cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3772526
title: Hydrogen storage properties of Mn and Cu for Fe substitution in TiFe0.9 intermetallic compound - Raw Dataset related to publication

description: Data type: Experimental measurements and Rietveld Refinement. Date format: .opj, .pcr, .dat (Software FullProf package outputs). Origin of the data: Experimental x-ray diffraction patterns, and kinetic measurements of hydrogen absorption. Data generated by a Bruker D8 Advance Bragg Brentano diffractometer using Cu-Kα radiation (λ=1.5418 Å), and a home-made Sieverts’ type apparatus from CNRS, ICMPE, Thiais, France. Software needed to plot the data: Origin. Software needed to analyse the data: FullProf package.
DOI: 10.5281/zenodo.3694342
title: Petromagnetic characteristics of serpentinization and magnetite formation at the Zedang ophiolite in southern Tibet

description: Table 1. Density and Magnetic Data Table 2. Mineral Chemistry Data Table 3. Summery of Magnetization Intensity Table S1. Electron Microprobe Analysis Data
DOI: 10.5281/zenodo.5163029
title: MHD-test particles simulations of moderate CME and CIR-driven geomagnetic storms at solar minimum

description: field100x180.t0.data contains results from GAMERA code to produce Figure 3. Variables, grids, and units are described in the file. May2019_kp3_2000_both-Lstar_PSD.h5 contains simulated 2000 MeV/G electron phase space density during the May event on a radial and time grid and is used to plot Figure 5. Its radial profile at 05/14 10UT is used in Figure 7a. The unit of PSD is (c/MeV/cm)^3. May2019_kp3_5000_both-Lstar_PSD.h5 contains simulated 5000 MeV/G electron phase space density during the May event on a radial and time grid. Its radial profile at 05/14 10UT is used in Figure 7b. The unit of PSD is (c/MeV/cm)^3. Sept2019_Gamera_2000_both-Lstar_PSD.h5 contains simulated 2000 MeV/G electron phase space density during the May event on a radial and time grid and is used to plot Figure 6. Its radial profile at 09/03 00UT is used in Figure 7c. The unit of PSD is (c/MeV/cm)^3. Sept2019_Gamera_5000_both-Lstar_PSD.h5 contains simulated 5000 MeV/G electron phase space density during the May event on a radial and time grid. Its radial profile at 09/03 00UT is used in Figure 7d. The unit of PSD is (c/MeV/cm)^3.
DOI: 10.5281/zenodo.5834838
title: AI tutorial data

description: Preprocessing demo
DOI: 10.5281/zenodo.6544528
title: AI Ethics

description: This repository contains datasets to support our paper titled <code>The Different Faces of AI Ethics Across the World: A Principle-Implementation Gap Analysis</code> submitted to IEEE Transactions on Artificial Intelligence.
DOI: 10.5281/zenodo.3596695
title: Energy Balance Flanders quarterly and monthly data and related auxiliary data

description: This data set is used in the VITO pilot study of the UNECE Machine Learning project 2019-2020.
DOI: 10.5281/zenodo.4621143
title: Raw Data for the article: Vitamin D levels in liver transplantation recipients and early postoperative outcomes: Prospective observational DLiverX study

