cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5212399
title: Malignancy probability computer model

description: Malignancy probability scores of the computer model and information of the study group as input for the computer model
DOI: 10.6084/m9.figshare.5212402.v1
title: Malignancy Probability Observers

description: Malignancy probability scores of the observers for the two subsets of nodules and different subsets of observers
DOI: 10.6084/m9.figshare.5212399.v1
title: Malignancy probability computer model

description: Malignancy probability scores of the computer model and information of the study group as input for the computer model
DOI: 10.6084/m9.figshare.5212087
title: Data on Cameroonian and Namibian faces

description: Supplementary data to atricle entitled "African and European perception of African female attractiveness"
DOI: 10.6084/m9.figshare.5212099
title: Labview program DC resistance measurement during mechanical bending of conductive film

description: Labview program DC resistance measurement during mechanical bending of conductive film<br>
DOI: 10.6084/m9.figshare.5212096
title: AC Impedance and DC resistance LabVIEW program during cure

description: AC Impedance and DC resistance LabVIEW program during cure
DOI: 10.6084/m9.figshare.5212087.v1
title: Data on Cameroonian and Namibian faces

description: Supplementary data to atricle entitled "African and European perception of African female attractiveness"
DOI: 10.6084/m9.figshare.5212099.v2
title: Labview program DC resistance measurement during mechanical bending of conductive film

description: Labview program DC resistance measurement during mechanical bending of conductive film<br>
DOI: 10.6084/m9.figshare.5212099.v1
title: DC Resistance measurement during conductive film mechanical aging

description: DC Resistance measurement during conductive film mechanical aging
DOI: 10.6084/m9.figshare.5211982
title: max-front2-PHASE3B-P.YRC22.zip

description: <br>zip file containing data files associated to the paper:<br>"Petrological Geodynamics of Mantle Melting II. AlphaMELTS + Multiphase Flow: Dynamic Fractional Melting"<br>by Max Tirone<br>Front. Earth Sci. DOI: 10.3389/feart.2018.00018<br><br>
DOI: 10.6084/m9.figshare.5212003
title: CV sequences

description: 16S Raw Sequences fron CV (Vapour Col.) Deception Island
DOI: 10.6084/m9.figshare.5211982.v1
title: max-front2-PHASE3B-P.YRC22.zip

description: <br>zip file containing data files associated to the paper:<br>"Petrological Geodynamics of Mantle Melting II. AlphaMELTS + Multiphase Flow: Dynamic Fractional Melting"<br>by Max Tirone<br>Front. Earth Sci. DOI: 10.3389/feart.2018.00018<br><br>
DOI: 10.6084/m9.figshare.5211931
title: Gomes-Koban et al, PLOS ONE Data.xlsx

description: This dataset comes from the following article:<br>Gomes-Koban, C.; Simpson, I. C.; Valle, A. & Defior, S. (2017). Oral Vocabulary Training Program for Spanish Third-Graders with Low Socio-Economic Status: A Randomized Controlled Trial. PLOS ONE.<br><br>Although the importance of vocabulary training in English speaking countries is well recognized and has been extensively studied, the same is not true for Spanish - few evidence based vocabulary studies for Spanish speaking children have been reported. Here, two rich oral vocabulary training programs (definition and context), based on literature about vocabulary instruction for English-speaking children, were developed and applied in a sample of 100 Spanish elementary school third-graders recruited from areas of predominantly low socio-economic status (SES). Compared to an alternative read-aloud method which served as the control, both explicit methods were more effective in teaching word meanings when assessed immediately after the intervention. Nevertheless, five months later, only the definition group continued to demonstrate significant vocabulary knowledge gains. The definition method was more effective in specifically teaching children word meanings and, more broadly, in helping children organize and express knowledge of words. We recommend the explicit and rich vocabulary instruction as a means to fostering vocabulary knowledge in low SES children.
DOI: 10.6084/m9.figshare.5211931.v1
title: Gomes-Koban et al, PLOS ONE Data.xlsx

