cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25625/divfkp/3o6og7
title: significant_subgraph_mining.py

description: Main implementation of significant subgraph mining.
DOI: 10.25625/divfkp/icy5nk
title: network_samples_asd.pkl

description: Inferred transfer entropy networks in the autism spectrum group.
DOI: 10.25625/divfkp/aaeznd
title: effect_size_power_WY.pkl

description: Results of the detailed empirical power analysis for the n=60 case using the Westfall-Young correction. This file is used in the empirical_power_analysis_n60_detailed.py script to load the results instead of calculating them (which may take several hours).
DOI: 10.25625/divfkp/iet6da
title: empirical_power_analysis_joint_dist_sim_n_60_WY.pkl

description: Results of the empirical power analysis of the MEG data set. For each of the 400 simulations in the n=60 case the file contains all detected subgraphs using the Westfall-Young correction.
DOI: 10.25625/divfkp/hdxvtn
title: ssm_power_analysis_erdos_renyi.py

description: Coder underlying the power simulation based on Erdos-Renyi networks.
DOI: 10.25625/divfkp/euu9yz
title: subgraph_mining_empirical_power_analysis_joint_dist.py

description: Code underlying the empirical power analysis of the MEG data set based on resampling from the empirical joint distribution.
DOI: 10.25625/divfkp/qstarz
title: effect_size_power_tarone.pkl

description: Results of the detailed empirical power analysis for the n=60 case using the Tarone correction. This file is used in the empirical_power_analysis_n60_detailed.py script to load the results instead of calculating them (which may take roughly one hour).
DOI: 10.25625/divfkp/3gx2j5
title: subgraph_mining_empirical_power_analysis_independent_links.py

description: Code underlying the empirical power analysis of the MEG data set assuming independent sampling of links.
DOI: 10.25625/divfkp/76clvu
title: network_samples_cont.pkl

description: Inferred transfer entropy networks for the control group.
DOI: 10.25625/divfkp/cllel2
title: empirical_power_analysis_n60_detailed.py

description: Code underlying the detailed empirical power analysis of the n=60 case. Calculates the empirical detection for each subgraph in the original data set that occurs with different frequencies in the two groups.
DOI: 10.25625/divfkp/4gwe3j
title: WY_standard_errors.pkl

description: Standard errors of the estimator of the average detection probability of subgraphs with a given effect size in the MEG data set (using Westfall-Young correction). Can be loaded in the empirical_power_analysis_n60_detailed.py script.
DOI: 10.25625/divfkp/e8cjm9
title: tarone_standard_errors.pkl

description: Standard errors of the estimator of the average detection probability of subgraphs with a given effect size in the MEG data set (using Tarone correction). Can be loaded in the empirical_power_analysis_n60_detailed.py script.
DOI: 10.25625/divfkp
title: Replication Data and Code for: Significant Subgraph Mining for Neural Network Inference with Multiple Comparisons Correction

description: Contains data and code underlying results presented in Gutknecht, Aaron J.; Wibral, M. (2021): "Significant Subgraph Mining for Neural Network Inference with Multiple Comparisons Correction".
DOI: 10.25721/r8q3-gw10
title: Adieu foulard, adieu madras
DOI: 10.25721/8hkt-q557
title: A la jolie menotte
DOI: 10.5517/ccdc.csd.cc27p919
title: CCDC 2076040: Experimental Crystal Structure Determination

description: Related Article: Xin Zhang, Linqing Qin, Xingzheng Liu, Caixia Zhang, Jianwei Yu, Zuo Xiao, Nan Zheng, Boxuan Wang, Yanan Wei, Zengqi Xie, Yishi Wu, Zhixiang Wei, Kai Wang, Feng Gao, Liming Ding, Hui Huang|2021|Solar RRL|5|2100522|doi:10.1002/solr.202100522
DOI: 10.5281/zenodo.5592276
title: Dataset of "Atomic-level description of thermal fluctuations in inorganic lead halide perovskites" publication

