cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jav8sp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((151.225 -4.641848, 151.154507 -4.647411, 151.085746 -4.663963, 151.020408 -4.691098, 150.960098 -4.728149, 150.906301 -4.774204, 150.86034 -4.828131, 150.823347 -4.888604, 150.796235 -4.954136, 150.779673 -5.023115, 150.774073 -5.093842, 150.779576 -5.164577, 150.79605 -5.233577, 150.823092 -5.299144, 150.86004 -5.35966, 150.905986 -5.413635, 150.959798 -5.459738, 151.020153 -5.496832, 151.085561 -5.524001, 151.154409 -5.540575, 151.225 -5.546146, 151.295591 -5.540575, 151.364439 -5.524001, 151.429847 -5.496832, 151.490202 -5.459738, 151.544014 -5.413635, 151.58996 -5.35966, 151.626908 -5.299144, 151.65395 -5.233577, 151.670424 -5.164577, 151.675927 -5.093842, 151.670327 -5.023115, 151.653765 -4.954136, 151.626653 -4.888604, 151.58966 -4.828131, 151.543699 -4.774204, 151.489902 -4.728149, 151.429592 -4.691098, 151.364254 -4.663963, 151.295493 -4.647411, 151.225 -4.641848))"},{"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/0002364-260119153935675/datasets/export for details.
DOI: 10.5281/zenodo.18311032
title: Setaria vaginata Spreng. 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 16:54
DOI: 10.15468/dl.amfw5n
title: Occurrence Download

description: A dataset containing 9 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Succisella inflexa)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 9 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002365-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18311045
title: Setaria subtransiens Hitchc. & Ekman. 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 16:54
DOI: 10.5281/zenodo.18311046
title: Setaria subtransiens Hitchc. & Ekman. 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 16:54
DOI: 10.15468/dl.rgh83u
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((111.487 -1.64182, 111.416708 -1.647386, 111.348146 -1.663946, 111.283 -1.691092, 111.222874 -1.728158, 111.169248 -1.77423, 111.123441 -1.828175, 111.086582 -1.888665, 111.059579 -1.954212, 111.043097 -2.023201, 111.037544 -2.093935, 111.043058 -2.164672, 111.059503 -2.233671, 111.086478 -2.299231, 111.123319 -2.359739, 111.169119 -2.413704, 111.222752 -2.459796, 111.282896 -2.496879, 111.34807 -2.52404, 111.416668 -2.540609, 111.487 -2.546177, 111.557332 -2.540609, 111.62593 -2.52404, 111.691104 -2.496879, 111.751248 -2.459796, 111.804881 -2.413704, 111.850681 -2.359739, 111.887522 -2.299231, 111.914497 -2.233671, 111.930942 -2.164672, 111.936456 -2.093935, 111.930903 -2.023201, 111.914421 -1.954212, 111.887418 -1.888665, 111.850559 -1.828175, 111.804752 -1.77423, 111.751126 -1.728158, 111.691 -1.691092, 111.625854 -1.663946, 111.557292 -1.647386, 111.487 -1.64182))"},{"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/0002367-260119153935675/datasets/export for details.
DOI: 10.15468/dl.msm4us
title: Occurrence Download

description: A dataset containing 57709 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((3.3465639729340233 51.340657658051974, 3.346092615067062 51.3432840347708, 3.3448121062571503 51.345802340012376, 3.3427715426629874 51.348115772121375, 3.3400492681858474 51.35013539119345, 3.3367498750140987 51.351783542467366, 3.333000187766893 51.35299684693962, 3.328944385016093 51.35372864330098, 3.3247384463731433 51.35395078639074, 3.3205441403961964 51.35365473224803, 3.3165227870858653 51.35285186753736, 3.312829037850775 51.35157307052263, 3.309604915117269 51.34986752068139, 3.306974343263737 51.347800803276996, 3.305038382761742 51.34545238256601, 3.303871351204942 51.342912541716984, 3.303517979567099 51.34027890800006, 3.3039917111024892 51.33765269758586, 3.3052742055330735 51.33513482478653, 3.3073160644074378 51.33282202542208, 3.3100387466295973 51.330803143067236, 3.313337597935618 51.32915572032469, 3.317085876200419 51.32794302528568, 3.321139617356905 51.32721162647864, 3.3253431556527153 51.326989608540366, 3.3295350879608714 51.327285496378465, 3.333554455650396 51.3280879286468, 3.3372469096054616 51.32936609291692, 3.340470624594327 51.33107090604094, 3.3431017383139467 51.33313689491397, 3.345039107798478 51.3354847061918, 3.346208200949419 51.338024149486515, 3.3465639729340233 51.340657658051974))",
 "KingdomKey is one of (Animalia, Fungi, Plantae)",
 "Year is one of (2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025, 2026)"
 ]
}

