cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.uth4sk
title: Occurrence Download

description: A dataset containing 153469 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Trifolium hybridum L."
 ]
}

 The dataset includes 153469 records from 1049 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126176-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x6ck2g
title: Occurrence Download

description: A dataset containing 17 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Turraea kimbozensis Cheek"
 ]
}

 The dataset includes 17 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126216-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.h4y9bc
title: Occurrence Download

description: A dataset containing 2388962 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Acridotheres tristis (Linnaeus, 1766)"
 ]
}

 The dataset includes 2388962 records from 338 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0126189-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48597/4wph-3m5p
title: Measurement of Sulphate_corrected at Auchencorth Moss

description: Measurement of Sulphate_corrected at Auchencorth Moss
DOI: 10.48597/4y3n-ekf8
title: Measurement of Sulphate_corrected at Jarczew

description: Measurement of Sulphate_corrected at Jarczew
DOI: 10.48597/522d-9nkt
title: Measurement of Sulphate_corrected at Janiskoski

description: Measurement of Sulphate_corrected at Janiskoski
DOI: 10.48597/5493-pzkr
title: Measurement of Sulphate_corrected at Carnsore Point

description: Measurement of Sulphate_corrected at Carnsore Point
DOI: 10.48597/54c3-xbcu
title: Measurement of Sulphate_corrected at Ispra

description: Measurement of Sulphate_corrected at Ispra
DOI: 10.48597/5689-qe6c
title: Measurement of Sulphate_corrected at Montandon

description: Measurement of Sulphate_corrected at Montandon
DOI: 10.48597/5c9w-6b2x
title: Measurement of Sulphate_corrected at Els Torms

description: Measurement of Sulphate_corrected at Els Torms
DOI: 10.6084/m9.figshare.12581072
title: 510 Ma S-Hg-C data

description: Tables 1-2, Tables s1-s4
DOI: 10.48597/5tca-7wak
title: Measurement of Sulphate_corrected at Montandon

description: Measurement of Sulphate_corrected at Montandon
DOI: 10.48597/5ukw-xa8k
title: Measurement of Sulphate_corrected at Jarczew

description: Measurement of Sulphate_corrected at Jarczew
DOI: 10.48597/5uwz-bq5r
title: Measurement of Sulphate_corrected at Saint-Nazaire-le-Désert

description: Measurement of Sulphate_corrected at Saint-Nazaire-le-Désert
DOI: 10.48597/5zkk-y9sk
title: Measurement of Sulphate_corrected at Vredepeel

description: Measurement of Sulphate_corrected at Vredepeel
DOI: 10.48597/67k7-2tjh
title: Measurement of Sulphate_corrected at Peyrusse Vieille

description: Measurement of Sulphate_corrected at Peyrusse Vieille
DOI: 10.48597/7773-jue9
title: Measurement of Sulphate_corrected at Malin Head

description: Measurement of Sulphate_corrected at Malin Head
DOI: 10.48597/7kq8-48qe
title: Measurement of Sulphate_corrected at La Coulonche

description: Measurement of Sulphate_corrected at La Coulonche
DOI: 10.48597/7z76-vzw9
title: Measurement of Sulphate_corrected at Johnstown Castle

description: Measurement of Sulphate_corrected at Johnstown Castle
DOI: 10.48597/873b-stse
title: Measurement of Sulphate_corrected at Víznar

description: Measurement of Sulphate_corrected at Víznar
DOI: 10.48597/8ayp-3kq8
title: Measurement of Sulphate_corrected at San Pablo de los Montes

description: Measurement of Sulphate_corrected at San Pablo de los Montes
DOI: 10.48597/8fvy-23sy
title: Measurement of Sulphate_corrected at Guipry

description: Measurement of Sulphate_corrected at Guipry
DOI: 10.48597/9mek-5uat
title: Measurement of Sulphate_corrected at High Muffles

