cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/jvppzjg7d6.2
title: Data for: Optimization of speckle pattern based on integer programming method

description: The optimized speckle patterns generated in this study
DOI: 10.21227/fk3q-wc57
title: Twitter Sentiment Analysis Data

description: Each database (*.db) contain three columns. First column: date and time of the tweet, second column: tweet, third 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.########################################Collect Corona virus-related Tweets from here.########################################The tweets have been collected by the LSTM model deployed here at sentiment.live[1]. The last column, viz. sentiment score, is not the score estimated by the model. The LSTM model is still in the pre-alpha phase. Therefore, 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. The sentiment scores produced by our model will be made public after the project is completely open-sourced.References:[1]https://sentiment.live/ [2]https://textblob.readthedocs.io/en/dev/
DOI: 10.5281/zenodo.3756802
title: Coronavirus Open Citations Dataset

description: The Coronavirus Open Citations Dataset curated by OpenCitations currently contains (as of 16 May 2020) information about 189,697 citations and about the 49,719 citing or cited articles involved in these citations. A subset of these data (stored in the "_partial.json" files introduced below) is used for creating the visualization available at https://opencitations.github.io/coronavirus/. Each item in both the JSON files storing citations ('citations_full.json' and 'citations_partial.json') contains the following fields: "id", a numeric identifier of the citation; "source", the citing entity; "target", the cited entity. Each item in both the JSON files storing article metadata ('metadata_full.json' and 'metadata_partial.json') contains the following fields: "id", the DOI of the article; "author", the surname of all the authors of the article; "year", the year of publication; "title", the title of the article; "source_title", the title of the venue where the article has been published. In addition, any item in the file 'metadata_partial.json' contains another field: "count": the overall number of citations that the article received.
description: This version extends the coverage of citation data in the dataset with those related with the COVID-19 pandemic, coming from the May 2020 release of COCI (see https://opencitations.wordpress.com/2020/05/13/coci-may-2020-release/).
DOI: 10.5281/zenodo.3756803
title: Coronavirus open citation data

description: These are the data (full and partial) used for creating the visualisation available at https://opencitations.github.io/coronavirus/. Each item in both the JSON files storing citations ('citations_full.json' and 'citations_partial.json') contains the following fields: "id", a numeric identifier of the citation; "source", the citing entity; "target", the cited entity. Each item in both the JSON files storing article metadata ('metadata_full.json' and 'metadata_partial.json') contains the following fields: "id", the DOI of the article; "author", the surname of all the authors of the article; "year", the year of publication; "title", the title of the article; "source_title", the title of the venue where the article has been published. In addition, any item in the file 'metadata_partial.json' contains another field: "count": the overall number of citations that the article received.
DOI: 10.5281/zenodo.3756667
title: MD simulation of HpTonB(30-285) in 150mM NaCl with Amber ff03ws force field

description: MD simulation of periplasmic part of TonB protein from <em>Helicobacter Pylori</em> HpTonB(30-285) with Amber ff03ws force field with 150 mM NaCl. Trajectory contains the last 1000ns of the simulation. micro_nojump_nowater.xtc (10 ps saving frequency), nowater.tpr, and confENDprot.gro contain only protein. 1microsecondSKIP.xtc (100 ps saving frequency), md.tpr and confEND.gro contain also solvent. Force field parameters for proteins and counterions are dowloaded from https://github.com/bestlab/force_fields, for NaCl from https://bitbucket.org/hseara/ions
DOI: 10.5281/zenodo.3756668
title: MD simulation of HpTonB(30-285) in 150mM NaCl with Amber ff03ws force field

description: MD simulation of periplasmic part of TonB protein from <em>Helicobacter Pylori</em> HpTonB(30-285) with Amber ff03ws force field with 150 mM NaCl. Trajectory contains the last 1000ns of the simulation. micro_nojump_nowater.xtc (10 ps saving frequency), nowater.tpr, and confENDprot.gro contain only protein. 1microsecondSKIP.xtc (100 ps saving frequency), md.tpr and confEND.gro contain also solvent. Force field parameters for proteins and counterions are dowloaded from https://github.com/bestlab/force_fields, for NaCl from https://bitbucket.org/hseara/ions
DOI: 10.5281/zenodo.3756814
title: wolfdiet

