cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4429297
title: Example 6-hour directory for FV3GFS atmospheric model

description: This dataset serves as an example run directory for the FV3GFS atmospheric model, used in publications to show execution of the Python-wrapped FV3GFS atmospheric model. Files in rundir/grb provided by the National Oceanic and Atmospheric Administration (NOAA) Environmental Modeling Center (EMC) are public domain. All other data and configuration files are distributed under a Creative Commons Attribution-ShareAlike 4.0 International License. SHiELD/FV3 model data and input files produced by the Geophysical Fluid Dynamics Laboratory is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.
description: We would like to acknowledge the many contributions of colleagues at NOAA EMC and GFDL towards the data used to compile this dataset.
DOI: 10.5281/zenodo.4279017
title: PICCOLO White-Light and Narrow-Band Imaging Colonoscopic Dataset

description: The PICCOLO White-Light and Narrow-Band Imaging Colonoscopic dataset comprises 3433 manually annotated images (2131 white-light images 1302 narrow-band images), originated from 76 lesions from 40 patients, which are distributed into training (2203), validation (897) and test (333) sets assuring patient independence between sets. Furthermore, clinical metadata are also provided for each lesion.
description: {"references": ["S\u00e1nchez-Peralta, L.F.; Pagador, J.B.; Pic\u00f3n, A.; Calder\u00f3n, \u00c1.J.; Polo, F.; Andraka, N.; Bilbao, R.; Glover, B.; Saratxaga, C.L.; S\u00e1nchez-Margallo, F.M. PICCOLO White-Light and Narrow-Band Imaging Colonoscopic Dataset: A Performance Comparative of Models and Datasets. Appl. Sci. 2020, 10, 8501."]}
DOI: 10.5281/zenodo.4279016
title: PICCOLO White-Light and Narrow-Band Imaging Colonoscopic Dataset

description: The PICCOLO White-Light and Narrow-Band Imaging Colonoscopic dataset comprises 3433 manually annotated images (2131 white-light images 1302 narrow-band images), originated from 76 lesions from 40 patients, which are distributed into training (2203), validation (897) and test (333) sets assuring patient independence between sets. Furthermore, clinical metadata are also provided for each lesion.
description: {"references": ["S\u00e1nchez-Peralta, L.F.; Pagador, J.B.; Pic\u00f3n, A.; Calder\u00f3n, \u00c1.J.; Polo, F.; Andraka, N.; Bilbao, R.; Glover, B.; Saratxaga, C.L.; S\u00e1nchez-Margallo, F.M. PICCOLO White-Light and Narrow-Band Imaging Colonoscopic Dataset: A Performance Comparative of Models and Datasets. Appl. Sci. 2020, 10, 8501."]}
DOI: 10.6084/m9.figshare.13553432
title: draft_assemblies.tar.gz

description: Draft genome assemblies for 82 KpSC strains used for benchmarking.
DOI: 10.23729/6273175a-ba2d-4126-83f3-b1bb31f3e2e3
title: Talvivaara-Vuonos preview

description: Two related rock samples from different locations. 3433:305_150.89m is from the Kolmisoppi ore deposit in Talvivaara mine, Finland. Sample was drilled by GTK before mining started. It is black slate that was imaged for a detailed 3D structure study. Same piece of rock has been investigated in detailed sulphur isotopic studies published in GTK Current Research in 1995: Loukola-Ruskeeniemi, K., 1995. Origin of the Talvivaara black-shale-hosted Ni-Cu-Zn deposit, eastern Finland. Other results from the same sample have been published in Loukola-Ruskeeniemi, K., Heino, T., 1996. Geochemistry and Genesis of the Black Shale-Hosted Ni-Cu-Zn Deposit at Talvivaara, Finland. Economic Geology. and Loukola-Ruskeeniemi, K., Lahtinen, H., 2012. Multiphase evolution in the black-shale-hosted Ni-Cu-Zn-Co deposit at Talvivaara, Finland. Ore Geology Reviews 52. Sample Vuonos has been described eg. in Loukola-Ruskeeniemi, K., 1999. Origin of Black Shales and the Serpentinite-Associated Cu-Zn-Co Ores at Outokumpu, Finland. Preview of PAS-dataset https://doi.org/10.23729/fe302b89-00e5-4805-a841-a02a37986436
DOI: 10.17632/zw4kstvxwp.1
title: Detecting trees near electric wires with Deep Learning