description: Measurement of Sulphate_corrected at High Muffles
DOI: 10.48597/9qg6-hj48
title: Measurement of Sulphate_corrected at Leova II

description: Measurement of Sulphate_corrected at Leova II
DOI: 10.48597/a2y6-gkpc
title: Measurement of Sulphate_corrected at Oak Park

description: Measurement of Sulphate_corrected at Oak Park
DOI: 10.48597/b4vc-ds2w
title: Measurement of Sulphate_corrected at Eskdalemuir

description: Measurement of Sulphate_corrected at Eskdalemuir
DOI: 10.48597/b7b8-jgtb
title: Measurement of Sulphate_corrected at Waldhof

description: Measurement of Sulphate_corrected at Waldhof
DOI: 10.48597/bf5n-qjf6
title: Measurement of Sulphate_corrected at Schauinsland

description: Measurement of Sulphate_corrected at Schauinsland
DOI: 10.48597/bgwk-3tcv
title: Measurement of Sulphate_corrected at Anholt

description: Measurement of Sulphate_corrected at Anholt
DOI: 10.48597/bm4m-8qmp
title: Measurement of Sulphate_corrected at Eskdalemuir

description: Measurement of Sulphate_corrected at Eskdalemuir
DOI: 10.48597/bsah-7rxf
title: Measurement of Sulphate_corrected at Lahemaa

description: Measurement of Sulphate_corrected at Lahemaa
DOI: 10.5281/zenodo.10168194
title: CERTH Grape Dataset

description: The CERTH grape dataset aims to advance computer vision and machine learning research in the field of viticulture by providing valuable annotated data for developing and refining algorithms for accurate grape segmentation, yield prediction, and, most importantly, maturity estimation. The dataset consists of 2502 high-resolution images captured from a vineyard cultivating the 'Crimson Seedless' table grape variety during the 2022–2023 development and harvesting period and exhibits different view angles, camera focus conditions, and illumination variations. The images are captured using an iPhone 11 Pro smartphone and are scaled to a resolution of 2160 × 3840 pixels.
The annotations include grape bunches with detailed object masks and are categorized into three distinct classes (i.e., immature, semi-mature, and mature) based on the degree of grape maturity, as identified by the color of the grapes in the bunch. As a result, grapes in the immature class were early in their development phase, grapes in the mature class were close to the harvesting season, and grapes in the semi-mature class were in the intermediate period when changes in the color of the grapes from yellow to red had initiated.
The CERTH grape dataset consists of 9832 labeled grape bunches, extracted from all 2502 images. The grape images are split into training, validation, and test sets, consisting of 2000, 251, and 251 images, respectively. The training set comprises 7959 annotated grape bunches, while the validation and test sets comprise 914 and 959 annotated grape bunches, respectively.
The CERTH grape datasets can be evaluated on two scenarios. The multi-instance / multi-class (mimc) scenario evaluates the performance of algorithms in multi-instance classification using the original test set, while the single-instance / one-class (sioc) scenario extracts 100 images from the original test set that contain a single grape bunch per image to evaluate the performance of algorithms in single-instance classification. The sioc subset consists of 36, 43, and 21 images that depict grape bunches from the immature, semi-mature, and mature classes, respectively.
To use this dataset, please also cite:
Blekos, A.; Chatzis, K.; Kotaidou, M.; Chatzis, T.; Solachidis, V.; Konstantinidis, D.; Dimitropoulos, K. A Grape Dataset for Instance Segmentation and Maturity Estimation. Agronomy 2023, 13, 1995. https://doi.org/10.3390/agronomy13081995.
DOI: 10.5281/zenodo.10168195
title: CERTH Grape Dataset

