cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1560060.v1
title: THE DETERMINANTS OF INTENTION TO

description: While the penetration of the Internet in consumers’ daily lives still continue with an increasing momentum, this new medium has experienced a radical transformation from being a communication tool to be an economic platform where consumers do not only communicate but also transact. In this perspective, online consumer behavior became an important area for both academics and professionals, which needs to be investigated and explored. As the Internet is a new technological channel for shopping, consumers need first to decide to use this new channel for shopping and then make their online retailer preference. Thus, online consumer behavior involves a two-step process composed of intention to shop online and selection of e-store. The purpose of this study is to develop and test a two steps online consumer behavior model which explains the dynamics of the intention and selection processes. A two staged research design has been implemented in the study. At the first stage, parallel to the existing literature, the effects of risk perceptions, technology acceptance factors, and benefit perceptions on the intention to shop online has been measured. The effect of retailer brand equity on e-store selection process has been measured on the second stage. The research hypotheses have been developed based on both the existing theoretical ground and current findings in the literature. The results of the study confirmed that risk perceptions, technology acceptance factors and benefit perceptions regarding online shopping play a decisive role in the intention of consumers to shop online. A second important finding of the study is that once consumers’ involve into online shopping activity, the strength of retailers’ brand equity directly affects the consumers’ store preference.
DOI: 10.17632/25d88xwj8x
title: Mendeley Supplementary Table 1: Demographics of surveyed physicians

description: Supplementary table for our A survey of clinicians regarding preferred severity assessment tools for hidradenitis suppurativa. This table details the demographic information of surveyed physicians.
DOI: 10.17632/93sd22b7zy
title: THE ESSENCE OF NATIONAL UNITY AND INFLUENCING FACTORS

description: National unity is essential for societal stability, economic growth, and global influence. Achieving this requires addressing internal divisions and external pressures through inclusive policies, cultural preservation, and equitable development. A shared national identity and commitment to common goals are crucial for overcoming challenges and fostering unity. Governments play a pivotal role by implementing policies in education, language preservation, legal systems, and economic advancement to promote cohesion.
DOI: 10.17632/x2pv3jghk7
title: Development of a valid and reliable VR-based decision-making assessment system for basketball players

description: This is expert and novice assessment data as well as novice retest assessment data.
DOI: 10.6084/m9.figshare.19420058.v1
title: Genome assembly, annotation for rice bean

description: We present a high-quality reference genome for rice bean landrace FF25 based on PacBio long-read, Illumina short-read and HiC map.
DOI: 10.6084/m9.figshare.26087377.v1
title: The de novo assembly sequences of <i>Z. nevadensis</i> and <i>G. satsumensis</i>

description: The de novo assembly sequences of <i>Z. nevadensis</i> and <i>G. satsumensis</i> were used to obtain genes. We used Trinityrnaseq v. 2.15.0 to assemble the sequences of each termite species.
DOI: 10.6084/m9.figshare.3121582.v1
title: Working Memory Training in Healthy Adults

description: This is a database of healthy adults, aged 30-60, who participated in a study comparing online working memory training to online processing speed training. Participants are English speaking and data was collected at the University of Calgary, Calgary, Alberta, Canada between 2011-2013.Participants completed a demographics questionnaire, a brief measure of intelligence (Wechsler Abbreviated Scale of Intelligence; WASI), and measures of working memory, processing speed, and fluid intelligence. After completing 5-weeks of working memory training or processing speed training, participants again completed measures of working memory, processing speed, and fluid intelligence. Of the 81 participants who consented to participate, 61 (75%) completed baseline and post-training testing. Four participants were removed from analysis due to low training dosage, resulting in 57 participants.The University of Calgary Conjoint Faculties Research Ethics Board approved this study, and all participants provided written informed consent. <br>
DOI: 10.17632/2r9mzf9kf7
title: Mitochondrial DNA copy number and risk of diabetes mellitus and metabolic syndrome

description: Supplementary Material for Mitochondrial DNA copy number and risk of diabetes mellitus and metabolic syndrome.
DOI: 10.17632/m4s2jn3csb
title: Chest X-Ray Image

