cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4011584
title: Anthropometric data

description: In this dataset, body dimensions of students for calculations suitability of school furniture are presented.
DOI: 10.5281/zenodo.4011583
title: Anthropometric data

description: In this dataset, body dimensions of students for calculations suitability of school furniture are presented.
DOI: 10.5281/zenodo.3991751
title: Fall events and ordinal daily activities from a sensored smart floor

description: Data about fall events and ordinal daily activities from a smart floor wired with a matrix of sixteen pressure sensors. The dataset includes: sensor data gathered on a session simulating falls. The data was gathered from a proprietary setting of an array of pressure sensors mounted on a 1.2m x 1.2m floor setting with 15 sensors. The dataset also includes the questionary that each participant filled and source code for a program that collects the data from sensors and manages the data gathering process.
DOI: 10.5281/zenodo.4060298
title: DeepArk variant effect predictions for MPRA of ALDOB enhancer in mouse

description: The individual DeepArk predictions for every possible variant tested by the massively parallel <em>in vivo</em> reporter assay of the <em>ALDOB</em> enhancer in mouse livers from Patwardhan et al. 2012 (DOI:10.1038/nbt.2136). Predictions are provided for all regulatory features modeled in <em>M. musculus</em>. Accession numbers correspond to training data corresponding to an individual output probability from DeepArk.
DOI: 10.5281/zenodo.4060297
title: DeepArk variant effect predictions for MPRA of ALDOB enhancer in mouse

description: The individual DeepArk predictions for every possible variant tested by the massively parallel <em>in vivo</em> reporter assay of the <em>ALDOB</em> enhancer in mouse livers from Patwardhan et al. 2012 (DOI:10.1038/nbt.2136). Predictions are provided for all regulatory features modeled in <em>M. musculus</em>. Accession numbers correspond to training data corresponding to an individual output probability from DeepArk.
DOI: 10.25810/v575-3r57.22
title: Japanese Newspaper Coverage of Climate Change or Global Warming, 2000-2020 - August 2020

description:         The Media and Climate Change Observatory Data monitors 120 sources (across newspapers, radio and TV) in 54 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.6073/pasta/dafd787651f06e15ca8c775e52d877da
title: Effects of frequent fire and mowing on resprouting shrubs of Florida, USA, scrub

description: Background: Resprouting is an effective strategy for persistence of perennial plants after disturbances such as fire. However, can disturbances be so frequent that they limit resprouting? We examined the effects of fire and mowing frequency on eight species of resprouting shrubs (three oaks (Quercus chapmanii, Q. inopina, Q. geminata), three ericaceous species (Lyonia fruticosa, L. lucida, Vaccinium myrsinites), and two palmettos (Sabal etonia, Serenoa repens)) in Florida scrub using a factorial field experiment. We burned or mowed plots at four disturbance return intervals (DRI) – either annually, biennially, every three years, or once in six years (with all plots being treated in the sixth year to control for time-since-disturbance). We analyzed plant growth responses (height, aboveground biomass, number of stems) based on sampling pre-treatment, and six months, one, two, and four years post-treatment. We also measured non-structural carbohydrates (NSC) and soil properties to evaluate these factors as potential drivers of resprouting responses. Results: Fire temperatures were hot (mean maxima 414-698 C among burn days), typical of larger fires in Florida scrub. Plant biomass and heights were affected by DRI (being suppressed by frequent disturbance, especially initially) and varied among species with palmettos recovering biomass faster and species within the same genus generally showing similar responses. Biomass recovery in mown vs. burned treatments showed comparable effects of DRI and similar trajectories over time. Numbers of stems were affected by DRI, disturbance type, and species. Stems increased after disturbances, especially with less frequent disturbances and mowing, and subsequently declined over time. NSC concentrations varied among species and over time and was positively related to biomass. One-year post-disturbance, soil moisture and organic matter content were higher in mown plots, while pH was higher in burned plots. Given the slightly lower elevation of the mown plots, we interpreted these differences as site effects. Soil properties were not affected by DRI and did not affect biomass responses. Conclusions: Although very frequent disturbances reduced shrub growth responses, the magnitude of plant responses was modest and the effects temporary. Because resprouting shrubs in Florida scrub appear resilient to a range of disturbance return intervals, frequent fire or mowing can be effectively used in restorations.
DOI: 10.6084/m9.figshare.12844508
title: Anomaly Detection in High-Dimensional Data

