cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/4t5vy62fm6.1
title: HFCHEBY2D13

description: A Fortran90 source code of Function HFCHEBY2D13 to calculate values of Ambartsumian-Chandrasekhar H-function for isotropic scattering with 13-digit accuracy for a given set of values for the single scattering albedo and the angular parameter mu. The formula implemented is based on numerical fittings by a bivariate Chebyshev polynomial to the values of this function calculated with 15-digit accuracy.
DOI: 10.17632/dgydz74s5w
title: Supplementary material - Value Added models in Ibero-American education: A systematic review

description: The file contains two tables. Table 1 shows the search strategies used in the ERIC, Scopus, and Web of Science databases. It includes the terms applied and the number of studies retrieved for each combination. Table 2 presents the main selected studies and provides information on the authors, year, journal, statistical model used, study location, and research objective. Together, these tables summarize the selection process and the main characteristics of the analyzed studies, offering an overview of value-added models in Ibero-American education.
DOI: 10.17632/dgydz74s5w.1
title: Supplementary material - Value Added models in Ibero-American education: A systematic review

description: The file contains two tables. Table 1 shows the search strategies used in the ERIC, Scopus, and Web of Science databases. It includes the terms applied and the number of studies retrieved for each combination. Table 2 presents the main selected studies and provides information on the authors, year, journal, statistical model used, study location, and research objective. Together, these tables summarize the selection process and the main characteristics of the analyzed studies, offering an overview of value-added models in Ibero-American education.
DOI: 10.17632/bk5mvn9v6v
title: Bay of Bengal Rain Plume

description: Python scripts
DOI: 10.17632/bk5mvn9v6v.1
title: Bay of Bengal Rain Plume

description: Python scripts
DOI: 10.17632/cfwcyf2g2y
title: Research Data

description: Research Data
DOI: 10.17632/cfwcyf2g2y.1
title: Research Data

description: Research Data
DOI: 10.17632/p37bpsm5cb
title: Green Fintech

description: Scopus database about green fintech
DOI: 10.17632/p37bpsm5cb.1
title: Green Fintech

description: Scopus database about green fintech
DOI: 10.17632/4795szkw6d
title: EVALUATION OF HEALTH-RELATED PHYSICAL FITNESS, DEPRESSION AND QUALITY OF SLEEP IN PERI AND POST MENOPAUSAL WOMEN – A PILOT ANALYTICAL DESCRIPTIVE STUDY

description: Menopause marks a crucial phase in every woman's life, signalling the natural end of reproductive years and bringing about significant hormonal changes. Perimenopausal and postmenopausal women often experience physiological and psychological changes due to these hormonal fluctuations, which can adversely affect Health-Related Physical Fitness (HRPF), sleep quality, and mental well-being—sometimes leading to issues like depression. This pilot analytical descriptive study was conducted to assess and compare Health-Related Physical Fitness (HRPF), sleep quality, and depressive symptoms in perimenopausal and postmenopausal women. A total of 50 women, aged 45–60 years, were enrolled and equally divided into two groups., Using standardized outcome tools—such as the 6-Minute Walk Test, Sit-and-Reach Test, Partial Curl-Up Test, Waist-Hip Ratio, Pittsburgh Sleep Quality Index (PSQI), and CES-D Depression Scale—the study revealed that perimenopausal women exhibited significantly better aerobic capacity compared to their postmenopausal counterparts (p = 0.02). However, other HRPF components like flexibility, muscular endurance, and waist-hip ratio, as well as anthropometric measures (BMI, height, and weight), did not show significant differences between the groups. Both groups demonstrated poor sleep quality and elevated depressive symptoms, with postmenopausal women trending toward worse outcomes, though these differences were not statistically significant.
These findings align with previous literature suggesting that the menopausal transition adversely affects cardiovascular endurance, sleep, and mental health. The study emphasizes the need for early, targeted interventions—including structured physical activity programs and mental health support—to maintain functional fitness and improve overall quality of life in menopausal women. Further research with larger, more diverse populations is recommended to better understand the interplay between menopause, physical health, and psychological well-being.
DOI: 10.17632/4795szkw6d.1
title: EVALUATION OF HEALTH-RELATED PHYSICAL FITNESS, DEPRESSION AND QUALITY OF SLEEP IN PERI AND POST MENOPAUSAL WOMEN – A PILOT ANALYTICAL DESCRIPTIVE STUDY