description: Chest X-ray images are a critical diagnostic tool in the field of medicine, primarily used for the detection and monitoring of various lung diseases, including COVID-19 and pneumonia. These images offer a non-invasive way to visualize the internal structures of the chest, allowing medical professionals to identify abnormalities, lesions, or infections in the lungs. Lung diseases, such as pneumonia and COVID-19, are a significant global health concern. Understanding their prevalence and early detection are crucial in reducing morbidity and mortality associated with these conditions. Mortality statistics worldwide underscore the importance of effective lung disease and COVID-19 detection. According to the World Health Organization (WHO), lung diseases are a leading cause of death, accounting for approximately 4 million fatalities annually. In the case of the COVID-19 pandemic, the timely detection and management of infected individuals can significantly impact the course of the disease and reduce its spread. The "Chest X-Ray Image Dataset" is a valuable resource that aids in the diagnosis and research of lung diseases, including COVID-19. This dataset contains images collected from various hospitals in Bangladesh, where medical professionals have diligently monitored and gathered X-ray images for research and diagnostic purposes. It offers a total of 4,350 high-quality images, categorized into four distinct classes: Normal (Class Distribution: 1200 Images): This category includes X-ray images of healthy lungs, serving as a reference for comparison with diseased or infected lungs. Lung Opacity (Class Distribution: 1100 Images): These images represent cases with lung opacities or abnormalities that require further examination and diagnosis. COVID (Class Distribution: 1050 Images): This class contains X-ray images of patients with confirmed or suspected cases of COVID-19, aiding in the early detection and monitoring of the disease. Viral Pneumonia (Class Distribution: 1000 Images): X-ray images in this category are associated with viral pneumonia cases, assisting in the identification and understanding of this specific type of lung infection. This dataset plays a vital role in the healthcare sector. It empowers medical professionals and researchers by providing a comprehensive collection of chest X-ray images to facilitate lung disease and COVID-19 detection. By using machine learning and deep learning techniques, this dataset can contribute to the development of automated diagnostic tools, aiding in faster and more accurate disease identification. The insights gained from this dataset can enhance patient care, reduce mortality rates, and play a pivotal role in the ongoing battle against lung diseases and COVID-19.
DOI: 10.17632/nn85ck2wfj
title: Health Impact model - before and after intervention

description: This Python code utilizes Matplotlib to visualize the impact of an intervention on health outcomes over time. Here's a breakdown of the code:

Importing Libraries: The code begins by importing Matplotlib as plt and NumPy as np.

Defining Health Outcome Functions: Two functions, H(t) and H_prime(t), are defined to model the health outcomes before and after the intervention, respectively. These functions represent how health outcomes change over time.

Defining Time Range: The time range is defined using np.linspace() to create an array of evenly spaced values from 0 to 10, representing the time span over which the health outcomes are observed.

Creating the Plot: A new figure with a specified size is created using plt.figure(). The health outcomes before and after the intervention are plotted on the same graph using plt.plot(). Different line styles (dashed for before intervention and solid for after intervention) and colors (blue and green) are used to distinguish between the two sets of data.

Adding Significant Points: Marker points are added using plt.scatter() to indicate significant points in the data. These points represent critical points before and after the intervention.

Adding Annotations: Annotations with arrows are added using plt.annotate() to provide additional information about the critical points. These annotations help clarify the impact of the intervention on health outcomes.

Adding Labels and Title: Labels for the x-axis ('Time (years)') and y-axis ('Health Outcomes') are added using plt.xlabel() and plt.ylabel(), respectively. A title ('Health Impact Before and After Intervention') is added to describe the purpose of the plot.

Adding Legend and Grid: A legend is added using plt.legend() to identify the different data series (before and after intervention). Grid lines are added using plt.grid(True) for better readability.

Displaying the Plot: Finally, plt.show() is called to display the plot with all the added elements (lines, markers, annotations, labels, legend, and grid).