description: The CERTH grape dataset aims to advance computer vision and machine learning research in the field of viticulture by providing valuable annotated data for developing and refining algorithms for accurate grape segmentation, yield prediction, and, most importantly, maturity estimation. The dataset consists of 2502 high-resolution images captured from a vineyard cultivating the 'Crimson Seedless' table grape variety during the 2022–2023 development and harvesting period and exhibits different view angles, camera focus conditions, and illumination variations. The images are captured using an iPhone 11 Pro smartphone and are scaled to a resolution of 2160 × 3840 pixels.
The annotations include grape bunches with detailed object masks and are categorized into three distinct classes (i.e., immature, semi-mature, and mature) based on the degree of grape maturity, as identified by the color of the grapes in the bunch. As a result, grapes in the immature class were early in their development phase, grapes in the mature class were close to the harvesting season, and grapes in the semi-mature class were in the intermediate period when changes in the color of the grapes from yellow to red had initiated.
The CERTH grape dataset consists of 9832 labeled grape bunches, extracted from all 2502 images. The grape images are split into training, validation, and test sets, consisting of 2000, 251, and 251 images, respectively. The training set comprises 7959 annotated grape bunches, while the validation and test sets comprise 914 and 959 annotated grape bunches, respectively.
The CERTH grape datasets can be evaluated on two scenarios. The multi-instance / multi-class (mimc) scenario evaluates the performance of algorithms in multi-instance classification using the original test set, while the single-instance / one-class (sioc) scenario extracts 100 images from the original test set that contain a single grape bunch per image to evaluate the performance of algorithms in single-instance classification. The sioc subset consists of 36, 43, and 21 images that depict grape bunches from the immature, semi-mature, and mature classes, respectively.
To use this dataset, please also cite:
Blekos, A.; Chatzis, K.; Kotaidou, M.; Chatzis, T.; Solachidis, V.; Konstantinidis, D.; Dimitropoulos, K. A Grape Dataset for Instance Segmentation and Maturity Estimation. Agronomy 2023, 13, 1995. https://doi.org/10.3390/agronomy13081995.
DOI: 10.5281/zenodo.10777647
title: CERTH Grape Dataset

description: The CERTH grape dataset aims to advance computer vision and machine learning research in the field of viticulture by providing valuable annotated data for developing and refining algorithms for accurate grape segmentation, yield prediction, and, most importantly, maturity estimation. The dataset consists of 2502 high-resolution images captured from a vineyard cultivating the 'Crimson Seedless' table grape variety during the 2022–2023 development and harvesting period and exhibits different view angles, camera focus conditions, and illumination variations. The images are captured using an iPhone 11 Pro smartphone and are scaled to a resolution of 2160 × 3840 pixels.
The annotations include grape bunches with detailed object masks and are categorized into three distinct classes (i.e., immature, semi-mature, and mature) based on the degree of grape maturity, as identified by the color of the grapes in the bunch. As a result, grapes in the immature class were early in their development phase, grapes in the mature class were close to the harvesting season, and grapes in the semi-mature class were in the intermediate period when changes in the color of the grapes from yellow to red had initiated.
The CERTH grape dataset consists of 9832 labeled grape bunches, extracted from all 2502 images. The grape images are split into training, validation, and test sets, consisting of 2000, 251, and 251 images, respectively. The training set comprises 7959 annotated grape bunches, while the validation and test sets comprise 914 and 959 annotated grape bunches, respectively.
The CERTH grape datasets can be evaluated on two scenarios. The multi-instance / multi-class (mimc) scenario evaluates the performance of algorithms in multi-instance classification using the original test set, while the single-instance / one-class (sioc) scenario extracts 100 images from the original test set that contain a single grape bunch per image to evaluate the performance of algorithms in single-instance classification. The sioc subset consists of 36, 43, and 21 images that depict grape bunches from the immature, semi-mature, and mature classes, respectively.
To use this dataset, please also cite:
Blekos, A.; Chatzis, K.; Kotaidou, M.; Chatzis, T.; Solachidis, V.; Konstantinidis, D.; Dimitropoulos, K. A Grape Dataset for Instance Segmentation and Maturity Estimation. Agronomy 2023, 13, 1995. https://doi.org/10.3390/agronomy13081995.
DOI: 10.6084/m9.figshare.6813920
title: Additional file 1: of Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers

description: Mapping and UMI statistics of (A) RNA-seq and (B) small RNA-seq data generated in this study. (XLSX 112 kb)
DOI: 10.48597/bt36-8sp5
title: Measurement of Sulphate_corrected at Barcarrota

description: Measurement of Sulphate_corrected at Barcarrota
DOI: 10.48597/bur3-32tc
title: Measurement of Sulphate_corrected at K-puszta

description: Measurement of Sulphate_corrected at K-puszta
DOI: 10.6084/m9.figshare.6813920.v1
title: Additional file 1: of Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers

description: Mapping and UMI statistics of (A) RNA-seq and (B) small RNA-seq data generated in this study. (XLSX 112 kb)
DOI: 10.48597/ck4x-e82r
title: Measurement of Sulphate_corrected at Donon

description: Measurement of Sulphate_corrected at Donon
DOI: 10.48597/dv4z-2v4f
title: Measurement of PAHs (polycyclic aromatic hydrocarbons) at Guipry

description: Measurement of PAHs (polycyclic aromatic hydrocarbons) at Guipry
DOI: 10.48597/e5vp-cvza
title: Measurement of Sulphate_corrected at Storhofdi

description: Measurement of Sulphate_corrected at Storhofdi
DOI: 10.48597/e785-5cs7
title: Measurement of Inorganics in precipitation at Råö

description: Measurement of Inorganics in precipitation at Råö
DOI: 10.48597/eccf-uqrh
title: Measurement of Sulphate_corrected at De Zilk

description: Measurement of Sulphate_corrected at De Zilk
DOI: 10.48597/efw8-xufv
title: Measurement of Sulphate_corrected at Tange

description: Measurement of Sulphate_corrected at Tange
DOI: 10.48597/egwy-trhu
title: Measurement of OC/EC and inorganics in air and particle phase at Verneuil

description: Measurement of OC/EC and inorganics in air and particle phase at Verneuil
DOI: 10.48597/ehjv-g9jj
title: Measurement of Sulphate_corrected at Ulborg

description: Measurement of Sulphate_corrected at Ulborg
DOI: 10.48597/ekk6-7prt
title: Measurement of OC/EC and inorganics in air and particle phase at Guipry

description: Measurement of OC/EC and inorganics in air and particle phase at Guipry
DOI: 10.48597/ey5g-q6d4
title: Measurement of Sulphate_corrected at Verneuil

description: Measurement of Sulphate_corrected at Verneuil
DOI: 10.48597/f8nf-atwc
title: Measurement of Sulphate_corrected at Morvan

description: Measurement of Sulphate_corrected at Morvan
DOI: 10.48597/fukm-by6d
title: Measurement of Sulphate_corrected at Neuglobsow

description: Measurement of Sulphate_corrected at Neuglobsow
DOI: 10.48597/fv9x-mhtq
title: Measurement of Sulphate_corrected at O Saviñao

description: Measurement of Sulphate_corrected at O Saviñao
DOI: 10.48597/fw6r-ysp5
title: Measurement of Sulphate_corrected at Montandon

description: Measurement of Sulphate_corrected at Montandon
DOI: 10.48597/g4n7-9s4a
title: Measurement of Sulphate_corrected at Leova II

description: Measurement of Sulphate_corrected at Leova II
DOI: 10.48597/ghc8-sduf
title: Measurement of Sulphate_corrected at Auchencorth Moss

description: Measurement of Sulphate_corrected at Auchencorth Moss
DOI: 10.48597/gvsv-4s7q
title: Measurement of Sulphate_corrected at Waldhof

description: Measurement of Sulphate_corrected at Waldhof
DOI: 10.48597/h9fj-wjra
title: Measurement of Sulphate_corrected at Peyrusse Vieille