description: This dataset comes from the following article:<br>Gomes-Koban, C.; Simpson, I. C.; Valle, A. & Defior, S. (2017). Oral Vocabulary Training Program for Spanish Third-Graders with Low Socio-Economic Status: A Randomized Controlled Trial. PLOS ONE.<br><br>Although the importance of vocabulary training in English speaking countries is well recognized and has been extensively studied, the same is not true for Spanish - few evidence based vocabulary studies for Spanish speaking children have been reported. Here, two rich oral vocabulary training programs (definition and context), based on literature about vocabulary instruction for English-speaking children, were developed and applied in a sample of 100 Spanish elementary school third-graders recruited from areas of predominantly low socio-economic status (SES). Compared to an alternative read-aloud method which served as the control, both explicit methods were more effective in teaching word meanings when assessed immediately after the intervention. Nevertheless, five months later, only the definition group continued to demonstrate significant vocabulary knowledge gains. The definition method was more effective in specifically teaching children word meanings and, more broadly, in helping children organize and express knowledge of words. We recommend the explicit and rich vocabulary instruction as a means to fostering vocabulary knowledge in low SES children.
DOI: 10.6084/m9.figshare.5211979
title: Lipid Droplet Maturation in Adipocytes.xlsx

description: The files provide raw data derived from studies on the role of microsomal triglyceride transfer protein in lipid droplet biogenesis in adipocytes.
DOI: 10.6084/m9.figshare.5211979.v1
title: Lipid Droplet Maturation in Adipocytes.xlsx

description: The files provide raw data derived from studies on the role of microsomal triglyceride transfer protein in lipid droplet biogenesis in adipocytes.
DOI: 10.6084/m9.figshare.5212003.v2
title: CV sequences

description: 16S Raw Sequences fron CV (Vapour Col.) Deception Island
DOI: 10.6084/m9.figshare.5211892
title: cuadrado_models17.zip

description: This dataset corresponds to the artifact associated to the paper "Translating target to source constraints in model-to-model transformations" presented at MoDELS'17.<br><br>
DOI: 10.6084/m9.figshare.5211904
title: RiscoCV Os Jovens, os velhos e os outros _CHVNG

description: Cálculo do Risco Cardiovascular & Reclassificação.O que dizem as Guidelines ESC_2016<br>
DOI: 10.6084/m9.figshare.5211892.v1
title: cuadrado_models17.zip

description: This dataset corresponds to the artifact associated to the paper "Translating target to source constraints in model-to-model transformations" presented at MoDELS'17.<br><br>
DOI: 10.6084/m9.figshare.5211904.v1
title: RiscoCV Os Jovens, os velhos e os outros _CHVNG

description: Cálculo do Risco Cardiovascular & Reclassificação.O que dizem as Guidelines ESC_2016<br>
DOI: 10.6084/m9.figshare.5212003.v1
title: CV sequences

description: 16S Raw Sequences fron CV (Vapour Col.) Deception Island
DOI: 10.5281/zenodo.3648639
title: Results of the CNRS benchmark

description: Raw results obtained by each partner performing the CNRS benchmark.
DOI: 10.6084/m9.figshare.5211916.v1
title: Dataset Descriptions

description: Despite the fact that extensive list of linked open datasets are available in catalogues, most of the data publishers still connects their datasets to the most popular ones, such as DBpedia, Freebase and Geonames. Although the linkage with popular datasets would allow us to explore external resources, it would fail to cover highly specialized information. Catalogues of linked data describe the content of datasets in terms of the update periodicity, authors, SPARQL endpoints, linksets, amongst others, as recommended by W3C VoID Vocabulary. However, catalogues by themselves do not provide any explicit information to help the URI linkage process. <br>Searching techniques can rank available datasets according to the likelyhood that it will be possible to find links between them and a given target dataset, so that most of the links, if not all, could be found by inspecting the most relevant datasets in the ranking.<br>This dataset contains dataset descriptions using the VoID vocabulary for supporting the evaluation of searching techniques. The descriptions of each dataset include their linksets, classes, properties and topic categories which were harvested from the Datahub catalogue, dataset dumps, void files and the DBpedia knowledge graph. The DBpedia Spotlight allowed the detection of named entities in textual literals and thereafter of the DBpedia topic categories of each entity which were taken as the topic categories od the datasets containing de entities.
DOI: 10.5281/zenodo.3588365
title: Results of the CNRS benchmark

description: Raw results obtained by each partner performing the CNRS benchmark.
DOI: 10.6084/m9.figshare.5211916.v2
title: Dataset Descriptions