description: Urban images and scripts used to train and test a deep leaning framework architecture to classify images as having or not intersections between trees and overhead powerlines/wires.
DOI: 10.17632/zgrngg5hp5.3
title: Data for: Modelling the global economic consequences of a major African swine fever outbreak in China

description: Global model results of simulated shocks to pork production in China used in Mason-D'Croz et al (2020) to assess potential impacts of an African Swine Fever outbreak in China on the global food system. The scenarios explored a range of production shocks (20-80 percent), as well as sensitivity analysis around different assumptions on consumer responses. The results were simulated in a coupled bioeconomic modelling suite which included IMPACT, a global partial equilibrium model of the agriculture sector, and GLOBE, a global general equilibrium model of the full economy. Full analysis of these scenarios is available in Mason-D'Croz et al. (2020) published in Nature Food. Data available for download include: - Extended model results for IMPACT and GLOBE (Model Results Supplementary Data...) - Data underlying figures in Mason-D'Croz et al. (Published figures...) How to cite: Please cite both the mendeley dataset and the primary analysis Mason-D'Croz, D., J.R. Bogard, M. Herrero, S. Robinson, T.B. Sulser, K. Wiebe, D. Willenbockel, and H.C.J. Godfray (2020). "Modelling the global economic consequences of a major African swine fever outbreak in China". Nature Food. Mason-D'Croz, D., J.R. Bogard, M. Herrero, S. Robinson, T.B. Sulser, K. Wiebe, D. Willenbockel, and H.C.J. Godfray (2020). “Data for: Modelling the global economic consequences of a major African swine fever outbreak in China”, Mendeley Data, VX, doi: 10.17632/zgrngg5hp5.1
DOI: 10.17632/234jzp8stj.1
title: Dataset For CMAQ-3DVAR

description: This dataset is for the manuscript ‘Development of three-dimensional variational data assimilation method of aerosol for the CMAQ model: an application for PM2.5 and PM10 forecasts in the Sichuan Basin’. It includes the observation and the aerosol emission which has been deal with to fit the model grids used in the manuscript. Any questions please contact NUIST_ZZD@163.com.
DOI: 10.17632/3nyvj834p7.1
title: SP&AIC

description: Data deposition for the paper ‘Project schedule expediting under structural and parametric uncertainty’ by Nazimko V. and Zakharova L. File 2021.xlsx contains: List ‘initial data’ – min, mode, max duration of the tasks taken from Tolentino Rena, R.A. (2009). Project management: A simulation-based optimization method for dynamic time-cost tradeoff decisions (M.S. thesis) Rochester, NY: Rochester Institute of Technology List ‘Critical Paths’ – critical paths and their frequencies (probabilitiwes) received by SP and AIC run List ‘Task criticality’ – tasks criticality received by SP and AIC run List ‘Results’ – results of the run of SP and AIC. These results are dublicated in the file ‘result_realdstr.dat’ as output file of SP and AIC running.
DOI: 10.17632/6r8f9w87n2.1
title: An investigation of the effects of extraction and brushing variables on the properties of hedge sisal fibers using a raspador

description: This is the dateset for a project on the effects of extraction and brushing variables on the properties of sisal fibers.
DOI: 10.17632/6tmctzwkxf.1
title: Dataset for "A common framework for passive and active mitigation devices. Application to a scale two-storey building."

description: This dataset contains the experimental time series and FRF data associated to the article "A common Framework for Tuned and Active Mass Dampers. Application to a Two-Storey building model" published in the Experimental Techniques journal (10.1007/s40799-020-00432-2). Both folders contain a readme.txt file with a more detailed description of the files contents.
DOI: 10.17632/hy94fnc9d9.1
title: LINF_060010500

description: hypothetical protein - conserved; Leishmania infantum
DOI: 10.17632/9krhrpmwgz.1
title: LINF_060010600

description: SpoU rRNA Methylase family; Leishmania infantum
DOI: 10.17632/xfxdwgm3rb.1
title: LINF_060011200

description: dUTP nucleotidohydrolase | deoxyuridine triphosphatase; Leishmania infantum
DOI: 10.17632/r39n8sxyzr.3
title: The unexplored duality of poverty: cognitive costs and specialized adaptation. An RCT approach.