description: Measurement of Sulphate_corrected at Peyrusse Vieille
DOI: 10.48597/hhsu-2pwx
title: Measurement of Sulphate_corrected at Sepstrup Sande

description: Measurement of Sulphate_corrected at Sepstrup Sande
DOI: 10.48597/hpf3-2jj2
title: Measurement of Pm25_mass at Lahemaa

description: Measurement of Pm25_mass at Lahemaa
DOI: 10.48597/hsmz-xmrk
title: Measurement of Inorganics in precipitation at Montandon

description: Measurement of Inorganics in precipitation at Montandon
DOI: 10.48597/j7hf-x2vh
title: Measurement of Sulphate_corrected at Campisabalos

description: Measurement of Sulphate_corrected at Campisabalos
DOI: 10.48597/jfj3-z5h6
title: Measurement of Sulphate_corrected at Keldsnor

description: Measurement of Sulphate_corrected at Keldsnor
DOI: 10.48597/jkhk-e3d6
title: Measurement of Sulphate_corrected at Melpitz

description: Measurement of Sulphate_corrected at Melpitz
DOI: 10.48597/jvz6-nvvd
title: Measurement of Sulphate_corrected at Penausende

description: Measurement of Sulphate_corrected at Penausende
DOI: 10.48597/k233-3pxk
title: Measurement of Sulphate_corrected at Lough Navar

description: Measurement of Sulphate_corrected at Lough Navar
DOI: 10.48597/k4x3-vhpq
title: Measurement of Sulphate_corrected at Anholt

description: Measurement of Sulphate_corrected at Anholt
DOI: 10.48597/kf9y-kajq
title: Measurement of Sulphate_corrected at Víznar

description: Measurement of Sulphate_corrected at Víznar
DOI: 10.48597/kpcc-43b9
title: Measurement of Pm25_mass at Vilsandi

description: Measurement of Pm25_mass at Vilsandi
DOI: 10.48597/kxnw-pwb3
title: Measurement of Sulphate_corrected at Ispra

description: Measurement of Sulphate_corrected at Ispra
DOI: 10.48597/m7um-t4cx
title: Measurement of OC/EC at Leova II

description: Measurement of OC/EC at Leova II
DOI: 10.48597/ngk9-8suf
title: Measurement of Sulphate_corrected at Melpitz

description: Measurement of Sulphate_corrected at Melpitz
DOI: 10.48597/nq6u-vez7
title: Measurement of Sulphate_corrected at Yarner Wood

description: Measurement of Sulphate_corrected at Yarner Wood
DOI: 10.48597/nssj-s88p
title: Measurement of Sulphate_corrected at Auchencorth Moss

description: Measurement of Sulphate_corrected at Auchencorth Moss
DOI: 10.48597/nxsp-pp2m
title: Measurement of OC/EC and inorganics in air and particle phase at Revin

description: Measurement of OC/EC and inorganics in air and particle phase at Revin
DOI: 10.48597/psgm-r5df
title: Measurement of Sulphate_corrected at La Tardière

description: Measurement of Sulphate_corrected at La Tardière
DOI: 10.48597/q5vv-qcpn
title: Measurement of Inorganics in precipitation at Montandon

description: Measurement of Inorganics in precipitation at Montandon
DOI: 10.48597/qg97-cu2h
title: Measurement of Sulphate_corrected at Rigi

description: Measurement of Sulphate_corrected at Rigi
DOI: 10.48597/qtak-ykk3
title: Measurement of Sulphate_corrected at Valentia Observatory

description: Measurement of Sulphate_corrected at Valentia Observatory
DOI: 10.48597/qzg9-kfk4
title: Measurement of Sulphate_corrected at Donon

description: Measurement of Sulphate_corrected at Donon
DOI: 10.48597/r9ds-cweb
title: Measurement of Sulphate_corrected at Reykjavik