description: Despite the fact that extensive list of linked open datasets are available in catalogues, most of the data publishers still connects their datasets to the most popular ones, such as DBpedia, Freebase and Geonames. Although the linkage with popular datasets would allow us to explore external resources, it would fail to cover highly specialized information. Catalogues of linked data describe the content of datasets in terms of the update periodicity, authors, SPARQL endpoints, linksets, amongst others, as recommended by W3C VoID Vocabulary. However, catalogues by themselves do not provide any explicit information to help the URI linkage process. <br>Searching techniques can rank available datasets according to the likelyhood that it will be possible to find links between them and a given target dataset, so that most of the links, if not all, could be found by inspecting the most relevant datasets in the ranking.<br>This dataset contains dataset descriptions using the VoID vocabulary for supporting the evaluation of searching techniques. The descriptions of each dataset include their linksets, classes, properties and topic categories which were harvested from the Datahub catalogue, dataset dumps, void files and the DBpedia knowledge graph. The DBpedia Spotlight allowed the detection of named entities in textual literals and thereafter of the DBpedia topic categories of each entity which were taken as the topic categories od the datasets containing de entities.
DOI: 10.6084/m9.figshare.5211916
title: Dataset Descriptions

description: This repository contains descriptions of Linked Data datasets using VoID vocabulary. The descriptions include Linksets, classes, properties and topic categories and mashes up data from DataHub, dataset dumps, VoID files and DBpedia. The DBpedia Spotlight allowed the recognition of named entities in literal values. Each entity is associated with a list of topic categories through the predicate <i>dcterms:subject</i> and each topic category is subsumed by others through the predicate <i>skos:broader</i>. A category <i>c</i> is a topic category of a dataset <i>iff</i> there exists a property path <i>{e dcterms:subject/skos:broader* c.}</i> from a named entity <i>e</i> of the dataset to <i>c</i> in DBpedia.<br>
DOI: 10.6084/m9.figshare.5211916.v5
title: Dataset Descriptions

description: This repository contains descriptions of Linked Data datasets using VoID vocabulary. The descriptions include Linksets, classes, properties and topic categories and mashes up data from DataHub, dataset dumps, VoID files and DBpedia. The DBpedia Spotlight allowed the recognition of named entities in literal values. Each entity is associated with a list of topic categories through the predicate <i>dcterms:subject</i> and each topic category is subsumed by others through the predicate <i>skos:broader</i>. A category <i>c</i> is a topic category of a dataset <i>iff</i> there exists a property path <i>{e dcterms:subject/skos:broader* c.}</i> from a named entity <i>e</i> of the dataset to <i>c</i> in DBpedia.<br>
DOI: 10.6084/m9.figshare.5211916.v7
title: Dataset Descriptions

description: This repository contains descriptions of Linked Data datasets using VoID vocabulary. The descriptions include Linksets, classes, properties and topic categories and mashes up data from DataHub, dataset dumps, VoID files and DBpedia. The DBpedia Spotlight allowed the recognition of named entities in literal values. Each entity is associated with a list of topic categories through the predicate <i>dcterms:subject</i> and each topic category is subsumed by others through the predicate <i>skos:broader</i>. A category <i>c</i> is a topic category of a dataset <i>iff</i> there exists a property path <i>{e dcterms:subject/skos:broader* c.}</i> from a named entity <i>e</i> of the dataset to <i>c</i> in DBpedia.<br>
DOI: 10.6084/m9.figshare.5211916.v6
title: Dataset Descriptions

description: This repository contains descriptions of Linked Data datasets using VoID vocabulary. The descriptions include Linksets, classes, properties and topic categories and mashes up data from DataHub, dataset dumps, VoID files and DBpedia. The DBpedia Spotlight allowed the recognition of named entities in literal values. Each entity is associated with a list of topic categories through the predicate <i>dcterms:subject</i> and each topic category is subsumed by others through the predicate <i>skos:broader</i>. A category <i>c</i> is a topic category of a dataset <i>iff</i> there exists a property path <i>{e dcterms:subject/skos:broader* c.}</i> from a named entity <i>e</i> of the dataset to <i>c</i> in DBpedia.<br>
DOI: 10.6084/m9.figshare.5211577
title: Spatiotemporal variability of epibenthic assemblages in Moreton Bay

