cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30665177
title: Blood (POS) untargeted metabolomics raw data

description: Metabolomic analyses of blood samples from 50 Hunner-type IC/BPS patients and 30 healthy controls were performed at Shanghai Applied Protein Technology Co. Ltd. (Shanghai, China). 100 µL of supernatant was then mixed with 400 µL of ice-cold methanol/acetonitrile (1:1, v/v) to precipitate proteins, followed by vortexing and a second centrifugation at 15,000 × g for 15 min at 4 °C. The resulting supernatant was collected for LC-MS/MS analysis. Using a UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex). Processed data were normalized and subjected to multivariate analysis, including Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Variable importance in projection (VIP) score was calculated from the OPLS-DA model to evaluate each metabolite's contribution to group separation. Metabolites with VIP ≥ 1 and P &lt; 0.05 were considered statistically significant. Functional prediction of differentially abundant metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
DOI: 10.6084/m9.figshare.30665177.v1
title: Blood (POS) untargeted metabolomics raw data

description: Metabolomic analyses of blood samples from 50 Hunner-type IC/BPS patients and 30 healthy controls were performed at Shanghai Applied Protein Technology Co. Ltd. (Shanghai, China). 100 µL of supernatant was then mixed with 400 µL of ice-cold methanol/acetonitrile (1:1, v/v) to precipitate proteins, followed by vortexing and a second centrifugation at 15,000 × g for 15 min at 4 °C. The resulting supernatant was collected for LC-MS/MS analysis. Using a UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex). Processed data were normalized and subjected to multivariate analysis, including Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Variable importance in projection (VIP) score was calculated from the OPLS-DA model to evaluate each metabolite's contribution to group separation. Metabolites with VIP ≥ 1 and P &lt; 0.05 were considered statistically significant. Functional prediction of differentially abundant metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
DOI: 10.6084/m9.figshare.30665177.v2
title: Blood (POS) untargeted metabolomics raw data

description: Metabolomic analyses of blood samples from 50 Hunner-type IC/BPS patients and 30 healthy controls were performed at Shanghai Applied Protein Technology Co. Ltd. (Shanghai, China). 100 µL of supernatant was then mixed with 400 µL of ice-cold methanol/acetonitrile (1:1, v/v) to precipitate proteins, followed by vortexing and a second centrifugation at 15,000 × g for 15 min at 4 °C. The resulting supernatant was collected for LC-MS/MS analysis. Using a UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex). Processed data were normalized and subjected to multivariate analysis, including Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Variable importance in projection (VIP) score was calculated from the OPLS-DA model to evaluate each metabolite's contribution to group separation. Metabolites with VIP ≥ 1 and P &lt; 0.05 were considered statistically significant. Functional prediction of differentially abundant metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
DOI: 10.15468/dl.bp5kwx
title: Occurrence Download

description: A dataset containing 891 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hippopus hippopus, Chama asinus, Chama hippopus, Hippopus brassica, Hippopus equinus, Hippopus maculatus, Tridachnes ungula)",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 891 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057347-251120083545085/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.30655688
title: Blood (NEG) untargeted metabolomics raw data

description: Metabolomic analyses of blood samples from 50 Hunner-type IC/BPS patients and 30 healthy controls were performed at Shanghai Applied Protein Technology Co. Ltd. (Shanghai, China). 100 µL of supernatant was then mixed with 400 µL of ice-cold methanol/acetonitrile (1:1, v/v) to precipitate proteins, followed by vortexing and a second centrifugation at 15,000 × g for 15 min at 4 °C. The resulting supernatant was collected for LC-MS/MS analysis. Using a UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex). Processed data were normalized and subjected to multivariate analysis, including Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Variable importance in projection (VIP) score was calculated from the OPLS-DA model to evaluate each metabolite's contribution to group separation. Metabolites with VIP ≥ 1 and P &lt; 0.05 were considered statistically significant. Functional prediction of differentially abundant metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
DOI: 10.6084/m9.figshare.30655688.v1
title: Blood (NEG) untargeted metabolomics raw data

