cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/k47yd3m28w.4
title: H-Voice: Fake voice histograms (Imitation+DeepVoice)

description: This data set consists of (6672) histograms of original voice recordings and fake voice recordings obtained by Imitation [1, 2] and Deep Voice [3]. The histograms provided in this dataset can be used to train a machine learning system to classify original and fake voice recordings obtained with the imitation and Deep Voice algorithms. Each directory has the following composition: -- corrupted images have been fixed -- Training_fake: 2088 histograms of fake voice recordings (2016 with Imitation and with 72 Deep Voice) Training_original: 2020 histograms of original voice recordings Validation_fake: 864 histograms of fake voice recordings (all with Imitation) Validation_original: 864 histograms of original voice recordings External_test1: 760 histograms (380 original + 380 fake with Imitation) External_test2: 76 histograms (4 original + 72 fake with Deep Voice) References: [1] DM Ballesteros L, JM Moreno A. Highly transparent steganography model of speech signals using Efficient Wavelet Masking. Expert Systems with Applications 39 (10), 2012, 9141-9149, https://doi.org/10.1016/j.eswa.2012.02.066 [2] DM Ballesteros L, JM Moreno A. On the ability of adaptation of speech signals and data hiding, Expert Systems with Applications 39 (16), 2012, 12574-12579, https://doi.org/10.1016/j.eswa.2012.05.027 [3] S.O. Arik, M. Chrzanowski, A. Coates, G. Diamos, A. Gibiansky, Y. Kang, X. Li, J. Miller, A. Ng, J. Raiman, S. Sengupta, M. Shoeybi. Deep Voice: Real-time Neural Text-to-Speech. 2017. https://arxiv.org/abs/1702.07825
DOI: 10.17632/dhvrsdmvfz.1
title: chronic obstructive pulmonary disease hospitalization

description: Data regarding the relationship between walk,physical activity and the risk of chronic obstructive pulmonary disease hospitalization
DOI: 10.17632/zr5x7h25r3.1
title: Data Set for Optimization of Electric Vehicle Recharge Schedule and Routing Problem with Time Windows and Partial Recharge: A Comparative Study for an Urban Logistics Fleet

description: These data used to test VNS and VND optimization heuristics in paper titled "Optimization of Electric Vehicle Recharge Schedule and Routing Problem with Time Windows and Partial Recharge: A Comparative Study for an Urban Logistics Fleet". Data shared here includes small and large size instances for the optimization problem of electric vehicle routing problem with time windows and partial recharge (EWRPTW-PR) opportunities. Each instance includes different numbers of electric vehicles (EVs) used, customers (C), visits required by customers (V), depots (D), recharging stations (S). Size specification of data sets is given in "Specifications of data set.xlsx" file. Data is generated for different types of EVs with different load capacities, different battery capacities with different charging times, different travel times considering distance, speed and current random load. Provided data set can be used to test the effectiveness an efficiency of different vehicle routing algorithms designed for electric vehicles. Additionally, provided data is suitable for a comparison of heuristics with exact optimization methods.
DOI: 10.17632/nddmgkm3cc.4
title: A new method for analyzing sustainability performance of global supply chains and its application to material resources

description: VERSION 3 This version runs with all matlab versions (Version 1 has issues e.g. with matlab 2020) and it further covers the years 2012-2015. In addition, the exiobase data for the years 2010-2015 are already included in the Input_Data folder. The data of the remaining years (1995–2009) need to be downloaded from the exiboase homepage: https://www.exiobase.eu/index.php/data-download/exiobase3mon OVERALL DESCRIPTION (same as for version 1 and 2): We share here the data compiled to calculate the results presented in the study «A new method for analyzing sustainability performance of global supply chains and its application to material resources». In order to allow for the compilation of all results of interest, we provide an application. This application is based on the multi-regional-input output database EXIOBASE3 (version 3.4) and data to assess the potential environmental impacts of emissions and resource use. While the data for assessing the environmental impacts is provided here, the user must download the Exiobase data from the Exiobase website (due to copyright issues). The provided application allows to assess the cumulated upstream impacts of any sector or region on the globe without double-counting and to track these impacts upstream and downstream the global value chain. The application covers a broad set of environmental and socio-economic indicators and the timespan from 1995 to 2011. The methodology of this application is comprehensively explained in the study: «A new method for analyzing sustainability performance of global supply chains and its application to material resources» (e.g Section 2.1 gives a broad overview of the principle of the method). Link to the study: https://doi.org/10.1016/j.scitotenv.2019.04.434
DOI: 10.17632/ktmg7xtt4j.1
title: NACID - Nitrogen Deposition 1