description: <strong>Background & aims: </strong>In critically ill patients with liver disease, vitamin D deficiency is associated with higher disease severity, increased frequency of infections, and worse outcomes. This study sought to describe the trend of vitamin D in orthotopic liver transplantation (OLT) recipients and its association with outcomes. <strong>Methods: </strong>Prospective observational study of 67 consecutive OLT recipients enrolled between September, 2016 and August, 2017 at IRCCS-ISMETT, Palermo (Italy). Trend of vitamin D levels and potential factors influencing it levels were evaluated through a generalized linear mixed regression model. <strong>Results: </strong>Sixty-four (95.5%) recipients were vitamin D deficient (&lt;20 ng/ml), with a median value of 8.8 ng/ml [6.2-12.9], and forty-seven of these (70.1%) showed severe deficiency (&lt;12 ng/ml) at baseline, 7.9 ng/ml [5.4-8.9]. The baseline vitamin D showed an inverse correlation with liver disease severity: Child-Pugh, MELD score, bilirubin, INR, and organ failure (p &lt; 0.01) at baseline. Vitamin D increased on postoperative day (POD) 28 compared with POD1: +4.5 ng/ml, C.I. 95% 3.6-5.3 ng/ml, p &lt; 0.01. Lower baseline vitamin D, donor age, transfusion of fresh frozen plasma (negative impact, all p &lt; 0.05), and intra-operative bypass (positive impact at POD 28, p &lt; 0.01) were associated with variation of vitamin D levels after transplantation. Incomplete graft recovery was associated with lower vitamin D on POD28: 8.2 ± 4.4 versus 13.8 ± 9.4 ng/ml, p &lt; 0.01; the odds ratio (OR) was 0.84; CI 95% 0.73-0.97, p = 0.014. The OR for infections within POD 28 was inversely associated with baseline vitamin D: 0.87; CI 95% 0.79-0.98, p = 0.02, and with vitamin D level at baseline &lt;12 ng/ml: OR 6.44; CI 95% 1.66-24.94; p &lt; 0.01. <strong>Conclusions: </strong>Preoperative Vitamin D is correlated with disease severity, and was highly associated with invasive infection in the first 28 PODs. After OLT, the value on POD 28 had a strong association with graft function.
DOI: 10.5281/zenodo.5769956
title: SciCheck

description: This archive contains AI-KG with additional 300K triples used in the paper "Completing Scientific Facts in Knowledge Graphs of Research Concepts", accepted in IEEE Access.
DOI: 10.5281/zenodo.6983471
title: Structure of MAPbI3 surface models in VASP format

description: Structure of MAPbI<sub>3</sub> surface models in VASP format, with the slab thickness of 6 stoichiometric units, along (001) planes. These models were generated for the study published in reference 1. (1) Lodeiro, L.; Barría-Cáceres, F.; Jiménez, K.; Contreras, R.; Montero-Alejo, A. L.; Menéndez-Proupin, E. Methodological Issues in First-Principle Calculations of CH3NH3PbI3 Perovskite Surfaces: Quantum Confinement and Thermal Motion. <em>ACS Omega</em> <strong>2020</strong>, <em>5</em> (45), 29477–29491. https://doi.org/10.1021/acsomega.0c04420.
description: {"references": ["Lodeiro, L.; Barr\u00eda-C\u00e1ceres, F.; Jim\u00e9nez, K.; Contreras, R.; Montero-Alejo, A. L.; Men\u00e9ndez-Proupin, E. Methodological Issues in First-Principle Calculations of CH 3 NH 3 PbI 3 Perovskite Surfaces: Quantum Confinement and Thermal Motion. ACS Omega 2020, 5 (45), 29477\u201329491. https://doi.org/10.1021/acsomega.0c04420."]}
DOI: 10.5281/zenodo.3381858
title: DGU-AI-LAB/Korean-Tourist-Spot-Dataset: Korean Tourist Spot Dataset

description: The KTS dataset has four modals (image, text, hashtag, likes) and consists of 10 classes related to Korean tourist spots. All data were extracted from Instagram and preprocessed.
DOI: 10.5281/zenodo.3381859
title: DGU-AI-LAB/Korean-Tourist-Spot-Dataset: Korean Tourist Spot Dataset

description: The KTS dataset has four modals (image, text, hashtag, likes) and consists of 10 classes related to Korean tourist spots. All data were extracted from Instagram and preprocessed.
DOI: 10.5281/zenodo.3607251
title: Photovoltaic system power production

