cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21227/b3cb-9828
title: "IEEE BioCAS 2025 Grand Challenge on Pediatric Leukemia Diagnosis"

description: "The AI recognition of bone marrow\/blood cell images has become one of the important research directions in the field of medical imaging. By analyzing bone marrow images, doctors can quickly and accurately diagnose and monitor a range of blood diseases such as leukemia, anemia, and others. However, traditional bone marrow image analysis usually requires doctors to spend a lot of time and effort, and the results are subject to subjective factors, leading to issues such as inconsistent diagnoses.In recent years, with the development of artificial intelligence and machine learning technologies, AI recognition technology based on deep learning for bone marrow images has gradually matured. A large body of research indicates that using deep learning algorithms can effectively automatically identify abnormal cells, blood components, and structural features in bone marrow images, thereby assisting doctors in diagnosis and treatment decisions.However, despite significant progress in deep learning for bone marrow image recognition, there are still some challenges. These include difficulties in dataset annotation, insufficient generalization ability of models, and limitations in hardware resources. Especially when deploying large deep learning models on mobile medical devices and edge computing platforms, the limited availability of hardware resources becomes a constraining factor.In order to further promote the development and application of bone marrow image AI recognition technology, we will hold a challenge competition for bone marrow cell image AI recognition. This event aims to invite researchers, scholars, and medical experts from around the world to jointly explore and innovate bone marrow image AI recognition technology, improve the accuracy and efficiency of bone marrow disease diagnosis. Through this challenge competition, we hope to leverage artificial intelligence technology to bring faster, more accurate, and reliable diagnostic solutions to the field of medical imaging, provide better auxiliary tools for clinical doctors, and promote the development of healthcare."
DOI: 10.15468/dl.fee2xe
title: Occurrence Download

description: A dataset containing 973 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Leontice L."
 ]
}

 The dataset includes 973 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004663-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j6hc29
title: Occurrence Download

description: A dataset containing 2302939 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Poecilus cupreus (Linnaeus, 1758), Pterostichus melanarius (Illiger, 1798), Cladochytrium caespitis Griffon & Maubl., Rhynchosporium orthosporum Caldwell, Phyllobius parvulus (Olivier, 1807), Amara convexior Stephens, 1828, Anthomyza gracilis Fallén, 1823, Cerodontha denticornis (Panzer, 1806), Psammotettix helvolus (Kirschbaum, 1868), Psammotettix confinis (Dahlbom, 1850), Graphocraerus ventralis (Fallén, 1806), Hebata solani (Curtis, 1846), Macrosteles cristatus (Ribaut, 1927), Psammotettix alienus (Dahlbom, 1850), Macrosteles sexnotatus (Fallén, 1806), Phyllobius betulinus (Bechstein & Scharfenberg, 1805), Euscelis incisa (Kirschbaum, 1858), Errastunus ocellaris (Fallén, 1806), Ochlodes venata faunus (Turati, 1905), Amblytylus nasutus (Kirschbaum, 1856), Empoasca decipiens Paoli, 1930, Eurygaster maura (Linnaeus, 1758), Tytthaspis sedecimpunctata (Linnaeus, 1758), Limothrips denticornis (Haliday, 1836), Haplothrips aculeatus (Fabricius, 1803), Chorthippus albomarginatus (De Geer, 1773), Amara similata (Gyllenhal, 1810), Laodelphax striatellus (Fallén, 1826), Limothrips cerealium (Haliday, 1836), Frankliniella tenuicornis (Uzel, 1895), Urocystis alopecuri A.B.Frank, Chlorotettix fallax Sanders & DeLong, 1922, Acherontia atropos Linnaeus, 1758, Anartia jatrophae (Linnaeus, 1763), Phomopsis citriodora Grove, Diplodina aloysiae Grove, Cephaloleia distincta Baly, 1885, Coereba flaveola (Linnaeus, 1758), Udaspes folus (Cramer, 1775), Notocrypta curvifascia (C.Felder & R.Felder, 1862), Notocrypta feisthamelii (Boisduval, 1832), Jamides alecto (Felder, 1860), Camponotus grandidieri Forel, 1886, Eagris sabadius maheta Evans, 1937, Cinnyris dussumieri (Hartlaub, 1861), Lasioglossum mahense (Cameron, 1908), Rhynchium brunneum (Fabricius, 1793), Polistes olivaceus (Deg., 1773), Ornidia obesa (Fabricius, 1775), Technomyrmex albipes (Smith, 1861))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2302939 records from 4141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004654-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zdjnmk
title: Occurrence Download