description: To replicate the results, download all files from the /input folder. If necessary, create the /input and /output folder locally on your computer. Then download the .Rmd file and run all the script.
DOI: 10.17632/4vgy45mzr2.6
title: Effect of modified properties on geologic carbon storage

description: Research data for a manuscript under peer-review
DOI: 10.17632/k6wv3kffzs.3
title: Replication data for "Urbanization Policy and Economic Development: A Quantitative Analysis of China’s Differential Hukou Reforms"

description: The codes to replicate the results in "Urbanization Policy and Economic Development: A Quantitative Analysis of China’s Differential Hukou Reforms" by Wen-Tai Hsu and Lin Ma
DOI: 10.17632/nvcwgy2y4p.5
title: Microbial modified mechanical properties of shales

description: Research data for a manuscript under peer-review
DOI: 10.17632/ftp6xbx5gd.1
title: vaurien film complet vf

description: https://springfield.instructure.com/eportfolios/20715/Home/Regarder_Vaurien_2021_film_complet_en_francais_gratuit_en_ligne https://springfield.instructure.com/eportfolios/20716/Home/REGARDERVaurien_2021_Film_Streaming_Online_VF https://springfield.instructure.com/eportfolios/20717/Home/_VOSTFRVaurien_FILM__2021__Streaming_VF https://springfield.instructure.com/eportfolios/20718/Home/Regarder_HD_1080p_Vaurien_Film_complet_VOSFR_en_France https://springfield.instructure.com/eportfolios/20719/Home/Vaurien_2021_Film_Complet_Streaming_VF_Entier_Franais https://springfield.instructure.com/eportfolios/20721/Home/Regarder_Vaurien_2021_Film_Complet_streaming_vf https://springfield.instructure.com/eportfolios/20722/Home/Regarder_Film_Vaurien_Streaming_2021_VF_Complet_En_Ligne https://springfield.instructure.com/eportfolios/20723/Home/Voir_Vaurien_2021_film_streaming_complet_vf_vostfr_gratis https://springfield.instructure.com/eportfolios/20724/Home/REGARDER_Vaurien_2021_en_Streaming_VF_GRATUIT_Complet_HD https://springfield.instructure.com/eportfolios/20725/Home/Regarder_Vaurien_2021_Streaming_vf__Film_complet
DOI: 10.17632/f35nry7hjz.1
title: A Test to Compare Interval Time Series - Supplementary Material

description: Supplementary material for the manuscript "A Test to Compare Interval Time Series". This includes figures and tables referred to in the manuscript as well as details of scripts and data files used for the simulation studies and the application. All scripts are in MATLAB (.m) format and data files are is MATLAB (.mat) and in EXCEL (. xlsx) formats.
DOI: 10.17632/n59hcz4r3n.1
title: Data for: Morphology change of submerged artificial sandbar and its impacts on beach evolution under erosive wave condition

description: This data was uploaded for supporting findings in the manuscript entitled 'Morphology change of submerged artificial sandbar and its impacts on beach evolution under erosive wave condition' which will be submitted to Marine Geology. The data included beach profile evolution and detailed artificial sandbar morphological changes and berm responses.
DOI: 10.17632/yvvmz7w9xt.1
title: Dateset for studying the dominant control of relief on soil water content distribution during wet-dry transitions in headwaters

description: This dataset used to generate figures and tables (including the supporting information) for the paper entitled The dominant control of relief on soil water content distribution during wet-dry transitions in headwaters.
DOI: 10.17632/ffn745r57z.2
title: Data for "Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics"

