cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/9sxpkmm8xn.1
title: A Curated Hate Speech Dataset

description: This dataset contains hate speech sentences in English. It has 451709 sentences in total. 371452 of these are hate speech, and 80250 are non-hate speech. 

The dataset is organized into folders as follows:

0_RawData contains data collected from different sources to assemble a dataset of hate speech sentences.

1_ContractionProfanitiesEnglish contains commonly used contractions and a list of profanities used in the English language.

2_PreprocessedData contains the final_preprocessed_data_yidong_devansh.csv file with sentences generated by the following process:
1. Removing multiple spaces, hyperlinks, user mentions, emojis, and emoticons converted to text, and removed new line characters;
2. After all these characters were removed, the contractions found in the text were expanded. Grammatical errors were corrected using the word mover's distance between sentences generated from contraction with multiple possibilities using the Google News Word2Vectors [https://code.google.com/archive/p/word2vec/] and the opensource Gensim mode [https://radimrehurek.com/gensim/models/word2vec.html];
3. Removing date and time values;
4. Removing accented numbers and characters (e.g., ^ea, or ^12);
5. The remaining numbers are converted to words;
6. Removing ampersands from the beginning of words;
7. Removing the following characters (_"\-;%()|+&=*%.,!?:#$@[]/) from the text;
8. Generating an intermediate file preprocessed_data_yidong_devansh.csv;
9. Replacing misspelled profanities from the text with correctly spelled versions based on the Profanities.csv file;
10. Generating the final_preprocessed_data_yidong_devansh.csv.

3_DataAugmentationAndBERTVocab
Final_Y_D_data.csv was used to generate the YD_aug_data_balanced.csv file by downsampling the class with more samples.

4_PretrainedBERT Contains the custom BERT tokenizer vocabulary and configuration.

5_TrainValidationFolds Contains the training data and validation folds for a 5-Fold CrossValidation scheme.

6_MissclassifiedBERT2DataFolds Contains sentences that were misclassified by the HS-Bert Model and their true labels

7_BILSTM-model1 Contains the Keras embedding layer for the BILSTM-model1 network.

8_BILSTM-model2 Contains the word embeddings for the BILSTM-model2 network.

9_TFIDF Contains the TF-IDF vectors for the logistic regression and decision tree models.

10_GabAndRedditComparison contains the training and test files for comparison with the authors from [Jing Qian, Anna Bethke, Yinyin Liu, Elizabeth Belding, and William Yang Wang, "A Benchmark Dataset for Learning to Intervene in Online Hate Speech", arXiv:1909.04251v1 [cs.CL] 10 Sep 2019.].

–

For data sources please check the README file.
DOI: 10.17632/pgrvssrwy6.2
title: Human Wellbeing and Machine Learning

description: Supplementary Material for

Human Wellbeing and Machine Learning

by Ekaterina Oparina (r) Caspar Kaiser (r) Niccolò Gentile; Alexandre Tkatchenko, Andrew E. Clark, Jan-Emmanuel De Neve and Conchita D'Ambrosio

This repository contains the list of variables that are used in the Extended Set analysis for the German Socio-Economic Panel, the UK Household Longitudinal Study, and the American Gallup Daily Poll. The variables are grouped into categories, the summary table is reported at the beginning of the document. We use the 2013 Wave of Gallup and SOEP, and Wave 3 of the UKHLS (which covers 2011-2012). Our dataset includes all of the available variables, apart from direct measures of subjective wellbeing (such as domain satisfaction, happiness, or subjective health) or mental health and technical variables (e.g. id numbers). We also exclude variables with more than 50% missing values.

The presented lists include the variables before processing. For the analysis, we convert categorical variables into a set of dummies, one for each category. We then drop all perfectly collinear variables.
DOI: 10.17632/5gp976kchf.1
title: Factors associated with maternal survival in a low-resource setting

