cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20113592
title: Eye-Tracking Dataset to Support the Research on Autism Spectrum Disorder

description: <strong>Abstract:</strong> This study aims to publish an eye-tracking dataset developed for the purpose of autism diagnosis. Eye-tracking methods are used intensively in that context, whereas abnormalities of the eye gaze are largely recognised as the hallmark of autism. As such, it is believed that the dataset can allow for developing useful applications or discovering interesting insights. As well, Machine Learning is a potential application for developing diagnostic models that can help detect autism at an early stage of development. <br> <strong>Dataset Description:</strong> The dataset is distributed over 25 CSV-formatted files. Each file represents the output of an eye-tracking experiment. However, a single experiment usually included multiple participants. The participant ID is clearly provided at each record at the ‘Participant’ column, which can be used to identify the class of participant (i.e., Typically Developing or ASD). Furthermore, a set of metadata files is included. The main metadata file, Participants.csv, is used to describe the key characteristics of participants (e.g. gender, age, CARS). Every participant was also assigned a unique ID. <br> <strong>Dataset Citation:</strong> Cilia, F., Carette, R., Elbattah, M., Guérin, J., & Dequen, G. (2022). Eye-Tracking Dataset to Support the Research on Autism Spectrum Disorder. In Proceedings of the IJCAI–ECAI Workshop on Scarce Data in Artificial Intelligence for Healthcare (SDAIH). <br>
DOI: 10.6084/m9.figshare.22491970
title: Raw Bone Mineral Density and Material Properties Data

description: Raw data for bone mineral denisty and bone mechanical properties of two frog species.
DOI: 10.6084/m9.figshare.22491970.v1
title: Raw Bone Mineral Density and Material Properties Data

description: Raw data for bone mineral denisty and bone mechanical properties of two frog species.
DOI: 10.6084/m9.figshare.22491991
title: Bauza2023_PlosOne_hAge_databaze_Phase1and2.mat

description: These are two data sets of all Participants described in Plos One paper Unsupervised, frequent and remote: a novel platform for personalised digital phenotyping of long-term memory in humans
DOI: 10.6084/m9.figshare.22491991.v1
title: Bauza2023_PlosOne_hAge_databaze_Phase1and2.mat

description: These are two data sets of all Participants described in Plos One paper Unsupervised, frequent and remote: a novel platform for personalised digital phenotyping of long-term memory in humans
DOI: 10.5281/zenodo.7792079
title: SG - March 2023

description: Measurements of SG (Global) in March 2023 Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792078
title: SG - March 2023

description: Measurements of SG (Global) in March 2023 Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792081
title: LPL1 - March 2023

description: Measurements of LPL1 (Teide NP) in March 2023 Tenerife Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792080
title: LPL1 - March 2023

description: Measurements of LPL1 (Teide NP) in March 2023 Tenerife Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792083
title: LPL2 - March 2023

description: Measurements of LPL2 (Caldera de Taburiente NP) in March 2023 La Palma Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792082
title: LPL2 - March 2023

description: Measurements of LPL2 (Caldera de Taburiente NP) in March 2023 La Palma Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7789377
title: Appendices (Tables and figures)

description: A survey conducted in 2,000 companies in Taiwan, obtaining 901 valid replies. Questions about digital maturity, management innovation, and digital technology adoption were asked. The file contained detailed tables for the analyses.
DOI: 10.5281/zenodo.7789376
title: Appendices (Tables and figures)

description: A survey conducted in 2,000 companies in Taiwan, obtaining 901 valid replies. Questions about digital maturity, management innovation, and digital technology adoption were asked. The file contained detailed tables for the analyses.
DOI: 10.5281/zenodo.7789422
title: Appendices (Tables and figures)

description: A survey conducted in 2,000 companies in Taiwan, obtaining 901 valid replies. Questions about digital maturity, management innovation, and digital technology adoption were asked. The file contained detailed tables for the analyses.
DOI: 10.5281/zenodo.7792077
title: Appendices (Tables and figures)

description: A survey conducted in 2,000 companies in Taiwan, obtaining 901 valid replies. Questions about digital maturity, management innovation, and digital technology adoption were asked. The file contained detailed tables for the analyses.
DOI: 10.5281/zenodo.7792085
title: LPL3 - March 2023

description: Measurements of LPL3 (Madeira East Coast) in March 2023 Madeira Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792084
title: LPL3 - March 2023

