cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7898003.v1
title: Surface impedance of porous multilayers

description: Surface impedance measured in a Kundt's tube of different porous multilayer configurations. Each file contains the frequency values and the complex-valued surface impedance with in a rigid-backed configuration or backed by an air gap of 20mm. The thickness of sample 1 (recycled foam) is 32mm and the thickness of sample 4 (fibrous material) is 45mm.<br>
DOI: 10.17632/787mkh2kjc
title: Machine Learning and Handcrafted Image Processing Weed Classification Results Data

description: Shape features extracted from ImageJ particle analysis based on four weed species (Common Lambsquarters, Common Purslane, Horseweed, and Redroot Pigweed) images that were used in the hand crafted image processing and machine learning models/methodology development to identify the weeds.
DOI: 10.17632/fpj8vbpw37
title: Dataset for CDMB-SegNet

description: This dataset includes a normalized and paired database of complete denture boundaries on 3D edentulous jaws from 27 dental laboratories, which is the first public available database for DL-based investigations in Efficient Complete Denture Metal Base (CDMB) design. For efficient and automated design of CDMB, we develop a computer-aided Segmentation Network-driven CDMB design framework, called CDMB-SegNet. The main codes of CDMB-SegNet are also included.
DOI: 10.17632/ybvcdmtrpc
title: TPS coordinate files of horse shape space data

description: Based on the work from Druml et al. 2015 (https://doi.org/10.1017/S1751731114003309 ), and the expanded version of Gmel et al. 2022 (https://doi.org/10.3390/ani12172186), the horse shape space model was applied on 2489 images of 1241 horses photographed from the side in open posture. A mix of landmarks and converted semi-landmarks result in 253 landmarks per image and were saved as tps files. These tps files are available for download in this repository. The tps files are sorted by horse breed (WB=Warmblood, SHA=Shagya Arabian, PRE=Pura Raza Español, LUS=Lusitano, LIP=Lipizzaner, FM=Franches-Montagnes, AR=Purebred Arabian). Each folder also contains R code lines for transforming the data into .csv files, and a metafile describing the individual horse identifier, followed by the sex, year of birth, year of the photograph to derive age on the photograph, wither’s height, country of origin of the photograph, and the scores for the six posture parameters previously described in Gmel et al. (https://doi.org/10.1371/journal.pone.0202931).
DOI: 10.17632/7yvrhkxz22
title: Riverine Plastic Litter Dataset

description: A dataset of floating plastic litter in river was established, including five types of images: plastic bags, plastic bottles, plastic boxes, plastic cups, and cans. Originated in the Research Lab of Automation in Construction Engineering and Management (ACEM), Department of Civil Engineering, Xi'an Jiaotong-Liverpool University
DOI: 10.17632/bhg8c4mmg4
title: How spatial policies can leverage energy transition -  Finding pareto optimal solutions of wind turbine locations supported by evolutionary multi objective optimization (data)

description: We provide the geospatial data of the possible wind turbine locations as shapefiles. In addition we present the scripts used for the NSGA3 optimization and the scripts to reproduce the basic analysis of the NSGA3 output.
DOI: 10.17632/c9cj9nyhxy
title: PolyUQ: framework for solving problems with polymorphic uncertainties

description: The consideration of aleatory and epistemic uncertainties is an important challenge in structural engineering problems, especially from the viewpoint of realistic analysis. Inaccuracy and variability are always present and have to be quantified by either probabilistic, possibilistic, polymorphic or other uncertainty approaches. Thus, the authors have developed the framework PolyUQ in MATLAB for solving problems in which uncertainties in the fuzzy space, the interval space and the stochastic space can be treated simultaneously.
DOI: 10.17632/wrkp986xjp
title: Data_ AI applied in Smart Tourism

description: Four hundred twenty-nine available questionnaires were collected that meet the sample size to conduct structural equation modeling and the other multivariate analysis. The samples include 196 males (45.7%) and 233 females (54.3%). Most respondents have a bachelor’s degree (78.3%) and are aged from 19 to 40 (92.7%). Students account for the majority of occupations (39.4%), followed by workers/employees (33.8%), public institution staff (18.2%), and civil servants (3.3%). The sample distribution aligns with the visit distribution of general smart tourism attractions without bias.
There are two worksheets in the excel file. One is the questionnaire items, the other one is the data.
DOI: 10.6084/m9.figshare.19294142.v1
title: Data for Spatio-temporal dynamics of the ecological community in Lake George, NY, USA

