cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5809047
title: Late Palaeozoic igneous rocks of the Great Xing’an Range, NE China: the Tayuan example

description: The Tayuan plutons located at the boundary of the Erguna and Xing’an blocks expose a coexisting mafic–felsic association that is made of monzogranite and gabbro-monzodiorite as well as subordinate quartz monzonite. LA–ICP–MS U–Pb zircon dating revealed a synchronous emplacement of the monzogranite (314–317 Ma), gabbro (308–315 Ma), and quartz monzonite (310 ± 3 Ma). The majority of these intrusions are characterized by an enrichment in light rare earth elements relative to heavy rare earth elements and a depletion of high strength field elements (e.g. Nb, Ta, Ti). Zircons from the gabbro and monzogranite have ε<sub>Hf</sub>(t) values of 1.1–9.6 and −3.0–3.3, respectively. Geochemical data show that the gabbro-monzodiorite may have been generated by the melting of a fluid-metasomatized lithospheric mantle, while the monzogranite may have been formed by a partial melting of the Mesoproterozoic crust. The quartz monzonite has similar whole-rock geochemical and Hf isotopic compositions to those of the gabbros and could have been produced from the same mantle source as that from which the gabbros were extracted. The Tayuan plutonic rocks have high contents of K<sub>2</sub>O and total alkalis and show a northwestward polarity like that of the continental margin plutonic rocks along the Hegenshan–Heihe suture zone. Combined with data from published studies, our data indicate that the Tayuan intrusive rocks were generated by the northwestward subduction of the Hegenshan–Heihe Oceanic plate.
DOI: 10.6084/m9.figshare.5809047.v2
title: Late Palaeozoic igneous rocks of the Great Xing’an Range, NE China: the Tayuan example

description: The Tayuan plutons located at the boundary of the Erguna and Xing’an blocks expose a coexisting mafic–felsic association that is made of monzogranite and gabbro-monzodiorite as well as subordinate quartz monzonite. LA–ICP–MS U–Pb zircon dating revealed a synchronous emplacement of the monzogranite (314–317 Ma), gabbro (308–315 Ma), and quartz monzonite (310 ± 3 Ma). The majority of these intrusions are characterized by an enrichment in light rare earth elements relative to heavy rare earth elements and a depletion of high strength field elements (e.g. Nb, Ta, Ti). Zircons from the gabbro and monzogranite have ε<sub>Hf</sub>(t) values of 1.1–9.6 and −3.0–3.3, respectively. Geochemical data show that the gabbro-monzodiorite may have been generated by the melting of a fluid-metasomatized lithospheric mantle, while the monzogranite may have been formed by a partial melting of the Mesoproterozoic crust. The quartz monzonite has similar whole-rock geochemical and Hf isotopic compositions to those of the gabbros and could have been produced from the same mantle source as that from which the gabbros were extracted. The Tayuan plutonic rocks have high contents of K<sub>2</sub>O and total alkalis and show a northwestward polarity like that of the continental margin plutonic rocks along the Hegenshan–Heihe suture zone. Combined with data from published studies, our data indicate that the Tayuan intrusive rocks were generated by the northwestward subduction of the Hegenshan–Heihe Oceanic plate.
DOI: 10.6084/m9.figshare.5809047.v1
title: Late Palaeozoic igneous rocks of the Great Xing’an Range, NE China: the Tayuan example

description: The Tayuan plutons located at the boundary of the Erguna and Xing’an blocks expose a coexisting mafic–felsic association that is made of monzogranite and gabbro-monzodiorite as well as subordinate quartz monzonite. LA–ICP–MS U–Pb zircon dating revealed a synchronous emplacement of the monzogranite (314–317 Ma), gabbro (308–315 Ma), and quartz monzonite (310 ± 3 Ma). The majority of these intrusions are characterized by an enrichment in light rare earth elements relative to heavy rare earth elements and a depletion of high strength field elements (e.g. Nb, Ta, Ti). Zircons from the gabbro and monzogranite have ε<sub>Hf</sub>(t) values of 1.1–9.6 and −3.0–3.3, respectively. Geochemical data show that the gabbro-monzodiorite may have been generated by the melting of a fluid-metasomatized lithospheric mantle, while the monzogranite may have been formed by a partial melting of the Mesoproterozoic crust. The quartz monzonite has similar whole-rock geochemical and Hf isotopic compositions to those of the gabbros and could have been produced from the same mantle source as that from which the gabbros were extracted. The Tayuan plutonic rocks have high contents of K<sub>2</sub>O and total alkalis and show a northwestward polarity like that of the continental margin plutonic rocks along the Hegenshan–Heihe suture zone. Combined with data from published studies, our data indicate that the Tayuan intrusive rocks were generated by the northwestward subduction of the Hegenshan–Heihe Oceanic plate.
DOI: 10.6084/m9.figshare.5808885
title: sequencing data (NPFC)

