cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/px8kjhtg6v.2
title: Supplementary Data of “Research letter: Pre-existing cutaneous conditions could increase the risk for SARS-COV-2 infection”

description: Elevated ACE2 expression in the lesion of psoriasis and atopic dermatitis. Elevated ACE2 expression in inflammatory skin disorders with barrier dysfunction mouse models and could be reduced by topical skin recovery moisture. S protein transmitted through the skin of inflammatory skin disorders with barrier dysfunction mouse models. SARS-COV-2 pseudovirus could be detected in the dermal and lung of mouse skin with inflammatory status and deteriorated skin barrier.
DOI: 10.17632/ktzx8rvv9h.1
title: Notre Dame fire text processing - word libraries

description: The dataset presents the word libraries that we've used for processing tweet data for the Notre Dame fire investigation project. It includes three major word libraries: 1) fire cause filtering seeds, 2) removing texts libraries, and 3) lexicon-based libraries. 1. Downloaded tweets with the search phrase “Notre Dame” were written in 62 different languages, in which the top 13 most commonly used languages are English, French, Spanish, Portuguese, German, Italian, Japanese, Polish, Turkish, Dutch, Swedish, Catalan, and Thai. This library presents the filter seeds translated in these 13 languages with the aid of Google Translation API. 2. The phrase “Notre Dame” in a tweet for the present dataset can be referred to the University of “Notre Dame” in the United States, so a filtering word library was developed containing university-related words. Another word library was developed to filter out those records not indicating the fire causes of Notre Dame Cathedral (“false” fire causes filters). 3. The research team randomly selected a sampled set of n=1,500 unique tweets from the dataset and manually identified and collected these cues to detect the negation from a tweet. The full libraries of these word patterns are attached. This file exhibits the lists of word patterns that we input into python to filter the tweets and build the opinion detection model.
DOI: 10.17632/mdvzh7prjz.1
title: Best track data

description: This is the track data for the 1999 Super cyclone and 2013 Phailin cyclone data
DOI: 10.17632/7r9rymybwc.1
title: THE IMPACT OF COVID-19 OUTBREAK ON UROLITHIASIS EMERGENCY DEPARTMENT ADMISSIONS, HOSPITALIZATIONS AND CLINICAL MANAGEMENT IN CENTRAL ITALY

description: Aim of this study was to explore how the COVID-19 outbreak influenced emergency admissions for ureteral lithiasis, complications, hospitalizations and management of the hospitalized patients in 3 urologic Departments in Italy
DOI: 10.17632/4vmzckmmxk.1
title: LINF_010005700

description: Hypothetical protein - conserved
DOI: 10.17632/m8ncdtv82f.1
title: LINF_010005800

description: mitochondrial UMP-CMP kinase
DOI: 10.5281/zenodo.4034859
title: The CONTEXT Dataset containing Contextual Faults of a Smart Factory

description: Here you download the CONTEXT Dataset containing Contextual Faults of a Smart Factory. If you refer or use this dataset, cite this publication (DOI follows after publication): Lukas Kaupp, Heiko Webert, Kawa Nazemi, Bernhard Humm, Stephan Simons, 2020. CONTEXT: An Industry 4.0 Dataset of Contextual Faults in a Smart Factory (in Press), in: Proceedings of the International Conference on Industry 4.0 and Smart Manufacturing, Vienna, Austria. The dataset contains contextual faults recorded in the smart factory of the Darmstadt University of Applied Sciences. Each recording (CSV format) consists of an OPC-UA log file and log files of the corresponding machinery measured by our developed sensing units. Foldernames reflect experiment structure. &lt;date&gt;-&lt;run&gt;_&lt;count of build relays&gt;_&lt;g(ood/ok)/n(ot/failure)&gt;_&lt;experiment name&gt; You can find a detailed description of the experiments in our publication.<br>
DOI: 10.17632/c6gbb3shsz.1
title: LINF_010006000

description: Monothiol glutaredoxin
DOI: 10.17632/6c8pxrd8x3.1
title: LINF_010006100

description: hypothetical protein - conserved
DOI: 10.17632/ds6g796xyg.2
title: The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19. Consiglio et al.

