cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22819997.v1
title: The data entitled The Level of Deep Convective Transport over the Asian Summer Monsoon Anticyclone Region based on Balloon-borne Measurements

description: This is the data entitled The Level of Deep Convective Transport over the Asian Summer Monsoon Anticyclone Region based on Balloon-borne Measurements. The profiles of water vapor mixing ratio, cirrus, and temperature were obtained from the sounding water vapor, ozone, and particles (SWOP) campaign, conducted by the Institute of Atmospheric Physics, Chinese Academy of Sciences, during the ASM season. The campaign was equipped with an electrochemical concentration cell (ECC) ozonesonde, the cryogenic frost point hygrometer (CFH), the Compact Optical Backscatter Aerosol Detector (COBALD), and radiosonde.
DOI: 10.6084/m9.figshare.23008151
title: Diene Isomerization Energies Database

description: We introduce a representative database of 60 accurate diene isomerization energies obtained by means of the high-level, ab initio Wn–F12 thermochemical protocols. The isomerization reactions involve a migration of one double bond that breaks the p-conjugated system. The considered dienes involve a range of hydrocarbon functional groups, including linear, branched, and cyclic moieties. This set of benchmark isomerization energies allows an assessment of the performance of more approximate theoretical procedures for the calculation of p-conjugation stabilization energies in dienes. We evaluate the performance of a large number of density functional theory (DFT) and double-hybrid DFT (DHDFT) procedures. We find that, with few exceptions (most notably BMK-D3 and M05-2X), conventional DFT procedures have difficulty describing reactions of the type: conjugated diene --&gt; non-conjugated diene, with root mean square deviations (RMSDs) between 4.5 and 11.7 kJ/mol. However, DHDFT procedures show excellent performance with RMSDs well below the ‘chemical accuracy’ threshold. <br>
DOI: 10.35003/ba2o5g/qmnqn9
title: maps13921-sup-0001-supinfo.docx

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DOI: 10.35003/ba2o5g/qtctov
title: figure_discription.xlsx

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DOI: 10.35003/ba2o5g/msfv4q
title: maps13921-fig-0004-m.png

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DOI: 10.35003/ba2o5g/us9g43
title: maps13921-fig-0003-m.png

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DOI: 10.35003/ba2o5g/4kzfgi
title: tables.tab

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DOI: 10.35003/ba2o5g/mwskao
title: maps13921-fig-0001-m.png

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DOI: 10.35003/ba2o5g/nze0sy
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DOI: 10.35003/m8i5lm/ak6d8g
title: jgre20795-fig-0004.pptx

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DOI: 10.35003/m8i5lm/cp9ep9
title: jgre20795-fig-0007.pptx

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DOI: 10.35003/m8i5lm/4ffvnz
title: jgre20795-fig-0001.pptx

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DOI: 10.35003/m8i5lm/ethahu
title: jgre20795-fig-0009.pptx

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DOI: 10.35003/m8i5lm/rvibs2
title: jgre20795-fig-0010.pptx

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DOI: 10.35003/m8i5lm/9achpr
title: jgre20795-fig-0002.pptx

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DOI: 10.35003/m8i5lm/c79q7m
title: README.txt

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DOI: 10.35003/m8i5lm/fsdjni
title: jgre20795-fig-0006.pptx

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DOI: 10.35003/m8i5lm/t1atto
title: jgre20795-fig-0008.pptx

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DOI: 10.35003/m8i5lm/8iws3i
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DOI: 10.35003/m8i5lm/oas6gw
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DOI: 10.35003/m8i5lm/4alzp3
title: jgre20795-fig-0003.pptx

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DOI: 10.35003/z1jo72/yimgxa
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DOI: 10.35003/z1jo72/1v05sp
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DOI: 10.35003/z1jo72/vs00bx
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DOI: 10.35003/z1jo72/rxhwn1
title: 1-s2.0-S0012821X20304428-gr008_lrg.jpg

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DOI: 10.35003/z1jo72/jvglpd
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DOI: 10.35003/z1jo72/lrfmsa
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DOI: 10.35003/z1jo72/ptkyy0
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DOI: 10.35003/z1jo72/oqfyos
title: 1-s2.0-S0012821X20304428-gr008.jpg