description: Maternal mortality is a global concern and a consensus has been reached that the health of mothers and children is an important indicator of national health and the socio-economic development of countries. In 2015 the reduction of maternal mortality was adopted in the global and national initiatives for improving maternal health under Sustainable Development Goals(SDG). Despite the commitment set out in SDGs maternal mortality remains high, Zimbabwe is among the 40 countries in the world with high maternal mortality rate. There was need to analyse the causes for such high maternal mortalityhence the need for this research.The objective of the study was to determine the factors associated with maternal survival of pregnant mothers at Mpilo Central Hospital. The results of the study could help reduce maternal mortality. Data were entered into Stata12.1 statistical package. Univariate statistics were performed and presented as frequencies and percentages for categorical variables. We used Variance Inﬂated Factor (VIF) to test for multi-collinearity for all the candidate explanatory variables. Binary logistic regression was used to calculate the probability of maternal death given different variables. A p value &lt; 0.05 was taken as statistically significant. 95% Conﬁdence Interval (CI) was used. The Cox proportional hazard model was used on the factors which were found to be statistically significant in maternal mortality to analyze if they have an effect on the survival time of patients. The p-value of our model was &lt;0.0001 which identified that the model fits the data and can be used to predict survival. Kaplain Meir survival curves were used to compare survival of patients with respect to their booking status. Using binary logistic regression, the following were statistically significant associated with maternal death: age (OR 3.434, 95% CI 1.508-7.819, p=0.003), education level (OR 0.114, 95% CI 0.018-0.724, p=0.021), booking status (OR 29.547, 95% CI 8.016-111.290, p=0.001), ANC visits (OR 2.549, 95% CI 1.732-3.750, p = 0:001), PPH (0R 3.302, 95% CI 1.291-8.447, p=0.013), PIH(OR 0.010, 95% CI 0.001-0.112, p=0.001), APH (OR 3.941, 95% CI 1.371-11.329, p=0.011), sepsis (OR 5.358, 95% CI 1.792-16.022, p=0.003), retroviral infection (OR 8.466, 95% CI 1.921-37.320, p=0.005), anaemia (OR 5.647, 95% CI 1.491-21.383, p=0.011), other mode of deliveries which includes vacuum and forceps (OR 21.751, 95% CI 2.305-205.276, p=0.007) and miscarriages (OR 6.995, 95% CI 1.813-26.987, p=0.005). Using Cox regression, the following were found to be statistically significant; patients who did not book their pregnancies (HR 5.196, 95% CI 2.342-11.527, p=0.001), PPH (HR 1.790, 95% CI 1.097-2.919, p=0.020), PIH (HR 0.071, 95% CI 0.010-0.515, p=0.009), APH (HR 2.153, 95% CI 1.345-3.447, p=0.001) and ANC visits (HR 1.379, 95% CI 1.039-1.739, p=0.006)
DOI: 10.17632/gy97bcv4dm.2
title: Development of a 2NN-MEAM potential for Ti-B system and studies of the temperature dependence of the nanohardness of TiB2

description: The data provided below are files to reproduce the results presented in the article "Development of a 2NN-MEAM potential for Ti-B system and studies of the temperature dependence of the nanohardness of TiB2"
DOI: 10.17632/2pybr7f7yc.2
title: CRCCD_V1 (Colorectal Cancer Classification and Detection)

description: Colorectal Cancer Classification and Detection(CRCCD_V1). This data is collected from SUM Hospital, SOA University of Medical Science, Bhubaneswar, Odisha, India. Data is collected after all the institutional formalities and permissions from the Ethical Committee. Data is authenticated by the doctors of Gastroenterological Department. This data collection is possible by the collaboration of GIET university with SOA Institute of Medical Sciences, SUM Hospital. The dataset contains 8750 colorectal images in total having two sets: Train set and Test Set. Train set contains 7000 colorectal images consisting of 14 classes, each class having 500 images. Test set contains 1750 images consisting of 14 classes, each class having 125 images.
DOI: 10.17632/tvtg7gs59p.1
title: Aluminium Alloy Dataset for unsupervised learning

description: Experimental aluminium alloy dataset for unsupervised learning.
DOI: 10.17632/92s8ns44nf.1
title: Cold Chain in  Food Industry

description: Cold Chain Resources, Capability, and Performance in the Frozen and Chilled Food Industry
DOI: 10.17632/7kd5wj7v7p.2
title: IXI Sample Dataset

description: This project is a modified version of the IXI Dataset adapted for particular cases of use where each subject is represented by a directory containing all the modalities associated with them.
DOI: 10.17632/mpsdd9tdd7.1
title: Impact of COVID - 19 pandemic on nursing students’ attitude and practice during clinical training