description: sequencing data of microRNA released from mPFC in normal mice.
DOI: 10.6084/m9.figshare.5808885.v1
title: sequencing data (NPFC)

description: sequencing data of microRNA released from mPFC in normal mice.
DOI: 10.6084/m9.figshare.5808876
title: sequencing data(PPFC)

description: sequencing data of miRNA released from mPFC under CCI model
DOI: 10.6084/m9.figshare.5808876.v1
title: sequencing data(PPFC)

description: sequencing data of miRNA released from mPFC under CCI model
DOI: 10.6084/m9.figshare.5808864
title: Data files from the Australian Marine Microbial Biodiversity Initiative

description: Tab delimited text files containing sample by abundance tables for unique bacterial (B16S) and archaeal (A16S) 16S v1-3 and eukaryote (18Sv4) 18S v4 rRNA sequence variants, and corresponding taxonomic classification generated by the Australian Marine Microbial Biodiversity Initiative. Sequences were classified using the Silva v132 database using MOTHURs implementation of the Wang classifier and a 60% Bayesian probability.<br><br>AMMBI_Contextual_data<br>Environmental data collected by the Integrated Marine Observing System at National Reference Stations that correspond with samples for which molecular data was generated by the Australian marine Microbial Biodiversity Initiative. Data were collated from the Australian Ocean Data Network portal (https://portal.aodn.org.au/) as of 31 Jan 2018<br><br>
DOI: 10.6084/m9.figshare.5808864.v1
title: Data files from the Australian Marine Microbial Biodiversity Initiative

description: Text files containing unique bacterial (Brown_B16S) and archaeal (Brown_A16S) 16S v1-3 and eukaryote (Brown_18Sv4) 18S v4 rRNA sequence variants and corresponding taxonomic classification generated by the Australian Marine Microbial Biodiversity Initiative. Sequences were classified using the Silva v128 database using MOTHURs implementation of the Wang classifier and a 60% sequence similarity cutoff. <br>AMMBI_Contextual_data_Jan_18_2018.Environmental data collected by the Integrated Marine Observing System at National Reference Stations that correspond with samples for which molecular data was generated by the Australian marine Microbial Biodiversity Initiative. Data were collated from the Australian Ocean Data Network portal (https://portal.aodn.org.au/) as of 18 Jan 2018<br><br>
DOI: 10.6084/m9.figshare.5808864.v2
title: Data files from the Australian Marine Microbial Biodiversity Initiative

description: Text files containing unique bacterial (Brown_B16S) and archaeal (Brown_A16S) 16S v1-3 and eukaryote (Brown_18Sv4) 18S v4 rRNA sequence variants and corresponding taxonomic classification generated by the Australian Marine Microbial Biodiversity Initiative. Sequences were classified using the Silva v128 database using MOTHURs implementation of the Wang classifier and a 60% sequence similarity cutoff. <br>AMMBI_Contextual_dataEnvironmental data collected by the Integrated Marine Observing System at National Reference Stations that correspond with samples for which molecular data was generated by the Australian marine Microbial Biodiversity Initiative. Data were collated from the Australian Ocean Data Network portal (https://portal.aodn.org.au/) as of 31 Jan 2018<br><br>
DOI: 10.6084/m9.figshare.5808864.v4
title: Data files from the Australian Marine Microbial Biodiversity Initiative

