cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/k22zxz29kr
title: Diesel Engine Faults Features Dataset (3500-DEFault)

description: The objective of this dataset is the fault diagnosis in diesel engines to assist the predictive maintenance, through the analysis of the variation of the pressure curves inside the cylinders and the torsional vibration response of the crankshaft. Hence a fault simulation model based on a zero-dimensional thermodynamic model was developed. The adopted feature vectors were chosen from the thermodynamic model and obtained from processing signals as pressure and temperature inside the cylinder, as well as, torsional vibration of the engine’s flywheel. These vectors are used as input of the machine learning technique in order to discriminate among several machine conditions. The database is expected to emulate all operating scenarios under study. In our case, all possible diesel machine faults and system conditions variations, which correspond to severities levels containing enough information to characterize and discriminate the faults. The developed database covered the following operating conditions: Normal (without faults), Pressure reduction in the intake manifold, Compression ratio reduction in the cylinders and Reduction of amount of fuel injected into the cylinders. In all scenarios, the motor rotation frequency was set at 2500 RPM. The rotation of 2500 RPM was used, since it presented the lowest joint error rate in the estimation of the mean and maximum pressures of the burning cycle, between the experimental data (according to data supplied by the manufacturer) and the simulated data, during the validation stage of the thermodynamic and dynamic models. The entire database comprises a total of 3500 different fault scenarios for 4 distinct operational conditions. 250 of which from the normal class, 250 from ``pressure reduction in the intake manifold" class, 1500 from ``compression ratio reduction in the cylinders" class and 1500 from the ``reduction of amount of fuel injected into the cylinders" class. This database is named 3500-DEFault database.
DOI: 10.17632/txgdw36vxc
title: Recombination shapes the 2022 monkeypox outbreak

description: Supplemental File 1. The Newick tree of the MPXV sequence dataset for Supplemental File 2. 
Supplemental File 2. Rooted phylogenetic tree of MPXV genomes during 2022 pandemics. Alignments of viral sequences were generated using MAFFT, and the phylogenetic tree was visualized using FigTree. Rooting was done by introducing the camelpox virus sequence (MZ300860) as an outgroup virus. Group U, M, and I of MPXV genomes is labeled in green, blue, and red, respectively. Recombinant MPXV isolates based on TR analysis are labeled in orange.
Supplemental File 3. Genomic sequences of MPXV (B.1 clade) from January 1 to July 20, 2022 (N=415) in this study. The camelpox virus sequence (MZ300860) is included for phylogenetic analysis in Supplemental File 2.
Supplemental File 4. TRAL analysis of the annotated TRs in MPXV genomic sequences of Supplemental File 3 and Figure S6.
Supplemental Table 1. Summary of MPXV genome sequence information in this study.
Figure S1. Sequences that contain SNP pairs with strong linkage disequilibrium, which the upper 95% confidence bound of the D’ is above 0.98 and the lower bound is above 0.7.
Figure S2. TR C in the intergenic region of monkeypox A47R and A49R. (A) The map of TR C, A47R, and A49R gene. Arrows indicate the gene direction. (B) The location of TR C at the 3’-untranslated region of A47R transcript. The 3’ termination UUUUUNU sequence for adding poly(A) tail is boxed in red. Reference MPXV sequence is OP19276.
Figure S3. TR B in the intergenic region of monkeypox A41L and A42R. (A) The map of TR B, A41L, and A42R gene. Arrows indicate the gene direction.  Sequence b and c are shown in (B) and (C). (B) Sequence of TR B insertion in monkeypox genome as in (A) compared to vaccinia sequence. (C) Alignment of monkeypox and vaccinia in A42R promoter. TAAAT and AAAAAA element are boxed in red. Reference MPXV sequence is OP19276.
Figure S4. TR D in the intergenic region of monkeypox B18R and B19R. (A) (A) The map of TR D, B18R, and B19R gene. Arrows indicate the gene direction.  Sequence b, c and d are shown in (B), (C) and (D). (B) Alignment of monkeypox sequence B with vaccinia B19R promoter, including TAAAT and AAAAAAA element only found in vaccinia.  (C and D) Sequences of B19R promoter of monkeypox. Sequence of TR D insertion in monkeypox genome as in (A). Reference MPXV sequence is OP19276.
Figure S5. Comparison of vaccinia K3L and monkeypox C3L sequence. The stop codon was introduced at bp 130-132, causing C3L a truncated protein compared to K3L. 
Figure S6. (A) Table of divergence value ranges of TR A to F. The value of TR B is not available because its sequence is AT only. (B)  Each box (TR A, C, D, E, F) contains individual TRNs with different colors associated with the parental viral sequences: IRBA22-14 (I, ON755040), MUW1527495 (M, ON019276) or USA_2022_CA002 (U, ON954773) as Figure 1F. TRs and TRNs were validated by the TRAL algorithm with p-value < 10-4.
DOI: 10.17632/x7wv899bzr
title: Smith et al., Objective Autonomic Signatures of Tinnitus and Sound Sensitivity Disorders

