cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5554540
title: Experiment CLA-SubjectF-150917-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554525
title: Experiment CLA-SubjectE-151225-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554528
title: Experiment CLA-SubjectE-160119-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554519
title: Experiment CLA-SubjectC-151126-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554513
title: Experiment CLA-SubjectC-151223-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554516
title: Experiment CLA-SubjectC-151216-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554522
title: Experiment CLA-SubjectD-151125-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554504
title: Experiment CLA-SubjectA-160108-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554507
title: Experiment CLA-SubjectB-151020-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554510
title: Experiment CLA-SubjectB-151215-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.6084/m9.figshare.5554450
title: Dataset description file.

description: A text file containing general description-summary of the dataset.
DOI: 10.6084/m9.figshare.5554501
title: Experiment CLA-SubjectB-151019-3States

description: Experiment in which subject performed 3 imageries of left and right hand motion and a passive state.
DOI: 10.21227/7dpg-nf30
title: Edge/Fog Computing Bibliographic Data from Google Scholar 2003-2019

description: This Dataset includes the lsit of articles indexed by Google Scholar from 2003-2019, realted to: Edge Computing, Fog Computing, Multi-Access Edge Computing, Mobile Cloud Computing.The data has been cleaned by removing duplicates, non-english articles, un-realted articles (i.e. computing edges in a picture is not about Edge Computing) and articles that weren't directly or easily accessable.
DOI: 10.6084/m9.figshare.5554195
title: Advances in numerical calibration of the Permian timescale based on radioisotope geochronology

description: <b>Table S1:</b> CA-ID-TIMS U–Pb data for the analysed ash bed from Nipple Hill, Guadalupe Mountains National Park, Texas.
DOI: 10.6084/m9.figshare.5554195.v1
title: Advances in numerical calibration of the Permian timescale based on radioisotope geochronology

description: <b>Table S1:</b> CA-ID-TIMS U–Pb data for the analysed ash bed from Nipple Hill, Guadalupe Mountains National Park, Texas.
DOI: 10.21227/1qrf-zv58
title: Edge/Fog Computing Bibliographic Data from Google Scholar 2003-2019

description: This Dataset includes the lsit of articles indexed by Google Scholar from 2003-2019, realted to: Edge Computing, Fog Computing, Multi-Access Edge Computing, Mobile Cloud Computing.The data has been cleaned by removing duplicates, non-english articles, un-realted articles (i.e. computing edges in a picture is not about Edge Computing) and articles that weren't directly or easily accessable.
DOI: 10.6084/m9.figshare.5554192
title: Toponym matching through deep neural networks

description: Toponym matching, i.e. pairing strings that represent the same real-world location, is a fundamental problemfor several practical applications. The current state-of-the-art relies on string similarity metrics, either specifically developed for matching place names or integrated within methods that combine multiple metrics. However, these methods all rely on common sub-strings in order to establish similarity, and they do not effectively capture the character replacements involved in toponym changes due to transliterations or to changes in language and culture over time. In this article, we present a novel matching approach, leveraging a deep neural network to classify pairs of toponyms as either matching or nonmatching. The proposed network architecture uses recurrent nodes to build representations from the sequences of bytes that correspond to the strings that are to be matched. These representations are then combined and passed to feed-forward nodes, finally leading to a classification decision. We present the results of a wide-ranging evaluation on the performance of the proposed method, using a large dataset collected from the GeoNames gazetteer. These results show that the proposed method can significantly outperform individual similarity metrics from previous studies, as well as previous methods based on supervised machine learning for combining multiple metrics.
DOI: 10.6084/m9.figshare.5554192.v1
title: Toponym matching through deep neural networks

description: Toponym matching, i.e. pairing strings that represent the same real-world location, is a fundamental problemfor several practical applications. The current state-of-the-art relies on string similarity metrics, either specifically developed for matching place names or integrated within methods that combine multiple metrics. However, these methods all rely on common sub-strings in order to establish similarity, and they do not effectively capture the character replacements involved in toponym changes due to transliterations or to changes in language and culture over time. In this article, we present a novel matching approach, leveraging a deep neural network to classify pairs of toponyms as either matching or nonmatching. The proposed network architecture uses recurrent nodes to build representations from the sequences of bytes that correspond to the strings that are to be matched. These representations are then combined and passed to feed-forward nodes, finally leading to a classification decision. We present the results of a wide-ranging evaluation on the performance of the proposed method, using a large dataset collected from the GeoNames gazetteer. These results show that the proposed method can significantly outperform individual similarity metrics from previous studies, as well as previous methods based on supervised machine learning for combining multiple metrics.
DOI: 10.6084/m9.figshare.5554162
title: Supplementary Material for: Electrophysiological Evidence of the Basilar-Membrane Travelling Wave and Frequency Place Coding of Sound in Cochlear Implant Recipients