description: The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. In this article, we propose an algorithm that addresses these limitations. We define an anomaly as an observation where its <i>k</i>-nearest neighbor distance with the maximum gap is significantly different from what we would expect if the distribution of <i>k</i>-nearest neighbors with the maximum gap is in the maximum domain of attraction of the Gumbel distribution. An approach based on extreme value theory is used for the anomalous threshold calculation. Using various synthetic and real datasets, we demonstrate the wide applicability and usefulness of our algorithm, which we call the stray algorithm. We also demonstrate how this algorithm can assist in detecting anomalies present in other data structures using feature engineering. We show the situations where the stray algorithm outperforms the HDoutliers algorithm both in accuracy and computational time. This framework is implemented in the open source R package stray. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12844508.v2
title: Anomaly Detection in High-Dimensional Data

description: The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. In this article, we propose an algorithm that addresses these limitations. We define an anomaly as an observation where its <i>k</i>-nearest neighbor distance with the maximum gap is significantly different from what we would expect if the distribution of <i>k</i>-nearest neighbors with the maximum gap is in the maximum domain of attraction of the Gumbel distribution. An approach based on extreme value theory is used for the anomalous threshold calculation. Using various synthetic and real datasets, we demonstrate the wide applicability and usefulness of our algorithm, which we call the stray algorithm. We also demonstrate how this algorithm can assist in detecting anomalies present in other data structures using feature engineering. We show the situations where the stray algorithm outperforms the HDoutliers algorithm both in accuracy and computational time. This framework is implemented in the open source R package stray. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.12844508.v1
title: Anomaly Detection in High Dimensional Data

description: The HDoutliers algorithm is a powerful unsupervised algorithm for detecting anomalies in high-dimensional data, with a strong theoretical foundation. However, it suffers from some limitations that significantly hinder its performance level, under certain circumstances. In this article, we propose an algorithm that addresses these limitations. We define an anomaly as an observation where its k-nearest neighbour distance with the maximum gap is significantly different from what we would expect if the distribution of k-nearest neighbours with the maximum gap is in the maximum domain of attraction of the Gumbel distribution. An approach based on extreme value theory is used for the anomalous threshold calculation. Using various synthetic and real datasets, we demonstrate the wide applicability and usefulness of our algorithm, which we call the stray algorithm. We also demonstrate how this algorithm can assist in detecting anomalies present in other data structures using feature engineering. We show the situations where the stray algorithm outperforms the HDoutliers algorithm both in accuracy and computational time. This framework is implemented in the open source R package stray.
DOI: 10.6084/m9.figshare.13030670
title: MetaData .xlsx

description: test
DOI: 10.6084/m9.figshare.13030670.v1
title: MetaData .xlsx

description: test
DOI: 10.6084/m9.figshare.13030601
title: DATA and METADATA for Rajpreet Dhanoas Pilot Experiment

description: The data was collected over a 3 day period ranging from 3 different locations as well. The metadata is implemented to describe the data provided as well as give an informative backing for the analyzers.
DOI: 10.6084/m9.figshare.13030601.v2
title: DATA and METADATA for Rajpreet Dhanoas Pilot Experiment

description: The data was collected over a 3 day period ranging from 3 different locations as well. The metadata is implemented to describe the data provided as well as give an informative backing for the analyzers.
DOI: 10.6084/m9.figshare.13030601.v1
title: DATA and METADATA for Rajpreet Dhanoas Pilot Experiment

description: The data was collected over a 3 day period ranging from 3 different locations as well. The metadata is implemented to describe the data provided as well as give an informative backing for the analyzers.
DOI: 10.5281/zenodo.4060287
title: Data for: Physics-based Reconstruction Methods for Magnetic Resonance Imaging

description: Magnetic Resonance Imaging measurement data used in our paper about 'Physics-based Reconstruction Methods for Magnetic Resonance Imaging'
DOI: 10.6084/m9.figshare.13030442
title: JULES-Sheffield 1948-2010

description: July-August monthly soil moisture data derived from JULES-Sheffield simulation in inner East Asia over 1948-2010<br>
DOI: 10.6084/m9.figshare.13030442.v1
title: JULES-Sheffield 1948-2010

