cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/kbt8xt3678.3
title: Ransomware/Benignware System Calls

description: This is a collection of System calls of 270 Ransomware of different family and 270 Benignware of various categories. This data is collected by running the collected samples in Windows 10 within a virtual machine using API Monitor. The  dataset contains the following files :
1-	List of Ransomware.xlsx : List of Ransomware Hash
2-	List of Benign applications.xlsx : List of Benignware
3-	dataset - System calls.zip: The collected System calls
4-	dataset - output.csv : The output vector
5-	Ransomwares Syscall CSV : The collected raw system calls of Ransomware
DOI: 10.17632/r6m6zzvfp2.1
title: Financial data of selected listed companies in the Dhaka Stock Exchange (DSE)

description: This panel dataset contains the financial information of selected publicly traded non banking banking institutes listed in the Dhaka Stock Exchange (DSE) of Bangladesh. All data are compiled from the company annual reports. The currency of this dataset is Bangladeshi Taka (BDT). It also contains a exhaustive dataset of companies for the year 2017.
DOI: 10.17632/bmwyh3np9v.1
title: Internet drug trading: national review of new online drug markets for young people

description: llicit drugs are marketed both via dark web platforms and social media, but there are also research reports buying these drugs online. This study is intended to analyse the risk factors for the purchase of online illicit drugs. We assumed that social interactions, low levels of self-control, and impaired mental health would be correlated with online opioid sales following criminological and addiction analysis research. Moreover, online drug sales are expected to be related to low self-control and daily drug consumption. Participants in this nationwide study were aged 15 to 25 years and lived in Germany (N=1,732) and France (N=1,732). Measures of impulsivity, ability sensitivity, social association, psychological tension, and repetitive activity (drinking, gambling, and Internet use) predicted online drug use. 4% of German and French respondents reported buying drugs online of which, 63% did so via social media services. Online opioid purchases were associated with lower self-control, elevated social anxiety, heavy gambling, and Internet use, as shown by multinomial logistic regression and binary intervention regression models. It was not a risk factor to have online friends, but close social links with offline friends served as a security factor.r. The results indicate that more attention should be paid to mainstream social media services as a source for buying drugs as there are many psychological and self-control issues among online drug consumers.
DOI: 10.17632/493s6f753v.1
title: Human tracking dataset of 3D anatomical landmarks and pose keypoints

description: Image pose detectors in which the pose if defined by anatomical landmarks are rare and scarcely available, which impedes progress in methods of markerless motion capture and analysis applied to biomechanics. Temporal 3D scanning (or 4D scanning) systems allow human bodies in motion to be obtained with high precision, as well as providing a realistic 3D avatar of the scanned person. These two aspects can be used to obtain the pose by different methods. A first method is the location of anatomical landmarks on the mesh surface in a direct way. The other method consists in obtaining virtual images of the mesh from different points of view from which a neural network can estimate the location of body markers. This dataset associates 2D and 3D human pose keypoints estimated from images with MediaPipe (https://developers.google.com/mediapipe) with the location of their corresponding 3D anatomical landmarks. It consists of 567 movement sequences of 71 participants in A-Pose and performing 7 movements (walking, running, squatting, and four types of jump) who were scanned with Move4D (https://www.move4d.net/) to build a collection of 3D human moving meshes with texture and with anatomical correspondence (a total amount of 50,952 poses). From each mesh of that collection, the 3D locations of 53 anatomical landmarks were obtained and 48 images were created using virtual cameras with different perspectives. 2D pose keypoints from those images were obtained using MediaPipe's Pose landmarker model and their corresponding 3D keypoints were calculated by linear triangulation. There is one folder per participant which contains two Track Row Column (TRC) files and one JSON file per movement sequence. One TRC file is used to store the 3D keypoints triangulated and the other contains the 3D anatomical landmarks. The JSON file stores 2D keypoints and the calibration parameters of the virtual cameras. The anthropometric characteristics of the participants (height, weight, age and sex) are annotated in a single CSV file. The files are named following the next scheme [CODE]_[MOVEMENT]_[DATA].[EXT], in which: [CODE]: is the participant code. The last character (F/M) makes reference to the sex ("F" female, "M" male). [MOVEMENT]: Name of the movement (A-POSE / F-JUMP / GAIT / J-JACKS / JUMP / RUNNING / SQUATS / T-JUMP). [DATA]: Reference data (AL = anatomical landmarks / KP2D = keypoints in pixels and cameras calibration / KP3D = 3D keypoints obtained by triangulating the 2D keypoints). [EXT]: file extension (TRC / JSON). The JSON files contains general sequence data ("subject", "movement", "fps") and a list of annotations ("frame", "camera", "keypoint_scores", "proj_matrix", "proj_matrix_rows", "proj_matrix_cols" ). "keypoint_scores" is vector of size 99 (u1, v1, score1, … u33, v33, score33) where (ui,vi) is the 2D keypoint location and score(i) is its associated score. The AVI file shows an example of the 3D landmarks contained in both TRC for TDB_001_F.
DOI: 10.17632/6m5gbr9gr2.1
title: Research Methodology and Scientific Publishing Practices