description: The dataset contains data related to the photovoltaic (PV) system installed at Poznan Supercomputing and Networking Center used to power the servers in one of the server rooms. The data come from a 1-month measurement period taken between 03.09.2019-03.10.2019. The PV system consists of 80 PV panels with 20kW peak power. Servers are directly connected to inverters so that they can be supplied directly by the power grid, PV system in the case of sufficient generation or by batteries (75kWh) if energy production is too low. Switching between power sources can be controlled by the user, however, if batteries are discharged below 60%, servers immediately switch to the power grid to extend battery life. During the measurements, only part of the servers was attached to the PV system responsible for ~1kW power usage. Poznan’s coordinates: 52°24'24.91" N 16°55'47.75" E Time period: 03.09.2019-03.10.2019
description: Dataset is provided in CSV format, with the following headers: Date [DD/MM/YY hh:mm] - time of measurements Power [W] - current power production Day_yield [Wh] - energy yield (on a daily basis)
DOI: 10.5281/zenodo.3930567
title: Petromagnetic characteristics of serpentinization and magnetite formation at the Zedang ophiolite in southern Tibet

description: Table 1. Density and Magnetic Data Table 2. Mineral Chemistry Data Table 3. Summery of Magnetization Intensity Table S1. Electron Microprobe Analysis Data
DOI: 10.5281/zenodo.5511994
title: 2021 UN Open GIS Challenge 1 - Training on Satellite Data Analysis and Machine Learning with QGIS (Satellite_QGIS)

description: This dataset is part of the 2021 UN Open GIS Challenge 1 - Training on Satellite Data Analysis and Machine Learning with QGIS (Satellite_QGIS), Exercise 2. Trend Detection: Monitoring deforestation in São Félix do Xingu, Pará - Brazil. The folder structure is the following: points.gpkg: This file contains 3 random points inside São Félix do Xingu. They are used to explore historical data with the GEE Timeseries Explorer plugin in QGIS. sao_felix_do_xingu.geojson: This file is the boundary of São Félix do Xingu, a municipality from Pará state (in the Northern part of Brazil). This municipality contains part of: Tapirapé Biological Reserve, created in 1989. Tapirapé-Aquiri National Forest, created in 1989. Terra do Meio Ecological Station, created in 2005. Serra do Pardo National Park, created in 2005. Source: Geodata BR - Brasil.
DOI: 10.5281/zenodo.573991
title: Illinois Synthetic Ecosystem

description: Illinois synthetic population dataset consisting of tables for persons, households, schools, and workplaces.  This dataset was created by the SPEW program from 2010 ACS SF 5-Year counts;  2010 US TIGER Roads; ACS PUMS 1-Year micro data; 2013 and 2011 NCES schools; and 2009 ESRI workplaces.
DOI: 10.5281/zenodo.3463688
title: ai-matrix Faster_RCNN

description: Large files in ai-matrix.
DOI: 10.5281/zenodo.3463691
title: ai-matrix NCF

description: Large files in ai-matrix.
DOI: 10.5281/zenodo.4247447
title: Disease and lesion maps - part of the Scientific opinion on the evaluation of public and animal health risks in case of a delayed post-mortem inspection in ungulates

description: EFSA was requested to assess the impact on effectiveness of <em>post-mortem</em> inspection in terms of any change in the sensitivity of detection of animal diseases of domestic and wild ungulates listed according to Article 5 of Regulation (EC) No 2016/429 and septicaemia, pyaemia, toxaemia or viraemia, when carried out after up to 24 hours or up to 72 hours after slaughter in comparison to when it is carried out immediately after slaughter. In order to identify the main lesions associated with the target diseases, a so called “disease map” was built, with the information about the clinical forms of the diseases (acute, subacute, chronic, or latent forms) and clinical signs, as well as potential lesions that could be observed on the respective diseased animals. The following information is indicated for each disease/condition in the disease map: The susceptible animal species Whether there is any surveillance programme in place in the EU The signs associated with the disease that could be detected at <em>ante mortem </em>inspection; The lesions associated with the disease that could be detected at <em>post mortem</em> inspection The probability of detecting the disease during the PMI as normally carried out. Whether carcass swabbing and/or laboratory tests are normally carried out. From the disease map, the list of organs to be considered at <em>post mortem</em> inspection and the lesions, a “lesion map” was built by connecting animal species with organs, lesions and corresponding disease. This was done to facilitate the construction of a questionnaire where, for each organ and the five types of lesions, the respondents (meat inspectors) had to provide a numerical answer about how many carcasses out of 100 with the given lesion, will be still detected after 24- or 72-h of refrigerated storage.
description: EU; XLSX; biohaz@efsa.europa.eu
DOI: 10.5281/zenodo.582892
title: Baseline Models And Optimized Cnn Models For 8 Datasets

description: Datasets:


