cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/m0fa-mc71
title: Reconstruction of the admissible joint-references for the N-trailer kinematics: the source Matlab files.

description: This dataset consists of the source Matlab files (the m-files) which implement the computational Newton-like algorithm solving the reconstruction problem for the joint-references of the non-Standard and Generalized N-Trailers upon a prescribed reference path of the last trailer. A user can examine the effectiveness and properties of the algorithm by selecting one of the seven possible 3-trailer structures with various types of hitching. The default reference path prescribed for the last trailer implemented in the code is a parametrized Lissajous-like closed curve defined on the normalized interval [0,1] of the parametrizing variable. Forward as well as backward motion strategy can be selected. The program computes a set of parameters (the weights) for a Fourier basis with up to 2000 harmonics chosen to approximate an evolution of the reference joint angles. The results being obtained during the computations are plotted on-the-fly, and the approximation accuracy is provided by the values of quality factors.
DOI: 10.21227/3ng6-z728
title: Reconstruction of the admissible joint-references for the N-trailer kinematics: the source Matlab files.

description: This dataset consists of the source Matlab files (the m-files) which implement the computational Newton-like algorithm solving the reconstruction problem for the joint-references of the non-Standard and Generalized N-Trailers upon a prescribed reference path of the last trailer. A user can examine the effectiveness and properties of the algorithm by selecting one of the seven possible 3-trailer structures with various types of hitching. The default reference path prescribed for the last trailer implemented in the code is a parametrized Lissajous-like closed curve defined on the normalized interval [0,1] of the parametrizing variable. Forward as well as backward motion strategy can be selected. The program computes a set of parameters (the weights) for a Fourier basis with up to 2000 harmonics chosen to approximate an evolution of the reference joint angles. The results being obtained during the computations are plotted on-the-fly, and the approximation accuracy is provided by the values of quality factors.
DOI: 10.21227/hmxk-5z83
title: Reconstruction of the admissible joint-references for the N-trailer kinematics: the source Matlab files.

description: This dataset consists of the source Matlab files (the m-files) which implement the computational Newton-like algorithm solving the reconstruction problem for the joint-references of the non-Standard and Generalized N-Trailers upon a prescribed reference path of the last trailer. A user can examine the effectiveness and properties of the algorithm by selecting one of the seven possible 3-trailer structures with various types of hitching. The default reference path prescribed for the last trailer implemented in the code is a parametrized Lissajous-like closed curve defined on the normalized interval [0,1] of the parametrizing variable. Forward as well as backward motion strategy can be selected. The program computes a set of parameters (the weights) for a Fourier basis with up to 2000 harmonics chosen to approximate an evolution of the reference joint angles. The results being obtained during the computations are plotted on-the-fly, and the approximation accuracy is provided by the values of quality factors.
DOI: 10.21227/p4vw-zd79
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains the IDs of geo-tagged tweets. The tweets were captured by an on-going project deployed at https://live.rlamsal.com.np. The geolocation data was extracted from the tweets which mentioned anything about "corona", "covid-19", "coronavirus" or the variants of "sars-cov-2". Complying with Twitter's data sharing policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted with an exact location that contained any of the previously mentioned keywords.Note: I started sharing the IDs of the tweets that contained the exact location information, only since April 28, 2020, with some genuine requests coming in from academic researchers who did not want to hydrate the whole lists of IDs (above 100+ million tweets) shared in the Coronavirus (COVID-19) Tweets Dataset.If you need the geolocation-based data starting March 20, 2020, then use the Coronavirus (COVID-19) Tweets Dataset and hydrate the IDs while adding the following condition:data = json.loads(data) if data["coordinates"]: longitude, latitude = data["coordinates"]["coordinates"]The data is available in two formats: CSV and JSON. I'll be sharing new files every day, and the files will be named period-wise. For example, april28-april29.* will contain tweet ID and sentiment data of the tweets that were tweeted between April 28, 2020, and April 29, 2020.
DOI: 10.5281/zenodo.3840764
title: Paired fruit flies synchronize behavior - data

description: This contains the .mat file with behavioral labels, heading direction, and centroid data for female/female, male/male, and courtship (female/male) pairings of <em>Drosophila melanogaster. </em>
DOI: 10.5281/zenodo.3840765
title: Paired fruit flies synchronize behavior - data