description: A dataset containing 37219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Belgium",
 "TaxonKey is one of (Crassula helmsii, Lithobates catesbeianus, Misgurnus mohoity, Myriophyllum aquaticum, Procambarus clarkii, Procambarus virginalis, Xenopus laevis, Zizania latifolia)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 37219 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010379-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18250881
title: A CONUS-wide Monthly Baseflow Dataset (1982-2022) for HUC8 Basins Derived from Random Forest Modeling

description: This dataset provides continuous monthly baseflow estimates for 2,185 Hydrologic Unit Code 8 (HUC8) basins across the contiguous United States (CONUS) spanning 41 years from 1982 to 2022. The data were generated using an optimized Random Forest machine learning model trained on observed baseflow measurements, incorporating 31 predictor variables including static watershed attributes (topography, soil properties), dynamic environmental variables (climate, vegetation, snow dynamics), and human activity indicators (land use proportions).
DOI: 10.5281/zenodo.18250882
title: A CONUS-wide Monthly Baseflow Dataset (1982-2022) for HUC8 Basins Derived from Random Forest Modeling

description: This dataset provides continuous monthly baseflow estimates for 2,185 Hydrologic Unit Code 8 (HUC8) basins across the contiguous United States (CONUS) spanning 41 years from 1982 to 2022. The data were generated using an optimized Random Forest machine learning model trained on observed baseflow measurements, incorporating 31 predictor variables including static watershed attributes (topography, soil properties), dynamic environmental variables (climate, vegetation, snow dynamics), and human activity indicators (land use proportions).
DOI: 10.5281/zenodo.18250956
title: Callianthe picta (Gillies ex Hook. & Arn.) Donnell. 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 16:43
DOI: 10.5281/zenodo.18250957
title: Callianthe picta (Gillies ex Hook. & Arn.) Donnell. 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 16:43
DOI: 10.15468/dl.d4np9y
title: Occurrence Download

description: A dataset containing 20755 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Blicca bjoerkna",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2015",
 "Year is less than or equal to 2019"
 ]
}

 The dataset includes 20755 records from 92 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010382-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b9us9a
title: Occurrence Download