description: Menopause marks a crucial phase in every woman's life, signalling the natural end of reproductive years and bringing about significant hormonal changes. Perimenopausal and postmenopausal women often experience physiological and psychological changes due to these hormonal fluctuations, which can adversely affect Health-Related Physical Fitness (HRPF), sleep quality, and mental well-being—sometimes leading to issues like depression. This pilot analytical descriptive study was conducted to assess and compare Health-Related Physical Fitness (HRPF), sleep quality, and depressive symptoms in perimenopausal and postmenopausal women. A total of 50 women, aged 45–60 years, were enrolled and equally divided into two groups., Using standardized outcome tools—such as the 6-Minute Walk Test, Sit-and-Reach Test, Partial Curl-Up Test, Waist-Hip Ratio, Pittsburgh Sleep Quality Index (PSQI), and CES-D Depression Scale—the study revealed that perimenopausal women exhibited significantly better aerobic capacity compared to their postmenopausal counterparts (p = 0.02). However, other HRPF components like flexibility, muscular endurance, and waist-hip ratio, as well as anthropometric measures (BMI, height, and weight), did not show significant differences between the groups. Both groups demonstrated poor sleep quality and elevated depressive symptoms, with postmenopausal women trending toward worse outcomes, though these differences were not statistically significant.
These findings align with previous literature suggesting that the menopausal transition adversely affects cardiovascular endurance, sleep, and mental health. The study emphasizes the need for early, targeted interventions—including structured physical activity programs and mental health support—to maintain functional fitness and improve overall quality of life in menopausal women. Further research with larger, more diverse populations is recommended to better understand the interplay between menopause, physical health, and psychological well-being.
DOI: 10.17632/b4gd8g9yyt
title: Meteorological Measurements obtained during 2024 Texas Panhandle Wildfire

description: The WTM currently provides meteorological observations every one minute at 163 locations (i.e., WTM sites or stations) distributed primarily across West Texas (Fig. 1). The network provides real-time datasets including all standard meteorological parameters as well as radiation fields, rainfall, and leaf wetness and evapotranspiration. Agricultural data include soil temperature and moisture at different levels in both bare and covered soil. Additional details on the data infrastructure and instrument details can be found elsewhere [10] and at the WTM website (mesonet.ttu.edu).
DOI: 10.17632/b4gd8g9yyt.1
title: Meteorological Measurements obtained during 2024 Texas Panhandle Wildfire

description: The WTM currently provides meteorological observations every one minute at 163 locations (i.e., WTM sites or stations) distributed primarily across West Texas (Fig. 1). The network provides real-time datasets including all standard meteorological parameters as well as radiation fields, rainfall, and leaf wetness and evapotranspiration. Agricultural data include soil temperature and moisture at different levels in both bare and covered soil. Additional details on the data infrastructure and instrument details can be found elsewhere [10] and at the WTM website (mesonet.ttu.edu).
DOI: 10.17632/fdmj7kjwkv
title: Lidar data for 2024 Feb Texas Panhandle Wildfire Case

description: We deployed a ground-based scanning Doppler lidar (Halo Photonics Stream LineXR Scanning Doppler LiDAR system, TTU-DL) at Reese Laboratory. The lidar delivers three-dimensional wind and aerosol backscatter structures in pre-defined scanning regions (plane, vertical or volume scans) and via post-processing, aerosol variability, boundary layer dynamics and entrainment processes could be studied. 
The TTU-DL is a modular, autonomous, turn-key, pulsed Doppler lidar which make remote sensing of motion and backscatter in the atmosphere. In this mode of operation, naturally occurring aerosols and clouds act as a distributed target and backscatter the transmitted pulses. The receiver detects the Doppler shift brought about by the motion of the distributed targets and therefore the line-of-sight component of their velocity. The novel optical technology employed, and the design approach have led to a new class of eye-safe (Class 1M), high performance lidar exhibiting exceptional stability which is compatible with a continuous and unattended mode of operation.
In the archived files, we provided Doppler lidar data in netcdf format an a text file as a meta data to help guide the process of analyses.
DOI: 10.17632/fdmj7kjwkv.1
title: Lidar data for 2024 Feb Texas Panhandle Wildfire Case