description: July-August monthly soil moisture data derived from JULES-Sheffield simulation in inner East Asia over 1948-2010<br>
DOI: 10.5281/zenodo.4060329
title: Cosby_et_al_2020_Supplemental_Data

description: Supplemental Data S1-S6 for Cosby, et al. 2020, titled: <em>Recurrent evolution of vertebrate transcription factors by transposase capture.</em>
description: This work was supported by R35GM122550, from the National Institutes of Health to Cedric Feschotte. Julius Judd was supported by NHGRI fellowship F31HG010820.
DOI: 10.5281/zenodo.4060328
title: Cosby_et_al_2020_Supplemental_Data

description: Supplemental Data S1-S6 for Cosby, et al. 2020, titled: <em>Recurrent evolution of vertebrate transcription factors by transposase capture.</em>
description: This work was supported by R35GM122550, from the National Institutes of Health to Cedric Feschotte. Julius Judd was supported by NHGRI fellowship F31HG010820.
DOI: 10.6084/m9.figshare.13030535
title: Cell distribution after characterization with stainings for 5 days

description: Cell distribution after characterization with stainings for 5 days. stacked bar graph illustrating cell fraction composition per day over the five-day period. ANOVA by live cells (<b>LC</b>) increased while the levels of the autophagy process decreased (<b>AG</b>) significantly.
DOI: 10.6084/m9.figshare.13030535.v1
title: Cell distribution after characterization with stainings for 5 days

description: Cell distribution after characterization with stainings for 5 days. stacked bar graph illustrating cell fraction composition per day over the five-day period. ANOVA by live cells (<b>LC</b>) increased while the levels of the autophagy process decreased (<b>AG</b>) significantly.
DOI: 10.17632/rwmfhxnmbd.1
title: Data for: Hydrogen Cyanide and Mycotoxins: Their Incidence and Dietary Exposure from Cassava Products in Anyigba, Nigeria

description: Data on Hydrogen cyanide and Mycotoxin contaminating cassava products in Anyigba, Nigeria
DOI: 10.6084/m9.figshare.13030307
title: R0235_20181026a_videos

description: Rat 0235, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.6084/m9.figshare.13030307.v1
title: R0235_20181026a_videos

description: Rat 0235, skilled reaching data collected in Leventhal laboratory by Alexandra Bova
DOI: 10.5281/zenodo.4060319
title: Ionic and water stable isotope composition of different Mendoza River basin (Argentina) water sources

description: Samples obtained in a high temporal resolution from different water sources of the upper Mendoza River basin (Argentinean Central Andes). Ionic and water stable isotopes compositions are expressed and electric conductivity, pH and mean catchments altitudes. Decimal positions are expressed with comma.
description: The analysis of this data can be found at: Sebastián A. Crespo, Francisco Fernandoy, Leandro Cara, Sebastián Klarian & Céline Lavergne (2020) First snow, glacier and groundwater contribution quantification in the upper Mendoza River basin using stable water isotopes, Isotopes in Environmental and Health Studies, DOI: 10.1080/10256016.2020.1797713
DOI: 10.5281/zenodo.4060318
title: Ionic and water stable isotope composition of different Mendoza River basin (Argentina) water sources

description: Samples obtained in a high temporal resolution from different water sources of the upper Mendoza River basin (Argentinean Central Andes). Ionic and water stable isotopes compositions are expressed and electric conductivity, pH and mean catchments altitudes. Decimal positions are expressed with comma.
description: The analysis of this data can be found at: Sebastián A. Crespo, Francisco Fernandoy, Leandro Cara, Sebastián Klarian & Céline Lavergne (2020) First snow, glacier and groundwater contribution quantification in the upper Mendoza River basin using stable water isotopes, Isotopes in Environmental and Health Studies, DOI: 10.1080/10256016.2020.1797713
DOI: 10.5517/ccdc.csd.cc235hrk
title: CCDC 1941708: Experimental Crystal Structure Determination

description: Related Article: Kai Xiong, Chen Qian, Yixian Yuan, Lin Wei, Xinxing Liao, Liting He, Thomas W. Rees, Yu Chen, Jian Wan, Liangnian Ji, Hui Chao|2020|Angew.Chem.,Int.Ed.|59|16631|doi:10.1002/anie.202006089
DOI: 10.21223/wx2hit/cxqouh
title: PTYield082019_CIPHYO_exp1.tab

