cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.6796211.v2
title: Supplementary Information from Unexpected formation of polymeric silver(I) complexes of azine-type ligand via self-assembly of Ag-salts with isatin oxamohydrazide.

description: Isatin oxamohydrazide (<b>L</b>) reacted with the aqueous solution of silver nitrate at room temperature afforded the polymeric silver(I) nitrato complex, [Ag<sub>2</sub>L′(NO<sub>3</sub>)<sub>2</sub>]<i><sub>n</sub></i>, <b>(1)</b> of the azine ligand (<b>L′</b>). Similarly, the reaction of <b>L</b> with silver(I) perchlorate gave the [Ag<sub>2</sub>L′<sub>2</sub>(ClO<sub>4</sub>)<sub>2</sub>]<i><sub>n</sub></i>, <b>(2)</b> coordination polymer. Careful inspection of the crystals from the nitrato complex preparation showed the presence of another crystalline product which is found to be [Ag(Isatin-3-hydrazone)NO<sub>3</sub>], <b>(3)</b> suggesting that the reaction between silver(I) nitrate and <b>L</b> proceeds first by the hydrolysis of <b>L</b> to the isatin hydrazone which attacks another molecule of <b>L</b> to afford <b>L′</b>. Testing metal salts such as Ni<sup>2+</sup>, Co<sup>2+</sup>, Mn<sup>2+</sup>, Cu<sup>2+</sup> and Cd<sup>2+</sup> did not undergo any reaction with <b>L</b> either under the same reaction conditions or with heating under reflux up to 24 h. Treatment of the warm alcoholic solution of <b>L</b> with few drops of 1 : 1 (<i>v</i>/<i>v</i>) hydrochloric acid gave the free ligand (<b>L′</b>) in good yield. The [Ag<sub>2</sub>L′(NO<sub>3</sub>)<sub>2</sub>]<i><sub>n</sub></i> complex forms a two-dimensional infinite coordination polymer, while the [Ag<sub>2</sub>L′<sub>2</sub>(ClO<sub>4</sub>)<sub>2</sub>]<i><sub>n</sub></i> forms one-dimensional infinite chains with an alternating silver-azine backbone. Quantitative analysis of the intermolecular interactions in their crystals is made using Hirshfeld surface analysis. Density functional theory studies were performed to investigate the coordination bonding in the studied complexes.
DOI: 10.6084/m9.figshare.6796211.v1
title: Supplementary Information from Unexpected formation of polymeric silver(I) complexes of azine-type ligand via self-assembly of Ag-salts with isatin oxamohydrazide

description: Isatin oxamohydrazide (<b>L</b>) reacted with the aqueous solution of silver nitrate at room temperature afforded the polymeric silver(I) nitrato complex, [Ag<sub>2</sub>L′(NO<sub>3</sub>)<sub>2</sub>]<i><sub>n</sub></i>, <b>(1)</b> of the azine ligand (<b>L′</b>). Similarly, the reaction of <b>L</b> with silver(I) perchlorate gave the [Ag<sub>2</sub>L′<sub>2</sub>(ClO<sub>4</sub>)<sub>2</sub>]<i><sub>n</sub></i>, <b>(2)</b> coordination polymer. Careful inspection of the crystals from the nitrato complex preparation showed the presence of another crystalline product which is found to be [Ag(Isatin-3-hydrazone)NO<sub>3</sub>], <b>(3)</b> suggesting that the reaction between silver(I) nitrate and <b>L</b> proceeds first by the hydrolysis of <b>L</b> to the isatin hydrazone which attacks another molecule of <b>L</b> to afford <b>L′</b>. Testing metal salts such as Ni<sup>2+</sup>, Co<sup>2+</sup>, Mn<sup>2+</sup>, Cu<sup>2+</sup> and Cd<sup>2+</sup> did not undergo any reaction with <b>L</b> either under the same reaction conditions or with heating under reflux up to 24 h. Treatment of the warm alcoholic solution of <b>L</b> with few drops of 1 : 1 (<i>v</i>/<i>v</i>) hydrochloric acid gave the free ligand (<b>L′</b>) in good yield. The [Ag<sub>2</sub>L′(NO<sub>3</sub>)<sub>2</sub>]<i><sub>n</sub></i> complex forms a two-dimensional infinite coordination polymer, while the [Ag<sub>2</sub>L′<sub>2</sub>(ClO<sub>4</sub>)<sub>2</sub>]<i><sub>n</sub></i> forms one-dimensional infinite chains with an alternating silver-azine backbone. Quantitative analysis of the intermolecular interactions in their crystals is made using Hirshfeld surface analysis. Density functional theory studies were performed to investigate the coordination bonding in the studied complexes.
DOI: 10.6084/m9.figshare.6792344
title: Data file, Dougherty & Guillette 2018 from Linking personality and cognition: a meta-analysis.