description: Nursing students are the future health care providers; according to their quality of training and teaching, this can positively affect their knowledge, attitude, and practice. The challenges faced by student nurses during the COVID-19 pandemic caused them to have a negative impact on their attitude and practice during clinical training and can affect patient care. Objective: To assess the impact of the COVID - 19 pandemic on nursing students’ attitude and practice during clinical training. Design: The study was a quantitative, descriptive, cross-sectional study. Setting(s): The study was done in selected Nursing Colleges of the Northern Emirates of United Arab Emirates. Participants: The participants were 345 Bachelor of Science in nursing students currently studying in the Nursing Colleges of Northern Emirates and attending clinical training in the hospitals. Methods: The samples were all Bachelor of Science in nursing students who are attending clinical training. The sample size was a consecutive sample; the total number of students who participated was 198 students from a total population of 345. The data collection tool consists of two parts. The first part was about demographic information of the nursing students, and the second part was consists of two questionnaires on the attitude and practice of nursing students towards patient care during the COVID- 19 pandemic. Results: The study finding indicated that the majority of nursing students were age group between 21 to 25 years old (58.3%), females (93.4%), 4th year of nursing study (35.4%), working in medical ward (25.8%) and living with their parents (75.8%). Whereas about 74.9% of the students were not suffering from any health risk condition, but their families were suffering from health risk conditions, especially hypertension (40.2%). The majority of the students were tested between 11 to 19 times (47%), negative test results (94%), not isolated (58.6%) with family negative test results (55.1%). The total score category of nursing student's attitude and practice toward patient care were showed that nursing students were having average attitudes (73.7%) and average practice (70.2%) toward patient care. Conclusions: The study's finding showed that nursing students' attitude and practice were average during clinical training toward patient care during the COVID – 19 pandemics and recommended developing a training program to cultivate nursing students' skills in managing disasters.
DOI: 10.17632/w6wgkccgbc.1
title: Dataset for: Từng bước thực hành phương pháp thư mục lượng để làm tổng quan tài liệu

description: Bộ dữ liệu lưu trữ bảy tệp dữ liệu phục vụ quyển sách Từng bước thực hành phương pháp thư mục lượng để làm tổng quan tài liêu. Các tệp dữ liệu được trích xuất từ các cơ sở dữ liệu khác nhau theo các chủ đề nghiên cứu khác nhau. Các từ khóa tìm kiếm được liệt kê ở Phụ lục 2 của quyển sách. Các chủ đề được trình bày như sau. Đầu tiên, bộ dữ liệu liên quan đến các tài liệu chỉ mục Scopus về học tập trực tuyến cấp giáo dục đại học (tên tệp là demo - online learning in higher education.csv), được sử dụng làm ví dụ minh họa cho các phương pháp phân tích thư mục lượng xuyên suốt quyển sách. Thứ hai, bộ dữ liệu bao gồm các tài liệu chỉ mục Scopus về tiêu thu và sản xuất có trách nhiệm từ Việt Nam (demo 2 - Tieu thu va san xuat co trach nhiem tu Viet Nam.csv). Thứ ba, bộ dữ liệu bao hàm các tài liệu chỉ mục Scopus về giáo dục có chất lượng từ Việt Nam (demo 3 - Giao duc co chat luong tu Viet Nam.csv). Thứ tư, tệp demo 4 - e-tourism chứa các tài liệu chỉ mục Web of Sciences liên quan các vấn đề du lịch số. Thứ năm, các tài liệu chỉ mục Web of Sciences liên quan chủ đề tâm lý học mạng được lưu ở tệp demo 5 - cyber-spychology.txt. Thứ sáu, các vấn đề liên quan đến lão hóa từ Việt nam (demo 6 - Lao hoa tu Viet Nam.txt) được chỉ mục PubMed. Thứ bảy, tệp demo 7 - ChatGPT.csv lưu trữ một số tài liệu chỉ mục Dimensions liên quan đến ChatGPT. Các bộ dữ liệu từ thứ hai đến thứ bảy được sử dụng thực hành các phương pháp phân tích thư mục lượng ở trên lớp hoặc ở nhà.
DOI: 10.15468/dl.5bky2k
title: Occurrence Download

description: A dataset containing 62 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pittosporum phillyraeoides DC.",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 62 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009272-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/cxbxs9btsv.1
title: LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales

