cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13153919
title: Complete behaviour dataset from Host behaviour alteration by its parasite: from brain gene expression to functional test

description: Many parasites with complex life cycles modify their intermediate hosts' behaviour, presumably to increase transmission to their final host. The threespine stickleback (<i>Gasterosteus aculeatus</i>) is an intermediate host in the cestode <i>Schistocephalus solidus</i> life cycle, which ends in an avian host, and shows increased risky behaviours when infected. We studied brain gene expression profiles of sticklebacks infected with <i>S. solidus</i> to determine the proximal causes of these behavioural alterations. We show that infected fish have altered expression levels in genes involved in the inositol pathway. We thus tested the functional implication of this pathway and successfully rescued normal behaviours in infected sticklebacks using lithium exposure. We also show that exposed but uninfected fish have a distinct gene expression profile from both infected fish and control individuals, allowing us to separate gene activity related to parasite exposure from consequences of a successful infection. Finally, we find that Selective Serotonin Reuptake Inhibitor-treated sticklebacks and infected fish do not have similarly altered gene expression, despite their comparable behaviours, suggesting that the serotonin pathway is probably not the main driver of phenotypic changes in infected sticklebacks. Taken together, our results allow us to predict that if <i>S. solidus</i> directly manipulates its host, it could target the inositol pathway.
DOI: 10.6084/m9.figshare.13153919.v1
title: Complete behaviour dataset from Host behaviour alteration by its parasite: from brain gene expression to functional test

description: Many parasites with complex life cycles modify their intermediate hosts' behaviour, presumably to increase transmission to their final host. The threespine stickleback (<i>Gasterosteus aculeatus</i>) is an intermediate host in the cestode <i>Schistocephalus solidus</i> life cycle, which ends in an avian host, and shows increased risky behaviours when infected. We studied brain gene expression profiles of sticklebacks infected with <i>S. solidus</i> to determine the proximal causes of these behavioural alterations. We show that infected fish have altered expression levels in genes involved in the inositol pathway. We thus tested the functional implication of this pathway and successfully rescued normal behaviours in infected sticklebacks using lithium exposure. We also show that exposed but uninfected fish have a distinct gene expression profile from both infected fish and control individuals, allowing us to separate gene activity related to parasite exposure from consequences of a successful infection. Finally, we find that Selective Serotonin Reuptake Inhibitor-treated sticklebacks and infected fish do not have similarly altered gene expression, despite their comparable behaviours, suggesting that the serotonin pathway is probably not the main driver of phenotypic changes in infected sticklebacks. Taken together, our results allow us to predict that if <i>S. solidus</i> directly manipulates its host, it could target the inositol pathway.
DOI: 10.6084/m9.figshare.13153928
title: Dataset README from Host behaviour alteration by its parasite: from brain gene expression to functional test

description: Many parasites with complex life cycles modify their intermediate hosts' behaviour, presumably to increase transmission to their final host. The threespine stickleback (<i>Gasterosteus aculeatus</i>) is an intermediate host in the cestode <i>Schistocephalus solidus</i> life cycle, which ends in an avian host, and shows increased risky behaviours when infected. We studied brain gene expression profiles of sticklebacks infected with <i>S. solidus</i> to determine the proximal causes of these behavioural alterations. We show that infected fish have altered expression levels in genes involved in the inositol pathway. We thus tested the functional implication of this pathway and successfully rescued normal behaviours in infected sticklebacks using lithium exposure. We also show that exposed but uninfected fish have a distinct gene expression profile from both infected fish and control individuals, allowing us to separate gene activity related to parasite exposure from consequences of a successful infection. Finally, we find that Selective Serotonin Reuptake Inhibitor-treated sticklebacks and infected fish do not have similarly altered gene expression, despite their comparable behaviours, suggesting that the serotonin pathway is probably not the main driver of phenotypic changes in infected sticklebacks. Taken together, our results allow us to predict that if <i>S. solidus</i> directly manipulates its host, it could target the inositol pathway.
DOI: 10.17632/96p2n7fsh4.1
title: Data for: New Evidence on Non-Covalent Interactions in Crystalline Halo-Substituted Boron Difluoride Acetylacetonates from Vibrational Spectra, Model Calculations and Visualization Program Tools

