cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3712397
title: Time series measurements of leucine incorporation as a measure of bacterial production in the subtropical North Pacific Ocean

description: Samples were collected at or in the vicinity of Station ALOHA on 24 different cruises. On each cruise, rates of 3H-Leu incorporation into protein were measured. Seawater samples for measurements of production were collected from pre-dawn vertical hydrocasts at 6 discrete depths (5, 25, 45, 75, 100, 125 m) using polyvinyl chloride sampling bottles affixed to a rosette sampler. Polyethylene amber bottles (125 ml capacity) were subsampled from the CTD rosette bottles, and duplicate acid-cleaned 12 ml polycarbonate centrifuge tubes were filled from each depth. Each polycarbonate tube was inoculated with 20 nmol L-1 (final concentration) 3,4,5-3H-leucine. An additional 1.5 ml per depth was subsampled into 2 ml microcentrifuge tubes containing 100 µl of 100% (w/v) ice-cold trichloroacetic acid (TCA) to serve as a killed blank. The polycarbonate sample tubes were capped and incubated in situ over the photoperiod to measure rates of 3H-Leu incorporation in both dark (through use of black cloth bags) and light on a free-drifting array. At the end of the photoperiod, triplicate 1.5 ml subsamples were removed from each tube and added to 2 ml microcentrifuge tubes containing 100 µl of 100% ice-cold TCA; these tubes were stored frozen until analysis. Samples were processed following a modified method of the microcentrifuge method.
description: {"references": ["Viviani, Donn & Church, Matthew. (2017). Decoupling between bacterial production and primary production over multiple time scales in the North Pacific Subtropical Gyre. Deep Sea Research Part I: Oceanographic Research Papers. 121. 10.1016/j.dsr.2017.01.006."]}
DOI: 10.5281/zenodo.3712399
title: Time-series measurements of size fractionated primary production (14C-assimilation) in the subtropical North Pacific Ocean

description: Filter size-fractionated (&gt;0.2-3 μm) particulate 14C-based rates of primary production were measured at six discrete depths (5, 25, 45, 75, 100, and 125 m) throughout the euphotic zone. Seawater samples from each depth were subsampled into triplicate 30-mL polycarbonate centrifuge tubes from a pre-dawn cast, inoculated with 70 µL of NaH14CO3-, then incubated over the full photoperiod (~12-14 hours) on a floating in situ array at the corresponding depths where the water was collected. At the end of the incubation period (after sundown), 25 mL of each sample was vacuum-filtered first onto a 25-mm diameter 3-μm pore size polycarbonate membrane, then the filtrate was vacuum-filtered onto a 25-mm diameter 0.2-μm pore size polycarbonate membrane filter. The rates reported here are for the &gt;0.2-3 μm size fraction.
description: {"references": ["YM Rii, DM Karl and MJ Church, Temporal and vertical variability in picophytoplankton primary productivity in the North Pacific Subtropical Gyre, Marine Ecology Progress Series, 10.3354/meps11954, 562, (1-18), (2016)."]}
DOI: 10.5281/zenodo.3712400
title: Time-series measurements of size fractionated primary production (14C-assimilation) in the subtropical North Pacific Ocean

description: Filter size-fractionated (&gt;0.2-3 μm) particulate 14C-based rates of primary production were measured at six discrete depths (5, 25, 45, 75, 100, and 125 m) throughout the euphotic zone. Seawater samples from each depth were subsampled into triplicate 30-mL polycarbonate centrifuge tubes from a pre-dawn cast, inoculated with 70 µL of NaH14CO3-, then incubated over the full photoperiod (~12-14 hours) on a floating in situ array at the corresponding depths where the water was collected. At the end of the incubation period (after sundown), 25 mL of each sample was vacuum-filtered first onto a 25-mm diameter 3-μm pore size polycarbonate membrane, then the filtrate was vacuum-filtered onto a 25-mm diameter 0.2-μm pore size polycarbonate membrane filter. The rates reported here are for the &gt;0.2-3 μm size fraction.
description: {"references": ["YM Rii, DM Karl and MJ Church, Temporal and vertical variability in picophytoplankton primary productivity in the North Pacific Subtropical Gyre, Marine Ecology Progress Series, 10.3354/meps11954, 562, (1-18), (2016)."]}
DOI: 10.5281/zenodo.3710463
title: GEMINI3D: 2-D test data