description: Lakes have complex interplays between spatial processes and environmental conditions for multiple taxa. Differences among taxa in their ability to disperse and respond to the environment impact the food web and will be reflected in their abundances over time at different sites within the lake. Depending on their mobility, we may expect to see synchronous dynamics throughout the lake for populations that are highly mobile while populations may exhibit asynchronous dynamics if they are unable to overcome local environmental conditions via dispersal. We provide a high-level overview of changes in the densities of key food web groups in Lake George, NY to determine how their densities have changed over time and whether those changes are similar across multiple sub-basins of the lake. Phytoplankton abundance (indirectly measured as chlorophyll a) and zooplankton densities showed strong seasonal and longer-term trends that are mostly synchronous across space. Similarly, most macroinvertebrate groups showed significant non-linear long-term trends, though some showed differences across basins. For phytoplankton and several macroinvertebrate groups, we found that density was highest in the South Basin, potentially reflecting the gradient of decreasing nutrients in the lake from south to north. We also found differences across basins in the relationship between fish length and weight, suggesting that fish condition varies across space. Despite these differences in fish growth, which suggest variability in food web structure across basins, plankton and macroinvertebrates generally follow synchronous trends in abundance across all three basins, possibly reflecting the importance of bottom-up regulation. <br>
DOI: 10.6084/m9.figshare.20457099.v1
title: Commodity Sector Classification

description: The classification used by the CEFIO dataset in the 166- and 55-sector versions. It is provided in English and Chinese and saved in an Excel spreadsheet.
DOI: 10.6084/m9.figshare.28999301.v1
title: Agility, Handball, Male, Vertical Jump - Datas

description: Agility, Handball, Male, Vertical Jump
DOI: 10.17632/dwyvhggssg
title: Cash Flow Patterns_Replication Files

description: Replication files for “Financial Constraints, Cash Flow Timing Patterns, and Asset Prices”
DOI: 10.17632/syzcbykjw3
title: Web of Science Dataset (Engineering, Computing & Technology Journals)

description: This dataset contains information about journals in the realm of Engineering, Computing & Technology available on the Web of Science. Currently, 1655 journals are indexed in this field.

The properties are as follows:

- Journal Name
- Publisher
- ISSN / eISSN
- Web of Science Core Collection
- Additional Web of Science Indexes
- Journal Website
- Publication Frequency
- Aims and Scope
- Indexing and Abstracting
DOI: 10.6084/m9.figshare.14751711.v1
title: Heat flow data in the Amerasia Basin measured by the CAEs

description: This dataset contains the heat flow measured by the Chinese Arctic Expeditions from 2014 to 2018. The measurements were mostly conducted in the region of Chukchi Borderland in the central Arctic
DOI: 10.6084/m9.figshare.16625071.v2
title: TrainingDML-AI JSON Encoding

description: Prototype of TrainingDML-AI JSON schema and examples in the paper "Towards an interoperable training data markup language for artificial intelligence in earth observation"<br><br>
DOI: 10.6084/m9.figshare.22643980.v1
title: adata_rna.h5ad

description: scRNA data from 3 cell lines preprocessed by scGLUE
DOI: 10.17632/xbjccc3jc3
title: Data for: Conditional probability estimation based classification with class label missing at random

description: he breast cancer dataset studied by \citet{Cummings1986Tamoxifen}, which is conducted to evaluate tamoxifen as a treatment for stage \uppercase\expandafter{\romannumeral2} breast cancer among elder women. In this dataset, 78 patients died during the clinical trial. Specifically, 43 of them died from breast cancer, 17 of them died from other known reasons and the remaining 18 patients died from unknown reasons. Therefore, we have two types of cause of death: breast cancer (class 1) and other known reasons (class 0). Moreover, 43 samples come from class 1, 17 samples come from class 0 and class labels of 18 samples are missing. According to \citet{chen2018reweighted}, we choose the observed survival time of a patient as the predictor and assume that the class label is missing at random (MAR).
DOI: 10.6084/m9.figshare.3569034.v1
title: Appendix A. Representation of illustrative models within the proposed framework.