description: Since the classical molecular dynamics simulator LAMMPS was released as an open source code in 2004, it has become a widely-used tool for particle-based modeling of materials at length scales ranging from atomic to mesoscale to continuum. Reasons for its popularity are that it provides a wide variety of particle interaction models for different materials, that it runs on any platform from a single CPU core to the largest supercomputers with accelerators, and that it gives users control over simulation details, either via the input script or by adding code for new interatomic potentials, constraints, diagnostics, or other features needed for their models. As a result, hundreds of people have contributed new capabilities to LAMMPS and it has grown from fifty thousand lines of code in 2004 to a million lines today. In this paper several of the fundamental algorithms used in LAMMPS are described along with the design strategies which have made it flexible for both users and developers. We also highlight some capabilities recently added to the code which were enabled by this flexibility, including dynamic load balancing, on-the-fly visualization, magnetic spin dynamics models, and quantum-accuracy machine learning interatomic potentials.
DOI: 10.17632/6vvkrsk755
title: Race, language similarity and feeling safe

description: Race and language similarity within South African municipalities with self-reported feelings of safety and fear of crime. The data for this paper was constructed using a combination of proprietary municipality-level data accessed through University of Pretoria library licenses and publicly available individual-level survey microdata.
DOI: 10.17632/w8y95npv35.1
title: Matlab code for Effects of Higher Education Subsidy

description: It contains the matlab code for "Effects of Higher Education Subsidies on Equity and Efficiency across Developmental Stages," forthcoming economic modelling
DOI: 10.17632/8gb9r2yhfc.6
title: Labeled dataset for bee detection and direction estimation on beehive landing boards

description: Bee detection/segmentation datasets contain directories of images and labels. Detection dataset contains 7200 frames. Segmentation dataset contains 2300 cropped images of bees labeled with triangle shape for direction vector estimation. Labels are saved in yolo format. Frame resolution 1920x1080. Frames were captured 30 cm above 8 different beehive landing boards. Time: June-July 2023. Location: Lithuania.

In version no. 5, labels were corrected in detection dataset.
Pose directory was added for bee direction estimation. Annotations in pose dataset were saved in yolo format.
If bee is fully visible then first point [px1, py1] marks a head, second point [px2, py2] marks stinger.
If only part of bee is visible then first point marks the front, second point marks the back.
Annotation format in pose dataset: [class=0, x, y, w, h, px1, py1, px2, py2]
Pose dataset contains total 400 frames of 8 beehives entrances. 50 frames per beehive.

In version no. 6, the ramp detection dataset was added. It contains 156 images.
Annotation format in ramp detection dataset: [class=0, x, y, w, h, px1, py1, px2, py2, px3, py3, px4, py4]
Here, x, y, w, h are coordinates of the bounding boxes and px1, py1, px2, py2, px3, py3, px4, py4 are coordinates of 4 keypoints: 1 - top left, 2 - top right, 3 - bottom right, 4 - bottom left.

The tracking and behavior datasets represent annotated MP4 files with tracks of bees during foraging, defense, fanning, and washboarding. It contains 17162 tracks, 21946 frames.
The tracks and behavior are annotated only for the bees that are in the entrance zone. The bounding boxes are normalized to the width and height of the frame.
Annotation format in tracking dataset: [frame-id, track-id, bb-left, bb-top, bb-width, bb-height].
Annotation format in behavior dataset: [frame-id, track-id, bb-left, bb-top, bb-width, bb-height, class-for, class-def, class-fan, class-wash]
DOI: 10.17632/6jd4rn2z9x.1
title: Test dataset for: Automatic multi-label ECG diagnosis of impulse or conduction abnormalities in patients with deep learning algorithm: a cohort study