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DOI: 10.35003/z1jo72/alljes
title: 1-s2.0-S0012821X20304428-gr010_lrg.jpg

description: :unav
DOI: 10.35003/z1jo72/yoh5z0
title: README.txt

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DOI: 10.35003/z1jo72/gspjwh
title: 1-s2.0-S0012821X20304428-gr005_lrg.jpg

description: :unav
DOI: 10.35003/z1jo72/9moxx6
title: 1-s2.0-S0012821X20304428-gr004.jpg

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DOI: 10.35003/z1jo72/mr41sc
title: tables_1_to_3.tab

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DOI: 10.35003/z1jo72/fh1nfw
title: 1-s2.0-S0012821X20304428-gr009.jpg

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DOI: 10.35003/z1jo72/2ydjir
title: 1-s2.0-S0012821X20304428-gr006_lrg.jpg

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DOI: 10.35003/z1jo72/pdylfb
title: 1-s2.0-S0012821X20304428-gr006.jpg

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DOI: 10.35003/z1jo72/hjlalb
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DOI: 10.34740/kaggle/dsv/5734980
title: Dota 2 Pro League Matches 2023
DOI: 10.34740/kaggle/dsv/5734965
title: 🇺🇦 Ukraine Conflict Twitter Dataset
DOI: 10.35003/11ghb7/bgbz7j
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DOI: 10.35003/11ghb7/oit3ve
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DOI: 10.35003/11ghb7/llfqva
title: 1-s2.0-S0016703722005853-mmc3.tab

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DOI: 10.35003/11ghb7/ifpule
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DOI: 10.35003/11ghb7/megoe3
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DOI: 10.35003/11ghb7/5gvfsc
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DOI: 10.35003/11ghb7/idflix
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DOI: 10.35003/11ghb7/qpbq1n
title: 1-s2.0-S0016703722005853-mmc1.pdf

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DOI: 10.35003/11ghb7/0t8i1f
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DOI: 10.35003/11ghb7/anto2w
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DOI: 10.35003/11ghb7/n6e9r2
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DOI: 10.35003/11ghb7/kxjwj9
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DOI: 10.35003/11ghb7/xrvisa
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DOI: 10.35003/11ghb7/h5ylik
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DOI: 10.35003/11ghb7/inidnv
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DOI: 10.35003/11ghb7/xdzwzv
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DOI: 10.35003/11ghb7/kwkbkl
title: EET83225-4-5-ID275.png

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DOI: 10.35003/11ghb7/4e2cdj
title: IDd_Images_Description.txt

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DOI: 10.35003/11ghb7/vtvd8t
title: 1-s2.0-S0016703722005853-gr1.jpg

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DOI: 10.35003/11ghb7/rlk0zm
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DOI: 10.35003/11ghb7/i1xuav
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DOI: 10.35003/11ghb7/6aftyz
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DOI: 10.35003/11ghb7/qmzlus
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DOI: 10.35003/11ghb7/bvx6c4
title: UPBH2O_SuppImages_TableofContents.txt

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DOI: 10.35003/11ghb7/lknqys
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DOI: 10.35003/11ghb7/k2q8kd
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DOI: 10.35003/11ghb7/fqvapq
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DOI: 10.35003/11ghb7/d8pxwx
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DOI: 10.35003/11ghb7/kgv6cv
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DOI: 10.35003/11ghb7/cgdpr1
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DOI: 10.35003/11ghb7/gri3wr
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DOI: 10.35003/11ghb7/vhjcyq
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DOI: 10.35003/11ghb7/quwxy4
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DOI: 10.35003/11ghb7/gzhgkx
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DOI: 10.35003/11ghb7/wf0y25
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DOI: 10.35003/11ghb7/8hsk3r
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DOI: 10.35003/11ghb7/g59zft
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DOI: 10.35003/11ghb7/dupzir
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DOI: 10.35003/11ghb7/mrehiu
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DOI: 10.35003/11ghb7/1bcijz
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DOI: 10.35003/11ghb7/i97pqb
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DOI: 10.35003/11ghb7/g7amtk
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DOI: 10.35003/11ghb7/tztp57
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DOI: 10.35003/11ghb7/2wd2d1
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DOI: 10.35003/11ghb7/hknkq5
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DOI: 10.35003/11ghb7/uwarxg
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DOI: 10.35003/11ghb7/ocsvdl
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DOI: 10.35003/11ghb7/r0sdoq
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DOI: 10.35003/11ghb7/ao99sm
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DOI: 10.35003/11ghb7/i7ipkw
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DOI: 10.35003/11ghb7/z5lgwk
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DOI: 10.35003/11ghb7/0jblq9
title: 1-s2.0-S0016703722005853-gr2.jpg

