cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/vs24fkf9v3
title: Long-term survival after cryopreservation of the endangered exceptional species Crotalaria avonensis. Philpott et al., 2025.

description: Data for publication, "Long-term survival after cryopreservation of the endangered exceptional species Crotalaria avonensis". Data represents long- and short-term survival after cryopreservation for the endangered plant species, Crotalaria avonensis. This study presents an assessment of survival across three variations on the encapsulation vitrification method for 3 – 16 years of cryostorage for shoot tips of the federally endangered exceptional plant species, C. avonensis. In addition, the more recently-developed droplet vitrification method was compared to encapsulation vitrification for short-term survival. Overall, over 92% of banked genotypes survived after long-term cryo-storage, and the droplet vitrification method appears to improve survival over the original encapsulation vitrification procedures. In addition, the long-term survival data validate the previously published guidance that a 40% initial survival after liquid nitrogen exposure will lead to a 95% chance of survival after long-term storage, with 39% initial survival in C. avonensis leading to a 95% probability of survival after long-term storage per genotype. Initial survival after short-term liquid nitrogen exposure appears to be an indicator of long-term survival in storage, which can give practitioners some indication of their banking success.
DOI: 10.17632/vs24fkf9v3.1
title: Long-term survival after cryopreservation of the endangered exceptional species Crotalaria avonensis. Philpott et al., 2025.

description: Data for publication, "Long-term survival after cryopreservation of the endangered exceptional species Crotalaria avonensis". Data represents long- and short-term survival after cryopreservation for the endangered plant species, Crotalaria avonensis. This study presents an assessment of survival across three variations on the encapsulation vitrification method for 3 – 16 years of cryostorage for shoot tips of the federally endangered exceptional plant species, C. avonensis. In addition, the more recently-developed droplet vitrification method was compared to encapsulation vitrification for short-term survival. Overall, over 92% of banked genotypes survived after long-term cryo-storage, and the droplet vitrification method appears to improve survival over the original encapsulation vitrification procedures. In addition, the long-term survival data validate the previously published guidance that a 40% initial survival after liquid nitrogen exposure will lead to a 95% chance of survival after long-term storage, with 39% initial survival in C. avonensis leading to a 95% probability of survival after long-term storage per genotype. Initial survival after short-term liquid nitrogen exposure appears to be an indicator of long-term survival in storage, which can give practitioners some indication of their banking success.
DOI: 10.17632/788nx76nrp
title: TFG Bibliografía

description: Biblio
DOI: 10.17632/788nx76nrp.1
title: TFG Bibliografía

description: Biblio
DOI: 10.17632/db297ty35v.1
title: Additional supplementary data and method details for Wang, Kulkarni, Nong et al., Cell 2025

description: 1) WangOrigamiSequences.docx: Sequences for DNA origami tiles with azide terminated strands for conjugation to functional proteins.
2) Movie1.m4v: Scattering nanoparticle tracking analysis recording for liposomes in buffer.
3) Movie2.m4v: Fluorescence nanoparticle tracking analysis recording for liposomes in buffer, showing no background signal from liposomes.
4) Movie6.m4v: Fluorescence nanoparticle tracking analysis recording for plasma with fluorescent C3 and protein-liposomes with surface protein spacing = 25 nm. Corresponds to data in Fig. S4g-h in the paper.
5) Movie7.m4v: Fluorescence nanoparticle tracking analysis recording for plasma with fluorescent C3 and protein-liposomes with surface protein spacing = 29 nm. Corresponds to data in Fig. S4g-h in the paper.
6) Movie8.m4v: Fluorescence nanoparticle tracking analysis recording for plasma with fluorescent C3 and protein-liposomes with surface protein spacing = 36 nm. Corresponds to data in Fig. S4g-h in the paper.
7) Movie10.m4v: Fluorescence nanoparticle tracking analysis recording for plasma/gelatin veronal buffer with fluorescent C3 and protein-liposomes with surface protein spacing = 25 nm. Corresponds to data in Fig. 2h-i in the paper.
8) Movie11.m4v: Fluorescence nanoparticle tracking analysis recording for plasma/gelatin veronal buffer with fluorescent C3 and protein-liposomes with surface protein spacing = 29 nm. Corresponds to data in Fig. 2h-i in the paper.
9) Movie12.m4v: Fluorescence nanoparticle tracking analysis recording for plasma/gelatin veronal buffer with fluorescent C3 and protein-liposomes with surface protein spacing = 36 nm. Corresponds to data in Fig. 2h-i in the paper.
10) Movie14.m4v: Agent-based model of complement deposition on a sphere with surface protein spacing = 24 nm. Corresponds to data in Fig. 6 in the paper.
11) Movie15.m4v: Agent-based model of complement deposition on a sphere with surface protein spacing = 34 nm. Corresponds to data in Fig. 6 in the paper.
DOI: 10.17632/9675zcb38d.1
title: Revista Ciencias y Humanidades