description: In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this link. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale; however, the <i>direction</i> of this relationship is highly variable and when both positive and negative effect sizes are considered, the average effect size does not differ significantly from zero. Importantly, this variation between studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated predator) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
DOI: 10.6084/m9.figshare.6792341
title: R code, Dougherty & Guillette 2018 from Linking personality and cognition: a meta-analysis.

description: In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this link. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale; however, the <i>direction</i> of this relationship is highly variable and when both positive and negative effect sizes are considered, the average effect size does not differ significantly from zero. Importantly, this variation between studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated predator) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
DOI: 10.6084/m9.figshare.6792344.v2
title: Data file, Dougherty & Guillette 2018 from Linking personality and cognition: a meta-analysis.

description: In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this link. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale; however, the <i>direction</i> of this relationship is highly variable and when both positive and negative effect sizes are considered, the average effect size does not differ significantly from zero. Importantly, this variation between studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated predator) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
DOI: 10.6084/m9.figshare.6792341.v2
title: R code, Dougherty & Guillette 2018 from Linking personality and cognition: a meta-analysis.

description: In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this link. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale; however, the <i>direction</i> of this relationship is highly variable and when both positive and negative effect sizes are considered, the average effect size does not differ significantly from zero. Importantly, this variation between studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated predator) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
DOI: 10.6084/m9.figshare.6792344.v1
title: Data file, Dougherty & Guillette 2018 from Linking personality and cognition: a meta-analysis

description: In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this question. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale, however the <i>direction</i> of this relationship is highly variable and when both positive and negative effect sizes are considered the average effect size does not differ significantly from zero. Importantly, this variation between studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
DOI: 10.6084/m9.figshare.6792341.v1
title: R code, Dougherty & Guillette 2018 from Linking personality and cognition: a meta-analysis

description: In the past decade, several conceptual papers have linked variation in animal personality to variation in cognition, and recent years have seen a flood of empirical studies testing this question. However, these results have not been synthesized in a quantitative way. Here, we systematically search the literature and conduct a phylogenetically controlled meta-analysis of empirical papers that have tested the relationship between animal personality (exploration, boldness, activity, aggression and sociability) and cognition (initial learning/reversal speed, number of correct choices/errors after standard training). We find evidence for a small but significant relationship between variation in personality and variation in learning across species in the absolute scale, however the <i>direction</i> of this relationship is highly variable and when both positive and negative effect sizes are considered the average effect size does not differ significantly from zero. Importantly, this variation between studies is not explained by differences in personality or learning measure, or taxonomic grouping. Further, these results do not support current hypotheses suggesting that that fast-explorers are fast-learners or that slow-explorers perform better on tests of reversal learning. Rather, we find evidence that bold animals are faster learners, but only when boldness is measured in response to a predator (or simulated) and not when boldness is measured by exposure to a novel object (or novel food). Further, although only a small sub-sample of papers reported results separately for males and females, sex explained a significant amount of variation in effect size. These results, therefore, suggest that, while personality and learning are indeed related across a range of species, the direction of this relationship is highly variable. Thus further empirical work is needed to determine whether there are important moderators of this relationship.This article is part of the theme issue ‘Causes and consequences of individual differences in cognitive ability’.
DOI: 10.6084/m9.figshare.6796979
title: Supplemental Data Items part 2 (excel) from No detectable effect of <i>Wolbachia w</i>Mel on the prevalence and abundance of the RNA virome of <i>Drosophila melanogaster</i>.

description: Table S2
DOI: 10.6084/m9.figshare.6796979.v2
title: Supplemental Data Items part 2 (excel) from No detectable effect of <i>Wolbachia w</i>Mel on the prevalence and abundance of the RNA virome of <i>Drosophila melanogaster</i>.

description: Table S2
DOI: 10.6084/m9.figshare.6796982
title: Supplemental Data Items part 3 (excel) from No detectable effect of <i>Wolbachia w</i>Mel on the prevalence and abundance of the RNA virome of <i>Drosophila melanogaster</i>.

