cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/msh2-wz06
title: Decomposition-Residuals Neural Networks: Hybrid system identification applied to electricity forecasting

description: COVID-19 causes issues in energy demand profile forecasting. Day-ahead energy forecasting systems struggle to provide accurate demand predictions. Decomposition-Residuals Deep Neural Networks (DR-DNN) is a two-layer hybrid architecture with: a decomposition and a nonlinear layer. Based on statistical tests, the decomposition layer applies robust signal decomposition and low-order system identification of input data streams into: trend, seasonal and residuals signals. Utilizing calendar information, temporal signals are added: sinusoidal day/night cycles, weekend/weekday, etc. The nonlinear layer can learn unknown nonlinear patterns using typical DNN models like Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN). DR-DNN outperformed baseline, linear, and plain DNN models on next-day electricity forecasts within the COVID-19 era (September 2020-January 2021).
DOI: 10.6084/m9.figshare.14340200
title: SUPPLEMENTAL INFORMATION.xlsx

description: Table.S1-S8
DOI: 10.6084/m9.figshare.14340200.v1
title: SUPPLEMENTAL INFORMATION.xlsx

description: Table.S1-S8
DOI: 10.15468/j36e4u
title: Revision of Eccoptolonthus Bernhauer (Coleoptera: Staphylininae: Philonthina) with descriptions of four new species from China

description: This dataset contains the digitized treatments in Plazi based on the original journal article Fei, Xu-Dong, Zhou, Hong-Zhang (2021): Revision of Eccoptolonthus Bernhauer (Coleoptera: Staphylininae: Philonthina) with descriptions of four new species from China. Zootaxa 4949 (3): 473-498, DOI: https://doi.org/10.11646/zootaxa.4949.3.3
DOI: 10.5281/zenodo.4647821
title: CICE gx3 Grid and Initial Condition Data - 2021-03-19

description: New initial states for gx3 with monthly initial files.
DOI: 10.5281/zenodo.4647753
title: MECPerf experimentation on Fed4FIRE+/NITOS

description: This dataset contains the outcome of the MECPerf experiment, funded within the 6th Fed4FIRE+ open call for experimenters. MECPerf is an open source tool to measure key performance indices (KPIs) of a MEC/cloud infrastructure, at both network and application level. MECPerf is available at https://github.com/MECPerf/MECPerf. The dataset contains bandwidth and latency measurements collected in three different operational scenarios: i) active measurements, in which MECPerf measures KPIs such as TCP bandwidth, UDP bottleneck capacity, TCP and UDP RTT of a MEC and a cloud environment, in presence of increasing cross traffic; ii) passive measurements through edge application, in which a DASH streaming application running on multiple clients measures its own KPIs in presence of increasing cross traffic, and communicates them to MECPerf via an open interface; iii) passive measurements through traffic redirection, in which MECPerf sniffs the traffic produced in the same setup as scenario ii to extract KPIs. More details can be found in the deliverables and final report of the MECPerf project.
DOI: 10.5281/zenodo.3767096
title: MECPerf experimentation on Fed4FIRE+/NITOS

description: This dataset contains the outcome of the MECPerf experiment, funded within the 6th Fed4FIRE+ open call for experimenters. MECPerf is an open source tool to measure key performance indices (KPIs) of a MEC/cloud infrastructure, at both network and application level. MECPerf is available at https://github.com/MECPerf/MECPerf. The dataset contains bandwidth and latency measurements collected in three different operational scenarios: i) active measurements, in which MECPerf measures KPIs such as TCP bandwidth, UDP bottleneck capacity, TCP and UDP RTT of a MEC and a cloud environment, in presence of increasing cross traffic; ii) passive measurements through edge application, in which a DASH streaming application running on multiple clients measures its own KPIs in presence of increasing cross traffic, and communicates them to MECPerf via an open interface; iii) passive measurements through traffic redirection, in which MECPerf sniffs the traffic produced in the same setup as scenario ii to extract KPIs. More details can be found in the deliverables and final report of the MECPerf project.
DOI: 10.6084/m9.figshare.14340221.v1
title: Supplementary files

description: Figure.S1-S5
DOI: 10.25375/uct.8229557
title: Nutrition related health status and associated factors in juvenile male and female on remand detainees at entry into Pollsmoor correctional service facility in the Western Cape (dataset)