description: :unav
DOI: 10.21223/wx2hit/1rwx0m
title: PTYield062019_CIPSRM-2_exp1.tab

description: :unav
DOI: 10.21223/wx2hit/uibbuj
title: PTYield062019_HUAMACHUCO_exp1.tab

description: :unav
DOI: 10.21223/wx2hit/mrrb73
title: PTYield062019_HUANUCO_exp1.tab

description: :unav
DOI: 10.6084/m9.figshare.13030895
title: pilot experiment Data set and Meta-data

description: this file is a combination of a pilot experiment data set and meta-data.
DOI: 10.6084/m9.figshare.13030895.v1
title: pilot experiment Data set and Meta-data

description: this file is a combination of a pilot experiment data set and meta-data.
DOI: 10.6084/m9.figshare.13030931
title: Supplementary Material - SMS on Chitosan Delivery System

description: Supplementary material of the following article: THE DEVELOPMENT PROGRESSING OF THE INSULIN DELIVERY SYSTEMS BASED ON CHITOSAN: A SYSTEMATIC LITERATURE REVIEW
DOI: 10.6084/m9.figshare.13030931.v1
title: Supplementary Material - SMS on Chitosan Delivery System

description: Supplementary material of the following article: THE DEVELOPMENT PROGRESSING OF THE INSULIN DELIVERY SYSTEMS BASED ON CHITOSAN: A SYSTEMATIC LITERATURE REVIEW
DOI: 10.5281/zenodo.4060378
title: Pakistan Journal of Surgery and Medicine Citation Record

description: Pak J Surg Med Citation Report Upto 30-09-2020
description: all communications may please be directed to editor@pjsm.com.pk
DOI: 10.6084/m9.figshare.13030241.v1
title: Data with meta-data

description: This a rearranged dataset of bird species and their related amount and activities recorded.
DOI: 10.5281/zenodo.4060382
title: DR.

description: This is an ensemble precipitation forecasts dataset (May 21-22, 2018) from four topography perturbation experiments based on 3km WRF model as well as the corresponding verifying precipitation analysis for a JGR-Atmospheric manuscript.
DOI: 10.5281/zenodo.4060381
title: DR.

description: This is an ensemble precipitation forecasts dataset (May 21-22, 2018) from four topography perturbation experiments based on 3km WRF model as well as the corresponding verifying precipitation analysis for a JGR-Atmospheric manuscript.
DOI: 10.17632/98byx9whv5.1
title: Data for: Measuring human wellbeing: a protocol for selecting local indicators

description: Individual wellbeing data collected from two study villages in Tanzania to test the wellbeing indicator selection protocol (WISP)
DOI: 10.5281/zenodo.4060385
title: VIR MAXIMUS Catalogue

description: This database is the second, upgraded version of the WP1 (Catalogue) under the project “VIR MAXIMUS: Tracking the transfer of moral-political ideas through the reception of B. Gracián’s texts (XVII-XXI cent.)”. The Catalogue contains the biobibliographical data on all the existent translations of the work of Baltasar Gracián, under the form of: 1) general dataset (.ods file), 2) zipped separate fiches (.odt files).
DOI: 10.5281/zenodo.4008174
title: VIR MAXIMUS Catalogue

description: This database is the second, upgraded version of the WP1 (Catalogue) under the project “VIR MAXIMUS: Tracking the transfer of moral-political ideas through the reception of B. Gracián’s texts (XVII-XXI cent.)”. The Catalogue contains the biobibliographical data on all the existent translations of the work of Baltasar Gracián, under the form of: 1) general dataset (.ods file), 2) zipped separate fiches (.odt files).
DOI: 10.5281/zenodo.4060388
title: Convolutional Neural Net (CNN) models for ENCODE-Roadmap DNase-seq peaks and Transcription Factor ChIP-seq peaks - Basset architecture