description: The "Zenodo_27-09-2021.zip" file contains a "files" folder and a jupyter notebook to plot the figures reported in the publication. The "files" folder contains several subfolders with the txt files required to plot the figures. The "XAS_simulations.zip" file contains a README.txt and few subfolders with input and output files needed to reproduce the XAS simulations. The README.txt explains the structure of the archive and the content of each subfolders.
DOI: 10.6084/m9.figshare.15019593
title: Madzivanzira et al. 2021 Fish and Macrophytes consumption.xlsx

description: This data supports laboratory experiments to determine potential ecological and socioeconomic impacts conferred by the crayfish species: <i>Cherax quadricarinatus</i> and <i>Procambarus clarkii</i> relative to a functionally similar native analogue, the river crab <i>Potamonautes perlatus</i>, on two static but different resources. The data contains the individual consumption rates of macrophyte and scavenging rates on fish by the three decapods. The data also contains the morphometric measurements of crayfish and crabs used for the experiments.
DOI: 10.6084/m9.figshare.15019593.v2
title: Madzivanzira et al. 2021 Fish and Macrophytes consumption.xlsx

description: This data supports laboratory experiments to determine potential ecological and socioeconomic impacts conferred by the crayfish species: <i>Cherax quadricarinatus</i> and <i>Procambarus clarkii</i> relative to a functionally similar native analogue, the river crab <i>Potamonautes perlatus</i>, on two static but different resources. The data contains the individual consumption rates of macrophyte and scavenging rates on fish by the three decapods. The data also contains the morphometric measurements of crayfish and crabs used for the experiments.
DOI: 10.25721/werm-rb98
title: Seigneur notre monde t'attend
DOI: 10.25721/1dd9-nm45
title: Messe de minuit. Sonnerie des cloches annonçant la messe
DOI: 10.6084/m9.figshare.16858096.v1
title: Test Malthes data.xlsx

description: Test
DOI: 10.6084/m9.figshare.16858096
title: Test Malthes data.xlsx

description: Test
DOI: 10.34740/kaggle/dsv/2730669
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.25721/j9fe-4045
title: Chante noël
DOI: 10.34740/kaggle/dsv/2730690
title: 2021 World Population (updated daily)
DOI: 10.6084/m9.figshare.16641073
title: The utilization of new products formulated from water coconut, palm sup sugar, and fungus to increase nutritional feed quality, feed efficiency, growth, and carcass of gurami sago (Osphronemus goramy Lacepède, 1801) juvenile

description: The utilization of new products formulated from water coconut, palm sup sugar, and fungus to increase nutritional feed quality, feed efficiency, growth, and carcass of gurami sago (Osphronemus goramy Lacepède, 1801) juvenile
DOI: 10.6084/m9.figshare.16641073.v2
title: The utilization of new products formulated from water coconut, palm sup sugar, and fungus to increase nutritional feed quality, feed efficiency, growth, and carcass of gurami sago (Osphronemus goramy Lacepède, 1801) juvenile

description: The utilization of new products formulated from water coconut, palm sup sugar, and fungus to increase nutritional feed quality, feed efficiency, growth, and carcass of gurami sago (Osphronemus goramy Lacepède, 1801) juvenile
DOI: 10.6084/m9.figshare.16641073.v1
title: The utilization of new products formulated from water coconut, palm sup sugar, and fungus to increase nutritional feed quality, feed efficiency, growth, and carcass of gurami sago (Osphronemus goramy Lacepède, 1801) juvenile

description: The utilization of new products formulated from water coconut, palm sup sugar, and fungus to increase nutritional feed quality, feed efficiency, growth, and carcass of gurami sago (Osphronemus goramy Lacepède, 1801) juvenile
DOI: 10.5281/zenodo.5592337
title: Epizoanthus scotinus SPAdes preassembly

description: .
DOI: 10.5281/zenodo.5592336
title: Epizoanthus scotinus SPAdes preassembly

description: .
DOI: 10.6084/m9.figshare.16859593
title: water body extraction

description: water body extraction from different spatial resolution remote sensing images
DOI: 10.25345/c5s270
title: MassIVE MSV000088256 - Quantitative proteomics study on RA+BDNF induced SHSY5Y differentiation
title: A detailed quantitative proteomic study upon neuronal differentiation of SHSY5Y by sequential exposure of RA+BDNF
DOI: 10.25721/6193-t530
title: Nuit de noël, nuit de lumière
DOI: 10.6084/m9.figshare.16859701
title: mask.nii.gz