description: Datasets are included in folders according to the figures in the manuscript "The Immunology of Multisystem Inflammatory Syndrome in Children with COVID-19.". This project used multiple omics data from Plasma protein expression (Olink - NPX values), FACS and Autoantibodies. Project is created with RStudio version: 3.6.2.
DOI: 10.17632/4nddv7ftxn.1
title: The experimental results of shale from Lower Silurian longmaxi formation subjected to uniaxial compression

description: There are experimental results of longmaxi formation shale subjected to uniaxial compression, including the stress-strain curves, macroscopic mechanical parameters and failure modes. The shale samples were divided into four groups in terms of layer orientations, which were predefined as 0°, 30°, 60°, and 90°. Every group contains three samples. Cylindrical samples with diameters of 50 mm and lengths of 100 mm were cored from shale, with the parallelism and smoothness of end surfaces meeting the suggested experimental standards of International Society for Rock Mechanics (ISRM). All the uniaxial compression experiments were conducted by strain controlling mode at a constant strain rate of 0.001%/s.
DOI: 10.17632/v992cb6bw7.3
title: HFRD: Human Face Recognition Datasets on COVID-19 pandemic stage (v2020)

description: The HFRD (v2020) dataset includes 4835 images of masked human faces. Originally, the faces were taken from three different publicly available datasets: MUCT, FASSEG, and AT&T datasets. The collected subsets of the HFRD dataset contain standard images that are previously used in the field of facial recognition, and then we added masks to cover the nose, mouth, and chin area, as for what remains visible from the face are the eyes, forehead, and hair. Thus, we have introduced new standard images for use in the field of partial facial recognition (PFR) domain. The new structure of the current HFRD store inherits the structure of each original dataset, which means there are three main datasets: MaskedMUCT contains five folders, MaskedFASSEG contains four folders, and MaskedAT&T has organized in 40 folders. This store of HFRD masked face datasets is not only inheriting the structure of the original datasets but also inheriting the varsity of them. Finally, all folders consist of facial images surrounded and covered by various shapes of masks. Consequently, the proposed new enhanced HFRD datasets have been developed based on the impact of the pandemic COVID-19 stage. Our enhanced improved Human Face Recognition Datasets (HFRD) datasets could be used to test studies of FR algorithms for human identification. The obtained outcomes from this enhanced HFRD data can also be useful in providing more knowledge for the Artificial Intelligence (AI) tools, and decision support system for predicting the spread of COVID-19.
DOI: 10.17632/892sn9w7g4.3
title: Millimeter Wave Reflection Data for Semi-Insulating Gallium Nitride on Sapphire Wafer

description: In order to estimate the dielectric properties of materials, we need vector measurements consisting of voltage reflection and transmission of electromagnetic radiation for the material under test (amplitude and phase). A recently developed apparatus for measuring time-resolved charge carrier dynamics in photo-responsive materials for millimeter-wave probe frequencies (TR-mmWC) was used to study dc reflection (amplitude only) characteristics of binary III/V direct bandgap material Gallium Nitride (GaN). Commercial-grade 2" N-GaN (Si-doped, high resistivity) on Sapphire wafer with thickness 430 +/- 25 micrometer and GaN layer thickness of 5 micrometers was used to collect reflected RF data using a Schottky barrier diode detector operable in the 110-170 GHz (D-waveguide band) range with responsivity around 2000 volts/watt. Output voltages of this negative polarity detector were collected in steps of 0.01 GHz. Reference voltages (E0) for reflection were collected by using a highly polished mirror. These data can be used to calculate the reflection coefficient (σ) of semi-insulating GaN. Anomalies in reflected voltages were observed in certain frequencies which may be neglected for this type of analysis. These frequencies to be flagged in the dataset are 110.4 GHz, 110.5GHz, 110.7GHz, 114.2 GHz, 114.7GHz, 114.8 GHz, 114.9GHz, 115GHz, 115.2GHz, 115.4GHz, 118.3GHz, 118.7GHz, and 156.4GHz. The cause of these anomalies could be the creation of standing wave/diffraction effects. Data were collected using Keithley digital multimeter operated with LabVIEW, 500 ms sampling period was used and a 30-sample average and standard deviation of signal voltages were stored in an ASCII-delimited comma-separated variable (.csv) file. Data column 1 is probe frequency, column2 is mirror reflected voltage, column 3 is the standard deviation of mirror reflected voltages. Column 4 is the GaN surface reflected voltage obtained at 65.4 degrees and column 5 is the standard deviation of GaN reflected voltage.
DOI: 10.17632/crwfkjm3fx.2
title: Data on Pelvic Fracture Urethral Injury from a tertiary trauma care center in southeast Nigeria