description: These are raw data for the manuscript "NEW EVIDENCE ON NON-COVALENT INTERACTIONS IN CRYSTALLINE HALO-SUBSTITUTED BORON DIFLUORIDE ACETYLACETONATES FROM VIBRATIONAL SPECTRA, MODEL CALCULATIONS AND VISUALIZATION PROGRAM TOOLS" with vibrational band assignment for the a-substituted difluoride boron acrtylacetonates based on the dimer and tetramer model DFT calculations. Marker band wavenumbers in the tables printed in specific color for each of related normal vibrations.
DOI: 10.17632/n5smb3cvjx.1
title: Data for: Solvent dependent Zinc(Ⅱ) coordination polymers with 1,3,5-benzenetricarboxylic acid and selective photocatalytic degradation for organic dyes

description: Three CIF files of three coordination polymer.
DOI: 10.6084/m9.figshare.12383162
title: Going Viral, Binge-Watching, and Attention Cannibalism

description: Binge-watching behavior is modeled for a single season of an original program from a streaming service to understand and make predictions about how individuals watch newly released content. Viewers make two choices in binge watching. First, the onset when individuals begin viewing the program is modeled using a change point between epidemic viewing with a nonconstant hazard rate and endemic viewing with a constant hazard rate. Second, the time it takes for individuals to complete the full season is modeled using an expanded negative binomial hurdle model to account for both binge racers (who watch all episodes in a single day) and other viewers. With the rapid increase in original content for streaming services, network executives are interested in the decision of simultaneously releasing multiple original programs or staggering premiere dates. The two model results are used to investigate competing risks to determine how the amount of time between premieres impacts attention cannibalism, when a viewer takes a long time watching their first choice program and consequently never watches the second program.
DOI: 10.6084/m9.figshare.12383162.v1
title: Going Viral, Binge-Watching, and Attention Cannibalism

description: Binge-watching behavior is modeled for a single season of an original program from a streaming service to understand and make predictions about how individuals watch newly released content. Viewers make two choices in binge watching. First, the onset when individuals begin viewing the program is modeled using a change point between epidemic viewing with a nonconstant hazard rate and endemic viewing with a constant hazard rate. Second, the time it takes for individuals to complete the full season is modeled using an expanded negative binomial hurdle model to account for both binge racers (who watch all episodes in a single day) and other viewers. With the rapid increase in original content for streaming services, network executives are interested in the decision of simultaneously releasing multiple original programs or staggering premiere dates. The two model results are used to investigate competing risks to determine how the amount of time between premieres impacts attention cannibalism, when a viewer takes a long time watching their first choice program and consequently never watches the second program.
DOI: 10.6084/m9.figshare.6973643
title: A Time-Series Model for Underdispersed or Overdispersed Counts

description: It is common for time series of unbounded counts (that is, nonnegative integers) to display overdispersion relative to the Poisson. Such an overdispersed series can be modeled by a hidden Markov model with Poisson state-dependent distributions (a “Poisson–HMM”), since a Poisson–HMM allows for both overdispersion and serial dependence. Time series of underdispersed counts seems less common, but more awkward to model; a Poisson–HMM cannot cope with underdispersion. But if in a Poisson–HMM one replaces the Poisson distributions by Conway–Maxwell–Poisson distributions, one gets a class of models which can allow for under- or overdispersion (and serial dependence). In addition, this class can cope with the combination of slight overdispersion and substantial serial dependence, a combination that is apparently difficult for a Poisson–HMM to represent. We discuss the properties of this class of models, and use direct numerical maximization of likelihood to fit a range of models to three published series of counts which display underdispersion, and to a series which displays slight overdispersion plus substantial serial dependence. In addition, we illustrate how such models can be fitted without imputation when some observations are missing from the series, and how approximate standard errors of the parameter estimates can be found. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9915803.v2
title: Assessing Bayes Factor Surfaces Using Interactive Visualization and Computer Surrogate Modeling