description: Data /code for Smith et al., Objective Autonomic Signatures of Tinnitus and Sound Sensitivity Disorders
DOI: 10.17632/h23kcd7vyk
title: Data for: Survey of male college students' perceptions and knowledge of speech-language pathology

description: Survey used to asses male undergraduate's knowledge and perceptions of speech-language pathology
DOI: 10.6084/m9.figshare.27236766.v1
title: Processed Data

description: The biomechanical analysis of human movement, particularly gait, is crucial in fields such as clinical medicine, sports, and rehabilitation. While traditional motion capture (Mocap) systems are effective, they are often limited by their complexity, high cost, and the unnatural settings they require in terms of the gesture and motion environment. Emerging tools like inertial sensors and mark- erless video-based systems offer greater flexibility but encounter challenges in motion cycle segmentation, as they present kinematic data as time series, adding new difficulties to the analysis. This paper introduces a novel machine learning-based system for automatic gait cycle segmentation using features extracted from two easily measurable lower limb kinematic variables: hip and knee extension angles. The proposed method leverages instantaneous information from these angles for segmentation, ensuring versatility and independence from specific data collection methods. This allows for rapid segmentation and potential implemen-tation on lower-performance processors. Experimental results demonstrate the high accuracy and efficiency of the proposed algorithm segmenting the gait cycle.The F1-score was 0.997. By using readily available hip and knee kinematic data and identifying crucial biomechanical relationships, our method offers a versa-tile and practical solution for motion analysis across various clinical and sports applications.
DOI: 10.17632/b7z68nykxt
title: Multimodal Dataset for Sentiment Analysis and Classification

description: In the proposed dataset, videos are collected and downloaded from social media sites like Facebook, Instagram, YouTube, Twitter, Telegram, and video libraries that match requirements. The proposed dataset consists of 600 videos of different emotions like Neutral, Happy, Anger, Disgust, Fear, Sad, and surprise. The proposed dataset has videos of variable length from people of different ages and different nationalities and the audio in each clip has the voice of a single speaker who is seen in the film. The language of the videos is US English. It is labeled and balanced video dataset. This dataset can serve as valuable resource for various research purposes, including sentiment analysis, opinion mining, trend analysis, and social behavior studies, etc.
DOI: 10.17632/nvnz4d44m2
title: Dataset for Behavioral Intentions based on Learning Acceptance of Information Flow Diagram Capability for Software Design

description: Thailand's private and public university students were the target demographic. Student's behavioral intentions to learn information flow diagrams for two semesters, from January 2021 to February 2022, were collected after the class. Primary data sources were collected from distributing online questionnaires (Google Forms). This study's sample consisted of 537 individuals with various characteristics who were required to examine a new software design called an information flow diagram for software design. The authors distributed and collected 537 completed questionnaires. During the survey, no invalid response forms were submitted. The authors conducted a survey using a sample of 537 students from four private and public universities.
Region: Asia
Kingdom of Thailand
DOI: 10.17632/yfsz6c36vc
title: Neonatal Jaundice Assessment: A Dataset of Forehead and Sternum Images for Bilirubin Estimation

description: This dataset includes images and clinical data aimed at estimating bilirubin levels in newborns to enhance non-invasive neonatal jaundice detection through deep learning. Images were captured using a digital microscope connected to a smartphone via USB, saved in jpg format with a resolution of 640 x 480 pixels.
Dataset Contents:
Images: Forehead and sternum images of 300 infants, saved in jpg format (640 x 480 pixels).
Data Collection Process:
Location: Ghaem Hospital, Mashhad, Iran
Duration: January 1, 2023 - May 30, 2023
Methodology:
TSB levels were determined via blood samples.
TcB levels were measured using the MBJ20 bilirubin meter (range: 0 to 32 mg/dL).
Images were taken within 30 minutes of TSB and TcB measurements to ensure consistency.
Ethics: Approved by the ethical committee at Mashhad University of Medical Sciences (IR.MUMS.MEDICAL.REC.1400.271), with informed written and verbal consent from parents.