 The dataset includes 57709 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002332-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18311053
title: Setaria vaginata var. tandilensis Nicora. 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 16:54
DOI: 10.5281/zenodo.18311054
title: Setaria vaginata var. tandilensis Nicora. 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 16:54
DOI: 10.5281/zenodo.18311056
title: Setaria vaginata var. bonariensis Nicora. 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 16:54
DOI: 10.5281/zenodo.18311057
title: Setaria vaginata var. bonariensis Nicora. 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 16:54
DOI: 10.15468/dl.xkesm4
title: Occurrence Download

description: A dataset containing 14441 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bactrocera dorsalis"
 ]
}

 The dataset includes 14441 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002369-260119153935675/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r8saja
title: Occurrence Download

description: A dataset containing 6969 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Mesosetum Steud."
 ]
}

 The dataset includes 6969 records from 201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003606-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15544041
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250529j Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250529j Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.15544042
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS250529j Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS250529j Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.17632/vtxmwt2958.1
title: Dataset on Does environmental reporting of banks affect their financial performance? Evidence from India

description: The Original data of environmental reporting practices has been obtained for the banks listed in the NSE Nifty Bank Index from 2016–2017 to 2020–2021. The content analysis technique was employed with the help of NVivo 14 . The financial data was collected from the CMIE Prowess database. The data was used to study the the effect of environmental reporting on the financial performance of banks in India. The article titled "Does environmental reporting of banks affect their financial performance? Evidence from India" has been published by using this raw original data. 

This raw data set will be useful for further research relating to environmental reporting and sustainability of banks in India. the academic researchers, bankers, corporate executives, and policy makers will be beneficiary of this data set.
DOI: 10.17632/vtxmwt2958
title: Environmental reporting and financial performance of NSE Nifty Banks: A longitudinal dataset

description: The Original data of environmental reporting practices has been obtained for the banks listed in the NSE Nifty Bank Index from 2016–2017 to 2020–2021. The content analysis technique was employed with the help of NVivo 14 . The financial data was collected from the CMIE Prowess database. The data was used to study the effect of environmental reporting on the financial performance of banks in India. The article titled "Does environmental reporting of banks affect their financial performance? Evidence from India" has been published by using this raw original data. 

This raw data set will be useful for further research relating to environmental reporting and sustainability of banks in India. the academic researchers, bankers, corporate executives, and policy makers will be beneficiary of this data set. The material and methods provided in this data set will provide a blueprint for the prospective researchers in this area because the environmental reporting data is not available readily as like other financial data. further environmental reporting data of banks in India is highly precious for the researchers.
DOI: 10.17632/vtxmwt2958.2
title: Environmental reporting and financial performance of NSE Nifty Banks: A longitudinal dataset

description: The Original data of environmental reporting practices has been obtained for the banks listed in the NSE Nifty Bank Index from 2016–2017 to 2020–2021. The content analysis technique was employed with the help of NVivo 14 . The financial data was collected from the CMIE Prowess database. The data was used to study the effect of environmental reporting on the financial performance of banks in India. The article titled "Does environmental reporting of banks affect their financial performance? Evidence from India" has been published by using this raw original data. 

This raw data set will be useful for further research relating to environmental reporting and sustainability of banks in India. the academic researchers, bankers, corporate executives, and policy makers will be beneficiary of this data set. The material and methods provided in this data set will provide a blueprint for the prospective researchers in this area because the environmental reporting data is not available readily as like other financial data. further environmental reporting data of banks in India is highly precious for the researchers.
DOI: 10.17632/643f5bbc2t.1
title: Image dataset of Lemon leaf disease

description: The dataset contains 1,282 color images of Lemon leaves, collected from various regions in Dhaka, Bangladesh. The images are divided into two broad categories: healthy leaves and diseased leaves. The diseased category is further segmented into eight specific classes, with the number of images per class as follows: 151 images of Anthracnose, 88 images of Black Spot, 33 images of Citrus Canker, 49 images of Citrus Leaf Miner, 79 images of Curl Leaf, 97 images of Dry Leaf, 438 images of Greening, and 126 images of Melanose.
DOI: 10.17632/643f5bbc2t.2
title: Image dataset of Lemon leaf disease

