cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/vxkj334rzv
title: Vibration and Motor Current Dataset of Rolling Element Bearing Under Varying Speed Conditions for Fault Diagnosis: Subset1

description: This dataset discloses vibration and motor current data for bearing faults under varying speed conditions from 680 RPM to 2460 RPM. The bearing conditions include healthy bearing, bearings with inner race faults, and bearings with outer race faults. For each faulty bearing condition, the three-phase induction motor is operated under randomly varying speed conditions. 
Important: Datasets are divided into three parts because of storage limitations (Subset1, Subset2, and Subset3). 

---- Description of vibration file format ----
Vibration data file contains five columns namely ‘Time Stamp’, ‘x_direction_housing_A’, ‘y_direction_housing_A’, ‘x_direction_housing_B’, and ‘y_direction_housing_B’. The unit of the vibration is ‘gravitational constant (g)’. 
vibration_aaaa_bbbb.csv : This file is "bbbb"-th vibration data includes rotating speed data of the condition of "aaaa".

---- Description of motor current file format ----
Motor current data file contains five columns namely ‘Time Stamp’, ‘R_phase’, ‘S_phase’, and ‘T_phase’. The unit of the motor current is ‘Ampare (A)’.

current_aaaa_bbbb.csv : This file is "bbbb"-th motor current data includes rotating speed data of the condition of "aaaa".

---- Description of rotating speed file format ----
Rotating speed data file contains two columns namely ‘Time Stamp’, and ‘speed’. The unit of the acoustic is revolutions per minute (RPM)’.
rpm_aaaa_bbbb.csv : This file is "bbbb"-th speed data includes rotating speed data of the condition of "aaaa".


For more detailed information, check our published paper.
Title: Vibration, Acoustic, Temperature, and Motor Current Dataset of Rotating Machine Under Varying Operating Conditions for Fault Diagnosis
Link: https://www.sciencedirect.com/journal/data-in-brief
DOI: 10.6084/m9.figshare.29069507.v1
title: Supplementary Material for: Effectiveness and safety of combining transarterial chemoembolization with tyrosine kinase and immune checkpoint inhibitors in hepatocellular carcinoma: a meta-analysis

description: Background
Standard treatments for intermediate-stage hepatocellular carcinoma (HCC), such as transarterial chemoembolization (TACE), offer limited efficacy, necessitating the exploration of additional therapeutic strategies. Tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have shown potential to enhance HCC outcomes when combined with TACE. This meta-analysis aimed to evaluate safety and efficacy of TACE, TKIs and ICIs (TACE+T+I) combination compared to TACE with TKIs alone (TACE+T) in patients with HCC. 

Methods
A systematic search was performed in “PubMed”, “Google Scholar”, “Cochrane Library”, “Web of Science”, “Scopus”, and “Embase” databases on November 1, 2024. Studies involving patients with HCC comparing TACE+T+I versus TACE+T were included. Efficacy outcomes including objective response rate (ORR), disease control rate (DCR), overall survival (OS), progression free survival (PFS), and adverse events, were extracted. Meta-analysis was conducted using RevMan 5.4.

Results
Seventeen studies were included for analysis. Pooled analysis showed a markedly improvement in ORR (risk ratio (RR)=1.57, 95%CI:1.36–1.80, P&lt;0.00001) and DCR (RR=1.13, 95%CI:1.06–1.20, P=0.0004) for TACE+T+I regimen over TACE+T. TACE+T+I group also showed a marked benefit in OS (hazard ratio (HR)=0.37, 95%CI:0.29–0.48, P&lt;0.0001) and PFS (HR=0.44, 95%CI:0.36–0.53, P&lt;0.0001). No differences in adverse events were detected between the two groups, indicating comparable tolerability.