	Asirra
	CIFAR-10
	CIFAR-100
	GTSRB
	HASYv2
	MNIST
	STL-10
	SVHN
DOI: 10.5281/zenodo.6616631
title: Fire, smoke and gas leakage detection Dataset

description: This is an open free dataset associated with fire, smoke and gas leakage detection captured from the Smart Building sensor system, namely SB112, with edge computing and Next Generation (NG) 112 emergency call capabilities. In case you use or process this dataset please refer to your work/study the following paper in which the SB112 is described in detail. Maltezos, E.; Petousakis, K.; Dadoukis, A.; Karagiannidis, L.; Ouzounoglou, E.; Krommyda, M.; Hadjipavlis, G.; Amditis, A. A Smart Building Fire and Gas Leakage Alert System with Edge Computing and NG112 Emergency Call Capabilities. <em>Information</em> 2022, <em>13</em>, 164. https://doi.org/10.3390/info13040164 The excel files contain data from 08/03/2022 to 11/03/2022. From 08/03 to 10/03/2022 the data is gathered from continuous operation without physical triggering. On 11/03/2022 a physical trigger of the sensors was performed by: Burning a piece of paper in a distance of 15 cm - 20cm to the Smoke and CO sensors. By exposing the LPG/CNG sensors to lighter gas in a distance of 5 cm - 10cm. By exposing the Flame/IR sensor to a moving flame from a lighter in a distance of 15 cm - 100cm. In each sheet of the excel files there are four columns: i) the datetime that a measurement was captured, ii) the type of the sensor, iii) the unit of the measurement, and iv) the data value. <strong>Acknowledgments: </strong>This work is a part of the S4AllCities project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 883522. Content reflects only the authors’ views; the Research Executive Agency (REA)/European Commission is not responsible for any use that may be made of the information it contains.
DOI: 10.5281/zenodo.1299152
title: Example Mri Scans From Sleep Deprivation Experiment

description: As part of a pre-study in a sleep deprivation experiment, large amount of brain MRI scans were collected.<br>
An example set is shared here. The scans were taken after being awake for approximately 3, 14, 27 and 35 hours. 

The primary goal is to help researchers with example data. For instance, image co-registration between repeated scans could be challenging, or co-registering volumes from various protocols, visualization, etc. 

The dataset is voluntarily shared and published by the subject (me) for any scientific and non-commercial use.
DOI: 10.5281/zenodo.3521071
title: ai-matrix BERT_PyTorch

description: ai-matrix BERT_PyTorch pretrained model, converted from TensorFlow model, <strong>uncased_L-24_H-1024_A-16</strong>
DOI: 10.5281/zenodo.5030895
title: Effects of disturbances on aboveground biomass of alpine meadow in the Yellow River Source Zone, Western China

description: Dataset for ''Effects of disturbances on aboveground biomass of alpine meadow in the Yellow River Source Zone, Western China''
DOI: 10.5281/zenodo.6616632
title: Fire, smoke and gas leakage detection Dataset

description: This is an open free dataset associated with fire, smoke and gas leakage detection captured from the Smart Building sensor system, namely SB112, with edge computing and Next Generation (NG) 112 emergency call capabilities. In case you use or process this dataset please refer to your work/study the following paper in which the SB112 is described in detail. Maltezos, E.; Petousakis, K.; Dadoukis, A.; Karagiannidis, L.; Ouzounoglou, E.; Krommyda, M.; Hadjipavlis, G.; Amditis, A. A Smart Building Fire and Gas Leakage Alert System with Edge Computing and NG112 Emergency Call Capabilities. <em>Information</em> 2022, <em>13</em>, 164. https://doi.org/10.3390/info13040164 The excel files contain data from 08/03/2022 to 11/03/2022. From 08/03 to 10/03/2022 the data is gathered from continuous operation without physical triggering. On 11/03/2022 a physical trigger of the sensors was performed by: Burning a piece of paper in a distance of 15 cm - 20cm to the Smoke and CO sensors. By exposing the LPG/CNG sensors to lighter gas in a distance of 5 cm - 10cm. By exposing the Flame/IR sensor to a moving flame from a lighter in a distance of 15 cm - 100cm. In each sheet of the excel files there are four columns: i) the datetime that a measurement was captured, ii) the type of the sensor, iii) the unit of the measurement, and iv) the data value. <strong>Acknowledgments: </strong>This work is a part of the S4AllCities project. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 883522. Content reflects only the authors’ views; the Research Executive Agency (REA)/European Commission is not responsible for any use that may be made of the information it contains.
DOI: 10.5281/zenodo.3596694
title: Energy Balance Flanders quarterly and monthly data and related auxiliary data

