cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3825704
title: Experimental data for PanDDA analysis of the bromodomain of human FALZ

description: The repository contains processed data from the entire crystallographic fragment screen of the bromodomain of human nucleosome-remodeling factor subunit BPTF (FALZ). Crystals of FALZ were screened against the DSPL and 3D-Fragment Consortium Libraries by X-ray Crystallography at the XChem facility of Diamond Light Source beamline I04-1 (FALZ_XChem_screen.tar.bz2). Additionally, metadata about the experiment can be found in the <em>mainTable</em> of the corresponding SQLite database file (FALZ_XChem_screen.sqlite). All identified ligand-bound structures were deposited in the Protein Data Bank under Group ID <strong>G_1002123</strong>. The individual PDB codes are: FALZA-x0079 5R4G FALZA-x0085 5R4H FALZA-x0172 5R4I FALZA-x0177 5R4J FALZA-x0271 5R4K FALZA-x0309 5R4L FALZA-x0402 5R4M FALZA-x0438 5R4N All structures necessary to reproduce the deposited PanDDA event maps which were used for ligand identification were deposited in the Protein Data Bank under PDB ID 5R4O (group ID <strong>G_1002124</strong>). <strong><em>Usage:</em></strong> download <em>FALZ_XChem_screen.tar.bz2</em> and save into the desired project directory, e.g. <pre><strong>/home/me/FALZ</strong></pre> unpack the tar archive: <pre><strong>tar –xvjf FALZ_XChem_screen.tar.bz2</strong></pre> run pandda, e.g. <pre><strong>pandda.analyse data_dirs="/home/me/FALZ/*" out_dir="/home/me/FALZ_pandda" pdb_style=dimple.pdb mtz_style=dimple.mtz</strong></pre> For more information about PanDDA, please check the PanDDA CCP4 program documentation. <em><strong>Reference:</strong></em> Pearce, N. M. <em>et al.</em> A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density. <em>Nature Communications</em> <strong>8</strong>, ncomms15123 (2017).
DOI: 10.5281/zenodo.3825703
title: Experimental data for PanDDA analysis of the bromodomain of human FALZ

description: The repository contains processed data from the entire crystallographic fragment screen of the bromodomain of human nucleosome-remodeling factor subunit BPTF (FALZ). Crystals of FALZ were screened against the DSPL and 3D-Fragment Consortium Libraries by X-ray Crystallography at the XChem facility of Diamond Light Source beamline I04-1 (FALZ_XChem_screen.tar.bz2). Additionally, metadata about the experiment can be found in the <em>mainTable</em> of the corresponding SQLite database file (FALZ_XChem_screen.sqlite). All identified ligand-bound structures were deposited in the Protein Data Bank under Group ID <strong>G_1002123</strong>. The individual PDB codes are: FALZA-x0079 5R4G FALZA-x0085 5R4H FALZA-x0172 5R4I FALZA-x0177 5R4J FALZA-x0271 5R4K FALZA-x0309 5R4L FALZA-x0402 5R4M FALZA-x0438 5R4N All structures necessary to reproduce the deposited PanDDA event maps which were used for ligand identification were deposited in the Protein Data Bank under PDB ID 5R4O (group ID <strong>G_1002124</strong>). <strong><em>Usage:</em></strong> download <em>FALZ_XChem_screen.tar.bz2</em> and save into the desired project directory, e.g. <pre><strong>/home/me/FALZ</strong></pre> unpack the tar archive: <pre><strong>tar –xvjf FALZ_XChem_screen.tar.bz2</strong></pre> run pandda, e.g. <pre><strong>pandda.analyse data_dirs="/home/me/FALZ/*" out_dir="/home/me/FALZ_pandda" pdb_style=dimple.pdb mtz_style=dimple.mtz</strong></pre> For more information about PanDDA, please check the PanDDA CCP4 program documentation. <em><strong>Reference:</strong></em> Pearce, N. M. <em>et al.</em> A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density. <em>Nature Communications</em> <strong>8</strong>, ncomms15123 (2017).
DOI: 10.5281/zenodo.3826425
title: Automatic image-based identication and biomass estimation of invertebrates

