cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/vw2tdrn24b
title: Digital Microscope Supplemental Figures 1-5

description: Supplemental Figure 1: Portable Handheld Mini Microscope (US$20, Ashfly, Amazon.com). Unlike older USB-connected models, a built-in screen and memory allow easy lesion evaluation and image capture. Describing lesion characteristics to learners may be easier than with conventional dermatoscopes. 

Supplemental Figure 2: Palmar nevus. 1mm in diameter, visualized by polarized dermoscopy (A) and by digital microscopy (B). Dermoscopy image (A) was captured via DE-400 Dermatoscope (Shenzhen Iboolo Optics Co., Shenzhen, China) and cropped with zoom to improve comparison. Digital microscopy image (B) was captured via Portable Handheld Mini Microscope (US$20, Ashfly, Amazon.com) and cropped without zoom. Pigment pattern is visualized in both images with pigment sparing the ridges that have eccrine gland openings, indicating a benign feature. 

Supplemental Figure 3: Cherry angioma. 1mm in diameter, visualized by polarized dermoscopy (A) and by digital microscopy (B) (US$20, Ashfly, Amazon.com). Dermoscopy image (A) was cropped with zoom to improve comparison. Digital microscopy image (B) was cropped without zoom. Vessel lacunae are visualized in both images. 

Supplemental Figure 4: Handheld digital microscope (US$30, NUOTON ABS-506A, Amazon.com). This model features an adjustable focusing dial in addition to built-in screen and memory. Adjustable focus can accommodate variable distances in concave or convex body surfaces. Polarizing filters for light sources and cameras can be cut to size and oriented to show cross-polarization (overlapping dark region) (B). A set of polarizing filters can be placed in the barrel of the camera to approximate polarized dermoscopy (C).

Supplemental Figure 5: Forearm nevus. 2mm in diameter, visualized by digital microscopy alone (A) and by digital microscopy with diascopy (B). Surface scale is removed, and superficial structures are enhanced. Images were captured with NUOTON ABS-506A digital microscope.
DOI: 10.17632/vw2tdrn24b.1
title: Digital Microscope Supplemental Figures 1-5

description: Supplemental Figure 1: Portable Handheld Mini Microscope (US$20, Ashfly, Amazon.com). Unlike older USB-connected models, a built-in screen and memory allow easy lesion evaluation and image capture. Describing lesion characteristics to learners may be easier than with conventional dermatoscopes. 

Supplemental Figure 2: Palmar nevus. 1mm in diameter, visualized by polarized dermoscopy (A) and by digital microscopy (B). Dermoscopy image (A) was captured via DE-400 Dermatoscope (Shenzhen Iboolo Optics Co., Shenzhen, China) and cropped with zoom to improve comparison. Digital microscopy image (B) was captured via Portable Handheld Mini Microscope (US$20, Ashfly, Amazon.com) and cropped without zoom. Pigment pattern is visualized in both images with pigment sparing the ridges that have eccrine gland openings, indicating a benign feature. 

Supplemental Figure 3: Cherry angioma. 1mm in diameter, visualized by polarized dermoscopy (A) and by digital microscopy (B) (US$20, Ashfly, Amazon.com). Dermoscopy image (A) was cropped with zoom to improve comparison. Digital microscopy image (B) was cropped without zoom. Vessel lacunae are visualized in both images. 

Supplemental Figure 4: Handheld digital microscope (US$30, NUOTON ABS-506A, Amazon.com). This model features an adjustable focusing dial in addition to built-in screen and memory. Adjustable focus can accommodate variable distances in concave or convex body surfaces. Polarizing filters for light sources and cameras can be cut to size and oriented to show cross-polarization (overlapping dark region) (B). A set of polarizing filters can be placed in the barrel of the camera to approximate polarized dermoscopy (C).

Supplemental Figure 5: Forearm nevus. 2mm in diameter, visualized by digital microscopy alone (A) and by digital microscopy with diascopy (B). Surface scale is removed, and superficial structures are enhanced. Images were captured with NUOTON ABS-506A digital microscope.
DOI: 10.5281/zenodo.18247905
title: Baccharis stenocephala Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.5281/zenodo.18247906
title: Baccharis stenocephala Baker. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/hpffm3tct5
title: Patterns of Egg Laying, Overwintering Survival, and Spring Hatch in the Green Apple Aphid (Aphis pomi De Geer) on Apple Trees