description: This test dataset comprised of 828 ECGs, where patients were not included in the training/validation set and each patient only contributed one ECG trace to prevent the overlapping of patients, is constructed to correspond to the training/validation set of this paper. Three board-certified actively-practicing cardiologists, including one board-certified actively-practicing cardiac electrophysiologist, annotated ECGs in this test dataset. Cardiologist committees discussed the records and annotated by consensus, providing an expert standard for model evaluation. The data included standard 10-second, 12-lead ECGs recorded at a sampling rate of 500 Hz using GE-Marquette type 3500 or 5500 ECG machine (General Electrical company, Marquette, WI, USA), 24-hour dynamic 12-lead ECGs recorded by a Holter machine (DMS Holter Company, California, USA), or Electrophysiological monitor (Dong Fang Company, Shanghai, China, only offending ECG data of PSVT). The raw data were stored using the MUSE data management system. The ECGs were classified into 21 specific class rhythms including: normal (N), Sinus Tachycardia (ST), Sinus Bradycardia (SB), Premature Atria contraction (PAC), Atrial Rhythm (AR), Atrial tachycardia (AT), Atrial Flutter (AFlutter), Atrial Fibrillation (AFib), Premature Junctional Contraction (PJC), Junctional Rhythm (JR), Paroxysmal supraventricular tachycardia (PSVT), Premature Ventricular Contraction (PVC), Idioventricular Rhythm (IVR), Ventricular Tachycardia (VT), Artificial Atrial pacing Rhythm (AAPR), Artificial Ventricular pacing Rhythm (AVPR), Left bundle branch block (LBBB), First-degree atrial-ventricular Block (1st Deg AVB), Mobitz I second-degree atrial-ventricular Block (Mobitz I AVB), Wolff-Parkinson-White Syndrome type A (WPW-A) and Wolff-Parkinson-White Syndrome type B (WPW-B)
DOI: 10.17632/7vhh46pgtk.1
title: Data for: Bank privatization, finance, and growth

description: Abstract of associated article: This paper examines whether privatizing state-owned banks improves finance and economic growth. To do so, we exploit regional banking variations in Russia induced by the idiosyncratic creation of “specialized banks” in the last years of the Soviet Union (1988–91) that were subsequently privatized. Starting in 1999 private banks including surviving spetsbanks emerged as an important source of external finance for private firms and households. We document that the regional concentration of spetsbanks in the early years of the Russian federation is orthogonal to economic fundamentals that are related to growth after the emergence of bank finance. Results indicate that while privatized banking increased lending significantly, it did not increase economic growth. However, privatization did increase growth when banks retained fewer political connections and when regional property rights were better protected, highlighting the importance of both factors.
DOI: 10.17632/kjgrct2yn3.2
title: Fitness-gym and Living-room Occupancy Estimation Data

description: This dataset comprises the environmental information (pressure, altitude, humidity and temperature) and corresponding occupancy level of two different locations: (1) a fitness-gym and (2) a living-room. The fitness-gym data were collected over six days between September 18 and October 02 of 2019. The living-room data were collected over 11 days be-tween May 14 and June 4 of 2020. Additionally, the number of mechanic ventilators is provided for the living-room data.
DOI: 10.17632/4rw7ssp3y8.1
title: Dataset: Habitat Use by Iberian Harbour Porpoises: Ecological and Human Factors

description: Data collected from 195 daily boat surveys spanning eight years along the north-western coast of Spain, we observed 287 harbour porpoise groups comprising 1383 individuals.
DOI: 10.17632/nhsktkcs3d.1
title: LiP-SMap screen

description: Supplementary analyzed data from Manuscript: TITLE: A map of protein-metabolite interactions reveals principles of chemical communication. JOURNAL: CELL. Article Type: Resource Article First Author: Ilaria Piazza Authors: Ilaria Piazza, Karl Kochanowski, Valentina Cappelletti, Tobias Fuhrer, Elad Noor, Uwe Sauer, Paola Picotti. Corresponding Author: Paola Picotti FILE: Piazza_SupplDataS8: Supplementary_DataAnalysis_S8. Related to Figure 6 and S6. Differential SEC-MS elution profiles upon ATP binding of ATP binding proteins undergoing large structural changes found by LiP-SMap. FILE: Piazza_SupplDataS9: Supplementary_DataAnalysis_S9. Related to Figure S6. Differential SEC-MS elution profiles upon ATP binding of proteins that do not bind ATP. FILE: Piazza_SupplDataS10: Supplementary_DataAnalysis_S10. Related to Figure 7. Concentration dependent local structural response curves relative to single conformotypic peptides.
DOI: 10.17632/99xzvh86p9.1
title: Survey on the use of online learning tools among students in COVID-19.

description: Survey on the use of online learning tools among students in COVID-19 Number of Students: 496