description: This database contains estimates of annual total nitrogen (N) deposition for the purpose of supporting terrestrial ecosystem modelling in North America. It was constructed at 1-km resolution with coverage of Alaska, Canada, and the conterminous U.S., with continuous annual coverage from 1860 to 2013. Estimates were produced by acquiring and compiling best-available data sources: Wet N deposition was estimated from interpolation of monthly ammonium and nitrate concentration measurements and from grids of monthly precipitation. Dry N deposition was estimated from satellite measurements of ammonium and nitrogen oxides. Total N deposition for the pre-industrial era was derived from previous modelling studies. As these source datasets covered different time periods, several assumptions were required to produce a continuous record. Additional details are presented in Hember (2018). Hember, 2018. Spatially and temporally continuous estimates of annual total nitrogen deposition over North America, 1860-2013. Data In Brief. Specs: Version: 1 Release: 2017-11-30 Spatial coverage: Alaska, Canada, and conterminous United States Spatial resolution: 1 km Temporal coverage: 1860-2013 Temporal resolution: Annual Format: Geotiff Units: kgN/ha/yr Scale factor: 0.1
DOI: 10.17632/tmnwvtd24h.1
title: Replication folder for Forge, Garred and Kwon, "When are Tariff Cuts Not Enough? Heterogeneous Effects of Trade Preferences for the Least Developed Countries"

description: This is the replication folder for the Journal of International Economics paper "When are Tariff Cuts Not Enough? Heterogeneous Effects of Trade Preferences for the Least Developed Countries", which studies effects of extensions of the trade preferences offered by OECD countries to the least developed countries.
DOI: 10.17632/wb6yvr725d.3
title: A semi-simulated EEG/EOG dataset for the comparison of EOG artifact rejection techniques

description: This work presents a semi-simulated EEG dataset, where artifact-free EEG signals are manually contaminated with ocular artifacts following the model proposed by [1]. The significant part of this dataset is that it contains the pre-contamination EEG signals, so the brain signals underlying the EOG artifacts are known and thus the performance of every artifact rejection technique can be objectively assessed. The main differences of the proposed dataset compared to others (p.e. see [2,3]) is that it is focused only on EOG artifacts, using a realistic model for the contamination of artifact-free EEGs and not a random procedure. [1] T. Elbert, W. Lutzenberger, B. Rockstroh, N. Birbaumer, Removal of ocular artifacts from the EEG--a biophysical approach to the EOG., Electroencephalogr. Clin. Neurophysiol. 60 (1985) 455–63. http://www.ncbi.nlm.nih.gov/pubmed/2580697 (accessed April 10, 2013). [2] X. Yong, M. Fatourechi, R.K. Ward, G.E. Birch, Automatic artefact removal in a self-paced hybrid brain- computer interface system, J. Neuroeng. Rehabil. 9 (2012) 50. doi:10.1186/1743-0003-9-50. [3] A.K. Abdullah, C.Z. Zhang, A.A.A. Abdullah, S. Lian, Automatic Extraction System for Common Artifacts in EEG Signals Based on Evolutionary Stone’s BSS Algorithm, Math. Probl. Eng. 2014 (2014) 1–25. doi:10.1155/2014/324750.
DOI: 10.17632/3p8gcg3gbp.1
title: Data

description: Data for the research of public and fdi in Zimbabwe. . Data was obtained from several sources including the World Bank, the IMF, RBZ and Zimbabwe Statistical Office (ZIMSTATS). Data was collected on the two main variables for the study namely public debt and FDI. Public debt is the independent variable of interest whilst FDI is the dependent variable. FDI was measured by the FDI net inflows (in US$ million) for Zimbabwe for the period 1990 to 2021. Public debt was proxied by total government debt in US$ Billion.
DOI: 10.17632/x38yzs6cd3.1
title: Efficacy and Safety of Teprotumumab in the Treatment of Thyroid Eye Disease Patients with Long Duration and Low Disease Activity

