cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dgs6y9yb5j.1
title: Optimizing Windbreak Geometry for Enhanced Wind Erosion Control using Machine Learning-Accelerated CFD

description: Abstract
Wind erosion is a major geophysical crisis, threatening global food security, ecological stability, and critical infrastructure. The crisis manifests as large-scale dust events and land degradation. While vegetation cover is the sustainable solution, severe drought often makes its establishment infeasible in arid regions. Consequently, engineered, non-living windbreaks remain a vital mitigation tool. Their performance critically relies on achieving a precise, optimized geometric design. This study introduces a fast and efficient computational framework for optimizing windbreak geometry to maximize the erosion-protected area. The method employs a hybrid approach, integrating Computational Fluid Dynamics (CFD) simulations to generate datasets with advanced Machine Learning (ML) models serving as high-fidelity surrogates. Among the tested models, the Random Forest (RF) model achieved the highest performance (R2 =0.98, MAE = 0.09), establishing it as a reliable surrogate for optimizing five key geometric parameters (porosity, shape, area, distribution, and angle). Subsequently, using the Random Forest (RF) model as a surrogate fitness function, the Genetic Algorithm (GA) identified the optimal geometry. This design characterized by 34.53% porosity, square pores (0.5 cm2), homogeneous distribution, and a porosity angle of 11.54֯, This optimized design resulted in a 22.78% increase in protection efficiency compared to non-porous barriers and achieved a 9.1% higher wind-proofing efficiency. This innovative approach offers a powerful, time-efficient tool for windbreak design, and may help to enhance ecological sustainability and protect soil resources from the impacts of climate change and drought.
Keywords: Wind erosion, Windbreak, Computational Fluid Dynamics (CFD), Machine Learning (ML), Optimization, Genetic Algorithm (GA)
DOI: 10.17632/dcpkzpcm63
title: Good and Bad classification of Radish

description: Title: Good and Bad Classification of Radish: Techniques, Parameters, and Perspectives .Radish is an edible root vegetable belonging to the family Brassicaceae. It is widely grown and consumed fresh in salads, curries, and pickles.🔹 Botanical name Raphanus sativus🔹 Parts eaten Mainly the root, sometimes the leaves as leafy vegetables🔹 Types White radish .
Red radish
Pink radish
Long and round varieties
🔹 Nutritional value (approx.)
High water content
Rich in vitamin C
Contains fiber, potassium, calcium
Very low in calories
🔹 Uses
Consumed raw (salads)
🔹 Quality characteristics
Firm texture
Smooth skin
Mild pungent taste
Free from cracks and discoloration
Radish (Raphanus sativus) – Nutritional Value
 Minerals
Calcium: 25 mg
Phosphorus: 20 mg
Potassium: 233 mg
Iron: 0.3 mg
Magnesium: 10 mg
Vitamins
Vitamin C: 14–15 mg
Standard Shelf Life of Radish (Mooli)
The shelf life of radish depends on storage condition and form:
At room temperature
1–3 days
Leaves wilt quickly, roots lose moisture
Refrigerated storage (0–4 °C, 90–95% RH)
2–3 weeks (without leaves)
7–10 days (with leaves)
Cold storage (commercial)
Temperature: 0 °C
Relative Humidity: 95–100%
Up to 3–4 weeks
Processed forms
Cut radish (refrigerated): 2–3 days
Pickled radish: Several months
Dehydrated radish: 6–12 months .
Sample Preparation of Radish
(Collected from Malda Rathabari )
🔹 Objective 
To prepare a representative radish sample collected from Rathabari Market, Malda for quality or laboratory analysis.
🔹 Sample Collection
Fresh radishes were randomly collected from different vendors at Rathabari MaldaWest Bengal latitude and longitude.
Diseased, damaged, or over-mature samples were avoided.
Samples were placed in clean polyethylene bags and transported to the laboratory.
Washing of Radish (Sample Preparation Step)
🔹 Objective
To remove soil, dust, pesticide residues, and microorganisms from radish before analysis or processing.
🔹 Procedure (Washing of Radish)
Pre-cleaning:
Remove adhering soil and mud by gentle shaking or brushing.
First washing:
Wash radish thoroughly under running potable water to remove visible dirt.
Final rinse:
Rinse again with clean potable or distilled water to remove chlorine residues.
Realme 7 – 
Camera
Rear Quad Camera System:
Main: 64 MP Sony sensor
Ultra wide: 8 MP, 119° field
B&W portrait lens
Macro lens
Camera features: Nightscape, Starry mode, Ultra wide/macros, portrait modes. 
Realme
Front Camera: 16 MP for selfies. 
Realme
 Battery & Charging
5000 mAh battery
Memory & Storage
Several options: 6 GB 
Storage: 64 GB 
For radish images:
Good radish images = 500
Bad radish images = 500
Total number of pictures = 1000 images
DOI: 10.17632/dcpkzpcm63.1
title: Good and Bad classification of Radish