description: A dataset containing 110 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.43.90_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 110 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010383-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eqrdkr
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "KingdomKey is Plantae",
 "Geometry POLYGON ((14.6801 50.21003, 14.68009 50.21006, 14.68009 50.21009, 14.68008 50.21012, 14.68007 50.21015, 14.68005 50.21018, 14.68004 50.21021, 14.68002 50.21023, 14.68 50.21026, 14.67998 50.21029, 14.67995 50.21031, 14.67993 50.21034, 14.6799 50.21036, 14.67987 50.21038, 14.67984 50.21041, 14.6798 50.21043, 14.67977 50.21045, 14.67973 50.21047, 14.67969 50.21048, 14.67965 50.2105, 14.67961 50.21051, 14.67957 50.21053, 14.67952 50.21054, 14.67948 50.21055, 14.67943 50.21056, 14.67939 50.21056, 14.67934 50.21057, 14.67929 50.21057, 14.67925 50.21057, 14.6792 50.21057, 14.67915 50.21057, 14.67911 50.21057, 14.67906 50.21057, 14.67901 50.21056, 14.67897 50.21056, 14.67892 50.21055, 14.67888 50.21054, 14.67883 50.21053, 14.67879 50.21051, 14.67875 50.2105, 14.67871 50.21048, 14.67867 50.21047, 14.67863 50.21045, 14.6786 50.21043, 14.67856 50.21041, 14.67853 50.21038, 14.6785 50.21036, 14.67847 50.21034, 14.67845 50.21031, 14.67842 50.21029, 14.6784 50.21026, 14.67838 50.21023, 14.67836 50.21021, 14.67835 50.21018, 14.67833 50.21015, 14.67832 50.21012, 14.67831 50.21009, 14.67831 50.21006, 14.6783 50.21003, 14.6783 50.21, 14.6783 50.20997, 14.67831 50.20994, 14.67831 50.20991, 14.67832 50.20988, 14.67833 50.20985, 14.67835 50.20982, 14.67836 50.20979, 14.67838 50.20977, 14.6784 50.20974, 14.67842 50.20971, 14.67845 50.20969, 14.67847 50.20966, 14.6785 50.20964, 14.67853 50.20962, 14.67856 50.20959, 14.6786 50.20957, 14.67863 50.20955, 14.67867 50.20953, 14.67871 50.20952, 14.67875 50.2095, 14.67879 50.20949, 14.67883 50.20947, 14.67888 50.20946, 14.67892 50.20945, 14.67897 50.20944, 14.67901 50.20944, 14.67906 50.20943, 14.67911 50.20943, 14.67915 50.20943, 14.6792 50.20943, 14.67925 50.20943, 14.67929 50.20943, 14.67934 50.20943, 14.67939 50.20944, 14.67943 50.20944, 14.67948 50.20945, 14.67952 50.20946, 14.67957 50.20947, 14.67961 50.20949, 14.67965 50.2095, 14.67969 50.20952, 14.67973 50.20953, 14.67977 50.20955, 14.6798 50.20957, 14.67984 50.20959, 14.67987 50.20962, 14.6799 50.20964, 14.67993 50.20966, 14.67995 50.20969, 14.67998 50.20971, 14.68 50.20974, 14.68002 50.20977, 14.68004 50.20979, 14.68005 50.20982, 14.68007 50.20985, 14.68008 50.20988, 14.68009 50.20991, 14.68009 50.20994, 14.6801 50.20997, 14.6801 50.21, 14.6801 50.21003))",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010384-260108223611665/datasets/export for details.
DOI: 10.57760/sciencedb.nbsdc.00315
title: Experimental and Theoretical Dataset on Decreasing Gas Holdup with Increasing Gas Flux in Millimetre–Micrometre Dual-Sized Bubble Columns
title: 毫米–微米双尺度气泡柱中：随气体通量增加而气含率降低的实验与理论研究数据集

description: This dataset focuses on the response characteristics of the system gas holdup and the interaction mechanism between dual-size bubbles within a bubble tower reactor in a coalescence and suppression system. It conducts a systematic quantitative comparative analysis between dual-size and single-size systems, centred on characterising gas-liquid contact and transfer capabilities under conditions where micrometre-scale and millimetre-scale bubbles coexist. Results indicate micron-scale bubbles dominate the contribution to system gas holdup. Furthermore, when millimetre-scale bubbles are progressively introduced into a fixed microbubble system, the system gas holdup exhibits a non-monotonic variation pattern. To explain these evolutionary characteristics, this study proposes a coupled model within the drift flux framework. The decline in gas holdup during the intermediate phase is attributed to increased rise velocities of micron-sized bubbles caused by interactions between dual-sized bubbles, thereby altering their residence and accumulation levels. Based on these observed patterns and the proposed model interpretation, this dataset provides mechanistic rationale and empirical support for optimising bubble tower operating parameters and structural design. It is particularly applicable to scenarios requiring high gas flux and enhanced gas-liquid mass transfer, such as wastewater oxidation, 1,4-butanediol synthesis, and electrolytic hydrogen production.
description: This dataset focuses on the response characteristics of the system gas holdup and the interaction mechanism between dual-size bubbles within a bubble tower reactor in a coalescence and suppression system. It conducts a systematic quantitative comparative analysis between dual-size and single-size systems, centred on characterising gas-liquid contact and transfer capabilities under conditions where micrometre-scale and millimetre-scale bubbles coexist. Results indicate micron-scale bubbles dominate the contribution to system gas holdup. Furthermore, when millimetre-scale bubbles are progressively introduced into a fixed microbubble system, the system gas holdup exhibits a non-monotonic variation pattern. To explain these evolutionary characteristics, this study proposes a coupled model within the drift flux framework. The decline in gas holdup during the intermediate phase is attributed to increased rise velocities of micron-sized bubbles caused by interactions between dual-sized bubbles, thereby altering their residence and accumulation levels. Based on these observed patterns and the proposed model interpretation, this dataset provides mechanistic rationale and empirical support for optimising bubble tower operating parameters and structural design. It is particularly applicable to scenarios requiring high gas flux and enhanced gas-liquid mass transfer, such as wastewater oxidation, 1,4-butanediol synthesis, and electrolytic hydrogen production.
DOI: 10.57760/sciencedb.nbsdc.00285
title: Dataset of Lactate derived from cancer-associated fibroblasts promotes alternative splicing and castration resistance in prostate cancer
title: Dataset of Lactate derived from cancer-associated fibroblasts promotes alternative splicing and castration resistance in prostate cancer

