cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18725/oparu-48815
title: SemanticSpray Dataset

description: LiDARs are one of the main sensors used for autonomous driving applications, providing accurate depth estimation regardless of lighting conditions. However, they are severely affected by adverse weather conditions such as rain, snow, and fog. This dataset provides semantic labels for a subset of the RoadSpray [1] dataset, which contains scenes of vehicles traveling at different speeds on wet surfaces, creating a trailing spray effect. We provide semantic labels for over 200 dynamic scenes, labeling each point in the LiDAR point clouds as background (road, vegetation, buildings, ...), foreground (moving vehicles), and noise (spray, LiDAR artifacts). The dataset toolkit is available at: https://github.com/aldipiroli/semantic_spray_dataset References: [1] C. Linnhoff, L. Elster, P. Rosenberger, and H. Winner, "Road spray in lidar and radar data for individual moving objects," 2022-04. [Online]. DOI: https://doi.org/10.48328/tudatalib-930 Available: https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3537
DOI: 10.6084/m9.figshare.22677616.v1
title: Electro-thermal actuation in percolative ferroelectric polymer nanocomposites

description: Source data of the figures and Extended Data Figures
DOI: 10.6084/m9.figshare.22677616
title: Electro-thermal actuation in percolative ferroelectric polymer nanocomposites

description: Source data of the figures and Extended Data Figures
DOI: 10.6084/m9.figshare.22725695.v1
title: Bre1/RNF20 promotes Rad51-mediated strand exchange and antagonizes the Srs2/FBH1 helicases

description: It is supplementary data containing primers and siRNA/shRNA sequence information
DOI: 10.6084/m9.figshare.22649758.v1
title: Retrosynthesis prediction using an end-to-end graph generative architecture for molecular graph editing

description: The USPTO-50k dataset and the trained Graph2Edits model for retrosynthesis prediction.
DOI: 10.6084/m9.figshare.22725695
title: Bre1/RNF20 promotes Rad51-mediated strand exchange and antagonizes the Srs2/FBH1 helicases

description: It is supplementary data containing primers and siRNA/shRNA sequence information
DOI: 10.6084/m9.figshare.22586323.v1
title: Structure-evolution-designed amorphous oxides for dielectric energy storage

description: This is the source data for the manuscript.
DOI: 10.6084/m9.figshare.22586323
title: Structure-evolution-designed amorphous oxides for dielectric energy storage

description: This is the source data for the manuscript.
DOI: 10.18419/darus-3292
title: Replication Data for: Increasing the Dynamic Accuracy of Ball Screw Drives with Quasi-Sliding-Mode (qSMC) Position Control

description: To increase the dynamics of ball screw drives, a nonlinear position controller, based on sliding-mode control, is presented together with its parameterization for robust stability. The controller is validated experimentally on a ball screw axis and shown increase the controller bandwidth from 8 Hz to 15.9 Hz in comparison to P position control with feedforward, to reduce the mean absolute tracking error under static high performance cutting forces by 24 % and to be robustly performant with a maximum degradation of the tracking error of 2.7 % for variations of 20 % in the model parameters. Please refer to Readme.md contained in the dataset for more detailed information. Measurement names: SPP ... s profile measurements PRBS ... pseudo random binary sequence with offset velocity of 0.01m/s dStep ... Disturbance steps of 1kN on table (with linear direct drive) dSweep ... Disturbance sweep signal (500 N amplitude) on table (with linear direct drive) milling ... simulated HPC forces added with LDD during s profile along whole axis length Abbreviations used in data/metadata: LDA/LDD ... linear direct drive KGT/BSC ... ball screw drive
DOI: 10.17028/rd.lboro.23019596
title: Macroinvertebrate data from Pitsford Reservoir over three years

description: Data provided is primary data collected from Pitsford Reservoir in Northamptonshire, UK where three non-native amphipods have established populations. Data collected in 2016, 2017, and 2018.
DOI: 10.17028/rd.lboro.23019596.v1
title: Macroinvertebrate data from Pitsford Reservoir over three years

