cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/xbks8674n9.1
title: Nimasari's Research: The Perception of the Roles of English Test in EFL Context:  Does it Matter to Test-Takers’ Score of Performance?

description: Research Question 
(1)	What is the test-takers’ perception of the roles of English test in EFL context?
(2)	How well do the five sub-aspects of perception (PTU, ES, TV, PLK, PCK) predict test-takers’ score of performance (ScP)? 
(3)	What are the sources of students’ perception (SoP) to the roles of English test?

Method:
Mix-method research design

Instruments:
An adapted Likert-scale questionnaire from Razavipour et al. (2020) was used to measure five subskills of perception to the roles of English language test. We adopted a qualitative research design to complement quantitative research. Sources of such views were explored using an open-ended questionnaire developed by Fan (2014)
•	ScP, as dependent variable, is test-takers’ final score of performance having STAcEP course.
•	TtP, as independent variable, is general test-takers’ perception that consists of five sub-aspects that is statistically measured and one aspect that is qualitatively reported.
•	PTU stands for perceived test use that describe test-takers’ mental representation accepting the test.
•	ES or expectation of success concerns on test takers’ hopes having the test completed or achieving particular target of score. 
•	TV is a test value in which how test-takers attach to the test
•	PLK is perceived of linguistic knowledge, related to discourse of the test.
•	PCK is perceived of content knowledge which concerns how test-takers comprehend listening and reading strategy.
•	SoP or source of perception aspect explores wider insight to support quantitative data results.


Population:
Adopting a purposive sampling method, three faculty in the university: Engineering, Health Science, and Economics took part, providing a total sample of 200 test-takers. 

The quantitative data were analyzed using descriptive statistics and multiple regression test. For try-out purposes, the questionnaire was disseminated and filled by 30 participants. The validity of adapted structure of the questionnaire, internal consistency and reliability had been statistically measured: all composite reliability coefficients above the acceptable .7 value. In addition, all quantitative components were significantly associated based on the results of structural model evaluation using PLS-SEM (Razavipour et al., 2020). Multiple regression analysis using SPSS Statistics 20 was performed to investigate RQ 1 and RQ 2. 
The qualitative data were analyzed using thematic coding. SoP was reported to answer RQ 3 according to sequential items given, exploring deeper insights from the respondents. 

The data:
Questionnaire Result (measuring PTU, ES, TV, PCK, PLK, and SoP) and Score of Performance
DOI: 10.17632/2z9gxryd5j.1
title: Vietnam trade data

description: Except for the money supply data gatherers from the State Bank of Vietnam (SBV), the monthly dataset utilized in this study is sourced from the World Bank's Global Economic Monitor (GEM). Due to data constraints, the Industrial Production Index (IIP) of Vietnam and the World are adopted as proxy variables for the Vietnamese GDP and the global GDP, respectively. All data, apart from the REER and the money supply, have undergone seasonal adjustments and span from January 2009 to December 2022
DOI: 10.17632/yzhcvn7sj5.3
title: Ransomware Combined Structural Feature Dataset

description: This dataset contains several strutuctural features extracted of 2675 binary executable samples. The training and validation set consisted of 2157 samples (80%): 1023 ransomware belonging to 25 relevant families and 1134 goodware. Meanwhile, a testing set consisted of 518 samples (20%): 385 ransomware belonging to the 15 recent families and 133 goodware.

The CSV file columns are sample ID, filename, target class (GR), family ID, and numerical columns (features), as follows:
 | ID | filename | GR | family | Features |
Training Goodware | 10000 to 11133 | Their name.exe | 0 | 0 | Numerical features |
Testing Goodware | 12000 to 12132 | Their name.exe | 0 | 0 | Numerical features |
Training Ransomware | 20000 to 21022 | Their SHA-256 hash | 1 | 1-25 family IDs | Numerical features |
Testing Ransomware | 22000 to 22384 | Their SHA-256 hash | 1 | 26-40 family IDs | Numerical features |

Options:
1) The dataset is split into individual types of features without preprocessing, including headers, imported DLLs, function calls, entropy of sections, and 3, 4, and 5-grams opcode frequencies.

2) The combined datasets include headers, imported DLLs, function calls, and entropy of sections feature sets, with and without the 3-gram feature set, after the preprocessing step, according to our research paper entitled "A Comprehensive Analysis Combining Structural Features for Detection of New Ransomware Families," from the Journal of Information Security and Applications.
Note: The preprocessing step primarily involved merging similar APIs, feature selection, and normalizing the features based on their maximum and minimum values, considering only the training data. Some features exclusively exist in the test data, with zero occurrences in the training samples. For accurate testing, it's advisable to exclude these features from the training set.