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DOI: 10.35003/11ghb7/xctpa5
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DOI: 10.35003/11ghb7/nepxga
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DOI: 10.34740/kaggle/dsv/5735145
title: Egypt Gold Prices | Daily Updated
DOI: 10.5519/qd.5km6tft9
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (6 records)
DOI: 10.5281/zenodo.7954441
title: Taste Peptides and their derivatives

description: Food Ai Researcher
DOI: 10.5281/zenodo.7954440
title: Taste Peptides and their derivatives

description: Food Ai Researcher
DOI: 10.5281/zenodo.7954445
title: micropsitta_pusio_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.7954444
title: micropsitta_pusio_zanfona_1.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/5735338
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.6084/m9.figshare.14987043
title: Supplementary File for the paper "Risk of Cerebrovascular Disease After Cancer Diagnosis in the United States "

description: Supplementary File for the paper "Risk of Cerebrovascular Disease After Cancer Diagnosis in the United States "
DOI: 10.6084/m9.figshare.14987043.v1
title: Supplementary File for the paper "Risk of Cerebrovascular Disease After Cancer Diagnosis in the United States "

description: Supplementary File for the paper "Risk of Cerebrovascular Disease After Cancer Diagnosis in the United States "
DOI: 10.35003/cow5y2/hbhjpy
title: 2021je006985-sup-0003-table si-s01-03.xlsx

description: :unav
DOI: 10.35003/cow5y2/kejxgl
title: 2021je006985-sup-0001-supporting information si-s01.pdf

description: :unav
DOI: 10.35003/cow5y2/fwrcmq
title: 2021je006985-sup-0002-table si-s04.tab

description: :unav
DOI: 10.35003/cow5y2/tbzpbc
title: 2021je006985-sup-0003-table si-s05.tab

description: :unav
DOI: 10.35003/cow5y2/plsyp3
title: 2021je006985-sup-0004-table si-s06.tab

description: :unav
DOI: 10.35003/cow5y2/ioige0
title: 10.1029-2021JE006985Figure217970001.pptx

description: :unav
DOI: 10.35003/cow5y2/n4ti2d
title: 10.1029-2021JE006985Figure217970003.pptx

description: :unav
DOI: 10.35003/cow5y2/j1x2km
title: 10.1029-2021JE006985Figure217970007.pptx

description: :unav
DOI: 10.35003/cow5y2/wbzvep
title: 10.1029-2021JE006985Figure217970006.pptx

description: :unav
DOI: 10.35003/cow5y2/d7qspq
title: README.txt

description: :unav
DOI: 10.35003/cow5y2/3d2bfe
title: 10.1029-2021JE006985Figure217970005.pptx

description: :unav
DOI: 10.35003/cow5y2/qf3bup
title: 10.1029-2021JE006985Figure217970004.pptx

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DOI: 10.35003/cow5y2/a3xyh5
title: 10.1029-2021JE006985Figure217970002.pptx

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DOI: 10.5281/zenodo.7954475
title: psittacara_rubritorquis_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.5281/zenodo.7954474
title: psittacara_rubritorquis_decontaminated_FSCR.fasta.gz

description: .
DOI: 10.3886/e191704
title: Replication files for "COVID-19 Emergency Policies, Financial Security, and Social Equity: Worldwide Evidence"

description: Replication files for An, Porcher, Tang & Maille-Lefranc, "COVID-19 Emergency Policies, Financial Security, and Social Equity: Worldwide Evidence", Public Administration Review, 2023. <br>
DOI: 10.3886/e191704v1
title: Replication files for "COVID-19 Emergency Policies, Financial Security, and Social Equity: Worldwide Evidence"