description: The dataset contains 1,282 color images of Lemon leaves, collected from various regions in Dhaka, Bangladesh. The images are divided into two broad categories: healthy leaves and diseased leaves. The diseased category is further segmented into eight specific classes, with the number of images per class as follows: 151 images of Anthracnose, 88 images of Black Spot, 33 images of Citrus Canker, 49 images of Citrus Leaf Miner, 79 images of Curl Leaf, 97 images of Dry Leaf, 438 images of Greening, and 126 images of Melanose. Also, Healthy folder contains 221 healthy leaf images.
DOI: 10.17632/643f5bbc2t.3
title: Image dataset of Lemon leaf disease

description: The dataset contains 1,322 color images of Lemon leaves, collected from various regions in Dhaka, Bangladesh. The images are divided into two broad categories: healthy leaves and diseased leaves. The diseased category is further segmented into eight specific classes, with the number of images per class as follows: 151 images of Anthracnose, 88 images of Black Spot, 33 images of Citrus Canker, 89 images of Citrus Scab, 79 images of Curl Leaf, 97 images of Dry Leaf, 438 images of Greening, and 126 images of Melanose. Also, Healthy folder contains 221 healthy leaf images.
DOI: 10.17632/643f5bbc2t.4
title: BDLemonLeaf: Image Dataset of Healthy and Disease Lemon (Citrus limon) Leaves

description: This dataset consists of 2,848 colour images of Lemon (Citrus limon) leaves collected from various locations in Dhaka, Bangladesh. The images are categorized into two primary groups: healthy and diseased leaves where disease leaves category is sub-divided into further nine disease classes. The sample distribution is given below: 
 
Anthracnose = 275 images 
Black Spot =146 images 
Citrus Canker = 326 images
Citrus Hindu Mite = 564 images 
Citrus Leafminer =116 images
Curl Leaf = 222 images
Dry leaf = 228 images
Greening = 574 images
Melanose = 176 images 
Healthy = 221 images

All images were resized to 640 x 480 pixels.
DOI: 10.17632/643f5bbc2t.5
title: BDLemonLeaf: Image Dataset of Healthy and Disease Lemon (Citrus limon) Leaves

description: This dataset consists of 3,513 colour images of Lemon (Citrus limon) leaves collected from various locations in Dhaka, Bangladesh. The images are categorized into two primary groups: healthy and disease leaves where disease leaves category is sub-divided into further thirteen disease classes. The sample distribution is given below: 
 
Anthracnose = 235 images 
Bacterial Blight = 122 images
Black Spot =112 images 
Citrus Canker = 294 images
Citrus Hindu Mite = 544 images 
Citrus Leafminer =125 images
Curl Leaf = 291 images
Deficiency = 382 images
Dry leaf = 195 images
Greening = 597 images
Melanose = 188 images 
Sooty Mould = 82 images
Spider Mites = 125 images

Healthy = 221 images

All images were resized to 640 x 480 pixels.
DOI: 10.17632/643f5bbc2t.6
title: BDLemonLeaf: Image Dataset of Healthy and Disease Lemon (Citrus limon) Leaves

description: This dataset consists of 3,431 color images of lemon (Citrus limon) leaves collected from various locations in Dhaka, Bangladesh. The images are categorized into two groups: healthy and disease leaf. The disease leaves are further divided into twelve specific disease classes. Each image showing disease has been carefully annotated with bounding boxes to mark the affected areas. These annotations help highlight exactly where the symptoms appear on the leaf. Finally, the Readme.png file describes the folder hierarchy of our dataset.

