cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5876169
title: Additional file 10: of Effect of heat shock on hot water plumbing microbiota and Legionella pneumophila control

description: Table S3. Simplified model for estimating proportion of directly impacted water along time. “Remained” is the remaining “original” heat shocked water within water heater and recirculating line. Assumptions include: water heater and recirculating line is a complete mixed system with no (little) change between distal pipe and recirculating line; no microbial death or growth; no interference with biofilm; only considering physical mixing. Recirculating line sampling not accounted for. (XLS 58 kb)
DOI: 10.6084/m9.figshare.5876169.v1
title: Additional file 10: of Effect of heat shock on hot water plumbing microbiota and Legionella pneumophila control

description: Table S3. Simplified model for estimating proportion of directly impacted water along time. “Remained” is the remaining “original” heat shocked water within water heater and recirculating line. Assumptions include: water heater and recirculating line is a complete mixed system with no (little) change between distal pipe and recirculating line; no microbial death or growth; no interference with biofilm; only considering physical mixing. Recirculating line sampling not accounted for. (XLS 58 kb)
DOI: 10.6084/m9.figshare.5876163
title: Additional file 1: Table S4. of On Burkholderiales order microorganisms and cystic fibrosis in Russia

description: Characteristics of the patients, included in the microbiome analysis. FEV1,% - percentage of predicted forced expiratory volume in 1Â s; SD - substantial decline; S â stable. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5876163.v1
title: Additional file 1: Table S4. of On Burkholderiales order microorganisms and cystic fibrosis in Russia

description: Characteristics of the patients, included in the microbiome analysis. FEV1,% - percentage of predicted forced expiratory volume in 1Â s; SD - substantial decline; S â stable. (XLSX 13 kb)
DOI: 10.6084/m9.figshare.5876160
title: MOESM1 of Cinnamomum zeylanicum bark essential oil induces cell wall remodelling and spindle defects in Candida albicans

description: Additional file 1: Table S1. Chemical composition of CNB oil.
DOI: 10.6084/m9.figshare.5876160.v1
title: MOESM1 of Cinnamomum zeylanicum bark essential oil induces cell wall remodelling and spindle defects in Candida albicans

description: Additional file 1: Table S1. Chemical composition of CNB oil.
DOI: 10.6084/m9.figshare.5876154
title: MOESM3 of Transcriptomic response in Acropora muricata under acute temperature stress follows preconditioned seasonal temperature fluctuations

description: Additional file 3: Table S1. Assembly results of transcripts and statistical analyses of transcripts between different samples.
DOI: 10.6084/m9.figshare.5876154.v1
title: MOESM3 of Transcriptomic response in Acropora muricata under acute temperature stress follows preconditioned seasonal temperature fluctuations

description: Additional file 3: Table S1. Assembly results of transcripts and statistical analyses of transcripts between different samples.
DOI: 10.6084/m9.figshare.5876145
title: Additional file 2: Table S1 of Precise genome-wide mapping of single nucleosomes and linkers in vivo

description: The coordinates of the dominant positions of +1 and â 1 nucleosomes identified in this study. (XLSX 396 kb)
DOI: 10.6084/m9.figshare.5876145.v1
title: Additional file 2: Table S1 of Precise genome-wide mapping of single nucleosomes and linkers in vivo

description: The coordinates of the dominant positions of +1 and â 1 nucleosomes identified in this study. (XLSX 396 kb)
DOI: 10.6084/m9.figshare.5876064
title: Multiresolution Consensus Clustering in Networks - Network Data Sets

