cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6280672
title: Raw Data for the article: Klebsiella pneumoniae Lipopolysaccharides Serotype O2afg Induce Poor Inflammatory Immune Responses Ex Vivo

description: Currently, <em>Klebsiella pneumoniae</em> is a pathogen of clinical relevance due to its plastic ability of acquiring resistance genes to multiple antibiotics. During <em>K. pneumoniae</em> infections, lipopolysaccharides (LPS) play an ambiguous role as they both activate immune responses but can also play a role in immune evasion. The LPS O2a and LPS O2afg serotypes are prevalent in most multidrug resistant <em>K. pneumoniae</em> strains. Thus, we sought to understand if those two particular LPS serotypes were involved in a mechanism of immune evasion. We have extracted LPS (serotypes O1, O2a and O2afg) from <em>K. pneumoniae</em> strains and, using human monocytes ex vivo, we assessed the ability of those LPS antigens to induce the production of pro-inflammatory cytokines and chemokines. We observed that, when human monocytes are incubated with LPS serotypes O1, O2a or O2afg strains, O2afg and, to a lesser extent, O2a but not O1 failed to elicit the production of pro-inflammatory cytokines and chemokines, which suggests a role in immune evasion. Our preliminary data also shows that nuclear translocation of NF-κB, a process which regulates an immune response against infections, occurs in monocytes incubated with LPS O1 and, to a smaller extent, with LPS O2a, but not with the LPS serotype O2afg. Our results indicate that multidrug resistant <em>K. pneumoniae</em> expressing LPS O2afg serotypes avoid an initial inflammatory immune response and, consequently, are able to systematically spread inside the host unharmed, which results in the several pathologies associated with this bacterium.
DOI: 10.15482/usda.adc/1524725
title: Effect of Holstein genotype on immune response to an intramammary Escherichia coli challenge
DOI: 10.5281/zenodo.6281075
title: msd-errors - Random walk data

description: The data related to the random walk components of the msd-error work, including truly random and temporarily anti-correlated random walks at a series of system and step size. These have either be analysed numerically or analytically (using kinisi, WLS, or OLS).<br><br>Created using showyourwork from this GitHub repo.<br>
DOI: 10.6084/m9.figshare.19236510
title: BB_R_S_raw_snps_and_indels_2.vcf

description: The data represents the variants obtained by whole genome re-sequencing alignment of two species of <i>C. moschata, </i>Papaya ringspot virus resistance (Nigerian Local) and Papaya Ringspot virus susceptible (Butterbush).
DOI: 10.5281/zenodo.5944854
title: Dataset from a survey on stored data of meals served in healthcare facilities in Italy and Germany.

description: Dataset from a survey on stored data of meals served in healthcare facilities in Italy and Germany.
DOI: 10.5281/zenodo.5944853
title: Dataset from a survey on stored data of meals served in healthcare facilities in Italy and Germany.

description: Dataset from a survey on stored data of meals served in healthcare facilities in Italy and Germany.
DOI: 10.5281/zenodo.6279838
title: DataZhengzhou

description: Data for the manuscript 2022GL098401. The time of nc data is universal time.
DOI: 10.5281/zenodo.6279736
title: DataZhengzhou

description: Data for the manuscript 2022GL098401. The time of nc data is universal time.
DOI: 10.6084/m9.figshare.19236714
title: Supplementary files: Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials

description: Supplementary files: Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials
DOI: 10.6084/m9.figshare.19236714.v1
title: Supplementary files: Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials

description: Supplementary files: Seroconversion rates among different designs of COVID-19 vaccines: a network meta-analysis of randomized controlled trials
DOI: 10.5281/zenodo.6281444
title: Replication package for: We are all behavioral, more or less: A taxonomy of consumer decision making

description: Code and data for reproducing tables in the paper.
DOI: 10.5281/zenodo.5948725
title: Dataset of "Towards Artefact Aware Human Motion Capture using Inertial Sensors Integrated into Loose Clothing"