description: The Revista Ciencias y Humanidades (ISSN 2500-784X) is a biannual online publication of the Centro de Estudios en Ciencias y Humanidades at the Corporación Educativa Jorge Robledo. Since 2015, it has promoted the publication of articles that disseminate the results of local and regional research, as well as reviews, essays, translations, and, in general, reflections on topics related to social and human sciences. 

In doing so, it seeks to contribute to the dissemination of knowledge that enables the understanding of various issues in Latin America and other parts of the world, fostering interdisciplinary dialogue and critical thinking. Moreover, it constitutes an open space for researchers, teachers, and students who wish to share their reflections and academic findings, strengthening scientific production and access to knowledge in multiple areas of study.
DOI: 10.17632/9ff5jzj94s.1
title: AI-Driven Plant Pathology with Multifaceted Snake Gourd Leaf Disease Dataset

description: 1. The Significance of Snake Gourd in Horticulture and Disease Challenges 
 In the horticulture sector, snake gourds are highly valued for their aesthetic appeal as well as their economic worth. However, a number of illnesses that can seriously impair plant health and productivity frequently make it difficult to cultivate these plants. To lessen these risks, leaf diseases must be identified promptly and accurately. The Snake Gourd Disease Dataset was created expressly to help horticulturists, researchers, and machine learning experts identify and categorize illnesses that impact snake gourd leaves in order to meet this demand. This dataset includes high-resolution photos of snake gourd leaves that show both disease-free and healthy specimens. Among the important illnesses mentioned are yellowing and anthracnose. Precise model training and validation are made possible by the thorough annotation of every image, which includes specifics about the nature and severity of the disease. The collection is further enhanced with metadata, which offers important background information about the locations and weather at the time of picture acquisition. Contextual information is essential for comprehending the variables influencing the occurrence of disease and improves the precision of prediction models.
2. The Role of Deep Learning and Computer Vision 
The Snake Gourd Disease Dataset has a plethora of opportunities for classification and detection tasks that can be addressed by modern deep learning and computer vision techniques.
3. A Comprehensive Dataset for Deep Learning in Snake Gourd Disease Classification
This dataset was created especially to aid in the creation of sophisticated deep learning models. To ensure accuracy and relevance, the dataset's classifications were developed in conjunction with subject matter specialists from a leading agricultural institute.
4. Data Collection and Augmentation
A total of five hundred photos were taken at the Savar demonstration location in Dhaka, Bangladesh. These photos included instances of yellowing, anthracnose, and healthy leaves. From the original collection of photos, 15,000 augmented images were created in order to improve the dataset and expand the amount of data points that were available. These augmented samples were made by applying several techniques like flipping, rotating, shearing, brightness modification, and magnification.
DOI: 10.17632/9ff5jzj94s.2
title: AI-Driven Plant Pathology with Multifaceted Snake Gourd Leaf Disease Dataset