description: Tab delimited text files containing sample by abundance tables for unique bacterial (B16S) and archaeal (A16S) 16S v1-3 and eukaryote (18Sv4) 18S v4 rRNA sequence variants, and corresponding taxonomic classification generated by the Australian Marine Microbial Biodiversity Initiative. Sequences were classified using the Silva v132 database using MOTHURs implementation of the Wang classifier and a 60% Bayesian probability.<br><br>AMMBI_Contextual_data<br>Environmental data collected by the Integrated Marine Observing System at National Reference Stations that correspond with samples for which molecular data was generated by the Australian marine Microbial Biodiversity Initiative. Data were collated from the Australian Ocean Data Network portal (https://portal.aodn.org.au/) as of 31 Jan 2018<br><br>
DOI: 10.6084/m9.figshare.5808864.v3
title: Data files from the Australian Marine Microbial Biodiversity Initiative

description: Tab delimited text files containing sample by abundance tables for unique bacterial (B16S) and archaeal (A16S) 16S v1-3 and eukaryote (18Sv4) 18S v4 rRNA sequence variants, and corresponding taxonomic classification generated by the Australian Marine Microbial Biodiversity Initiative. Sequences were classified using the Silva v132 database using MOTHURs implementation of the Wang classifier and a 60% Bayesian probability. Eukaryote sequences were additionally classified using the Protist Ribosomal Reference Database (PR2).<br><br>AMMBI_Contextual_data<br>Environmental data collected by the Integrated Marine Observing System at National Reference Stations that correspond with samples for which molecular data was generated by the Australian marine Microbial Biodiversity Initiative. Data were collated from the Australian Ocean Data Network portal (https://portal.aodn.org.au/) as of 31 Jan 2018<br><br>
DOI: 10.17608/k6.auckland.5808855
title: Equine bone mineral density files

description: Text file lists of greyscale values from CT DICOM files. To be used in conjunction with the STL surface files
DOI: 10.17608/k6.auckland.5808852
title: Equine_MC3_STLs

description: STL files of the third metacarpal bone geometry in a sample population of third metacarpal bones. These files were used with the list of BMD values to create a statistical shape and image intensity model
DOI: 10.17608/k6.auckland.5808852.v1
title: Equine_MC3_STLs

description: STL files of the third metacarpal bone geometry in a sample population of third metacarpal bones. These files were used with the list of BMD values to create a statistical shape and image intensity model
DOI: 10.6084/m9.figshare.5808837
title: Data associated with "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik"

description: These data are associated with the article "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik", published in Ecological Monographs. They include field data, GPS locations, as well as land cover maps. A README file has been provided to explain the contents of each file.<br>Abstract of the article :<br>A circumpolar increase in shrub growth and cover has been underway in Arctic and subarctic ecosystems for the last few decades, but there is considerable spatial heterogeneity in this shrubification process. Although topography, hydrology and edaphic factors are known to influence shrubification patterns, a better understanding of the landscape-scale factors driving this phenomenon is needed to accurately predict its impacts on ecosystem function. In this study, we generated land cover change models in order to identify variables driving shrub cover increase near Umiujaq (Québec, Canada). Using land cover maps from 1990/1994 and 2010, we modelled observed changes using two contrasting conceptual approaches: binomial modelling of transitions to shrub dominance and multinomial modelling of all land cover transitions. Models were used to generate spatially explicit predictions of transition to shrub dominance in the near future as well as long-term predictions of the abundance of different land cover types. Model predictions were validated using both field data and current Landsat-derived trends of NDVI increase in the region in order to assess their consistency with observed patterns of change. We found that both variables related to topography and to vegetation were useful in modelling land cover changes occurring near Umiujaq. Shrubs tended to preferentially colonize low-elevation areas and moderate slopes, while their cover was more likely to increase in the vicinity of existing shrub patches. Deterministic realizations of the spatially explicit models of land cover change had a good predictive capability, although they performed better at predicting the proportion of different cover types than at predicting the precise location of the changes. Binomial models performed as well as multinomial models, indicating that neglecting land cover changes other than shrubification does not result in decreased prediction accuracy. The predicted probabilities of shrub increase in the region were consistent with patterns of change inferred from field data, but only partly supported by recent local increases in NDVI. Our findings increase the current understanding of the factors driving shrubification, while warranting further research on its impacts on ecosystem function and on the link between land cover changes and shifts in remotely sensed vegetation indices.
DOI: 10.6084/m9.figshare.5808837.v2
title: Data associated with "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik"