description: The overwintering biology of the green apple aphid (Aphis pomi De Geer) was examined over two years to quantify oviposition schedule, egg dispersion, survival, and hatch dynamics. Oviposition started from October, spanned 11–12 weeks peaking between late October and mid-November, with cumulative green eggs per shoot (30 cm long) averaging 385 in 2022 and 462 in 2023. Eggs were most concentrated on the second to fifth 10-cm shoot segments, and the gradient became less steep towards the termination of oviposition. Survival varied markedly among treatments: laboratory-stored shoots retained 63.6% egg viability, intact shoots 42.6–49.6%, and ground-excised shoots only 23.9–33.4%. Kaplan–Meier analysis showed a 73% higher hazard of egg mortality on ground shoots compared to intact shoots. Spring hatch commenced in early March and reached 100% by early April, with median hatch dates clustering around March 20–21. Cumulative egg hatch was found as more sensitive parameter for analysis of various effects. These results establish detailed phenological benchmarks and demonstrate that oviposition precision and overwintering success are strongly shaped by microhabitat and possibly plant status. The study represents the first comprehensive, data-driven investigation of this scale, providing robust parameters for temperature-driven forecasting models and informing integrated pest management strategies aimed at reducing early-season aphid establishment in apple orchards.
DOI: 10.17632/hpffm3tct5.1
title: Patterns of Egg Laying, Overwintering Survival, and Spring Hatch in the Green Apple Aphid (Aphis pomi De Geer) on Apple Trees

description: The overwintering biology of the green apple aphid (Aphis pomi De Geer) was examined over two years to quantify oviposition schedule, egg dispersion, survival, and hatch dynamics. Oviposition started from October, spanned 11–12 weeks peaking between late October and mid-November, with cumulative green eggs per shoot (30 cm long) averaging 385 in 2022 and 462 in 2023. Eggs were most concentrated on the second to fifth 10-cm shoot segments, and the gradient became less steep towards the termination of oviposition. Survival varied markedly among treatments: laboratory-stored shoots retained 63.6% egg viability, intact shoots 42.6–49.6%, and ground-excised shoots only 23.9–33.4%. Kaplan–Meier analysis showed a 73% higher hazard of egg mortality on ground shoots compared to intact shoots. Spring hatch commenced in early March and reached 100% by early April, with median hatch dates clustering around March 20–21. Cumulative egg hatch was found as more sensitive parameter for analysis of various effects. These results establish detailed phenological benchmarks and demonstrate that oviposition precision and overwintering success are strongly shaped by microhabitat and possibly plant status. The study represents the first comprehensive, data-driven investigation of this scale, providing robust parameters for temperature-driven forecasting models and informing integrated pest management strategies aimed at reducing early-season aphid establishment in apple orchards.
DOI: 10.18738/t8/eb4u0r
title: Bridging Language and Data: Transforming Agricultural Curricula for Data Analytics Through Linguistic Insights

description: Bridging Language and Data: Transforming Agricultural Curricula for Data Analytics Through Linguistic Insights
DOI: 10.17632/9cm9h5mv3y
title: Deposit-resolved Taguchi design, kinetics, and spectroscopy datasets for fulvic-acid recovery from coal gangue via H₂O₂ oxidation

description: This dataset contains the experimental design matrix, replicate fulvic-acid (FA) yields, kinetic time-series tables, Arrhenius-derived temperature dependence, and supporting characterization summaries for deposit-resolved FA recovery from four coal-gangue sources (GLC, NEC, SGC, SMC) using single-oxidant H₂O₂ oxidation. The study compares deposit-specific oxidation windows using a Taguchi L9(3⁴) orthogonal design with confirmation runs, links yield to acidity and surface functionalization, and reports pseudo-first-order kinetic parameters and apparent activation energies across 40–80 °C. The files enable independent verification of yield optima (including the order-of-magnitude yield contrast across deposits), reproduction of kinetic/Arrhenius calculations, and reuse of derived structural indices (fluorescence, UV–vis, XPS C1s fractions) for meta-analysis and process–structure modeling. 

This dataset contains design matrices/yield tables, kinetics/Arrhenius tables (where provided), response-surface modeling outputs (coefficients, diagnostics, OriginPro NLFit reports/templates), and supporting documentation used in a coal-gangue → fulvic-acid (FA) recovery study based on single-oxidant H₂O₂ oxidation. Files are organized into data and report folders for direct reuse and verification of modeling/optimization steps.
DOI: 10.17632/9cm9h5mv3y.1
title: Deposit-resolved Taguchi design, kinetics, and spectroscopy datasets for fulvic-acid recovery from coal gangue via H₂O₂ oxidation

description: This dataset contains the experimental design matrix, replicate fulvic-acid (FA) yields, kinetic time-series tables, Arrhenius-derived temperature dependence, and supporting characterization summaries for deposit-resolved FA recovery from four coal-gangue sources (GLC, NEC, SGC, SMC) using single-oxidant H₂O₂ oxidation. The study compares deposit-specific oxidation windows using a Taguchi L9(3⁴) orthogonal design with confirmation runs, links yield to acidity and surface functionalization, and reports pseudo-first-order kinetic parameters and apparent activation energies across 40–80 °C. The files enable independent verification of yield optima (including the order-of-magnitude yield contrast across deposits), reproduction of kinetic/Arrhenius calculations, and reuse of derived structural indices (fluorescence, UV–vis, XPS C1s fractions) for meta-analysis and process–structure modeling. 