description: Data provided is primary data collected from Pitsford Reservoir in Northamptonshire, UK where three non-native amphipods have established populations. Data collected in 2016, 2017, and 2018.
DOI: 10.25592/uhhfdm.12330
title: VL17 Informationsmappe zu Bibliotheksbeständen für Autoren Lebaldt-Omeis (Handschriften, gedruckte Briefe)

description: Verfasserlexikon 1620-1720 (VL17) Informationsmappe zu Bibliotheksbeständen für Autoren Lebaldt-Omeis (Handschriften, gedruckte Briefe) Nähere Informationen siehe in der beiliegenden Datei "Autoren - Bibliotheken - Übersicht - VL17 - Lebaldt-Omeis.pdf"
DOI: 10.25592/uhhfdm.12329
title: VL17 Informationsmappe zu Bibliotheksbeständen für Autoren Lebaldt-Omeis (Handschriften, gedruckte Briefe)

description: Verfasserlexikon 1620-1720 (VL17) Informationsmappe zu Bibliotheksbeständen für Autoren Lebaldt-Omeis (Handschriften, gedruckte Briefe) Nähere Informationen siehe in der beiliegenden Datei "Autoren - Bibliotheken - Übersicht - VL17 - Lebaldt-Omeis.pdf"
DOI: 10.5281/zenodo.7971397
title: Translated Wikipedia Biographies (English-Catalan)

description: A professional translation of the Translated Wikipedia Biographies dataset, designed to analyze common gender errors in machine translation like incorrect gender choices in anaphora resolutions, possessives and gender agreement, commissioned by BSC LangTech Unit. License type: CC BY-SA 4.0 This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.
DOI: 10.5281/zenodo.7971398
title: Translated Wikipedia Biographies (English-Catalan)

description: A professional translation of the Translated Wikipedia Biographies dataset, designed to analyze common gender errors in machine translation like incorrect gender choices in anaphora resolutions, possessives and gender agreement, commissioned by BSC LangTech Unit. License type: CC BY-SA 4.0 This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.
DOI: 10.6084/m9.figshare.22689649.v1
title: Environmental conditions are the dominant factor to influence stability of terrestrial ecosystems on the Tibetan plateau

description: This dataset is the supporting data and code for the article "Environmental conditions are the dominant factor to influence stability of terrestrial ecosystems on the Tibetan plateau". <strong>unprocessed data.xlsx </strong>is all the data supporting this study, provided in different sheets by type. Sheet1 has a description of the original dataset. <strong>stability.csv</strong> is the supporting data used to complete all analyses in the main text, which has been organized into a format that can be analyzed directly using the R code provided. <strong>analysis.R</strong> is the R code that completes the main analysis of the paper;
DOI: 10.5281/zenodo.7016829
title: The condition of forest ecosystems in Europe mapped by a global standard

description: The datasets describe a European forest ecosystem condition account complient with the System of Environmental-Economic Accounting. Three datasets are provided: 1. An excel file with a forest extent and condition account at European level for 44 forest types 2. A raster map with the forest typology 3. A raster map with the forest condition index (0-1) at 100 m resolution for the years 2000 and 2018
description: Embargoed dataset until the publication is accepted.
DOI: 10.5281/zenodo.7417571
title: Kirchhoff pre-stack depth migration images of the multi-channel seismic data, SO190, RV. SONNE

description: The dataset consists of four newly processed 2-D pre-stack depth migrated multi-channel seismic lines (BGR06_303, BGR06_305, BGR06_311 and BGR06_313) collected by GEOMAR and BGR in 2006. The dataset reveals the subducted oceanic reliefs and detailed accretionary wedge structure offshore eastern Java, Bali, Lombok, and Sumbawa islands, along the Sunda arc. The dataset is saved in standard SEGY format and could be loaded in open-source or commercial software.
DOI: 10.5281/zenodo.7973111
title: Kirchhoff pre-stack depth migration images of the multi-channel seismic data, SO190, RV. SONNE

