cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/3nz4fkwn3y.1
title: corneal-parameters-KC-study_2020-07-03

description: Data is from a study of 44 keratoconus patients. The aim of the study was to find which corneal shape parameters are most associated with vision quality (measured as contrast sensitivity and visual acuity). Dataset has 77 rows (number of eyes) and 60 columns. It contains data on keratoconus position (central/peripheral), stage, contrast sensitivity (after logarithmic transformation), visual acuity, cornea elevation measurements at different positions, and some calculated corneal shape irregularity indicators for each eye.
DOI: 10.15468/dl.8w7x3u
title: Occurrence Download

description: A dataset containing 633969 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2024-10-05",
 "EventDate is less than or equal to 2024-11-04",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 }
 ]
}

 The dataset includes 633969 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009318-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8r4drpvwkz.1
title: Guideline to teach how to describe past events

description: This guideline teaches how to use the simple past tense to describe different kinds of events.
DOI: 10.17632/6gwtwnfty7.1
title: Enhancing Alumni Employability: Aligning Higher Education Quality with Workforce Expectations

description: he file contains data from an alumni survey with two sheets: "Form Responses 1" and "coded". The responses include alumni demographics, employment details, and other feedback related to their university experience.

Here’s a summary based on the dataset, focusing on enhancing alumni employability:

Key Data Points:
Demographic Information: Includes gender, age, faculty attended, and marital status, which helps in understanding the alumni profile.
Employment Information:
Job position and sector (public/private) post-graduation.
The time it took to secure employment after completing education, indicating initial employability.
Monthly income and number of employees in their current organizations.
University Engagement:
Frequency of using the university library, a proxy for academic involvement and resource utilization during studies.
Additional information like participation in alumni events or further studies.
This data can serve as a foundation for analyzing the alignment between higher education quality and workforce expectations. Understanding employability outcomes such as unemployment periods post-graduation and the types of positions alumni secure offers insights into how well the curriculum prepares students for the job market.

Further Analysis Suggestions:
Gap Analysis: Compare employability duration and positions attained with alumni feedback on educational support (e.g., practical skills, career services).
Income vs. Job Position: Assess whether alumni in higher-paying roles were better equipped through specific university programs.
Employer Expectations: Analyze whether alumni in certain sectors faced fewer challenges in securing employment, offering insights into sector-specific preparation.
Would you like to conduct further analysis on any specific aspects of this data
DOI: 10.17632/8z6cr3sy9v.1
title: Analyzing the Randomness of the USEncryption Block Cipher

description: This repository contains the datasets generated and analysis code for the “Analyzing the Randomness of the USEncryption Block Cipher” study performed by USEncryption.

Testing the randomness of a block cipher is a key step for analyzing its overall security. This report provides a thorough analysis of randomness for the USEncryption block cipher using both the NIST and Dieharder statistical test suites. Our results show that continuous strings of random bits generated using this cipher with the recommended configuration in output feedback (OFB) mode indeed appear to be random and comparable to the randomness of the state-of-the-art 256-bit AES block cipher.

This new cipher is a critical building block to a pioneering Encrypted Operator Computing (EOC) method being developed by USEncryption to enable the processing of encrypted data. The main use case for this technology is the ability to share confidential data with privacy and security, allowing non-trusted parties to extract insights from the confidential encrypted data, without actually seeing the plaintext.
DOI: 10.17632/t2bdr663ms.2
title: QR-DN1.0: A new Distorted and Noisy QRs dataset

description: Barcodes are playing a significant role in different industries in the recent years and among the two most popular 2D barcodes, the QR code has grown exponentially. The QR-DN1.0 dataset includes 5 categories of QR codes that will cover low to high density levels. Each group has 15 QR codes: 5 images for testing and 10 images for training. After embedding the QRs into 30 color images using blind watermarking techniques and then extracting the QRs from the images taken with the mobile phone camera with three different methods, we will have three groups of 2250 extracted QR images, which provides a total of 6750 distorted and noisy QR images. In each of the mentioned three categories, the data is divided into two parts: testing, with 750 images, and training, with 2250 images. For every distorted QR in the dataset, a non-distorted instance of it is placed as a ground truth. One of the advantages of this data set is that it is real. Because no simulated noise has been added to the images and this dataset is completely derived from the real word challenge of extracting embedded QRs in color images captured from the watermarked image on the screen. It also includes various types of QRs such as single character, short sentence, long sentence, URL and location.
DOI: 10.17632/jhpkpm5gf8
title: Evaluating Bio-Based