description: Measurements of LPL3 (Madeira East Coast) in March 2023 Madeira Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792087
title: LPL4 - March 2023

description: Measurements of LPL4 (Ilha do Corvo) in March 2023 Corvo Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792086
title: LPL4 - March 2023

description: Measurements of LPL4 (Ilha do Corvo) in March 2023 Corvo Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792089
title: LPL5 - March 2023

description: Measurements of LPL5 (Tejeda) in March 2023 Gran Canaria Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792088
title: LPL5 - March 2023

description: Measurements of LPL5 (Tejeda) in March 2023 Gran Canaria Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792091
title: LPL7 - March 2023

description: Measurements of LPL7 (Archipielago Chinijo) in March 2023 Archipielago Chinijo Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792090
title: LPL7 - March 2023

description: Measurements of LPL7 (Archipielago Chinijo) in March 2023 Archipielago Chinijo Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792093
title: LPL8 - March 2023

description: Measurements of LPL8 (Timanfaya NP) in March 2023 Lanzarote Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792092
title: LPL8 - March 2023

description: Measurements of LPL8 (Timanfaya NP) in March 2023 Lanzarote Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792095
title: LPL12 - March 2023

description: Measurements of LPL12 (Ilhas Desertas) in March 2023 Madeira Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792094
title: LPL12 - March 2023

description: Measurements of LPL12 (Ilhas Desertas) in March 2023 Madeira Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792099
title: LPL14 - March 2023

description: Measurements of LPL14 (Ilha das Flores) in March 2023 Flores Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792098
title: LPL14 - March 2023

description: Measurements of LPL14 (Ilha das Flores) in March 2023 Flores Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792101
title: LPL15 - March 2023

description: Measurements of LPL15 (Badajoz) in March 2023 Provincia de Badajoz Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792100
title: LPL15 - March 2023

description: Measurements of LPL15 (Badajoz) in March 2023 Provincia de Badajoz Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792103
title: LPL16 - March 2023

description: Measurements of LPL16 (Caceres) in March 2023 Provincia de Cáceres Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792102
title: LPL16 - March 2023

description: Measurements of LPL16 (Caceres) in March 2023 Provincia de Cáceres Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792105
title: LPL17 - March 2023

description: Measurements of LPL17 (Isla de Tabarca) in March 2023 Alicante Light Pollution Laboratorie info
DOI: 10.5281/zenodo.7792104
title: LPL17 - March 2023

description: Measurements of LPL17 (Isla de Tabarca) in March 2023 Alicante Light Pollution Laboratorie info
DOI: 10.5281/zenodo.4661202
title: The Pixels and Sounds of Emotion: Dataset

description: This dataset was used in: <strong>Makantasis, Konstantinos, Antonios Liapis, and Georgios N. Yannakakis. "The Pixels and Sounds of Emotion: General-Purpose Representations of Arousal in Games." <em>IEEE Transactions on Affective Computing</em> (2021).</strong> If you use this dataset please cite the following papers: <pre>@inproceedings{camilleri2017towards, title={Towards general models of player affect}, author={Camilleri, Elizabeth and Yannakakis, Georgios N and Liapis, Antonios}, booktitle={2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)}, pages={333--339}, year={2017}, organization={IEEE} } </pre> <pre>@article{makantasis2021pixels, title={The Pixels and Sounds of Emotion: General-Purpose Representations of Arousal in Games}, author={Makantasis, Konstantinos and Liapis, Antonios and Yannakakis, Georgios N}, journal={IEEE Transactions on Affective Computing}, year={2021}, publisher={IEEE} } </pre>
description: Part of this dataset was created and processed in the framework of the TAMED project (Grant Agreement 101003397) funded by the European Union's H2020 research and innovation programme.
DOI: 10.5281/zenodo.5643075
title: Smoldering Fires