description: Network data sets used in:<br>Multiresolution Consensus Clustering in Networks, Scientific Reports, https://doi.org/10.1038/s41598-018-21352-7<br><br><b>Data Sets:</b><br>Each '.mat' file contains the adjacency matrix 'A', reference partitions 'S' and a label for the reference partition 'gtlabels'. Some files have additional information.<br>Zachary Karate Club<i>File</i>: 'karate.mat'<i>Citation</i>: Zachary, W. W. An information flow model for conflict and fission in small groups. <i>Journal of Anthropological Research</i> <b>33</b>, 452–473 (1977).<i>Source: </i>http://www-personal.umich.edu/~mejn/netdata/<br>College Football<i>File:</i> 'football.mat'<i>Citations</i>: Girvan, M. & Newman, M. E. J. Community structure in social and biological networks. <i>Proceedings of the National Academy of Sciences</i> <b>99</b>, 7821–7826 (2002).Evans, T. S. Clique graphs and overlapping communities. <i>Journal of Statistical Mechanics: Theory and Experiment</i> <b>2010</b>, P12037 (2010).<br><i>Source: </i>https://doi.org/10.6084/m9.figshare.93179.v2<br>Political Blogs<i>File: </i>'polblogs.mat'<i>Citation</i>: Adamic, L. A. & Glance, N. The political blogosphere and the 2004 U.S. election: Divided they blog. In <i>Proceedings of the 3rd International Workshop on Link Discovery</i>, LinkKDD ’05, 36–43 (ACM, New York, NY, USA 2005).<i>Source</i>: http://www-personal.umich.edu/~mejn/netdata/<br>Political Books<i>File</i>: 'polbooks.mat'<i>Citation</i>: Krebs, V. Books about US politics.<i>Source</i>: http://www-personal.umich.edu/~mejn/netdata/<br>Human Structural Brain<i>File:</i> 'DSI_network.mat'<i>Citation: </i>Hagmann, P. et al. Mapping the structural core of human cerebral cortex. <i>PLOS Biology</i> <b>6</b>, 1–15 (2008).<i>Raw Data File: '</i>DSI_release2_2011.mat'<br>Rat Structural Brain<i>File: </i>'rat_cortex.mat'<i>Additional Data:</i> has extra variable 'labels' which contain the abbreviated names of the anatomical regions<i>Citation: </i>Bota, M., Sporns, O. & Swanson, L. W. Architecture of the cerebral cortical association connectome underlying cognition. <i>Proceedings of the National Academy of Sciences </i><b>112</b>, E2093–E2101 (2015).<br>
DOI: 10.6084/m9.figshare.5876061.v2
title: Supplemental_Material_Novel_FoV_MMS

description: This document contains 3 tables which are 3 design examples used in our paper titled as "Novel field of view in monocentric multiscale cameras". The first table shows prescription of a ring FoV MMS lens, the second is prescription of multifocal MMS lens design, and the final one shows prescription of 360 horizontal FoV MMS lens with interleaving strategy.
DOI: 10.6084/m9.figshare.5875734
title: Data for 'Dynamical origins of heat capacity changes in enzyme catalysed reactions'

description: Dynamical origins of heat capacity changes in enzyme catalysed reactions<br>Marc W van der Kamp, Erica J. Prentice, Kirsty L. Kraakmann, Michael Connolly, Adrian J. Mulholland & Vickery L. Arcus<br>School of Biochemistry, Biomedical Sciences Building, University Walk, University of Bristol, BS8 1TD, UK.Centre of Computational Chemistry, School of Chemistry, Cantock's Close, University of Bristol, BS8 1TS, UK.School of Science, University of Waikato, Hamilton, New Zealand.<br>The data files contained in this repository are as follows: <br>1a. Input coordinates (starting structures) in PDB format are named as enzyme_state.pdb. <br>1b. Input coordinates are named as enzyme_state.inpcrd and are in the standard Amber format (generated with Amber12). <br>2. Topology and parameter files are named as enzyme_state.prmtop and are also in standard Amber format (generated with Amber12).<br>3. Input files for the MD simulations are in the subdirectories KSI_md_input_files and MalL_md_input files. Input files are included for the equilibration, heating and production runs of molecular dynamics, which were performed in this order: a. minsolv.i b. mdsolv.i c. min.i d. heat.i e. npt_release1.i f. npt_release2.i g. npt_release3.i h. npt_release4.i i. eq_npt.i j. md10.i For KSI, a restraint was used in both RS and IS states, which is included in the file r7.RST. A restraint was also used in the MalL states (RS and TSA), which is included in the file d_com.rst. All input files are in the standard Amber format (see e.g. Amber16.pdf manual). <br>
DOI: 10.6084/m9.figshare.5875734.v1
title: Data for 'Dynamical origins of heat capacity changes in enzyme catalysed reactions'