description: This data focus on three promising adsorbent types—bio-based, nano-structured, and hybrid materials
DOI: 10.17632/x47k6prsv8.5
title: Dataset on potential risk factors to COVID19 disease among Health Workers in Kenya

description: Occupational characteristics, as well as personal and health systems characteristics of the health workers, were hypothesized to be associated with an increased risk of COVID-19 disease within the Kenyan tertiary-level hospital. Therefore, data collection was done using a researcher-administered and literature-based questionnaire via phone interviews on self-reported occupational and personal characteristics of health workers who worked in Kenyatta National Hospital between November 2021 to December 2021. The responses in the dataset therefore were treated as potential explanatory exposure variables for the study while the COVID-19 status was the study outcome. The participants consented to participation and their consent was documented before questionnaire administration. The collection of the data was approved by the Kenyatta National Hospital-University of Nairobi Ethics Review Committee(P462/06/2021), permission to conduct the study was also given by the administration of Kenyatta National Hospital and the study licence was also given by the National Commission For Science, Technology and Innovation for Kenya. The participants' identifier information was removed and de-identified, first, by anonymizing the questionnaire responses, second, the contact information database used during phone interviews was strictly kept confidential, restricted and password-protected and used for the purpose of this study only.
The dataset was then cleaned in Ms EXCEL to remove obvious errors and exported into R statistical software for analysis. Missingness of data was acknowledged prior to analysis. Aggregate variables of interest were derived based on the primary variables and multiple imputation of the dataset was applied to address missing data bias.
This data was analysed by regression methods and future researchers can apply similar methods to prove or disapprove their hypotheses based on the dataset.
DOI: 10.17632/76jwxm8c23.1
title: ED Visits at Mount Nittany 2018-2022

description: This data is all the alcohol-related ED visits at Mt Nittany medical center from 2018-2022
DOI: 10.17632/jbjzvmtfj8.3
title: Urban Heat Island Mitigation via Rooftop Garden - Sensor based data

description: 2 rooms of a Chennai, Tamil Nadu, India-based facility were fitted with sensors at the terrace and room level. One room's terrace had a roof garden, and the other was exposed. The dataset presents the details of the temperature and humidity recorded at 4 places (garden indoor, garden outdoor, exposed indoor and exposed outdoor).

Two sets of industry-grade temperature and humidity sensors were installed for data collection. These sensors included cased sensors for outdoor measurements and exposed sensors for internal regions. One set of sensors was placed in the baseline monitoring zone, which was the area without a garden, while the second set was installed in the green/heat mitigation monitoring zone, which 
was the area with the garden. 
The precise locations of the four installed sensors were as follows:
1. The external baseline sensor was positioned in the southwest corner of the terrace in the exposed portion.
2. The internal baseline sensor was mounted on the restroom ceiling, below the external sensor in the southwest corner.
3. The external sensor for measuring data from the green roof was installed among the planter bags, near the parapet wall.
4. A corresponding internal sensor to measure the impact of the green terrace was mounted on the ceiling of the storeroom directly below the planter bags.
In addition to the sensors, secondary weather data for the larger Otteri neighbourhood was sourced from weather online, AccuWeather and Visual Crossing to complement the study.
DOI: 10.17632/7bmfgkkm3z.3
title: CBCovid19EC: A dataset Complete Blood Count and PCR test for COVID-19 detection in Ecuadorian population