Usage Notes:
This dataset is ideal for researchers focusing on the development and validation of non-invasive methods for bilirubin estimation using image processing. It is particularly useful for studies related to the detection and management of neonatal jaundice.
DOI: 10.17632/knhvdbjv3r
title: SH-TBL project dataset

description: Data obtained on the cohort of patients included in the clinical study entitled "Study of TB Lesions Obtained in Therapeutical Surgery" (SH-TBL project, ClinicalTrials.gov Identifier: NCT02715271). The dataset includes: -One file ("SHTBL HQoL") including: patient information; TB reated information; data on surgery performed; and Health-Related Quality of Life data (results of the St. George's Respiratory Questionnaire (SGRQ) and the BCN Questionnaire).
DOI: 10.17632/r7g5gnrzdh
title: The CIR software

description: This file includes executable files of our programs, parameter files which are used to generate simulated data
DOI: 10.6084/m9.figshare.19209714.v1
title: Raw_Data

description: Raw data from EyeTforEmpathy
DOI: 10.6084/m9.figshare.8292176.v3
title: SoilHealthDB

description: Here, we compiled data from a set of soil health measurements collected across 41 countries around the world, named SoilHealthDB, which includes 5,241 data entries from 281 published studies. The SoilHealthDB includes 42 soil health indicators and 45 background indicators that describe factors such as climate, elevation, and soil type. A primary goal of SoilHealthDB is to enable the research community to perform comprehensive analyses, e.g., meta-analyses, of soil health changes related to cropland conservation management. The database also provides a common framework for sharing soil health, and the scientific research community is encouraged to contribute their own measurements. R code for quality checking and data processing are available at RScripts. All data (including meta data for clerification) were stored in 'SoilHealthDB_V1.xlsx'.
DOI: 10.17632/54ppk4mnxy
title: Data for: How Do Oil and Natural Gas Prices Affect U.S. Industrial Production? Utilizing wavelet nonlinear denoised based quantile analysis

description: Data includes western texas crude oil prices, Henry hub natural gas prices and industrial production of the U.S.
DOI: 10.6084/m9.figshare.28917632.v1
title: Raw data for Yuan et al. plant litter C:N:P ratios

description: Raw data for Yuan et al, global litter C:N:P ratio. Any use of the data should contact the corresponding author Kai Yue at kyleyuechina@163.com.
DOI: 10.17632/zsv69t2j4r
title: LINF_300008800

description: phosphatase 2C
Leishmania infantum (strain JPCM5)
DOI: 10.17632/9ygs9vhnpw
title: Allergen30

description: Allergen30 is created with the goal of building a robust detection model that can assist people in avoiding possible allergic reactions. It contains images of 30 commonly used food items that can cause an adverse reaction within a human body. These food items pertain to specific food intolerances which can trigger an allergic reaction. Such food intolerance primarily includes Lactose, Histamine, Gluten, Salicylate, Caffeine, and Ovomucoid intolerance.

The 30 food items (labels) in the dataset include 'alcohol', 'alcohol glass', 'almond', 'avocado', 'blackberry', 'blueberry', 'bread', 'bread loaf', 'capsicum', 'cheese', 'chocolate', 'cooked meat', 'dates', 'egg', 'eggplant', 'icecream', 'milk', 'milk based beverage', 'mushroom', 'non milk based beverage', 'pasta', 'pineapple', 'pistachio', 'pizza', 'raw meat', 'roti', 'spinach', 'strawberry', 'tomato' and 'whole egg boiled'.
DOI: 10.17632/92y5khgv55
title: Suppl Mat JAAD

description: Supplementary Materials JAAD
DOI: 10.17632/nxnwj6hy4s
title: LineaMapper: A deep learning-powered tool for mapping linear surface features on Europa (Haslebacher et al., Icarus, 2023) accompanying data