description: This is the pre-release of the GitHub based <strong>wolfdiet</strong> database repository. For instructions on how to download and to use data, please visit the GitHub page.
description: Compared to the version 0.1.0, we have improved the database structure and readability, enhanced the repository structure, implemented an R package, created different sources to access and use data (csv, R, and psql), and load the first studies from Eurasia.
DOI: 10.5281/zenodo.3756815
title: wolfdiet

description: This is the pre-release of the GitHub based <strong>wolfdiet</strong> database repository. For instructions on how to download and to use data, please visit the GitHub page.
DOI: 10.5519/qd.49ha02xk
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.17632/7w3sxvw2hc.1
title: Data for: Revealing male genital morphology in the giant ant genus Dinoponera with geometric morphometrics
DOI: 10.25919/5e9b24a9db9d3
title: Parkes observations for project P958 semester 2020APRS_03

description: Fast radio bursts (FRBs) continue to raise more questions than they answer. Until last year, only one burst – the only one known to repeat - had been localized to a bright radio nebula (either a young supernova remnant or pulsar wind nebulae) in a distant dwarf galaxy. Over the last three years searches with the Australian Square Kilometre Array Pathfinder (ASKAP) have detected 35 bursts, eight of which have been localised to host galaxies at redshifts ranging from 0.1 to 0.5. These bursts and their hosts are very unlike the repeater, suggesting there may be a dichotomy in the population. However one of the arcminute-localised ASKAP FRBs has recently been found to repeat. Here we propose to search and study repetitions in this FRB population. Our comprehensive sample and a dense monitoring campaign of well localised bursts, at a fluence limit more than 60 times lower than that of their detections to characterise the fraction of bursts that repeat. For bursts that repeat the unique wide bandwidth observations will be used to test leading models of burst emission.
DOI: 10.17632/jvppzjg7d6.1
title: Data for: Optimization of speckle pattern based on integer programming method

description: The optimized speckle patterns generated in this study
DOI: 10.14272/ohhqmuahxrnafq-uhfffaoysa-n.1
title: 3-phenyl-2-quinoxalinecarboxaldehyde
title: InChI=1S/C15H10N2O/c18-10-14-15(11-6-2-1-3-7-11)17-13-9-5-4-8-12(13)16-14/h1-10H

description: This dataset contains experimental data from a sample (3-phenylquinoxaline-2-carbaldehyde, InChI=1S/C15H10N2O/c18-10-14-15(11-6-2-1-3-7-11)17-13-9-5-4-8-12(13)16-14/h1-10H). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) mass spectrometry (MS) infrared absorption spectroscopy (IR)
DOI: 10.14272/ohhqmuahxrnafq-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) (3-phenylquinoxaline-2-carbaldehyde)
title: InChI=1S/C15H10N2O/c18-10-14-15(11-6-2-1-3-7-11)17-13-9-5-4-8-12(13)16-14/h1-10H

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 80 °C): 235 (18) [M+H]+, 234 (100) [M]+, 233 (11), 207 (13), 206 (90), 205 (75), 179 (33), 117 (13), 103 (18), 102 (33), 77 (40), 76 (24), 75 (17), 51 (20).HRMS–EI (m/z): [M]+ calcd for C14H10O1N2, 234.0793; found, 234.0794.
DOI: 10.14272/ohhqmuahxrnafq-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) (3-phenylquinoxaline-2-carbaldehyde)
title: InChI=1S/C15H10N2O/c18-10-14-15(11-6-2-1-3-7-11)17-13-9-5-4-8-12(13)16-14/h1-10H

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CDCl3, ppm) δ = 7.56–7.58 (m, 3H), 7.68–7.75 (m, 2H), 7.89 (ddd, J = 8.4, 6.9, 1.5 Hz, 1H), 7.95 (ddd, J = 8.4, 6.8, 1.6 Hz, 1H), 8.23 (dd, J = 8.4, 1.6 Hz, 1H), 8.33 (dd, J = 8.4, 1.5 Hz, 1H), 10.33 (s, 1H). Impurities: Spectra containing solvent peaks of water (1.56 ppm), ethyl acetate (2.17 ppm) and grease (1.26 ppm).
DOI: 10.14272/ohhqmuahxrnafq-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) (3-phenylquinoxaline-2-carbaldehyde)
title: InChI=1S/C15H10N2O/c18-10-14-15(11-6-2-1-3-7-11)17-13-9-5-4-8-12(13)16-14/h1-10H