description: Research data for the MA Thesis: Nutrition related health status and associated factors in juvenile male and female on remand detainees at entry into Pollsmoor correctional service facility in the Western Cape.<br>Design/Methodology: In this cross-sectional comparative study of 67 male and 52 female young on-remand detainees the following was assessed during 2016-2017: socio-demographic information, hunger score (CDC FANTA project hunger score), meal pattern, food choices (Non-quantified FFQ), understanding of healthy eating, physical activity (GPAQv2), risk taking behaviours, body shape perception, symptoms of depression and anxiety (K10 tool) and specific anthropometric measures including weight, height, triceps-skinfold, mid-upper arm circumference and handgrip strength. BMI and the corrected arm muscle area were calculated.<br>The pdf of the thesis is accessible at http://hdl.handle.net/11427/33202 <br>Approval was granted by UCT HREC, National department of correctional services South Africa and permission was granted to publish information. <br>
DOI: 10.6084/m9.figshare.14340221
title: Supplementary files

description: Figure.S1-S5
DOI: 10.6084/m9.figshare.14340221.v3
title: Supplementary files

description: Figure.S1-S5
DOI: 10.6084/m9.figshare.14340221.v2
title: Supplementary files

description: Figure.S1-S5
DOI: 10.6084/m9.figshare.14336735.v1
title: Peltigera lichens from Karukinka Natural Park, Magallanes Region, Chile (2020, above tree line)

description: Peltigera lichen samples collected by the Microbial Ecology Lab (Universidad de Chile), from an area above tree line in the Karukinka Natural Park in 2020.
DOI: 10.5281/zenodo.4642347
title: Enregistrement du son de 6 pianos

description: Cette base de donnée est le résultat de l'enregistrement par 2 étudiants ingénieurs de l'École Centrale de Nantes (Tom Oviste et Pierre Lambert) du son de 6 pianos à des fins de traitement audionumérique, sous la tutelle de Sébastien Bourguignon et Vincent Lostanlen. Elle comprend l'enregistrement de 8 notes, 4 accords et un extrait de morceau pour chaque piano par deux enregistreurs différents.
DOI: 10.5281/zenodo.4642346
title: Enregistrement du son de 6 pianos

description: Cette base de donnée est le résultat de l'enregistrement par 2 étudiants ingénieurs de l'École Centrale de Nantes (Tom Oviste et Pierre Lambert) du son de 6 pianos à des fins de traitement audionumérique, sous la tutelle de Sébastien Bourguignon et Vincent Lostanlen. Elle comprend l'enregistrement de 8 notes, 4 accords et un extrait de morceau pour chaque piano par deux enregistreurs différents.
DOI: 10.6084/m9.figshare.14270267.v3
title: SplitFrictionModel Worksheet

description: Worksheet from The Split Friction Model - Introducing Mixed Lubrication to Curling by Martin Ziegler<br>
DOI: 10.6084/m9.figshare.14340251
title: Supplementary files

description: Figure.S1-S5
DOI: 10.6084/m9.figshare.14340251.v1
title: Supplementary files

description: Figure.S1-S5
DOI: 10.5281/zenodo.4647691
title: Training Data for DeepArk

description: Training data for the DeepArk models. The first prefix of the file name indicates the genome that the data is intended to be used with.
DOI: 10.5281/zenodo.4647690
title: Training Data for DeepArk

description: Training data for the DeepArk models. The first prefix of the file name indicates the genome that the data is intended to be used with.
DOI: 10.6084/m9.figshare.10317368
title: Tactile and proximity fracture/crack dataset

description: The names are encoded as follows:<br>“crack_type/width_R.mat”<br>type/width: the type of surface or the width of the crack<br>R: the number of complete repetition<br>The data acquired with the sensor and the Geomagic have been synchronised using the provided timestamp.For each surface the dataset contains one matlab synchronised.mat file:The position of the Geomagic on the X-axis (especially useful for plotting))The value obtained from the left part displacement (D1) of the fibre-optic sensorThe value obtained from the right part displacement (D2) of the fibre-optic sensorThe value obtained from the back part displacement (D3) of the fibre-optic sensorThe proximity value (P) of the fibre-optic sensorThe sliding movement direction of the Geomagic, 1 indicates movement from left to right and 0 indicates movement from right to leftThe number of complete sliding repetition (from left to right and backward), from 1 to 12The type of surface explored. For the type: 0 = flat surface, 1 = crack surface, 2 = bump surface, 3 = wavy pattern surface. For the width of the crack, the size of the crack is used (e.g. 0 if no crack, 5 if a 5mm crack was explored).The number of complete repetition, from 1 to 5.For additional Information, please refer to https://francescapalermo.github.io/dataset/tactileproximitydataset <br>If you use the dataset, please cite the following paper. Bibtext Citation:<code>@article{palermo2020automatic, title={Automatic Fracture Characterization Using Tactile and Proximity Optical Sensing}, author={Palermo, Francesca and Konstantinova, Jelizaveta and Althoefer, Kaspar and Poslad, Stefan and Farkhatdinov, Ildar}, journal={Frontiers in Robotics and AI}, volume={7}, year={2020}, publisher={Frontiers Media SA}}</code>
DOI: 10.6084/m9.figshare.14340224
title: Raw Data meta-analysis of the e-learning influence on VET