description: Title: Good and Bad Classification of Radish: Techniques, Parameters, and Perspectives .Radish is an edible root vegetable belonging to the family Brassicaceae. It is widely grown and consumed fresh in salads, curries, and pickles.🔹 Botanical name Raphanus sativus🔹 Parts eaten Mainly the root, sometimes the leaves as leafy vegetables🔹 Types White radish .
Red radish
Pink radish
Long and round varieties
🔹 Nutritional value (approx.)
High water content
Rich in vitamin C
Contains fiber, potassium, calcium
Very low in calories
🔹 Uses
Consumed raw (salads)
🔹 Quality characteristics
Firm texture
Smooth skin
Mild pungent taste
Free from cracks and discoloration
Radish (Raphanus sativus) – Nutritional Value
 Minerals
Calcium: 25 mg
Phosphorus: 20 mg
Potassium: 233 mg
Iron: 0.3 mg
Magnesium: 10 mg
Vitamins
Vitamin C: 14–15 mg
Standard Shelf Life of Radish (Mooli)
The shelf life of radish depends on storage condition and form:
At room temperature
1–3 days
Leaves wilt quickly, roots lose moisture
Refrigerated storage (0–4 °C, 90–95% RH)
2–3 weeks (without leaves)
7–10 days (with leaves)
Cold storage (commercial)
Temperature: 0 °C
Relative Humidity: 95–100%
Up to 3–4 weeks
Processed forms
Cut radish (refrigerated): 2–3 days
Pickled radish: Several months
Dehydrated radish: 6–12 months .
Sample Preparation of Radish
(Collected from Malda Rathabari )
🔹 Objective 
To prepare a representative radish sample collected from Rathabari Market, Malda for quality or laboratory analysis.
🔹 Sample Collection
Fresh radishes were randomly collected from different vendors at Rathabari MaldaWest Bengal latitude and longitude.
Diseased, damaged, or over-mature samples were avoided.
Samples were placed in clean polyethylene bags and transported to the laboratory.
Washing of Radish (Sample Preparation Step)
🔹 Objective
To remove soil, dust, pesticide residues, and microorganisms from radish before analysis or processing.
🔹 Procedure (Washing of Radish)
Pre-cleaning:
Remove adhering soil and mud by gentle shaking or brushing.
First washing:
Wash radish thoroughly under running potable water to remove visible dirt.
Final rinse:
Rinse again with clean potable or distilled water to remove chlorine residues.
Realme 7 – 
Camera
Rear Quad Camera System:
Main: 64 MP Sony sensor
Ultra wide: 8 MP, 119° field
B&W portrait lens
Macro lens
Camera features: Nightscape, Starry mode, Ultra wide/macros, portrait modes. 
Realme
Front Camera: 16 MP for selfies. 
Realme
 Battery & Charging
5000 mAh battery
Memory & Storage
Several options: 6 GB 
Storage: 64 GB 
For radish images:
Good radish images = 500
Bad radish images = 500
Total number of pictures = 1000 images
DOI: 10.57903/uj/rpu7zi
title: Unsupervised detection of decoupled subspaces: many-body scars and beyond - replication data

description: This dataset includes the raw data (eigenvectors, eigenvalues, trained weights) and codes (PXP model, spin ladder model, CQVAE circuit training) to reproduce results from the article "Unsupervised detection of decoupled subspaces: Many-body scars and beyond".
DOI: 10.17632/jx6997f7w8
title: A Comprehensive Database of Phenolic Acids in Plant Foods: Soluble Free, Soluble Conjugated, and Insoluble-Bound Forms

description: We developed a database on the contents of soluble free, soluble conjugated and insoluble-bound forms of 8 individual phenolic acids across 322 plant foods and beverages.
DOI: 10.17632/jx6997f7w8.1
title: A Comprehensive Database of Phenolic Acids in Plant Foods: Soluble Free, Soluble Conjugated, and Insoluble-Bound Forms

description: We developed a database on the contents of soluble free, soluble conjugated and insoluble-bound forms of 8 individual phenolic acids across 322 plant foods and beverages.
DOI: 10.15468/dl.wgx583
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tylototriton broadoridgus"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068462-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gw2tcn8z55
title: Cement Composite Performance