Overall, this code visualizes the change in health outcomes before and after an intervention, providing insights into the effectiveness of the intervention over time.
DOI: 10.17632/mpjbr7nfv9
title: Handwritten Notations of Digits and Fractions in Telugu Script : A Language of India

description: This repository consists of three folders of Handwritten Telugu Fraction numerals. The folder "preprocessed_img" is a balanced dataset of a total of 4000 Telugu Fraction notations (32x32 4000 images), each having 500 images per class (per digit, i.e., 8 classes). The 8 classes are ౸ (haḷḷi), ౹ (k̄alu), ౺ (ara), ౻ (mukk̄alu), ౦ (sunna), ౼ (v̄isamu), ౽ (paraka) and ౾ (muvv̄isamu). While the datasets for handwritten "0 to 9" digit images of Telugu and many other Indian Scripts are prevalent, this is the first-ever initiative to curate a Telugu Fractions-only dataset of handwritten single-digit images. A total of 80 people contributed to this dataset with their handwriting. Those handwritten sets can be found in the folder "pages_grey". The preprocessed images from this dataset helped hugely in researching handwritten digit recognition systems for Telugu Script. Telugu is a largely spoken Dravidian Language from the southern part of India. If you land upon this dataset and want to work on the same or anything better, starting from starch with the non-processed images in the folder "digit_cropped" is suggested. Please cite this creator if you adapt this dataset to your work. 

How to Cite? Check below -

Vempati, Lakshmi Sravani (2024), “Handwritten Notations of Digits and Fractions in Telugu Script : A Language of India”, Mendeley Data, V1, doi: 10.17632/mpjbr7nfv9.1
DOI: 10.17632/shs3h9df84
title: Original Spectral Data of Roasted Coffee Degree

description: This is spectral data of roasted coffee of the Robusta variety (Subang, Indonesia) measured using the AS7265X sensor
DOI: 10.17632/t89wmz5jxs
title: Dataset Measuring organizational culture, motivation, and interpersonal communication based on the multicultural teacher performance

description: The data article investigates the performance of multicultural teachers with measures organizational culture, motivation, commitment and interpersonal communication. The total number of participants was one hundred 100 survey questionnaires from multicultural teachers in Yogyakarta, Indonesia. A sample of participants from six school levels that were four multicultural elementary schools, one multicultural junior high school, and one multicultural high school. By documenting data information, the data article This article includes information on reliability and factor loadings, as well as results of regression analyses.
DOI: 10.17632/wj2h5hn7kc
title: Rice seed dataset

description: Terahertz spectral and imaging data set for detecting rice seed plumpness
DOI: 10.6084/m9.figshare.7964423.v1
title: The raw data of Psoralea corylifolia

description: The raw data of <i>Psoralea corylifolia</i><br>
DOI: 10.17632/gcvn2x7v3d
title: Job satisfaction and consumption value

description: The study combines conceptualisation of employees as consumers and jobs as products and theory of consumption values in examining job satisfaction as envisaged by Locke.
DOI: 10.5061/dryad.t4362
title: Data from: Improving automated annotation of benthic survey images using wide-band fluorescence
DOI: 10.6084/m9.figshare.22801163.v1
title: <strong>Microbial communities in terrestrial surface soils are not widely limited by carbon</strong>

description: This data set (named MCL_v. 1.0) in Excel format is a global investigation (n = 2476) of microbial carbon limitation in terrestrial surface soils, including ten variables (Numbers, Paper ID, Reference, Continent, MAT, MAP, Sample size, Longitude, Latitude and MCL). The list of reference of data sources can be found in the Supplemental information of publication.
DOI: 10.17632/r7bthvstxw
title: Vehicle Type Image Dataset (Version 1): VTID1

description: The main objective for the use of an image dataset was to examine the five vehicle types of motor vehicles that were the most commonly used ones in Thailand (sedan, hatchback, pick-up, SUV, and van). The recording devices to collect the images were part of a video surveillance system located at Loei Rajabhat University in Loei province, Thailand. The collection process took place during the daytime for four weeks between July and December 2018. Two cameras were installed at the front gate of the university. However, a small number of van images was produced in the dataset compared to the number of images of the other four vehicle types. Because of this, the researchers decided to add other vehicle-type images such as those of motorcycles into the van group and changed the name of the group to "other vehicles" to increase diversity. Finally, the first dataset called "Vehicle Type Image Dataset (VTID)" had a total of 1,410 images that could be separated into vehicle types as follows; 400 sedans, 478 pick-ups, 129 SUVs, 181 hatchbacks, and 122 other vehicle images. Each image was collected using the 224x224 pixel resolution.
DOI: 10.17632/jfx5zsypxf
title: EntomonVR: VR Experience in Insect Morphology