description: SUPPLEMENT Efficacy and Safety of Teprotumumab in the Treatment of Thyroid Eye Disease Patients with Long Duration and Low Disease Activity: A Randomised Double-Masked, Placebo-controlled, Multicenter Trial Raymond S. Douglas et al
DOI: 10.17632/ygmrc3kcrt.1
title: Wind speed dataset

description: the dataset from the Sotavento wind farm in Galicia, Spain is utilized. The wind farm includes 24 onshore turbines with 17,560 kW capacity. It provides real-time data such as wind direction, speed, and power generated by the turbine.
DOI: 10.17632/mm7ygtx8vh.1
title: UCLA_1 Dataset (Locally Linear Embedding and fMRI feature selection for psychiatric classification)

description: ABIDE dataset collected at the University of California Los Angeles Ahmanson Lovelace Brain Mapping Centre
DOI: 10.17632/xdrwrh9zbk.2
title: Hemoglobin Photoplethysmography Dataset

description: Dataset consists of photoplethysmography (PPG) signal, Hb value, age, and gender. The PPG signal was measured by a MAX30102 module sensor that emitted two types of light (red and infrared light) and measured using a photodetector. The Hb value was measured by a Hb meter, Nesco Multicheck 2®. Total of 68 subjects (56% female and 44% male) within the age of 18-65 years were collected. The total dataset is 816 data from 68 subjects, which each subject provides 12 sets of red and infrared light signals. The data were collected at Primary Health Center Jatiuwung, Tangerang City, Banten 15138, Indonesia. Researchers interested in anemia monitoring and those pursuing the development of non-invasive hemoglobin measurement devices can leverage this dataset.
DOI: 10.17632/hd96prn3nc.1
title: DTU - Drone inspection images of wind turbine

description: This dataset set has temporal inspection images for the years of 2017 and 2018 of the same 'Nordtank' wind turbine at DTU wind facilities in Roskilde, Denmark.
DOI: 10.17632/6c2htvh94h.1
title: Data for: A symmetric alternating minimization algorithm for total variation minimization

description: A symmetric alternating minimization algorithm for total variation minimization.
DOI: 10.17632/syc2mnmswz.1
title: Signature Size and Individual Preferences

description: In this digital economy, customers’ handwriting, such as signatures and related characteristics, can be easily collected and quantitatively analyzed. From the perspective of decision-making, obtaining information from signature characteristics is an important data-driven business leverage. In this regard, can we infer individual preferences from signatures? Thus, through a large-scale laboratory experiment, this study measured the participants’ risk and time preferences and collected their signature information in order to determine the influence of behavioral preferences on their signatures. Based on the empirical results, the higher the risk and ambiguity aversion of the participants, the smaller is their signature size. Moreover, the greater their level of patience, the more likely their signatures showed a trend of increasing size. Overall, this study fills a research gap in signature-related behavior by highlighting the application of text mining in digital handwriting, especially in broad business settings such as the insurance industry.
DOI: 10.17632/v6m7br9vc3.2
title: Data for: Video Object Segmentation Based on Motion-Aware ROI Prediction and Adaptive Reference Updating

description: This contains experimental data for this article, including DAVIS 2017, DAVIS 2016 segmentation results and adaptive reference frame update process. In order to verify the validity of our algorithm, we also added the experimental results of the largest video object segmentation dataset YoutubeVOS.
DOI: 10.17632/54npy2ngm7.1
title: Supplementary Materials: Supplementation of isoacids to lactating dairy cows fed low- or high-forage diets: Effects on performance, digestibility, and milk fatty acid profile

description: This supplementary material provides a detailed breakdown of the ingredient composition used in the diets for lactating dairy cows supplemented with isoacids.
DOI: 10.17632/ggyh2g2mwj.1
title: Global online trade is driving poison dart frogs (family: Dendrobatidae) towards extinction

description: The datasets used to construct Figure 5 in the manuscript "Global online trade is driving poison dart frogs (family: Dendrobatidae) towards extinction" were written by me.
DOI: 10.17632/v7nmy2296k.1
title: Proteins with amino acid repeats constitute a rapidly evolvable and human-specific essentialome. Anjali K Singh et al.