description: The dataset consists of four newly processed 2-D pre-stack depth migrated multi-channel seismic lines (BGR06_303, BGR06_305, BGR06_311 and BGR06_313) collected by GEOMAR and BGR in 2006. The dataset reveals the subducted oceanic reliefs and detailed accretionary wedge structure offshore eastern Java, Bali, Lombok, and Sumbawa islands, along the Sunda arc. The dataset is saved in standard SEGY format and could be loaded in open-source or commercial software.
DOI: 10.5281/zenodo.7590909
title: Understanding cirrus clouds using explainable machine learning

description: This repository contains the data for the paper: Authors: Kai Jeggle , David Neubauer , Gustau Camps-Valls and Ulrike Lohmann<br> Titel: Understanding cirrus clouds using explainable machine learning<br> Date: 2023 Note that the scripts can be found in the accompanying package (https://github.com/tabularaza27/explaining_cirrus)
description: v1 was causing extraction errors for some users, please use v2.
DOI: 10.5281/zenodo.7590910
title: Understanding cirrus clouds using explainable machine learning

description: This repository contains the data for the paper: Authors: Kai Jeggle , David Neubauer , Gustau Camps-Valls and Ulrike Lohmann<br> Titel: Understanding cirrus clouds using explainable machine learning<br> Date: 2023 Note that the scripts can be found in the accompanying package (https://github.com/tabularaza27/explaining_cirrus)
DOI: 10.5281/zenodo.7965381
title: Understanding cirrus clouds using explainable machine learning

description: This repository contains the data for the paper: Authors: Kai Jeggle , David Neubauer , Gustau Camps-Valls and Ulrike Lohmann<br> Titel: Understanding cirrus clouds using explainable machine learning<br> Date: 2023 Note that the scripts can be found in the accompanying package (https://github.com/tabularaza27/explaining_cirrus)
description: v1 was causing extraction errors for some users, please use v2.
DOI: 10.5519/qd.mqvglftj
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1376484 records)
DOI: 10.25934/pr00008964
title: Global Antimicrobial Resistance Trends and Patterns Identification using Machine Learning: Data Challange

description: Antimicrobial resistance (AMR) is one of the significant public health threats that interferes with the ability to effectively treat infectious diseases, thereby leading to increased morbidity and mortality worldwide. Rapidly developing multidrug-resistant bacterial strains have substantially inspired new approaches to combating, preventing, and treating illnesses. Conventional statistical models frequently provide reduced accuracy in their predictions when AMR data is non-normally distributed, which can lead to assumptions underlying these models being violated. As a potential alternative, machine learning models are capable of processing larger datasets and making more precise predictions.
In this project, we propose to apply semi-supervised machine learning algorithms coupled with natural language processing techniques to extract trends in antimicrobial resistance. We propose to cluster the global spatiotemporal trends and patterns of AMR by integrating clinical, surveillance, and genomic AMR datasets. Data preprocessing steps will include data cleaning, model selection, and feature selection. Next, semi-supervised machine learning techniques will be used to group similar data points into clusters based on their similarity in feature space. The resulting clusters will be explored to identify meaningful trends and patterns in the data. To integrate raw genomic data into the proposed clustering approach, we intend to use a natural language processing method to transform the genomic data into numeric features that will be incorporated in the clustering analysis. 
The outcome of this project will have the potential to first; identify novel trends of antimicrobial resistance species across different countries and determine bacterial strains that are more prevalent in a given country. Secondly, the project outcome will guide on the new preventive measures for managing AMR resistance and provide insights that can inform the development of new interventions to reduce the spread of antibiotic resistance.
DOI: 10.6084/m9.figshare.20521224
title: mixratio_dataset_20230526.tar.xz

description: The image dataset for mixing ratio prediction
DOI: 10.6084/m9.figshare.20521224.v1
title: mixratio_dataset_20220819.tar.xz

description: The image dataset for mixing ratio prediction
DOI: 10.6084/m9.figshare.20521224.v2
title: mixratio_dataset_20230526.tar.xz