description: Data accompanying publication "LineaMapper: a deep learning-powered tool for mapping linear surface features on Europa" (Haslebacher et al., Icarus, 2023, https://doi.org/10.1016/j.icarus.2023.115722)
In this folder, you find most of the code we wrote for this project, the model weights, the training log files, and the training, validation and test data set.
Each folder contains a readme.txt file with more information. Each code file contains a header with a short description.
DOI: 10.17632/z3ychcthm2
title: Sociodemographic data on live births children, Brazil, 2018-2022

description: The dataset is an open data from the Sistema de Informação de Nascidos Vivos (SINASC), which is a system implemented by the Brazilian federal government in the 1990s, with the purpose of collecting data on all live births in the national territory. The system makes it possible to provide information on birth rates for all levels of the Brazilian health system, as well as the development of relevant indicators in the strategic planning of management to support the planning of actions, activities, public policies and programs aimed at health.

The dataset is related to three years (2018, 2019, 2020, 2021 and 2022) of SINASC referring only to the state of Pernambuco, and it is composed of routine prenatal data, gestational history, sociodemographic data and data of newborns. born, including their weight.
DOI: 10.6084/m9.figshare.26393275.v2
title: Source data

description: All soure date of manuscript's and supporting information's figure
DOI: 10.17632/4fh598c8w2
title: Gross Tumour Volume CT Radiomics for Prognostication of Recurrence & Death following Curative-Intent Radiotherapy for Non-Small Cell Lung Cancer

description: Recurrence occurs in up to 36% of patients treated with curative-intent radiotherapy for NSCLC. Identifying patients at higher risk of recurrence for more intensive surveillance may facilitate earlier introduction of the next line of treatment. We aimed to use radiotherapy planning CT scans to develop radiomic classification models that predict overall survival (OS), recurrence-free survival (RFS) and recurrence two years post-treatment for risk-stratification. A retrospective multi-centre study of >900 patients receiving curative-intent radiotherapy for stage I-III NSCLC was undertaken. Models using radiomic and/or clinical features were developed, compared with ten-fold cross-validation and an external test set, and benchmarked against TNM-stage. Such models could be integrated into the routine radiotherapy workflow, thus informing a personalised surveillance strategy at the point of treatment. Our work lays the foundations for future prospective clinical trials for quantitative personalised risk-stratification for surveillance following curative-intent radiotherapy for NSCLC.
The radiomic feature data are provided here. Due to confidentiality, clinical data collected for the study are not publicly available for download, however the corresponding authors can be contacted for academic inquiries.
DOI: 10.17632/5sjfp2334f
title: Dataset: Questionnaire-based survey of coffee consumption in Japan

description: The data were generated from a survey on coffee consumption in Japan, and were collected from three regions: Kyoto Prefecture, Osaka Prefecture, and Tokyo. The data includes variables that represent the scale of coffee consumption, such as purchase frequency, quantity, and expenditure. Additionally, it contains variables related to eating habits, which are considered determinants of coffee consumption. Furthermore, different forms of coffee purchases, including beans, powder, and liquid, are accounted for, and respondents reported their consumption for each category. The available data files are three: (i) a codebook that maps the variables’ names and values to the questionnaire’s questions and answers; (ii) raw data of the collected survey translated into English; and (iii) a grand total table (GT table) for each questionnaire item. The simple aggregate results of this survey are immediately available in the GT table.
DOI: 10.17632/7b68fzgy6b
title: Software Engineering Skillset Assessment Dataset for Computer Science Students

description: The Software Engineering Skillset Dataset comprises Soft Skills, Life Skills, and Technical Skills, which are key components for evaluating and predicting the software engineering competencies of computer science students. The surveys, conducted using a meticulously crafted questionnaire, served as the primary data collection method, targeting computer science students in software engineering courses across higher educational institutions in Kerala, India. This extensive survey engaged over two thousand students, evaluating each skill category through a dedicated assessment quiz comprising a total of fifteen questions. The survey was designed to assess Soft Skills, Life Skills, and Technical Skills through a series of questions, each employed a six-point scale for responses as follows:
0: "Never"
1: "Rarely"
2: "Sometimes"
3: "Often"
4: "Mostly"
5: "Always"
The dataset, designed as a classification problem, features two distinct classes (0 and 1). Participants scoring above 60% in each skill area are classified as proficient. The survey comprises three segments and 54 questions for a detailed evaluation of the skills:
1. Soft Skills: Assessed through five tests covering 18 attributes.
2. Life Skills: Evaluated through five tests focusing on nine attributes, emphasizing workplace practices and developmental strategies.
3. Technical Skills: Measured via five tests with nine specific features.
This dataset not only enables a comprehensive analysis of individual and combined skills but also provides valuable insights for students, highlighting their academic strengths and areas needing improvement.
DOI: 10.17632/7mhxkg2kfb
title: Data for Measurement report: Ground-Based MAX-DOAS Measurements of NO2 and SO2 over India