description: Files used for self-verification of GEMINI program. https://github.com/gemini3d/gemini v3.0.0 compressed HDF5, new config.nml groups
DOI: 10.5281/zenodo.3712480
title: Gemini 3D test data

description: Gemini 3D simulation reference data https://www.github.com/gemini3d/gemini v3.0.0 compressed HDF5, new config.nml groups
DOI: 10.5281/zenodo.3712462
title: Photochemical Model Output For Restricted Inverse

description: Dr. Michael Kleeman at University of California, Davis contributed a photochemical mechanism in Fortran which was modified to create these two text files. This is a box model of a system photochemical reactions used when teaching the modeling of atmospheric photochemistry. Each column of S.txt is an integrated rate of reaction over 6 minutes. Each column of delC.txt is a change in concentration over 6 minutes for various species. Each new row is a new 6 minute time-step. These two text files are used in a script that constructs a restricted inverse. Further documentation on the system of reactions, the mechanism and the purpose of these files can be found in the archive GenerateAG, DOI: 10.5281/zenodo.3712458 For questions please contact P. Obin Sturm at posturm@ucdavis.edu
DOI: 10.5281/zenodo.3712463
title: Photochemical Model Output For Restricted Inverse

description: Dr. Michael Kleeman at University of California, Davis contributed a photochemical mechanism in Fortran which was modified to create these two text files. This is a box model of a system photochemical reactions used when teaching the modeling of atmospheric photochemistry. Each column of S.txt is an integrated rate of reaction over 6 minutes. Each column of delC.txt is a change in concentration over 6 minutes for various species. Each new row is a new 6 minute time-step. These two text files are used in a script that constructs a restricted inverse. Further documentation on the system of reactions, the mechanism and the purpose of these files can be found in the archive GenerateAG, DOI: 10.5281/zenodo.3712458 For questions please contact P. Obin Sturm at posturm@ucdavis.edu
DOI: 10.5281/zenodo.3712420
title: ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets

description: This page links to the data associated with the publication "ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets ". The data have been curated and analyzed using our open-source R package, ToxicoGx (cran.r-project.org/web/packages/ToxicoGx) and are available publicly in the ToxicoDB web application (www.toxicodb.ca). Please see the included DOIs below, or download the .csv file which contains the names, dates and DOIs of all datasets listed here. The TGGATES data was generated by Igarashi Y, Nakatsu N, Yamashita T, Ono A, Ohno Y, Urushidani T, Yamada H. Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res [Internet]. 2015 Jan;43(Database issue):D921–7. Available from: http://dx.doi.org/10.1093/nar/gku955 PMCID: PMC4384023.<br> <br> Data: TGGATEs human (https://doi.org/10.5281/zenodo.3712283) TGGATEs rat (https://doi.org/10.5281/zenodo.3712292) This Drug Matrix data was generated by Ganter B, Snyder RD, Halbert DN, Lee MD. Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database. Pharmacogenomics [Internet]. 2006 Oct;7(7):1025–1044. Available from: http://dx.doi.org/10.2217/14622416.7.7.1025 PMID: 17054413. Data: Drug Matrix (https://doi.org/10.5281/zenodo.3712247)
DOI: 10.5281/zenodo.3712494
title: FCA-estimated wind using EAR spaced antenna

description: Dataset for horizontal wind estimation using EAR spaced antenna from configuration 1, 2, 3, 4, and 5. These are the output from FCA method.
DOI: 10.6084/m9.figshare.11992272
title: Additional file 1 of Omori-like slow decay (p

description: Additional file 1: Table S1. Results of the Omori-like fitting for the horizontal displacement rates at each GNSS station.
DOI: 10.6084/m9.figshare.11992272.v1
title: Additional file 1 of Omori-like slow decay (p