Anthracnose = 235 images 
Bacterial Blight = 122 images
Black Spot =112 images 
Citrus Canker = 294 images
Citrus Hindu Mite = 544 images 
Citrus Leafminer =125 images
Curl Leaf = 291 images
Deficiency = 382 images
Dry leaf = 195 images
Greening = 597 images
Melanose = 188 images 
Spider Mites = 125 images

Healthy = 221 images

All images were resized to 640 x 480 pixels.
DOI: 10.5281/zenodo.15477516
title: Simulations for Baseline and Full Ensembles for Sea Level Rise Adaptation in Boston Harbor Model

description: The files here contain the raw csv outputs from the Boston Sea Level Rise Adaptation model for use in the paper "More Than the Climate: Governance and Coordination Trade-offs for Sea Level Rise Adaptation in Boston" by Catherine Knox, Paul Kirshen, Jonathan Lamontagne, and Shafiqul Islam. All authors aided in the design and development of the model. These files are all csv outputs from the Behavior Space functionality of NetLogo (Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.).
DOI: 10.5281/zenodo.15477517
title: Simulations for Baseline and Full Ensembles for Sea Level Rise Adaptation in Boston Harbor Model

description: The files here contain the raw csv outputs from the Boston Sea Level Rise Adaptation model for use in the paper "More Than the Climate: Governance and Coordination Trade-offs for Sea Level Rise Adaptation in Boston" by Catherine Knox, Paul Kirshen, Jonathan Lamontagne, and Shafiqul Islam. All authors aided in the design and development of the model. These files are all csv outputs from the Behavior Space functionality of NetLogo (Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.).
DOI: 10.17632/bshsghhny3.1
title: EHI/ERI/ESsI/ESI (2000/2005/2010/2015/2020)

description: This dataset includes the Ecological Health Index (EHI), Ecological Risk Index (ERI), Ecosystem Service Index (ESsI), and Ecological Security Index (ESI) for the source regions of the Yangtze and Yellow Rivers from 2000 to 2020. All data are in raster format.
DOI: 10.25824/redu/2wigyp
title: Tables, images, graphs selective extraction UAPLE Inline Rosemary

description: Tables, Images, Graphs for the Development of a System for Selective Extraction Separation and Quantification of Carnosic Derivatives and Rosmarinic Acid by UAPLE Inline, from Rosemary (Rosmarinus officinalis, L)
DOI: 10.6084/m9.figshare.29945264
title: <b>V2V/V2H/V2G/G2G four-port multi-function portable electric vehicle charging converter</b>

description: The fact that electric vehicles (EVs) have the ability to perform flexibly will help reduce greenhouse gas emissions in the process of using energy, saving electricity worldwide in general, in a local area in particular corresponding to the relocation of electric vehicles. The article provides a solution to help the energy source used for EVs be used effectively at three other ports in the charger. One is port number one, another electric vehicle uses parameters such as electric vehicles to collect energy. Port number two is a DC power line with a combination of DC load components, renewable energy sources and storage systems. Port number three is an AC microgrid connection. The feature of the converter is flexible and convenient to accompany each electric vehicle at each time and location to perform power exchange. The converter performs the highest voltage charging parameters for EVs of 860VDC, 5kW exchange capacity, and 40kHz control frequency. The results of the study achieved an average efficiency simulated by Mablab software for the converter of over 98%. The DPWM control method was used in this conversion process.
DOI: 10.6084/m9.figshare.29945264.v1
title: <b>V2V/V2H/V2G/G2G four-port multi-function portable electric vehicle charging converter</b>

description: The fact that electric vehicles (EVs) have the ability to perform flexibly will help reduce greenhouse gas emissions in the process of using energy, saving electricity worldwide in general, in a local area in particular corresponding to the relocation of electric vehicles. The article provides a solution to help the energy source used for EVs be used effectively at three other ports in the charger. One is port number one, another electric vehicle uses parameters such as electric vehicles to collect energy. Port number two is a DC power line with a combination of DC load components, renewable energy sources and storage systems. Port number three is an AC microgrid connection. The feature of the converter is flexible and convenient to accompany each electric vehicle at each time and location to perform power exchange. The converter performs the highest voltage charging parameters for EVs of 860VDC, 5kW exchange capacity, and 40kHz control frequency. The results of the study achieved an average efficiency simulated by Mablab software for the converter of over 98%. The DPWM control method was used in this conversion process.
DOI: 10.15468/dl.h3aryb
title: Occurrence Download

description: A dataset containing 302 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "GadmGid is IDN.21_1",
 "IucnRedListCategory is CR",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 302 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009323-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qj52f7
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "PublishingOrg is 28eb1a3f-1c15-4a95-931a-4af90ecb574d",
 "TaxonKey is Ailuropoda melanoleuca",
 "Year 2000-2025"
 ]
}

 The dataset includes 24 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000879-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.