Family IDs:
Avaddon 1
Babuk 2
Blackmatter 3
Conti 4
Darkside 5
Dharma 6
Doppelpaymer 7
Exorcist 8
Gandcrab 9
Lockbit 10
Makop 11
Maze 12
Mountlocker 13
Nefilim 14
Netwalker 15
Phobos 16
Pysa 17
Ragnarok 18
RansomeXX 19
Revil 20
Ryuk 21
Stop 22
Thanos 23
Wastedlocker 24
Zeppelin 25

AvosLocker 26
BianLian 27
BlackBasta 28
BlackByte 29
BlackCat 30
BlueSky 31
Clop 32
Hive 33
HolyGhost 34
Karma 35
Lorenz 36
Maui 37
Night Sky 38
PlayCrypt 39
Quantum 40
DOI: 10.17632/xt993dk3sj.1
title: Data for: Deep belief network for gold price forecasting
DOI: 10.17632/28xc6v5cdg.1
title: Memediasi Ujaran Kebencian, dan Berita Palsu, Berita Bohong, Hoax di Facebook

description: Memediasi Ujaran Kebencian, dan Berita Palsu, Berita Bohong, Hoax di Facebook. Tata Kelola Platform sebagai Koordinasi Refleksif. 

Platform digital telah menjadi pemain dominan dalam masyarakat kontemporer dengan memposisikan diri sebagai situs kunci untuk komunikasi dan transaksi sosial. 

Artikel ini berkontribusi pada perdebatan secara teoritis dengan membangun konsep tata kelola platform sebagai koordinasi refleksif.


Tata Kelola Platform Berteori sebagai Koordinasi Refleksif. Tata kelola digunakan secara luas sebagai istilah umum untuk semua jenis proses pengaturan dan pengaturan.

Namun, ini adalah istilah yang sangat licin yang seringkali tidak jelas dan sulit dioperasionalkan.

Berulang kali digabungkan dengan istilah regulasi. Kelemahan konseptual ini tercermin dalam literatur tentang tata kelola platform. Tata kelola platform biasanya mengacu pada langkah-langkah kebijakan publik.


Tetapi perpaduan tata kelola dan regulasi ini mengurangi nilai analitis konsep tersebut. Baik efek samping dari tindakan dan proses mengejar tujuan non-regulasi.

Seperti misalnya <a href="https://caramelihat.com/"> Cara Hack FB</a>, atau seperti Facebook mengoptimalkan platformnya untuk keterlibatan maupun peran publik.

Tata Kelola Platform sebagai Koordinasi Refleksif Memediasi, Ujaran Kebencian, dan Berita Palsu di Platform. Perdebatan dan keluhan pengguna dapat ditangkap secara memadai dengan perspektif regulasi.

Mengintegrasikan beragam mode pemesanan (ketentuan layanan, debat publik, algoritme) tetapi berfokus pada kontroversi dan momen kritis ketika aktivitas rutin menjadi objek kontestasi dan perlu direvisi.


Metode Yang Digunakan

Menyatukan analisis longitudinal dari platform yang mengembangkan kebijakan dan pedoman komunitas dengan analisis wacana publik tentang penanganan konten kontroversial Facebook.

Dan ketentuan layanan atau standar komunitas serta sinonim masing-masing. Menerapkan alat penyaring dan pengkodean tematik untuk mengidentifikasi aktor yang relevan.


Hasil Yang Didapatkan

Dalam kasus, perdebatan lama tentang kelayakan gambar menyusui merupakan momen kritis. Rutinitas Facebook menghapus foto yang menampilkan bagian payudara wanita terlepas dari konteks menjadi diperebutkan untuk pertama kalinya.

Facebook memperkenalkan pengecualian eksplisit untuk aturan kontennya bahwa foto wanita yang aktif menyusui selalu diizinkan. Sejak itu, data kami menunjukkan penurunan yang jelas dalam debat publik.

Menemukan kriteria yang memadai untuk menangani di Facebook hanya menjadi masalah lagi ketika Facebook menghapus foto ikonik. 

Meskipun tidak disebut berita palsu, informasi yang salah atau menyesatkan telah diidentifikasi sebagai masalah yang bermasalah jauh sebelum pemilihan AS. 