description: Prediction of Phakic Intraocular Lens Vault Using Machine Learning of Anterior Segment Optical Coherence Tomography Metrics. Authors: Kazutaka Kamiya, MD, PhD, Ik Hee Ryu, MD, MS, Tae Keun Yoo, MD, Jung Sub Kim MD, In Sik Lee, MD, PhD, Jin Kook Kim MD, Wakako Ando CO, Nobuyuki Shoji, MD, PhD, Tomofusa, Yamauchi, MD, PhD, Hitoshi Tabuchi, MD, PhD. We hypothesize that machine learning of preoperative biometric data obtained by the As-OCT may be clinically beneficial for predicting the actual ICL vault. Therefore, we built the machine learning model using Random Forest to predict ICL vault after surgery. This multicenter study comprised one thousand seven hundred forty-five eyes of 1745 consecutive patients (656 men and 1089 women), who underwent EVO ICL implantation (V4c and V5 Visian ICL with KS-AquaPORT) for the correction of moderate to high myopia and myopic astigmatism, and who completed at least a 1-month follow-up, at Kitasato University Hospital (Kanagawa, Japan), or at B&VIIT Eye Center (Seoul, Korea). This data file (RFR_model(feature=12).mat) is the final trained random forest model for MATLAB 2020a. Python version: *************************************************************** from sklearn.model_selection import train_test_split import pandas as pd import numpy as np from sklearn.ensemble import RandomForestClassifier from sklearn.ensemble import RandomForestRegressor # connect data in your google drive from google.colab import auth auth.authenticate_user() from google.colab import drive drive.mount('/content/gdrive') # Change the path for the custom data # In this case, we used ICL vault prediction using preop measurement dataset = pd.read_csv('gdrive/My Drive/ICL/data_icl.csv') dataset.head() #optimal features (sorted by importance) : # 1. ICL size 2. ICL power 3. LV 4. CLR 5. ACD 6. ATA # 7. MSE 8.Age 9. Pupil size 10. WTW 11. CCT 12. ACW y = dataset['Vault_1M'] X = dataset.drop(['Vault_1M'], axis = 1) # Split the dataset to train and test data, if necessary. # For example, we can split data to 8:2 as a simple validation test train_X, test_X, train_y, test_y = train_test_split(X, y, test_size=0.2, random_state=0) # In our study, we already defined the training (B&VIIT Eye Center, n=1455) and test (Kitasato University, n=290) dataset, this code was not necessary to perform our analysis. # Optimal parameter search could be performed in this section parameters = {'bootstrap': True, 'min_samples_leaf': 3, 'n_estimators': 500, 'criterion': 'mae' 'min_samples_split': 10, 'max_features': 'sqrt', 'max_depth': 6, 'max_leaf_nodes': None} RF_model = RandomForestRegressor(**parameters) RF_model.fit(train_X, train_y) RF_predictions = RF_model.predict(test_X) importance = RF_model.feature_importances_
DOI: 10.17632/v2jrv3s58c.2
title: Dataset for SEM and ANN analysis in cloud computing acceptance

description: This article includes analytical results an raw data for our research. Using the Unified Theory of Acceptance and Use of Technology (UTAUT), this study seeks the predictors of individual-level adoption of cloud computing (CC) by combining structural equation modeling (SEM) and an artificial neural network (ANN) to analyze data collected by an online survey in South Korea. The dataset consists of four hundred valid responses of general public in South Korea using cloud computing. The dataset has seven variables such as performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, habit and behavioral intention.
DOI: 10.17632/hmk63hc686.1
title: Alcala_etal_2021_Ext&Patt

description: This is the data set analysed in Experiment and Experiment 2 of the manuscript entitled "Experiencing Extinction Facilitates Subsequent Acquisition of Positive, but not Negative Patterning in Human Predictive Learning".
DOI: 10.17632/zc67y4m47v.2
title: Analysis of options for treatment of varicose veins

description: Model of options for treatment of varicose veins: spreadsheet model, dataset from systematic review, and meta-analysis script (STATA)
DOI: 10.17632/vmp5hx97rj.1
title: Indonesian local government bureaucracy reform and performance management 2018-2019

description: The dataset shows the result of bureaucracy reform index and performance management (SAKIP) index of 54 local governments in Indonesia from 2018-2019. Data is gathered from the Ministry of Administrative and Bureauratic Reform (Kemen PANRB). The use of this data can only be done by asking for contributor's permission due to the restriction made by Kemen PANRB.
DOI: 10.17632/h4tdmjkg5r.1
title: Supplementary Data A5

description: Phylogeny of odorant receptor (OR) amino acid sequences inferred under the optimality criterion Maximum Likelihood after 250 bootstrap tree convergence (figure image) and the phylogenetic tree file (newick format). The gene tree was rooted with the ORCo clade. Identified clades (names adopted from Zhou et al. 2015) clustering with at least 70% bootstrap support are labeled alphabetically A to Z, ZA, ORCo, and 9-exon with some entries "Unclassified" (Zhou et al. 2012; Zhou et al. 2015; McKenzie and Kronauer 2018), and another labeled Novel, had not been formally identified in previous studies. The clades exclusively found in species not sampled by us are not indicated here but are shown in Supplementary Figure S4. Results show species-specific expansions of OR gene subfamilies.
DOI: 10.17632/r8p67nfjc8.3
title: Multi-Omic Pan-Cancer data from TCGA.