description: We deployed a ground-based scanning Doppler lidar (Halo Photonics Stream LineXR Scanning Doppler LiDAR system, TTU-DL) at Reese Laboratory. The lidar delivers three-dimensional wind and aerosol backscatter structures in pre-defined scanning regions (plane, vertical or volume scans) and via post-processing, aerosol variability, boundary layer dynamics and entrainment processes could be studied. 
The TTU-DL is a modular, autonomous, turn-key, pulsed Doppler lidar which make remote sensing of motion and backscatter in the atmosphere. In this mode of operation, naturally occurring aerosols and clouds act as a distributed target and backscatter the transmitted pulses. The receiver detects the Doppler shift brought about by the motion of the distributed targets and therefore the line-of-sight component of their velocity. The novel optical technology employed, and the design approach have led to a new class of eye-safe (Class 1M), high performance lidar exhibiting exceptional stability which is compatible with a continuous and unattended mode of operation.
In the archived files, we provided Doppler lidar data in netcdf format an a text file as a meta data to help guide the process of analyses.
DOI: 10.17632/7mxzjmg6gn
title: The Relationship Between Menopausal Syndrome and Salivary Microbiome

description: Forty patients with diagnosed MPS were recruited from Jiangsu Provincial Hospital of Traditional Chinese Medicine, alongside 20 healthy perimenopausal controls enrolled through the physical examination center. All MPS participants fulfilled the clinical diagnostic criteria established by the Menopause Group of the Obstetrics and Gynecology Branch of the Chinese Medical Association through outpatient assessment. 
Participants of the MPS group were recruited according to the following inclusion criteria: (1) Fulfilled diagnostic criteria for MPS; (2) Females aged 45–55 years; (3) Modified Kupperman Menopausal Index (KMI) ≥15; (4) HFs with sweating ≥3 times/day; (5) FSH (Follicule-stimulating hormone) &gt;10 U/L during menopausal transition or &gt;40 U/L postmenopause; (6) Estradiol (E₂) &lt;10–20 pg/mL. Participants of the Healthy Control (HC) Group were recruited according to the following inclusion criteria: (1) Females aged 45–55 years; (2) KMI &lt;15 with absence of HFs; (3) FSH &gt;10 U/L during menopausal transition or &gt;40 U/L postmenopause; (4) Estradiol (E₂) &lt;10–20 pg/mL. Exclusion criteria of both groups were: (1) Use of hormonal contraceptives or menopausal hormone therapy within 3 months prior to enrollment; (2) Antibiotic exposure or probiotic/prebiotic supplementation within 2 weeks before screening; (3) Clinically significant psychological comorbidity, defined by Self-Rating Anxiety Scale (SAS) ≥50 or Self-Rating Depression Scale (SDS) ≥53; (4) Major systemic disorders including: uncompensated cardiovascular or cerebrovascular diseases, severe hepatic or renal dysfunction, endocrine disorders, hematologic abnormalities, active psychiatric conditions requiring treatment; (5) Oral pathologies: active infections (e.g., abscesses), premalignant lesions, or histologically confirmed malignancies; (6) Chronic heavy smoking (&gt;10 cigarettes/day for ≥5 years).
DOI: 10.17632/7mxzjmg6gn.1
title: The Relationship Between Menopausal Syndrome and Salivary Microbiome

description: Forty patients with diagnosed MPS were recruited from Jiangsu Provincial Hospital of Traditional Chinese Medicine, alongside 20 healthy perimenopausal controls enrolled through the physical examination center. All MPS participants fulfilled the clinical diagnostic criteria established by the Menopause Group of the Obstetrics and Gynecology Branch of the Chinese Medical Association through outpatient assessment. 
Participants of the MPS group were recruited according to the following inclusion criteria: (1) Fulfilled diagnostic criteria for MPS; (2) Females aged 45–55 years; (3) Modified Kupperman Menopausal Index (KMI) ≥15; (4) HFs with sweating ≥3 times/day; (5) FSH (Follicule-stimulating hormone) &gt;10 U/L during menopausal transition or &gt;40 U/L postmenopause; (6) Estradiol (E₂) &lt;10–20 pg/mL. Participants of the Healthy Control (HC) Group were recruited according to the following inclusion criteria: (1) Females aged 45–55 years; (2) KMI &lt;15 with absence of HFs; (3) FSH &gt;10 U/L during menopausal transition or &gt;40 U/L postmenopause; (4) Estradiol (E₂) &lt;10–20 pg/mL. Exclusion criteria of both groups were: (1) Use of hormonal contraceptives or menopausal hormone therapy within 3 months prior to enrollment; (2) Antibiotic exposure or probiotic/prebiotic supplementation within 2 weeks before screening; (3) Clinically significant psychological comorbidity, defined by Self-Rating Anxiety Scale (SAS) ≥50 or Self-Rating Depression Scale (SDS) ≥53; (4) Major systemic disorders including: uncompensated cardiovascular or cerebrovascular diseases, severe hepatic or renal dysfunction, endocrine disorders, hematologic abnormalities, active psychiatric conditions requiring treatment; (5) Oral pathologies: active infections (e.g., abscesses), premalignant lesions, or histologically confirmed malignancies; (6) Chronic heavy smoking (&gt;10 cigarettes/day for ≥5 years).
DOI: 10.34740/kaggle/dsv/12188955
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.17632/p58597ygp5
title: Annotated Uzbek Sentences Dataset for Binary Sentiment Classification