description: Additional file 1: Table S1. Results of the Omori-like fitting for the horizontal displacement rates at each GNSS station.
DOI: 10.24431/rw1k445
title: Estimation of Abundance and Demographic Rates of Pacific Walruses in the Bering and Chukchi Seas, 2015

description: This study estimated abundance and demographic rates, including survival and recruitment, of Pacific walruses in the Beaufort Sea in 2015. The data collected was used to determine the feasibility of conducting a large scale and long-term capture-mark-recapture effort to determine the size of the Pacific walrus population as well as age and sex specific survival and recruitment of the population. The decline in sea ice habitat and the associated stressors are causing a population decline of Pacific walrus. This study provided a baseline for monitoring Pacific walrus populations. The data was collected from visual observations of Pacific walruses in which skin biopsy samples were collected and used for individual identification. The field data was collected on an electronic field entry system, a Juniper Mesa and converted to a csv file.
DOI: 10.5281/zenodo.3712423
title: ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets

description: This page links to the data associated with the publication "ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets ". The data have been curated and analyzed using our open-source R package, ToxicoGx (cran.r-project.org/web/packages/ToxicoGx) and are available publicly in the ToxicoDB web application (www.toxicodb.ca). Please see the included DOIs below, or download the .csv file which contains the names, dates and DOIs of all datasets listed here. The TGGATES data was generated by Igarashi Y, Nakatsu N, Yamashita T, Ono A, Ohno Y, Urushidani T, Yamada H. Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res [Internet]. 2015 Jan;43(Database issue):D921–7. Available from: http://dx.doi.org/10.1093/nar/gku955 PMCID: PMC4384023.<br> <br> Data: TGGATEs human (https://doi.org/10.5281/zenodo.3712283) TGGATEs rat (https://doi.org/10.5281/zenodo.3712292) This Drug Matrix data was generated by Ganter B, Snyder RD, Halbert DN, Lee MD. Toxicogenomics in drug discovery and development: mechanistic analysis of compound/class-dependent effects using the DrugMatrix database. Pharmacogenomics [Internet]. 2006 Oct;7(7):1025–1044. Available from: http://dx.doi.org/10.2217/14622416.7.7.1025 PMID: 17054413. Data: Drug Matrix (https://doi.org/10.5281/zenodo.3712247)
DOI: 10.5281/zenodo.3712429
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Rainer, Heimo, https://orcid.org/0000-0002-5963-349X. Claims were made on Bloodhound, https://bloodhound-tracker.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
DOI: 10.5281/zenodo.3712496
title: Datasets used for Multi-omics integration using Deep Learning and other state-of-the-art regression models

description: This repository link contains the LIHC files that were downloaded using TCGA Assembler 2 and used in the publication for benchmarking DL and other state-of-the-art regression models. The contents are as follows. Gene level CNA , filename= "LIHC__genome_wide_snp_6__GeneLevelCNA.txt" DNA Methylation data around 1500 bp around TSS (450K) , filename= "LIHC_Methylation450__SingleValue__TSS1500__Both.txt" RNASeq data, filename= "LIHC_RNASeq__illuminahiseq_rnaseqv2__GeneExp.txt"
DOI: 10.5281/zenodo.3712495
title: Datasets used for Multi-omics integration using Deep Learning and other state-of-the-art regression models

description: This repository link contains the LIHC files that were downloaded using TCGA Assembler 2 and used in the publication for benchmarking DL and other state-of-the-art regression models. The contents are as follows. Gene level CNA , filename= "LIHC__genome_wide_snp_6__GeneLevelCNA.txt" DNA Methylation data around 1500 bp around TSS (450K) , filename= "LIHC_Methylation450__SingleValue__TSS1500__Both.txt" RNASeq data, filename= "LIHC_RNASeq__illuminahiseq_rnaseqv2__GeneExp.txt"
DOI: 10.5281/zenodo.3712183
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712182
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712187
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712186
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712189
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712188
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712184
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712185
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.21227/hnws-g792
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 12.9 Million plus (collecting since Feb 1, 2020)Update: I have been receiving a lot of requests asking to add the user's ID & location for each collected tweets. I've made necessary changes to the model to include these two details as well. Tweets tweeted after March 17, 2020 12:20 GMT 5:45 will have these extra details.The first column has date and time in the Unix timestamp. You can easily make it readable using pandas: df['date'] = pd.to_datetime[df['unix'], unit='ms'].Each database (*.db) contain three columns.First column: date and time of the tweetSecond column: tweetThird column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3712191
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712190
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.15468/ongxb0
title: An extremely large saber-tooth cat skull from Uruguay (late Pleistocene - early Holocene, Dolores Formation): body size and paleobiological implications