Dan Halaman Facebook tidak boleh berisi klaim atau konten yang salah, menyesatkan, curang, atau menipu.
DOI: 10.17632/x4s5j9cs96.1
title: Table S1. Tomato genes with SINE_Au at intronic regions

description: Table S1. Tomato genes with SINE_Au at intronic regions. This table contains the names of genes of Solanum lycopersicum 'Heinz 1706' SL3.0 -NCBI annotation release 103- inhabited by Au SINE members at intronic regions. This table is supplementary material 
to the contribution in BABT "Au Family Short Retroposons Contribute to Transcriptional and Phenotypic Diversity in Tomato (Solanaceae)" by Grabiele & Aguilera.
DOI: 10.17632/yp2s4rdjjk.1
title: Data for: Dynamic walking stability of elderly people with various BMIs

description: Raw data recorded by a 15-camera motion analysis system at 60 Hz (Motion Analysis Corp., Santa Rosa, CA, USA).
DOI: 10.17632/hfnzb7ct67.5
title: Data on the most common laboratory tests with pathology in the SmartLab Kazakhstan laboratory information system database

description: The data presented in this paper are based on laboratory tests and pathology results that were found to be outside the normal range. The data was collected from several Kazakhstan medical laboratories, including the SmartLab laboratory information system. The raw data includes  7,674,353 results and raw data abnormal includes 1,898,410 results. The ranking of abnormal results was done using the TF-IDF statistical method.
The raw data tests in the Russian language and computed data in English. In this study, we performed a logistic regression analysis to predict a dependent variable. The goal of the analysis was to understand the relationship between the independent variables and the dependent variable and to make predictions about the dependent variable based on the independent variables.
DOI: 10.17632/ydtms99mjm.3
title: Languages and Social Cohesion: A transdisciplinary literature review (Dataset)

description: This dataset complements the book by Gabriela Meier (University of Exeter, UK) and Simone Smala (University of Queensland, Australia): Meier, G. & Smala, S. (2022). Languages and Social Cohesion: A Transdisciplinary Literature Review. Routledge. https://www.routledge.com/Languages-and-Social-Cohesion-A-Transdisciplinary-Literature-Review/Meier-Smala/p/book/9780367637200. Available from 26 July 2021. The dataset of 285 references to peer-reviewed articles published in academic journals between 1992 and 2017 (identified systematically following the PRISMA protocol as is explained in the Chapter 3 of the book) is offered here as an EndNote Library to increase transparency and utility of the work we present, analyse and discuss in the book. It is designed to support researchers and other stakeholders to quickly and easily find literature related to themes and sub-themes, as well as by research design. The project described in the book had the aim to answer the question: In what way are languages associated with social cohesion in academic articles? As can be seen in the concluding chapter of the book (Chapter 5), this transdisciplinary literature review resulted in a transdisciplinary language and social cohesion framework, which is accompanied by user-friendly tools that can be used to explore the language-and-social cohesion constellation in diverse real-life contexts. The EndNote Library available here presents the results of our systematic literature search and thematic analysis, which formed the basis of our analysis, discussion and interpretation of the data. In the EndNote Library, the articles are sorted by research design (qualitative, quantitative, and mixed method research, theory articles, case studies, practice reports and literature reviews). Importantly, the EndNote Library is also sorted by the main themes (see below) and respective sub-themes, which correspond to the themes discussed in the book. Main themes in the book (headings used in the EndNote Library): A: Social networks and access to resources through languages (social networks and resources) B: Norms related to languages and groups (ideological orientations) C: Languages and a sense of group belonging (belonging to groups) D: Manifestation of linguistic behaviour and social cohesion (practices in education/society) E: Formal language planning and social cohesion (policy and curricula)
DOI: 10.17632/2d6z932mzw.1
title: Bile acid-dependent transcription factors and chromatin accessibility determine regional heterogeneity of intestinal antimicrobial peptides

description: The newly generated scRNA-seq data and bulk RNA-seq data are provided here:
1. ScRNA-seq data. To investigate the regional heterogeneity of human intestine, 14 bioptic samples from human duodenum, jejunum and ileum were collected from 10 healthy donors recruited at the time of routine gastroscopy or enteroscopy or colonoscopy for single cell RNA sequencing. Healthy volunteers were individuals without gastrointestinal tumors, polyps or other organic diseases, and who were overall healthy with no underlying diseases such as hypertension and diabetes.
2. Bulk RNA-seq data. To investigate the effect of bile acis on the transcriptome of mouse intestinal organoids, mouse small intestinal organoids cultured for 2 days were incubated with a series of bile acids at 50 mmol/L for 96 hours and lysed for RNA extraction.
3. ScRNA-seq experiments in mouse duodenum organoids stimulated with DCA (50 mmol/L for 96 hours) and DMSO were employed to directly depict the changes in the proportion of epithelial lineages.
DOI: 10.17632/vt8nhp2y2t.1
title:  Metabolomic and proteomic dataset of  trauma patients in PAMPer Trial