description: The image dataset for mixing ratio prediction
DOI: 10.6084/m9.figshare.23212715
title: Serum Phosphorus and AH in children

description: The potential correlation between phosphorus and calcium levels and adenoid hypertrophy (AH) .
DOI: 10.6084/m9.figshare.23212715.v1
title: Serum Phosphorus and AH in children

description: The potential correlation between phosphorus and calcium levels and adenoid hypertrophy (AH) .
DOI: 10.5281/zenodo.7741636
title: Accounting for forest condition in Europe based on an international statistical standard

description: The datasets describe a European forest ecosystem condition account compliant with the System of Environmental-Economic Accounting. Four datasets are provided: 1. An excel file with a forest extent and condition account at European level for 44 forest types 2. A raster map with the forest typology 3. A raster map with the forest condition index (0-1) at 100 m resolution for the years 2000 and 2018 4. A map quantifying the uncertainty of the condition estimates using a semi-quantitative scale (low uncertainty, low to medium uncertainty, medium to high uncertainty, high uncertainty)
DOI: 10.5281/zenodo.7016828
title: Accounting for forest condition in Europe based on an international statistical standard

description: The datasets describe a European forest ecosystem condition account compliant with the System of Environmental-Economic Accounting. Four datasets are provided: 1. An excel file with a forest extent and condition account at European level for 44 forest types 2. A raster map with the forest typology 3. A raster map with the forest condition index (0-1) at 100 m resolution for the years 2000 and 2018 4. A map quantifying the uncertainty of the condition estimates using a semi-quantitative scale (low uncertainty, low to medium uncertainty, medium to high uncertainty, high uncertainty)
DOI: 10.25934/pr00008961
title: Data Challenge: Predicting Antimicrobial resistance in different geographical locations, micobes, antimicrobial classes and infection types using spatial temporal analysis. 

description: Antimicrobial resistance (AMR) is one of the leading global public health issues that pose a great social and economic burden. The relationship between AMR and the different factors associated with it are not yet well understood and thus AMR is still on the rise despite ongoing antimicrobial stewardship efforts and public health policies in place, therefore, necessitating the use of data driven solutions to inform new and precision policies and stewardship programs that are tailored to specific issues that promote AMR in the different micro environments globally. 
We propose the use of Statistical models like Generalised Additive Models (GAM) and geospatial analysis models to identify trends and geographical distribution of AMR so as to predict future AMR trends and geographical distribution. None-linear time series models have been previously used to understand the trends and geographical distribution of AMR but have been limited by a lack of high-quality AMR surveillance data to accurately and precisely develop models that can predict AMR trends and geographic distribution. Pfizer ATLAS data presents high quality surveillance data with many data points and associated factors such as geographical locations,organisms, antimicrobial classes and infection type, collected since 2004. This data can be used to quantify the association between AMR phenotypes and the different factors so as to understand their role in AMR outcomes and also study the trends of AMR in the different factors. This will improve our understanding of the association of these factors with AMR which can then further be used to predict future trends and global distribution of AMR. 
The findings from this study will be used to design new and problem tailored interventions and public health policies that are unique to each of the causes associated with AMR in the different geographical locations worldwide.
DOI: 10.5519/qd.qzfxzj6n
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5519/qd.tacwz2n7
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.7958437
title: BCC-Cu nanoparticles: from a transient to a stable allotrope by tuning size and reaction conditions

description: Open data for "BCC-Cu nanoparticles: from a transient to a stable allotrope by tuning size and reaction conditions"
DOI: 10.5281/zenodo.7958436
title: BCC-Cu nanoparticles: from a transient to a stable allotrope by tuning size and reaction conditions

description: Open data for "BCC-Cu nanoparticles: from a transient to a stable allotrope by tuning size and reaction conditions"
DOI: 10.6084/m9.figshare.23213000
title: Proteome database of <em>Helicobacter pylori</em> bacteriophage KHP30