description: The dataset was acquired using a gas sensor array placed in the celling of a validated standard fire room (240 m3) located in Minimax Company. The dataset includes measurements of three different campaigns that were performed over 15 months. The dataset includes standard EN-54 smoldering fires and non-standard smoldering fires (such as plastic fires; PVC, cables Fire). In order to generate scenarios that may result in false-positive alarms when gas sensors are used, different nuisance experiments were also performed (such as cleaners, and air fresheners). Additionally, an additional measurement campaign was performed in a small chamber. The small-scale experiments dataset includes scale-down replicates of the fire and nuisances experiments performed in the standard fire room (EN-54 smoldering fire experiments, non-standard fires, and nuisance experiments).
description: {"references": ["Ana Sol\u00f3rzano, Jens Eichmann, Luis Fernandez, Bernd Ziems, Juan Manuel Jim\u00e9nez-Soto, Santiago Marco, Jordi Fonollosa, Early fire detection based on gas sensor arrays: Multivariate calibration and validation, Sensors and Actuators B: Chemical, 2021, 130961, ISSN 0925-4005, https://doi.org/10.1016/j.snb.2021.130961."]}
DOI: 10.5281/zenodo.4287499
title: Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study

description: This is the code and associated data that was used to generate conclusions for the following manuscript published in Applied and Environmental Microbiology: DOI: 10.1128/AEM.02278-20 Implementation of ATP and Microbial Indicator Testing for Hygiene Monitoring in a Tofu Production Facility Improves Product Quality and Hygienic Conditions of Food Contact Surfaces: A Case Study Authors: Jonathan H. Sogin(a), Gabriela Lopez Velasco(b), Burcu Yordem(b), Cari K. Lingle(b), John M. David(b), Mario Cobo(a), Randy W. Worobo(a) (a)Department of Food Science, Cornell University, Ithaca, NY, USA (b)3M Company, St. Paul, MN, USA Address correspondence to Jonathan H. Sogin, jhs397@cornell.edu
description: Changes were made to the V1 R script to document editorial changes to figures to comply with publication requirements and polish mismatched fonts. 1. Font change of Figure 2 labels 'Phase 1', 'Phase 2', and 'Phase 3' to a serif-style font 2. Figure 3 legend, '(LAB)' added to clarify lactic acid bacteria in figure 3. Figures 4 and 5, removal of phase 1 and 3 legend, as information is already conveyed on X axis 4. Figures 4 and 5, clarification of log CFU/g to log[10] CFU/g 5. Addition of a figure export section that documents the size and resolution of publication-quality figures exported from R.
DOI: 10.5281/zenodo.5509853
title: Daily surface all-wave net radiation over global land (1981—2019) from AVHRR data

description: Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (1981-2019). After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm<sup>-2</sup>, which is generally better than some current reanalysis and satellite products.
DOI: 10.5281/zenodo.55295
title: Nivolumab-Associated Acute Glomerulonephritis: Case Report And Literature Review

description: <strong>Background:</strong> Immune checkpoint inhibitors are changing the landscape of oncologic treatment as they are significantly improving treatment of multiple malignancies. Nivolumab, anti PD-1 antibody, is FDA-approved for treatment of melanoma, non-small cell lung cancer and kidney cancer and can cause a spectrum of autoimmune reaction. The adverse effect can occur at any organ system in the body, but most commonly affects colon, lung, liver or endocrine system. Although rare, kidneys also can be involved.

<strong>Case presentation: </strong>A 70 year old male with clear cell kidney cancer was admitted with acute kidney injury while he was receiving nivolumab treatment. A kidney biopsy revealed diffuse tubular injury and immune complex mediated glomerulonephritis. Electron microscopic exam of the specimen demonstrated hump-like subepithelial deposits. Nivolumab was discontinued and the patient was started on high dose steroid. After 5 months of systemic corticosteroid and hemodialysis, patient’s kidney function improved to his baseline. In spite of the prolonged treatment interruption, immunosuppressive therapy did not compromise the anticancer effect of nivolumab.

<strong>Conclusion: </strong>Immune-related adverse effect in kidney can cause autoimmune glomerulonephritis as well as tubulo-interstitial injury. In previous literature, immune-related nephritis generally responded well to systemic corticosteroid. Based our experience, prolonged course of high dose of steroid and hemodialysis may be required to achieve adequate treatment effect.
DOI: 10.5281/zenodo.4772209
title: Location of ground stations, targets and spacecraft for randomised study

description: Datasets for randomised study in article:<br> "Data sink selection using consensus leadership: improving target connectivity for a spacecraft constellation"
DOI: 10.5281/zenodo.3457638
title: Yellow River Kenli\Lijin Station Survey

description: Measurements of vertical concentration and velocity profiles from Yellow River, China, near Kenli.
DOI: 10.5281/zenodo.4395277
title: Salinity measurements in the Mekong Delta