description: The experiments have been performed to find Blaine’s Measurement (m2/kg), Soundness, LOI (wt %), Insoluble Residue (wt %), SO3 (wt %) and Initial Setting Time (min), Final Setting Time (min), 1 Day Strength (MPa), 3 Day Strength (MPa), 7 Day Strength (MPa), 28 Day Strength (MPa) for cement
DOI: 10.17632/gw2tcn8z55.1
title: Cement Composite Performance

description: The experiments have been performed to find Blaine’s Measurement (m2/kg), Soundness, LOI (wt %), Insoluble Residue (wt %), SO3 (wt %) and Initial Setting Time (min), Final Setting Time (min), 1 Day Strength (MPa), 3 Day Strength (MPa), 7 Day Strength (MPa), 28 Day Strength (MPa) for cement
DOI: 10.15468/dl.x6zujf
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Parashorea chinensis"
 ]
}

 The dataset includes 25 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068463-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/c73fzwyhjw
title: Gifted_Adults_Data

description: Data of gifted and non gifted adults - attitude to work and organizational behavior
DOI: 10.17632/c73fzwyhjw.1
title: Gifted_Adults_Data

description: Data of gifted and non gifted adults - attitude to work and organizational behavior
DOI: 10.17632/5frp348b7s
title: Firms under fire ! How insecurity affects formal firms' existence

description: Replication package of the paper: Firms under fire ! How insecurity affects formal firms' existence
DOI: 10.17632/5frp348b7s.2
title: Firms under fire ! How insecurity affects formal firms' existence

description: Replication package of the paper: Firms under fire ! How insecurity affects formal firms' existence
DOI: 10.57903/uj/yxri0w
title: Postcolonial feminism and auteur theory in video games - the case of Muriel Tramis - replication data
title: English

description: The data collected while working on the project, including the table of examined games and screenshots from the selected titles.
DOI: 10.17632/hvwth9dsfd
title: CocoaSwolSet

description: This dataset is part of the Deep Farm project (https://deepfarm.eu/), funded by the European Union's ERASMUS program, which aims to bridge the skills gap and build the capacity of students and teachers in digital agriculture through the use of Artificial Intelligence (AI), Big Data, and the Internet of Things (IoT). One of the pilot projects is Deep Cacao, led in Côte d'Ivoire by ESATIC and INPHB.
This project involves implementing an AI model based on neural networks to detect and prevent Swollen Shoot disease, one of the greatest threats to cocoa cultivation in Côte d'Ivoire, as early as possible. To this end, our team has been working on setting up the CocoaSwolSet dataset. 
CocoaSwolSet is a dataset of images of cocoa leaves, pods, and stems. This dataset is intended to feed AI models for the early detection of one of the most devastating diseases affecting cocoa, namely Swollen Shoot Disease. It therefore consists of images of healthy cocoa plants (currently approximately 1,500 images) and images of diseased cocoa plants (currently approximately 1,000 images). The CocoaSwolSet folder contains three subfolders: "Leaves," "Stems," and "Pods." With the exception of the Leaves subfolder, the other two folders contain "Healthy" and "Diseased" folders. For the Leaves subfolder, we have the Young and Adult folders, which contain the Healthy and Diseased folders. It should be noted that this dataset will be constantly updated as we continue to collect images of different plants. However, at this stage, we can train initial AI models for the detection of swollen shoot disease. This dataset is one of the first datasets on swollen shoot disease and is a valuable resource for training AI models in the classification or detection of the disease.
DOI: 10.17632/hvwth9dsfd.2
title: CocoaSwolSet

description: This dataset is part of the Deep Farm project (https://deepfarm.eu/), funded by the European Union's ERASMUS program, which aims to bridge the skills gap and build the capacity of students and teachers in digital agriculture through the use of Artificial Intelligence (AI), Big Data, and the Internet of Things (IoT). One of the pilot projects is Deep Cacao, led in Côte d'Ivoire by ESATIC and INPHB.
This project involves implementing an AI model based on neural networks to detect and prevent Swollen Shoot disease, one of the greatest threats to cocoa cultivation in Côte d'Ivoire, as early as possible. To this end, our team has been working on setting up the CocoaSwolSet dataset. 
CocoaSwolSet is a dataset of images of cocoa leaves, pods, and stems. This dataset is intended to feed AI models for the early detection of one of the most devastating diseases affecting cocoa, namely Swollen Shoot Disease. It therefore consists of images of healthy cocoa plants (currently approximately 1,500 images) and images of diseased cocoa plants (currently approximately 1,000 images). The CocoaSwolSet folder contains three subfolders: "Leaves," "Stems," and "Pods." With the exception of the Leaves subfolder, the other two folders contain "Healthy" and "Diseased" folders. For the Leaves subfolder, we have the Young and Adult folders, which contain the Healthy and Diseased folders. It should be noted that this dataset will be constantly updated as we continue to collect images of different plants. However, at this stage, we can train initial AI models for the detection of swollen shoot disease. This dataset is one of the first datasets on swollen shoot disease and is a valuable resource for training AI models in the classification or detection of the disease.
DOI: 10.34740/kaggle/dsv/14331638
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.17632/hvfc7zmf8x
title: Combined Cranberry Proanthocyanidins and Organic Acids Attenuate Urinary Tract Infection via EGFR/PI3K/Akt Pathway Modulation