description: Trauma is a leading cause of death and morbidity worldwide. The lack of a comprehensive characterization of the human response to severe injury limits progress in this field. Here, we present the analysis of a longitudinal, multi-omic dataset comprised of clinical, cytokine, endotheliopathy biomarker, lipidome, metabolome and proteome data from severely injured humans. This includes the validation of seven distinct modules within the metabolome in an external dataset. A “Systemic Storm” pattern with release of 1061 markers together with a pattern suggestive of the “Massive Consumption” of 892 constitutive circulating markers are identified in the hyper-acute phase post-trauma. Data integration reveals two human injury response endotypes, which align with clinical trajectory. Prehospital allogeneic thawed plasma rescues only endotype 2 patients with traumatic brain injury (30d mortality: 30.3% vs. 75.0%, p=0.0015). A machine learning based approach identifies UCHL1 as the most predictive circulating biomarker for patients most likely to benefit from early plasma treatment. These response patterns re-define the paradigm and the datasets provide a resource for the study of critical illness, trauma and human stress responses.
DOI: 10.17632/w7cvnmn4c5.1
title: Data for: Fast and robust segmentation of cell images by self-supervised learning

description: Two datasets consisting of white blood cell (WBC) images were tested in our experiments. These two datasets are chosen for our experiments, as they are significantly different from each other in terms of the image color, cell shape, background, etc., which can better evaluate the robustness of the proposed approach. The ground truth segmentation results are manually sketched by domain experts, where the nuclei, cytoplasms and background including red blood cells are marked in white, gray and black respectively. We also submitted the segmentation results by our approach, where the whole WBC region are marked in white and the others are marked in black. Dataset 1 was obtained from Jiangxi Tecom Science Corporation, China. It contains three hundred 120×120 images of WBCs and their color depth is 24 bits. The images of Dataset 1 were taken by a Motic Moticam Pro 252A optical microscope camera with a N800-D motorized auto-focus microscope, and the blood smears were processed with a newly-developed hematology reagent for rapid WBC staining. The overall background of images in Dataset one looks yellow. Dataset 2 consists of one hundred 300×300 color images, which were collected from the CellaVision blog (http://blog.cellavision.com). The cell images are generally purple and may contain many red blood cells around the white blood cells, which is quite different from Dataset 1.
DOI: 10.17632/s9tt5dvyjy.1
title: Data for: Higher and Increased Concentration of hs-CRP within Normal Range Can Predict the Incidence of Metabolic Syndrome in Healthy Men
DOI: 10.17632/pkvdfy8nby.1
title: Data for: Quantitative immunodetection of metalloprotein II in Perinereis aibuhitensis after heavy metal exposure
DOI: 10.17632/rvnk26krjs.2
title: Geological and geophysical data compilation for the western Wabigoon and southern Abitibi subprovinces of the Superior Province, Ontario, Canada

description: Geological layers representing geological observations (e.g., structural measurements, mineral occurrences) and interpretations (e.g., faults traces, map units) for and Archean greenstone belt near Dryden and Timmins, Ontario, Canada in the geological Superior Province. Newly interpreted layers such as lithology polygons (‘MapUnits’) and structural traces (‘Geolines’) are included as ESRI shapefiles. Two geophysical datasets are provided, including a database of new magnetic susceptibility measurements from 2018 and 2019 field seasons near Dryden, Ontario. Additionally, an ensemble of reprocessed aeromagnetic grids (40 m by 40 m cell size) from the Ontario Geological Survey’s (2011) geophysical survey datasets are included as projected geo .tiff and .grd files. The ensemble includes total magnetic intensity with cosine roll off filtering, first vertical derivative, second vertical derivative, tilt derivative, and dynamic range compression. Hill-shaded relief grids are also included, and their azimuth and angle of incidence are indicated in their filename.
DOI: 10.17632/y3649cmgg6.1
title: Ripe Unripe Banana Dataset

description: This dataset of 1340 photos of bananas focuses on identifying ripe and unripe fruit. Each photograph has metadata that identifies whether or not the banana in the image is considered ripe.
The data set was gathered in indoor lighting circumstances , to identify ripe and unripe bananas. Each image in this dataset has a YOLO.txt label attached to it. This data can be used to train all YOLO Object Detection models. The dataset has been divided into three sections: Train, Test, and Validation, each of which contains 65%, 20%, and 15% of the total data.
DOI: 10.17632/jrgntpv8b8.1
title: Development of a deep learning model for epiretinal membrane detection in fundus photography

description: We retrospectively collected CFP (color fundus photography) data containing ERM (epiretinal membrane) from the eyecare healthcare center (B&VIIT Eye Center, Seoul, South Korea). We collected CFP images from the patients with ERM diagnosed with KCD code H3539 (IDC-10 code H35.379) . Sample anonymized CFP data with ERM was available at the publicly accessible repository.