description: This is raw data from an article that is in the process of submission at F1000Research with the title A meta-analysis of the e-learning influence on VET learning: preliminary study of virtual to actualization.
DOI: 10.6084/m9.figshare.14340224.v1
title: Raw Data meta-analysis of the e-learning influence on VET

description: This is raw data from an article that is in the process of submission at F1000Research with the title A meta-analysis of the e-learning influence on VET learning: preliminary study of virtual to actualization.
DOI: 10.6084/m9.figshare.10317368.v1
title: Tactile and proximity fracture/crack dataset

description: The names are encoded as follows:<br>“crack_type/width_R.mat”<br>type/width: the type of surface or the width of the crack<br>R: the number of complete repetition<br>The data acquired with the sensor and the Geomagic have been synchronised using the provided timestamp.For each surface the dataset contains one matlab synchronised.mat file:The position of the Geomagic on the X-axis (especially useful for plotting))The value obtained from the left part displacement (D1) of the fibre-optic sensorThe value obtained from the right part displacement (D2) of the fibre-optic sensorThe value obtained from the back part displacement (D3) of the fibre-optic sensorThe proximity value (P) of the fibre-optic sensorThe sliding movement direction of the Geomagic, 1 indicates movement from left to right and 0 indicates movement from right to leftThe number of complete sliding repetition (from left to right and backward), from 1 to 12The type of surface explored. For the type: 0 = flat surface, 1 = crack surface, 2 = bump surface, 3 = wavy pattern surface. For the width of the crack, the size of the crack is used (e.g. 0 if no crack, 5 if a 5mm crack was explored).The number of complete repetition, from 1 to 5.For additional Information, please refer to https://francescapalermo.github.io/dataset/tactileproximitydataset <br>If you use the dataset, please cite the following paper. Bibtext Citation:<code>@article{palermo2020automatic, title={Automatic Fracture Characterization Using Tactile and Proximity Optical Sensing}, author={Palermo, Francesca and Konstantinova, Jelizaveta and Althoefer, Kaspar and Poslad, Stefan and Farkhatdinov, Ildar}, journal={Frontiers in Robotics and AI}, volume={7}, year={2020}, publisher={Frontiers Media SA}}</code>
DOI: 10.5281/zenodo.4647621
title: K Th U concentration in the West African Craton

description: Geochemical Database. Literature review of K, Th and U Concentrations in samples from the West African Craton
DOI: 10.5281/zenodo.4647620
title: K Th U concentration in the West African Craton

description: Geochemical Database. Literature review of K, Th and U Concentrations in samples from the West African Craton
DOI: 10.5281/zenodo.4647254
title: RNAProt: An efficient and feature-rich RNA binding protein binding site predictor

description: RNAProt Supplementary Data, containing benchmark and training datasets (see content.txt inside .zip file for more details on included datasets)
DOI: 10.5281/zenodo.4010641
title: Larval abundance and recruitment densities of a non-native colonial ascidian in a marina in Nova Scotia, Canada

description: This dataset contains data described in the paper entitled 'Larval supply is a limited determinant of settlement at mesoscales across an anthropogenic seascape'. Data include larval abundance and recruitment densities of a non-native colonial ascidian, <em>Botryllus schlosseri </em>(Pallas, 1766), in a marina in Ben Eoin, Nova Scotia, Canada.
DOI: 10.5281/zenodo.4010640
title: Larval abundance and recruitment densities of a non-native colonial ascidian in a marina in Nova Scotia, Canada

description: This dataset contains data described in the paper entitled 'Larval supply is a limited determinant of settlement at mesoscales across an anthropogenic seascape'. Data include larval abundance and recruitment densities of a non-native colonial ascidian, <em>Botryllus schlosseri </em>(Pallas, 1766), in a marina in Ben Eoin, Nova Scotia, Canada.
DOI: 10.5281/zenodo.3920535
title: Supporting data for "Latitudinal patterns in intertidal ecosystem structure in West Greenland suggest resilience to climate change"