description: Dataset containing images of macroinvertebrates from updated BIODISCOVER (2019). The task of the image collection was to determine optimal camera settings, from 2 parameters: Exposure time and Aperture. A combination of 3 exposure time and aperture settings was tested (total of 9 combinations of settings): Exposure time: 1000, 1500, 2000 Aperture: 3.8, 8, 16 All images contained within the dataset are separated by camera settings, species and sample number. Samples containing several specimen within one sample number are indexed (example: 10023_1, 10023_2, 10023_3). Further labeling and information can be found within "setup data.csv".
DOI: 10.5281/zenodo.3826426
title: Automatic image-based identication and biomass estimation of invertebrates

description: Dataset containing images of macroinvertebrates from updated BIODISCOVER (2019). The task of the image collection was to determine optimal camera settings, from 2 parameters: Exposure time and Aperture. A combination of 3 exposure time and aperture settings was tested (total of 9 combinations of settings): Exposure time: 1000, 1500, 2000 Aperture: 3.8, 8, 16 All images contained within the dataset are separated by camera settings, species and sample number. Samples containing several specimen within one sample number are indexed (example: 10023_1, 10023_2, 10023_3). Further labeling and information can be found within "setup data.csv".
DOI: 10.5281/zenodo.3831445
title: Evaluating Mixed and Augmented Reality: A Systematic Literature Review (2009 – 2019)

description: A data set of evaluations of mixed and augmented reality in 2009 – 2019.
DOI: 10.5281/zenodo.3831206
title: Experimental data for PanDDA analysis of human JMJD1B

description: The repository contains processed data from the entire crystallographic fragment screen of human JMJD1B at the XChem facility of Diamond Light Source beamline I04-1 (JMJD1BA_XChem_screen.tar.bz2). Additionally, metadata about the experiment can be found in the <em>mainTable</em> of the corresponding SQLite database file (JMJD1BA_XChem_screen.sqlite). All identified ligand-bound structures were deposited in the Protein Data Bank under Group ID <strong>G_1002146. </strong>All structures necessary to reproduce the deposited PanDDA event maps which were used for ligand identification were deposited in the Protein Data Bank under PDB ID 5R7X (group ID <strong>G_1002141</strong>). <strong><em>Usage:</em></strong> download <em>JMJD1BA_XChem_screen.tar.bz2</em> and save into the desired project directory, e.g. <strong>/home/me/JMJD1B</strong> unpack the tar archive: <strong>tar –xvjf JMJD1BA_XChem_screen.tar.bz2</strong> run pandda, e.g. <strong>pandda.analyse data_dirs="/home/me/JMJD1B/*" out_dir="/home/me/JMJD1B_pandda" pdb_style=dimple.pdb mtz_style=dimple.mtz</strong> For more information about PanDDA, please check the PanDDA CCP4 program documentation. <strong><em>Reference:</em></strong> Pearce, N. M. <em>et al.</em> A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density. <em>Nature Communications</em> <strong>8</strong>, ncomms15123 (2017).
DOI: 10.5281/zenodo.3831207
title: Experimental data for PanDDA analysis of human JMJD1B

description: The repository contains processed data from the entire crystallographic fragment screen of human JMJD1B at the XChem facility of Diamond Light Source beamline I04-1 (JMJD1BA_XChem_screen.tar.bz2). Additionally, metadata about the experiment can be found in the <em>mainTable</em> of the corresponding SQLite database file (JMJD1BA_XChem_screen.sqlite). All identified ligand-bound structures were deposited in the Protein Data Bank under Group ID <strong>G_1002146. </strong>All structures necessary to reproduce the deposited PanDDA event maps which were used for ligand identification were deposited in the Protein Data Bank under PDB ID 5R7X (group ID <strong>G_1002141</strong>). <strong><em>Usage:</em></strong> download <em>JMJD1BA_XChem_screen.tar.bz2</em> and save into the desired project directory, e.g. <strong>/home/me/JMJD1B</strong> unpack the tar archive: <strong>tar –xvjf JMJD1BA_XChem_screen.tar.bz2</strong> run pandda, e.g. <strong>pandda.analyse data_dirs="/home/me/JMJD1B/*" out_dir="/home/me/JMJD1B_pandda" pdb_style=dimple.pdb mtz_style=dimple.mtz</strong> For more information about PanDDA, please check the PanDDA CCP4 program documentation. <strong><em>Reference:</em></strong> Pearce, N. M. <em>et al.</em> A multi-crystal method for extracting obscured crystallographic states from conventionally uninterpretable electron density. <em>Nature Communications</em> <strong>8</strong>, ncomms15123 (2017).
DOI: 10.5281/zenodo.3831270
title: Data for: Fluid Geochemistry of Hot Springs at the Tengchong Field, Southwest China