description: Dataset of uncropped image of WB, PCR and colony formation assay for the manuscript: Lactate derived from cancer-associated fibroblasts promotes alternative splicing and castration resistance in prostate cancer
description: Dataset of uncropped image of WB, PCR and colony formation assay for the manuscript: Lactate derived from cancer-associated fibroblasts promotes alternative splicing and castration resistance in prostate cancer
DOI: 10.57760/sciencedb.nbsdc.00211
title: Data for "Few-shot Estimation of Entanglement with Bell Measurement Assistance" (arXiv:2405.20696)
title: Data for "Few-shot Estimation of Entanglement with Bell Measurement Assistance" (arXiv:2405.20696)

description: This project contains the simulation of CS and RM methods under Gaussian noise.
description: This project contains the simulation of CS and RM methods under Gaussian noise.
DOI: 10.57760/sciencedb.nbsdc.00268
title: Defective Chinese Character Dataset of Stone Inscriptions from the Song Dynasty
title: 宋代石碑缺损汉字数据集

description: The Song Dynasty stone tablet missing Chinese character dataset includes 10 types of missing Chinese character image data, including "ze", "wei", "wu", "xue", "shu", etc. The image specifications are unified at 128 × 128 pixels, with 3-channel RGB images. The data directory structure is as follows:data/├─ze/           │ ├─Complete/      │ └─Damage/      │   ├─ze_1/    │   ├─ze_2/│   └─...
description: The Song Dynasty stone tablet missing Chinese character dataset includes 10 types of missing Chinese character image data, including "ze", "wei", "wu", "xue", "shu", etc. The image specifications are unified at 128 × 128 pixels, with 3-channel RGB images. The data directory structure is as follows:data/├─ze/           │ ├─Complete/      │ └─Damage/      │   ├─ze_1/    │   ├─ze_2/│   └─...
DOI: 10.15468/dl.q7g5fw
title: Occurrence Download

description: A dataset containing 9663 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Blicca bjoerkna",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 2020",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 9663 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010385-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18250950
title: ESTRATÉGIAS EMPRESARIAIS PARA CRESCIMENTO E SUSTENTABILIDADE

description: Ao longo das próximas páginas, exploraremos

estratégias empresariais que equilibram crescimento

econômico e responsabilidade socioambiental. Mais do

que um guia de gestão, este livro é um convite para

refletir sobre como podemos construir um futuro

empresarial mais eficiente, sustentável e lucrativo.
DOI: 10.5281/zenodo.18250951
title: ESTRATÉGIAS EMPRESARIAIS PARA CRESCIMENTO E SUSTENTABILIDADE