description: This data set contains along-channel and over-depth salinity structure measurements along the two lower estuarine distributary channels of the Hau River within the Mekong Delta, Vietnam. The data was collected during the dry season of the year 2016.
description: On two different dates, Apr-1st and April-9th of 2016, respectively during neap and spring tides, we measured salinity structures and intrusion lengths, simultaneously along the two channels. Starting from the estuary mouth during the slack tide, we sailed upstream along the thalweg at approximately 30 km hr-1 125 (i.e., approximate tidal propagation speed) and at intervals of every 3 km measured salinity over depth (See Figure 1b for the salinity routes). Salinity was transformed to PSU from conductivity [µS cm-1] and temperature [°C] measurements made by of the conductivity sensors (SensorNet TetraCon 700 IQ).
DOI: 10.5281/zenodo.1195781
title: Observed Vlf/Lf Data For The 2017 Great American Solar Eclipse

description: Observed VLF/LF data for the 2017 Great American Solar Eclipse
DOI: 10.5281/zenodo.4061968
title: data set related to article Clinical and electroencephalographic correlates of psychiatric features in children with frontal lobe epilepsy

description: This record contains raw data related to article Clinical and electroencephalographic correlates of psychiatric features in children with frontal lobe epilepsy
DOI: 10.5281/zenodo.3931163
title: Monthly GPP datasets for 2000-2017 in China from the big-leaf TEC model and the two-leaf DTEC model

description: The monthly GPP datasets were calculated from MODIS LAI/FPAR products (MOD15A2, Version 6) and meteorological data for 2000-2017 in China at a resolution of 0.05 degree ×0.05 degree. The TwoLeaf-DTEC-GPP-5km data was derived from the Two-leaf-based DTEC GPP model. The BigLeaf-TEC-GPP-5km data was calculated from the Big-leaf-based TEC GPP model. The BigLeaf-TEC-GPP-5km-2000-2017.zip includes 19 separate GPP data files and each represents one year data including 12 monthly data.
DOI: 10.5281/zenodo.4498410
title: UniPi AIS data 2018

description: *******************************************************************<br> AIS data collected from the receiver at the University of Pireaus<br> ******************************************************************* -------------------------------------------------<br> KINEMATIC DATA (position reports from vessels)<br> ------------------------------------------------- Attribute Data type Significance<br> ----------------------------------------------------------------------------------------------------<br> t double precision timestamp in UNIX epochs (seconds from 1/1/1970)<br> type integer AIS message type<br> mmsi integer MMSI identifier for vessel<br> status integer Navigational status<br> lon double precision Longitude (georeference: WGS 1984)<br> lat double precision Latitude (georeference: WGS 1984)<br> heading integer True heading in degrees (0-359), relative to true north<br> turn double precision Rate of turn, right or left, 0 to 720 degrees per minute<br> speed double precision Speed over ground in knots (allowed values: 0-102.2 knots)<br> course double precision Course over ground (allowed values: 0-359.9 degrees). <br> EXPORTED FILES: (ASCII text files with their attributes separated by ;)<br> ---------------------------------------------------------------------- unipi_kinematic_AIS_jan2018.csv -&gt; 5695691 records during January 2018<br> unipi_kinematic_AIS_feb2018.csv -&gt; 6106246 records during February 2018<br> unipi_kinematic_AIS_mar2018.csv -&gt; 6704124 records during March 2018<br> unipi_kinematic_AIS_apr2018.csv -&gt; 7894245 records during April 2018<br> unipi_kinematic_AIS_may2018.csv -&gt; 7651667 records during May 2018<br> unipi_kinematic_AIS_jun2018.csv -&gt; 8966477 records during June 2018<br> unipi_kinematic_AIS_jul2018.csv -&gt; 14339768 records during July 2018<br> unipi_kinematic_AIS_aug2018.csv -&gt; 13842609 records during August 2018<br> unipi_kinematic_AIS_sep2018.csv -&gt; 13226954 records during September 2018<br> unipi_kinematic_AIS_oct2018.csv -&gt; 8583870 records during October 2018<br> unipi_kinematic_AIS_nov2018.csv -&gt; 5312060 records during November 2018<br> unipi_kinematic_AIS_dec2018.csv -&gt; 4760420 records during December 2018 *************************************************************************** REFERENCES<br> --------------- <br> UNIVERSITY OF PIRAEUS - STATION #2782:<br> --------------------------------------------- https://www.marinetraffic.com/en/ais/details/stations/2782 <br> PRELIMINARY DEMO APPLICATION<br> ---------------------------------<br> http://infolab.cs.unipi.gr/aminess_demo/AIS_antenna_logs.htmlAIS specifications:<br> ----------------------- http://www.imo.org/en/OurWork/Safety/Navigation/Pages/AIS.aspx http://www.navcen.uscg.gov/?pageName=AISmain <br> INDICATIVE RELATED COMMERCIAL APPLICATIONS:<br> --------------------------------------------- http://www.marinetraffic.com https://www.vesselfinder.com/ https://www.fleetmon.com/
DOI: 10.5281/zenodo.5921425
title: Active Travel Data