description: This dataset was used in the publication:<br> <strong>Towards Artefact Aware Human Motion Capture using Inertial Sensors Integrated into Loose Clothing</strong><br> presented at the IEEE International Conference on Robotics and Automation 2022 <strong>Abstract:</strong><br> Inertial motion capture has become an attractive alternative to optical motion capture for human joint angle estimation outside the laboratory. Usually inertial sensors are assumed to be tightly fixed to the body segments, which can be cumbersome regarding setup-time and ease-of-use. However, integrating the sensors directly into clothing, usually, results in additional clothing motion relative to the motion of the underlying bones that should be captured.<br> In this work we propose the <em>Difference Mapping</em> distributions approach that corrects the segment orientations of a given inertial motion capture system that assumes tightly coupled sensors.<br> The approach allows to reduce the joint angle errors due to clothing artefacts by at least 77.2 percent for people with similar morphology performing a similar task as seen in the training data, including an ergonomic assessments scenario at work places with 10 participants. <br> Moreover, we show that the uncertainty of the distribution can be used to measure the reliability of the predicted map if e.g. the motion is further away from the training data to allow for an artefact aware inertial motion tracking approach.<br> The experimental data for this study is available online <strong>Data structure:</strong><br> The data contains trials of 12 subjects for different motions, wearing at the same time a tight setup with inertial sensors and a loose working suit with integrated inertial sensors. It contains the raw IMU data, raw Magnetometer data and the estimated segment orientations using a Sensor Fusion engine provided by Sci-Track.<br> Please note, that in the publication only the first 10 subjects were used and the upper body information was used only. The Sternum sensor of the tight setup of subjects 11, 12 and 13 tilted slowly during the long-term measurements. For this reason only 10 subjects were included in the study. However all remaining sensor of the tight setup were not tilted during recording. In particular the lower body recordings of all subjects are not corrupted.<br> <br> Code samples, a visualizer and further useful information is provided under the following git repository:<br> https://github.com/lorenzcsunikl/Dataset-of-Artefact-Aware-Human-Motion-Capture-using-Inertial-Sensors-Integrated-into-Loose-Clothing
description: Code Samples how to access the data and how to work on it is available under: https://github.com/lorenzcsunikl/Dataset-of-Artefact-Aware-Human-Motion-Capture-using-Inertial-Sensors-Integrated-into-Loose-Clothing
DOI: 10.5281/zenodo.5948724
title: Dataset of "Towards Artefact Aware Human Motion Capture using Inertial Sensors Integrated into Loose Clothing"

description: This dataset was used in the publication:<br> <strong>Towards Artefact Aware Human Motion Capture using Inertial Sensors Integrated into Loose Clothing</strong><br> presented at the IEEE International Conference on Robotics and Automation 2022 <strong>Abstract:</strong><br> Inertial motion capture has become an attractive alternative to optical motion capture for human joint angle estimation outside the laboratory. Usually inertial sensors are assumed to be tightly fixed to the body segments, which can be cumbersome regarding setup-time and ease-of-use. However, integrating the sensors directly into clothing, usually, results in additional clothing motion relative to the motion of the underlying bones that should be captured.<br> In this work we propose the <em>Difference Mapping</em> distributions approach that corrects the segment orientations of a given inertial motion capture system that assumes tightly coupled sensors.<br> The approach allows to reduce the joint angle errors due to clothing artefacts by at least 77.2 percent for people with similar morphology performing a similar task as seen in the training data, including an ergonomic assessments scenario at work places with 10 participants. <br> Moreover, we show that the uncertainty of the distribution can be used to measure the reliability of the predicted map if e.g. the motion is further away from the training data to allow for an artefact aware inertial motion tracking approach.<br> The experimental data for this study is available online <strong>Data structure:</strong><br> The data contains trials of 12 subjects for different motions, wearing at the same time a tight setup with inertial sensors and a loose working suit with integrated inertial sensors. It contains the raw IMU data, raw Magnetometer data and the estimated segment orientations using a Sensor Fusion engine provided by Sci-Track.<br> Please note, that in the publication only the first 10 subjects were used and the upper body information was used only. The Sternum sensor of the tight setup of subjects 11, 12 and 13 tilted slowly during the long-term measurements. For this reason only 10 subjects were included in the study. However all remaining sensor of the tight setup were not tilted during recording. In particular the lower body recordings of all subjects are not corrupted.<br> <br> Code samples, a visualizer and further useful information is provided under the following git repository:<br> https://github.com/lorenzcsunikl/Dataset-of-Artefact-Aware-Human-Motion-Capture-using-Inertial-Sensors-Integrated-into-Loose-Clothing
description: Code Samples how to access the data and how to work on it is available under: https://github.com/lorenzcsunikl/Dataset-of-Artefact-Aware-Human-Motion-Capture-using-Inertial-Sensors-Integrated-into-Loose-Clothing
DOI: 10.5281/zenodo.6281750
title: Prediction and realisation of high mobility and degenerate p-type conductivity in CaCuP thin films Dataset

