cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25582/data.2020-02.1941274/2172142
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941430/2172143
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941533/2172144
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1947197/2172145
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1943175/2172146
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1931763/2172147
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1941525/2172148
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1938319/2172149
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1945857/2172150
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1931762/2172151
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1941422/2172152
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1937333/2172153
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1943129/2172154
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1943424/2172155
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1944881/2172156
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941645/2172157
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941580/2172158
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1945320/2172159
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1945396/2172160
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941440/2172161
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941461/2172162
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1945724/2172163
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1934320/2172164
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1939627/2172165
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1944910/2172166
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949348/2172167
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949365/2172168
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941389/2172169
title: Data for EMSL Project 51287 from February 2020
DOI: 10.6084/m9.figshare.24494761
title: Supplementary Material for: Exploring the expression of Adenosine Pathway-Related Markers CD73 and CD39 in Colorectal and Pancreatic Carcinomas Characterized by Multiplex Immunofluorescence: A Pilot Study

description: Introduction: Generating high levels of immunosuppressive adenosine in the tumor microenvironment contributes to cancer immune evasion. CD39 and CD73 hydrolyze adenosine triphosphate into adenosine; thus, efforts have been made to target this pathway for cancer immunotherapy. Our objective was optimizing a multiplex immunofluorescence (mIF) panel to explore the role of CD39 and CD73 within the tumor microenvironment. Materials and methods: In three-time points, a small cohort (n=8 ) of colorectal and pancreatic adenocarcinomas were automated staining using an mIF panel against CK, CD3, CD8, CD20, CD39, CD73 and CD68 to compare them with individual markers immunohistochemistry (IHC) for internal panel validation. Densities of immune cells and distances from different tumor-associated immune cells to tumor cells were exploratory assessment and compared with clinicopathologic variables and outcomes. Results: Comparing the three-time points and individual IHC staining results, we demonstrated high reproducibility of the mIF panel. CD39 and CD73 expression was low in malignant cells; the exploratory analysis showed higher densities of CD39 expression by various cells, predominantly stromal cells, followed by T cells, macrophages, and B cells. No expression of CD73 by B cells or macrophages was detected. Distance analysis revealed proximity of cytotoxic T cells, macrophages, and T cells expressing CD39 to malignant cells, suggesting a close regulatory signal driven by this adenosine marker. Conclusions: We optimized an mIF panel for detection of markers in the adenosine pathway, an emerging clinically relevant pathway. The densities and spatial distribution demonstrated that this pathway may modulate aspects of the tumor immune microenvironment.
DOI: 10.25582/data.2020-02.1941609/2172170
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941925/2172171
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941642/2172172
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1934262/2172173
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-01.1934269/2172174
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1943067/2172175
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1931790/2172176
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1943291/2172177
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1943290/2172178
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1937537/2172179
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1941946/2172180
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1942030/2172181
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1946188/2172182
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941620/2172183
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1942245/2172184
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941519/2172185
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1946887/2172186
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1938321/2172187
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1941592/2172188
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941627/2172189
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1944950/2172190
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949421/2172191
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1936295/2172192
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1941421/2172193
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941602/2172194
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941659/2172195
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949366/2172196
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1947066/2172197
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1936076/2172198
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1947048/2172199
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1919339/2172200
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1949386/2172201
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1936441/2172202
title: Data for EMSL Project 51287 from January 2020
DOI: 10.6084/m9.figshare.24494752
title: Elisa TNF-alpha,MDA,SOD and GPx

description: Concentration of TNF-α, MDA, SOD and GPx in diabetic induced rat with zinc oxide nanoparticle emulsion from <i>Tithonia diversifolia </i>leaf extract
DOI: 10.25582/data.2020-02.1942719/2172203
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949416/2172204
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949787/2172205
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941522/2172206
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1942720/2172207
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941641/2172208
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1947044/2172209
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1946918/2172210
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1919267/2172211
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-01.1919274/2172212
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1946173/2172213
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1938970/2172214
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1949383/2172215
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1941490/2172216
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1931796/2172217
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-01.1931653/2172218
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1947047/2172219
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-01.1932759/2172220
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-01.1938022/2172221
title: Data for EMSL Project 51287 from January 2020
DOI: 10.25582/data.2020-02.1941500/2172222
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949392/2172223
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-02.1949417/2172224
title: Data for EMSL Project 51287 from February 2020
DOI: 10.25582/data.2020-08.2032879/2172225
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2033341/2172226
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-11.2091066/2172227
title: Data for EMSL Project 51301 from November 2020
DOI: 10.25582/data.2020-08.2045069/2172228
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2044370/2172229
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2044558/2172230
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2033269/2172231
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2032827/2172232
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2044377/2172233
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2021-03.2187237/2172234
title: Data for EMSL Project 51301 from March 2021
DOI: 10.25582/data.2020-08.2045068/2172235
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2032810/2172236
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2021-03.2187244/2172237
title: Data for EMSL Project 51301 from March 2021
DOI: 10.25582/data.2020-08.2032958/2172238
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2032830/2172239
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2043817/2172240
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2043644/2172241
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2033405/2172242
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2032815/2172243
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2036435/2172244
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-08.2045000/2172245
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-02.1948601/2172246
title: Data for EMSL Project 51301 from February 2020
DOI: 10.25582/data.2020-08.2033483/2172247
title: Data for EMSL Project 51301 from August 2020
DOI: 10.25582/data.2020-09.2046558/2172248
title: Data for EMSL Project 51301 from September 2020
DOI: 10.25582/data.2020-08.2036469/2172249
title: Data for EMSL Project 51301 from August 2020
DOI: 10.6084/m9.figshare.24494758
title: A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety

description: This is the experimental data of the manuscript entitled “A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety”
DOI: 10.6084/m9.figshare.24494758.v1
title: A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety

description: This is the experimental data of the manuscript entitled “A novel collaborative electric location routing problem with battery-swapping stations considering range anxiety”
DOI: 10.15485/2204419
title: Geomorphic mapping and permafrost occurrence on the Koyukuk River floodplain near Huslia, Alaska

description: Permafrost occurrence measured in-situ and geomorphic maps drawn by hand using high-resolution satellite imagery for the Koyukuk River floodplain near Huslia, Alaska. The dataset was collected to characterize permafrost extent and rates of formation and degradation due to river processes and climate change. Permafrost occurrence and thickness of the active layer was measured using a 1 or 2 m long permafrost probe or through direct observation (coring, digging trench, exposed ice). Measurements were from June 27 - July 8, 2018 and September 26 - October 1, 2022 and are saved as a csv file. Geomorphic maps delineate floodplain landforms, the relative age of floodplain deposits, and prior paths of the river produced by connecting oxbow lakes. Maps are saved as georeferenced shapefiles that can be imported into QGIS or ArcGIS software.
DOI: 10.15485/2204420
title: ESS-DIVE Unoccupied Aerial Systems (UAS) Reporting Format v1

description: Here we present documentation of the ESS-DIVE reporting format for Unoccupied Aerial System (UAS) data and metadata. This reporting format provides guidance to data contributors on how to store data to maximize their discoverability, facilitate their efficient reuse, and add value to individual datasets. For data users, the reporting format will better allow data repositories to optimize data search and extraction, and more readily integrate similar data into harmonized synthesis products. The reporting format provides templates and guidance for the reporting of metadata for UAS experimental campaigns, individual flights, platform and sensor description. To improve data access and discoverability, the reporting format proposes a data description scheme of Levels based on the degree of processing, where Level 0 includes raw data, through to Level 3 being derived data end products. A range of examples of data types for each Level are given, with suggested file naming schemes. The reporting format presented here is intended to form a foundation for future development that will accommodate new UAS technologies and approaches to data access and use in the future. The reporting format documentation is maintained and updated on the ESS-DIVE Community Space GitHub at https://github.com/ess-dive-community/essdive-uas. This data package is the first published version of this reporting format, and comprises a zip file of the complete content of https://github.com/ess-dive-community/essdive-uas v1.0. The zip contains the reporting format description, instructions and variable definitions in GitHub markdown language (*.md) and metadata templates in csv format. The reporting format is designed to be compatible with other ESS-DIVE formats, and it is specifically recommended that this reporting format be used in conjunction with the File-level metadata (FLMD) and comma separated values (csv) reporting formats for submission to the ESS-DIVE repository.
DOI: 10.15485/2204421
title: Riverbed and Near-Surface Water Quality Data, Hanford Reach, Columbia River, February 2021 - April 2022

description: This dataset contains longitudinal profiles of natural groundwater tracers (temperature, electrical conductivity (EC), and Radon-222 (Rn)) collected to identify locations of hydrologic exchange flows along a 75-km reach of the Columbia River near Richland, Washington.A jetboat was used to tow a 30 foot long, weighted tether that had one set of temperature and EC sensors just below the water surface and one set of temperature and EC sensors on the end (just above the river bed). The dataset contains profiles of temperature/EC data (resolution: 1 second) collected along the left and right banks during three different sampling events. During the final sampling event, we revisited some "deep holes" where the river was more than 30 feet deep with a weighted tether that was 75 feet long. The dataset has been processed to remove data collected when the sensors were not in the water, or when the water was too deep to keep the tether on the riverbed. We collected grab samples of water for analysis of dissolved Rn in places where the temperature/EC was different from the background river water. The Rn data was joined to the temperature/EC profiles based on the sample times.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) installation methods; (4) February 2021 data; (5) July 2021 data; (6) April 2022 data; and (7) April 2022 deep hole data. All files are .csv format and can be opened with a spreadsheet program (such as Microsoft Excel or OpenOffice).
DOI: 10.4121/eba1143f-adbe-4038-bac9-dae804a8b65a
title: EMDAT disaster data used for article 'Floods have become less deadly: an analysis of global flood fatalities 1975-2022'