description: This contains the .mat file with behavioral labels, heading direction, and centroid data for female/female, male/male, and courtship (female/male) pairings of <em>Drosophila melanogaster. </em>
DOI: 10.5519/qd.jbnznj5y
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (42 records)
DOI: 10.3886/e119567v2
title: Are Parents’ Ratings and Satisfaction with Preschools related to Program Features

description: This study examines whether parents’ overall satisfaction with their child’s early childhood education (ECE) program is correlated with a broad set of program characteristics, including (a) observational assessments of teacher-child interactions; (b) structural features of the program, such as teacher education and class size; (c) practical and convenience factors (e.g., hours, cost); and (d) a measure of average classroom learning gains. It then describes associations between parents’ evaluation of specific program characteristics and externally collected measures of those features. Leveraging rich data from a sample of low-income parents whose 4-year-olds attend publicly funded ECE programs, we find little correspondence between parents’ evaluations of program characteristics and any external measures of those same characteristics. We discuss policy implications, especially in light of recent federal and state informational initiatives, which aim to help families make informed ECE choices.
DOI: 10.21227/zrx3-tk28
title: Lower Limb Prostheses Environmental Context Dataset

description: This is the data for paper "Environmental Context Prediction for Lower Limb Prostheses with Uncertainty Quantification" published on IEEE Transactions on Automation Science and Engineering, 2020. DOI: 10.1109/TASE.2020.2993399. For more details, please refer to https://research.ece.ncsu.edu/aros/paper-tase2020-lowerlimb.
DOI: 10.5281/zenodo.3841672
title: Towards Green Cartography & Visualization: An automated, semantically-enriched method of generating energy-aware color schemes for digital maps and visualizations

description: Towards Green Cartography & Visualization: An automated, semantically-enriched method of generating energy-aware color schemes for digital maps and visualizations
DOI: 10.5281/zenodo.3841673
title: Towards Green Cartography & Visualization: An automated, semantically-enriched method of generating energy-aware color schemes for digital maps and visualizations

description: Towards Green Cartography & Visualization: An automated, semantically-enriched method of generating energy-aware color schemes for digital maps and visualizations
DOI: 10.5281/zenodo.3841379
title: Chronicle of Nature - Phenology of Insects of Oka State Nature Biosphere Reserve

description: Insects Phenology dataset compiled in the context of Chronicle of Nature program in Oka State Nature Biosphere Reserve (Russian Federation) consisting of 1315 records collected during 85 years between 1938 and 2019.
description: This dataset export was created by EarthCape software platform version 20.4.38.0
DOI: 10.5281/zenodo.3841841
title: Linked COVID-19 Data: Johns Hopkins University (JHU) and European Centre for Disease Prevention and Control (ECDC)

description: Linked COVID-19 Data derived from <strong>Johns Hopkins University</strong> and <strong>European Centre for Disease Prevention and Control</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19_jhu.ttl - COVID-19 data collected by the JHU covid19_ecdc.ttl - COVID-19 data collected by the ECDC This RDF files are based on https://pomber.github.io/covid19/timeseries.json https://opendata.ecdc.europa.eu/covid19/casedistribution/json/
DOI: 10.5281/zenodo.3841038
title: BreathBase: Intra-Speech Breathing Dataset

description: BreathBase contains 5070 breath instances detected on the recordings of 20 participants reading pre-prepared random pseudo texts in 5 different postures with 4 different microphones, simultaneously. It is recorded in a studio with a maximum background noise of 40 dB SPL and with professional recording equipment. It also provides tagging for 5 different postures and 4 different channels as different recording conditions for data variety. More than 90% of the recordings is shorter than 600 milliseconds. The minimum number of breath instances per participant is 89, the maximum number of instances is 710 and the average for all participants is 253.5 breath instances.
description: Data in this dataset is collected for the thesis study: "Speaker and Posture Classification Using Instantaneous Acoustic Features of Breath Signals" in Multimedia Informatics program within the Informatics Institute at Middle East Technical University.
DOI: 10.5281/zenodo.3841039
title: BreathBase: Intra-Speech Breathing Dataset

