cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.29876489
title: 富山県に産するタイ類・ツノゴケ類 チェックリスト. Checklist of Liverworts and Hornworts of Toyama Prefecture in Japan

description: A list of liverworts and hornworts found in Toyama Prefecture was compiled based on a survey of literature up to the end of January 2025, specimens collected by the authors, and specimen information on the web. It was found that 220 liverwort taxa and 7 hornwort taxa occur in Toyama Prefecture. Of these, 51 liverwort taxa and 2 hornwort taxa are new to Toyama Prefecture. A reexamination of previously reported documentary specimens has resulted in the removal of 9 liverwort taxa from the list due to incorrect identification.
DOI: 10.6084/m9.figshare.29876489.v1
title: 富山県に産するタイ類・ツノゴケ類 チェックリスト. Checklist of Liverworts and Hornworts of Toyama Prefecture in Japan

description: A list of liverworts and hornworts found in Toyama Prefecture was compiled based on a survey of literature up to the end of January 2025, specimens collected by the authors, and specimen information on the web. It was found that 220 liverwort taxa and 7 hornwort taxa occur in Toyama Prefecture. Of these, 51 liverwort taxa and 2 hornwort taxa are new to Toyama Prefecture. A reexamination of previously reported documentary specimens has resulted in the removal of 9 liverwort taxa from the list due to incorrect identification.
DOI: 10.15468/dl.y97ngz
title: Occurrence Download

description: A dataset containing 90561 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Geometry POLYGON((-79.03465 39.98885,-73.6776 38.59787,-65.13098 39.43608,-66.06963 42.52194,-65.13098 48.51228,-80.62062 48.51228,-79.95099 43.30597,-79.03465 39.98885))",
 "HasGeospatialIssue is false",
 "TaxonKey is Carnivora"
 ]
}

 The dataset includes 90561 records from 124 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007206-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wg2uds
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Brazil",
 "TaxonKey is Mimus gilvus antelius Oberholser, 1919",
 "Year 1849-2025"
 ]
}

 The dataset includes 23 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007216-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5nmbzb
title: Occurrence Download

description: A dataset listing the 207149 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "Continent is South America",
 "Country is Brazil",
 "Year 1858-2025"
 ]
}

 The dataset's 207149 records were derived from 1796 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007208-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.29kqh7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Macropus fuliginosus (Desmarest, 1817))",
 "Country is one of (Algeria, Angola, Benin, Botswana, British Indian Ocean Territory, Burkina Faso, Burundi, Cabo Verde, Cameroon, Central African Republic, Chad, Comoros, Congo, Congo, Democratic Republic of the, Côte d’Ivoire, Djibouti, Egypt, Equatorial Guinea, Eritrea, Eswatini, Ethiopia, French Southern Territories, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Libya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mayotte, Morocco, Mozambique, Namibia, Niger, Nigeria, Réunion, Rwanda, Saint Helena, Ascension and Tristan da Cunha, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, South Sudan, Sudan, Tanzania, United Republic of, Togo, Tunisia, Uganda, Western Sahara, Zambia, Zimbabwe)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015970-250525065834625/datasets/export for details.
DOI: 10.15468/dl.bjw9gz
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Macropus fuliginosus (Desmarest, 1817))",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015971-250525065834625/datasets/export for details.
DOI: 10.6084/m9.figshare.30614921
title: fig_test

description: test
DOI: 10.6084/m9.figshare.30614921.v1
title: fig_test

description: test
DOI: 10.15468/dl.ekyvjr
title: Occurrence Download

description: A dataset listing the 184280 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "OccurrenceStatus is Present",
 "TaxonKey is Mollusca"
 ]
}

 The dataset's 184280 records were derived from 5615 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0031721-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17652386
title: A phase-modulation interferometer for intense, ultrashort, near-infrared laser pulses
DOI: 10.5281/zenodo.17652385
title: A phase-modulation interferometer for intense, ultrashort, near-infrared laser pulses
DOI: 10.5281/zenodo.17694320
title: DSEBench: DSEBench: A Test Collection for Dataset Search with Examples

description: DSEBench: A Test Collection for Dataset Search with Examples

 

DSEBench is a comprehensive test collection designed to support the evaluation of two complex information retrieval tasks in the dataset domain:





Dataset Search with Examples (DSE): A task that requires retrieving candidate datasets ($D_c$) that are both relevant to a textual query ($q$) and similar to a set of known relevant target datasets ($D_t$).