description: Replication files for An, Porcher, Tang & Maille-Lefranc, "COVID-19 Emergency Policies, Financial Security, and Social Equity: Worldwide Evidence", Public Administration Review, 2023. <br>
DOI: 10.34740/kaggle/dsv/5735600
title: 2021 World Population (updated daily)
DOI: 10.5281/zenodo.7954491
title: psittacara_rubritorquis_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7954490
title: psittacara_rubritorquis_decontaminated_gx.fasta.gz

description: .
DOI: 10.34740/kaggle/dsv/5735671
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.21782201.v2
title: Codes and data for Geographical Convergent Cross Mapping (GCCM) model

description: The compressed package includes the codes of Geographical Convergent Cross Mapping (GCCM) model written in R and the data of two case studies. The GCCM is propsed for spatial causation inference with cross-sectional data by resorting to dynamical systems theory and generalized embedding theory. It can identify and measure the strength of causal associations from cross map prediction in the phase space built by embedding of spatial observations.
DOI: 10.34740/kaggle/dsv/5735772
title: BD_DB_64
DOI: 10.6084/m9.figshare.22995434.v1
title: Dataset containing the increase in percent points of individuals (no age restriction) who have used a computer within the previous 3 months at least once sorted by their citicenshipt in an EU-member country over a period between 2007 and 2017 (excluding year 2016).

description: Data format: .csv Dataset size: &lt;1kb <strong>Header and data descriptions of the dataset: </strong> country [EU country codes, further information under references] increase [increasement in percent points over all 28 member countries of the EU between 2007 and 2017 (excluding 2016), Europe; data: percent points of increasement of individuals (no age restriction) who used a computer at least once within the previous three months between 2007 and 2017] <strong>Number of data-points per header:</strong> 29
DOI: 10.6084/m9.figshare.22995071
title: Dataset containing the percentage of individuals (no age restriction) who have used a computer within the previous 3 months at least once. Anual data between 2007 and 2017 (excluding year 2016) averaged over all 28 EU-member countries.

description: Data format: .csv Image size: &lt;1kb <strong>Header and data descriptions of the dataset: </strong> year [year in format yyyy form 2007 untill (and including) 2017 with the exclusion of the year 2016] percentage_of_individuals [percentage average taken over all 28 member countries of the EU between 2007 and 2017 (excluding 2016), Europe; data: percent of individuals (no age restriction) who used a computer at least once within the previous three months ] <strong>Number of data-points per header:</strong> 10
DOI: 10.6084/m9.figshare.22995071.v1
title: Dataset containing the percentage of individuals (no age restriction) who have used a computer within the previous 3 months at least once. Anual data between 2007 and 2017 (excluding year 2016) averaged over all 28 EU-member countries.

description: Data format: .csv Image size: &lt;1kb <strong>Header and data descriptions of the dataset: </strong> year [year in format yyyy form 2007 untill (and including) 2017 with the exclusion of the year 2016] percentage_of_individuals [percentage average taken over all 28 member countries of the EU between 2007 and 2017 (excluding 2016), Europe; data: percent of individuals (no age restriction) who used a computer at least once within the previous three months ] <strong>Number of data-points per header:</strong> 10
DOI: 10.6084/m9.figshare.22995434
title: Dataset containing the increase in percent points of individuals (no age restriction) who have used a computer within the previous 3 months at least once sorted by their citicenshipt in an EU-member country over a period between 2007 and 2017 (excluding year 2016).

description: Data format: .csv Dataset size: &lt;1kb <strong>Header and data descriptions of the dataset: </strong> country [EU country codes, further information under references] increase [increasement in percent points over all 28 member countries of the EU between 2007 and 2017 (excluding 2016), Europe; data: percent points of increasement of individuals (no age restriction) who used a computer at least once within the previous three months between 2007 and 2017] <strong>Number of data-points per header:</strong> 29
DOI: 10.6084/m9.figshare.22994054.v1
title: Dataset of annually averaged neutron detection per seconds, averaged over 8 European neutron detectors between 2007 and 2017.