description: BreathBase contains 5070 breath instances detected on the recordings of 20 participants reading pre-prepared random pseudo texts in 5 different postures with 4 different microphones, simultaneously. It is recorded in a studio with a maximum background noise of 40 dB SPL and with professional recording equipment. It also provides tagging for 5 different postures and 4 different channels as different recording conditions for data variety. More than 90% of the recordings is shorter than 600 milliseconds. The minimum number of breath instances per participant is 89, the maximum number of instances is 710 and the average for all participants is 253.5 breath instances.
description: Data in this dataset is collected for the thesis study: "Speaker and Posture Classification Using Instantaneous Acoustic Features of Breath Signals" in Multimedia Informatics program within the Informatics Institute at Middle East Technical University.
DOI: 10.5281/zenodo.3841842
title: Linked COVID-19 Data: Robert Koch-Institut (RKI)

description: Linked COVID-19 Data derived from <strong>Robert Koch Institute</strong> using the COVID-19 Ontology 10.5281/zenodo.3757828 developed for the Linked COVID-19 Data Dashboard: http://covid19data.link This files include data for covid19_rki*.ttl - single COVID-19 cases per day, collected by the RKI https://www.arcgis.com/home/item.html?id=dd4580c810204019a7b8eb3e0b329dd6 "confirmed" is calcaulated by the column "Refdatum" covid19_rki_ger.ttl - COVID-19 cases per day for Germany, collected by the RKI covid19_rki_ger_cum.ttl - COVID-19 cases accumulated per day for Germany, collected by the RKI covid19_rki_fs.ttl - COVID-19 cases per day for the federal states in Germany, collected by the RKI covid19_rki_fs_cum.ttl - COVID-19 cases accumulated per day for the federal states in Germany, collected by the RKI This RDF files are based on the NPGEO Corona Hub 2020 https://opendata.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0.geojson https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0/data
DOI: 10.5281/zenodo.3841840
title: generative commons database

description: This dataset is one of the deliverables of the H2020 project gE.CO Living Lab (generative European commons Living Lab). It collects communities of citizens that renovated urban spaces to provide welfare services, as well as urban policies adopted to support these initiatives. The dataset includes cased based in 16 different countries in Europe and more than 200 entities.
DOI: 10.18112/openneuro.ds002843.v1.0.0
title: Cognitive Training
DOI: 10.5281/zenodo.3841839
title: generative commons database

description: This dataset is one of the deliverables of the H2020 project gE.CO Living Lab (generative European commons Living Lab). It collects communities of citizens that renovated urban spaces to provide welfare services, as well as urban policies adopted to support these initiatives. The dataset includes cased based in 16 different countries in Europe and more than 200 entities.
DOI: 10.5281/zenodo.3840013
title: EXIOBASE v3.3.sm

description: A new version of the monetary product-by-product ITA IO database EXIOBASE v3.3 where materials produced with secondary technologies (i.e. recycling industries) are explicitly represented.
DOI: 10.5281/zenodo.3841118
title: SoilKsatDB: a global compilation of soil saturated hydraulic conductivity measurements

description: Contains a total of 1,910 sites with 13,267 Ksat (soil saturated hydraulic conductivity) measurements were assembled from published literature and other sources, standardized, and quality-checked in order to provide a global database of soil saturated hydraulic conductivity. The SoilKsatDB covers most global regions, with the highest data density from the USA, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11,667 measurements), bulk density (11,151 measurements), soil organic carbon (9,787 measurements), field capacity (7,389) and 10 wilting point (7,418) are also included in the dataset. For more details / to cite this dataset please use: Gupta, S., Hengl, T., Lehmann, P., Bonetti, S., and Or, D., (2020): <strong>SoilKsatDB: global soil saturated hydraulic conductivity measurements for geoscience applications</strong>. Earth Syst. Sci. Data Discuss., submitted. Import and bind steps are described in detail <strong>here</strong>. Prepared using the farff package for R. ARFF' (Attribute-Relation File Format) files are like 'CSV' files, with a little bit of added meta information in a header and standardized NA values. Column codes are based on the National Cooperative Soil Survey (NCSS) Soil Characterization Database naming convention (see "USDA_NRCS_variables" for explanation of codes). The SoilKsatDB is a compilation of numerous existing datasets from which the most significant: SWIG dataset (Rahmati et al., 2018), UNSODA (Leij et al., 1996), and HYBRAS (Ottoni et al., 2018). The study was supported by ETH Zurich (Grant ETH-18 18-1).
description: {"references": ["Leij, F., Alves, W., Van Genuchten, M. T., and Williams, J.: The UNSODA Unsaturated Soil Hydraulic Database; User's Manual, Version 1.0, Rep. EPA/600/R-96, 95, 103, 1996.", "Rahmati, M., Weiherm\u00fcller, L., Vanderborght, J., Pachepsky, Y. A., Mao, L., Sadeghi, S. H., Moosavi, N., Kheirfam, H., Montzka, C., Van Looy, K., et al.: Development and analysis of the Soil Water Infiltration Global database, 2018.", "Ottoni, M. V., Ottoni Filho, T. B., Schaap, M. G., Lopes-Assad, M. L. R., and Rotunno Filho, O. C.: Hydrophysical database for Brazilian soils (HYBRAS) and pedotransfer functions for water retention, Vadose Zone Journal, 17, 2018."]}
DOI: 10.25919/5ec97fc53faa7
title: Parkes observations for project P1058 semester 2020APRS_02