description: brain data
DOI: 10.6084/m9.figshare.16859701.v1
title: mask.nii.gz

description: brain data
DOI: 10.25721/svzw-8885
title: Merci Seigneur, merci
DOI: 10.18112/openneuro.ds003848.v1.0.0
title: Dataset Clinical Epilepsy iEEG to BIDS - RESPect_longterm_iEEG
DOI: 10.25721/cxjk-hb48
title: Messe de minuit. Thème de l'hymne à la joie
DOI: 10.25721/0bqx-jf06
title: Allez crier, crier, crier sur la montagne
DOI: 10.6084/m9.figshare.16859731
title: Ren Energy IRENA (2021).xlsx

description: Installed capacity for different renewable energy sources 2021 (Source: IRENA)<br>
DOI: 10.6084/m9.figshare.16859731.v1
title: Ren Energy IRENA (2021).xlsx

description: Installed capacity for different renewable energy sources 2021 (Source: IRENA)<br>
DOI: 10.6084/m9.figshare.16843630
title: Data

description: (1) There are 6 sets of data, namely: service facilities, community polygon, population, three sets of OD matrices. (2) The specific description information of each data is in the corresponding compressed package.<br>
DOI: 10.6084/m9.figshare.16843630.v1
title: Data

description: (1) There are 6 sets of data, namely: service facilities, community polygon, population, three sets of OD matrices. (2) The specific description information of each data is in the corresponding compressed package.<br>
DOI: 10.6084/m9.figshare.16859734
title: reoriented.nii.gz

description: brain
DOI: 10.6084/m9.figshare.16843207
title: Data_Real OD MatrixData

description: (1) The dataset is the real OD travel matrix from communities to tertiary hospitals created according to the Didi travel trajectory data in Chengdu city. (2) The dataset is ArcGIS file, shapefile format.
DOI: 10.6084/m9.figshare.16843207.v1
title: Data_Real OD Matrix

description: (1) The dataset is the real OD travel matrix from communities to tertiary hospitals created according to the Didi travel trajectory data in Chengdu city. (2) The dataset is ArcGIS file, shapefile format.
DOI: 10.6084/m9.figshare.16843201
title: Data_Potential OD MatrixData

description: Data_Potential OD MatrixData
DOI: 10.6084/m9.figshare.16843201.v1
title: Data_Potential OD Matrix

description: (1) The dataset is the potential OD travel matrix from all communities to tertiary hospitals in Chengdu city. (2) The dataset is ArcGIS file, shapefile format.
DOI: 10.6084/m9.figshare.16843198
title: Data_PopulationData

description: Data_PopulationData<br><br>
DOI: 10.6084/m9.figshare.16843198.v2
title: Data_PopulationData

description: Data_PopulationData<br><br>
DOI: 10.6084/m9.figshare.16843198.v1
title: Data_Population

description: (1) The dataset is point of community committees in Chengdu city, which contain the population of each community. (2) The dataset is ArcGIS file, shapefile format.<br><br>
DOI: 10.6084/m9.figshare.16843189
title: Data_FacilityData

description: The dataset is point of tertiary hosipital of chengdu, which is ArcGIS file, shp format.
DOI: 10.6084/m9.figshare.16843189.v2
title: Data_FacilityData

description: The dataset is point of tertiary hosipital of chengdu, which is ArcGIS file, shp format.
DOI: 10.6084/m9.figshare.16843189.v1
title: Data_Facility

description: The dataset is point of tertiary hosipital of chengdu, which is ArcGIS file, shp format.
DOI: 10.6084/m9.figshare.16843153
title: Data_Commnunity PolygonData

description: Data_Commnunity PolygonData<br><br>
DOI: 10.6084/m9.figshare.16843153.v1
title: Data_Commnunity Polygon

description: (1) The dataset is community polygon of chengdu city, and the polygon is the Thiessen polygon (Voronoi diagram) generated based on the point of community committee and used to replace administrative divisions as the basic research unit.(2) The dataset is ArcGIS file, shp format.<br>
DOI: 10.25721/ze84-mr55
title: Minuit Chrétien
DOI: 10.25721/8hk6-c682
title: Seigneur prends pitié
DOI: 10.5281/zenodo.5579070
title: Collision-induced dissociation of protonated uracil water clusters probed by molecular dynamics simulations