description: Representation of illustrative models within the proposed framework.
DOI: 10.6084/m9.figshare.9860924.v1
title: Supp_tables_S1_S3_S7_S8.xlsx from Highly heritable and functionally relevant breed differences in dog behaviour

description: Supplemental tables S1 S3 S8 and S8
DOI: 10.6084/m9.figshare.9893987.v4
title: Imine formation under catalysis by protonated amine: optimizations using (aug)-pcseg-1 basis set and D3-BJ, single points using pcseg2 and DSD-BLYP(D3-BJ)

description: Input and output files from quantum chemical computation of the reaction mechanism. This work has been published as<br><br>"New insights into the mechanism of Schiff base synthesis from aromatic amines in the absence of acid catalyst or polar solvents" PeerJ Organic Chemistry 2, e4 (DOI: 10.7717/peerj-ochem.4)
DOI: 10.6084/m9.figshare.12055989.v1
title: Supplemental files and figures for Thrash et al. 2017

description: Supplemental files and figures associated with the Thrash et al. 2017 mBio manuscript Metabolic roles of uncultivated bacterioplankton lineages in the northern Gulf of Mexico “Dead Zone.”
DOI: 10.6084/m9.figshare.13089143.v1
title: Han et al., WEOM and BEOM in Yangtze River-East China Searaw data.xlsx

description: Bulk geochemical data of surface sediments as well as water soluble organic matter (WEOM) and base soluble organic matter (BEOM) from surface sediments in lower Yangtze River, Estuary and East China Sea<br>
DOI: 10.6084/m9.figshare.19688730.v2
title: Dataset of mHealth event logs

description: How does Facebook always seems to know what the next funny video should be to sustain your attention with the platform? Facebook has not asked you whether you like videos of cats doing something funny: They just seem to know. In fact, FaceBook learns through your behavior on the platform (e.g., how long have you engaged with similar movies, what posts have you previously liked or commented on, etc.). As a result, Facebook is able to sustain the attention of their user for a long time. On the other hand, the typical mHealth apps suffer from rapidly collapsing user engagement levels. To sustain engagement levels, mHealth apps nowadays employ all sorts of intervention strategies. Of course, it would be powerful to know—like Facebook knows—what strategy should be presented to what individual to sustain their engagement. To be able to do that, the first step could be to be able to cluster similar users (and then derive intervention strategies from there). This dataset was collected through a single mHealth app over 8 different mHealth campaigns (i.e., scientific studies). Using this dataset, one could derive clusters from app user event data. One approach could be to differentiate between two phases: a process mining phase and a clustering phase. In the process mining phase one may derive from the dataset the processes (i.e., sequences of app actions) that users undertake. In the clustering phase, based on the processes different users engaged in, one may cluster similar users (i.e., users that perform similar sequences of app actions). <br> <strong>List of files</strong> `0-list-of-variables.pdf` includes an overview of different variables within the dataset. `1-description-of-endpoints.pdf` includes a description of the unique endpoints that appear in the dataset. `2-requests.csv` includes the dataset with actual app user event data. `2-requests-by-session.csv` includes the dataset with actual app user event data with a session variable, to differentiate between user requests that were made in the same session. <br>
DOI: 10.6084/m9.figshare.4135554.v1
title: Feasibility of the IoT for domestic refrigerators, food safety and waste

description: <strong>Feasibility of the IoT for domestic refrigerators, food safety and waste </strong>Led by: The <strong>University of Lincoln</strong>With partners: Tesco plc, Food Refrigeration and Process Engineering Research Centre (FRPERC), Grimsby Institute of Further and Higher Education (http://www.grimsby.ac.uk/)Project lead: Simon Pearson, Principal Lecturer in Agricultural TechnologyHe has a background in research and industry and has a good understanding of academic, industrial and consumer-facing issues associated with food.<strong>Overview</strong>This is a multi-disciplinary project combining the food quality and refrigeration expertise of the National Centre for Food Manufacturing (University of Lincoln) and the Food Refrigeration and Process Engineering Research Centre, Grimsby Institute. A data logger will be provided to 200 Tesco consumer panellists to record the temperature performance of their refrigerators over 14 days. Sensors will be positioned to capture behaviour patterns such as loading un-chilled food and frequency of door opening etc. Panellists will also record food purchases and disposal as waste including dates. This is one of the most significant studies of its kind for the last twenty years and results will be compared with similar domestic fridges measured in laboratory conditions.In parallel with this an app will be developed to explore how IoT technology combined with official guidance and recommendations can help support consumers in more efficient use of their fridges both in terms of food safety but also energy efficiency in the home. It is anticipated that the results of this work could help provide insight into the development of smarter fridges in the future as well as reducing food waste through more efficient management of food storage in the home.
DOI: 10.17632/n5wg3mbp9r
title: Oromo Auto-Grammar Dataset