description: This dataset accompanies the paper titled: Measurement report: Ground-Based MAX-DOAS Measurements of NO2 and SO2 over India by Prithviraj Mali et al. A detailed description of all the files can be found in Data_Files.docx. The data files are in matlab format.
DOI: 10.17632/9jhzmswdfj
title: XSS Attacks Dataset

description: This dataset has 7 feature named as App Names, Permissions, API Name, Website Name, IP, Location, Label
DOI: 10.17632/hg7x3cgsj2
title: Bullous Pemphigoid: A practical approach to diagnosis and management in the modern era

description: Supplemental dataset for JAAD Clinical Review: Bullous Pemphigoid: A practical approach to diagnosis and management in the modern era
DOI: 10.6084/m9.figshare.3545087.v1
title: Target Times data from Experiment 1b in the manuscript "The Importance of Search Strategy for Finding Targets in Open Terrain"

description: Target Times data from Experiment 1b in the manuscript "The Importance of Search Strategy for Finding Targets in Open Terrain".<br>Abstract:<br>A number of real world search tasks (i.e., police search, IED detection,) require searchers to search exhaustively across open ground. In the present study, we simulated this problem by asking individuals (Experiments 1a and 1b) and dyads (Experiment 2) to search for coin targets pseudo-randomly located in a bounded area of open grassland terrain. In Experiment 1a, accuracy, search time and the route used to search an area were measured. Participants tended to use an ‘S’ shaped pattern with a common width of search lane. Increased accuracy was associated with slower, but also variable, search speed, though only when participants moved along the length (as opposed to across the width) of the search area. Experiment 1b ,varied the number of targets available within the bounded search area and in doing so varied target prevalence and density. The results confirmed that the route taken in Experiment 1a generalizes across variations in target prevalence/density. In Experiment 2, accuracy, search time, and the search strategy used by dyads was measured. While dyads were more accurate than individuals, dyads that opted to conduct two independent searches were more accurate than those who opted to split the search space. The implications of these results for individuals and pairs when searching for targets in open space are discussed.
DOI: 10.17632/4phycm4pvt
title: Equity market data and risk-free rates for Spain and UK

description: We compile return data for all stocks listed on the Madrid Stock Exchange (MSE) and the London Stock Exchange (LSE) from the Datastream database, for the period from January 1989 to December 2018. Specifically, we compile the following data series: (i) total return index (RI series), (ii) market value (MV series), and (iii) dividend yield (DY series). Accordingly, our data series comprise 398 and 4,385 stocks for Spain and UK, respectively. Using these data, we determine the value-weighted market return and the value-weighted dividend yield for the period under consideration. Additionally, we compile one-year Treasury Bill rates data for Spain and UK, respectively, as provided by the OECD Statistics section. Therefore, the dataset comprises the following series: 1 Spain_returns_DY_M.txt: Monthly returns for the value-weighted market portfolio of the MSE and the utility firms Endesa, S.A. and Iberdrola, S.A. These data series also include the value-weighted dividend yield for the MSE. (Raw data source: Datastream database) 2 UK_returns_DY_M.txt: Monthly returns for the value-weighted market portfolio of the LSE and solar funds Foresight Solar Fund Ltd. and Bluefield Solar Income Fund Ltd. These data series also include the value-weighted dividend yield for the LSE. (Raw data source: Datastream database) 3 Spain_UK_RF_Y.txt: One-year Treasury Bill rates for Spain and UK. (Raw data source: OECD)
DOI: 10.6084/m9.figshare.25367671.v1
title: Data for: Diets of white-headed black langurs

description: Data for: Diets of white-headed black langurs