description: These data are associated with the article "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik", published in Ecological Monographs. They include field data, GPS locations, as well as land cover maps. A README file has been provided to explain the contents of each file.<br>Abstract of the article :<br>A circumpolar increase in shrub growth and cover has been underway in Arctic and subarctic ecosystems for the last few decades, but there is considerable spatial heterogeneity in this shrubification process. Although topography, hydrology and edaphic factors are known to influence shrubification patterns, a better understanding of the landscape-scale factors driving this phenomenon is needed to accurately predict its impacts on ecosystem function. In this study, we generated land cover change models in order to identify variables driving shrub cover increase near Umiujaq (Québec, Canada). Using land cover maps from 1990/1994 and 2010, we modelled observed changes using two contrasting conceptual approaches: binomial modelling of transitions to shrub dominance and multinomial modelling of all land cover transitions. Models were used to generate spatially explicit predictions of transition to shrub dominance in the near future as well as long-term predictions of the abundance of different land cover types. Model predictions were validated using both field data and current Landsat-derived trends of NDVI increase in the region in order to assess their consistency with observed patterns of change. We found that both variables related to topography and to vegetation were useful in modelling land cover changes occurring near Umiujaq. Shrubs tended to preferentially colonize low-elevation areas and moderate slopes, while their cover was more likely to increase in the vicinity of existing shrub patches. Deterministic realizations of the spatially explicit models of land cover change had a good predictive capability, although they performed better at predicting the proportion of different cover types than at predicting the precise location of the changes. Binomial models performed as well as multinomial models, indicating that neglecting land cover changes other than shrubification does not result in decreased prediction accuracy. The predicted probabilities of shrub increase in the region were consistent with patterns of change inferred from field data, but only partly supported by recent local increases in NDVI. Our findings increase the current understanding of the factors driving shrubification, while warranting further research on its impacts on ecosystem function and on the link between land cover changes and shifts in remotely sensed vegetation indices.
DOI: 10.6084/m9.figshare.5808837.v1
title: Data associated with "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik"

description: This data is associated with the article "Spatially explicit modelling and prediction of shrub cover increase near Umiujaq, Nunavik", published in Ecological Monographs. The data provided here should enable reproducing all the analyses described in the paper. They include digital elevation data, field data and GPS locations, as well as land cover maps. A README file has been provided to explain the contents of each file.<br>Abstract of the article :<br>A circumpolar increase in shrub growth and cover has been underway in Arctic and subarctic ecosystems for the last few decades, but there is considerable spatial heterogeneity in this shrubification process. Although topography, hydrology and edaphic factors are known to influence shrubification patterns, a better understanding of the landscape-scale factors driving this phenomenon is needed to accurately predict its impacts on ecosystem function. In this study, we generated land cover change models in order to identify variables driving shrub cover increase near Umiujaq (Québec, Canada). Using land cover maps from 1990/1994 and 2010, we modelled observed changes using two contrasting conceptual approaches: binomial modelling of transitions to shrub dominance and multinomial modelling of all land cover transitions. Models were used to generate spatially explicit predictions of transition to shrub dominance in the near future as well as long-term predictions of the abundance of different land cover types. Model predictions were validated using both field data and current Landsat-derived trends of NDVI increase in the region in order to assess their consistency with observed patterns of change. We found that both variables related to topography and to vegetation were useful in modelling land cover changes occurring near Umiujaq. Shrubs tended to preferentially colonize low-elevation areas and moderate slopes, while their cover was more likely to increase in the vicinity of existing shrub patches. Deterministic realizations of the spatially explicit models of land cover change had a good predictive capability, although they performed better at predicting the proportion of different cover types than at predicting the precise location of the changes. Binomial models performed as well as multinomial models, indicating that neglecting land cover changes other than shrubification does not result in decreased prediction accuracy. The predicted probabilities of shrub increase in the region were consistent with patterns of change inferred from field data, but only partly supported by recent local increases in NDVI. Our findings increase the current understanding of the factors driving shrubification, while warranting further research on its impacts on ecosystem function and on the link between land cover changes and shifts in remotely sensed vegetation indices.
DOI: 10.6084/m9.figshare.5808792
title: ABAQUS Input File

description: This folder contains ABAQUS input file for head model and corresponding blast-induced skull flexure injury simulations.
DOI: 10.6084/m9.figshare.5808783
title: Figure: Andean Condor Algorithm Conceptualization