description: Major elements analyses of the vent fluid in the Tengchong hydrothermal system
DOI: 10.5281/zenodo.3831271
title: Data for: Fluid Geochemistry of Hot Springs at the Tengchong Field, Southwest China

description: Major elements analyses of the vent fluid in the Tengchong hydrothermal system
DOI: 10.5281/zenodo.3831447
title: Lituya Bay 1958 Tsunami – pre-event bathymetry reconstruction and 3D-numerical modelling utilizing the CFD software Flow-3D

description: Simulation video, Model code, STL.File of the solid bodies
DOI: 10.5519/qd.q8rf0wym
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (121 records)
DOI: 10.23650/data.h.2018.p4
title: 全国地质资料馆数字地质资料馆主站日志数据集
title: TranslatedTitle"&gt;The Dataset of User’s Accessing Log to Digital Geological Library of National Geological Archives of China

description: In order to accurately find out the needs of users of geologic data and eliminate the information gap between data users and data managers, the National Geological Archives of China (NGAC) has conducted the data collection of user's accessing logs to the master station of the Digital Geological Library of NGAC. The automatic recording method is applied to register the user's location, their searching keywords, IP address and other related information for constructing the accessing log dataset. In order to make better use of these accessing data, a standardized processing method and quality control system are adopted. The dataset provides the accessing records to the Digital Geological Library of NGAC's master station from the year 2014 to 2017, which realistically reflects user's behaving habits while obtaining geological data. It also provides a sound basis for the further constructions of geological data service website, the development and utilization of geological data, and the geological data management and services.
DOI: 10.5519/qd.52owtyoe
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.3831116
title: Functional Brain Networks of Picture Naming in Broca's Aphasia and Healthy Controls

description: The data were from the picture-naming task with MEG scanning. Brain networks of ".net" format: Each network has 776 regions that were derived by subdividing USCBrain Atlas. Phase-locking values (PLV) were calculated between the 776 regions in a gamma-band of 30-45Hz. PLVs were normalized (z-PLVs) by using the mean and standard deviation of the 200-ms pre-stimulus baseline. The edges were weighted by z-PLVs. Vector files of ".vec" format: Each file contains activations, viz., amplitude, of regions. There are two types of amplitude. One is the estimated electric density in a physical unit of picoampere. Another is the z-score of amplitude calculated through comparison with a baseline of –200 ms. We provided both the group-averaged files (named as b999 for the Broca group and c999 for the control group) and the individuals' files (b1 to b5 for the Broca's aphasia and c1 to c5 for the control persons). We also provided two ".clu" files. One is the partition file of eight functional modules in two hemispheres. Another is the partition file of two hemispheres. The .net, .vec., and .clu files can be imported to Pajek for further interpretations and visualizations.
DOI: 10.5281/zenodo.3831117
title: Functional Brain Networks of Picture Naming in Broca's Aphasia and Healthy Controls

description: The data were from the picture-naming task with MEG scanning. Brain networks of ".net" format: Each network has 776 regions that were derived by subdividing USCBrain Atlas. Phase-locking values (PLV) were calculated between the 776 regions in a gamma-band of 30-45Hz. PLVs were normalized (z-PLVs) by using the mean and standard deviation of the 200-ms pre-stimulus baseline. The edges were weighted by z-PLVs. Vector files of ".vec" format: Each file contains activations, viz., amplitude, of regions. There are two types of amplitude. One is the estimated electric density in a physical unit of picoampere. Another is the z-score of amplitude calculated through comparison with a baseline of –200 ms. We provided both the group-averaged files (named as b999 for the Broca group and c999 for the control group) and the individuals' files (b1 to b5 for the Broca's aphasia and c1 to c5 for the control persons). We also provided two ".clu" files. One is the partition file of eight functional modules in two hemispheres. Another is the partition file of two hemispheres. The .net, .vec., and .clu files can be imported to Pajek for further interpretations and visualizations.
DOI: 10.5281/zenodo.3831119
title: jmcastagnetto/covid-19-peru-data: Datos hasta el 2020-05-16

description: Datos de casos confirmados, negativos, defunciones y recuperados, transcritos de los tweets del MINSA (https://twitter.com/Minsa_Peru), de sus comunicados y de su "Sala Situacional...".
DOI: 10.5281/zenodo.3831120
title: Sparkman: A Smart Parking Management Tool For University Campuses