description: Lecture given on September 9, 2021 by Professor Me. André Vieira Sonoda (Department of Digital Media of the Federal University of Paraíba (DEMID/ UFPB) in response to the invitation of the Professor Dr. Anderson de Sousa Mariano (Research Group on Electric Guitar Performance, Teaching and Learning – GPPEAGE/ CNPq), linked to LGEMU (Electric Guitar and Universal Music Laboratory – CCTA/ UFPB).
DOI: 10.17632/3kwhk8v5p3.1
title: Life satisfaction, leisure satisfaction, and self-reported health in Mexico, 2021

description: This data set contains the following variables: self-reported health, self-reported life satisfaction and self-reported leisure satisfaction. The data is reported for all 32 Mexican states during the year 2021, and were obtained from the National Institute of Statistics and Geography. 

The analysis has been carried out by way of applying a simple log-log multivariate regression in order to calculate the effect of self-reported health and self-reported leisure satisfaction on the level of self-reported life satisfaction. The results indicate that both dependent variables statistically significant at the 5% level, and that self-reported health has a higher impact on the Mexican’s level of life satisfaction. 

In addition to the files containing the data, the EViews file containing the multivariate regression analysis is shared
DOI: 10.17632/pn6y769thd.1
title: Raman data

description: This is Raman data for "Burnt Cervidae bones and sedimentary environments at Luotuodun, Jiangsu Province, China: New insights for Neolithic human behavior"
DOI: 10.17632/gzm5pxntyv.1
title: Nitrogen Deficiency of Rice Crop

description: The image data set consists of four category of Nitrogen deficient Rice crop Leaf images match with Leaf Color Chart.
DOI: 10.17632/t3hs3gwg3s.1
title: Acoustic phonon anisotropy: Phonon focusing

description: Title of program: ACOUSTIC PHONON ANISOTROPY Catalogue Id: AAOJ_v1_0 Nature of problem Calculation of the phase velocity, polarization vector, group velocity, and phonon-focusing enhancement factor for non-dispersive acoustic plane-waves of any wave-vector. Versions of this program held in the CPC repository in Mendeley Data AAOJ_v1_0; ACOUSTIC PHONON ANISOTROPY; 10.1016/0010-4655(82)90065-0 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2019)
DOI: 10.17632/bbvy6fvfnr.1
title: Revised Lake Bonny Dataset - Volante et al.

description: This file contains the data used in Figures 2 - 6, and the tabs in the file are named accordingly. Figure 2 contains the abundance of zinc, total lead, total lead-210, excess lead-210, and radium-226 in the Lake Bonny core. Figure 3 contains the raw data used in the serac model (left) and the age model produced by the serac piecewise CRS model (right). Figure 4 contains the radium-226 activity and phosphorous abundance in the core. Figure 5 contains the loss on ignition value, total mass accumulation rate, organic and mineral mass accumulation rates, and the population of Lakeland, Florida. Figure 6 contains the radium-226 activity and water pumpage values for Lakeland, Florida over time.
DOI: 10.17632/f6zw5bzfhc.1
title: Dephosphorylation of bZIP59 by PP2A ensures appropriate shade avoidance response in Arabidopsis