description: The data set presents information from PCR as a commonly used test for diagnosing SARS-Cov-2 infection by obtaining a positive or negative result for Covid-19. The CBCovid19EC dataset includes values from the hemogram examination, describing blood components measured in men and women from 7 to 82 years of age. The blood biometry tests were performed in private laboratories in Quito, with samples taken from patients from different provinces of Ecuador. The patients agreed to share their data by participating in this study. In total, 377 records included data on age, gender, and date of sample collection for PCR and CBC examination.
DOI: 10.17632/994kbk6c4z.1
title: Replication package for: Quid pro quo? Political ties and sovereign borrowing

description: The replication package contains publicly available data as well as the code required to replicate the results in "Quid pro quo? Political ties and sovereign borrowing." The replication package does not contain proprietary data that the user must obtain for themselves. Please see the README file.
DOI: 10.17632/bvcwx4tfjm.1
title: Mental health and well-being of university students during the fourth wave of the COVID-19 pandemic

description: The data include answers of 706 university students from Poland to demographic questions, mental and physical health, and well-being. The cross-sectional online survey was performed during the fourth wave of the COVID-19 pandemic, including measures of Exposure to Coronavirus (8 questions), Spirituality (2 questions), Physical Health (GSRH, 2-item), Perceived Stress (PSS-10), PTSD (Short PCL-6), anxiety (GAD-7), depression (PHQ-9), Life Satisfaction (SWLS), and Fear of COVID-19 (FoCV-19S). Differences between vaccinated and unvaccinated samples were investigated in the study using Pearson's Chi-square independence test, Student's t-test, and Mann-Whitney U-test. Also, network analysis was performed for unvaccinated and vaccinated university students, including selected demographic variables (age, gender, relationship status) and well-being dimensions. Overall, unvaccinated students showed better health and well-being than unvaccinated.
DOI: 10.17632/8ys8jssm9k.1
title: A dataset of dental periapical X-ray 

description: Please see the paper in Data in brief journal
DOI: 10.17632/srkp2j4v93.1
title: A Dataset for the Classification of Different Kurdish Dialects

description: Kurdish is an Indo-Iranian language that is largely spoken by people of Kurdish descent in the countries of Turkey, Iraq, Iran, and Syria. It contains a number of regional dialects, the most common of which is Northern Kurdish (also known as Kurmanji or Badini), while Central Kurdish (also known as Sorani) is spoken in some regions of Iraq and Iran. A unique Kurdish dialect, Hawrami, often referred to as Gorani, is the primary language spoken in the Hawraman area, which spans portions of western Iran and northeastern Iraq. Despite the fact that the dialects have separate pronunciations, vocabularies, and certain grammatical distinctions, they share a common core. In spite of the difficulties, the Kurdish language continues to be an essential component of Kurdish identity and cultural legacy. It plays an essential role in the protection and promotion of the distinct cultural identity of the Kurdish people.

The concepts of language and dialect recognition are intricately interconnected within the fields of linguistics and natural language processing. Having a good dataset for Kurdish dialect recognition improves identification and classification, natural language processing applications for Kurdish, preservation of Kurdish linguistic heritage, cultural insights, customized content and services for users, empowerment of local businesses, and a benchmark for evaluating dialect recognition systems.

The presented dataset was gathered by numerous members of the University of Halabja's Computer Science Department's teaching staff over the course of several months. During each stage of the data collecting process, the established policies, procedures, and guidelines were adhered to. This included taking into consideration the ages as well as the genders of the speakers who were included in the dataset.  The recordings are taken from a variety of TV programmes and TV interviews that were broadcast on Speda tv, NRT, and GK Sat. There were 2000 instances of the Sorani dialect, 2000 examples of the Badini dialect, and 2000 examples of the Hawrami language. The total duration of this dataset is 6000 s, and the duration of each sample is precisely one second.

