cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17017744
title: Dummy Dataset – Milking Robot Records for AgriFoodTEF Data Space Demonstrator

description: This dummy dataset simulates per-milking records from an automated milking robot. It contains cow identifiers, lactation stage, milking intervals, milk yield and composition, udder health indicators, animal activity, body weight, and robot feeding data. The dataset was generated for demonstration purposes in the AgriFoodTEF Data Space and does not represent real farm data.

 

1. cow_id

Unique identifier for each cow (ear tag or transponder ID).

 

2. lactation_number

Number of the current lactation cycle (1 = first lactation, 2 = second, etc.).

 

3. days_in_milk

Number of days since calving.

 

4. milking_id

Unique identifier for each milking event (incremental counter).

 

5. milking_datetime

Date and time when the milking took place.

 

6. milking_interval

Hours since the cow’s previous milking.

 

7. milk_yield_kg

Total milk yield (kg) for the milking session.

 

8. milk_flow_avg

Average milk flow during the milking (kg/min).

 

9. milk_flow_max

Maximum milk flow observed during the milking (kg/min).

 

10. milking_duration_min

Duration of the milking event (minutes).

 

11. fat_pct

Percentage of fat in the milk sample.

 

12. protein_pct

Percentage of protein in the milk sample.

 

13. lactose_pct

Percentage of lactose in the milk sample.

 

14. somatic_cell_count

Somatic cell count in the milk (indicator of udder health/mastitis).

 

15. conductivity_avg

Average electrical conductivity of the milk (mS/cm) – used as a mastitis indicator.

 

16. temperature_milk

Milk temperature (°C) measured during milking.

 

17. rumination_min

Time spent ruminating (chewing cud) before/around the milking event (minutes/day-part).

 

18. activity_level

Activity score of the cow (arbitrary units from sensors, higher = more active).

 

19. body_weight

Body weight of the cow measured on the robot’s scale (kg).

 

20. feed_intake_robot

Amount of concentrate feed consumed in the robot during the milking (kg).
DOI: 10.5281/zenodo.17045457
title: Dummy Dataset – Milking Robot Records for AgriFoodTEF Data Space Demonstrator

description: This dummy dataset simulates per-milking records from an automated milking robot. It contains cow identifiers, lactation stage, milking intervals, milk yield and composition, udder health indicators, animal activity, body weight, and robot feeding data. The dataset was generated for demonstration purposes in the AgriFoodTEF Data Space and does not represent real farm data.

 

1. cow_id

Unique identifier for each cow (ear tag or transponder ID).

 

2. lactation_number

Number of the current lactation cycle (1 = first lactation, 2 = second, etc.).

 

3. days_in_milk

Number of days since calving.

 

4. milking_id

Unique identifier for each milking event (incremental counter).

 

5. milking_datetime

Date and time when the milking took place.

 

6. milking_interval

Hours since the cow’s previous milking.

 

7. milk_yield_kg

Total milk yield (kg) for the milking session.

 

8. milk_flow_avg

Average milk flow during the milking (kg/min).

 

9. milk_flow_max

Maximum milk flow observed during the milking (kg/min).

 

10. milking_duration_min

Duration of the milking event (minutes).

 

11. fat_pct

Percentage of fat in the milk sample.

 

12. protein_pct

Percentage of protein in the milk sample.

 

13. lactose_pct

Percentage of lactose in the milk sample.

 

14. somatic_cell_count

Somatic cell count in the milk (indicator of udder health/mastitis).

 

15. conductivity_avg

Average electrical conductivity of the milk (mS/cm) – used as a mastitis indicator.

 

16. temperature_milk

Milk temperature (°C) measured during milking.

 

17. rumination_min

Time spent ruminating (chewing cud) before/around the milking event (minutes/day-part).

 

18. activity_level

Activity score of the cow (arbitrary units from sensors, higher = more active).

 

19. body_weight

Body weight of the cow measured on the robot’s scale (kg).