description: This work reports the proteome database of <em>Helicobacter pylori</em> bacteriophage KHP30 with the original dataset downloaded from UniProt. The dataset was processed by an in-house MATLAB proteome database analysis software to yield protein name, and amino acid sequence. Additional variables such as length of protein, molecular weight of protein, and nucleotide sequence of each protein were calculated by the MATLAB software. It is hoped that this dataset will provide basic information useful for different molecular biology, microbiology, and virology workflows surrounding this bacteriophage.
DOI: 10.6084/m9.figshare.23212994
title: Untitled Item

description: The file contain over 2000 min of feeding observation. Each observation takes 20-60 min. Male and female feeding as reported separately. The number of nestlings (age 6-8 days) is provided.
DOI: 10.6084/m9.figshare.23212994.v1
title: Untitled Item

description: The file contain over 2000 min of feeding observation. Each observation takes 20-60 min. Male and female feeding as reported separately. The number of nestlings (age 6-8 days) is provided.
DOI: 10.5281/zenodo.7524706
title: Dataset for: All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor

description: This dataset contains relevant structures, input and other files that are associated with our article "<em>All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor"</em>.
DOI: 10.5281/zenodo.7524705
title: Dataset for: All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor

description: This dataset contains relevant structures, input and other files that are associated with our article "<em>All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor", available at https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c00249</em>
DOI: 10.5281/zenodo.7544049
title: Dataset for: All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor

description: This dataset contains relevant structures, input and other files that are associated with our article "<em>All-atom simulations reveal the intricacies of signal transduction upon binding of HLA-E ligand to the transmembrane inhibitory CD94/NKG2A receptor", available at https://pubs.acs.org/doi/full/10.1021/acs.jcim.3c00249</em>
DOI: 10.23728/b2share.e98101581be64e6188836d73a19d0243
title: Rapid diagnostic testing for onchocerciasis in Maridi (South Sudan) before and after improving elimination strategies

description: Baseline and follow-up serosurveys were conducted in Maridi in 2019 (prior to strengthening onchocerciasis elimination efforts) and 2023, respectively. During both surveys, children aged three to nine years were recruited from five study sites situated at different distances from the Maridi Dam. Ov16 antibodies were detected via rapid diagnostic tests (RDTs) using whole blood obtained by finger-pricking the participants. Baseline and follow-up Ov16 prevalence rates were calculated and compared.
DOI: 10.57745/ymqcpt
title: DILEME_Fish larvae_DATA.tab

description: :unav
DOI: 10.5281/zenodo.7971252
title: Antimicrobial MMs - Flow Cytometry

description: Flow cytometry data subset. Acquired using a Sony SA3800 spectral analyzer (Sony Biotechnology, CA, USA).
DOI: 10.5281/zenodo.7971251
title: Antimicrobial MMs - Flow Cytometry

description: Flow cytometry data subset. Acquired using a Sony SA3800 spectral analyzer (Sony Biotechnology, CA, USA).
DOI: 10.34740/kaggle/dsv/5780332
title: AutoXGB
DOI: 10.5281/zenodo.7971162
title: BXL_DSMs_orthoplan_sample

description: validation dataset for the DSM-to-DTM project at github.com/davpergan/DTM_DSM_GAN Extracted from the DSM and orthoplan of Brussels downloaded from https://datastore.brussels/web/urbis-download In the context of the code on github, it should be in the directory : np_dataset/512/val/
DOI: 10.5281/zenodo.7971161
title: BXL_DSMs_orthoplan_sample

description: validation dataset for the DSM-to-DTM project at github.com/davpergan/DTM_DSM_GAN Extracted from the DSM and orthoplan of Brussels downloaded from https://datastore.brussels/web/urbis-download In the context of the code on github, it should be in the directory : np_dataset/512/val/
DOI: 10.6084/m9.figshare.22634719.v2
title: Extended data S1 to S5.xlsx

description: Extended data S1 to S5 for “ <strong>Pre-aged terrigenous organic carbon</strong> <strong>biases ocean ventilation-age reconstructions</strong> <strong>in the North Atlantic</strong> ”