description: This dataset contains the input and output files associated to the work of "Collision-induced dissociation of protonated uracil water clusters probed by molecular dynamics simulations"
DOI: 10.5281/zenodo.5579069
title: Collision-induced dissociation of protonated uracil water clusters probed by molecular dynamics simulations

description: This dataset contains the input and output files associated to the work of "Collision-induced dissociation of protonated uracil water clusters probed by molecular dynamics simulations"
DOI: 10.6084/m9.figshare.12622769
title: Tighten the Bolts and Nuts on GPP Estimations from Sites to the Globe: An Assessment of Remote Sensing Based LUE Models and Supporting Data Fields

description: This dataset provides monthly global gross primary production (GPP) product at 10km resoluution from 2000 to 2018.Model description:This model was developed mainly based on the principles of the EC-LUE model. Specifically, the regulation of water on GPP is represented by the normalized differential vegetation index (NDWI). The NDWI, strongly related to vegetation water content and the data is easily access, can be a very good proxy for vegetation water stress. In addition, two new modifiers of GPP were added to the original EC-LUE model. The first modifier considers the impact of cloudiness on GPP. The other modifier addresses the fertilization effect of increased CO<sub>2</sub> concentration in the atmosphere. Dataset information:Each .zip file contains 12 files for 12 months. The last number starts at 0, that is, 0 is January and 11 is December.Data format: tifSpatial extent: globalUnit: g C m<sup>-2</sup> day<sup>-1</sup>Any questions about the GPP dataset can be corresponded to: Author: zhaowang1003@gmail.com (Zhao Wang). Corresponding author: shuguang.liu@yahoo.com (Shuguang Liu).
DOI: 10.6084/m9.figshare.12622769.v1
title: Tighten the bolts and nuts on GPP estimations from sites to the globe: an assessment of LUE models and supporting data fields

description: This dataset provides monthly global gross primary production (GPP) product at 10km resoluution from 2000 to 2018.Model description:This model was developed mainly based on the principles of the EC-LUE model. Specifically, the regulation of water on GPP is represented by the normalized differential vegetation index (NDWI). The NDWI, strongly related to vegetation water content and the data is easily access, can be a very good proxy for vegetation water stress. In addition, two new modifiers of GPP were added to the original EC-LUE model. The first modifier considers the impact of cloudiness on GPP. The other modifier addresses the fertilization effect of increased CO<sub>2</sub> concentration in the atmosphere. Dataset information:Each .zip file contains 12 files for 12 months. The last number starts at 0, that is, 0 is January and 11 is December.Data format: tifSpatial extent: globalUnit: g C m<sup>-2</sup> day<sup>-1</sup>Any questions about the GPP dataset can be corresponded to: Author: zhaowang1003@gmail.com (Zhao Wang). Corresponding author: shuguang.li@yahoo.com (Shuguang Liu).
DOI: 10.15129/aed4b3a0-e90e-4030-b15c-8e2e140600f5
title: A 2010 Spanish IO : energy technical coefficients

description: This data represents the matrix of technical coefficients of the Spanish Input-Output Framework (symmetric IOFA-10), where renewable energies have been developed. Specifically, the energy sector is disaggregated at a detailed subsector level, including four energy accounts: coal, petroleum, gas, and non-renewable electricity, and ﬁve branches of renewable energy: wind, hydroelectric, solar, biomass, and biofuels. In the technical coefficients matrix, rows describe the production function of sectors, showing the share of inputs of the different sectors needed per unit of production in each sector. This matrix is a representation of the production structure for the whole production system in 2010, and represents the baseline for the calibration of the computable general equilibrium (CGE) model and the design of scenarios.
DOI: 10.25721/dgfj-6z23
title: Un sauveur nous est né à Bethléem en Judée
DOI: 10.25721/g7z1-fp74
title: Gloire à Dieu au plus haut des Cieux
DOI: 10.6084/m9.figshare.14558181
title: Streaming Dataset

description: Streaming.mat contains the continuous data from each trial.
DOI: 10.6084/m9.figshare.14125814
title: README