description: The original dataset of the article titled 'Cranberry Proanthocyanidins Combined with Organic Acids Alleviate Urinary Tract Infections by Regulating the EGFR/PI3K/Akt Pathway'
DOI: 10.17632/hvfc7zmf8x.1
title: Combined Cranberry Proanthocyanidins and Organic Acids Attenuate Urinary Tract Infection via EGFR/PI3K/Akt Pathway Modulation

description: The original dataset of the article titled 'Cranberry Proanthocyanidins Combined with Organic Acids Alleviate Urinary Tract Infections by Regulating the EGFR/PI3K/Akt Pathway'
DOI: 10.17632/v9m57ydj64
title: Alopecia in Hijab-Wearing Patients: A Systematic Review

description: Supplementary Material for Alopecia in Hijab-Wearing Patients: A Systematic Review
DOI: 10.17632/v9m57ydj64.2
title: Alopecia in Hijab-Wearing Patients: A Systematic Review

description: Supplementary Material for Alopecia in Hijab-Wearing Patients: A Systematic Review
DOI: 10.17632/3427x3wzzc
title: Human renal clearance of xenobiotics

description: Dataset contains human renal clearance values of exogenous substances. The final set contains over 1,700 experimental observations from 761 scientific articles and covers over 500 unique substances studied. The main source of the data were publicly available scientific articles.
DOI: 10.17632/3427x3wzzc.2
title: Human renal clearance of xenobiotics

description: Dataset contains human renal clearance values of exogenous substances. The final set contains over 1,700 experimental observations from 761 scientific articles and covers over 500 unique substances studied. The main source of the data were publicly available scientific articles.
DOI: 10.15468/9d2n9m
title: A long history in a short note-identity and typification of the name Hippion obtusifolium F. W. Schmidt, and synonymy of the species Gentianella obtusifolia (Gentianaceae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Reich, Dieter, Mráz, Patrik, Šída, Otakar, Gutermann, Walter (2023): A long history in a short note-identity and typification of the name Hippion obtusifolium F. W. Schmidt, and synonymy of the species Gentianella obtusifolia (Gentianaceae). Phytotaxa 598 (2): 157-166, DOI: 10.11646/phytotaxa.598.2.5, URL: http://dx.doi.org/10.11646/phytotaxa.598.2.5AbstractThe description of Hippion obtusifolium F.W. Schmidt was followed by more than 200 years of confusion concerning the identity of this taxon, the origin of the material it is based on, and its typification. Hereby, we briefly summarize this historical development, clarify the typification and the identity of the taxon currently known as Gentianella obtusifolia and designate an epitype to stabilize the application of the name having priority over G. aspera. Additionally, the morphological characterization and geographic distribution of the taxon are discussed and an exhaustive synonymy is provided.
DOI: 10.15468/dl.2ad3ak
title: Occurrence Download

description: A dataset containing 367 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Dipterocarpus turbinatus"
 ]
}

 The dataset includes 367 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068465-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18085583
title: citharinus_macrolepis_spades_01.fasta.gz
DOI: 10.5281/zenodo.18085584
title: citharinus_macrolepis_spades_01.fasta.gz
DOI: 10.15468/dl.3xmmme
title: Occurrence Download

description: A dataset containing 21851 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Switzerland",
 "OccurrenceStatus is Present",
 "PublishingOrg is 64ee55c9-570a-42af-b7da-3f13c6b4e5a9",
 "TaxonKey is Vespa"
 ]
}