description: As part of this study we compiled the first open corpus of short Uzbek sentences annotated for binary sentiment classification.

Corpus size and composition
- 4 676 sentences in total: 3 042 — Positive, 1 634 — Negative.
- All texts are written in the modern Uzbek Latin alphabet and consist mainly of short everyday utterances (average length ≈ 6.0 tokens).

Raw class files: UZ_positive.txt and UZ_negative.txt (one sentence per line).

Upd (Version 2): Now it is available to download .csv format file, which has both negative and positive sentences and phrases.
DOI: 10.17632/p58597ygp5.2
title: Annotated Uzbek Sentences Dataset for Binary Sentiment Classification

description: As part of this study we compiled the first open corpus of short Uzbek sentences annotated for binary sentiment classification.

Corpus size and composition
- 4 676 sentences in total: 3 042 — Positive, 1 634 — Negative.
- All texts are written in the modern Uzbek Latin alphabet and consist mainly of short everyday utterances (average length ≈ 6.0 tokens).

Raw class files: UZ_positive.txt and UZ_negative.txt (one sentence per line).

Upd (Version 2): Now it is available to download .csv format file, which has both negative and positive sentences and phrases.
DOI: 10.17632/4277ghnwyz
title: Analysis Scripts and data for Dung beetle communities in Serengeti savannah

description: R script and data for analysis of dung beetle communities in relation to soil, habitat, and dung types
DOI: 10.15468/dl.69ekw4
title: Occurrence Download

description: A dataset containing 1104421 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Germany, Netherlands)",
 "TaxonKey is one of (Ondatra zibethicus (Linnaeus, 1766), Myocastor coypus (Molina, 1782))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1104421 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049670-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/4277ghnwyz.1
title: Analysis Scripts and data for Dung beetle communities in Serengeti savannah

description: R script and data for analysis of dung beetle communities in relation to soil, habitat, and dung types
DOI: 10.17632/n4j6f2jhmp
title: Vegetation zonation across elevational gradients considering lithological influence: A case study from the Qinling Mountains heartland, China

description: This study focuses on a forest farm located in the hinterland of the Qinling Mountains, China, as the research site. Through the investigation and sampling within quadrat at different elevations in different lithology of the forest farm, the quantity, height, diameter at breast height(DBH) and coverage of arbors and shrubs within quadrat and the bedrock structure development degree, slope body unit were statistically analyzed. Soil and weathered parent rock samples were collected sequentially along soil depth profile within quadrat. After indoor experimental tests, the growth characteristics of vegetation, as well as the variation laws of physical and chemical properties and nutrients of soil along soil depth profile at different elevations in different lithology were analyzed, to explore the correlations of the overlying vegetation and soil long-term regulated by the bedrock along elevation in different lithology of Qinling Mountains.
DOI: 10.17632/n4j6f2jhmp.1
title: Vegetation zonation across elevational gradients considering lithological influence: A case study from the Qinling Mountains heartland, China