description: Dataset
DOI: 10.5281/zenodo.1471680
title: Group Contribution Models For Tetrahymena Pyriformis Toxicity

description: A data set of several models for Tetrahymena Pyriformis Toxicity (THPT) based on additive schemes (group contribution models).

Model building is performed by means of Ambit-GCM software (http://ambit.sourceforge.net/, https://doi.org/10.5281/zenodo.1470793)

The main goal of the created THPT models is to illustrate Ambit-GCM software usage.

Typically biological activity is not well modeled by means of additive schemes. In current modeling setup we demonstrate combination of group contribution scheme with external descriptors.
DOI: 10.5281/zenodo.3739138
title: N2-sorption and catalytic results of doped Cu-catalysts for glycerol hydrogenolysis

description: This repository includes experimental data associated with the following publication: A. Bouriakova et al., "Dopant induced stabilization of alumina supported copper – impact on the catalytic performance in the hydrogenolysis of glycerol to 1,2-propanediol", submitted to Catalysis Communications in April 2020 In this work, five catalysts supported on γ-Al<sub>2</sub>O<sub>3</sub> were studied, i.e. one bare Cu and four doped-Cu catalysts. The catalysts were prepared via sequential impregnation. The nominal dopant loading was 1wt%, for the Cu a nominal value of 10wt% was selected: - 10wt% Cu/-Al2O3, indicated as Cu - 1wt%Ba-10wt% Cu/-Al2O3, indicated as Ba-Cu<br> - 1wt%Ce-10wt% Cu/-Al2O3, indicated as Ce-Cu<br> - 1wt%Cs-10wt% Cu/-Al2O3, indicated as Cs-Cu<br> - 1wt%La-10wt% Cu/-Al2O3, indicated as La-Cu The catalysts were investigated for 68 h for continuous flow pure glycerol hydrogenolysis in a trickle bed regime at 473 K, 7.5 MPa, 135 kg<sub>cat </sub>s mol<sup>-1</sup><sub>glycerol </sub>and 7 mol<sub>H2</sub> mol<sup>-1</sup><sub>glycerol</sub>, and compared for glycerol conversion, 1,2-propanediol selectivity and stability. The data file contains the glycerol conversion and selectivities over time for the studied catalysts, in combination with N<sub>2</sub>-sorption data of those catalysts. In addition, an overview of literature data on glycerol hydrogenolysis is given (Fig 1 in the manuscript).
DOI: 10.5281/zenodo.573750
title: Simulated Sar Data Of Vehicles On A Background

description: The simulated data set is used as input to a convolutional neural network to train the classifier.
description: {"references": ["Malmgren-Hansen, D., A. Kusk, J. Dall, A. A. Nielsen, R. Engholm, and H. Skriver, \"Improving SAR automatic target recognition models with transfer learning from simulated data\", GRSL, 2017"]}
DOI: 10.5281/zenodo.2105899
title: OTU table of genus from Tibet WWTPs

description: Activated sludge was collected from two municipal wastewater treatment plants (WWTPs) located in a high altitude Plateau in Tibet, China (~3650 m above the sea level). T1 is applied for cyclic activated sludge system (CASS), while T2 is operated at anaerobic-anoxic-aerobic (A2O) process. DNA samples were taken from bioreactor of T1, aerobic and anaerobic bioreactors of T2 (marked as T2AE and T2AN). The 16S rRNA gene amplicons of V4-V5 regions that were sequenced on an Illumina HiSeq PE250 platform, and then annotated using the 16S-Silva database. Data present here are normalized OTU relative number of each sample are presented at the taxonomic levels of genus.