The dataset labeling procedure that has been suggested consists of two consecutive stages. Initially, it is necessary to categorize the distinct sounds of each dialect, namely Sorani, Badini, and Hawrami, into different directories. Following this, it is recommended that the files included inside these folders be systematically labeled from 1 to 2000, according to the prescribed scheme: for Sorani files, the labels should range from s1 to s2000; for Badini files, the labels should range from b1 to b2000; and for Hawrami files, the labels should range from h1 to h2000.
DOI: 10.17632/2n8cbgvspy.2
title: Data of CNC Incorporation in PVA-reinforced Geopolymer Composites: Mechanical performance, Bending and Fractural Behavior, and Reaction Heat Release.

description: Cellulose nanocrystals (CNC) were incorporated in PVA-Reinforced geopolymer composites. This Data set presents the results of introducing different cellulose nanocrystals contents in PVA-Reinforced geopolymer composites.

Data is organized as the following:

1. Mechanical testing data:

1.1. Typical Stress vs. strain data for bending data

1.2. Stress vs. strain data for bending of MK-CNC-0 samples

1.3. Stress vs. strain data for bending of MK-PVA-CNC-0 samples

1.4. Stress vs. strain data for bending of MK-PVA-CNC-0.05 samples

1.5. Stress vs. strain data for bending of MK-PVA-CNC-0.1 samples

1.6. Stress vs. strain data for bending of MK-PVA-CNC-0.15 samples

1.7. Mechanical properties summary


2. Digital Image Correlation (DIC) videos

2.1. DIC videos for bending

2.2. DIC videos for fracture

3. Heat release data
DOI: 10.17632/bc7fksmv3z.1
title: Nutrient digestibility of poultry viscera, poultry by-product meal, and mealworms in female mink (Neovision vision) feed 

description: This research was originally conducted to meet the requirements of an undergraduate Honour’s Thesis by Kiran Fong in 2019 at Dalhousie University in the Faculty of Agriculture in the Department of Animal Science, Bible Hill, NS, Canada, titled, “Nutrient digestibility of poultry viscera, poultry by-product meal, and mealworms in female mink (Neovision vision) feed.” A manuscript for this research is currently under consideration by Animal - Open Space.

Abstract 
Increasing cost of feed ingredients is a growing challenge in the mink industry.  Determining nutrient digestibility can improve feed efficiency and decrease costs.  This study measured the digestibility of crude protein, crude fat, ash, and dry matter in three protein sources including poultry by-product meal (PBPM), poultry viscera, and crushed mealworms using diatomaceous earth as an indicator.  A control diet was made, and test diets were mixed in a 70:30 control diet:test ingredient ratio. Forty-six female mink housed in individual cages were fed experimental diets for five days, and fecal samples were collected and analyzed for nutrient residues compared to the diet composition to determine digestible nutrient levels.  Significant differences (P<0.05) were found among the diets and ingredients in dry matter and ash digestibility, and among diets in crude fat digestibility, but no difference was found in crude protein digestibility.  Overall, mealworms had the highest ash and dry matter digestibility (116.37% and 96.26%, respectively) compared to poultry viscera (1.04% and 77.29%, respectively) and PBPM (39.16% and 86.76%, respectively).  PBPM had a lower fat digestibility (84.64%) than mealworms (94.78%) or poultry viscera (98.15%).  The data generated provides nutritional information to assist in formulating any of the three ingredients into female mink diets as a protein source.
DOI: 10.17632/9dz247gnyb.4
title: Perceptual Voice Qualities Database (PVQD)

description: This database was created through generous funding from The Voice Foundation's Advancing Scientific Voice Research Grant and contains voice samples which have been rated by experienced voice professionals (at least 3 different raters with a minimum of 2 years’ clinical experience) in order to provide educators with standardized materials to better train pre-service clinical voice professionals. It contains 296 audio files consisting of the sustained /a/ and /i/ vowels and the sentences from the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V; Kempster, 2007). All recordings were made in a quiet clinical environment using a head-mounted condenser microphone at a 6-centimeter distance from the corner of the mouth and the Computerized Speech Lab (CSL) using 16-bit quantization and a sampling rate of 44.1k. Audio recordings have been edited as best as possible to remove all clinician instructions. However, please listen to and look at each file carefully just in case there was simultaneous clinician-client talk. 