description: Essential genes, and their protein products, are necessary for organismal survival. These proteins, owing to their functional indispensability, are conserved and perform fundamental biological processes. Contrarily, proteins which contain stretches of identical amino acids (referred as homorepeats) tend to evolve rapidly, as repetitive sequences are hypermutable. Strikingly, eukaryotic essentialomes are enriched for proteins with amino acid homorepeats. This presents a function versus evolution paradox, as to why are the hypermutable homorepeats prevalent in essential proteins with conserved functionalities. In this study, we resolve this paradox by undertaking systems-level analyses in humans by assembling and integrating 60 publicly-available large-scale datasets spanning sequence, structure, molecular networks, regulation, spatio-temporal expression, phenotype and evolution. We found that essential proteins with homorepeats
(i) Show molecular pleiotropy, i.e., they are multifunctional and bring about cross-talk between processes,
(ii) Participate in regulatory processes and bring about expansive regulation at the genomic and transcriptomic levels, while essential proteins without repeats, are preponderantly involved in housekeeping functions
(iii) Rapidly evolve, with amino acid substitutions often affecting functionally important sites such as Post translational modification sites aiding rapid network rewiring and
(iv) Are involved in dynamic and human-specific temporal regulation of human embryonic and brain development, facilitating the emergence and evolution of human-specific processes.
The presence of repeats in essentialomes brings about a trade-off between robustness and evolvability facilitating rapid adaptability.

Here, we have uploaded all molecular interaction networks that were compiled and investigated in this study. We have also added the source code to facilitate repetition of this work and address other fundamental systems- and molecular-level questions. The instructions regarding usage of the codes are provided in individual scripts.
DOI: 10.17632/vpykhtncdz.1
title: Global Database of Foraminiferal Organic Linings: ForamL Version 1.3

description: This database is an updated collection of references to images of Foraminiferal Organic Linings (FOLs) published in the available scientific literature (see Godos et al., 2021). All organic linings are derived from recent marine samples and sedimentary rocks worldwide. The previous analysis of these publications resulted in a collection of 155 scientific reports, illustrating 614 foraminiferal organic linings. Here we presented an updated version of ForamL contains 207 additional images not published in Godos et al. (2021). Most of them have been published recently, since 2021. All of the 821 organic linings have been assigned to supraordinal groups of the phylum Foraminifera (Pawlowski et al. 2013), as well as to basic morphologic types of chamber arrangements. The database consists of three tables that cover the whole Phanerozoic, split into the Cenozoic, Mesozoic, and Paleozoic, and then to systems/periods such as the “modern period”, Quaternary, Neogene, Paleogene, Cretaceous, Jurassic, Triassic, and older intervals. The ”modern period” is a very short artificial period created by the authors, encompassing foraminiferal organic linings collected from natural environments, representing both living and dead material. This group includes subfossil remains found in marine sediments that were not fully fossilized. They are considered to be relatively young on a geological scale, having come from periods too recent to be classified as true fossils. For each system, scientific publications are referenced chronologically by year of publication. 
The main criterion on which the available publications were evaluated in our analysis was the preparation methods: we included the research based on the on palynological procedures. The procedures included treating samples with hydrochloric acid (HCl) to remove carbonates, followed by hydrofluoric acid (HF) to remove silicates from the sample. The next step was to sieve the extracted organic matter through a 10 or 15 or 20 μm sieve to separate larger organic particles, including palynomorphs with foraminiferal organic linings, for further preparation of palynological slides.
DOI: 10.17632/kpftzmsyyz.2
title: Datasets of Land Use Change and Flood Dynamics in the Vietnamese Mekong Delta

description: These datasets include 21 land use maps and 567 flooding maps in the Vietnamese Mekong Delta from 2000 to 2020 based on MODIS satellite products.
DOI: 10.17632/p657pvtb5h.1
title: Seed ball dataset