description: Raw data on the abundance and percentage cover of epibenthic taxa identified during surveys in Moreton Bay from 1998-2002 and 2012-2015. Surveys were taken using underwater videography at a total of 63 sites and used to determine where and how epibenthic assemblage structure had changed from 1998 to 2015. <br>Original surveys were taken from 1998-2002 for a habitat mapping study (Stevens & Connolly 2004). Resurveys of a subset of sites were taken from 2012-2014 by a study conducted for the Queensland Department of Science, Information, Technology, Innovation and the Arts (Stevens & Richmond 2014). Re-surveys of the remaining sites that had not yet been revisited were taken in 2015 and were combined with the 2012-2014 data, for comparison with the 1998-2002 data.<br>From each survey a total of 50 still images were extracted at 5 second intervals, and the abundance or percentage cover of each identifiable organism was determined. These values were then divided by 50 to obtain the relative abundance and percentage cover of each species per site. This data was then incorporated into Primer E (v.6) for analysis.<br>The relative influence of abiotic variables on assemblage structure was determined using long term data on sediment mud content (O'Brien, Tuazon et al. 2012) and on other abiotic variables such as sea surface temperature, turbidity and nutrient content (made available from the Healthy Waterways Ecosystem Health and Monitoring Program).
DOI: 10.6084/m9.figshare.5211577.v1
title: Spatiotemporal variability of epibenthic assemblages in Moreton Bay

description: Raw data on the abundance and percentage cover of epibenthic taxa identified during surveys in Moreton Bay from 1998-2002 and 2012-2015. Surveys were taken using underwater videography at a total of 63 sites and used to determine where and how epibenthic assemblage structure had changed from 1998 to 2015. <br>Original surveys were taken from 1998-2002 for a habitat mapping study (Stevens & Connolly 2004). Resurveys of a subset of sites were taken from 2012-2014 by a study conducted for the Queensland Department of Science, Information, Technology, Innovation and the Arts (Stevens & Richmond 2014). Re-surveys of the remaining sites that had not yet been revisited were taken in 2015 and were combined with the 2012-2014 data, for comparison with the 1998-2002 data.<br>From each survey a total of 50 still images were extracted at 5 second intervals, and the abundance or percentage cover of each identifiable organism was determined. These values were then divided by 50 to obtain the relative abundance and percentage cover of each species per site. This data was then incorporated into Primer E (v.6) for analysis.<br>The relative influence of abiotic variables on assemblage structure was determined using long term data on sediment mud content (O'Brien, Tuazon et al. 2012) and on other abiotic variables such as sea surface temperature, turbidity and nutrient content (made available from the Healthy Waterways Ecosystem Health and Monitoring Program).
DOI: 10.6084/m9.figshare.5211568
title: Goodness of Fit of Logistic Regression Models for Random Graphs

description: Logistic regression is a natural and simple tool to understand how covariates contribute to explain the topology of a binary network. Once the model is fitted, the practitioner is interested in the goodness of fit of the regression to check if the covariates are sufficient to explain the whole topology of the network and, if they are not, to analyze the residual structure. To address this problem, we introduce a generic model that combines logistic regression with a network-oriented residual term. This residual term takes the form of the graphon function of a <i>W</i>-graph. Using a variational Bayes framework, we infer the residual graphon by averaging over a series of blockwise constant functions. This approach allows us to define a generic goodness-of-fit criterion, which corresponds to the posterior probability for the residual graphon to be constant. Experiments on toy data are carried out to assess the accuracy of the procedure. Several networks from social sciences and ecology are studied to illustrate the proposed methodology. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.5211448
title: Functionality of tRNAs encoded in a mobile genetic element from an acidophilic bacterium

description: The genome of the acidophilic, bioleaching bacterium <i>Acidithiobacillus ferrooxidans</i>, strain ATCC 23270, contains 95 predicted tRNA genes. Thirty-six of these genes (all 20 species) are clustered within an actively excising integrative-conjugative element (ICEA<i>fe</i>1). We speculated that these tRNA genes might have a role in adapting the bacterial tRNA pool to the codon usage of ICEA<i>fe</i>1 genes. To answer this question, we performed theoretical calculations of the global tRNA adaptation index to the entire <i>A. ferrooxidans</i> genome with and without the ICEA<i>fe</i>1 encoded tRNA genes. Based on these calculations, we observed that tRNAs encoded in ICEA<i>fe</i>1 negatively contribute to adapt the tRNA pool to the codon use in <i>A. ferrooxidans.</i> Although some of the tRNAs encoded in ICE<i>Afe</i>1 are functional in aminoacylation or protein synthesis, we found that they are expressed at low levels. These findings, along with the identification of a tRNA-like RNA encoded in the same cluster, led us to speculate that tRNA genes encoded in the mobile genetic element ICEA<i>fe</i>1 might have acquired mutations that would result in either inactivation or the acquisition of new functions.
DOI: 10.6084/m9.figshare.5211568.v1
title: Goodness of fit of logistic regression models for random graphs