description: 1. The Significance of Snake Gourd in Horticulture and Disease Challenges In the horticulture sector, snake gourds are highly valued for their aesthetic appeal as well as their economic worth. However, a number of illnesses that can seriously impair plant health and productivity frequently make it difficult to cultivate these plants. To lessen these risks, leaf diseases must be identified promptly and accurately. The Snake Gourd Disease Dataset was created expressly to help horticulturists, researchers, and machine learning experts identify and categorize illnesses that impact snake gourd leaves in order to meet this demand. This dataset includes high-resolution photos of snake gourd leaves that show both disease-free and healthy specimens. Among the important illnesses mentioned are yellowing and anthracnose. Precise model training and validation are made possible by the thorough annotation of every image, which includes specifics about the nature and severity of the disease. The collection is further enhanced with metadata, which offers important background information about the locations and weather at the time of picture acquisition. Contextual information is essential for comprehending the variables influencing the occurrence of disease and improves the precision of prediction models. 
2. The Role of Deep Learning and Computer Vision The Snake Gourd Disease Dataset has a plethora of opportunities for classification and detection tasks that can be addressed by modern deep learning and computer vision techniques. 
3. A Comprehensive Dataset for Deep Learning in Snake Gourd Disease Classification This dataset was created especially to aid in the creation of sophisticated deep learning models. To ensure accuracy and relevance, the dataset's classifications were developed in conjunction with subject matter specialists from a leading agricultural institute. 
4. Data Collection and Augmentation A total of 592 images were taken at the Savar demonstration location in Dhaka, Bangladesh. These photos included instances of yellowing, anthracnose, and healthy leaves. From the original collection of photos, 2,100 augmented images were created in order to improve the dataset and expand the amount of data points that were available. These augmented samples were made by applying several techniques like flipping, rotating, shearing, brightness modification, and magnification.
DOI: 10.17632/9ff5jzj94s.3
title: AI-Driven Plant Pathology with Multifaceted Snake Gourd Leaf Disease Dataset

description: 1. The Significance of Snake Gourd in Horticulture and Disease Challenges In the horticulture sector, snake gourds are highly valued for their aesthetic appeal as well as their economic worth. However, a number of illnesses that can seriously impair plant health and productivity frequently make it difficult to cultivate these plants. To lessen these risks, leaf diseases must be identified promptly and accurately. The Snake Gourd Disease Dataset was created expressly to help horticulturists, researchers, and machine learning experts identify and categorize illnesses that impact snake gourd leaves in order to meet this demand. This dataset includes high-resolution photos of snake gourd leaves that show both disease-free and healthy specimens. Among the important illnesses mentioned are yellowing and anthracnose. Precise model training and validation are made possible by the thorough annotation of every image, which includes specifics about the nature and severity of the disease. The collection is further enhanced with metadata, which offers important background information about the locations and weather at the time of picture acquisition. Contextual information is essential for comprehending the variables influencing the occurrence of disease and improves the precision of prediction models. 
2. The Role of Deep Learning and Computer Vision The Snake Gourd Disease Dataset has a plethora of opportunities for classification and detection tasks that can be addressed by modern deep learning and computer vision techniques. 
3. A Comprehensive Dataset for Deep Learning in Snake Gourd Disease Classification This dataset was created especially to aid in the creation of sophisticated deep learning models. To ensure accuracy and relevance, the dataset's classifications were developed in conjunction with subject matter specialists from a leading agricultural institute. 
4. Data Collection and Augmentation A total of 600 images were taken at the Savar demonstration location in Dhaka, Bangladesh. These photos included instances of yellowing, anthracnose, and healthy leaves. From the original collection of photos, 1800 augmented images were created in order to improve the dataset and expand the amount of data points that were available. These augmented samples were made by applying several techniques like flipping, rotating, shearing, brightness modification, and magnification.
DOI: 10.17632/2hcpwpntx7.1
title: Data and CTRW-PT code for Effects of Evolving Precipitation on Chemical Transport through Porous Media

description: Data and CTRW-PT code for Effects of Evolving Precipitation on Chemical Transport through Porous Media
DOI: 10.17632/5bnrpkwkx9.1
title: Antibody Worksheet & FASTA File