 

20. feed_intake_robot

Amount of concentrate feed consumed in the robot during the milking (kg).
DOI: 10.6084/m9.figshare.30041632
title: Supplementary Material for: A Case of Uterine Serous Carcinoma in a Patient with a Germline BRCA1 Mutation: Genomic Profiling Reveals an Ovarian Cancer-like Molecular Signature

description: Introduction: Uterine serous carcinoma (USC) is a highly aggressive histological subtype of endometrial cancer that causes almost 40% of deaths related to this cancer, despite accounting for only about 10% of cases of endometrial cancer. This high mortality rate is due to the high metastatic potential of USC and its resistance to treatment. Genetic alterations frequently associated with USC include mutations in TP53 and PIK3CA. BRCA1, a major causative gene of hereditary breast and ovarian cancer (HBOC), may also contribute to the risk of USC. Case Presentation: We describe a case of USC with a germline pathogenic BRCA1 mutation, and we review the literature in this area. The patient was a 50-year-old woman who had abnormal genital bleeding and was diagnosed with USC by endometrial biopsy. The patient had a history of metachronous breast cancer. Surgical treatment was performed, and a subsequent pathological examination of the resected specimen indicated serous carcinoma in the endometrium and high-grade serous carcinoma in the left fallopian tube. Immunohistochemical analysis confirmed that these tumors originated from different primary sites, leading to diagnosis of synchronous malignancies. Genetic testing identified a germline BRCA1 mutation, and comprehensive genomic profiling of the uterine tumor revealed additional pathogenic mutations in TP53, MAP3K1, RB1, and MYC. Discussion: Some of these mutations are not common in USC, suggesting a unique genetic profile for USC associated with BRCA1 mutation. This finding suggests that BRCA1-associated USC may be sensitive to PARP inhibitors, and also raises the question of whether risk-reducing hysterectomy should be considered for patients with BRCA1 mutation. Conclusion: USC with a BRCA1 mutation may have molecular characteristics distinct from those of sporadic USC, and further accumulation and analysis of such cases are needed to evaluate the clinical implications.
DOI: 10.6084/m9.figshare.30041632.v1
title: Supplementary Material for: A Case of Uterine Serous Carcinoma in a Patient with a Germline BRCA1 Mutation: Genomic Profiling Reveals an Ovarian Cancer-like Molecular Signature

description: Introduction: Uterine serous carcinoma (USC) is a highly aggressive histological subtype of endometrial cancer that causes almost 40% of deaths related to this cancer, despite accounting for only about 10% of cases of endometrial cancer. This high mortality rate is due to the high metastatic potential of USC and its resistance to treatment. Genetic alterations frequently associated with USC include mutations in TP53 and PIK3CA. BRCA1, a major causative gene of hereditary breast and ovarian cancer (HBOC), may also contribute to the risk of USC. Case Presentation: We describe a case of USC with a germline pathogenic BRCA1 mutation, and we review the literature in this area. The patient was a 50-year-old woman who had abnormal genital bleeding and was diagnosed with USC by endometrial biopsy. The patient had a history of metachronous breast cancer. Surgical treatment was performed, and a subsequent pathological examination of the resected specimen indicated serous carcinoma in the endometrium and high-grade serous carcinoma in the left fallopian tube. Immunohistochemical analysis confirmed that these tumors originated from different primary sites, leading to diagnosis of synchronous malignancies. Genetic testing identified a germline BRCA1 mutation, and comprehensive genomic profiling of the uterine tumor revealed additional pathogenic mutations in TP53, MAP3K1, RB1, and MYC. Discussion: Some of these mutations are not common in USC, suggesting a unique genetic profile for USC associated with BRCA1 mutation. This finding suggests that BRCA1-associated USC may be sensitive to PARP inhibitors, and also raises the question of whether risk-reducing hysterectomy should be considered for patients with BRCA1 mutation. Conclusion: USC with a BRCA1 mutation may have molecular characteristics distinct from those of sporadic USC, and further accumulation and analysis of such cases are needed to evaluate the clinical implications.
DOI: 10.6084/m9.figshare.30041635
title: Supplementary Material for: Volatile Organic Compounds in Irritable Bowel Syndrome: Microbial Insights into Gut-Brain Dynamics and Clinical Applications