description: Experimental and computational datasets for this publication, including README files. To unzip, in the command line paste the following command: tar -xzvf cacup_data_repository_v2.tar.gz And repeat the command: tar -xzvf &lt;file.tar.gz&gt; for each necessary tar file. For any issues with accessibility, please email joe.willis.15@ucl.ac.uk.
DOI: 10.5281/zenodo.5834307
title: Prediction and realisation of high mobility and degenerate p-type conductivity in CaCuP thin films Dataset

description: Experimental and computational datasets for this publication, including README files. To unzip, in the command line paste the following command: tar -xzvf cacup_data_repository_v2.tar.gz And repeat the command: tar -xzvf &lt;file.tar.gz&gt; for each necessary tar file. For any issues with accessibility, please email joe.willis.15@ucl.ac.uk.
DOI: 10.34740/kaggle/dsv/3228135
title: Mahanagar Yatayat Dataset
DOI: 10.5281/zenodo.6278127
title: processed datasets of deepsignal-plant

description: processed datasets of deepsignal-plant
DOI: 10.5281/zenodo.5587401
title: processed datasets of deepsignal-plant

description: processed datasets of deepsignal-plant
DOI: 10.25345/c54t6f48b
title: MassIVE MSV000088919 - Escherichia coli and Synechococcus elongatus cell extract WT and deltacutA mutant
title: Untargeted metabolomics of MeOH extraction from Synechococcus elongatus WT and delta cutA mutant and Escherichia coli Wt and deltacutA mutant
DOI: 10.6084/m9.figshare.19236678
title: The effect of cost on hedonic adaptation of prosocial behavior

description: data
DOI: 10.6084/m9.figshare.19236678.v1
title: The effect of cost on hedonic adaptation of prosocial behavior

description: data
DOI: 10.5281/zenodo.6281992
title: Dipeptidyl peptidase 11 (PgDPP11); A Target Enabling Package

description: <em>Porphyromonas</em> gingivalis (<em>P. gingivalis</em>) is the main causative agent of Periodontitis, the most widespread inflammatory condition world-wide. Recently this organism has been implicated in several systemic conditions, such as Alzheimer’s disease and type 2 diabetes. <em>P. gingivalis</em> does not ferment carbohydrates, instead it uses proteases to generate energy and carbon source. Dipeptidyl peptidase 11 plays a central role in the energy metabolism of this bacterium and has been proposed as an attractive drug target. This TEP provide early tools to develop inhibitors of PgDPP11, including purification protocols of recombinant proteins, a crystal structure of the protein in complex with a dipeptide, crystallisation conditions suitable for crystallography-based fragment screening, an inhibition assay and fragment hits in the active site and an allosteric site. These molecules provide a promising starting point for the development of more specific and potent PgDPP11 inhibitors.
description: This document represents version 0 of the TEP. Future versions will include data for the PgDPP11 TEP. For more information about TEPs and the TEP Programme, please visit https://www.cmd.ox.ac.uk/resources/teps
DOI: 10.25549/one-c4-27462
title: ONE, Inc. meeting minutes (1990)

description: ONE, Inc. minutes for the annual, trustees, and board of directors meetings (1990)
DOI: 10.15156/bio/sh1163937.08fu
title: SH1163937.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163938.08fu
title: SH1163938.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh611439.07fu
title: SH611439.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh611440.07fu
title: SH611440.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh611441.07fu
title: SH611441.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163939.08fu
title: SH1163939.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163940.08fu
title: SH1163940.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh611442.07fu
title: SH611442.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh611443.07fu
title: SH611443.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.