description: The data contains three supporting datasets: 1. Mid-intertidal data 2. Vertical transect data 3. GPS coordinates for all sites
DOI: 10.5281/zenodo.3920534
title: Supporting data for "Latitudinal patterns in intertidal ecosystem structure in West Greenland suggest resilience to climate change"

description: The data contains three supporting datasets: 1. Mid-intertidal data 2. Vertical transect data 3. GPS coordinates for all sites
DOI: 10.6084/m9.figshare.14340329.v1
title: Identification of sequence changes in myosin II that adjust muscle contraction velocity Figure data

description: Identification of sequence changes in myosin II that adjust muscle contraction velocity<br>
DOI: 10.34740/kaggle/dsv/2072009
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.25387/g3.12579737
title: Supplemental Material for Mathew et al., 2020

description: 1. Trait data<br>2. Marker data<br>3. Analysis code<br>4. Simulation code
DOI: 10.25387/g3.12579737.v3
title: Supplemental Material for Mathew et al., 2020

description: 1. Trait data<br>2. Marker data<br>3. Analysis code<br>4. Simulation code
DOI: 10.25387/g3.12579737.v2
title: Supplemental Material for Mathew et al., 2020

description: 1. Trait data<br>2. Marker data<br>3. Analysis code<br>4. Simulation code
DOI: 10.6084/m9.figshare.12494654
title: bibliometric_DFT

description: Data for: Authorship and citation cultural nature in Density Functional Theory from solid state computational packages.CSV file containing 134,586 papers citing at least one of the 31 main DFT packages/software. <br>9 columns: authors, title, number of citations, year of publication, Unique WoS ID number, document type, countries of affiliation, number of pages and name of DFT code cited.<br>All observations for one code have been stripped from duplicates, based on the unique identifier of the papers. However, if using the whole dataset, there will be duplicates as one paper can cite several codes.<br><br>Authors and countries are separated by a semicolon within one column in the original file. The preview shows authors and countries separated in several columns but when downloaded, the data is correctly placed within the columns.<br>
DOI: 10.6084/m9.figshare.12494654.v3
title: bibliometric_DFT

description: Data for: Authorship and citation cultural nature in Density Functional Theory from solid state computational packages.CSV file containing 17,274 co-citations of the 31 main DFT packages/software. <br>9 columns: authors, title, number of citations, year of publication, DOI number, document type, countries of affiliation, number of pages and name of DFT code cited.<br>All observations for one code have been stripped from duplicates, based on the DOI number of papers. However, if using the whole dataset, there will be duplicates as one paper can cite several codes.<br><br>Authors and countries are separated by a semicolon within one column in the original file. The preview shows authors and countries separated in several columns but when downloaded, the data is correctly placed within the columns.<br>
DOI: 10.15131/shef.data.13342238
title: Data for 'Is ink heating a relevant concern in the High Speed Sintering process?'

description: High Speed Sintering (HSS) is a novel polymer additive manufacturing process which utilises inkjet printing of an infrared-absorbing pigment onto a heated polymer powder bed to create 2D cross-sections which can be selectively sintered using an infrared lamp. Understanding and improving the accuracy and repeatability of part manufacture by HSS are important, ongoing areas of research. In particular, the role of the ink is poorly understood; the inks typically used in HSS have not been optimised for it, and it is unknown whether they perform in a consistent manner in the process. Notably, the ambient temperature inside a HSS machine increases as a side effect of the sintering process, and the unintentional heating to which the ink is exposed is expected to cause changes in its fluid properties. However, neither the extent of ink heating during the HSS process nor the subsequent changes in its fluid properties have ever been investigated. Such investigation is important, since significant changes in ink properties at different temperatures would be expected to lead to inconsistent printing and subsequently variations in part accuracy and even the degree of sintering during a single build. For the first time, we have quantified the ink temperature rise caused by unintentional, ambient heating during the HSS process, and subsequently measured several of the ink’s fluid properties across the ink temperature range which is expected to be encountered in normal machine operation (25 to 45 ∘C). We observed only small changes in the ink’s density and surface tension due to this heating, but a significant drop (36%) in its viscosity was seen. By inspection of the ink’s <i>Z</i> number throughout printing, it is concluded that these changes would not be expected to change the manner in which droplets are delivered to the powder bed surface. In contrast, the viscosity decrease during printing is such that it is expected that the printed droplet sizes do change in a single build, which may indeed be a cause for concern with regard to the accuracy and repeatability of the inkjet printing used in HSS, and subsequently to the properties of the polymer parts obtained from the process.
DOI: 10.15131/shef.data.13342238.v1
title: Data for 'Is ink heating a relevant concern in the High Speed Sintering process?'