description: PI Kelvin Cheu and his students have developed a total parking demand model for students and a “base price” model for student parking permits based on data gathered from an internet survey on parking at 208 university campuses across the United States. This project aims to develop a student parking lot zoning and zone permit pricing model, and then integrate the total demand model, “base price” model and the zoning model into a software tool named Sparkman, which can be used by all university parking offices.
DOI: 10.5281/zenodo.3831121
title: Sparkman: A Smart Parking Management Tool For University Campuses

description: PI Kelvin Cheu and his students have developed a total parking demand model for students and a “base price” model for student parking permits based on data gathered from an internet survey on parking at 208 university campuses across the United States. This project aims to develop a student parking lot zoning and zone permit pricing model, and then integrate the total demand model, “base price” model and the zoning model into a software tool named Sparkman, which can be used by all university parking offices.
DOI: 10.3886/e116143v1-24405
title: Replication data for: Debt Relief and Debtor Outcomes: Measuring the Effects of Consumer Bankruptcy Protection

description: Consumer bankruptcy is one of the largest social insurance programs in the United States, but little is known about its impact on debtors. We use 500,000 bankruptcy filings matched to administrative tax and foreclosure data to estimate the impact of Chapter 13 bankruptcy protection on subsequent outcomes. Exploiting the random assignment of bankruptcy filings to judges, we find that Chapter 13 protection increases annual earnings by $5,562, decreases five-year mortality by 1.2 percentage points, and decreases five-year foreclosure rates by 19.1 percentage points. These results come primarily from the deterioration of outcomes among dismissed filers, not gains by granted filers. (JEL D14, I12, J22, J31, K35)
DOI: 10.5281/zenodo.3831446
title: Supporting Information for Recommender Systems in Antiviral Drug Discovery

description: Supporting Information for Recommender Systems in Antiviral Drug Discovery
DOI: 10.26300/9zz7-v355
title: AWI-FESOM.tgz
DOI: 10.21227/3etr-qz26
title: Corona Virus (COVID-19) Geolocation Enabled Tweets Dataset

description: This dataset contains the geolocation-based sentiment analysis data. The data is generated by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's data sharing policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted with an exact location that contained any of the previously mentioned keywords.Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 80 million tweets) shared in the Corona Virus (COVID-19) Tweets Dataset.If you need the geolocation-based data starting March 20, 2020, then use the Corona Virus (COVID-19) Tweets Dataset and hydrate the IDs while adding the following condition:data = json.loads(data) if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.
DOI: 10.26300/cj0y-gf98
title: CESM-POP.tgz Version 1
DOI: 10.26300/n1ev-vb74
title: CAS-LICOM3 Version 1
DOI: 10.5281/zenodo.3830820
title: JJIF Development & Statistics in the years 2010 - 2019

description: The following dataset is a digest from the JJIF world ranking list curated by the software Sportdata: http://setopen.sportdata.org/jjifranking/ranking_main.php and older hand-curated ranking lists. Used data: JJIF Raking lists from 31.12 of each year<br> - Not corrected for athletes participating in more than one category/discipline<br> (If an athlete participates in Fighting & Jiu-Jitsu he/she will be counted double)<br> - Duo & Show couples count as one (1) athlete Abbreviations for categories<br> -Discipline: FS = Fighting System; JJ = Jiu-Jitsu/Ne-Waza; DS= Duo System; SS = Show System; CS = Contact Ju-Jitsu -Gender: W = Women; M = Men; X = Mixed - Weight: +94kg is called 95; +70 is called 71 Disclaimer:<br> The information provided here is for general informational purposes only. All information on is provided in good faith, however, we make no representation or warranty of any kind, express or implied, regarding the accuracy, adequacy, validity, reliability, availability or completeness of any information.<br> <br> Rightfull owner of the data is the Ju-Jitsu International Federation (JJIF)
DOI: 10.5281/zenodo.3830821
title: JJIF Development & Statistics in the years 2010 - 2019