description: A 10year data retrieved retrospectively from the medical records of patients who sustained major traumatic pelvic injury from January 2010 to December 2019. The main objective of the research is to determine the hospital-based incidence rate of pelvic fracture urethral injury (PFUI) among patients with major pelvic injury. The other objective is to ascertain the pattern of pelvic disruptions associated with PFUI.
DOI: 10.17632/g3vtswd6m9.1
title: Raw Data

description: Improving the Antioxidation and Antibacterial Activities of the Pectin by Acylating with p-Coumaric and Caffeic Acids through Lipase-Catalysed Transesterification in Water/Organic Two-Phase System
DOI: 10.17632/78y7j4ksgg.1
title: data for Synergistic combination of nano-materialPEK-C for interleaving toughening and strengthening in carbon fibre reinforced epoxy composites

description: Here's data for a new English paper named"Synergistic combination of nano-materialPEK-C for interleaving toughening and strengthening in carbon fibre reinforced epoxy composites". It includes the basic data for flexual test and interlaminar shear test, the origin files for data processed and the processed data forms for Mode I tests.
DOI: 10.5281/zenodo.4034929
title: Combining StarDist and TrackMate example 2 - T cell dataset

description: <strong>Description</strong>: Contains a StarDist example training dataset, a test dataset, and the StarDist model generated using ZeroCostDL4Mic (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist) <strong>Training dataset</strong>: 209 Paired microscopy images (brightfield) and corresponding masks <strong>Microscopy data type</strong>: brightfield microscopy and masks obtained via manual segmentation (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist for details about the segmentation) <strong>Microscope</strong>: Imaging was done using a 10x phase contrast objective at 37°C on a Zeiss Axiovert 200M microscope equipped with an automated X-Y stage and a Roper EMCCD camera. Time-lapse images were collected every 30 sec for 10 min using SlideBook 6 software (Intelligent Imaging Innovations). <strong>File format</strong>: .tif (16-bit for brightfield images and 8 and 16-bit for the masks) <strong>Image size</strong>: 1024x1024 (Pixel size: 645 nm)
DOI: 10.17632/4y26wnpgbd.1
title: UV vis and Head-space analysis spectroscopic data on alloy nano-particles of Iron

description: This contains data obtained from head-space analysis and UV visible spectrometer on several alloy nano-particle species of iron
DOI: 10.5281/zenodo.4034928
title: Combining StarDist and TrackMate example 2 - T cell dataset

description: <strong>Description</strong>: Contains a StarDist example training dataset, a test dataset, and the StarDist model generated using ZeroCostDL4Mic (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist) <strong>Training dataset</strong>: 209 Paired microscopy images (brightfield) and corresponding masks <strong>Microscopy data type</strong>: brightfield microscopy and masks obtained via manual segmentation (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist for details about the segmentation) <strong>Microscope</strong>: Imaging was done using a 10x phase contrast objective at 37°C on a Zeiss Axiovert 200M microscope equipped with an automated X-Y stage and a Roper EMCCD camera. Time-lapse images were collected every 30 sec for 10 min using SlideBook 6 software (Intelligent Imaging Innovations). <strong>File format</strong>: .tif (16-bit for brightfield images and 8 and 16-bit for the masks) <strong>Image size</strong>: 1024x1024 (Pixel size: 645 nm)
DOI: 10.17632/fx83wkxm4z.1
title: Supplementary data for In silico PCR amplification data aid to design specific primers targeting Salmonella spp., S. Typhimurium and S. Enteritidis

description: In silico PCR amplification supplementary data for ENT, STM and invA primer pairs
DOI: 10.17632/c59kz5bfgs.1
title: Supplementary Materials for GAGS-2020-0351

description: Supplementary Materials for GAGS-2020-0351, including one table and three figures.
DOI: 10.17632/38gtdwky5j.2
title: Writing in L2: Norwegian Students’ Use of Translanguaging at the Draft Stage

description: Translanguaging corpus, raw data: drafts
DOI: 10.17632/m6fgnjgy3f.1
title: The Use of Students’ Linguistic Resources in Teaching English as an Additional Language in Norway. Prilutskaya, M., Knoph, R., & and Allen Hanssen, J. (2020)

description: Appendices
DOI: 10.17632/xyd7r5j8df.1
title: River discharge data

description: This is the discharge data for Mahanadi, Brahmani and Baitarani Rivers during the 1999 super cyclone and 2013 Phailin cyclone period.
DOI: 10.6084/m9.figshare.12968138
title: Supplementary Table 1. Raw data for the investigated water quality parameters of Mpanga river, Uganda