description: Header and data descriptions of the dataset: <br> year [year in format yyyy form 2007 untill (and including) 2017] neutron_detections_per_second_averaged [ Average taken over all 8 neutron detectors per year; data: neutron detections per second averaged over a 1 year period and all neutron detectors ] <strong>Number of data-points:</strong> 11 per header <strong>Neutron detector configuration for underlying dataset:</strong> STATION: ATHN, ROME, JUNG, JUNG1, LMKS, DRBS, KIEL, OULU START TIME: 2007-01-01 00:00:00 UTC END TIME: 2019-01-01 00:00:00 UTC NMDB TABLE: 1 hour validated DATA TYPE: corr_for_efficiency AVERAGING: Yes / 1 year ORIGINAL RES: 60 min Further information under NMDB
DOI: 10.6084/m9.figshare.22994054
title: Dataset of annually averaged neutron detection per seconds, averaged over 8 European neutron detectors between 2007 and 2017.

description: Header and data descriptions of the dataset: <br> year [year in format yyyy form 2007 untill (and including) 2017] neutron_detections_per_second_averaged [ Average taken over all 8 neutron detectors per year; data: neutron detections per second averaged over a 1 year period and all neutron detectors ] <strong>Number of data-points:</strong> 11 per header <strong>Neutron detector configuration for underlying dataset:</strong> STATION: ATHN, ROME, JUNG, JUNG1, LMKS, DRBS, KIEL, OULU START TIME: 2007-01-01 00:00:00 UTC END TIME: 2019-01-01 00:00:00 UTC NMDB TABLE: 1 hour validated DATA TYPE: corr_for_efficiency AVERAGING: Yes / 1 year ORIGINAL RES: 60 min Further information under NMDB
DOI: 10.6084/m9.figshare.22958729
title: marmgCAMI2_sample_5_reads.tar

description: CAMI marine sample 5 downloaded from https://data.cami-challenge.org/participate, used as a dataset in pipeline implementation.
DOI: 10.6084/m9.figshare.22958729.v1
title: marmgCAMI2_sample_5_reads.tar

description: CAMI marine sample 5 downloaded from https://data.cami-challenge.org/participate, used as a dataset in pipeline implementation.
DOI: 10.25790/bml0cm.143
title: GABA_76ms.zip
DOI: 10.34740/kaggle/dsv/5735942
title: COVID Vaccination in World (updated daily)
DOI: 10.6084/m9.figshare.23012576
title: Supplementary Tables

description: supplementary files supporting "Causal roles of SMAD2 and CREB3L4 in prostate cancer: a proteome Mendelian randomization study"
DOI: 10.6084/m9.figshare.23012576.v1
title: Supplementary Tables

description: supplementary files supporting "Causal roles of SMAD2 and CREB3L4 in prostate cancer: a proteome Mendelian randomization study"
DOI: 10.5281/zenodo.7954546
title: Supplemental Tables that will be submitted with Hydrothermal Seepage of Altered Crustal Formation Water Seaward of the Middle America Trench, Offshore Costa Rica

description: This spreadsheet will be submitted to JGR Solid Earth with a manuscrpt titled "Hydrothermal Seepage of Altered Crustal Formation Water Seaward of the Middle America Trench, Offshore Costa Rica" by Parsons et al. Keywords include Ridge flank, hydrothermal, Middle American Trench, hydrogeology, formation water, and pore water. Three short highlights include: Pore water chemical profiles reveal sediment diagenesis and seepage speeds up to 1.7 cm yr<sup>-1</sup> resulting in a net flux of 0.1 L s<sup>-1</sup>. Crustal formation water is warm (~75ºC) and chemically altered, stemming from water-basalt reactions and diffusive exchange with pore water. This ridge-flank hydrothermal system is not hydrologically connected to the ventilated crust to the west or the trench to the east.
description: Data are mostly pore water chemical compositions but do include some model results using the WORM portal.
DOI: 10.5281/zenodo.7902676
title: Dataset Antecedents of civil engineering students' entrepreneurial intentions

description: The dataset provides valuable insights into the factors that influence the entrepreneurial intentions of civil engineering students in Morocco. 0Log in to edit with Ginger×
DOI: 10.5281/zenodo.7902677
title: Dataset Antecedents of civil engineering students' entrepreneurial intentions

description: The dataset provides valuable insights into the factors that influence the entrepreneurial intentions of civil engineering students in Morocco. 0Log in to edit with Ginger×