 The dataset includes 21851 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068466-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/562ssy62mv
title: N2O concentration in the Tropical Western North Pacific Ocean

description: ● N2O concentration in the Tropical Western North Pacific Ocean 
● 12.5°N~20.5°N, 126.5°E~133.5°E, depth (0~1000m)
● Sampling date : 2023.09.26.~2023.10.10. 
● Equipment name: CRDS(Cavity Ring-Down Spectroscopy)
DOI: 10.17632/562ssy62mv.1
title: N2O concentration in the Tropical Western North Pacific Ocean

description: ● N2O concentration in the Tropical Western North Pacific Ocean 
● 12.5°N~20.5°N, 126.5°E~133.5°E, depth (0~1000m)
● Sampling date : 2023.09.26.~2023.10.10. 
● Equipment name: CRDS(Cavity Ring-Down Spectroscopy)
DOI: 10.17632/3s44yzbxxg
title: Soil Cr

description: A total of 368 topsoil samples (0–20 cm) were collected using a grid-sampling design in Shazi Town (193 km²), Guangxi Zhuang Autonomous Region, Southwest China.
DOI: 10.17632/3s44yzbxxg.1
title: Soil Cr

description: A total of 368 topsoil samples (0–20 cm) were collected using a grid-sampling design in Shazi Town (193 km²), Guangxi Zhuang Autonomous Region, Southwest China.
DOI: 10.17632/kzytwn7n6d.3
title: R Code for the Analysis of Late-night Eating Behaviors and Depressive Symptoms in U.S. Adults (NHANES 2007–2018)

description: The R scripts included in this dataset perform the following tasks:

• Data cleaning and merging across multiple NHANES cycles
• Construction of nighttime energy and macronutrient variables
• Categorization of nighttime intake levels (e.g., none, moderate, high)
• Survey-weighted logistic regression models
• Subgroup and sensitivity analyses
• Data-driven clustering of nighttime macronutrient composition patterns
• Visualization of results, including forest plots and pattern comparisons
DOI: 10.17632/sp62k69ydp
title: Major, Trace , and Rare earth element concentrations of aeolian sediments from the Kumkol Desert and fluvial deposits from the Arca and Qimantag Mountains

description: Dune samples from the Kumkol Desert and riverbed samples from the Arca and Qimantag Mountains were collected, and we obtained the minimum, maximum, and average values of major, trace, and rare earth elements for these three regions. This data has significant application value for interpreting the provenance of the Kumkol Desert on the Qinghai-Tibet Plateau in China.
DOI: 10.17632/sp62k69ydp.1
title: Major, Trace , and Rare earth element concentrations of aeolian sediments from the Kumkol Desert and fluvial deposits from the Arca and Qimantag Mountains

description: Dune samples from the Kumkol Desert and riverbed samples from the Arca and Qimantag Mountains were collected, and we obtained the minimum, maximum, and average values of major, trace, and rare earth elements for these three regions. This data has significant application value for interpreting the provenance of the Kumkol Desert on the Qinghai-Tibet Plateau in China.
DOI: 10.5281/zenodo.18085460
title: GEMSTONE Research Data: EEG Recordings from Chemogenetic Applications on GAERS

description: This file includes Labchart EEG images acquired and corresponding standard operating procedures used during the chemogenetic applications on the Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model conducted within the scope of the GEMSTONE Project.
DOI: 10.5281/zenodo.18085459
title: GEMSTONE Research Data: EEG Recordings from Chemogenetic Applications on GAERS

description: This file includes Labchart EEG images acquired and corresponding standard operating procedures used during the chemogenetic applications on the Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model conducted within the scope of the GEMSTONE Project.
DOI: 10.57903/uj/rh0j5l
title: Microbiota and gut inflammation - Stay in or leave? Immune adaptation upon stress: evolutionary conserved mechanisms of neutrophil redistribution

description: Raw data - Microbiome and gut inflammation - OPUS 17 project: Stay in or leave? Immune adaptation upon stress: evolutionary conserved mechanisms of neutrophil redistribution.
DOI: 10.17632/n6bdf8t784
title: Data from: Post-marketing surveillance of the safety and effectiveness of metreleptin in patients with lipodystrophy in Japan

description: Supplementary appendix for
Title: Post-marketing surveillance of the safety and effectiveness of metreleptin in patients with lipodystrophy in Japan
Ken Ebihara 1, Tomohisa Hata 2, Yumi Sato 3, and Makiko Miyano4
Affiliations:
1. Division of Endocrinology and Metabolism, Department of Internal Medicine, Jichi Medical University, Tochigi, Japan
2. Pharmacovigilance Department, Shionogi & Co., Ltd., Osaka, Japan
3. Medical Affairs Department, Shionogi & Co., Ltd., Osaka, Japan
4. Pharmacovigilance Division, Shionogi Business Partner Co., Ltd., Osaka, Japan
Correspondence to:
Name: Ken Ebihara