description: Dynamical origins of heat capacity changes in enzyme catalysed reactions<br>Marc W van der Kamp, Erica J. Prentice, Kirsty L. Kraakmann, Michael Connolly, Adrian J. Mulholland & Vickery L. Arcus<br>School of Biochemistry, Biomedical Sciences Building, University Walk, University of Bristol, BS8 1TD, UK.Centre of Computational Chemistry, School of Chemistry, Cantock's Close, University of Bristol, BS8 1TS, UK.School of Science, University of Waikato, Hamilton, New Zealand.<br>The data files contained in this repository are as follows: <br>1a. Input coordinates (starting structures) in PDB format are named as enzyme_state.pdb. <br>1b. Input coordinates are named as enzyme_state.inpcrd and are in the standard Amber format (generated with Amber12). <br>2. Topology and parameter files are named as enzyme_state.prmtop and are also in standard Amber format (generated with Amber12).<br>3. Input files for the MD simulations are in the subdirectories KSI_md_input_files and MalL_md_input files. Input files are included for the equilibration, heating and production runs of molecular dynamics, which were performed in this order: a. minsolv.i b. mdsolv.i c. min.i d. heat.i e. npt_release1.i f. npt_release2.i g. npt_release3.i h. npt_release4.i i. eq_npt.i j. md10.i For KSI, a restraint was used in both RS and IS states, which is included in the file r7.RST. A restraint was also used in the MalL states (RS and TSA), which is included in the file d_com.rst. All input files are in the standard Amber format (see e.g. Amber16.pdf manual). <br>
DOI: 10.6084/m9.figshare.5874159
title: FiPy Benchmark 3 version 2

description: Phase field benchmark 3 data upload<br><br>
DOI: 10.6084/m9.figshare.5874159.v1
title: FiPy Benchmark 3 version 2

description: Phase field benchmark 3 data upload<br><br>
DOI: 10.6084/m9.figshare.5874081
title: Role of Acid-Sensing Ion Channels in Hypoxia- and Hypercapnia-Induced 1 Ventilatory Responses.xlsx

description: The data included in this entry include two types of data: whole-body plethysmography data for ventilatory responses, and blood gas data obtained from femoral artery blood samples.<br><br>The plethysmography shows the ventilatory response of WT, ASIC1KO, ASIC2KO, and ASIC3KO mice to hypoxia and hypercapnia. This data was analyzed according to the methods section of the manuscript to obtain ventilatory frequency, tidal volume, and minute ventilation. The blood gas data include arterial O2 and CO2 saturation as well as arterial pH.<br>
DOI: 10.6084/m9.figshare.5874081.v1
title: Role of Acid-Sensing Ion Channels in Hypoxia- and Hypercapnia-Induced 1 Ventilatory Responses.xlsx

description: The data included in this entry include two types of data: whole-body plethysmography data for ventilatory responses, and blood gas data obtained from femoral artery blood samples.<br><br>The plethysmography shows the ventilatory response of WT, ASIC1KO, ASIC2KO, and ASIC3KO mice to hypoxia and hypercapnia. This data was analyzed according to the methods section of the manuscript to obtain ventilatory frequency, tidal volume, and minute ventilation. The blood gas data include arterial O2 and CO2 saturation as well as arterial pH.<br>
DOI: 10.6084/m9.figshare.5874045
title: Dataset for: Leptin attenuates D2 receptor-mediated inhibition of putative ventral tegmental area dopaminergic neurons