description: Use the Antibody Worksheet (Document S1) to document background information about the experiment (Tab 1), define the plate layout (Tab 1), specify exposure times for the respective fluorochromes (Tab 1), and list the antibodies used (Tab 2-5). Additionally, the Fasta file (Document S2) is for proteome data searches.
DOI: 10.17632/p8wkykmdnj
title: Raw data of results found in the artcle titled "The dietary phytocompounds carnosic acid and sulforaphane regulate inflammatory markers in ulcerative colitis patient-derived colonoids"

description: Absorbance, Cq, and densitometry data for Multiplex, ELISA, qPCR, and western blot experiments.
DOI: 10.17632/p8wkykmdnj.1
title: Raw data of results found in the artcle titled "The dietary phytocompounds carnosic acid and sulforaphane regulate inflammatory markers in ulcerative colitis patient-derived colonoids"

description: Absorbance, Cq, and densitometry data for Multiplex, ELISA, qPCR, and western blot experiments.
DOI: 10.17632/676thybbdh.1
title: A phytol εp-based core-top calibration to reconstruct past changes in atmospheric CO2

description: We investigated the relationship between photosynthetic fractionation (εp, calculated from the carbon isotopic composition of phytol (δ13C)) and dissolved CO2 concentrations (CO2 (aq)) using a globally distributed set of core top sediment and suspended particulate matter samples. The dataset here includes site locations, oceanographic variables, carbonate system parameters, δ13C, εp and CO2 (aq).
DOI: 10.17632/676thybbdh.2
title: A phytol εp-based core-top calibration to reconstruct past changes in atmospheric CO2

description: We investigated the relationship between photosynthetic fractionation (εp, calculated from the carbon isotopic composition of phytol (δ13C)) and dissolved CO2 concentrations (CO2 (aq)) using a globally distributed set of core top sediment and suspended particulate matter samples. The dataset here includes site locations, oceanographic variables, carbonate system parameters, δ13C, εp and CO2 (aq).
DOI: 10.17632/yv5fjdr3yn.1
title: Facebook comments about BRI

description: The data were collected using Fplus to scrape comments from Facebook posts about the Belt and Road Initiative (BRI) in Vietnam.
DOI: 10.17632/nb2hp99vxb.1
title: LINF_140010700

description: potassium channel; Leishmania infantum (strain JPCM5)
DOI: 10.17632/nb2hp99vxb.2
title: LINF_140010700

description: Potassium channel; Leishmania infantum (strain JPCM5)
DOI: 10.17632/9fy5k43fmm.1
title: Individualized Risk Prediction of Nodal Metastasis in cSCC_ A Systematic Review and Meta-Analysis of Prognostic Models

description: supplemental materials
DOI: 10.17632/gbkszkt8z3.1
title: ANCHOLIK-NER: A Benchmark Dataset for Bangla Regional Named Entity Recognition

description: We developed ANCHOLIK-NER, a Bangla Regional Named Entity Recognition dataset focusing on the Sylhet, Chittagong, and Barishal dialects. It comprises 10,443 sentences, evenly distributed across the three regions, with entities categorized into 10 types. The dataset, sourced from both formal (57.54%) and informal (42.46%) texts, enhances NER models by capturing regional linguistic nuances.
DOI: 10.17632/gbkszkt8z3.2
title: ANCHOLIK-NER: A Benchmark Dataset for Bangla Regional Named Entity Recognition

description: We developed ANCHOLIK-NER, a Bangla Regional Named Entity Recognition dataset focusing on the Sylhet, Chittagong, Barishal, Mymensingh, and Noakhali dialects. It comprises 17,405 sentences, evenly distributed across the five regions, with entities categorized into 10 types. The raw sentences were collected from two publicly available datasets and through web scraping from various online newspapers, articles.
DOI: 10.17632/gbkszkt8z3.3
title: ANCHOLIK-NER: A Benchmark Dataset for Bangla Regional Named Entity Recognition