description: Raw data for the investigated water quality of Mpanga river impacted by Kabundaire abbatoir effluents, Fort Portal Tourism City, Uganda
DOI: 10.6084/m9.figshare.12968138.v1
title: Supplementary Table 1. Raw data for the investigated water quality parameters of Mpanga river, Uganda

description: Raw data for the investigated water quality of Mpanga river impacted by Kabundaire abbatoir effluents, Fort Portal Tourism City, Uganda
DOI: 10.6084/m9.figshare.8191688
title: Modelling capacity along a patient pathway with delays to transfer and discharge

description: This article presents a versatile model to estimate capacity requirements along a patient pathway with delays to transfer and discharge caused by blocking after service. Blocking after service is a common property in health systems where patients requiring uninterrupted care can only leave a service when they can be admitted downstream to another. Unlike many studies, the approach appreciates both variability in arrivals and length of stay at each service point and the stochastic queuing dynamics between them. This is crucial to the understanding and identification of blockages which can present a significant source of inefficiency. The problem is framed as a continuous-time Markov chain where patient arrivals, transfers, and discharges are modelled through state transitions, with length of stay approximated by the Erlang distribution. The solution is through simulating movements around this chain by dynamically sampling the next state accessible from the neighbourhood of the current, thus bypassing the need for time-intensive manipulations of equations involving the entire transition matrix. This is packaged in easy-to-use code in free software so as to be readily available to healthcare practitioners. An example of use is illustrated for a stroke pathway reconfiguration where move to a centralised hyper-acute service is assessed.
DOI: 10.6084/m9.figshare.8191688.v1
title: Modelling capacity along a patient pathway with delays to transfer and discharge

description: This article presents a versatile model to estimate capacity requirements along a patient pathway with delays to transfer and discharge caused by blocking after service. Blocking after service is a common property in health systems where patients requiring uninterrupted care can only leave a service when they can be admitted downstream to another. Unlike many studies, the approach appreciates both variability in arrivals and length of stay at each service point and the stochastic queuing dynamics between them. This is crucial to the understanding and identification of blockages which can present a significant source of inefficiency. The problem is framed as a continuous-time Markov chain where patient arrivals, transfers, and discharges are modelled through state transitions, with length of stay approximated by the Erlang distribution. The solution is through simulating movements around this chain by dynamically sampling the next state accessible from the neighbourhood of the current, thus bypassing the need for time-intensive manipulations of equations involving the entire transition matrix. This is packaged in easy-to-use code in free software so as to be readily available to healthcare practitioners. An example of use is illustrated for a stroke pathway reconfiguration where move to a centralised hyper-acute service is assessed.
DOI: 10.5281/zenodo.4034939
title: Combining StarDist and TrackMate example 3 - Flow chamber dataset

description: <strong>Description</strong>: Contains a StarDist example training dataset, a test dataset, and the StarDist model generated using ZeroCostDL4Mic (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist) <strong>Training dataset</strong>: Paired microscopy images (brightfield) and corresponding masks <strong>Microscopy data type</strong>: brightfield microscopy and masks obtained via manual segmentation (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist for details about the segmentation) <strong>Microscope</strong>: Images were acquired with a brightfield microscope (Zeiss Laser-TIRF 3 Imaging System, Carl Zeiss) and a 10X objective. <strong>File format</strong>: .tif (8-bit for brightfield images and 8 and 16-bit for the masks) <strong>Image size</strong>: 1024x1024 (Pixel size: 650 nm)
DOI: 10.5281/zenodo.4034938
title: Combining StarDist and TrackMate example 3 - Flow chamber dataset

description: <strong>Description</strong>: Contains a StarDist example training dataset, a test dataset, and the StarDist model generated using ZeroCostDL4Mic (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist) <strong>Training dataset</strong>: Paired microscopy images (brightfield) and corresponding masks <strong>Microscopy data type</strong>: brightfield microscopy and masks obtained via manual segmentation (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist for details about the segmentation) <strong>Microscope</strong>: Images were acquired with a brightfield microscope (Zeiss Laser-TIRF 3 Imaging System, Carl Zeiss) and a 10X objective. <strong>File format</strong>: .tif (8-bit for brightfield images and 8 and 16-bit for the masks) <strong>Image size</strong>: 1024x1024 (Pixel size: 650 nm)
DOI: 10.6084/m9.figshare.12968171
title: Heavy Metals exposure through quarry Operations