Explainable DSE: An extension that requires identifying the specific metadata fields that explain the result dataset's relevance and similarity.



This archive includes the essential data files, relevance judgments, and baseline results required to reproduce and benchmark models for DSE and Explainable DSE.

 



 

Key Components of DSEBench

The collection is built upon 46,615 candidate datasets collected from NTCIR, and includes the following data resources:





Datasets: Metadata for 46,615 datasets, each with fields including id, title, description, tags, author, and summary.




Queries: 3,979 keyword queries, including both NTCIR queries and generated queries.




Test and Training Cases: 5,840 cases, each linking a query_id and a target_dataset_id, used to define the DSE input.




Relevance Judgments: A total of 130,000+ judgments are provided:





7,415 Human-Annotated Judgments.




122,585 LLM-Annotated Judgments.




Each judgment provides scores for query relevance (query_rel) and target similarity (target_sim), along with field-level scores (field_query_rel, field_target_sim) for explaining the judgments.






Predefined Splits: Files are included to ensure comparable evaluation, providing 5-Fold splits and an Annotators split for training, validation, and test sets.



 

Baselines and Source Code

This release also provides complete experimental results and source code for various baseline models:





Retrieval Models (7): TF-IDF, BM25, BGE, GTE, ColBERTv2, coCondenser, and DPR.




Reranking Models (4): Stella, SFR, BGE-reranker, and LLM (GLM-4-Plus).




Explanation Methods (4): Feature Ablation, LIME, SHAP, and LLM explainer.



The complete implementation source code, dependencies, and detailed documentation are available in the associated GitHub repository, ensuring full reproducibility.

 

License and Persistence

All data and software source code included in this test collection are licensed under the Apache License 2.0. This permanent Zenodo record, identified by its DOI, provides a stable, persistent, and citable archive of the resource, adhering to the highest standards of the FAIR principles.
DOI: 10.15468/dl.jgpc9k
title: Occurrence Download

description: A dataset containing 7 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bungarus bungaroides)",
 "Country is one of (China, India, Indonesia, Pakistan, Bangladesh, Japan, Philippines, Viet Nam, Türkiye, Iran (Islamic Republic of), Thailand, Myanmar, Korea, Republic of, Korea (Democratic People’s Republic of), Iraq, Afghanistan, Saudi Arabia, Uzbekistan, Malaysia, Yemen, Nepal, Sri Lanka, Kazakhstan, Syrian Arab Republic, Cambodia, Jordan, Azerbaijan, United Arab Emirates, Tajikistan, Israel, Lao People’s Democratic Republic, Lebanon, Kyrgyzstan, Turkmenistan, Singapore, Oman, Palestine, State of, Kuwait, Georgia, Mongolia, Armenia, Qatar, Bahrain, Timor-Leste, Cyprus, Bhutan, Maldives, Brunei Darussalam)",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 7 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007152-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13860690
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.6ezft7
title: Occurrence Download

description: A dataset containing 740 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Waarnemingen.be - Non-native animal occurrences in Flanders and the Brussels Capital Region, Belgium",
 "Geometry POLYGON((5.61743 50.96885,5.84888 50.96885,5.84888 51.09783,5.61743 51.09783,5.61743 50.96885))",
 "HasGeospatialIssue is false",
 "TaxonKey is Vespa velutina"
 ]
}

 The dataset includes 740 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007153-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17707826
title: land cover dataset of Sichuan Prrovince from 1985 to 2023 at 30-m resolution

description: The dataset provides 30-m resolution land-cover maps for Sichuan Province for the years 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2023. Each map is delivered as a GeoTIFF file and contains pixel values ranging from 0 to 9, representing the following land-cover classes:





0 – No data




1 – Built-up




2 – Grassland




3 – Bare land




4 – Forest




5 – Shrubland




6 – Water bodies




7 – Wetland




8 – Cropland 




9 – Snow/Ice



Visual inspection confirms that the 1985–2023 land-cover series is largely noise-free and provides consistent, reliable representations of all mapped classes. Accuracy assessment indicates an average overall accuracy (OA) of 89.6% across the nine time periods, with the highest OA (91.3%) in 2020 and the lowest (87.3%) in 1985. The average F1-score exceeds 85% for all classes. Among them, the water class achieves the highest F1-score, while shrubland and grassland exhibit comparatively lower accuracy.
DOI: 10.5281/zenodo.17707827
title: land cover dataset of Sichuan Prrovince from 1985 to 2023 at 30-m resolution

description: The dataset provides 30-m resolution land-cover maps for Sichuan Province for the years 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, and 2023. Each map is delivered as a GeoTIFF file and contains pixel values ranging from 0 to 9, representing the following land-cover classes:





0 – No data




1 – Built-up




2 – Grassland




3 – Bare land




4 – Forest




5 – Shrubland




6 – Water bodies




7 – Wetland




8 – Cropland 




9 – Snow/Ice



Visual inspection confirms that the 1985–2023 land-cover series is largely noise-free and provides consistent, reliable representations of all mapped classes. Accuracy assessment indicates an average overall accuracy (OA) of 89.6% across the nine time periods, with the highest OA (91.3%) in 2020 and the lowest (87.3%) in 1985. The average F1-score exceeds 85% for all classes. Among them, the water class achieves the highest F1-score, while shrubland and grassland exhibit comparatively lower accuracy.
DOI: 10.15468/dl.vknatt
title: Occurrence Download

description: A dataset containing 515 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bungarus fasciatus)",
 "Country is one of (China, India, Indonesia, Pakistan, Bangladesh, Japan, Philippines, Viet Nam, Türkiye, Iran (Islamic Republic of), Thailand, Myanmar, Korea, Republic of, Korea (Democratic People’s Republic of), Iraq, Afghanistan, Saudi Arabia, Uzbekistan, Malaysia, Yemen, Nepal, Sri Lanka, Kazakhstan, Syrian Arab Republic, Cambodia, Jordan, Azerbaijan, United Arab Emirates, Tajikistan, Israel, Lao People’s Democratic Republic, Lebanon, Kyrgyzstan, Turkmenistan, Singapore, Oman, Palestine, State of, Kuwait, Georgia, Mongolia, Armenia, Qatar, Bahrain, Timor-Leste, Cyprus, Bhutan, Maldives, Brunei Darussalam)",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 515 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007154-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17044/scilifelab.14124014
title: Swedish publications on COVID-19 and SARS-CoV-2 between May 2020 and May 2025

description: This page explores Swedish research related to COVID-19 over 5 years (May 2020 - May 2025). The manually curated dataset comprises publications about SARS-CoV-2/COVID-19 involving at least one author affiliated with a Swedish research institute/organisation. Each publication was tagged according to multiple factors, including subject (e.g. post-covid condition, vaccine research), type of publication (e.g. preprint, review, article), and the involvement of particular funders (e.g. the Swedish Research Council (Vetenskapsrådet)). Between May 2020 and May 2023, the list was compiled entirely manually after identifying articles using alerts from multiple resources, e.g. PubMed, Google Scholar, Web of Science, EuropePMC, MedRxiv, BioRxiv, Research square). From May 2023, the Europe PMC REST API was used to identify publications. The scripts used to do this are openly available on GitHub and can be reused for work with other pathogens.Visualisations based on this dataset, showing e.g. the number of publications over time and keywords according to funders involved in the research, are available on the Swedish Pathogens Portal. To see recent Swedish publications related to multiple infectious disease and pandemic preparedness topics, please visit the Swedish Pathogens Portal's publications page.Please note that, because the dataset is manually curated, some records may be missing or incomplete.
DOI: 10.17044/scilifelab.14124014.v1
title: Dataset of bibliographic information about publications on COVID-19 and SARS-CoV-19 by researchers affiliated with a university or research institute in Sweden

description: This is a metadata record for a continuously updated dataset of preprints and journal articles on SARS-CoV-2 and COVID-19 where at least one author has an affiliation with a Swedish university or research institute. The dataset is created as part of the Swedish COVID-19 Data Portal (https://covid19dataportal.se). The dataset is manually curated.<br>The most recent version can be browsed using the following link: https://covid19dataportal.se/publications/. <br>The most recent version can be downloaded as a .JSON file using the following link: https://publications-covid19.scilifelab.se/publications.json.<br><br>For each entry, the dataset contains information automatically imported from Crossref or PubMed such as: publication title, author list, abstract text, journal/preprint server name and other bibliographic information. In addition, each entry is manually assigned categories corresponding scientific field, publication type, acknowledged funder, associated data description and links/accession numbers. Please see the README.txt file for more information about available variables.<br><br>Researchers are welcome to use the data contained in the dataset for any projects. Please cite this metadata record upon use. We encourage reuse using the same CC BY 4.0 License.<br><br>The dataset is maintained using the Publications web-based reference database system, https://github.com/pekrau/Publications, built by Per Kraulis (https://github.com/pekrau) at the SciLifeLab Data Centre.
DOI: 10.17044/scilifelab.14124014.v2
title: Swedish publications on COVID-19 and SARS-CoV-2 between May 2020 and May 2025