Conclusions
The findings suggest that the addition of ICIs to TACE and TKI therapy offers substantial efficacy benefits without increasing toxicity for HCC patients. This combination therapy shows potential to improve DCR, ORR, PFS and OS, underscoring the value of immunotherapy in enhancing outcomes in HCC. However, further randomized trials with standardized treatment protocols are needed to confirm these results and inform clinical guidelines.
DOI: 10.6084/m9.figshare.12552077.v1
title: Gene database for Bacillus cereus ATCC 14579

description: Facultative anaerobic, Gram-positive and rod-shaped, <i>Bacillus cereus</i> is a common bacterium that we encounter during episodes of food poisoning. The bacterium is a common inhabitant of soil and water. From a food safety perspective, <i>B. cereus</i> is a serious microbial threat given its ability to form endospore, which makes its eradication during food processing a top priority. Besides sporulation ability, <i>B. cereus</i> also packs another microbial weapon, cereolysin, which is a virulence factor important to pathogenesis. This work sought to illuminate the genetic repertoire of this important food pathogen by parsing the annotated genome sequence of <i>B. cereus </i>ATCC 14579 obtained from Genbank. Comprising gene name, gene function and gene sequence of all genes in the genome of <i>B. cereus</i>, the resource should be useful in molecular cloning work or genome editing research seeking to understand the functions of individual genes in this important endospore forming pathogen.
DOI: 10.6084/m9.figshare.25452706.v3
title: 3_motor_EEGdata

description: This dataset contains EEG data in experiment 3.Each folder contains:a) Raw EEG files for one subject (subX), named as "subX.vhdr", "subX.vmrk", and "subX.eeg" generated by BP eego device;b) a log file (.txt) that records all information during preprocessing;c) pure EEG datasets (.set file generated by eeglab) for each of four conditions.
DOI: 10.17632/23tkrk7h4z
title: Malaysian Medicinal Leaf Images

description: Leaf images sample for Malaysian Medicinal Plant classification. Previous study using this dataset are using randomly selected training (45 images) and testing (20 images). Images are pre-processed and numeric values using shape-based features are extracted. Preliminary study using several classifiers such as SMO, J48, NB, k-NN and Random Forest show that SMO produced 50% accuracy.

Citation Request
Sainin, M. S., & Alfred, R., & Ahmad, F. (2021). Ensemble meta classifier with sampling and feature selection for data with imbalance multiclass problem. Journal of Information and Communication Technology, 20(2), 103-133. https://doi.org/10.32890/jict2021.20.2.1
DOI: 10.17632/6yh5xy7pmm
title: Fear and anxiety as hindrances to restaurant experience in the viral world

description: This researt data sets out to ascertain restaurant dining perceptions and experiences of Turkish consumers during the Covid-19 era. It also seeks to examine the link between restaurant dining perceptions and experiences amid Covid-19. This research adopted qualitative approach-semi structured interviews to address this purpose. The data were gathered from 27 restaurant consumers during March-May 2021 and examined through content analysis to address the research purposes.
DOI: 10.17632/shp6xm5rdt
title: Automating Efficiency: The Impact of Industrial Robots on Labor Investment in China

description: The file contains the data and code used in the paper. Data on industrial robots are sourced from the IFR, while company-level financial data are obtained from the CSMAR, WIND, and CNRDS databases. City-level data are derived from the China Urban Statistical Yearbook. Chinese manufacturing data come from the China Industrial Statistical Yearbook, and US manufacturing-level data are sourced from the NBER-CES. Manufacturing-level data for the importing country are collected from the World Import and Export Database (WIOD).
DOI: 10.6084/m9.figshare.27223518.v2
title: VPP“manuscript_20241013” data.