description: Measurement of Sulphate_corrected at Reykjavik
DOI: 10.48597/ramu-wrta
title: Measurement of Sulphate_corrected at Revin

description: Measurement of Sulphate_corrected at Revin
DOI: 10.48597/s6ht-v7nw
title: Measurement of OC/EC and inorganics in air and particle phase at Peyrusse Vieille

description: Measurement of OC/EC and inorganics in air and particle phase at Peyrusse Vieille
DOI: 10.48597/sbpu-w4xp
title: Measurement of Sulphate_corrected at Churanov

description: Measurement of Sulphate_corrected at Churanov
DOI: 10.48597/t7u9-w33s
title: Measurement of Sulphate_corrected at Preila

description: Measurement of Sulphate_corrected at Preila
DOI: 10.48597/tsg3-hpa9
title: Measurement of Sulphate_corrected at Schauinsland

description: Measurement of Sulphate_corrected at Schauinsland
DOI: 10.48597/tx8x-p8uf
title: Measurement of Sulphate_corrected at Montfranc

description: Measurement of Sulphate_corrected at Montfranc
DOI: 10.48597/uhwp-67c2
title: Measurement of Sulphate_corrected at Zarra

description: Measurement of Sulphate_corrected at Zarra
DOI: 10.48597/usjy-gq83
title: Measurement of Sulphate_corrected at Rigi

description: Measurement of Sulphate_corrected at Rigi
DOI: 10.48597/v8b7-v37b
title: Measurement of Sulphate_corrected at Kosetice (NOAK)

description: Measurement of Sulphate_corrected at Kosetice (NOAK)
DOI: 10.48597/v92d-w9ns
title: Measurement of PAHs (polycyclic aromatic hydrocarbons) at Peyrusse Vieille

description: Measurement of PAHs (polycyclic aromatic hydrocarbons) at Peyrusse Vieille
DOI: 10.6084/m9.figshare.6813953
title: Additional file 3: of Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers

description: UMI method comparison. (XLSX 11 kb)
DOI: 10.5281/zenodo.10761547
title: Historical LCA supplementary information

description: added excel sheet with energy efficiency, transport and loss, etc.
DOI: 10.5281/zenodo.10767208
title: Historical LCA supplementary information

description: added excel sheet with energy efficiency, transport and loss, etc.
DOI: 10.6084/m9.figshare.12056883
title: Individualized treatment for allergic rhinitis based on key nasal clinical manifestations combined with histamine and leukotriene D4 levels

description: Abstract Introduction The types of allergic rhinitis are roughly classified based on the causative antigens, disease types, predilection time, and symptom severity. Objective To examine the clinical typing and individualized treatment approach for allergic rhinitis and to determine the optimal treatment method for this disease using various drug combination therapies. Methods A total of 108 participants with allergic rhinitis were divided into three groups based on symptoms. Subsequently, each group was further categorized into four subgroups based on the medications received. The efficacy of the treatments was evaluated using the visual analog scale VAS scores of the total and individual nasal symptoms, decline index of the symptom score, histamine and leukotriene levels, and mRNA and protein expression levels of histamine 1 and cysteinyl leukotriene 1 receptors. Results Loratadine + mometasone furoate and loratadine + mometasone furoate + montelukast significantly improved the sneezing symptom and reduced the histamine levels compared with the other combination therapies (p &lt; 0.05). Meanwhile, montelukast + mometasone furoate and montelukast + mometasone furoate + loratadine considerably improved the nasal obstruction symptom and decreased the leukotriene D4 levels compared with the other combination therapies (p &lt; 0.05). Conclusion Clinical symptom evaluation combined with experimental detection of histamine and leukotriene levels can be an objective and accurate method to clinically classify the allergic rhinitis types. Furthermore, individualized treatment based on allergic rhinitis classification can result in a good treatment efficacy.