description: Changes in light quality and quantity experienced by many shade-intolerant plants grown in close proximity lead to transcriptional reprogramming and shade avoidance syndrome (SAS). Despite the importance of phosphorylation-dependent signaling in cellular physiology, phosphorylation events during SAS are largely unknown. Here, we examined shade-regulated phosphorylation events in Arabidopsis using quantitative phosphoproteomics. We confirmed shade-induced dephosphorylation of bZIP59, a basic region/leucine zipper motif (bZIP) transcription factor. Shade treatment promotes the nuclear localization of bZIP59, which can be mimicked by mutation of the phosphorylation sites on bZIP59. Phenotypic analysis identified that bZIP59 negatively regulated shade-induced hypocotyl elongation. bZIP59 repressed the shade-induced activation of certain growth-related genes, while shade increased the DNA binding of bZIP59. Furthermore, the protein phosphatase 2A (PP2A) mediated de-phosphorylation of bZIP59. Our study characterized a previously unidentified mechanism by which the phyB-PP2A-bZIP59 regulatory module integrates shade signals and transcriptomes, broadening our knowledge of phosphorylation strategies for rapid adaptation to shade.
DOI: 10.17632/g7fpgj57wc.2
title: Betel Leaf Image Dataset from Bangladesh

description: This dataset presents collection of images focused on betel leaves, aimed at categorizing them into four distinct conditions: healthy, dried, afflicted by bacterial disease, and suffering from fungal brown spot disease. Captured in Camperhat, Raipur, Lakshmipur, Bangladesh, this collection underscores a meticulous approach to data gathering for disease identification and classification in betel leaves.

Organized into two primary folders, Original and Augmented, the dataset contains a total of 3589 images. The Original folder houses 1000 images, evenly distributed across the four leaf conditions to ensure a balanced representation. The Augmented folder, on the other hand, expands this dataset to include 2589 images, which are then divided into training (2388 images) and testing (201 images) subsets. This structure is designed to support the training of both deep learning and machine learning algorithms, with a clear aim towards the precise classification and recognition of the various states of betel leaf health.
DOI: 10.17632/5rwpwr9rf2.1
title: Correlation of Personality Traits & GPA for Jordanian Medical Students

description: Objectives: To investigate the relation between personality traits and academic performance of medical students and evaluate if correlations between personality traits and examination scores are affected by gender or year of study.  

Methods: A sample of 307 medical students, at the Hashemite University, Jordan completed an online questionnaire to identify Big Five Model personality traits. Grade Point Average (GPA) scores were retrieved from the University database and data analysed using SPSS 16.0. 

Results: Correlation between personality traits and GPA score was investigated using Pearson coefficient. Only Conscientiousness had a significant positive correlation (r = .231, p < .001). Two-way ANOVA testing investigated the effect of gender, personality trait, and the interaction between them on GPA. Only Conscientiousness had a statistically significant effect on GPA (P = .001) and there was no significant effect of gender or its interaction with personality traits on GPA. Investigating the interaction between year of study and personality traits, there was only a statistically significant interaction effect between year of study and Openness (F (1, n=307) = 10.297, P =.001) on GPA.
DOI: 10.17632/fgs9pyfv2z.2
title: Updated Ljubljana Breast Cancer Data Set: reduced and cleaned version