description: EMDAT disaster data used for article 'Floods have become less deadly: an analysis of global flood fatalities 1975-2022'Additional data appended to the data also attached, including quality control , GDP and income data.Scripts to generate the data as presented in the (proposed) paper are also included.
DOI: 10.4121/eba1143f-adbe-4038-bac9-dae804a8b65a.v1
title: EMDAT disaster data used for article 'Floods have become less deadly: an analysis of global flood fatalities 1975-2022'

description: EMDAT disaster data used for article 'Floods have become less deadly: an analysis of global flood fatalities 1975-2022'Additional data appended to the data also attached, including quality control , GDP and income data.Scripts to generate the data as presented in the (proposed) paper are also included.
DOI: 10.5281/zenodo.8081476
title: Russia Interview Transcripts Sverdlovsk Oblast and Tartarstan

description: Interview transcripts in Russian taken by members of the Gulag Echoes team between October 2019 and February 2021. Taken in Sverdlovsk Oblast and Tartarstan Republic of the Russian Federation.
DOI: 10.5281/zenodo.10016251
title: Russia Interview Transcripts Sverdlovsk Oblast and Tatarstan

description: Interview transcripts in Russian taken by members of the Gulag Echoes team between October 2019 and February 2021. Taken in Sverdlovsk Oblast and Tatarstan Republic of the Russian Federation.
DOI: 10.5281/zenodo.8081475
title: Russia Interview Transcripts Sverdlovsk Oblast and Tatarstan

description: Interview transcripts in Russian taken by members of the Gulag Echoes team between October 2019 and February 2021. Taken in Sverdlovsk Oblast and Tatarstan Republic of the Russian Federation.
DOI: 10.14278/rodare.2536
title: µCT data of two drill cores of fractured crystalline rock (Grimsel)

description: Two crystalline rock drill cores from the Grimsel site were scanned with a Nikon XT H 225 - scanner. The samples were prepared (formatted and cast in epoxy) by UJV Rez, Czech Republic. The CT-data were acquired and processed at HZDR-FWOT. Sample 1 (GAM_UJV_1C_1) contains a complex system of interconnected fractures.<br> Sample 2 (GAM_UJV_1C_2) contains one single end-to-end fracture with larger aperture. Size of both samples: Diameter 80 mm, length 165 mm. Two tomograms were acquired for both samples:<br> 1) Complete drill core as one scan, voxel size ca. 75 µm.<br> 2) HR-tomogram merged from three sections with maximum resolution, voxel size ca. 40 µm. The tomograms were stored as 3D-raw files. Data format, acquisition parameters, and processing workflow, are documented in the tomogram header files (nrrd-format (text): see https://teem.sourceforge.net/nrrd/format.html).<br> This data format is importable into open-source visualization programs as 3D slicer (https://www.slicer.org) or Paraview (https://www.paraview.org). The data processing has been conducted with Avizo (https://www.thermofisher.com/de/de/home/electron-microscopy/products/software-em-3d-vis/avizo-software.html). Files:<br> Sample 1<br> GAM_UJV_1C_1_complet-2_01_NLM: Graylevel image of complete sample, ring artifact removal, non-local-means filter<br> GAM_UJV_1C_1_complet-2_01_thresholded: Tentative label image of complete sample, threshold segmentation with manual edit<br> Merged-GAM_UJV_1C_1_HR.Frac_section: Graylevel image of merged fracture section, unfiltered<br> Merged-GAM_UJV_1C_1_HR.Frac_section.Threshold: Tentative label image of merged fracture section, adaptive threshold segmentation with manual edit<br> GAM_UJV_1C_1_complet_2.png: Figure of complete sample <br> GAM_UJV_1C_1_HR_Frac_Y2.png: Figure of merged high-resolution tomogram Sample 2<br> GAM_UJV_1C_2_complet_01.filtered: Graylevel image of complete sample, ring artifact removal, non-local-means filter<br> GAM_UJV_1C_2_complet_01.filtered.thresholded: Tentative label image of complete sample, threshold segmentation with manual edit<br> Merged-GAM_UJV_1C_2_A_01.Frac_section.filtered: Graylevel image of merged fracture section, ring artifact removal, non-local-means filter<br> Merged-GAM_UJV_1C_2_A_01.Frac_section.filtered.segm: Tentative label image of merged fracture section, threshold segmentation with manual edit<br> GAM_UJV_1C_2_complett_2.png: Figure of complete sample<br> GAM_UJV_1C_2_HR_Frac_Y2.png: Figure of merged high-resolution tomogram Original acquistion data are stored on the HZDR bulk data storage system and available for reprocessing on request. <br> Financial support was granted from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 847593 (EURAD, WP FUTURE, task 2.2).<br>