description: <i>Aim:</i> To obtain direct evidence for the cochlear travelling wave in humans by performing electrocochleography from within the cochlea in subjects implanted with an auditory prosthesis. <i>Background:</i> Sound induces a travelling wave that propagates along the basilar membrane, exhibiting cochleotopic tuning with a frequency-dependent phase delay. To date, evoked potentials and psychophysical experiments have supported the presence of the travelling wave in humans, but direct measurements have not been made. <i>Methods:</i> Electrical potentials in response to rarefaction and condensation acoustic tone bursts were recorded from multiple sites along the human cochlea, directly from a cochlear implant electrode during, and immediately after, its insertion. These recordings were made from individuals with residual hearing. <i>Results:</i> Electrocochleography was recorded from 11 intracochlear electrodes in 7 ears from 6 subjects, with detectable responses on all electrodes in 5 ears. Cochleotopic tuning and frequency-dependent phase delay of the cochlear microphonic were demonstrated. The response latencies were slightly shorter than those anticipated which we attribute to the subjects' hearing loss. <i>Conclusions:</i> Direct evidence for the travelling wave was observed. Electrocochleography from cochlear implant electrodes provides site-specific information on hair cell and neural function of the cochlea with potential diagnostic value.
DOI: 10.6084/m9.figshare.5554147
title: Emu track and Undertracks in cement - photos + photogrammetric models.

description: Track and undertracks of emu, recorded in cement. Digitized using Photogrammetry.<br>Data from figure 5 of :<br>Milàn, J. and R. G. Bromley (2008). "The Impact of Sediment Consistency on Track and Undertrack Morphology: Experiments with Emu Tracks in Layered Cement." Ichnos 15: 19-27.<br>Dataset includes original photos and digital models. <br><br>
DOI: 10.6084/m9.figshare.5554063
title: KoRV Genome Alignment resulting Fasta files.

description: LTR depleted reads were then mapped to the complete genomes of Koala retrovirus KoRV A and KoRV B (AF151794.2 and KC779547.1 respectively) using Hisat2. FASTA files for each sample generated usingsamtools mpileup and bcftools consensus.<br>
DOI: 10.6084/m9.figshare.5554132
title: Table SI_GO_UC.xls

description: Supplemental material for Morilla et al., JAMP 2017
DOI: 10.6084/m9.figshare.5554063.v1
title: KoRV Genome Alignment resulting Fasta files.

description: LTR depleted reads were then mapped to the complete genomes of Koala retrovirus KoRV A and KoRV B (AF151794.2 and KC779547.1 respectively) using Hisat2. FASTA files for each sample generated usingsamtools mpileup and bcftools consensus.<br>
DOI: 10.6084/m9.figshare.5554132.v1
title: Table SI_GO_UC.xls

description: Supplemental material for Morilla et al., JAMP 2017
DOI: 10.6084/m9.figshare.5553535
title: Disparity vs. diversity in Stegosauria (Dinosauria, Ornithischia): cranial and post-cranial sub-dataset provide different signals

description: The Stegosauria represents an iconic group of ornithischian dinosaurs, with a fossil record spanning the Middle Jurassic to the Late Cretaceous. In this contribution I present the first detailed analysis of the relationship between disparity and diversity through the evolutionary history of the group. The analysis has been performed on a recently published cladistic dataset, allowing the separate study of the signals deriving from discrete characters and from continuous morphometric characters. Whereas the disparity as sum of variance is decoupled with respect to diversity, the sum of ranges provides a signal fairly consistent with the trend in the number of taxa. Both sub-data sets show that evolution of stegosaurs can be considered essentially as symmetrical, i.e. the maximum exploration of the possible morphospace takes place about half way through the history of the group, with subsequent significant decline until extinction in the Upper Cretaceous. An interesting result is a decoupling of the tempo and mode of evolution of the cranium and postcranium in stegosaurs. Specifically, the evolutionary radiation with maximum saturation of morphospace is anticipated in the cranial skeleton, with maximum peak in the Oxfordian; in contrast, the postcranium explores the largest number of morphotypes subsequently during the Kimmeridgian.
DOI: 10.6084/m9.figshare.5553535.v1
title: Disparity vs. diversity in Stegosauria (Dinosauria, Ornithischia): cranial and post-cranial sub-dataset provide different signals