description: Background: Irritable Bowel Syndrome (IBS) affects 4.1% of the global population, posing a significant healthcare challenge due to its complex pathophysiology and limited treatment options. Gut microbiota-derived volatile organic compounds (VOCs) are increasingly recognized as key players in IBS, with the potential for non-invasive diagnostics and personalized management.
Summary: This review examines VOCs—such as short-chain fatty acids (SCFAs), hydrocarbons, and alcohols—as microbial metabolites influencing IBS through gut barrier function, inflammation, motility, and gut-brain signaling. Cross-sectional studies highlight the diagnostic accuracy of VOCs (Area Under the Curve (AUC) 0.76-0.99) in distinguishing IBS from healthy controls (HC) and conditions like inflammatory bowel disease (IBD), while longitudinal studies underscore their utility in predicting and reflecting microbial changes to microbiota-targeted therapies. Despite this promise, variability in study designs, methodological inconsistencies, and confounding factors hinder clinical translation.
Key Messages: VOCs illuminate the microbial underpinnings of IBS and its gut-brain interactions, offering a pathway to precise diagnosis and treatment stratification. However, their full potential awaits standardized sampling, analytical protocols, and robust clinical trials to ensure reliability and applicability in IBS care.
DOI: 10.6084/m9.figshare.30041635.v1
title: Supplementary Material for: Volatile Organic Compounds in Irritable Bowel Syndrome: Microbial Insights into Gut-Brain Dynamics and Clinical Applications

description: Background: Irritable Bowel Syndrome (IBS) affects 4.1% of the global population, posing a significant healthcare challenge due to its complex pathophysiology and limited treatment options. Gut microbiota-derived volatile organic compounds (VOCs) are increasingly recognized as key players in IBS, with the potential for non-invasive diagnostics and personalized management.
Summary: This review examines VOCs—such as short-chain fatty acids (SCFAs), hydrocarbons, and alcohols—as microbial metabolites influencing IBS through gut barrier function, inflammation, motility, and gut-brain signaling. Cross-sectional studies highlight the diagnostic accuracy of VOCs (Area Under the Curve (AUC) 0.76-0.99) in distinguishing IBS from healthy controls (HC) and conditions like inflammatory bowel disease (IBD), while longitudinal studies underscore their utility in predicting and reflecting microbial changes to microbiota-targeted therapies. Despite this promise, variability in study designs, methodological inconsistencies, and confounding factors hinder clinical translation.
Key Messages: VOCs illuminate the microbial underpinnings of IBS and its gut-brain interactions, offering a pathway to precise diagnosis and treatment stratification. However, their full potential awaits standardized sampling, analytical protocols, and robust clinical trials to ensure reliability and applicability in IBS care.
DOI: 10.15468/dl.5z7f5n
title: Occurrence Download

description: A dataset containing 56075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tetraonid line transect surveys from Norway: Data from Fjellstyrene"
 ]
}

 The dataset includes 56075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022123-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7fhrfa
title: Occurrence Download

description: A dataset containing 56075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tetraonid line transect surveys from Norway: Data from Fjellstyrene"
 ]
}

 The dataset includes 56075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022122-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g4nn6p
title: Occurrence Download

description: A dataset containing 56075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tetraonid line transect surveys from Norway: Data from Fjellstyrene"
 ]
}

 The dataset includes 56075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022125-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pgtcvh
title: Occurrence Download

description: A dataset containing 2403 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((26.71144 28.0282,13.99367 -60.65249,148.38959 -61.68366,146.67098 -31.55056,141.40055 -19.40566,144.95236 -4.62554,132.34916 -2.21948,115.5067 1.67606,99.92457 7.97766,101.07031 19.77883,54.20933 35.47554,26.71144 28.0282))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Orcinus orca"
 ]
}

 The dataset includes 2403 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022138-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yyfdd4
title: Occurrence Download

description: A dataset containing 181 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Salmo macrostigma)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 181 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022139-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30041620
title: AI-Driven Personalization in Digital Marketing: Algorithmic Approaches and Applications in the Life Sciences Industry

description: This paper explores the strategic application of AI-driven personalization in digital marketing, with a specific focus on the highly regulated and sensitive life sciences industry. Bridging the fields of business management, industrial microbiology, and AI, it demonstrates how sophisticated algorithms can enhance engagement and drive business growth in specialized markets like pharmaceuticals, biotechnology, and food tech. The paper outlines key AI algorithms—including collaborative filtering, reinforcement learning, and neural networks—and examines their specific applications through illustrative case studies. It concludes by discussing the ethical considerations and future potential of these technologies in a life sciences context, highlighting their role in creating more effective, targeted, and compliant marketing campaigns.
DOI: 10.6084/m9.figshare.30041620.v1
title: AI-Driven Personalization in Digital Marketing: Algorithmic Approaches and Applications in the Life Sciences Industry