description: Data used for the paper titled "Viability of seed balls for large-scale restoration of native plant communities in New Zealand" to be published in the New Zealand Journal of Botany.
DOI: 10.17632/x9mv4krnm2.2
title: United States Surface Urban Heat Island database

description: This dataset contains urban and rural LST, DEM, and NDVI data for annual, summer, and winter daytime and nighttime for all census tracts in US urbanized areas, as well as the mean values for the entire urbanized area. METADATA DEM: Digital Elevation Model NDVI: Normalized Difference Vegetation Index LST: Land Surface Temperature _urb: Urban values (all urban pixels within urbanized areas) _rur: Rural reference (Spatial mean of the non-urban, non-water pixels within the region of interest) Regions of Interest: _CT: Spatial mean of pixels intersecting the Census Tract clipped to the urbanized area (one value per census tract). This should be equal to the _CT for census tracts that are completely within the urbanized areas (the census tracts with the green dots in the image below) _all: Spatial mean of all pixels intersecting the urbanized area, as defined by the US census (one value for one urbanized area) _CT_act: Spatial mean of all available pixels intersecting the Census Tract (one value per census tract) [This should be equal to the previous values I calculated] For the UHI: The ideal configuration is LST_urb_all-LST_rur_all for the entire urbanized area (from the US_Urbanized file) and LST_urb_CT_act-LST_rur_all for individual census tracts within the urbanized areas (from the census file) For the equity analysis: Either _CT or CT_act can be used if we are only concerned with spatial variation. Using CT_act leads to mismatch between census data for the tracts crossing the urban boundary and the remotely sensed data. Using _CT leads to mismatch between the UHI analysis and the equity analysis.
DOI: 10.17632/4sgt9tjs4w.3
title: ITC-Net-Blend-60: A Comprehensive Dataset for Robust Network Traffic Classification in Diverse Environments - Supplementary Materials

description: This repository contains supplementary material for the ITC5ScenMoblieApp dataset. It includes Python scripts to filter background traffic and extract capture file properties. Additionally, it contains documents detailing the traffic capture properties for each scenario - broken down per file and per application.
DOI: 10.17632/fp46gc7p33.2
title: Data for: Buckling and postbuckling of advanced grid stiffened truncated conical shells with laminated composite skins

description: The closed form formulation of buckling load and postbuckling behavior of advanced grid stiffened conical shells with laminated composite skins are translated to code in MATLAB software. All parameters of structure can be defined and then outputs can be evaluated through this code.
DOI: 10.17632/zjzhmgs3vx.1
title: Supplementary Table 3

description: Raw data of GC-MS profile of hydrocarbons degraded by Pseudomonas frederiksbergensis SI8 grown for 14 days at 4ºC in Jet A fuel.
DOI: 10.17632/jp567yrh6g.1
title: 2019 Atherosclerosis (Deep learning algorithm for CAD-RADS classification with CCTA)

description: Background and aims: Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary computed tomography angiography (CCTA) in the correct Coronary Artery Disease Reporting and Data System (CAD-RADS) category. Methods: Two hundred eighty eight patients who underwent clinically indicated CCTA were included in this single-center retrospective study. The CCTAs were stratified by CAD-RADS scores by expert readers and considered as reference standard. A deep CNN was designed and tested on the CCTA dataset and compared to on-site reading. The deep CNN analyzed the diagnostic accuracy of the following three Models based on CADRADS classification: Model A (CADRADS 0 vs CADRADS 1-2 vs CADRADS 3,4,5), Model 1 (CADRADS 0 vs CADRADS&gt;0), Model 2 (CADRADS 0-2 vs CADRADS 3-5). Time of analysis for both physicians and CNN were recorded. Results: Model A showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 47%, 74%, 77%, 46% and 60%, respectively. Model 1 showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 66%, 91%, 92%, 63%, 86%, respectively. Conversely Model 2 demonstrated the following sensitivity, specificity, negative predictive value, positive predictive value and accuracy: 82%, 58%, 74%, 69%, 71%, respectively. Time of analysis was significantly lower using CNN as compared to on-site reading (530.5179.1vs104.31.4 seconds, p:0.01) Conclusions: Deep CNN yielded accurate automated classification of patients with CAD-RADS.