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, CDCl3, ppm) δ = 128.8 (2C), 129.6, 130.0 (2C), 130.0, 130.5, 131.1, 133.2, 136.8, 141.2, 143.0, 145.2, 154.7, 191.4.
DOI: 10.14272/ohhqmuahxrnafq-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) (3-phenylquinoxaline-2-carbaldehyde)
title: InChI=1S/C15H10N2O/c18-10-14-15(11-6-2-1-3-7-11)17-13-9-5-4-8-12(13)16-14/h1-10H

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 3397, 3084, 3055, 3024, 2928, 2857, 2187, 1955, 1795, 1708, 1608, 1553, 1528, 1507, 1477, 1459, 1445, 1391, 1346, 1327, 1303, 1252, 1220, 1193, 1163, 1135, 1122, 1075, 1004, 997, 967, 932, 895, 870, 843, 806, 778, 761, 717, 700, 686, 622, 602, 582, 565, 552, 518, 465, 428, 409 cm–1.
DOI: 10.5281/zenodo.3756629
title: Wikidata Dump nouns_ru_en

description: RDF dump of wikidata produced with wdumps. Nouns Russian, English with grammar gender<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3756630
title: Wikidata Dump nouns_ru_en

description: RDF dump of wikidata produced with wdumps. Nouns Russian, English with grammar gender<br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.3756984
title: Artifacts related to "Using Informed Access Network Selection to Improve HTTP Adaptive Streaming Performance"

description: This archive contains data related to in the following paper: "Using Informed Access Network Selection to Improve HTTP Adaptive Streaming Performance" (published at the ACM MMSys 2020 conference) Copyright (c) 2020, Theresa Enghardt &lt;theresa@tenghardt.net&gt;, Fachgebiet INET - TU Berlin. <br> See https://github.com/fg-inet/MMSys2020_Informed-Access-Network-Selection for more information. This data is released under the Creative Commons Attribution 4.0 International license.
description: {"references": ["https://github.com/fg-inet/MMSys2020_Informed-Access-Network-Selection"]}
DOI: 10.21227/4xk4-jn30
title: Supplementary Material for TII

description: Supplementary material for TII.
DOI: 10.21227/tdy4-ts70
title: Supplementary Material for TII

description: Supplementary material for TII.
DOI: 10.21227/vtzq-af33
title: Supplementary Material for TII

description: Supplementary material for TII.
DOI: 10.21227/vv53-5145
title: Supplementary Material

description: Supplementary material for TII.
DOI: 10.7910/dvn/fok9ma/2hwee2
title: population_1km_China_201509.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/hnetjs
title: population_1km_China_201503.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/oyraa4
title: population_1km_China_201504.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/2hmoqi
title: population_1km_China_201508.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/7idcus
title: population_1km_China_201505.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/bvwoxw
title: population_1km_China_201511.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/d6smet
title: population_1km_China_201501.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/dvayfl
title: population_1km_China_201502.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/g29mif
title: population_1km_China_201512.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/qohnw5
title: population_1km_China_201506.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/wrdm3l
title: population_1km_China_201507.tif

description: :unav
DOI: 10.7910/dvn/fok9ma/xr0uz3
title: population_1km_China_201510.tif