description: Bayesian model selection provides a natural alternative to classical hypothesis testing based on <i>p</i>-values. While many articles mention that Bayesian model selection can be sensitive to prior specification on parameters, there are few practical strategies to assess and report this sensitivity. This article has two goals. First, we aim to educate the broader statistical community about the extent of potential sensitivity through visualization of the Bayes factor surface. The Bayes factor surface shows the value a Bayes factor takes as a function of user-specified hyperparameters. Second, we suggest surrogate modeling via Gaussian processes to visualize the Bayes factor surface in situations where computation is expensive. We provide three examples including an interactive R shiny application that explores a simple regression problem, a hierarchical linear model selection exercise, and finally surrogate modeling via Gaussian processes to a study of the influence of outliers in empirical finance. We suggest Bayes factor surfaces are valuable for scientific reporting since they (i) increase transparency by making instability in Bayes factors easy to visualize, (ii) generalize to simple and complicated examples, and (iii) provide a path for researchers to assess the impact of prior choice on modeling decisions in a wide variety of research areas. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9915803.v1
title: Assessing Bayes factor surfaces using interactive visualization and computer surrogate modeling

description: Bayesian model selection provides a natural alternative to classical hypothesis testing based on <i>p</i>-values. While many papers mention that Bayesian model selection can be sensitive to prior specification on parameters, there are few practical strategies to assess and report this sensitivity. This article has two goals. First, we aim to educate the broader statistical community about the extent of potential sensitivity through visualization of the Bayes factor surface. The Bayes factor surface shows the value a Bayes factor takes as a function of user-specified hyperparameters. Second, we suggest surrogate modeling via Gaussian processes to visualize the Bayes factor surface in situations where computation is expensive. We provide three examples including an interactive R shiny application that explores a simple regression problem, a hierarchical linear model selection exercise, and finally surrogate modeling via Gaussian processes to a study of the influence of outliers in empirical finance. We suggest Bayes factor surfaces are valuable for scientific reporting since they (i) increase transparency by making instability in Bayes factors easy to visualize, (ii) generalize to simple and complicated examples, and (iii) provide a path for researchers to assess the impact of prior choice on modeling decisions in a wide variety of research areas.
DOI: 10.6084/m9.figshare.6973643.v2
title: A Time-Series Model for Underdispersed or Overdispersed Counts

description: It is common for time series of unbounded counts (that is, nonnegative integers) to display overdispersion relative to the Poisson. Such an overdispersed series can be modeled by a hidden Markov model with Poisson state-dependent distributions (a “Poisson–HMM”), since a Poisson–HMM allows for both overdispersion and serial dependence. Time series of underdispersed counts seems less common, but more awkward to model; a Poisson–HMM cannot cope with underdispersion. But if in a Poisson–HMM one replaces the Poisson distributions by Conway–Maxwell–Poisson distributions, one gets a class of models which can allow for under- or overdispersion (and serial dependence). In addition, this class can cope with the combination of slight overdispersion and substantial serial dependence, a combination that is apparently difficult for a Poisson–HMM to represent. We discuss the properties of this class of models, and use direct numerical maximization of likelihood to fit a range of models to three published series of counts which display underdispersion, and to a series which displays slight overdispersion plus substantial serial dependence. In addition, we illustrate how such models can be fitted without imputation when some observations are missing from the series, and how approximate standard errors of the parameter estimates can be found. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9915803
title: Assessing Bayes Factor Surfaces Using Interactive Visualization and Computer Surrogate Modeling