description: This contribution is a novel dataset called Oromo-grammar-dataset. The dataset is prepared using a custom Python algorithm. To prepare the dataset, we used a sample of 200KB (about 100 Pages of raw text) collected from online sources. Our algorithm performed well to automatically generate a grammar-aware dataset for the Oromo language. The method can easily be reproducible to any other language with a systematic analysis and slight modifications to its affix structures to generate similar datasets. The output of the software is a grammar-rich dataset, which is applicable to modern NLP applications like machine translation, sentence completion, and grammar and spell checker. The dataset also helps linguists and academia in teaching language grammar structures.
DOI: 10.6084/m9.figshare.28870988.v1
title: The Impact of Web-Based Breastfeeding Education on the Exclusive Breastfeeding Self-Efficacy of Primiparous Mothers

description: This dataset contains the raw data related to a quasi-experimental study investigating the effect of web-based breastfeeding education on the exclusive breastfeeding self-efficacy among primiparous mothers. The study was conducted in 2024 at healthcare centers in Zahedan, Iran. Seventy first-time mothers participated, and data were collected using the Dennis Breastfeeding Self-Efficacy Scale before and three weeks after the intervention. The intervention group used a researcher-designed website over eight sessions to learn about breastfeeding practices. The dataset includes pre-test and post-test scores of breastfeeding self-efficacy.<br><br>
DOI: 10.6084/m9.figshare.7752530.v3
title: Contributing to a Crisis: How Deforestation is a Driver of Climate Change

description: Deforestation and climate change are two of the biggest environmental impacts facing the planet today therefor it is important to know the interaction between them. Using a meta-analysis we looked at the effect the deforestation has on the climate as well as climate change. Ten papers were selected from 185 initial results representing twenty-five with large rain forests and used for statistical analysis. In order to produce relevant and applicable results the papers were restricted to the last five years. We found that deforestation has both regional and global impacts on the climate. This result has significant implications because it shows that slowing deforestation is not only critical for the local environment but also for the entire global climate.
DOI: 10.6084/m9.figshare.7762070.v4
title: PIM Fig5C-E. QPCR of RAW cells and Nrf2KO cells infected with RH strain or not

description: qPCR results
DOI: 10.17632/7d825mgp3b
title: Stakeholder Identification Toolkit (SIT)

description: In a world of fleeting trends, handloom artisans face a constant struggle to keep pace. India's rich heritage provides a beautiful backdrop, yet the rapidly changing market leaves many artisans feeling lost. Limited education and inaccessible resources hinder their ability to adapt their craft to evolving demands. This lack of accessible and relevant educational resources ultimately restricts their entrepreneurial aspirations and artistic potential.
 The research addresses this gap by focusing on the design of a stakeholder identification tool for the unorganised sector, specifically handlooms and handicrafts. This tool will facilitate understanding the nature of these crafts and inform the creation of an entrepreneurship training program tailored for craftspeople. Secondary research analysed existing tools, followed by an ideation process that combined the most valuable aspects of these tools to develop a comprehensive and user-friendly toolkit. Finally, the iterative development process culminated in a final toolkit that was tested by handloom artisans in Assam.
Stakeholder Identification Toolkit (SIT) consists of four tools and needs to be followed sequentially. If the data is available with the trainer, then field data collection is not needed. However, we suggest that field data be collected from time to time so that the changing craft value chain can be captured.
Step 1: Predefined Roles and Questionnaires Tool
Step 2: Role x Actor Tool
Step 3: Role Card
Step 4: Role Mapping
DOI: 10.17632/g727dxrdwk
title: LINF_190012700

description: Protein of unknown function - conserved; Leishmania infantum (strain JPCM5)
DOI: 10.17632/y5b89bsv69
title: Pig Behavior Recognition Dataset