description: :unav
DOI: 10.21227/q1s4-8540
title: modified CASIA

description: The modified CASIA dataset is created for research topics like: perceptual image hash, image tampering detection, user-device physical unclonable function and so on. The ground truth images are taken from the CASIA image tampering detection evaluation (ITDE) v1.0 database (J.Dong, et. al, CASIA image tampering detection evaluation database, ChinaSIP2013), which contains images from eight categories (animal, architecture, article, character, nature, plant, scene and texture) of size 384X256 or 256X384. Instead of directly using the tampered image set from CASIA ITDE v1.0, the tampered versions of those authentic images are selected from CASIA ITDE V2.0, which are more challenging and comprehensive since it considers post-processing like blurring or filtering over the tampered regions to make the tampered images appear realistic to human eyes. For one authentic image, there may be several tampered versions in the CASIA ITDE v2.0 dataset. To increase the diversity, only one tampered version is kept for each authentic image. As a result, the modified CASIA database contains 400 (8 categories X 50 per category) authentic images and their corresponding tampered versions.According to CASIA ITDE v2.0, the tampered images are generated using crop-and-paste operation under Adobe Photoshop on the authentic images, and the tampered regions may have random shapes and different sizes, rotations or distortions. In order to evaluate the proposed system performance over content-preserving manipulations, we enrich the modified CASIA dataset by adding content-preserving manipulations to the authentic images using Matlab and ImageJ. Common image processing techniques like rotation, scaling, filtering and JPEG compression, and unavoidable process/transmission noises like Gaussian, Salt&Pepper and speckle noise are considered. Furthermore, the abovementioned content-preserving manipulations are also applied to the tampered dataset to evaluate if their combination can evade detection. As a result, the modified CASIA database D contains:1) D_au: 400 authentic images in 8 categories, each with 50 images;2) D_tampered: 400 tampered images corresponding to the authentic ones from D_au;3) D_au_cp: 3600 (400x 9) images generated by adding a single content-preserving manipulation (9 types: Gaussian noise, salt&pepper noise, speckle noise, Gaussian filter, motion blur, JPEG compression, gamma correction, rotation and scaling) to every image of D_au;4) D_tampered_cp: 3600 (400x9) tampered images by applying those 9 content-preserving manipulations listed in 3) to the images of Dtampered.To use the dataset, please cite: [1] Y. Zheng, Y. Cao and C. Chang, "A PUF-Based Data-Device Hash for Tampered Image Detection and Source Camera Identification," in IEEE Transactions on Information Forensics and Security, vol. 15, pp. 620-634, 2020.[2]J. Dong, W. Wang and T. Tan, "CASIA Image Tampering Detection Evaluation Database," 2013 IEEE China Summit and International Conference on Signal and Information Processing, Beijing, 2013, pp. 422-426.
DOI: 10.5063/f1hx1b2t
title: OHIBC: Changes in ocean health in British Columbia from 2001 to 2016

description: This dataset includes calculated scores, region spatial information, and a zipped repository of all the code necessary to generate the results for the Ocean Health Index British Columbia (OHIBC) project. The study was published in PLOS ONE in January 2020: https://doi.org/10.1371/journal.pone.0227502. Abstract of PLOS ONE publication: Effective management of marine systems requires quantitative tools that can assess the state of the marine social-ecological system and are responsive to management actions and pressures. We applied the Ocean Health Index (OHI) framework to retrospectively assess ocean health in British Columbia annually from 2001 to 2016 for eight goals that represent the values of British Columbia’s coastal communities. We found overall ocean health improved over the study period, from 75 (out of 100) in 2001 to 83 in 2016, with scores for inhabited regions ranging from 68 (North Coast, 2002) to 87 (West Vancouver Island, 2011). Highest-scoring goals were Tourism & Recreation (average 94 over the period) and Habitat Services (100); lowest-scoring goals were Sense of Place (61) and Food Provision (64). Significant increases in scores over the time period occurred for Food Provision (+1.7 per year), Sense of Place (+1.4 per year), and Coastal Livelihoods (+0.6 per year), while Habitat Services (-0.01 per year) and Biodiversity (-0.09 per year) showed modest but statistically significant declines. From the results of our time-series analysis, we used the OHI framework to evaluate impacts of a range of management actions. Despite challenges in data availability, we found evidence for the ability of management to reduce pressures on several goals, suggesting the potential of OHI as a tool for assessing the effectiveness of marine resource management to improve ocean health. Our OHI assessment provides an important comprehensive evaluation of ocean health in British Columbia, and our open and transparent process highlights opportunities for improving accessibility of social and ecological data to inform future assessment and management of ocean health.
DOI: 10.34725/dvn/hlrxnf/ipapbh
title: Documentation-1.docx
DOI: 10.34725/dvn/hlrxnf/mdxa16
title: Countries and their ISO 3166-1 alpha-3 codes matched to the World Geographical Scheme for Recording Plant Distributions version APR2020.tab

description: The dataset shows matches between countries and the World Geographical Scheme for Recording Plant Distributions (WGSRPD; Brummitt, 2001), which divides the terrestrial world into nine areas: Africa, Antarctic, Asia-Temperate, Asia-Tropical, Australasia, Europe, Northern America, Pacific, and Southern America.
DOI: 10.5281/zenodo.3756936
title: Selectomic and Evolvability Analyses of the Highly Pathogenic Betacoronaviruses SARS-CoV-2, SARS-CoV, and MERS-CoV