description: This paper explores the strategic application of AI-driven personalization in digital marketing, with a specific focus on the highly regulated and sensitive life sciences industry. Bridging the fields of business management, industrial microbiology, and AI, it demonstrates how sophisticated algorithms can enhance engagement and drive business growth in specialized markets like pharmaceuticals, biotechnology, and food tech. The paper outlines key AI algorithms—including collaborative filtering, reinforcement learning, and neural networks—and examines their specific applications through illustrative case studies. It concludes by discussing the ethical considerations and future potential of these technologies in a life sciences context, highlighting their role in creating more effective, targeted, and compliant marketing campaigns.
DOI: 10.5281/zenodo.15702696
title: ECHOES OF US-AND-THEM: POPULIST NARRATIVES AND SOCIAL POLARIZATION IN HUNGARIAN DISCOURSE ON PLATFORM X - DATASET

description: Data, scripcts etc.
DOI: 10.5281/zenodo.15675698
title: Comments on X

description: The data set (comments from X) I used for my research „ECHOES OF US-AND-THEM: POPULIST NARRATIVES AND SOCIAL POLARIZATION IN HUNGARIAN DISCOURSE ON PLATFORM X”
DOI: 10.15468/dl.v3ex3c
title: Occurrence Download

description: A dataset containing 56075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tetraonid line transect surveys from Norway: Data from Fjellstyrene"
 ]
}

 The dataset includes 56075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022127-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/nghlnq
title: Supplementary online appendix for: Thomann, E. (2025). Explaining regulatory intermediaries' compliance through the Accountability Regimes Framework.

description: Text:
Supplementary online materials for:
Explaining regulatory intermediaries’ compliance through the Accountability Regimes Framework, Policy & Society, DOI: 10.1093/polsoc/puaf029
Eva Thomann, Department of Politics and Public Administration, University of Konstanz, Germany, Eva.thomann@uni-konstanz.de
Contains:
- supplementary online appendix 
- replication materials (R codes and datasets)
DOI: 10.15468/dl.p72jsw
title: Occurrence Download

description: A dataset containing 56075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tetraonid line transect surveys from Norway: Data from Fjellstyrene"
 ]
}

 The dataset includes 56075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022126-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p9ebr3
title: Occurrence Download

description: A dataset containing 56075 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Tetraonid line transect surveys from Norway: Data from Fjellstyrene"
 ]
}

 The dataset includes 56075 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022128-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2djfjx
title: CCDC 2220329: Experimental Crystal Structure Determination

description: Related Article: Bo, He|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f1b50
title: CCDC 2235601: Experimental Crystal Structure Determination

description: Related Article: Bo, He|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h6pdt
title: CCDC 2300336: Experimental Crystal Structure Determination

description: Related Article: YOGESH BAIRAGI, Sandip Porey, Sai V. C. Vummaleti, Xinglong Zhang, Goutam Kumar Ph.D. Lahiri, Debabrata Maiti|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2j3yh3
title: CCDC 2327495: Experimental Crystal Structure Determination

description: Related Article: Hu Fang, Zuowei Sun, Shaokun Tao, Tianhua Cui, Qianhui Wu, Fanding Zhou, Xianwen Zhang, Weichao Xue, Chun-Chun Zhang, Yuqiao Zhou, Jiaqi Xu, Ruixiang Li, Haiyan Fu, Hua Chen, Xueli Zheng|2025|J.Catalysis|450|116285|doi:10.1016/j.jcat.2025.116285
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.18150/up5h0r
title: Inhibition of BK channels by GABAb receptors enhances intrinsic excitability of layer 2/3 vasoactive intestinal polypeptide-expressing interneurons in mouse neocortex

description: Datasets for the publication titled: Bogaj K, Urban-Ciecko J. Inhibition of BK channels by GABAb receptors enhances intrinsic excitability of layer 2/3 vasoactive intestinal polypeptide-expressing interneurons in mouse neocortex. J Physiol. 2025 Mar;603(5):1171-1196. doi: 10.1113/JP286439. Epub 2025 Feb 3. PMID: 39901494; PMCID: PMC11870045.Raw data contains electrophysiological records in *.abf format (Clampfit, Molecular Devices, free to open and analysis).Please consult the Readme.odt file for additional information. For more details see related publication or contact the corresponding author.
DOI: 10.5517/ccdc.csd.cc2nbqsj
title: CCDC 2453178: Experimental Crystal Structure Determination

description: Related Article: LI JIAQIAO|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2nbqvl
title: CCDC 2453180: Experimental Crystal Structure Determination

description: Related Article: Shan Zhang|2025|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.