description: Table S3
DOI: 10.6084/m9.figshare.6796979.v1
title: Supplemental Data Items part 2 (excel) from No detectable effect of <i>Wolbachia w</i>Mel on the prevalence and abundance of the RNA virome of <i>Drosophila melanogaster</i>

description: Table S2
DOI: 10.6084/m9.figshare.6796982.v2
title: Supplemental Data Items part 3 (excel) from No detectable effect of <i>Wolbachia w</i>Mel on the prevalence and abundance of the RNA virome of <i>Drosophila melanogaster</i>.

description: Table S3
DOI: 10.6084/m9.figshare.6796982.v1
title: Supplemental Data Items part 3 (excel) from No detectable effect of <i>Wolbachia w</i>Mel on the prevalence and abundance of the RNA virome of <i>Drosophila melanogaster</i>

description: Table S3
DOI: 10.6084/m9.figshare.6810005
title: Supplementary Table S1 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: Parameter estimates (credible intervals) of concentrations of Abs
DOI: 10.6084/m9.figshare.6810017
title: Supplementary Table S2 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: Parameter estimates (credible interval) of affinities of Abs
DOI: 10.6084/m9.figshare.6810005.v2
title: Supplementary Table S1 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: Parameter estimates (credible intervals) of concentrations of Abs
DOI: 10.6084/m9.figshare.6810005.v1
title: Supplementary Table S1 from Bayesian inference of antigenic and non-antigenic variables from haemagglutinin inhibition assays for influenza surveillance

description: Parameter estimates (credible intervals) of concentrations of Abs
DOI: 10.6084/m9.figshare.6810014
title: Supplementary Table S3 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: Parameter estimates (credible interval) of non-antigenic variables
DOI: 10.6084/m9.figshare.6810011
title: Supplementary Table S4 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: A collection of HI titers
DOI: 10.6084/m9.figshare.6810017.v1
title: Supplementary Table S2 from Bayesian inference of antigenic and non-antigenic variables from haemagglutinin inhibition assays for influenza surveillance

description: Parameter estimates (credible interval) of affinities of Abs
DOI: 10.6084/m9.figshare.6810011.v2
title: Supplementary Table S4 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: A collection of HI titers
DOI: 10.6084/m9.figshare.6810014.v2
title: Supplementary Table S3 from Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.

description: Parameter estimates (credible interval) of non-antigenic variables
DOI: 10.6084/m9.figshare.6810011.v1
title: Supplementary Table S4 from Bayesian inference of antigenic and non-antigenic variables from haemagglutinin inhibition assays for influenza surveillance

description: A collection of HI titers
DOI: 10.6084/m9.figshare.6810014.v1
title: Supplementary Table S3 from Bayesian inference of antigenic and non-antigenic variables from haemagglutinin inhibition assays for influenza surveillance

description: Parameter estimates (credible interval) of non-antigenic variables
DOI: 10.6084/m9.figshare.6820664
title: Dataset 4B from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: ‘Newick’ format file describing the presented functional dendrogram of Peracarida.
DOI: 10.6084/m9.figshare.6820649
title: Dataset 1 from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: Peracarid abundance assemblage matrices (genus abundance by box core and family abundance by box core).
DOI: 10.6084/m9.figshare.6820664.v2
title: Dataset 4B from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: ‘Newick’ format file describing the presented functional dendrogram of Peracarida.
DOI: 10.6084/m9.figshare.6820655
title: Supporting Appendix 1 from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: Details of taxonomic identity and accession number for all GenBank sequences analysed.
DOI: 10.6084/m9.figshare.6820664.v1
title: Dataset 4B from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance

description: ‘Newick’ format file describing the presented functional dendrogram of Peracarida.
DOI: 10.6084/m9.figshare.6820643
title: Dataset 3 from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: Functional trait matrix (Matrix of functional traits by peracarid family).
DOI: 10.6084/m9.figshare.6820649.v2
title: Dataset 1 from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: Peracarid abundance assemblage matrices (genus abundance by box core and family abundance by box core).
DOI: 10.6084/m9.figshare.6820655.v2
title: Supporting Appendix 1 from Phylogenetic and functional evidence suggests that deep-ocean ecosystems are highly sensitive to environmental change and direct human disturbance.

description: Details of taxonomic identity and accession number for all GenBank sequences analysed.