description: README file describing dataset
DOI: 10.6084/m9.figshare.14558184
title: Normalized Dataset

description: Normalized.mat contains the data parsed and normalized by stride.
DOI: 10.5517/ccdc.csd.cc285zn3
title: CCDC 2091125: Experimental Crystal Structure Determination

description: Related Article: Debashis Basu, Danielle L. Gray, Toby J. Woods, Thomas B. Rauchfuss, Federica Arrigoni, Giuseppe Zampella|2021|Organometallics|40|3306|doi:10.1021/acs.organomet.1c00412
DOI: 10.5517/ccdc.csd.cc285zp4
title: CCDC 2091126: Experimental Crystal Structure Determination

description: Related Article: Debashis Basu, Danielle L. Gray, Toby J. Woods, Thomas B. Rauchfuss, Federica Arrigoni, Giuseppe Zampella|2021|Organometallics|40|3306|doi:10.1021/acs.organomet.1c00412
DOI: 10.5517/ccdc.csd.cc2883m9
title: CCDC 2093170: Experimental Crystal Structure Determination

description: Related Article: Caleb D. Fast, Nathan D. Schley|2021|Organometallics|40|3291|doi:10.1021/acs.organomet.1c00391
DOI: 10.5517/ccdc.csd.cc289dff
title: CCDC 2094404: Experimental Crystal Structure Determination

description: Related Article: Masanori Shigeno, Masaya Imamatsu, Yusuke Kai, Moe Kiriyama, Shintaro Ishida, Kanako Nozawa-Kumada, Yoshinori Kondo|2021|Org.Lett.|23|8023|doi:10.1021/acs.orglett.1c03033
DOI: 10.5517/ccdc.csd.cc289djj
title: CCDC 2094407: Experimental Crystal Structure Determination

description: Related Article: Masanori Shigeno, Masaya Imamatsu, Yusuke Kai, Moe Kiriyama, Shintaro Ishida, Kanako Nozawa-Kumada, Yoshinori Kondo|2021|Org.Lett.|23|8023|doi:10.1021/acs.orglett.1c03033
DOI: 10.5517/ccdc.csd.cc28j3kh
title: CCDC 2100856: Experimental Crystal Structure Determination

description: Related Article: Sadig Aghazada, Dominik Munz, Frank W. Heinemann, Andreas Scheurer, Karsten Meyer|2021|J.Am.Chem.Soc.|143|17219|doi:10.1021/jacs.1c08202
DOI: 10.5517/ccdc.csd.cc28j3lj
title: CCDC 2100857: Experimental Crystal Structure Determination

description: Related Article: Sadig Aghazada, Dominik Munz, Frank W. Heinemann, Andreas Scheurer, Karsten Meyer|2021|J.Am.Chem.Soc.|143|17219|doi:10.1021/jacs.1c08202
DOI: 10.6084/m9.figshare.16847521
title: Amigo2_2019-07-11_11-57-07

description: Electrophysiology recordings<br>
DOI: 10.6084/m9.figshare.16847521.v1
title: Amigo2_2019-07-11_11-57-07

description: Electrophysiology recordings<br>
DOI: 10.34740/kaggle/dsv/2730814
title: COVID Vaccination in World (updated daily)
DOI: 10.25721/xve9-rt97
title: Alleluia alleluia la lumière s'est levée
DOI: 10.5281/zenodo.5575627
title: SWOT-like WSE for 38 large lakes (&gt; 150 square km) in the QTP

description: This dataset includes the SWOT Simulator output for the 38 large lakes (&gt; 150 km2) between 2005 and 2015 on thr QTP.
DOI: 10.5281/zenodo.5575626
title: SWOT-like WSE for 38 large lakes (&gt; 150 square km) in the QTP

description: This dataset includes the SWOT Simulator output for the 38 large lakes (&gt; 150 km2) between 2005 and 2015 on thr QTP.
DOI: 10.21227/r5mv-ax79
title: Exoskeleton Twitter Dataset: A Comprehensive Dataset of Tweets Related to Exoskeletons