description: 根据其行为特征将其分为Lying、Sleeping、Investigating、Eating、Walking、Moutend六个类别
DOI: 10.6084/m9.figshare.1050245.v2
title: Data Collection in CrowdFlower: SocialSkip

description: Crowdsourced Data with CrowdFlower and SocialSkip
DOI: 10.6084/m9.figshare.1066523.v2
title: Historical median heights for various countries, 1818-2013

description: Dutch, French, Italian (1818-1940): http://www.nber.org/chapters/c7435.pdf Dutch (1955-2009): http://www.nature.com/pr/journal/v73/n3/pdf/pr2012189a.pdf Swedish (1841-1952): http://pediatrisk-endokrinologi.no/2008/1/Werner_2008_1.pdf Danish and Germans (1856-1980): http://privatewww.essex.ac.uk/~hatton/Tim_height_paper.pdf Americans (1710-1980): http://www.cambridge.org/us/academic/subjects/history/economic-history/changing-body-health-nutrition-and-human-development-western-world-1700 All 2013 heights: http://www.averageheight.co/average-male-height-by-country Means and medians are not too different (rarely more than 1 cm difference) because within-country heights for specific gender are generally normally distributed.
DOI: 10.6084/m9.figshare.17040362.v1
title: System and Software architecting harmonization practices in ultra-large-scale Systems of Systems: a confirmatory case study

description: Replication package for the paper System and Software architecting harmonization practices in ultra-large-scale Systems of Systems: a confirmatory case study
DOI: 10.6084/m9.figshare.25965946.v1
title: The volitional control of individual motor units is constrained within low-dimensional neural manifolds by common inputs

description: This repository contains all the <b>raw</b> electromyographic (EMG) data and the <b>edited</b> motor unit spike trains. These data are associated with the following article submitted to <i>Journal of Neuroscience</i>: The volitional control of individual motor units is constrained within low-dimensional neural manifolds by common inputs. The <b>preprint</b> can be found at: https://www.biorxiv.org/content/10.1101/2024.01.05.573816v1Contact: <b>Julien Rossato</b> (julien.rossato14@gmail.com), <b>Simon Avrillon </b>(simon.avrillon@gmail.com) or <b>François Hug </b>(francois.hug@univ-cotedazur.fr)------<b>[muscle group]_[Participant]/[condition].mat</b><br>List of "muscle group": gastrocnemii (triceps surae experiment), vastii (quadriceps experiment)List of "Participant": P#1 to P#10 for the triceps surae experiment, and P#1 to P#5 for the quadriceps experimentList of “condition”: MVC (maximal voluntary contraction), Training_baseline (reference contractions [torque feedback]), Online_MU_trial (online contractions [motor unit + torque feedback])These files can be opened with Matlab (Mathworks) and with our open-source software for decompositing and editing motor units (https://github.com/simonavrillon/MUedit)Below are the decription of the main variables used in the article mentioned avove:signal.fsamp: sampling ratesignal.nChan: number of recroded channels (we used EMG grids of 64 electrodes)<b>signal.data: raw EMG signals</b>signal.muscle: name of the recorded musclessignal.EMGmask: excluded EMG channels due to noise or artefactssignal.path: effective torquesignal.path3D: data from the 3D force gauge (only for triceps surae experiment)signal.feedneuro: target to be reached (for online control tasks) in each of the 10 contractions. For more information about the targets, please refer to the article.parameters.MUID: ID of the decomposed motor units (GL, gastrocnemius lateralis; GM, gastrocnemius medialis; VL, vastus lateralis; VM vastus medialis)<b>e</b><b>dition.Dischargetimes: discharge times for each identified motor units (after manual editing).</b>edition.Pulsetrain. Pulse train for each identified motor units<i>Please note: Although we recorded data from the vastus lateralis and tibialis anterior muscles during the triceps surae experiments, we did not run the decomposition algorithm on these data.</i><br>------<b>MU_pairs.mat</b>This file contains information about the pairs of motor units, which have been tested during the online tasks.ID: ID of the participant where GM stands for triceps surae experiment and VL stands for quadriceps experimentMUID1: first motor unit of the pair being considered (it corresponds to parameters.MUID in the other files)MUID2: second motor unit of the pair being considered targetMU: target to be reached in each of the 10 contractions. For more information about the targets, please refer to the article.<br>