description: The Stegosauria represents an iconic group of ornithischian dinosaurs, with a fossil record spanning the Middle Jurassic to the Late Cretaceous. In this contribution I present the first detailed analysis of the relationship between disparity and diversity through the evolutionary history of the group. The analysis has been performed on a recently published cladistic dataset, allowing the separate study of the signals deriving from discrete characters and from continuous morphometric characters. Whereas the disparity as sum of variance is decoupled with respect to diversity, the sum of ranges provides a signal fairly consistent with the trend in the number of taxa. Both sub-data sets show that evolution of stegosaurs can be considered essentially as symmetrical, i.e. the maximum exploration of the possible morphospace takes place about half way through the history of the group, with subsequent significant decline until extinction in the Upper Cretaceous. An interesting result is a decoupling of the tempo and mode of evolution of the cranium and postcranium in stegosaurs. Specifically, the evolutionary radiation with maximum saturation of morphospace is anticipated in the cranial skeleton, with maximum peak in the Oxfordian; in contrast, the postcranium explores the largest number of morphotypes subsequently during the Kimmeridgian.
DOI: 10.6084/m9.figshare.5553505
title: SPCAM Preprocessed file with date, time, lat and lon info

description: SPCAM preprocessed file for CBRAIN with additional dimensions --&gt; CNNs and RNNs<br>Additionally with new mean and std files for normalization.
DOI: 10.6084/m9.figshare.5553493
title: Persistence length calculation

description: Persistence length calculation based on single nanofilament.<br>
DOI: 10.6084/m9.figshare.5553490
title: Brownian motion of nanofilament

description: Dataset presenting Brownian motion of single nanofilament with the code for persistence length calculation.<br>
DOI: 10.6084/m9.figshare.5553490.v1
title: Brownian motion of nanofilaments

description: Dataset presenting Brownian motion of single filament with the code for persistence length calculation.<br>
DOI: 10.6084/m9.figshare.5553505.v1
title: SPCAM Preprocessed file with date, time, lat and lon info

description: SPCAM preprocessed file for CBRAIN with additional dimensions --&gt; CNNs and RNNs
DOI: 10.6084/m9.figshare.5553445.v1
title: filtered_gene_bc_matrices.tar.gz

description: A comprehensive transcriptome gene-barcodes dataset based on 10x genomics platform at the single-cell level from antler stem cells. These data were generated from the Cell Ranger pipeline version 1.3.1.
DOI: 10.6084/m9.figshare.5553448.v1
title: cloupe.cloupe

description: The cloupe files were generated from the Cell Ranger pipeline version 1.3.1 based on 10x genomics platform at the single-cell level from antler stem cells.
DOI: 10.6084/m9.figshare.5553445.v2
title: filtered_gene_bc_matrices.tar.gz

description: A comprehensive transcriptome gene-barcodes matrix dataset based on 10x genomics platform at the single-cell level from antler stem cells. These data were generated from the Cell Ranger pipeline version 1.3.1.
DOI: 10.6084/m9.figshare.5552932
title: Pearmanetal_HiddenMajority_Archive-3.zip

description: This folder contains raw Illumina MiSeq sequence files. We amplified a 313bp of the mitochondrial Cytochrome c. Oxidase Subunit I gene (COI) for benthic coral reef samples collected in the Red Sea. Details of samples are provided in the metadata file "Pearmanetal_HiddenMajority_COI_metadata.xls"
DOI: 10.6084/m9.figshare.5552932.v1
title: Pearmanetal_HiddenMajority_Archive-3.zip

description: This folder contains raw Illumina MiSeq sequence files. We amplified a 313bp of the mitochondrial Cytochrome c. Oxidase Subunit I gene (COI) for benthic coral reef samples collected in the Red Sea. Details of samples are provided in the metadata file "Pearmanetal_HiddenMajority_COI_metadata.xls"
DOI: 10.6084/m9.figshare.5552914
title: LEAP Lampung conditional update 29 Oktober 2017

description: Pemodelan Energi yang dilakukan oleh dinas ESDM provinsi Lampung
DOI: 10.6084/m9.figshare.5552914.v1
title: LEAP Lampung conditional update 29 Oktober 2017