description: The newly proposed composite cleaning method for internal defects between additive manufacturing layers was studied, focusing on its process parameters and characteristics.
DOI: 10.6084/m9.figshare.5082697.v1
title: Test Run Output in SPSS format

description: Test Run Output in SPSS format
DOI: 10.6084/m9.figshare.26131852.v1
title: Hierarchical approach

description: We tried different machine learning models (SVM, MLP, KNN, LR, RF), and features extracted by ESM2, to predict different types of nucleic acid binding proteins using hierarchical approach, including the non-NABP/NABP classification, DBP/RBP classification and SSB/DSB classification. Files in the folder 1-non-NABP-NABP are the pre-trained models to predict non-NABPs and NABPs, and files in the folder 2-DBP-RBP are the pre-trained models to predict DBPs and RBPs. Each folder contains the README.txt file, indicating the user note for each model. For the SSBs and DSBs prediction, see https://figshare.com/articles/software/Prediction_of_SSB_DSB/25927360.<br>
DOI: 10.6084/m9.figshare.28092101.v2
title: <i>Genome assembly at the chromosome level of Clinopodium barosmum</i>

description: We performed the first genome assembly at the chromosome level and comparative genome analysis of <i>Clinopodium barosmum</i>. This work establishes a basic genomic resource for this medicinal plant.
DOI: 10.6084/m9.figshare.3848457.v1
title: Table 1. The Donkerhuk batholith, Namibia: A giant S-type granite emplaced in the mid crust, in a fore-arc setting

description: Partial chemical analyses for rocks of the main Donkerhuk batholith.
DOI: 10.17632/ksvb32cvw6
title: Geopolymer Concrete Compressive Strength Data Set for ML

description: this data set was prepared as part of a scientific paper conducted on the prediction of geopolymer concrete compressive strength using NNs. the data includes various input features such as fly ash amount, NaOH amount, GGBFS amount, recycled aggregate amount and ... against compressive strength. the data was gathered through experimental means in the laboratory with same ingredient, equipment and operators thus may include high bias against more variant data sets. this data set can be used in AI and Machine Learning models to further study the properties of geopolymer concrete.
DOI: 10.6084/m9.figshare.14627616.v1
title: Kurchaba et al-2022

description: Data generated from CRISPR mediated disruption of PGC-1a in Zebrafish
DOI: 10.6084/m9.figshare.17170781.v1
title: Data from: The evolution of carotenoid-based plumage colours in passerine birds

description: The spreadsheet (Dataset_carotenoid_colours_passerines.xlsx) has four different sheets corresponding to each dataset and its variable explanation. Further details can be found in the explanatory sheets.
DOI: 10.6084/m9.figshare.28836410.v1
title: FGD and IDI guide.docx

description: This document has FGD schedule and IDI guide used for the qualitative research titled “<b>Empowering Healthcare Access: </b><b>Ethnographic Insights into Sustainable Solutions for a Particularly Vulnerable Tribal Group (PVTG) in South India- a Qualitative Research”</b>.
DOI: 10.17632/5dz3c5tfw9
title: Coastal tidal wetland change in the northeastern United States

description: Coastal tidal wetlands are highly altered ecosystems at substantial risk due to widespread and frequent land-use change, coupled with sea-level rise, leading to disrupted hydrologic and ecologic functions and ultimately, significant reduction in climate resiliency. Knowing where and when the changes have occurred, and the nature of those changes and their associated risks, is paramount to coastal communities and natural resource management. Large-scale mapping of the costal tidal wetland changes is extremely difficult due to their inherent dynamic nature. 
To bridge this gap, we developed an automated algorithm for DEtection and Characterization of cOastal tiDal wEtlands change (DECODE) using dense Landsat time series. We used DECODE to track the status of coastal tidal wetlands in the northeastern United States from 1986 to 2020. The overall accuracy of land cover classification and change detection is approximate 95.8% and 99.8%, respectively. The vegetated wetlands and open water were mapped with 94.6% and 99.0% user’s accuracy, and 98.1% and 93.5% producer’s accuracy, respectively. The cover change and condition change were mapped with 68.0% and 80.0% user’s accuracy, and 80.5% and 97.1% producer’s accuracy, respectively. We discovered that approximately 3283 km2 (12%) of coastal tidal wetlands in the northeastern United States occurred at least one time of change but condition changes were responsible for majority (84.3%). Vegetated coastal tidal wetland decreased consistently (approximately 2.6 km2 per year) in the past 35 years, largely due to its conversion to open water.
DOI: 10.17632/9jkjtt28ry
title: An Einstein field equations solution predicting large and dwarf galaxies rotation velocity.