description: This page explores Swedish research related to COVID-19 over 5 years (May 2020 - May 2025). The manually curated dataset comprises publications about SARS-CoV-2/COVID-19 involving at least one author affiliated with a Swedish research institute/organisation. Each publication was tagged according to multiple factors, including subject (e.g. post-covid condition, vaccine research), type of publication (e.g. preprint, review, article), and the involvement of particular funders (e.g. the Swedish Research Council (Vetenskapsrådet)). Between May 2020 and May 2023, the list was compiled entirely manually after identifying articles using alerts from multiple resources, e.g. PubMed, Google Scholar, Web of Science, EuropePMC, MedRxiv, BioRxiv, Research square). From May 2023, the Europe PMC REST API was used to identify publications. The scripts used to do this are openly available on GitHub and can be reused for work with other pathogens.Visualisations based on this dataset, showing e.g. the number of publications over time and keywords according to funders involved in the research, are available on the Swedish Pathogens Portal. To see recent Swedish publications related to multiple infectious disease and pandemic preparedness topics, please visit the Swedish Pathogens Portal's publications page.Please note that, because the dataset is manually curated, some records may be missing or incomplete.
DOI: 10.25625/08xeam/uyiyfu
title: Figure3f_description.pdf

description: :unav
DOI: 10.25625/08xeam/egycpk
title: Figure3f_trajectory.png

description: :unav
DOI: 10.25625/08xeam/3topia
title: ACTG1-KO_meshsize.tab

description: :unav
DOI: 10.25625/08xeam/vt09ut
title: WT_meshsize.tab

description: :unav
DOI: 10.25625/08xeam
title: Data for "A feedback circuitry involving γ-actin, β-actin and nonmuscle myosin-2 A controls tight junction and apical cortex mechanics"

description: This dataset contains a dscription of the typical pathway for analyzing the mesh size of apical cell cortices as well as the data for the replication of Figure 3f.
DOI: 10.25625/l5psdk/holkyj
title: NM2B-A6.tab

description: :unav
DOI: 10.25625/l5psdk/tlqzzs
title: NM2B-A4.tab

description: :unav
DOI: 10.25625/l5psdk/6pakle
title: Figure2_Description.pdf

description: :unav
DOI: 10.25625/l5psdk/rmbnu0
title: WT.tab

description: :unav
DOI: 10.25625/l5psdk
title: Data for "Nonmuscle Myosin-2B Regulates Apical Cortical Mechanics, ZO-1 Dynamics and Cell Size in MDCK Epithelial Cells"