description: Pemodelan Energi yang dilakukan oleh dinas ESDM provinsi Lampung
DOI: 10.6084/m9.figshare.5552920
title: S1OriginalDataTAPSEPrePostFin.xlsx

description: Excel data sheet of clinical parameters
DOI: 10.6084/m9.figshare.5552887
title: CMRO2_CBF_data.sav

description: Data for Yv, Ya, CMRO2, CBF (total brain and grey matter), volumes of grey and white matter, cognitive composite scores. Participant age, gender and age-group. <br>
DOI: 10.6084/m9.figshare.5552887.v1
title: CMRO2_CBF_data.sav

description: Data for Yv, Ya, CMRO2, CBF (total brain and grey matter), volumes of grey and white matter, cognitive composite scores. Participant age, gender and age-group. <br>
DOI: 10.6084/m9.figshare.5552782
title: Pearmanetal_HiddenMajority_Archive-2.zip

description: This folder contains raw Illumina MiSeq sequence files. We amplified a 313bp of the mitochondrial Cytochrome c. Oxidase Subunit I gene (COI) for benthic coral reef samples collected in the Red Sea. Details of samples are provided in the metadata file "Pearmanetal_HiddenMajority_COI_metadata.xls"
DOI: 10.6084/m9.figshare.5552743
title: Indian Village Satellite Imagery and Energy Access Dataset

description: This dataset contains remote sensing data for every village in the state of Bihar, India. For most of these villages, the data contains the corresponding electrification rate as reported by the Garv data platform from the Indian government as of July 2017. This dataset contains satellite imagery, political boundaries, lights at night imagery, rainfall measurements, and vegetation indices data for 45,220 villages and the electrification rate data for 32,817 of those villages. This dataset may be of particular interest to those investigating how electricity access maps to infrastructure and agricultural production.<br>This dataset was compiled as part of the Summer 2017 Duke University Data+ team, titled "Electricity Access in Developing Countries from Aerial Imagery."
DOI: 10.6084/m9.figshare.5552704
title: Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US

description: Provenance tests are a common tool in forestry designed to identify superior genotypes for planting at specific locations. The trials are replicated experiments established with seed from parent trees collected from different regions and grown at several locations. In this work, a Bayesian spatial approach is developed for modeling the expected relative performance of seed sources using climate variables as predictors associated with the origin of seed source and the planting site. The proposed modeling technique accounts for the spatial dependence in the data and introduces a separable Matérn covariance structure that provides a flexible means to estimate effects associated with the origin and planting site locations. The statistical model was used to develop a quantitative tool for seed deployment aimed to identify the location of superior performing seed sources that could be suitable for a specific planting site under a given climate scenario. Cross-validation results indicate that the proposed spatial models provide superior predictive ability compared to multiple linear regression methods in unobserved locations. The general trend of performance predictions based on future climate scenarios suggests an optimal assisted migration of loblolly pine seed sources from southern and warmer regions to northern and colder areas in the southern USA. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5552704.v1
title: Optimal Seed Deployment Under Climate Change Using Spatial Models: Application to Loblolly Pine in the Southeastern US

description: Provenance tests are a common tool in forestry designed to identify superior genotypes for planting at specific locations. The trials are replicated experiments established with seed from parent trees collected from different regions and grown at several locations. In this work, a Bayesian spatial approach is developed for modeling the expected relative performance of seed sources using climate variables as predictors associated with the origin of seed source and the planting site. The proposed modeling technique accounts for the spatial dependence in the data and introduces a separable Matérn covariance structure that provides a flexible means to estimate effects associated with the origin and planting site locations. The statistical model was used to develop a quantitative tool for seed deployment aimed to identify the location of superior performing seed sources that could be suitable for a specific planting site under a given climate scenario. Cross-validation results indicate that the proposed spatial models provide superior predictive ability compared to multiple linear regression methods in unobserved locations. The general trend of performance predictions based on future climate scenarios suggests an optimal assisted migration of loblolly pine seed sources from southern and warmer regions to northern and colder areas in the southern USA. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5552665
title: Compression and Conditional Emulation of Climate Model Output

description: Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus it is important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset—1 year of daily mean temperature data—particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.5552665.v1
title: Compression and Conditional Emulation of Climate Model Output

description: Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus it is important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset—1 year of daily mean temperature data—particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers. Supplementary materials for this article are available online.