description: Deep learning models trained on epigenomic landscapes from ENCODE and Roadmap Epigenomics. The models are Basset convolutional neural networks (Kelley, et al 2016). The dataset used to train these models can be found at https://doi.org/10.5281/zenodo.4059038. The file `nn.encode-roadmap.models.basset.clf.tar.gz` contains 10 cross-validated models in Tensorflow framework files as well as details on the architecture, cross-validation scheme, and training of these models. The file `nn.encode-roadmap.models.basset.clf.np_weights.tar.gz` contains the 10 cross-validated models' weights extracted to numpy array files (.npz).
DOI: 10.5281/zenodo.4059060
title: Convolutional Neural Net (CNN) models for ENCODE-Roadmap DNase-seq peaks and Transcription Factor ChIP-seq peaks - Basset architecture

description: Deep learning models trained on epigenomic landscapes from ENCODE and Roadmap Epigenomics. The models are Basset convolutional neural networks (Kelley, et al 2016). The dataset used to train these models can be found at https://doi.org/10.5281/zenodo.4059038. The file `nn.encode-roadmap.models.basset.clf.tar.gz` contains 10 cross-validated models in Tensorflow framework files as well as details on the architecture, cross-validation scheme, and training of these models. The file `nn.encode-roadmap.models.basset.clf.np_weights.tar.gz` contains the 10 cross-validated models' weights extracted to numpy array files (.npz).
DOI: 10.5281/zenodo.4059039
title: Classification dataset for ENCODE-Roadmap DNase-seq peaks and Transcription Factor ChIP-seq peaks

description: Classification dataset for machine learning on epigenomic landscapes from ENCODE and Roadmap Epigenomics. The dataset includes the original peak files (BED format) for the DNase-seq and transcription factor (TF) ChIP-seq experiments that were used to label genomic regions as positives or negatives. The DNase-seq peak files along with processing details are in the file "encode-roadmap.DNase-seq.peaks.tar.gz". The TF ChIP-seq peak files along with processing details are in the file "encode.ChIP-seq.peaks.tar.gz". The processed dataset stored in hdf5 format files along with processing details are in the file "nn.encode-roadmap.hdf5_files.tar.gz".
DOI: 10.5281/zenodo.4059038
title: Classification dataset for ENCODE-Roadmap DNase-seq peaks and Transcription Factor ChIP-seq peaks

description: Classification dataset for machine learning on epigenomic landscapes from ENCODE and Roadmap Epigenomics. The dataset includes the original peak files (BED format) for the DNase-seq and transcription factor (TF) ChIP-seq experiments that were used to label genomic regions as positives or negatives. The DNase-seq peak files along with processing details are in the file "encode-roadmap.DNase-seq.peaks.tar.gz". The TF ChIP-seq peak files along with processing details are in the file "encode.ChIP-seq.peaks.tar.gz". The processed dataset stored in hdf5 format files along with processing details are in the file "nn.encode-roadmap.hdf5_files.tar.gz".
DOI: 10.3886/e123061
title: Classroom Age Composition and Preschoolers’ School Readiness

description: This provides instructions for accessing data and running all preparation and analyses to replicate findings in the AERA Open article, Classroom Age Composition and Preschoolers’ School Readiness: The Implications of Classroom Quality and Teacher Qualifications.
DOI: 10.3886/e123061v1
title: Classroom Age Composition and Preschoolers’ School Readiness

description: This provides instructions for accessing data and running all preparation and analyses to replicate findings in the AERA Open article, Classroom Age Composition and Preschoolers’ School Readiness: The Implications of Classroom Quality and Teacher Qualifications.
DOI: 10.3886/e113706v1-45420
title: Replication data for: The Effect of Pollution on Worker Productivity: Evidence from Call Center Workers in China

description: We investigate the effect of pollution on worker productivity in the service sector by focusing on two call centers in China. Using precise measures of each worker's daily output linked to daily measures of pollution and meteorology, we find that higher levels of air pollution decrease worker productivity. These results manifest themselves at levels of pollution commonly found in large cities throughout the developing and developed world.
DOI: 10.6084/m9.figshare.13010012
title: meta data analsysis .docx

description: The following data represents a pilot study which consisted of observing bird’s behaviour for 20 minutes at 5 different sites located in Mississauga Ontario, Canada (Heartland, Streetsville Memorial park, Jack Darling, Credit View Wetland, and area around my house) in the span of 6 days (September 17,2020 to September 23, 2020). Most of the observations were conducted in the morning between 7 am – 10 am except for the two-observation site’s (Mandolin place and Streets Ville Memorial Park) which was conducted at 3 pm. The species were identified using the Merlin Bird ID App with an Iphone 11 camara.<br>