description: The logistic regression model constitutes a natural and simple tool to understand how covariates (when available) contribute to explain the topology of a binary network. After estimating the logistic parameters, one of the main questions which arises in practice is to assess the goodness of fit of the corresponding model. To address this problem, we add a general term, related to the graphon function of W-graph models, to the logistic function. Such an extra term aims at characterizing the residual structure of the network, that is not explained by the covariates. We approximate this new generic logistic model using a class of models with blockwise constant residual structure. This framework allows to derive a Bayesian procedure from a model based selection context using goodness-of-fit criteria. All these criteria depend on marginal likelihood terms for which we do provide estimates relying on two series of variational approximations. Experiments on toy data are carried out to assess the inference procedure. Finally, six networks from social sciences and ecology are studied to illustrate the proposed methodology. Logistic regression is a natural and simple tool to understand how covariates contribute to explain the topology of a binary network. Once the model is fitted, the practitioner is interested in the goodness-of-fit of the regression in order to check if the covariates are sufficient to explain the whole topology of the network and, if they are not, to analyze the residual structure. To address this problem, we introduce a generic model that combines logistic regression with a network-oriented residual term. This residual term takes the form of the graphon function of a <i>W</i>-graph. Using a variational Bayes framework, we infer the residual graphon by averaging over a series of blockwise constant functions. This approach allows us to define a generic goodness-of-fit criterion, which corresponds to the posterior probability for the residual graphon to be constant. Experiments on toy data are carried out to assess the accuracy of the procedure. Several networks from social sciences and ecology are studied to illustrate the proposed methodology.
DOI: 10.6084/m9.figshare.5211439
title: DataSet_Figures 3-4-5.zip

description: This is the complete DataSet of the publication<br><br>L. Peter, J. Tunesi, A. Pasquazi and M. Peccianti "Optical Pump Rectification Emission: Route to Terahertz Free-Standing Surface Potential Diagnostics"<br><br>http://www.nature.com/articles/s41598-017-08734-z<br><br><br>In particular the file contains 3 folders which identify the original source data of Figure 3, Figure 4 and Figure 5<br><br>The format of the raw data is .mat - MATLAB binary -v7, which is compatible and portable to GNU Octave version &gt;4.0 (tested)<br><br>Descriptors of all the variables defined in the .mat files are contained in the files<br><br>Figure3_MetaData.txt<br>Figure4_MetaData.txt<br>Figure5_MetaData.txt<br><br><br>The format of the raw data is .mat - MATLAB binary -v7, which is compatible and portable to GNU Octave version &gt;4.0 (tested)<br><br><br><br><br><br> <br>
DOI: 10.6084/m9.figshare.5211448.v1
title: Functionality of tRNAs encoded in a mobile genetic element from an acidophilic bacterium

description: The genome of the acidophilic, bioleaching bacterium <i>Acidithiobacillus ferrooxidans</i>, strain ATCC 23270, contains 95 predicted tRNA genes. Thirty-six of these genes (all 20 species) are clustered within an actively excising integrative-conjugative element (ICEA<i>fe</i>1). We speculated that these tRNA genes might have a role in adapting the bacterial tRNA pool to the codon usage of ICEA<i>fe</i>1 genes. To answer this question, we performed theoretical calculations of the global tRNA adaptation index to the entire <i>A. ferrooxidans</i> genome with and without the ICEA<i>fe</i>1 encoded tRNA genes. Based on these calculations, we observed that tRNAs encoded in ICEA<i>fe</i>1 negatively contribute to adapt the tRNA pool to the codon use in <i>A. ferrooxidans.</i> Although some of the tRNAs encoded in ICE<i>Afe</i>1 are functional in aminoacylation or protein synthesis, we found that they are expressed at low levels. These findings, along with the identification of a tRNA-like RNA encoded in the same cluster, led us to speculate that tRNA genes encoded in the mobile genetic element ICEA<i>fe</i>1 might have acquired mutations that would result in either inactivation or the acquisition of new functions.