description: This dataset contains replication data for Figure 2A, B and C.
DOI: 10.25919/maby-ak90
title: NBDL-HK3SPRRFJG5A1C
DOI: 10.25919/wt1r-ek92
title: NBDL-HK3RZTQHQ4Y8J5
DOI: 10.15468/dl.77xzpz
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Bungarus lividus)",
 "Country is one of (China, India, Indonesia, Pakistan, Bangladesh, Japan, Philippines, Viet Nam, Türkiye, Iran (Islamic Republic of), Thailand, Myanmar, Korea, Republic of, Korea (Democratic People’s Republic of), Iraq, Afghanistan, Saudi Arabia, Uzbekistan, Malaysia, Yemen, Nepal, Sri Lanka, Kazakhstan, Syrian Arab Republic, Cambodia, Jordan, Azerbaijan, United Arab Emirates, Tajikistan, Israel, Lao People’s Democratic Republic, Lebanon, Kyrgyzstan, Turkmenistan, Singapore, Oman, Palestine, State of, Kuwait, Georgia, Mongolia, Armenia, Qatar, Bahrain, Timor-Leste, Cyprus, Bhutan, Maldives, Brunei Darussalam)",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2025",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 13 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007156-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25919/96j5-nq61
title: NBDL-HK3SPRQQHH3RR7
DOI: 10.25919/8bnn-pm67
title: NBDL-HK3SMQFDPSN08F
DOI: 10.25919/c6y4-0g16
title: NBDL-HK3SMQF7JSJGHQ
DOI: 10.25919/y66j-sr53
title: NBDL-HK3RZTQEN4YXKH
DOI: 10.25919/bmw0-w083
title: NBDL-HK3SJ4CMGNSS5X
DOI: 10.25919/gmb5-an50
title: NBDL-HK3SDG6QJ3170H
DOI: 10.25919/ch5s-h466
title: NBDL-HK3SJ4DWGNRK2X
DOI: 10.25919/v7gw-1q80
title: NBDL-HK3SDG8EH3SWAY
DOI: 10.25919/33n2-aq37
title: NBDL-HK3S2V6RH9SV7V
DOI: 10.25919/c8kn-xz11
title: NBDL-HK3SDG7DP33CYS
DOI: 10.25919/00fd-d173
title: NBDL-HK3SPRRBJG54FW
DOI: 10.25919/kkz9-gd63
title: NBDL-HK3SJ4DAMNSPEN
DOI: 10.25919/cppv-sv24
title: NBDL-HK3RZTPXQ4WDAN
DOI: 10.25919/gezt-sv64
title: NBDL-HK3RZTQZK4ZRTD
DOI: 10.25919/e31b-b448
title: NBDL-HK3SJ4D4GNR0FX
DOI: 10.25919/0ek3-zb93
title: NBDL-HK3S2V8BG8V3DW
DOI: 10.25919/t9dr-2691
title: NBDL-HK3SPRRWGG2ZP8
DOI: 10.25919/7hhn-ke43
title: NBDL-HK3S2V74H9RWPB
DOI: 10.25919/b5np-my96
title: NBDL-HK3S9B55M3PEYF
DOI: 10.25919/hhj6-0476
title: NBDL-HK3SJ4D7PNR2R9
DOI: 10.25919/9skb-1693
title: NBDL-HK3S9B4WJ39GBV
DOI: 10.25919/fhz3-nj67
title: NBDL-HK3SMQE1PSM1RZ
DOI: 10.25919/h1ef-8068
title: NBDL-HK3SJ4DFPNRE59
DOI: 10.25919/0t34-kz40
title: NBDL-HK3RZTQDQ4Y2RN
DOI: 10.25919/ke90-xh36
title: NBDL-HK3SJ4CGGNS0ZD
DOI: 10.25919/hm51-gh10
title: NBDL-HK3S2V83G8VP0W
DOI: 10.25919/d0fp-fa26
title: NBDL-HK3SJ4DCGNRDRX
DOI: 10.25919/pats-cq63
title: NBDL-HK3SMQG2NSHYVR
DOI: 10.25919/dp1z-6p87
title: NBDL-HK3S2V7SK9V71F
DOI: 10.25919/9a4b-ny83
title: NBDL-HK3S2V86J8VV9G
DOI: 10.25919/38hz-we25
title: NBDL-HK3SJ4CQPNSVP9
DOI: 10.25919/zpnz-q873
title: NBDL-HK3SPRQVHH3YKQ
DOI: 10.25919/r9pf-hc80
title: NBDL-HK3SPRRGGG5CKR
DOI: 10.25919/nj5k-aw25
title: NBDL-HK3SMQD9QSD5RJ
DOI: 10.71947/arim.jpmxp1222nm0066-2
title: 800MHzナローボア固体高分解能NMRシステムによるカルシウムシリケート水和物の構造の金属イオンの吸着挙動
DOI: 10.25919/ap1y-cq40
title: NBDL-HK3SDG8JH3R96E
DOI: 10.25919/zx54-k761
title: NBDL-HK3SMQDVKSA1DT
DOI: 10.25919/xvq0-wb53
title: NBDL-HK3SJ4DXJNRJG1
DOI: 10.25919/qyka-a276
title: NBDL-HK3SMQDFKSDE9A
DOI: 10.25919/skv6-2c67
title: NBDL-HK3SJ4DEMNSGQ5
DOI: 10.25919/p422-6m82
title: NBDL-HK3S2V8CP8V5Y8