description: Ao longo das próximas páginas, exploraremos

estratégias empresariais que equilibram crescimento

econômico e responsabilidade socioambiental. Mais do

que um guia de gestão, este livro é um convite para

refletir sobre como podemos construir um futuro

empresarial mais eficiente, sustentável e lucrativo.
DOI: 10.15468/dl.qp68dg
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"equals","key":"GADM_LEVEL_2_GID","value":"USA.43.91_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 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010386-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n5pqrr
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "KingdomKey is Plantae",
 "Geometry POLYGON ((16.9609 49.73573, 16.96089 49.73576, 16.96089 49.73579, 16.96088 49.73582, 16.96087 49.73585, 16.96085 49.73588, 16.96084 49.73591, 16.96082 49.73594, 16.9608 49.73596, 16.96078 49.73599, 16.96075 49.73602, 16.96073 49.73604, 16.9607 49.73607, 16.96067 49.73609, 16.96064 49.73611, 16.9606 49.73613, 16.96057 49.73615, 16.96053 49.73617, 16.96049 49.73619, 16.96045 49.7362, 16.96041 49.73622, 16.96037 49.73623, 16.96032 49.73624, 16.96028 49.73625, 16.96023 49.73626, 16.96019 49.73627, 16.96014 49.73627, 16.96009 49.73628, 16.96005 49.73628, 16.96 49.73628, 16.95995 49.73628, 16.95991 49.73628, 16.95986 49.73627, 16.95981 49.73627, 16.95977 49.73626, 16.95972 49.73625, 16.95968 49.73624, 16.95963 49.73623, 16.95959 49.73622, 16.95955 49.7362, 16.95951 49.73619, 16.95947 49.73617, 16.95943 49.73615, 16.9594 49.73613, 16.95936 49.73611, 16.95933 49.73609, 16.9593 49.73607, 16.95927 49.73604, 16.95925 49.73602, 16.95922 49.73599, 16.9592 49.73596, 16.95918 49.73594, 16.95916 49.73591, 16.95915 49.73588, 16.95913 49.73585, 16.95912 49.73582, 16.95911 49.73579, 16.95911 49.73576, 16.9591 49.73573, 16.9591 49.7357, 16.9591 49.73567, 16.95911 49.73564, 16.95911 49.73561, 16.95912 49.73558, 16.95913 49.73555, 16.95915 49.73552, 16.95916 49.73549, 16.95918 49.73546, 16.9592 49.73544, 16.95922 49.73541, 16.95925 49.73538, 16.95927 49.73536, 16.9593 49.73533, 16.95933 49.73531, 16.95936 49.73529, 16.9594 49.73527, 16.95943 49.73525, 16.95947 49.73523, 16.95951 49.73521, 16.95955 49.7352, 16.95959 49.73518, 16.95963 49.73517, 16.95968 49.73516, 16.95972 49.73515, 16.95977 49.73514, 16.95981 49.73513, 16.95986 49.73513, 16.95991 49.73512, 16.95995 49.73512, 16.96 49.73512, 16.96005 49.73512, 16.96009 49.73512, 16.96014 49.73513, 16.96019 49.73513, 16.96023 49.73514, 16.96028 49.73515, 16.96032 49.73516, 16.96037 49.73517, 16.96041 49.73518, 16.96045 49.7352, 16.96049 49.73521, 16.96053 49.73523, 16.96057 49.73525, 16.9606 49.73527, 16.96064 49.73529, 16.96067 49.73531, 16.9607 49.73533, 16.96073 49.73536, 16.96075 49.73538, 16.96078 49.73541, 16.9608 49.73544, 16.96082 49.73546, 16.96084 49.73549, 16.96085 49.73552, 16.96087 49.73555, 16.96088 49.73558, 16.96089 49.73561, 16.96089 49.73564, 16.9609 49.73567, 16.9609 49.7357, 16.9609 49.73573))",
 "Year is greater than or equal to 2000",
 "Year is less than or equal to 2026"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010387-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18250965
title: Callianthe striata (G.F.Dicks. ex Lindl.) Donnell. 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 16:43
DOI: 10.5281/zenodo.18250966
title: Callianthe striata (G.F.Dicks. ex Lindl.) Donnell. 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 16:43
DOI: 10.5281/zenodo.18250934
title: Data-Micropenetration-test
DOI: 10.5281/zenodo.18250935
title: Data-Micropenetration-test
DOI: 10.25345/c5v980533
title: MassIVE MSV000100485 - The investigation of anticancer constituentions from the Artemisia annua based on the molecular networking
title: Studying the diterpenoid components with anticancer effects in Artemisia annua.
DOI: 10.5281/zenodo.18250967
title: Callitriche L. 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 16:43