description: We developed ANCHOLIK-NER, a Bangla Regional Named Entity Recognition dataset focusing on the Sylhet, Chittagong, Barishal, Mymensingh, and Noakhali dialects. It comprises 17,405 sentences, evenly distributed across the five regions, with entities categorized into 10 types. The raw sentences were collected from two publicly available datasets and through web scraping from various online newspapers, articles.
DOI: 10.17632/34d6kb4yc3.1
title: LINF_140006000

description: DnaJ domain-containing protein | JDP35 | J35 Leishmania infantum (strain JPCM5)
DOI: 10.17632/34d6kb4yc3.2
title: LINF_140006000

description: DnaJ domain-containing protein | JDP35 | J35; Leishmania infantum (strain JPCM5)
DOI: 10.17632/f9m6c45kb5.1
title: CAPTCHA_CHAOS_79 - A Dataset of 79 Stylized Characters Tailored for Secure CAPTCHA Applications

description: This dataset comprises a collection of approximately 9,000 high-resolution images representing 79 unique characters, including uppercase and lowercase alphabets (A–Z, a–z), numerical digits (0–9), and a variety of special symbols. Each character is rendered in multiple font styles, background textures, colors, and orientations, creating significant visual diversity and complexity. The dataset emphasizes variations in typography, contrast levels, noise patterns, and distortion effects, making it suitable for tasks involving character recognition, pattern analysis, and robustness testing against varied visual inputs. All images are uniformly labeled and categorized based on their respective character classes, ensuring ease of use for training and evaluation in machine learning workflows.
DOI: 10.17632/f9m6c45kb5.2
title: CAPTCHA_CHAOS_79 - A Dataset of 79 Stylized Characters Tailored for Secure CAPTCHA Applications

description: This dataset comprises a collection of approximately 9,000 high-resolution images representing 79 unique characters, including uppercase and lowercase alphabets (A–Z, a–z), numerical digits (0–9), and a variety of special symbols. Each character is rendered in multiple font styles, background textures, colors, and orientations, creating significant visual diversity and complexity. The dataset emphasizes variations in typography, contrast levels, noise patterns, and distortion effects, making it suitable for tasks involving character recognition, pattern analysis, and robustness testing against varied visual inputs. All images are uniformly labeled and categorized based on their respective character classes, ensuring ease of use for training and evaluation in machine learning workflows.
DOI: 10.17632/5vsz5s426g.1
title: CORRELATION OF CHANGES IN PHYSICAL ACTIVITY LEVELS ON PULMONARY FUNCTION AND QUALITY OF LIFE AMONG MIDDLE AGED ADULTS

description: 1.1 NEED OF THE STUDY

The need for this study arises from the limited understanding of how alterations in physical activity levels affect pulmonary health and overall well-being in the middle -age population. As middle age represents an important life stage where preventive health measures can significantly impact long term outcomes, identifying the relationships between physical activity, pulmonary function and quality of life becomes necessary. This research is significant for informing public health strategies and interventions aimed at promoting physical activity to enhance both pulmonary health and the overall quality of life among middle aged individuals.
 
1.2 AIMS AND OBJECTIVES

1.2.1 Aims of the Study

• To determine the correlation between changes in physical activity levels and pulmonary function among middle-aged adults.
• To assess the correlation between changes in physical activity levels and perceived quality of life among middle-aged adults.
1.2.2 Objectives of the Study

• To compare changes in physical activity levels among middle-aged adults sedentary to active or active to more active).
• Evaluate pulmonary function parameters and quality-of-life domains using standardized assessments.
• Analyze the correlation between physical activity changes on pulmonary function and quality of life.
DOI: 10.17632/67cw9gw7t3.1
title: LINF_140005300

description: j-binding protein | JBP2 Leishmania infantum (strain JPCM5)
DOI: 10.17632/67cw9gw7t3
title: LINF_140005300

description: Base J-binding protein 2 | JBP2; Leishmania infantum (strain JPCM5)
DOI: 10.17632/67cw9gw7t3.2
title: LINF_140005300

description: Base J-binding protein 2 | JBP2; Leishmania infantum (strain JPCM5)