description: analytical tensor computation maxima file and numerical computation excel file

Recently we derived a galactic Machian model from the Einstein field equations. This model predicted the rotation velocity of the large galaxies M31, M101 and M81, without any dark matter halo. However, the predicted total mass of the three galaxies was significantly lower than that commonly observed. This results from the imposed axial symmetry which gave an inner galaxy gravitation attraction in as the inverse of the radial distance. We solved here the Einstein fields equation using spherical coordinates. As a result, the gravitation attraction from the bulge at short radial distance is well as the inverse of its square. However, the motion equation is non-linear versus the density due the presence of a slowing term intrinsically originating from the Einstein field equations. The solution correctly predicts the total mass and rotation velocity of the three large galaxies and of the dwarf galaxy M33 as well. The model predicts the presence of an ultra-high dense central core in all galaxies. Furthermore, it also predicts an extended stellar halo in M33, which was recently observed using the Subaru Telescope / Hyper Suprime-Cam. This model overcomes the core-cusp issue observed in dwarf galaxy when using the dark matter halo thesis in Newtonian dynamics and avoids the introduction of an additional physical constant as in MOND.
DOI: 10.17632/vybmz8cbwn
title: SeismicWaveTool: Continuous and discrete wavelet analysis and filtering for multichannel seismic data

description: Abstract A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of multichannel seismic data. The considered time–frequency transforms include the continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform. The developed approaches provide a fast and precise time–frequency examination of the seismograms at different frequency bands. Moreover, filtering methods for noise, transients or even baseline removal, are im... Title of program: SeismicWaveTool Catalogue Id: AENG_v1_0 Nature of problem Numerous research works have developed a great number of free or commercial wavelet based software, which provide specific solutions for the analysis of seismic data. On the other hand, standard toolboxes, packages or libraries, such as the MathWorks' Wavelet Toolbox for MATLAB, offers command line functions and interfaces for the wavelet analysis of one-component signals. Thus, software usually is focused on very specific problems or carries out the wavelet analysis from a wide point of view. Versions of this program held in the CPC repository in Mendeley Data AENG_v1_0; SeismicWaveTool; 10.1016/j.cpc.2012.08.008 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)
DOI: 10.6084/m9.figshare.7513418.v1
title: A simple approach to calculate active power of electrosurgical units

description: Abstract Introduction: Despite of more than a hundred years of electrosurgery, only a few electrosurgical equipment manufacturers have developed methods to regulate the active power delivered to the patient, usually around an arbitrary setpoint. In fact, no manufacturer has a method to measure the active power actually delivered to the load. Measuring the delivered power and computing it fast enough so as to avoid injury to the organic tissue is challenging. If voltage and current signals can be sampled in time and discretized in the frequency domain, a simple and very fast multiplication process can be used to determine the active power. Methods This paper presents an approach for measuring active power at the output power stage of electrosurgical units with mathematical shortcuts based on a simple multiplication procedure of discretized variables – frequency domain vectors – obtained through Discrete Fourier Transform (DFT) applied on time-sampled voltage and current vectors. Results Comparative results between simulations and a practical experiment are presented – all being in accordance with the requirements of the applicable industry standards. Conclusion An analysis is presented comparing the active power analytically obtained through well-known voltage and current signals against a computational methodology based on vector manipulation using DFT only for time-to-frequency domain transformation. The greatest advantage of this method is to determine the active power of noisy and phased out signals with neither complex DFT or ordinary transform methodologies nor sophisticated computing techniques such as convolution. All results presented errors substantially lower than the thresholds defined by the applicable standards.
DOI: 10.17632/83k2rtz4bc
title: Fine-Tuned YOLO Family Model Weights for Automatic Tooth Detection and FDI-Based Notation in Dental Panoramic Radiographs