description: This dataset contains information for Machine Learning algorithms to forecast recurrence events (RE) for patients with breast cancer stages I to III. The dataset contains 252 instances and six attributes, including a binary class indicating whether RE occurred. This dataset has been reduced and denoised from the original Ljubljana, which holds 286 instances with ten attributes each (LBCD, Zwitter M. and Soklic M. (1988). Breast Cancer. UCI Machine Learning Repository. https://archive.ics.uci.edu/dataset/14/breast+cancer). The ranking results by eight different Machine learning algorithms and statistical handling of the ranking 8-component vectors for attributes allow one to reduce ten features to six of the most relevant ones. The most pertinent features were the following five: {deg_malig, irradiat, node_caps, tumor_size, inv_nodes}. Less relevant found four attributes: {age, breast_quad, breast, menopause}. The CAIRAD: Co-appearance based Analysis for Incorrect Records and Attribute-values Detection ( Rahman MG, Islam MZ, Bossomaier T, Gao J. CAIRAD: A co-appearance based analysis for incorrect records and attribute-values detection. Proc Int Jt Conf Neural Networks. 2012;(June). https://doi.org/10.1109/IJCNN.2012.6252669) filter has been determined the noises in attributes and class features. Per the filtering results, 34 instances of LBCD had noises in half (or even more than half) of their features. Those were removed from the data. It is known that the noises in the class are riskier and teasing than those of attributes. Meantime, the class attribute had 35 (14%) missed values from 252 after COIRAD filtering. It was unacceptable, considering the comparable number (only 85 cases) of recurrence events in the class of initial LBCD. The imputation (reconstruction, "cure") of missed values was performed via the algorithm offered in: Bai BM, Mangathayaru N, Rani BP. An approach to find missing values in medical datasets. In: ACM International Conference Proceeding Series. Vol 24-26-Sept. ; 2015. https://doi.org/10.1145/2832987.2833083. The noises presented in the remaining attributes, ranging from 1% to 14%, were neglected. There are 252 instances in the dataset, of which 206 do not have RE, and the remaining 46 have RE. Six attributes, including its class, define each instance. This dataset is obtained from the initial version of the LBCD betterment, and it provides a significant advantage in the performance over the original LBCD for most classifying algorithms of Machine Learning. However, the dataset is slightly more imbalanced than the LBCD, which is a minus.
DOI: 10.17632/hm5n8w628c.1
title: ARC: An open-source library for calculating properties of alkali Rydberg atoms

description: We present an object-oriented Python library for computation of properties of highly-excited Rydberg states of alkali atoms. These include single-body effects such as dipole matrix elements, excited-state lifetimes (radiative and black-body limited) and Stark maps of atoms in external electric fields, as well as two-atom interaction potentials accounting for dipole and quadrupole coupling effects valid at both long and short range for arbitrary placement of the atomic dipoles. The package is cross-referenced to precise measurements of atomic energy levels and features extensive documentation to facilitate rapid upgrade or expansion by users. This library has direct application in the field of quantum information and quantum optics which exploit the strong Rydberg dipolar interactions for two-qubit gates, robust atom-light interfaces and simulating quantum many-body physics, as well as the field of metrology using Rydberg atoms as precise microwave electrometers.
DOI: 10.17632/jg2z4xgtmz.1
title: Dataset of Retinal blood Vessels of Healthy and Diabetic Retinopathy Individuals

description: This dataset contains 50 retinal blood vessels extracted from retinal images available in Diabetic Retinopathy Image Database (DRiDB) public database. The database contains 50 colour fundus images that were captured with Zeiss VISUCAM 200 fundus camera at 45o field of view. 36 of these images has signs of DR while 14 does not show any signs of DR.
DOI: 10.17632/bfmpbx432k.1
title: Contrast based lesion segmentation on DermIs and DermQuest datasets.

description: In this companion paper, we present the results obtained by our contrast based approach for lesion segmentation on two datasets used by amelard et al. (Amelard, J. Glaister, A. Wong and D. A. Clausi, High-Level Intuitive Features (HLIFs) for Intuitive Skin Lesion Description, IEEE Transactions on Biomedical Engineering, 62(3) (2015), 820-831). The first is a subset of a DermIs database (Dermatology Information System, available online: http://www.dermis.net) that contains 43 macroscopic photographs with lesion diagnosed as melanoma and 26 diagnosed as non melanoma. The second is the subset of the DermQuest database (Available online: http://www.dermquest.com) that contains 76 images of melanoma lesions and 61 images of non melanoma lesions. The images are subject to various artifacts like drastic shadow effect and the variation of illumination. We also provide the ground truth segmentation to evaluate visually the accuracy of our results.
DOI: 10.17632/cvyhwh6d65.2
title:  Site-specific Glycan Alterations in Pemphigus Vulgaris: Sialylated Modifications Correlate with Disease Activity

