for the images calculated by Rapideye images acquired on 18 April 2013, 15 April 2015, 17 March 2016, 9 April 2019. </p>
773782 COASTAL EU Project: oceanographic data from the marine sector of SW Messinia, Greece
<p><strong>COASTAL Project: Marine Data Set</strong></p> <p>In the framework of COASTAL Project (<a href="https://h2020-coastal.eu/">https://h2020-coastal.eu/</a>), EU-H2020 Grant Number 773782, the Institute of Oceanography/HCMR coordinates the Multi-Actor Lab for the SW Messinia case study (MAL02).</p> <p><strong>Data set description</strong></p> <p>In this area (SW Messinia) five research cruises in three periods were conducted. Data presented here include:</p> <table> <tbody> <tr> <td> <p>Nutrients, chlorophyll, dissolved oxygen, carbon, nitrogen, phosphorus in water</p> </td> </tr> <tr> <td> <p>Metals, carbon, nitrogen, mineralogy in sediment</p> </td> </tr> <tr> <td> <p>Metals, carbon, nitrogen, mineralogy in sediment cores</p> </td> </tr> <tr> <td> <p>Particulate matter</p> </td> </tr> <tr> <td> <p>Hydrocarbons (PAHs, PCBs) in water</p> </td> </tr> <tr> <td> <p>Hydrocarbons (PAHs) in sediment</p> </td> </tr> <tr> <td> <p>Zooplankton biomass</p> </td> </tr> <tr> <td> <p>Zoobenthos taxonomic abundance</p> </td> </tr> </tbody> </table>
773782 COASTAL EU Project: oceanographic data from the marine sector of SW Messinia, Greece
<p><strong>COASTAL Project: Marine Data Set</strong></p> <p>In the framework of COASTAL Project (<a href="https://h2020-coastal.eu/">https://h2020-coastal.eu/</a>), EU-H2020 Grant Number 773782, the Institute of Oceanography/HCMR coordinates the Multi-Actor Lab for the SW Messinia case study (MAL02).</p> <p><strong>Data set description</strong></p> <p>In this area (SW Messinia) five research cruises in three periods were conducted. Data presented here include:</p> <table> <tbody> <tr> <td> <p>Nutrients, chlorophyll, dissolved oxygen, carbon, nitrogen, phosphorus in water</p> </td> </tr> <tr> <td> <p>Metals, carbon, nitrogen, mineralogy in sediment</p> </td> </tr> <tr> <td> <p>Metals, carbon, nitrogen, mineralogy in sediment cores</p> </td> </tr> <tr> <td> <p>Particulate matter</p> </td> </tr> <tr> <td> <p>Hydrocarbons (PAHs, PCBs) in water</p> </td> </tr> <tr> <td> <p>Hydrocarbons (PAHs) in sediment</p> </td> </tr> <tr> <td> <p>Zooplankton biomass</p> </td> </tr> <tr> <td> <p>Zoobenthos taxonomic abundance</p> </td> </tr> </tbody> </table>
Data from: An objective approach to select climate scenarios when projecting species distribution under climate change
[No abstract entered]
Official Science Repository of the QB50 Project
<p>QB50 data will provide the opportunity to study the mid-lower thermosphere in unparalleled detail with a completely novel data set. These data will be generated by a constellation of instruments in orbit and they will offer in-situ measurements of the density of the most prominent gases (i.e. N<sup>2</sup>, NO, O, O<sup>2</sup>, e<sup>-</sup>) in the thermosphere.</p> <p>This is an ideal situation for students at universities around the world to use QB50 as a basis for research projects, either at Master degree level or for a PhD since the data will guarantee the chance to publish peer-reviewed scientific articles and possibly provide important discoveries or new phenomena in the thermosphere. The aim for students of postdoctoral researchers is to become involved in the mission operations or data calibration once the mission is flying and so get hands-on experience with the data as they are recorded. This allows the researchers the opportunity to design specific experiments they may wish to try, for example studying a specific region in the thermosphere, or finding specific conjunctions of CubeSats in the QB50 fleet, and respond to interesting events found in the data.</p> <p><strong>The structure of the dataset is given in the readme.txt file.</strong></p>
Vocera Project Dataset and Analysis
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Weimar (East Germany), house project for art, colourful variety and subculture at Gerberstraße 3
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1653149661.6439.jpg">https://4dcity.org/imgupload/1653149661.6439.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/51549087193_c43a051144_m.jpg">https://live.staticflickr.com/65535/51549087193_c43a051144_m.jpg</a> <br><br><u>Image-Metadata:</u><br>Filename: 1653149661.6439.jpg<br>Image Dimensions: 240x160<br>Megapixels: 0.04 MP<br>Filesize: 26.77 KB<br><br>Copyright: Ralf Steinberger<br>ExifOffset: 86<br>Artist: Ralf Steinberger
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.