description: <b>Summary</b>: The figure represents a conceptualization of the behavior in the search of food of the Andean Condor, to a behavior of intensification and exploration.<br><br>Left figure: A real seasonal variation of the home range of an Andean Condor (Pavez, Eduardo F., 2014). Map located in the Andean Mountains, central zone Chile-Argentina.<br>Right figure: Intensification and exploration movements. These movements are conceptualized by the Andean condor flights carried out during the seasons.<br><b>References</b>:<i>Almonacid, B. & Soto, R. Andean Condor Algorithm for cell formation problems, Natural Computing (2018). https://doi.org/10.1007/s11047-018-9675-0</i><i><br></i><i>Pavez, Eduardo F. "Patrón de movimiento de dos cóndores andinos Vultur gryphus(aves: cathartidae) en los Andes centrales de Chile y Argentina." Bol. Chil. Ornitol 20 (2014).</i>
DOI: 10.6084/m9.figshare.5808783.v2
title: Figure: Andean Condor Algorithm Conceptualization

description: <b>Summary</b>: The figure represents a conceptualization of the behavior in the search of food of the Andean Condor, to a behavior of intensification and exploration.<br><br>Left figure: A real seasonal variation of the home range of an Andean Condor (Pavez, Eduardo F., 2014). Map located in the Andean Mountains, central zone Chile-Argentina.<br>Right figure: Intensification and exploration movements. These movements are conceptualized by the Andean condor flights carried out during the seasons.<br><b>References</b>:<i>Almonacid, B. & Soto, R. Andean Condor Algorithm for cell formation problems, Natural Computing (2018). https://doi.org/10.1007/s11047-018-9675-0</i><i><br></i><i>Pavez, Eduardo F. "Patrón de movimiento de dos cóndores andinos Vultur gryphus(aves: cathartidae) en los Andes centrales de Chile y Argentina." Bol. Chil. Ornitol 20 (2014).</i>
DOI: 10.6084/m9.figshare.5808780
title: Dataset: Andean Condor Algorithm for Solving Cell Formation Problems

description: The original paper was published in https://link.springer.com/article/10.1007/s11047-018-9675-0<br><br>Dataset for Cell Formation Problems (35 problems) in txt and json.<br><br>Include dataset for Minizinc (.dzn) and model (.mzn), using the following configuration: -s -f ‘‘fzngecode -mode stat’’. Only for the problems CFP01 to CFP20.
DOI: 10.6084/m9.figshare.5808780.v1
title: Dataset: Andean Condor Algorithm for Solving Cell Formation Problems

description: Dataset for Cell Formation Problems.<br>Includes 35 arrays of incidents (problems) with 2 types of configurations for each problem (with C = 2, C = 3).
DOI: 10.6084/m9.figshare.5808780.v3
title: Dataset: Andean Condor Algorithm for Solving Cell Formation Problems

description: The original paper was published in https://link.springer.com/article/10.1007/s11047-018-9675-0<br><br>Dataset for Cell Formation Problems (35 problems) in txt and json.<br><br>Include dataset for Minizinc (.dzn) and model (.mzn), using the following configuration: -s -f ‘‘fzngecode -mode stat’’. Only for the problems CFP01 to CFP20.
DOI: 10.6084/m9.figshare.5808780.v2
title: Dataset: Andean Condor Algorithm for Solving Cell Formation Problems

description: The original paper was published in https://link.springer.com/article/10.1007/s11047-018-9675-0<br><br>Dataset for Cell Formation Problems.<br>Includes 35 arrays of incidents (problems) with 2 types of configurations for each problem (with C = 2, C = 3).
DOI: 10.6084/m9.figshare.5808720
title: datasets.zip

description: The six datasets of vineyard thermal information acquired by on-the-go thermal imaging, to predict water status:<br>- With thermal indices: - East side: train and test. - West side: train and test. - Global model: with both sides; train and test.- Without thermal indices: - East side: train and test. - West side: train and test. - Global model: with both sides; train and test.
DOI: 10.6084/m9.figshare.5808702
title: Data from: Hornworm counterattacks: defensive strikes and sound production in response to invertebrate attackers

description: Sugiura S, Takanashi T (2018) Hornworm counterattacks: defensive strikes and sound production in response to invertebrate attackers. Biological Journal of the Linnean Society (http://dx.doi.org/10.1093/biolinnean/blx156)