description: We propose to carry out a Parkes timing campaign of the new millisecond pulsar, J1431-6328, discovered by the Australian SKA Pathfinder (ASKAP) and Parkes Ultra-Wideband Low (UWL) receiver. PSR J1431-6328 has a spin period of 2.77 ms and is in a very wide binary system with an orbital period of 88 days. The relatively low mass of the companion and the long orbital period make this binary system extremely interesting for the understanding of binary evolution. The wide orbit of J1431-6328 also makes it useful for tests of the strong equivalence principle. The proposed program will allow us to better measure its binary parameters and to achieve more precise localisation of the pulsar, which is crucial for the optical follow-up of the system.
DOI: 10.5281/zenodo.3842137
title: LG-covid19-HOTP: Literature Graph of Scholarly Articles Relevant to COVID-19 Study

description: Parallel to the dataset CORD-19 of scholarly articles, we provide the literature graph LG-covid19-HOTP composed of not only articles (graph nodes) that are relevant to the study of coronavirus, but also in and out citation links (directed graph edges) to base navigation and search among the articles. The article records are related and connected, not isolated. The graph has been updated weekly since March 26, 2020. The current graph includes <strong>23,919</strong> hot-off-the-press (HOTP) articles since January 2020. It contains <strong>260,149</strong> articles and <strong>1,871,303</strong> links. The link-to-node ratio is remarkably higher than some other existing literature graphs. In addition to the dataset we provide more functionalities at lg-covid-19-hotp.cs.duke.edu such as new articles, weekly meta-data analysis in terms of publication growth over time, ranking by citation, and statistical near-neighbor embedding maps by similarity in co-citation, and similarity in co-reference. Since April 11, we have enabled a novel functionality - self-navigated surf-search over the maps. At the site we also take courtesy input of COVID-19 articles that are missing from the current collection.
description: {"references": ["Semantic Scholar Open Research Corpus. 2019. Version 2019-11-01. Retrieved from http://s2-public-api-prod.us-west-2.elasticbeanstalk.com/corpus/download/. Accessed 2019-12-06.", "Elsevier Scopus Citation Overview API. Accessed 2020-03-25.", "COVID-19 Open Research Dataset (CORD-19). 2020. Version 2020-03-20. Retrieved from https://pages.semanticscholar.org/coronavirus-research. Accessed 2020-03-26. 10.5281/zenodo.3727291", "Crossref REST API. Available at www.crossref.org. Accessed 2020-03-25."]}
DOI: 10.21227/c0kw-c455
title: Aircraft Fuel Distribution System

description: The aircraft fuel distribution system has two primary functions: storing fuel and distributing fuel to the engines. These functions are provided in refuelling and consumption phases, respectively. During refuelling, the fuel is first loaded in the Central Reservation Tank and then distributed to the Front and Rear Tanks. In the consumption phase, the two engines receive an adequate level of fuel from the appropriate tanks. For instance, the Port Engine (PE) will receive fuel from Front Tank and the Starboard Engine (SE) will receive fuel from Rear Tank. Each of the tanks has a level sensor and a temperature sensor. They measure the level of fuel and the temperature of the tank, respectively. When the fuel level reaches a pre-specified level in the Front and the Rear Tank, they can draw fuel from the central reservation tank. Similar to the tanks, the valves have their own sensor to measure the rate of flow through them. Additionally, there are flow sensors attached to the pipes to measure the flow rate through the pipes. This dataset provides different failure scenarios and sensor measurements. For more detail please check the following reference. Gheraibia, Y., Kabir, S., Aslansefat, K., Sorokos, I., & Papadopoulos, Y. (2019). Safety+ AI: A Novel Approach to Update Safety Models Using Artificial Intelligence. IEEE Access, 7, 135855-135869.
DOI: 10.21227/eg3t-ke89
title: Benchmark Data for "Reclaimer Scheduling in Dry Bulk Terminals", IEEE Access, 2020