description: This data set is used in the VITO pilot study of the UNECE Machine Learning project 2019-2020.
DOI: 10.5281/zenodo.4485002
title: grasshoppermouse/gossipdata2008: Data for revised version of competitive gossip paper

description: No description provided.
DOI: 10.5281/zenodo.5834557
title: AI tutorial data

description: Preprocessing demo
DOI: 10.5281/zenodo.5834805
title: AI tutorial data

description: Preprocessing demo
DOI: 10.5281/zenodo.6368831
title: Nasdaq Stocks Dataset

description: NASDAQ (National Association of Securities Dealers Automated Quotation) is the world's second largest automated and electronic stock exchange and securities market in the United States, the first being the New York Stock Exchange, with more than 8,000 companies and corporations. It has more trading volume per hour than any other stock exchange in the world. More than 7,000 small and mid-cap stocks are traded on the NASDAQ. It is characterized by comprising high-tech companies in electronics, computers, telecommunications, biotechnology, and many others.<br> <br> This dataset was created as a result of an automatic extraction of open & public data available in nasdaq.com, using web scraping techniques. The only purpose of creating it was for academic reasons
description: https://github.com/jadvani/NasdaqScraper
DOI: 10.5281/zenodo.7638511
title: DBLP-QuAD DBLP Dump

description: This is the RDF dump of DBLP released on August 1, 2022. The DBLP RDF dump is published to allow fair and replicable evaluation of KGQA systems with the DBLP-QuAD dataset.
DOI: 10.1594/pangaea.66394
title: Magnetic profile from the 4th Dec 2001 during cruise ANT-XIX/2 in the South Atlantic
DOI: 10.5281/zenodo.3733785
title: Data for plant aggregation explained by litter traits and litter decomposition

description: Dataset used in the article "After-life traits and interactions among decomposing litters control during-life aggregation of plant species" in Functional Ecology
DOI: 10.5281/zenodo.4094682
title: Dataset of Correlation of clinical decision-making with probability of disease: A web-based study among general practitioners

description: In databases we find the following information: - the true probability of the disease in the clinical vignette<br> - the probability of the disease estimated by the general practitioner (GP) in the clinical vignette<br> - the clinical decision of the general practitioner<br> - the baseline characteristics of the participants
DOI: 10.5281/zenodo.4545641
title: ADMO-tableSuppl1

description: ADMO-tableSuppl1
DOI: 10.5281/zenodo.6500096
title: 基于随机森林的加热卷烟烟叶原料适用性评估

description: 化学计量学
DOI: 10.5281/zenodo.6983470
title: Structure of MAPbI3 surface models in VASP format