description: To identify glycan alterations in pemphigus, we obtained de-identified serum samples from patients with pemphigus vulgaris and healthy controls from the University of Utah reference laboratory. For these samples, DSG1 and DSG3-specific autoantibody titers were determined by standardized ELISA assay. Skin-directed autoantibodies were determined by indirect immunofluorescence using normal skin as a substrate. Glycoproteomic profiling was performed by Multiple Reaction Monitoring (MRM) mass spectrometry (MS) (Hong et al., 2015, Li et al., 2019, Merleev et al., 2020, Park et al., 2018). Associations between glycopeptides and age, gender, and presence or absence of disease were determined by multiple regression.
DOI: 10.17632/jxwvdwhpc2.1
title: BreakHis - Breast Cancer Histopathological Database

description: This dataset was created to be used in machine learning tasks for both binary and multiclass classification problems. It consists of 7,909 microscopic images of breast tumor tissue, captured using different magnification factors (40X, 100X, 200X, and 400X). The images in this dataset were resized to 224x224 pixels and organized according to binary and multiclass classification tasks.
DOI: 10.17632/s7zh769rsc.1
title: Dietary Data

description: The Excel sheet 1 provides information on the frequency and the amount of food items consumed, daily intakes of macro and micronutrients, phytochemicals, dietary fibre, servings of food groups (vegetables, fruits, grains, dairy, meat/beans, dairy and fat/sugar/sweets) and health indices (glycaemic index, glycaemic load and healthy eating index). The frequency of consumption of food items is presented as the following codes; 1=never, 2=a few times per year, 3=once per month, 4=2-3 times per month, 5=once per week, 6=2 times per week, 7=3-4times per week, 8=5-6 times per week, 9=every day. To be consistent, we have converted the frequency of consumption of food items to per week. As shown in Excel sheet 1, the amount of food consumed is coded as 1, 2, 3, 4 referring to the serving sizes from small to large and M referring to missing data. Excel sheet 2 provides the codes based on the number of servings from 1-4 or missing data as “M” for each food item or a group of similar items. Excel sheet 3 provides the data dictionary for demographic and lifestyle variables, indicators of EBW, and food items provided in the excel sheet 1.
DOI: 10.17632/834vsxnb99.1
title: Urdu News Dataset 1M

description: The dataset – A Large-Scale News Dataset for Urdu Text Processing, to the best our knowledge, is the only available large-scale dataset on Urdu lan- guage for many NLP, Machine/Deep Learning tasks: text processing, classification, summarization, Named Entity Recognition, Topic Modeling, and Text Generation. This dataset offers above 1 Million Urdu news stories text corpus for four distinct categories: Business & Economics, Science & Technology, Entertain- ment, and Sports. These four distinct categories are appropriately chosen to elim- inate any ambiguity therefore this dataset is suitable for many Urdu NLP tasks.
DOI: 10.17632/8vgy8wjdnz.1
title: Dataset of Bibliometric Research in Indonesia (2004-2020)

description: The bibliometric reseach dataset with affiliated research institutions is from Indonesia, which was indexed by Scopus from 2004 to 2020. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/8hdt269s7r.1
title: Medical MNIST

description: This dataset is a simple MNIST-style medical image in 64x64 dimensions;
There were originally taken from other datasets and processed into such style. There are 58954 medical images belonging to 6 classes.
DOI: 10.17632/nfc34n8svj.2
title: DATS_2022

description: DATS_2022 is a dataset that covers the images from Indian roads to capture the unstructured Indian traffic scenario. The dataset contains more than 10,000 images.  A mix of photo and video mode of the camera was used to capture the images. 10-15 sec long video sequences  with 30 frames per second (FPS) were recorded on various locations at different times of the day.  VLC Media Player was used to extract the frames from the video sequences. Annotations for a small set of images in .xml, .txt and .json formats are also included. It aims to support research in the area of object detection and classification using machine learning and deep learning algorithms.