description: This dataset contains the benchmark files that used in "Reclaimer Scheduling in Dry Bulk Terminals", IEEE Acccess, 2020.
DOI: 10.21227/frsv-ad98
title: Benchmark Data for "Reclaimer Scheduling in Dry Bulk Terminals", IEEE Access, 2020

description: This dataset contains the benchmark files that used in "Reclaimer Scheduling in Dry Bulk Terminals", IEEE Acccess, 2020.
DOI: 10.21227/15gk-s444
title: Aircraft Fuel Distribution System

description: The aircraft fuel distribution system has two primary functions: storing fuel and distributing fuel to the engines. These functions are provided in refuelling and consumption phases, respectively. During refuelling, the fuel is first loaded in the Central Reservation Tank and then distributed to the Front and Rear Tanks. In the consumption phase, the two engines receive an adequate level of fuel from the appropriate tanks. For instance, the Port Engine (PE) will receive fuel from Front Tank and the Starboard Engine (SE) will receive fuel from Rear Tank. Each of the tanks has a level sensor and a temperature sensor. They measure the level of fuel and the temperature of the tank, respectively. When the fuel level reaches a pre-specified level in the Front and the Rear Tank, they can draw fuel from the central reservation tank. Similar to the tanks, the valves have their own sensor to measure the rate of flow through them. Additionally, there are flow sensors attached to the pipes to measure the flow rate through the pipes. This dataset provides different failure scenarios and sensor measurements. For more detail please check the following reference. Gheraibia, Y., Kabir, S., Aslansefat, K., Sorokos, I., & Papadopoulos, Y. (2019). Safety+ AI: A Novel Approach to Update Safety Models Using Artificial Intelligence. IEEE Access, 7, 135855-135869.
DOI: 10.21227/4mzz-za04
title: Experimental evaluation of test-driven development with interns working on a real industrial project: Replication Package

description: Experimental evaluation of test-driven development with interns working on a real industrial project: - raw experimental data: unit test, integration tests results and coverage, - R statistical analysis script, - processing scripts.
DOI: 10.21227/xag2-zg33
title: Experimental evaluation of test-driven development with interns working on a real industrial project: Replication Package

description: Experimental evaluation of test-driven development with interns working on a real industrial project: - raw experimental data: unit test, integration tests results and coverage, - R statistical analysis script, - processing scripts.
DOI: 10.5281/zenodo.3841714
title: Supplementary Materials

description: Table S1-Heritability of fatty acid content in soybean seeds. Table S2-SNPs identified to be associated with oleic acid content in two years (<em>P</em> &lt; 0.000001). Table. S3-Correlation between <em>Glyma.11G229600.1</em> expression and oleic acid content. Table. S4-Correlation between<em> Glyma.04G102900.1</em> expression and oleic acid content. Figure.S1-Expression of <em>Glyma.11G229600.1</em> in different tissues of soybean lines. Figure. S2-Expression of <em>Glyma.04G102900.11 </em>in different tissues of soybean lines.
DOI: 10.5281/zenodo.3841715
title: Supplementary Materials

description: Table S1-Heritability of fatty acid content in soybean seeds. Table S2-SNPs identified to be associated with oleic acid content in two years (<em>P</em> &lt; 0.000001). Table. S3-Correlation between <em>Glyma.11G229600.1</em> expression and oleic acid content. Table. S4-Correlation between<em> Glyma.04G102900.1</em> expression and oleic acid content. Figure.S1-Expression of <em>Glyma.11G229600.1</em> in different tissues of soybean lines. Figure. S2-Expression of <em>Glyma.04G102900.11 </em>in different tissues of soybean lines.