description: Dataset for Heavy Metals' exposure through quarry opertaions in Ago Iwoye, Ogun state, Nigeria<b> </b><b><br></b>
DOI: 10.5281/zenodo.4034976
title: Combining StarDist and TrackMate example 1 - Breast cancer cell dataset

description: <strong>Description</strong>: Contains a StarDist example training dataset, a test dataset, and the StarDist model generated using ZeroCostDL4Mic (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist) <strong>Training dataset</strong>: 72 Paired microscopy images (fluorescence) and corresponding masks <strong>Microscopy data type</strong>: Fluorescence microscopy (SiR-DNA) and masks obtained via manual segmentation (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist for details about the segmentation) <strong>Microscope</strong>: Spinning disk confocal microscope with a 20x 0.8 NA objective <strong>Cell type</strong>: DCIS.COM Lifeact-RFP cells <strong>File format</strong>: .tif (16-bit for fluorescence and 8 and 16-bit for the masks) <strong>Image size</strong>: 1024x1024 (Pixel size: 634 nm)
DOI: 10.5281/zenodo.4034975
title: Combining StarDist and TrackMate example 1 - Breast cancer cell dataset

description: <strong>Description</strong>: Contains a StarDist example training dataset, a test dataset, and the StarDist model generated using ZeroCostDL4Mic (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist) <strong>Training dataset</strong>: 72 Paired microscopy images (fluorescence) and corresponding masks <strong>Microscopy data type</strong>: Fluorescence microscopy (SiR-DNA) and masks obtained via manual segmentation (see https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist for details about the segmentation) <strong>Microscope</strong>: Spinning disk confocal microscope with a 20x 0.8 NA objective <strong>Cell type</strong>: DCIS.COM Lifeact-RFP cells <strong>File format</strong>: .tif (16-bit for fluorescence and 8 and 16-bit for the masks) <strong>Image size</strong>: 1024x1024 (Pixel size: 634 nm)
DOI: 10.6084/m9.figshare.12045450
title: Data and R Code for "Continuous proximity-sensing reveals lower social connectedness in LPS-challenged wild vampire bats"

description: Belize_pre-fusion.csv is data from proximity sensors.Belize_tracked_bats02.csv is data on captured vampire bats.LPS_belize_analysis14.R is R code for main analysis<br>LPS_belize_effect_size08.R is R code for effect of network construction on effect size.<br><br><b></b><br><br>
DOI: 10.6084/m9.figshare.12045450.v5
title: Data and R Code for "Continuous proximity-sensing reveals lower social connectedness in LPS-challenged wild vampire bats"

description: Belize_pre-fusion.csv is data from proximity sensors.Belize_tracked_bats02.csv is data on captured vampire bats.LPS_belize_analysis14.R is R code for main analysis<br>LPS_belize_effect_size08.R is R code for effect of network construction on effect size.<br><br><b></b><br><br>
DOI: 10.6084/m9.figshare.12045450.v4
title: Data and R Code for "Continuous proximity-sensing reveals lower social connectedness in LPS-challenged wild vampire bats"

description: Belize_pre-fusion.csv is data from proximity sensors.Belize_tracked_bats02.csv is data on captured vampire bats.LPS_belize_analysis13.R is R code for main analysis<br>LPS_belize_effect_size07.R is R code for effect of network construction on effect size.<br><br><b></b><br><br>
DOI: 10.5519/qd.nhjf1b63
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (47 records)
DOI: 10.5281/zenodo.4034985
title: Raw data for viscoelastic anterior cruciate ligament characteristics

description: Here, you can find three MS Excel files containing raw, statistical and analysed data for the study of viscoelastic properties of canine cranial cruciate ligaments at slow strain rates.
DOI: 10.5064/f61z429b
title: Democracies and Dictatorships in Latin America: Political Actors, 1944-2010
title: Data for Democracies and Dictatorships in Latin America (Cambridge University Press, 2013)

description: The book for which this data collection was generated seeks to explain why democracies and authoritarian regimes have emerged and then survived or fallen in Latin America from 1945 to 2005. The authors created a set of reports covering all Latin American countries for that period, providing systematic historical measures of normative regime preferences (ideological support for democracy or authoritarianism) and of policy radicalism for major political actors. The reports were produced between 2008 and 2013 with the help of research assistants by archival research and synthesis of existing material (notes based on secondary sources subsequently integrated into country reports). The data collection includes all of these reports as well as the coding rules guiding their production.