This dataset contains design matrices/yield tables, kinetics/Arrhenius tables (where provided), response-surface modeling outputs (coefficients, diagnostics, OriginPro NLFit reports/templates), and supporting documentation used in a coal-gangue → fulvic-acid (FA) recovery study based on single-oxidant H₂O₂ oxidation. Files are organized into data and report folders for direct reuse and verification of modeling/optimization steps.
DOI: 10.17632/r2dmj96stf
title: Adaptive capacity of peasant communities in Brazil: enhanced by financial and natural capitals, constrained by historical power dynamics

description: This dataset contains all data used for the analyses presented in "Adaptive capacity of peasant communities in Brazil: enhanced by financial and natural capitals, constrained by historical power dynamics", Brito et al. 2026.
DOI: 10.17632/r2dmj96stf.1
title: Adaptive capacity of peasant communities in Brazil: enhanced by financial and natural capitals, constrained by historical power dynamics

description: This dataset contains all data used for the analyses presented in "Adaptive capacity of peasant communities in Brazil: enhanced by financial and natural capitals, constrained by historical power dynamics", Brito et al. 2026.
DOI: 10.17632/x8j293yyn3
title: Impact of multi-directional scanning strategies on mechanical & microstructural homogeneity of LW-DED printed IN718
DOI: 10.17632/x8j293yyn3.1
title: Impact of multi-directional scanning strategies on mechanical & microstructural homogeneity of LW-DED printed IN718
DOI: 10.17632/24vr3gk8c5
title: Dog breed behavior, dependence and reliance dimensions

description: We focused on behaviour-based analysis of the characteristic reliance of dog breeds on human behaviour. We utilized N=187 adult purebred dogs’ performance in a social learning task. Dogs observed a human demonstrator performing a detour around a transparent obstacle. With Principal Component Analysis, we established two behavioural dimensions: detour latency improvement and watching the demonstrator. Then, with K-means cluster analysis, we found six easily distinguishable clusters along these dimensions. The clusters showed significant differences in both behavioural dimensions, highlighting reliance-dependence types among purebred working dogs.
DOI: 10.5281/zenodo.18247917
title: Baccharis subopposita DC. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.5281/zenodo.18247916
title: Baccharis subopposita DC. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/24vr3gk8c5.1
title: Dog breed behavior, dependence and reliance dimensions

description: We focused on behaviour-based analysis of the characteristic reliance of dog breeds on human behaviour. We utilized N=187 adult purebred dogs’ performance in a social learning task. Dogs observed a human demonstrator performing a detour around a transparent obstacle. With Principal Component Analysis, we established two behavioural dimensions: detour latency improvement and watching the demonstrator. Then, with K-means cluster analysis, we found six easily distinguishable clusters along these dimensions. The clusters showed significant differences in both behavioural dimensions, highlighting reliance-dependence types among purebred working dogs.
DOI: 10.15468/dl.svd9qg
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Syngnathus taenionotus"
 ]
}

 The dataset includes 90 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009516-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/hrfxycfwgz.1
title: Drone-Based Shrub and Grass Monitoring Dataset

description: This dataset contains drone-captured aerial images of shrubs, grass, and surrounding vegetation collected from the campus area of Daffodil International University, located in Savar, Dhaka, Bangladesh, Asia. The data was acquired using low-altitude drone footage and later converted into high-resolution image frames to support computer vision and deep learning research.

The primary objective of this dataset is to enable analysis of environmental impacts on shrub and grass life cycles using deep learning techniques. The images capture natural variations in vegetation structure, density, color, and growth patterns influenced by environmental factors such as sunlight exposure, soil conditions, seasonal changes, and human activity.

The dataset is suitable for a wide range of tasks, including vegetation classification, object detection, segmentation, lifecycle analysis, and environmental monitoring. It can be used to train and evaluate deep learning models such as convolutional neural networks for understanding plant health, growth stages, and stress indicators from aerial imagery.

All images were extracted from drone videos to ensure diversity in viewing angles, scales, and spatial context. Minimal preprocessing was applied to preserve real-world conditions and visual complexity. This makes the dataset particularly useful for developing robust models that can generalize to real environmental scenarios.