description: The following dataset is a digest from the JJIF world ranking list curated by the software Sportdata: http://setopen.sportdata.org/jjifranking/ranking_main.php and older hand-curated ranking lists. Used data: JJIF Raking lists from 31.12 of each year<br> - Not corrected for athletes participating in more than one category/discipline<br> (If an athlete participates in Fighting & Jiu-Jitsu he/she will be counted double)<br> - Duo & Show couples count as one (1) athlete Abbreviations for categories<br> -Discipline: FS = Fighting System; JJ = Jiu-Jitsu/Ne-Waza; DS= Duo System; SS = Show System; CS = Contact Ju-Jitsu -Gender: W = Women; M = Men; X = Mixed - Weight: +94kg is called 95; +70 is called 71 Disclaimer:<br> The information provided here is for general informational purposes only. All information on is provided in good faith, however, we make no representation or warranty of any kind, express or implied, regarding the accuracy, adequacy, validity, reliability, availability or completeness of any information.<br> <br> Rightfull owner of the data is the Ju-Jitsu International Federation (JJIF)
DOI: 10.21227/h498-px29
title: Database of Singular Value Decompositions of Matrix Representations of the Costas Condition

description: The Costas condition on a permutation matrix, expressed as row indices as elements of a vector c, can be expressed as A*c=b, where b is a vector of integers in which no element is zero. A particular formulation of the matrix A allows a singular value decomposition in which the eigenvalues are squared integers and the eigenvalues may be scaled to vectors with all integer elements. This is a database of the Costas constraint matrices A, the scaled eigenvectors, and the squared eigenvalues for orders 3 through 100.
DOI: 10.21227/kwwf-9k03
title: Database of Singular Value Decompositions of Matrix Representations of the Costas Condition

description: The Costas condition on a permutation matrix, expressed as row indices as elements of a vector c, can be expressed as A*c=b, where b is a vector of integers in which no element is zero. A particular formulation of the matrix A allows a singular value decomposition in which the eigenvalues are squared integers and the eigenvalues may be scaled to vectors with all integer elements. This is a database of the Costas constraint matrices A, the scaled eigenvectors, and the squared eigenvalues for orders 3 through 100.
DOI: 10.26300/4vmf-7233
title: CMCC-NEMO.tgz Version 1
DOI: 10.26300/gsb8-fc88
title: Kiel-NEMO.tgz Version 1
DOI: 10.26300/m2av-3c98
title: EC-Earth3-NEMO.tgz Version 1
DOI: 10.26300/tzkj-1f90
title: FSU-HYCOM.tgz
DOI: 10.26300/y0qy-s468
title: GFDL-MOM.tgz Version 1
DOI: 10.25345/c55h88
title: MassIVE MSV000085428 - Queen spermathecal fluid proteomics to investigate proteins underlying variation in stored sperm viability
title: Queens of social insects have the remarkable ability to keep sperm alive for years within their specialized storage organ, the spermatheca. Despite being one of the most critical determinants of colony health, precisely what biochemical processes enable this sustained sperm viability are largely unknown. Here, we survey quality metrics (sperm count, sperm viability, and ovary size) of honey bee queens from nine genetic sources. We then performed quantitative proteomics on spermathecal fluid from N = 123 individual queens in order to investigate the biochemical processes underlying natural variation in sperm viability.
DOI: 10.25919/5ec1acf19428a
title: Parkes observations for project P1050 semester 2020APRS_15

description: This is a request for observing time for the initial follow-up of pulsar discoveries from the re-processing of the low-latitude Galactic plane section of the HTRU survey (P630). We have now completed a first pass re-processing of the 60 % of the survey with GPU based coherent acceleration search and template bank search pipelines, and have discovered potential 54 previously unknown pulsars. Interesting science can usually only be derived from a new pulsar after confirmation and a follow-up timing campaign is carried out. One year of initial timing is the minimum timespan required to fully characterise any newly-discovered pulsars, essential for deriving pulsar parameters such as the characteristic age, magnetic field strength, spin-down rate, as well as to detect any unexpected behaviour of the pulsar which might result from emission instabilities. This follow-up and timing project is necessary for following up on any interesting pulsar systems discovered from the HTRU Galactic plane survey. Since all of the pulsars on the observing list here are being followed-up for the first time, they will produce completely new and exciting results. In addition, this timing project will enable a large-scale examination of the Galactic plane pulsar population, exploring the true boundaries of pulsar parameter space.
DOI: 10.26300/c4m2-e383
title: MIROC-COCO4-9.tgz Version 1
DOI: 10.26300/s6m0-rg32
title: NorESM-BLOM.tgz Version 1
DOI: 10.26300/shyb-v098
title: MRI-COM.tgz Version 1