description: Bayesian model selection provides a natural alternative to classical hypothesis testing based on <i>p</i>-values. While many articles mention that Bayesian model selection can be sensitive to prior specification on parameters, there are few practical strategies to assess and report this sensitivity. This article has two goals. First, we aim to educate the broader statistical community about the extent of potential sensitivity through visualization of the Bayes factor surface. The Bayes factor surface shows the value a Bayes factor takes as a function of user-specified hyperparameters. Second, we suggest surrogate modeling via Gaussian processes to visualize the Bayes factor surface in situations where computation is expensive. We provide three examples including an interactive R shiny application that explores a simple regression problem, a hierarchical linear model selection exercise, and finally surrogate modeling via Gaussian processes to a study of the influence of outliers in empirical finance. We suggest Bayes factor surfaces are valuable for scientific reporting since they (i) increase transparency by making instability in Bayes factors easy to visualize, (ii) generalize to simple and complicated examples, and (iii) provide a path for researchers to assess the impact of prior choice on modeling decisions in a wide variety of research areas. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6973643.v1
title: A time-series model for underdispersed or overdispersed counts

description: It is common for time series of unbounded counts (that is, nonnegative integers) to display overdispersion relative to the Poisson. Such an overdispersed series can be modeled by a hidden Markov model with Poisson state-dependent distributions (a ‘Poisson–HMM’), since a Poisson–HMM allows for both overdispersion and serial dependence. Time series of underdispersed counts seem less common, but more awkward to model; a Poisson–HMM cannot cope with underdispersion. But if in a Poisson–HMM one replaces the Poisson distributions by Conway–Maxwell–Poisson distributions, one gets a class of models which can allow for under- or overdispersion (and serial dependence). In addition, this class can cope with the combination of slight overdispersion and substantial serial dependence, a combination that is apparently difficult for a Poisson–HMM to represent. We discuss the properties of this class of models, and use direct numerical maximization of likelihood to fit a range of models to three published series of counts which display underdispersion, and to a series which displays slight overdispersion plus substantial serial dependence. In addition, we illustrate how such models can be fitted without imputation when some observations are missing from the series, and how approximate standard errors of the parameter estimates can be found.
DOI: 10.4119/unibi/2946741
title: English Novels of the Long Eighteenth Century (Dataset)

description: This corpus consists of novels published during the Long Eighteenth Century in England. They can be dated to the period between 1680 and 1820. Since the data is representing works from British literature, all authors are either from Great Britain or Ireland. The selected novels are available in .txt format for reading and further analysis.<br> The data used to support the findings of the research project "English Novels of the Long Eighteenth Century" (SFB 1288 B5) have been deposited in the DKAN platform of the Collaborative Research Center 1288 (SFB 1288). It is available at [https://dkan.sfb1288.uni-bielefeld.de/dataset/2946741](https://dkan.sfb1288.uni-bielefeld.de/dataset/2946741) for download.
DOI: 10.6084/m9.figshare.13153952
title: Data

description: Data describing travel times from sections to hospital using emergency medical services, in the Lisbon Metropolitan Area. The dataset includes the material deprivation index.
DOI: 10.6084/m9.figshare.13153952.v1
title: Data

description: Data describing travel times from sections to hospital using emergency medical services, in the Lisbon Metropolitan Area. The dataset includes the material deprivation index.
DOI: 10.4119/unibi/2946744
title: Utopias of the 15th century to present (Dataset)

description: Corpus consisting of English utopias ranging from the 15th century till the present. The data used to support the findings of the research project [C03 | The Conceptual History of Comparison] have been deposited in the DKAN platform of the Collaborative Research Center 1288 (SFB 1288). It is available at https://dkan.sfb1288.uni-bielefeld.de/dataset/2946744 for download.
DOI: 10.5519/qd.a6192bfm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (65 records)
DOI: 10.6084/m9.figshare.13153868
title: Supplementary Material for: The Propensity to Form Biofilm in vitro by <b><i>Staphylococcus aureus</i></b> Strains Isolated from the Anterior Nares of Patients with Atopic Dermatitis: Clinical Associations