Listeners rated approximately 50 files each and each file was rated twice for reliability measurement (for a total of approximately 100 ratings per rater). Raters used a computer to listen to the samples and rate voice quality via a web-based system that included custom-made electronic scales for the CAPE-V (Kempster, 2007) and the GRBAS (Hirano, 1981) using Qualtrics survey software. Listeners rated each file on a 100-point visual analogue scale (VAS) to mimic the paper-based CAPE-V protocol. Please note that severity markers (mild, moderate, severe) were not included on the 100-point VAS to avoid influencing the concurrent rating using the GRBAS scale. Raters were urged to rate the samples over several days to avoid fatigue. Further description of methods is located in the folders below.
Questions about the database can be directed to Patrick R. Walden, Ph.D., CCC-SLP at pwalden@monmouth.edu. Dr. Walden's affiliation is with Monmouth University in West Long Branch, NJ.

References:
Kempster G. CAPE-V: Development and Future Direction. Perspect Voice Voice Dis. 2007;17(2):11-13. doi:10.1044/vvd17.2.11

Hirano M. Clinical Examination of Voice. Springer-Verlag; 1981.
DOI: 10.17632/nk8k7b998x.2
title: The inter-municipal educational migration in Russia

description: The database was formed based on the results of a study aimed at regionalizing the Russia territory in terms of attraction to higher education centers based on the digital data using. The source of non–personalized data is 3.656 million user profiles of the VKontakte social network. This research was supported by a grant from the Russian Science Foundation No. 22-28-00766, https://rscf.ru/project/22-28-00766/
DOI: 10.17632/zm89rbf5xt
title: shurb encroachment Meta

description: Data on the influence of grassland shrub on microorganisms
DOI: 10.17632/smv6xzm5k4.1
title: Precipitation Data

description: Precipitation data, as used in the research titled Effect of Climate Change on Pre-Monsoon Severe Thunderstorms in Dhaka City
DOI: 10.17632/8kt969dhx6.2
title: Labeled Retinal Optical Coherence Tomography Dataset for Classification of Normal, Drusen, and CNV Cases

description: This dataset consists of more than 16,000 retinal OCT B-scans from 441 cases (Normal: 120, Drusen: 160, CNV: 161) and is acquired at Noor Eye Hospital, Tehran, Iran. Images are labeled by a retinal specialist. The structure of the folders are as below: - CNV, DRUSEN, NORMAL folders - Within each class, folders are separated patient-wise with numbers from 1 to . - Within each patient folder, images (B-scans) are labeled with &lt;0XX_LABEL&gt; format where is the B-scan number, and is the specialist's selected label for that specific B-scan. The excel spreadsheet (data_information.csv) includes information such as "Patient ID", "Class", "Eye", "B-scan", "Label", and "Directory" for all images (16823 rows, 6 columns). The python code (read_data.py) includes code for loading images and labels as NumPy arrays. The written function outputs the input data as an array with shape (number_of_images, imageSize, imageSize, 3) and output data as a list of labels (Normal: 0, Drusen: 1, CNV: 2). There are two different options for reading the files: - Option 1: Reading all images. This would result in 16822 images. - Option 2: Reading the worst-case condition images for each volume (i.e., if a patient was detected as a CNV case, only CNV-appearing B-scans were included for training procedure and normal and drusen B-scans of that patient are excluded from the dataset). This would result in 12649 images. ***************************************************************************************************************************************************** ***************************************************************************************************************************************************** If you utilize the dataset, kindly acknowledge and cite our work by referencing the following publication: Sotoudeh-Paima, S., Jodeiri, A., Hajizadeh, F., & Soltanian-Zadeh, H. (2022). Multi-scale convolutional neural network for automated AMD classification using retinal OCT images. Computers in biology and medicine, 144, 105368. The following repository contains implementation of the abovementioned publication: https://github.com/SamanSotoudeh/Multi-scale-convolutional-neural-network-for-automated-AMD-classification-using-retinal-OCT-images