description: Obesity causes hyperleptinemia. We have previously shown that D2 receptor-mediated inhibition of ventral tegmental area (VTA) dopaminergic neurons is attenuated in diet-induced mice with obesity. Consequently, we hypothesized that high concentrations of serum leptin during obesity might modulate D2 receptor-mediated effects on VTA dopaminergic neurons. To investigate our hypothesis, we examined leptin effects on D2 receptor-mediated inhibition of putative VTA dopaminergic neurons from lean mice using electrophysiological techniques. Leptin (100 nM) directly inhibited spontaneous firing in 71% of putative VTA dopaminergic neurons (leptin-responsive), while the remaining 29% of neurons were leptin-non-responsive. In 41% of leptin-responsive neurons, leptin attenuated the reduced firing rate produced by quinpirole (100 nM), while the remaining 59% of neurons exhibited no effect of leptin. In leptin-non-responsive neurons, no significant leptin-induced effect was observed on reduced firing rate produced by quinpirole. In leptin-responsive neurons with positive leptin-induced attenuation of quinpirole effects, leptin-induced attenuation persisted for &gt; 20 min, while no such persistent attenuation was observed in other types of neurons. In conclusion, leptin attenuates D2 receptor-mediated inhibition in a subpopulation of putative VTA dopaminergic neurons. We suggest that leptin directly decreases, and indirectly increases, excitability of VTA dopaminergic neurons. In turn, this may contribute to a change in feeding behavior through the mesolimbic dopaminergic system during development of obesity.
DOI: 10.6084/m9.figshare.5874045.v1
title: Dataset for: Leptin attenuates D2 receptor-mediated inhibition of putative ventral tegmental area dopaminergic neurons

description: Obesity causes hyperleptinemia. We have previously shown that D2 receptor-mediated inhibition of ventral tegmental area (VTA) dopaminergic neurons is attenuated in diet-induced mice with obesity. Consequently, we hypothesized that high concentrations of serum leptin during obesity might modulate D2 receptor-mediated effects on VTA dopaminergic neurons. To investigate our hypothesis, we examined leptin effects on D2 receptor-mediated inhibition of putative VTA dopaminergic neurons from lean mice using electrophysiological techniques. Leptin (100 nM) directly inhibited spontaneous firing in 71% of putative VTA dopaminergic neurons (leptin-responsive), while the remaining 29% of neurons were leptin-non-responsive. In 41% of leptin-responsive neurons, leptin attenuated the reduced firing rate produced by quinpirole (100 nM), while the remaining 59% of neurons exhibited no effect of leptin. In leptin-non-responsive neurons, no significant leptin-induced effect was observed on reduced firing rate produced by quinpirole. In leptin-responsive neurons with positive leptin-induced attenuation of quinpirole effects, leptin-induced attenuation persisted for &gt; 20 min, while no such persistent attenuation was observed in other types of neurons. In conclusion, leptin attenuates D2 receptor-mediated inhibition in a subpopulation of putative VTA dopaminergic neurons. We suggest that leptin directly decreases, and indirectly increases, excitability of VTA dopaminergic neurons. In turn, this may contribute to a change in feeding behavior through the mesolimbic dopaminergic system during development of obesity.
DOI: 10.6084/m9.figshare.5873979
title: Bayesian Latent Class Analysis Tutorial

description: This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R. The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.
DOI: 10.6084/m9.figshare.5873979.v1
title: Bayesian Latent Class Analysis Tutorial

description: This article is a how-to guide on Bayesian computation using Gibbs sampling, demonstrated in the context of Latent Class Analysis (LCA). It is written for students in quantitative psychology or related fields who have a working knowledge of Bayes Theorem and conditional probability and have experience in writing computer programs in the statistical language R. The overall goals are to provide an accessible and self-contained tutorial, along with a practical computation tool. We begin with how Bayesian computation is typically described in academic articles. Technical difficulties are addressed by a hypothetical, worked-out example. We show how Bayesian computation can be broken down into a series of simpler calculations, which can then be assembled together to complete a computationally more complex model. The details are described much more explicitly than what is typically available in elementary introductions to Bayesian modeling so that readers are not overwhelmed by the mathematics. Moreover, the provided computer program shows how Bayesian LCA can be implemented with relative ease. The computer program is then applied in a large, real-world data set and explained line-by-line. We outline the general steps in how to extend these considerations to other methodological applications. We conclude with suggestions for further readings.
DOI: 10.6084/m9.figshare.5873838
title: 2D Landmarks.txt

description: 2D Landmark Data for cut marks produced at an angle of both 45º and 90º
DOI: 10.6084/m9.figshare.5873838.v1
title: 2D Landmarks.txt

description: 2D Landmark Data for cut marks produced at an angle of both 45º and 90º
DOI: 10.6084/m9.figshare.5873835
title: 90º Measurements of Profile.xlsx

description: Measurements of Cut Mark Profiles - Incisions produced at 90º
DOI: 10.6084/m9.figshare.5873832
title: 3D Landmarks.txt