description: Model weights used in the study entitled "Performance Evaluation of YOLO Family for Tooth Detection and Segmentation on Panoramic Dental Radiographs".
DOI: 10.17632/g4r22w9pp8
title: Evolutionary origin of Group 3/4 medulloblastoma

description: This repository contains variant calls from bulk whole genome sequencing of medulloblastomas that were first published in Northcott, P. A. et al. The whole-genome landscape of medulloblastoma subtypes. Nature 547, 311-317 (2017); https://doi.org/10.1038/nature22973 and re-analyzed for reconstructing evolutionary dynamics driving medulloblastoma initiation in the manuscript

Key oncogenic event are late-stage drivers of medulloblastoma evolution and progression

Konstantin Okonechnikov1,2,3*, Piyush Joshi1,2,3,4*, Verena Körber5,6*, et al.

1. Hopp Children’s Cancer Center (KiTZ), Heidelberg, Germany
2. National Center for Tumor Diseases (NCT), NCT Heidelberg, a partnership between DKFZ and Heidelberg University Hospital, Germany
3. Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany
4. Developmental Origins of Pediatric Cancer Junior Research Group, German Cancer Research Center (DKFZ), Heidelberg, Germany.
5. Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany
6. MRC Molecular Hematology Unit, Weatherall Institute of Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, UK

* these authors contributed equally

The repository additionally contains reference data used for the analysis in Okonechnikov, Joshi & Körber et al.
DOI: 10.6084/m9.figshare.20357793.v1
title: State of the Art and Future Directions of HR Analytics Literature

description: The dataset contain the papers used for the analysis shown in the paper "<em>State of the Art and Future Directions of HR Analytics Literature: A Scoping Review Based on Natural Language Processing Technique."</em>
DOI: 10.6084/m9.figshare.28119845.v1
title: Supplementary Material - <b>Diversity, Succession and Application of Coprophilous Fungi</b>

description: This file contains the supplementary data to Calaça's chapter "Diversity, Succession and Application of Coprophilous Fungi", to the Manual of Mycology: Tools and Techniques (SpringerNature). The spreadsheet named 'Calaça_Dung_Fungi_bibliometric_database_1994_2024' is a database organized from data retrieved from the Web of Science database and cleaned by using the different functions available in the bibliometrix package (Aria & Cuccurullo 2017) for the R environment. In this way, both fonts, style, and formatting of the database in 'Calaça_Dung_Fungi_bibliometric_database_1994_2024', follow the necessary structure for uploading in the R environment using the code: install.packages("bibliometrix") library(bibliometrix)data &lt;- read.csv("~/desktop/Calaça_Dung_Fungi_bibliometric_database_1994_2024.csv"M &lt;- convert2df(data, dbsource = "wos", format = "csv")head(M["TC"])
DOI: 10.6084/m9.figshare.28844624.v1
title: Fake news detection through machine learning and deep learning by Yogita IIngale and Shraddha Pathare

description: Social media has become a dominant platform where individuals freely express their opinions and share information widely and rapidly. While it serves as a convenient and accessible source of news and communication, it also poses significant risks due to the widespread circulation of “fake news.” The rapid dissemination of misinformation can mislead the public, cause societal unrest, and influence major events, such as political elections. This growing concern has drawn attention from both the public and governmental organizations, as the manipulation of information can significantly affect public opinion and decision-making processes. Consequently, the detection of fake news on social media has emerged as a critical area of research. Identifying misinformation presents numerous challenges due to its complexity and the evolving tactics of those spreading it. This paper explores various contemporary approaches to fake news detection, focusing on the implementation of machine learning and deep learning techniques to enhance detection accuracy and reliability.
DOI: 10.17632/7ttmgrmb6d
title: Dataset of Biopolymers from Wine Industry

description: Main authors potentially importatn from the chimical epistemic field in byopolimers. (from 2006 to 2019) - Patents registered and papers (Conferences are not included. Database in .bib bibliographic format.