description: In recent years, the study of insect morphology benefited enormously from the emergence of new digital imaging and analysis technologies like X-ray micro-computed tomography (μ-CT), digital 3D reconstruction and animation. Through interactive gaming, virtual reality applied to learn the external morphology of insects could reach a broad audience of both entomologists and non-specialists. EntomonVR is a serious game designed to investigate the external morphology of insects with acceptable quality for the virtual reality platform. We discuss the advantages of virtual reality, introduce the EntomonVR new edutainment game and conclude about perspectives. For game assessment, we have tested this game on 15 participants with entomological background and improved the game based on their feedback. This study demonstrates the efficacy of virtual reality technology for an experimental learning environment in teaching morphology of parasitoid wasps and the need for educational programs to develop efficient and interactive tools to realize this potential.
DOI: 10.17632/ttprc6d3hg
title: Data for: Suspended sediment fluxes in a shallow macrotidal estuary

description: Timeseries of water level, tidal velocity, backscatter, suspended sediment concentration, and sediment flux derived from acoustic doppler current profilers. Sediment fluxes calculated according to Dyer decomposition equation and Yu et al. (2012) analytical model. Two deployments in 2013: February and September. Two locations in the estuary: Site 1 near the mouth of the river (48° 16.842’ N, 004° 16.009’ W), and Site 3 in the central estuary (48° 14.851’ N, 004° 10.140’ W). Yu, Q., Wang, Y.P., Flemming, B., Gao, S., 2012. Tide-induced suspended sediment transport: Depth-averaged concentrations and residual fluxes. Continental Shelf Research 34, 53-63.
DOI: 10.17632/45skyv5hzy
title: Characterization of oral and cloacal microbial communities of wild and rehabilitated loggerhead sea turtles (Caretta caretta)

description: Dataset related to the publication Filek et al. 2021 "Characterization of oral and cloacal microbial communities of wild and rehabilitated loggerhead sea turtles (Caretta caretta)" 

The data here consist of raw read count with assigned taxonomy and representative sequences (raw_reads_taxonomy_sequences.csv) and extended metadata describing each sample (extended_metadata.csv). qiime2_import.txt describes the pipeline used in QIIME2 to analyze the sequences.
DOI: 10.17632/zk6scwv52p
title: A convolutional neural network for an automatic biopsy needle detection and segmentation on ultrasound images

description: The dataset contains a convolutional neural network (CNN) which was trained to segment a biopsy needle in 2D ultrasound images. Together with the network, source files of Matlab scripts and a few input images are provided. The files are enough to run experiments. See the `README' file for further instructions.
The CNN structure and results ware described in the article "An automatic biopsy needle detection and segmentation on ultrasound images using a convolutional neural network" published by Ultrasonic Imaging in June 2021 (doi.org/10.1177/01617346211025267).
It is a fully automatic method that uses a CNN to detect a biopsy needle in 2D ultrasound images. In the paper, the CNN architecture is described, which was trained using the adaptive moment estimation optimizer. The needle is eventually located in the image by applying the Radon transform.
DOI: 10.17632/v955jxxrsc
title: DateSnO2

description: Article date
DOI: 10.17632/x29rjbpk8r
title: Raw Data for "A chemical screen identifies PRMT5 as a therapeutic vulnerability for paclitaxel-resistant triple-negative breast cancer"

description: This file contains the following raw data for "A chemical screen identifies PRMT5 as a therapeutic vulnerability for paclitaxel-resistant triple-negative breast cancer"
DOI: 10.17632/zmj5gkxbyf
title: Review Paper: From Shallow to Deep Bioprocess Hybrid Modeling: Advances and Future Perspectives

description: This dataset comprises a list of articles collected through a systematic literature review. The result is a paper titled "Advancements and Future Prospects in Shallow to Deep Hybrid Modeling for Bioprocess Digitalization."
DOI: 10.17632/kxc2fxvs2s
title: Dataset of research in homework