description: 3D Landmark Data for cut marks produced at an angle of both 45º and 90º
DOI: 10.6084/m9.figshare.5873829
title: 45º Measurements of Profile.xlsx

description: Measurements of Cut Mark Profiles - Incisions produced at 45º
DOI: 10.6084/m9.figshare.5873823
title: Dataset for Conflicting Statements Detection in Text

description: The files are from three different. One of the three datasets (SemEval) is downloaded from SemEval-2014 which was an international workshop on semantic evaluation conducted in Dublin (Ireland). Another dataset is same dataset (Stanford) as used by Marneffe et al. for their work on finding contradictions in text. Another dataset that we use is the PHEME RTE (Recognizing Textual Entailment). The attached dataset consists of annotated dataset into four different types of contradictions. It consists of intermediate results and feature values on our work on conflicting statements detection in text.
DOI: 10.6084/m9.figshare.5873757
title: Kirkwood–Buff integrals of finite systems: shape effects

description: The Kirkwood–Buff (KB) theory provides an important connection between microscopic density fluctuations in liquids and macroscopic properties. Recently, Krüger <i>et al.</i> derived equations for KB integrals for finite subvolumes embedded in a reservoir. Using molecular simulation of finite systems, KB integrals can be computed either from density fluctuations inside such subvolumes, or from integrals of radial distribution functions (RDFs). Here, based on the second approach, we establish a framework to compute KB integrals for subvolumes with arbitrary convex shapes. This requires a geometric function <i>w</i>(<i>x</i>) which depends on the shape of the subvolume, and the relative position inside the subvolume. We present a numerical method to compute <i>w</i>(<i>x</i>) based on Umbrella Sampling Monte Carlo (MC). We compute KB integrals of a liquid with a model RDF for subvolumes with different shapes. KB integrals approach the thermodynamic limit in the same way: for sufficiently large volumes, KB integrals are a linear function of area over volume, which is independent of the shape of the subvolume.
DOI: 10.6084/m9.figshare.5873757.v1
title: Kirkwood–Buff integrals of finite systems: shape effects

description: The Kirkwood–Buff (KB) theory provides an important connection between microscopic density fluctuations in liquids and macroscopic properties. Recently, Krüger <i>et al.</i> derived equations for KB integrals for finite subvolumes embedded in a reservoir. Using molecular simulation of finite systems, KB integrals can be computed either from density fluctuations inside such subvolumes, or from integrals of radial distribution functions (RDFs). Here, based on the second approach, we establish a framework to compute KB integrals for subvolumes with arbitrary convex shapes. This requires a geometric function <i>w</i>(<i>x</i>) which depends on the shape of the subvolume, and the relative position inside the subvolume. We present a numerical method to compute <i>w</i>(<i>x</i>) based on Umbrella Sampling Monte Carlo (MC). We compute KB integrals of a liquid with a model RDF for subvolumes with different shapes. KB integrals approach the thermodynamic limit in the same way: for sufficiently large volumes, KB integrals are a linear function of area over volume, which is independent of the shape of the subvolume.
DOI: 10.6084/m9.figshare.5873703
title: Pax6 functions in development and evolution of amniote brains

description: This is the datasets to produce the main text figures and supplementary figures in the study of Yamashita et al.(2018).<br>The evolution of unique organ structures is associated with changes in conserved developmental programs. However, functional conservation and variation of homologous transcription factors (TFs) that dictate species-specific cellular dynamics have remained elusive. Here, we dissect shared and divergent functions of Pax6 during amniote brain development. Comparative functional analyses revealed that neurogenic function of Pax6 is highly conserved in the developing mouse and chick pallium, while stage-specific binary functions of Pax6 in neurogenesis are unique to mouse neuronal progenitors, which are consistent with temporal regulation of Notch signaling. Furthermore, we identified that Pax6-dependent enhancer activity of Dbx1 is extensively conserved between mammals and chick, although Dbx1 expression in the developing pallium are highly divergent in these species. Our results suggest that spatio-temporal changes in Pax6-dependent regulatory programs contributed to species-specific neurogenic patterns in mammalian and avian lineages, which underlie morphological divergence of amniote pallial architectures.<br>