This dataset is intended for academic research, environmental studies, and machine learning experimentation. Researchers can use it to explore sustainable environmental monitoring approaches, assess vegetation dynamics, and develop data-driven solutions for mitigating environmental impacts on shrub and grass ecosystems.
DOI: 10.15468/dl.skyzfy
title: Occurrence Download

description: A dataset containing 11801 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((13.18793 41.23996,13.71955 41.22148,13.73625 41.49927,13.20225 41.51785,13.18793 41.23996))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 1990-2026"
 ]
}

 The dataset includes 11801 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009517-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18247923
title: Baccharis subpingraea Heering. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.15468/dl.zhng7n
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"IND.28.6_1","matchCase":false},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009519-260108223611665/datasets/export for details.
DOI: 10.5281/zenodo.18247922
title: Baccharis subpingraea Heering. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:42
DOI: 10.17632/kbd3jzng43
title: Dataset for: The "sponsored content residue" in influencer marketing

description: Dataset for the upcoming research article: The “sponsored content residue” in influencer marketing, on IJRM

This dataset is only shared for academic purpose only.

Unfortunately, the unprocessed raw data is too large to be uploaded here. Please contact the article authors for more inquiry about data.
DOI: 10.17632/kbd3jzng43.1
title: Dataset for: The "sponsored content residue" in influencer marketing

description: Dataset for the upcoming research article: The “sponsored content residue” in influencer marketing, on IJRM

This dataset is only shared for academic purpose only.

Unfortunately, the unprocessed raw data is too large to be uploaded here. Please contact the article authors for more inquiry about data.
DOI: 10.17632/82vn9k44ky
title: Multi-Fruit Leaf Image Dataset: Guava, Jackfruit, Mango, and Olive

description: This dataset presents a high-quality and visually diverse collection of multi-fruit leaf images, including Guava (Psidium guajava), Jackfruit (Artocarpus heterophyllus), Mango (Mangifera indica), and Olive (Olea europaea) leaves, captured in real agricultural environments across Rajbari, Savar, Ashulia, and Dhaka. The dataset encompasses a wide range of leaf conditions, representing healthy leaves, multiple disease categories, pest-induced damage, senescence, and different growth stages, ensuring comprehensive coverage of fruit plant health variations. Each leaf image is carefully categorized into well-defined classes based on fruit type and leaf condition, and the dataset is accompanied by a structured CSV metadata file containing image filenames, class labels, and collection location information. The images reflect real-world field variability, including differences in lighting conditions, backgrounds, leaf textures, and orientations. Designed for machine learning and deep learning applications, this dataset supports tasks such as leaf disease detection, multi-class classification, growth-stage recognition, and intelligent crop health monitoring. It serves as a valuable resource for precision agriculture, smart farming systems, and sustainable management of fruit crops.

Dataset Original Classes and Image Counts:
Guava _Defective:100 images
Guava _Healthy:131 images
Guava _Senescent:112 images
Jackfruit_Blight:134 images
Jackfruit_Dried:149 images
Jackfruit_Fungal_Spot:145 images
Jackfruit_Healthy:130 images
Jackfruit_Pest_Damage:135 images
Jackfruit_Senescent:138 images
Jackfruit_Young:143 images
Mango_Anthracnose:159 images
Mango_Healthy:166 images
Mango_Senescent:137 images
Olive_Healthy:118 images
Olive_Mild_Edge_Damage:121 images
Olive_Pest_Damage:82 images
Olive_Senescent_Spot:63 images
Olive_Young:145 images
Total Image: 2308

Dataset Augmented Classes and Image Counts:
Guava _Defective:1000 images
Guava _Healthy:1000 images
Guava _Senescent:1000 images
Jackfruit_Blight:1000 images
Jackfruit_Dried:1000 images
Jackfruit_Fungal_Spot:1000 images
Jackfruit_Healthy:1000 images
Jackfruit_Pest_Damage:1000 images
Jackfruit_Senescent:1000 images
Jackfruit_Young:1000 images
Mango_Anthracnose:1000 images
Mango_Healthy:1000 images
Mango_Senescent:1000 images
Olive_Healthy:1000 images
Olive_Mild_Edge_Damage:1000 images
Olive_Pest_Damage:1000 images
Olive_Senescent_Spot:1000 images
Olive_Young:1000 images
Total Image: 18,000

Image Details:
Original image resolution:3072 x 4096 
Resized image resolution:512 x 512
Image format: JPG
Color mode: RGB
Collection device: Smartphone camera
Location: Rajbari, Savar, and Daffodil Smart City, Bangladesh