description: Structure of MAPbI<sub>3</sub> surface models in VASP format, with the slab thickness of 6 stoichiometric units, along (001) planes. These models were generated for the study published in reference 1. (1) Lodeiro, L.; Barría-Cáceres, F.; Jiménez, K.; Contreras, R.; Montero-Alejo, A. L.; Menéndez-Proupin, E. Methodological Issues in First-Principle Calculations of CH3NH3PbI3 Perovskite Surfaces: Quantum Confinement and Thermal Motion. <em>ACS Omega</em> <strong>2020</strong>, <em>5</em> (45), 29477–29491. https://doi.org/10.1021/acsomega.0c04420.
description: {"references": ["Lodeiro, L.; Barr\u00eda-C\u00e1ceres, F.; Jim\u00e9nez, K.; Contreras, R.; Montero-Alejo, A. L.; Men\u00e9ndez-Proupin, E. Methodological Issues in First-Principle Calculations of CH 3 NH 3 PbI 3 Perovskite Surfaces: Quantum Confinement and Thermal Motion. ACS Omega 2020, 5 (45), 29477\u201329491. https://doi.org/10.1021/acsomega.0c04420."]}
DOI: 10.57760/sciencedb.20076
title: Data on water consumption of Haloxylon ammodendron in the Minqin desert, root isotopes, soil moisture content, and meteorological elements
title: 民勤荒漠梭梭耗水量、根系同位素、土壤含水率、气象要素等数据

description: Soil particle size, soil moisture content, water consumption of Haloxylon ammodendron, and restoration measures in degraded Haloxylon ammodendron forest land
description: Soil particle size, soil moisture content, water consumption of Haloxylon ammodendron, and restoration measures in degraded Haloxylon ammodendron forest land
DOI: 10.1594/pangaea.407449
title: Meteorological data from Subduction Buoy SUBUOYNE
DOI: 10.5281/zenodo.3463706
title: ai-matrix SegLink

description: Large files in ai-matrix.
DOI: 10.5281/zenodo.3778915
title: DBLP Article Similarities (DBLP-ArtSim) dataset

description: This dataset contains similarity scores among articles in AMiner's DBLP v10 dataset. Similarities are calculated using the JoinSim [1] similarity measure on the derived citation network using the following metapaths: Paper - Author - Paper (PAP.csv.gz) Paper - Topic - Paper (PTP.csv.gz) Paper - Venue - Paper (PVP.csv.gz) The Paper to Venue relationships also also provided in PV_relationships.csv.gz. The file aminer_ids.csv.gz contains a mapping from AMiner's ids to our internal numeric ids used in the similarities files. [1] Xiong, Y., Zhu, Y., Yu, P.S.: Top-k similarity join in heterogeneous information networks. IEEE Transactions on Knowledge and Data Engineering 27(6), 1710– 1723 (2015)
description: We acknowledge support of this work by the project "Moving from Big Data Management to Data Science" (MIS 5002437/3) which is implemented under the Action "Reinforcement of the Research and Innovation Infrastructure", funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund).
DOI: 10.5281/zenodo.5834773
title: AI tutorial data

description: Preprocessing demo
DOI: 10.5281/zenodo.4468721
title: GUT MICROBIOME COMPOSITION IN ALZHEIMER'S DEMENTIA PATIENTS: REPORT FROM PILOT STUDY IN KAZAKHSTAN

description: Sequencing raw data of microbiome in fastq format
DOI: 10.5281/zenodo.5834792
title: AI tutorial data

description: Preprocessing demo
DOI: 10.5281/zenodo.7668171
title: Juneau Alaska Invasive Plant Control Sites (2020-2022)

description: This dataset provides the location of invasive plant sites where herbicide was used to control reed canarygrass, Bohemian knotweed, European mountain ash, and European bird cherry that threaten salmon and steelhead habitat in the City and Borough of Juneau, Alaska (2020-2022).
DOI: 10.57760/sciencedb.o00009.00005
title: Dataset Test
title: 尊敬的用户，您好！您提交的数据集现在可以公开发布了吗? 数据集正式发布同时会进行数据集DOI的注册。如果您选择暂不发布，请您在需要发布的时候及时告知我们。请回信至：nssdc_service@nssc.ac.cn

description: What methods are used to generate data sets, processing methods, steps, and specific content introduction, etc
description: 数据集通过什么样的方法产生、处理方法、步骤，具体内容介绍等
DOI: 10.5281/zenodo.4009368
title: Vesuvius deformation modeling, Comsol numerical model code

description: The java file represenst a set of coherent procedures that allow a multiparametric analysis in the computing environment of the commercial package Comsol. The files .txt and .dat are files needed by the code to run the model. They represents the data related to our model.