description: Any work using this dataset should cite the following paper:Nirmalya Thakur and Chia Y. Han, "Exoskeleton Twitter Dataset: A Dataset of Tweets related to Exoskeletons and 100 Research Questions", Journal of Data (In Press)AbstractThe exoskeleton technology has been rapidly advancing in the recent past due to its multitude of applications and use cases in assisted living, military, healthcare, firefighting, and industries. With the projected increase in the diverse uses of exoskeletons in the next few years in these application domains and beyond, it is crucial to study, interpret, and analyze user perspectives, public opinion, reviews, and feedback related to exoskeletons, for which a dataset is necessary. The Internet of Everything era of today's living, characterized by people spending more time on the Internet than ever before, holds the potential for developing such a dataset by the mining of relevant web behavior data from social media communications, which have increased exponentially in the last few years. Twitter, one such social media platform, is highly popular amongst all age groups, who communicate on diverse topics including but not limited to news, current events, politics, emerging technologies, family, relationships, and career opportunities, via tweets, while sharing their views, opinions, perspectives, and feedback towards the same. Therefore, this work presents a dataset of approximately 20,000 tweets related to exoskeletons. that were mined for a period of 231 days, from December 1, 2020, to July 19, 2021. The tweets contain diverse forms of communications and conversations related to exoskeletons which communicate user interests, user perspectives, public opinion, reviews, feedback, suggestions, etc., related to exoskeletons.The above-mentioned paper is a Data Descriptor which provides the description of the dataset as well as the details about the methodology that was used for mining the Big Data available in this dataset. Furthermore, based on an exploratory review of 108 emerging works in this field and its interrelated disciplines, the paper also discusses multiple interdisciplinary applications of this dataset in the fields of Big Data, Natural Language Processing, Human-Computer Interaction, Human Factors, Hu-man-Centered Design, Information Retrieval, Artificial Intelligence, Pattern Recognition, and User Experience, and presents 100 research questions for researchers to study, analyze, evaluate, and investigate based on this dataset.For any questions related to the dataset or the associated paper, please contact Nirmalya Thakur at thakurna@mail.uc.edu
DOI: 10.15468/chhg5n
title: A taxonomic assessment of Chlorospingus flavopectus phaeocephalus and Chlorospingus semifuscus (Passeriformes: Passerellidae), including the description of a new subspecies

description: This dataset contains the digitized treatments in Plazi based on the original journal article Sánchez-Nivicela, Manuel, Avendaño, Jorge Enrique, Sánchez-Nivicela, Juan C., Torres, Ana, Fuchs, Jérôme, Bird, Bentley, Bonaccorso, Elisa (2021): A taxonomic assessment of Chlorospingus flavopectus phaeocephalus and Chlorospingus semifuscus (Passeriformes: Passerellidae), including the description of a new subspecies. Zootaxa 5057 (2): 151-180, DOI: https://doi.org/10.11646/zootaxa.5057.2.1
DOI: 10.15468/bbjvhu
title: Pluteus lauracearum (Agaricales, Basidiomycota), a new species of Pluteus sect. Hispidoderma from thermophilic Laurus forests

description: This dataset contains the digitized treatments in Plazi based on the original journal article Kaygusuz, Oğuzhan, Justo, Alfredo, Knudsen, Henning, Ševčíková, Hana, Türkekul, Ibrahim (2021): Pluteus lauracearum (Agaricales, Basidiomycota), a new species of Pluteus sect. Hispidoderma from thermophilic Laurus forests. Phytotaxa 523 (2): 126-140, DOI: 10.11646/phytotaxa.523.2.1
DOI: 10.15482/usda.adc/1523394
title: Data from: Conditions to terminate reproductive diapause of a univoltine insect: Ceratapion basicorne (Coleoptera: Apionidae), a biological control agent of yellow starthistle
DOI: 10.6084/m9.figshare.14960085
title: Thy7_2020-11-11_16-05-00

description: Electrophysiology recording<br>
DOI: 10.25721/6ce9-7j42
title: Seigneur, écoute-nous, alleluia
DOI: 10.25721/n5pv-6h07
title: Bergers et bergères accourez venez tous
DOI: 10.6084/m9.figshare.13547684
title: Archaeological sites in the Department of Loreto, Peruvian Amazon

description: Excel file