description: This study focuses on a forest farm located in the hinterland of the Qinling Mountains, China, as the research site. Through the investigation and sampling within quadrat at different elevations in different lithology of the forest farm, the quantity, height, diameter at breast height(DBH) and coverage of arbors and shrubs within quadrat and the bedrock structure development degree, slope body unit were statistically analyzed. Soil and weathered parent rock samples were collected sequentially along soil depth profile within quadrat. After indoor experimental tests, the growth characteristics of vegetation, as well as the variation laws of physical and chemical properties and nutrients of soil along soil depth profile at different elevations in different lithology were analyzed, to explore the correlations of the overlying vegetation and soil long-term regulated by the bedrock along elevation in different lithology of Qinling Mountains.
DOI: 10.17632/mhy5vxnths
title: RAVI: Synthetic Urdu Text Image Dataset for OCR

description: The RAVI dataset is a synthetic image dataset designed to support the development and training of Urdu OCR (Optical Character Recognition) models. It consists of 99,000 high-resolution images (256x256 pixels), each containing a single Urdu word rendered in black text on a white background. The images are labeled with their corresponding Urdu words, enabling both supervised training and evaluation of word-level OCR systems. The text in the images is rendered using the “Jameel Noori Nastaleeq” font, a popular and widely used Nastaliq-style Urdu font, at font size 40.
The dataset is organized into subfolders corresponding to the Urdu alphabet, allowing for easier categorization, retrieval, and model evaluation based on character-specific performance.
This dataset is particularly valuable for researchers and developers working on CNN-based OCR systems, including both printed and future handwritten text recognition in Urdu. It can serve as a benchmark for word-level OCR models, sequence prediction architectures, and other deep learning applications in low-resource languages.

Key Features:
99,000 annotated images
Image resolution: 256x256 pixels
Black Urdu text on white background
Font: Jameel Noori Nastaleeq, size 40
Organized alphabetically by Urdu letters
Suitable for training, validation, and benchmarking of OCR systems
DOI: 10.17632/mhy5vxnths.1
title: RAVI: Synthetic Urdu Text Image Dataset for OCR

description: The RAVI dataset is a synthetic image dataset designed to support the development and training of Urdu OCR (Optical Character Recognition) models. It consists of 99,000 high-resolution images (256x256 pixels), each containing a single Urdu word rendered in black text on a white background. The images are labeled with their corresponding Urdu words, enabling both supervised training and evaluation of word-level OCR systems. The text in the images is rendered using the “Jameel Noori Nastaleeq” font, a popular and widely used Nastaliq-style Urdu font, at font size 40.
The dataset is organized into subfolders corresponding to the Urdu alphabet, allowing for easier categorization, retrieval, and model evaluation based on character-specific performance.
This dataset is particularly valuable for researchers and developers working on CNN-based OCR systems, including both printed and future handwritten text recognition in Urdu. It can serve as a benchmark for word-level OCR models, sequence prediction architectures, and other deep learning applications in low-resource languages.

Key Features:
99,000 annotated images
Image resolution: 256x256 pixels
Black Urdu text on white background
Font: Jameel Noori Nastaleeq, size 40
Organized alphabetically by Urdu letters
Suitable for training, validation, and benchmarking of OCR systems
DOI: 10.17632/khdg28v5d7
title: BD RiceSeed: A Multi-Class Image Dataset of Bangladeshi Rice Seed Varieties for Classification Tasks

description: The dataset was curated from rice seed samples collected across agricultural zones in Bangladesh and features eight distinct rice seed types. The dataset comprises high-resolution seed images categorized into eight varieties: 25, 28, 29, 89, 100, Chinigura, Kata Irri, and Kata Irri Vog. Each category contains 400 original images, each captured at a resolution of 1920 × 1080 pixels.

To enhance the dataset quality and ensure consistency, background removal preprocessing was performed on the original images, resulting in a refined set of seed images optimized for better feature extraction. This preprocessed dataset is stored separately under the "BGRemoved_Image" directory.

In order to mitigate class imbalance and strengthen model performance through diverse visual perspectives, data augmentation techniques were applied. These techniques produced 1,000 synthetic images per class, resulting in a balanced and enriched dataset totaling 8,000 images in the "Augmented_Image" directory.

The dataset is organized into three primary directories:

1) Rice_Image: Contains the original, unaltered images of eight rice seed varieties.
2) BGRemoved_Image: Includes preprocessed images with background removed to improve feature clarity.
3) Augmented_Image: Holds the balanced dataset created via augmentation, used for training and evaluation purposes.

This rice seed classification dataset provides a valuable resource for researchers in the fields of agricultural informatics, machine vision, and deep learning-based crop seed classification. It supports the advancement of AI-driven agricultural technologies for seed identification, classification, and quality assurance.