description: <b><i>Background:</i></b> Atopic dermatitis is a chronic inflammatory dermatosis with complex pathogenesis. The skin microbiome in atopic dermatitis is dominated by <i>Staphylococcus aureus</i> which shows the ability to produce biofilm. <b><i>Objectives:</i></b> The aim of this work was to assess the influence of <i>S. aureus</i> biofilm on the course of atopic dermatitis. <b><i>Methods:</i></b> Disease severity was evaluated based on the SCORAD index in 56 adult patients with atopic dermatitis. Microtiter plate assay of the propensity to form biofilm was performed on <i>S. aureus</i> strains isolated from the anterior nares, lesional skin, and nonlesional skin. Microbiological results were correlated to the clinical parameters and total IgE concentration. <b><i>Results:</i></b> Biofilm-producing strains of <i>S. aureus</i> were identified in 76.3% (29/38) and 79.1% (34/43) of samples from the anterior nares and lesional skin, respectively (<i>p</i> &gt; 0.05), and in 48.5% (16/33) of samples from nonlesional skin (<i>p</i> &lt; 0.03). Patients colonized by biofilm-producing strains of <i>S. aureus</i> within the anterior nares showed statistically higher mean values of total and objective SCORAD and its components (extent, dryness), and of the largest extent of skin lesions during the flares in the last year when compared to patients colonized by non-biofilm-producing strains. Carriage of biofilm-producing <i>S. aureus</i> on lesional skin was associated with higher mean values of the extent of skin lesions during stable periods of the disease. <b><i>Conclusions:</i></b> The results of this study may suggest a relationship between the production of biofilm by <i>S. aureus</i> strains colonizing the anterior nares and the course of atopic dermatitis. Biofilm seems crucial for dispersal and persistent colonization of large areas of the skin by this pathogen. Destruction of <i>S. aureus</i> biofilm could positively affect the course of atopic dermatitis.
DOI: 10.6084/m9.figshare.13153868.v1
title: Supplementary Material for: The Propensity to Form Biofilm in vitro by <b><i>Staphylococcus aureus</i></b> Strains Isolated from the Anterior Nares of Patients with Atopic Dermatitis: Clinical Associations

description: <b><i>Background:</i></b> Atopic dermatitis is a chronic inflammatory dermatosis with complex pathogenesis. The skin microbiome in atopic dermatitis is dominated by <i>Staphylococcus aureus</i> which shows the ability to produce biofilm. <b><i>Objectives:</i></b> The aim of this work was to assess the influence of <i>S. aureus</i> biofilm on the course of atopic dermatitis. <b><i>Methods:</i></b> Disease severity was evaluated based on the SCORAD index in 56 adult patients with atopic dermatitis. Microtiter plate assay of the propensity to form biofilm was performed on <i>S. aureus</i> strains isolated from the anterior nares, lesional skin, and nonlesional skin. Microbiological results were correlated to the clinical parameters and total IgE concentration. <b><i>Results:</i></b> Biofilm-producing strains of <i>S. aureus</i> were identified in 76.3% (29/38) and 79.1% (34/43) of samples from the anterior nares and lesional skin, respectively (<i>p</i> &gt; 0.05), and in 48.5% (16/33) of samples from nonlesional skin (<i>p</i> &lt; 0.03). Patients colonized by biofilm-producing strains of <i>S. aureus</i> within the anterior nares showed statistically higher mean values of total and objective SCORAD and its components (extent, dryness), and of the largest extent of skin lesions during the flares in the last year when compared to patients colonized by non-biofilm-producing strains. Carriage of biofilm-producing <i>S. aureus</i> on lesional skin was associated with higher mean values of the extent of skin lesions during stable periods of the disease. <b><i>Conclusions:</i></b> The results of this study may suggest a relationship between the production of biofilm by <i>S. aureus</i> strains colonizing the anterior nares and the course of atopic dermatitis. Biofilm seems crucial for dispersal and persistent colonization of large areas of the skin by this pathogen. Destruction of <i>S. aureus</i> biofilm could positively affect the course of atopic dermatitis.