Files: 256 by 256 pixels fundus photographs with epiretinal membrane
DOI: 10.17632/phb9y6cp5c.3
title: Physiological Features and Inertial Features Based Dataset: PIFv3

description: Description of PIF v3 dataset General Information: 
This dataset is acquired using wearable sensors such as ECG Sensor, GSR Sensor, IMU Sensor, ProtoCentral Pulse Express with MAX30102 and max32664, and EMG Sensor from 32 participants with different age, sex, height and weights. 

Dataset File Structure:
The dataset is organised so that each subject has a folder. The folders are labelled according to participant identification number (PIDX). Each subject folder contains the following two csv files: PID_X.csv and PID_X_BPM.csv contains the information about the participant electrocardiogram, electromyography, GSR, IMU and Pulse sensor and Label performing 18 activities and Falls. 

Features that are extracted in Dataset are: 
Datetime, Sys, Dia, HR, Spo2, GSRRaw, Resistance, GSR (kohm), SCL, GSRRMS, GSRMAV, AccX, AccY, AccZ, GyroX, GyroY, GyroZ, Aroll, Apitch, Groll, Gpitch, Gyaw, Combroll, Combpitch, ECGRaw, AvgECG, ampECG, MAX, EMGRaw, EMGRMS, EMGMAV, EMGVAR, EMGSSI, IEMG and Activities.

This dataset also contains a file Participants.xlsx in which the information related to participants Age, Height, Weight, PID number, Gender, Medical History, State, etc are given. Elderly as well as young people performed all the 18 Activities.

Activities: Standing, Left Fall while Standing, Right Fall while Standing, Forward Fall while Standing, Sitting, Left Fall while Sitting, Right Fall while Sitting, Forward Fall while Sitting, Walking, Relaxing, Anxiety, Sad, Motivational, Funny, Pressing Stress Ball, Hand at Rest and Fist.

Videos link that are used to display the participants during data collection to acquire the different emotional values.

Emotions Links
Relaxing https://www.youtube.com/watch?v=0LJtn6yERns&list=PL585q5uwv3PEN4gc1OV9-Z3twsfBBLSbX&index=6&pp=gAQBiAQB
Anxiety https://www.youtube.com/watch?v=we2YF1J6jxg
Sad https://www.youtube.com/watch?v=PdSGSw3wI4Q 
Motivational https://www.youtube.com/watch?v=mFMapVqIbuE
Funny https://www.youtube.com/watch?v=jbHaP79UMpE 

Related Article: Dhaliwal MK, Sharma R, Bindra N. Analyzing Wearable Data for Diagnosing COVID-19 Using Machine Learning Model. Lect. Notes Electr. Eng., vol. 946, Springer, Singapore; 2023, p. 285–99. https://doi.org/10.1007/978-981-19-5868-7_22.
DOI: 10.17632/vhgyn5yk4g.1
title: Cardiovascular Disease Risk Dataset

description: The Cardiovascular Disease Risk Dataset (CVDR) contains anonymized data on risk factors of 71 participants, recorded in 2 different periods, totaling 142 instances.  Participants were registered with a unique ID. Data for the same participant in a different period was registered with the same ID. 

The database includes data on age, sex, weight (kg), height (m), BMI, blood pressure (mmHg), total cholesterol (mg/dl), HDL (mg/dl), abdominal circumference (cm), fasting blood sugar (mg/dl) and information on smoking (Y/N). The dataset also includes the risk score (CVD RISK): low, intermediate and high risk of cardiovascular disease development, evaluated by health professionals.
DOI: 10.17632/ypjv4pwfjd.1
title: Exploring the metabolic dynamics, storage stability, and functional potential of Lacticaseibacillus rhamnosus Probio-M9 fermented milk

description: Supplemental material for the manuscript of "Exploring the metabolic dynamics, storage stability, and functional potential of Lacticaseibacillus rhamnosus Probio-M9 fermented milk"