description: High Speed Sintering (HSS) is a novel polymer additive manufacturing process which utilises inkjet printing of an infrared-absorbing pigment onto a heated polymer powder bed to create 2D cross-sections which can be selectively sintered using an infrared lamp. Understanding and improving the accuracy and repeatability of part manufacture by HSS are important, ongoing areas of research. In particular, the role of the ink is poorly understood; the inks typically used in HSS have not been optimised for it, and it is unknown whether they perform in a consistent manner in the process. Notably, the ambient temperature inside a HSS machine increases as a side effect of the sintering process, and the unintentional heating to which the ink is exposed is expected to cause changes in its fluid properties. However, neither the extent of ink heating during the HSS process nor the subsequent changes in its fluid properties have ever been investigated. Such investigation is important, since significant changes in ink properties at different temperatures would be expected to lead to inconsistent printing and subsequently variations in part accuracy and even the degree of sintering during a single build. For the first time, we have quantified the ink temperature rise caused by unintentional, ambient heating during the HSS process, and subsequently measured several of the ink’s fluid properties across the ink temperature range which is expected to be encountered in normal machine operation (25 to 45 ∘C). We observed only small changes in the ink’s density and surface tension due to this heating, but a significant drop (36%) in its viscosity was seen. By inspection of the ink’s <i>Z</i> number throughout printing, it is concluded that these changes would not be expected to change the manner in which droplets are delivered to the powder bed surface. In contrast, the viscosity decrease during printing is such that it is expected that the printed droplet sizes do change in a single build, which may indeed be a cause for concern with regard to the accuracy and repeatability of the inkjet printing used in HSS, and subsequently to the properties of the polymer parts obtained from the process.
DOI: 10.5281/zenodo.4647892
title: Twitter dataset - Coordinated Behavior on Social Media in 2019 UK General Election

description: This dataset contains ~11M tweets related to the 2019 United Kingdom General Election, published and collected between November 12, 2019, and December 12, 2019. In addition, we provide nodes and edges of the superspreader user similarity network, as described in the paper below. Please, refer to the paper below for more details. <strong>Nizzoli, L., Tardelli, S., Avvenuti, M., Cresci, S., & Tesconi, M. (2021). Coordinated Behavior on Social Media in 2019 UK General Election. In 15th International Conference on Web and Social Media. AAAI.</strong> In detail, the dataset consists of: <em>tweet-ids.csv.zip</em>: a CSV file with the column "tweet_id," containing 11,264,820 tweet IDs related to the 2019 United Kingdom General Election, published and collected between November 12, 2019, and December 12, 2019. <em>superspreader-nodes.csv.zip</em>: a CSV file with the columns "id" and "cluster," relating to the nodes of the superspreader user similarity network mentioned in the paper. <em>superspreader-edges.csv.zip</em>: a CSV file with the columns "source," "target," and "weight," relating to the edges of the superspreader user similarity network mentioned in the paper.
DOI: 10.25345/c5181z
title: MassIVE MSV000087127 - JGI Genome Portal Zerbe-Murphy 2017 maize secondary metabolites ( Project ID: 1188675 ) - GNPS
title: Elucidating the function of the maize (Zea mays) diterpene secondary metabolic network on fitness-promoting plant-microbiome interactions (Proposal ID: 503533). Downloaded from https://genome.jgi.doe.gov/portal/ZerMuretabolites_FD/ZerMuretabolites_FD.info.html
DOI: 10.6084/m9.figshare.14336873
title: Peltigera lichens from Leones Valley, Aysén Region, Chile (2014)

description: Peltigera lichen samples collected by the Microbial Ecology Lab (Universidad de Chile), from a mesophytic shrubland in Leones Valley in 2014.
DOI: 10.6084/m9.figshare.14336873.v2
title: Peltigera lichens from Leones Valley, Aysén Region, Chile (2014)

description: Peltigera lichen samples collected by the Microbial Ecology Lab (Universidad de Chile), from a mesophytic shrubland in Leones Valley in 2014.