description: Data consist of three omic blocks from The Cancer Genome Atlas (TCGA), containing whole-genome profiles of -Gene expression (file GE.RData), -DNA methylation (file METH.RData), and -Copy number variants (file CNV.RData). Omic profiles consist of information from 5,408 tumor samples across 33 cancer types (as matrix rows), and 60,112 features (expression of 20,319 genes, methylation of 28,241 CpG islands, and copy number variant intensity for 11,552 genes). GE profiles by sample corresponded with the logarithm of RNA-Seq counts by gene (Illumina HiSeq RNA V2 platform). METH profiles corresponded with CpG sites B-values from the Illumina HM450 platform, summarized at the CpG island level, using the maximum connectivity approach from the WGCNA R package (Langfelder and Horvath 2008) , and further transformed into M-values (M=beta/(1-beta); Du et al. 2010). Omic blocks were adjusted for batch and tissue specific effects (see Gonzalez-Reymundez and Vazquez (2020) and references therein for further details on quality controls and data edition).
DOI: 10.17632/jj992d7cvd.1
title: Mémek a koronavírus idején

description: A kutatás során a koronavírus 2020-as első hulláma alatt megjelent népszerű mémeket elemeztük kvalitatív, deduktív tartalomelemzéssel. A feltöltött fájlokban megtalálható a magyar és az olasz minta, valamint az elemzési eredményeket tartalmazó táblázat is. Itt az elemzett mémeket téma, stresszor, érzelem, valamint humorstílus szempontjából kategorizáltuk.
DOI: 10.17632/5xngwv5kps.1
title: A simple regulatory architecture allows learning the statistical structure of a changing environment

description: Python 3.7.4 simulation code and scripts reproducing all figures in Landmann, Holmes, Tikhonov (2021) "A simple regulatory architecture allows learning the statistical structure of a changing environment". Optional pre-computed simulation data included to speed-up figure plotting; remove or rename any data file to rerun the relevant simulations from scratch. Code by Stefan Landmann.
DOI: 10.17632/497wsb3nsm.1
title: microRNA-mediated translational control of antiviral immunity by the cap-binding protein 4EHP. Xu et al.

description: Original unprocessed data accompanying the manuscript "microRNA-mediated translational control of antiviral immunity by the cap-binding protein 4EHP".
DOI: 10.17632/ddf4dcjf57.2
title: Nuclear Latency, Nuclear Power and Nuclear Proliferation

description: The dataset for the replication of "Nuclear Latency, Nuclear Power and Nuclear Proliferation" paper.
DOI: 10.17632/89v7d4wmmk.1
title: Distinct geochemical behavior of water in olivine between silicate and carbonatite metasomatism

description: Water content analysis result.
DOI: 10.17632/n468trh5my.1
title: (Dataset) The most visited health websites in the world

description: Evaluation of the most visited health websites in the world
DOI: 10.17632/7yw7fj7p5w.1
title: Big Fish in Thin Markets: Competing with the Middlemen to Increase Market Access in the Amazon

description: These codes and datasets can be used to replicate the analyses in the paper, "Big Fish in Thin Markets: Competing with the Middlemen to Increase Market Access in the Amazon."
DOI: 10.17632/kk6tng94xr.1
title: Fully 3D Modeling of Single-Phase Fluid Flow

description: Data for a Fully 3D Modeling of Single-Phase Fluid Flow in Fractured-Vuggy Carbonate Formations
DOI: 10.17632/85d73fv3y2.2
title: Data for Fully 3D Modeling of Single-Phase Fluid Flow

description: Data for a Fully 3D Modeling of Single-Phase Fluid Flow in Fractured-Vuggy Carbonate Formations Using the Transient Brinkman Equation Coupled with the Second-order Gradient Rock Mechanics Equation Including Porosity Evolution study
DOI: 10.17632/dwg3ggtfgg.1
title: nf1 gene data

description: nf1 gene mutation of patients with Neurofibromatosis Type 1 dataset
DOI: 10.17632/vv5ch6yb6v.1
title: Data for "Pre-decisional information acquisition: why do we pay too much for information?"

description: This is the original data for the paper "Pre-decisional information acquisition: why do we pay too much for information?" in Journal of Economic Psychology
DOI: 10.17632/dx8kbs5yxc.1
title: HHVannPRO: ANN trained to predict the biomass HHV based on the results of the proximate analysis

description: For the comparative analysis of different algorithms for training the ANNs the same network structure is used but with diferent training functions. In all cases this network was fed with the same sets of input data. Data sets were formed on the basis of literature data on measured HHV of biomass characterized by the proximate analysis. In order to improve the ANNs response, the training data sets were augmented with the additional literature data on measured HHV and biomass composition in terms of the proximate analysis, so that the final set of data consisted of 318 training input records and corresponding 318 outputs. The custom designed MATLAB functions were then applied to a new set of input data completely unknown to ANNs and the results were recorded.