description: This dataset contains 429 documents related to homework in education from Clarivate Web of Science from 1977 to 2020. Information for each document includes abstract, title, authors, references, keywords, etc. Researchers can use this dataset to draw a big picture about homework literature and find out the most studied topics throughout history. A plaintext file also provided for using with VOSviewer.
DOI: 10.17632/pxtvghghb9
title: Data on ESG disclosure and corporate overleveraging

description: =This study employed data from Chinese listed non-financial companies from 2013 to 2022 to explore whether environmental, social, and governance (ESG) disclosures reduce corporate over-leveraging and the impact of economic policy uncertainty on this relationship.
All data are obtained from the China stock market and accounting research (CSMAR: https://data.csmar.com/), wind database (https://www.wind.com.cn/portal/en/EDB/index.html) and the policy uncertainty website (https://www.policyuncertainty.com/scmp_monthly.html). This study eliminates all records with missing values and used 1% and 99% tail-cutting methods to address extreme values in the data. Consequently, 12,869 sample data points are obtained.
DOI: 10.17632/bxxm6zvf49
title: DNA barcode sequences and images of subimago, exuvia, and egg of a spiny crawler mayfly Drunella trispina (Uéno, 1928)

description: Species name: Drunella trispina (Uéno, 1928) (Ephemeroptera, Ephemerellidae)
Specimen voucher: OPU_BS_2022-159-KM-EP
Sampling site: Japan: Wakayama, Hashimoto, 34°15'56.5"N 135°38'35.9"E
Date of collection: 21-May-2022, emerged on 25-May-2022
Collected by: Mikio Kato
Reared to emerge by: Mikio Kato
Identified by: Kei Wakimura
DNA sequence data: INSD accession numbers OP018496 (cox1, partial coding sequence) and OP851721 (18S rRNA gene, partial sequence)
Image 1: Dorsal view of subimago and exuvia
Image 2: Ventral view of subimago and exuvia
Image 3: Scanning electron microscopic (SEM) image of the egg obtained by Shin-ichi Ishiwata using a model JSM-6010LA (JEOL) after coating with gold by an ion coater MP-19020NCTR (JEOL).
DOI: 10.17632/s6gdxvhppk
title: ExHuME 1.3: A Monte Carlo event generator for exclusive diffraction

description: Abstract We have written the Exclusive Hadronic Monte Carlo Event (ExHuME) generator. ExHuME is based around the perturbative QCD calculation of Khoze, Martin and Ryskin of the process p p → p + X + p , where X is a centrally produced colour singlet system. Title of program: ExHuME Catalogue Id: ADYA_v1_0 Nature of problem Central exclusive production offers the opportunity to study particle production in a uniquely clean environment for a hadron collider. This program implements the KMR model [5], which is the only fully perturbative model of exclusive production. Versions of this program held in the CPC repository in Mendeley Data ADYA_v1_0; ExHuME; 10.1016/j.cpc.2006.04.005 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/yk6vpgd585
title: Data for: Familiarity, empathy and comprehension of metaphors in patients with borderline personality disorder.

description: Data used in for the manuscript "Familiarity, empathy and comprehension of metaphors in patients with borderline personality disorder." For each stimulus type, the dataset includes the absolute number of correct identified stimuli, the number of familiar stimuli and the proportion of familiar metaphors that had been answered correctly. Moreover, demographics and self-rating questionnaires are depicted for each participant. The supplementary material includes the applied German language metaphor comprehension test including English translations. The aim of the study was to address metaphor comprehension in borderline personality disorder (BPD) and its relationship to cognitive and affective empathy in 20 patients with BPD and 20 matched healthy controls who completed a metaphor task comprising conventional metaphors (CM), novel metaphors (NM), meaningless stimuli (MS), and a rating scale of familiarity, a factor known to influence performance. For cognitive and affective empathy, the interpersonal reactivity index was applied. Patients with BPD had significantly more problems in comprehending CM, but not NM or MS, and were less familiar with CM. When familiarity with the stimulus was controlled, this difference disappeared. Across all participants, fantasy correlated negatively with familiar CM. Results indicate a lack of knowledge rather than a pragmatic impairment in the comprehension of metaphors in patients with BPD.
DOI: 10.6084/m9.figshare.21440925.v1
title: PA_patch

description: These files are data generated in the article 'A photoacoustic patch for three-dimensional imaging of hemoglobin and core temperature'.