description: This dataset contains the digitized treatments in Plazi based on the original journal article Manzuetti, Aldo, Perea, Daniel, Jones, Washington, Ubilla, Martın, Rinderknecht, Andres (2020): An extremely large saber-tooth cat skull from Uruguay (late Pleistocene - early Holocene, Dolores Formation): body size and paleobiological implications. Alcheringa 44: 1-8, DOI: 10.1080/03115518.2019.1701080
DOI: 10.5281/zenodo.3712167
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712166
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.21227/ym7k-s638
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 12.9 Million plus (collecting since Feb 1, 2020)Update: I have been receiving a lot of requests asking to add the user's ID & location for each collected tweets. I've made necessary changes to the model to include these two details as well. Tweets tweeted after March 17, 2020 12:20 GMT 5:45 will have these extra details.The first column has date and time in the Unix timestamp. You can easily make it readable using pandas: df['date'] = pd.to_datetime[df['unix'], unit='ms'].Each database (*.db) contain five columns.First column: date and time of the tweetSecond column: user's ID (tweets collected after March 17, 2020 12:20 GMT 5:45 )Third column: user's location (tweets collected after March 17, 2020 12:20 GMT 5:45 )Fourth column: tweetFifth column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3712171
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712170
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712173
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712172
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712174
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712175
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712177
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712176
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712169
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712168
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3932947
title: Data used in paper "Crustal structure across the extinct mid-ocean ridge ..."

description: Seismograms used for generating receiver functions for 11 OBS in the Central sub-basin of the SCS. We note that seismograms were cut from the continuous recordings with the origin times of the Earthquakes. Note: This dataset can only be used to verify the RF results. it can not be used to other seismic applications because it has already been allocated to specific groups who are working on seismic tomography, anisotropy, noise analysis, microearthquake relocations, and waveform modeling.
DOI: 10.5281/zenodo.3712179
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712178
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712180
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3712181
title: Wikidata Dump test_physics

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.21227/42qb-da14
title: ProcMon log file

description: The dataset is system activities captured by Procmon on Windows, including running malware WannaPeace.
DOI: 10.21227/ykck-zf14
title: ProcMon log file

description: The dataset is system activities captured by Procmon on Windows, including running malware WannaPeace.
DOI: 10.21227/45w8-j945
title: Corona Virus (COVID-19) Tweets Dataset

description: Tweets Counter: 14.8 Million plus (collecting since Feb 1, 2020)Update: I have been receiving a lot of requests asking to add the user's ID & location for each collected tweets. I've made necessary changes to the model to include these two details as well. Tweets tweeted after March 17, 2020 12:20 GMT 5:45 will have these extra details.The first column has date and time in the Unix timestamp. You can easily make it readable using pandas: df['date'] = pd.to_datetime[df['unix'], unit='ms'].Each database (*.db) contain five columns.First column: date and time of the tweetSecond column: user's ID (tweets collected after March 17, 2020 12:20 GMT 5:45 )Third column: user's location (tweets collected after March 17, 2020 12:20 GMT 5:45 )Fourth column: tweetFifth column: sentiment score for the particular tweet within the range [-1,1] with -1 being the most negative, 0 being the neutral and +1 being the most positive sentiment.The tweets have been collected by the LSTM model deployed here at sentiment.live.To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score out of TextBlob [2] has been appended as the last column. New databases will be added to this dataset every week. Bookmark this page for further updates. [1] https://sentiment.live/ [2] https://textblob.readthedocs.io/en/dev/