description: SARS-CoV-2, the causative agent of COVID-19, is widespread in several countries around the world following its late 2019 emergence in humans. We determined the SARS-CoV-2 selectome by calculating rates of pervasive and episodic diversifying selection for every amino acid coding position in the SARS-CoV-2 genome. To provide context for evolutionary dynamics of a highly pathogenic betacoronavirus following a zoonotic spillover into human hosts, we also determined the selectomes of SARS-CoV and MERS-CoV, and performed evolvability calculations for SARS-CoV-2 based on SARS-CoV. These findings provide a comprehensive view of zoonotic, highly pathogenic betacoronavirus evolutionary dynamics that can be directly applied to diagnostic assay and vaccine design for SARS-CoV-2.
DOI: 10.5281/zenodo.3756937
title: Selectomic and Evolvability Analyses of the Highly Pathogenic Betacoronaviruses SARS-CoV-2, SARS-CoV, and MERS-CoV

description: SARS-CoV-2, the causative agent of COVID-19, is widespread in several countries around the world following its late 2019 emergence in humans. We determined the SARS-CoV-2 selectome by calculating rates of pervasive and episodic diversifying selection for every amino acid coding position in the SARS-CoV-2 genome. To provide context for evolutionary dynamics of a highly pathogenic betacoronavirus following a zoonotic spillover into human hosts, we also determined the selectomes of SARS-CoV and MERS-CoV, and performed evolvability calculations for SARS-CoV-2 based on SARS-CoV. These findings provide a comprehensive view of zoonotic, highly pathogenic betacoronavirus evolutionary dynamics that can be directly applied to diagnostic assay and vaccine design for SARS-CoV-2.
DOI: 10.21227/6nhk-3t43
title: Cross-domain Ontology of Web Application over Encrypted Data

description: An ontology for the multidisciplinary phenomenon of creating web application ove encrypted data
DOI: 10.21227/e0bk-2x38
title: Cross-domain Ontology of Web Application over Encrypted Data

description: An ontology for the multidisciplinary phenomenon of creating web application ove encrypted data
DOI: 10.34725/dvn/hlrxnf/opubxc
title: CodeBook.tab
DOI: 10.5281/zenodo.3757266
title: Inspector Javert's Xref Database

description: It would have been really useful for Inspector Javert to find Jean Valjean if he had the cross-references between the identifies of all of the people he met in Montreuil-sur-Mer to the prisoner database (all he needed was 24601!). Since this dataset has a long name, you can feel free to abbreviate it as IJXD. We have the same problem in bioinformatics, so this is a database of cross-references extracted from OBO Foundry and other sources by PyOBO. It is a gzipped five-column TSV file that has source namespace, source identifier, target namespace, target identifier, and provenance. Each has been normalized so cross-references from different sources can be integrated and traversed. It was generated with the following code in the shell: <pre>pip install git+https://github.com/pyobo/pyobo.git obo javerts-xrefs</pre>
DOI: 10.5281/zenodo.3757280
title: Linked COVID-19 Data: JHU and ECDC

description: Linked COVID-19 Data derived from <strong>Johns Hopkins University</strong> and <strong>European Centre for Disease Prevention and Control</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828
DOI: 10.5281/zenodo.3757284
title: Linked COVID-19 Data: RKI

description: Linked COVID-19 Data derived from <strong>Robert Koch Institute</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828
DOI: 10.5281/zenodo.3756956
title: Open Data Articles of Journal of Contemporary Administration (Jul2018-Jan2020)

description: This table shows the list of articles with Open Data published by The Journal of Contemporary Administration between Jul2018-Jan2020. All of them are Open, without any kind of fee/cost.
DOI: 10.21227/0f06-kv55
title: Mathematical Insight - Part II

description: This dataset is in support of my claim to new theory mathematical insight-Part 1, submitted to IEEE Transactions on Circuits and Systems I
DOI: 10.21227/ejtx-ey77
title: Mathematical Insight - Part I

description: This dataset is in support of my claim to new theory mathematical insight-Part 1, submitted to IEEE Transactions on Circuits and Systems IRegular Papers
DOI: 10.21227/a3qb-sd35
title: Terrain Identification for Humanoid Robots

description: Stable and efficient walking strategies for humanoid robots usually relies on assumptions regarding terrain characteristics. If the robot is able to classify the ground type at the footstep moment, it is possible to take preventive actions to avoid falls and to reduce energy consumption. This dataset contains raw data from 10 inertial and torque sensors of a humanoid robot, sampled after the impact between foot and ground. There are two types of data: simulated using gazebo and data from a real robot.