description: Metabolomic analyses of blood samples from 50 Hunner-type IC/BPS patients and 30 healthy controls were performed at Shanghai Applied Protein Technology Co. Ltd. (Shanghai, China). 100 µL of supernatant was then mixed with 400 µL of ice-cold methanol/acetonitrile (1:1, v/v) to precipitate proteins, followed by vortexing and a second centrifugation at 15,000 × g for 15 min at 4 °C. The resulting supernatant was collected for LC-MS/MS analysis. Using a UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex). Processed data were normalized and subjected to multivariate analysis, including Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Variable importance in projection (VIP) score was calculated from the OPLS-DA model to evaluate each metabolite's contribution to group separation. Metabolites with VIP ≥ 1 and P &lt; 0.05 were considered statistically significant. Functional prediction of differentially abundant metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
DOI: 10.6084/m9.figshare.30655688.v2
title: Blood (NEG) untargeted metabolomics raw data

description: Metabolomic analyses of blood samples from 50 Hunner-type IC/BPS patients and 30 healthy controls were performed at Shanghai Applied Protein Technology Co. Ltd. (Shanghai, China). 100 µL of supernatant was then mixed with 400 µL of ice-cold methanol/acetonitrile (1:1, v/v) to precipitate proteins, followed by vortexing and a second centrifugation at 15,000 × g for 15 min at 4 °C. The resulting supernatant was collected for LC-MS/MS analysis. Using a UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (TripleTOF 6600, AB Sciex). Processed data were normalized and subjected to multivariate analysis, including Pareto-scaled principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Variable importance in projection (VIP) score was calculated from the OPLS-DA model to evaluate each metabolite's contribution to group separation. Metabolites with VIP ≥ 1 and P &lt; 0.05 were considered statistically significant. Functional prediction of differentially abundant metabolites was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.
DOI: 10.6084/m9.figshare.30646847
title: Human fecal 16S rRNA sequencing raw data

description: 16S rRNA sequencing was performed on fecal samples from 32 Hunner-type IC/BPS patients and 30 healthy controls. The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified using primers 338F and 806R on a GeneAmp 9700 PCR system. Sequencing was conducted on an Illumina MiSeq PE300 platform (Illumina, San Diego, USA) according to the standard protocols of Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). Alpha diversity indices (Chao, ACE, Shannon, Simpson) were calculated to assess within-sample diversity, and the coverage index was used to evaluate sequencing depth. Beta diversity (inter-individual variation) was analyzed via principal coordinates analysis (PCoA) and the Adonis test. Differentially abundant taxa between groups were identified using Linear Discriminant Analysis Effect Size (LEfSe).
DOI: 10.6084/m9.figshare.30646847.v1
title: Human fecal 16S rRNA sequencing raw data

description: 16S rRNA sequencing was performed on fecal samples from 32 Hunner-type IC/BPS patients and 30 healthy controls. The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified using primers 338F and 806R on a GeneAmp 9700 PCR system. Sequencing was conducted on an Illumina MiSeq PE300 platform (Illumina, San Diego, USA) according to the standard protocols of Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). Alpha diversity indices (Chao, ACE, Shannon, Simpson) were calculated to assess within-sample diversity, and the coverage index was used to evaluate sequencing depth. Beta diversity (inter-individual variation) was analyzed via principal coordinates analysis (PCoA) and the Adonis test. Differentially abundant taxa between groups were identified using Linear Discriminant Analysis Effect Size (LEfSe).
DOI: 10.6084/m9.figshare.30646847.v2
title: Human fecal 16S rRNA sequencing raw data

description: 16S rRNA sequencing was performed on fecal samples from 32 Hunner-type IC/BPS patients and 30 healthy controls. The V3–V4 hypervariable regions of the bacterial 16S rRNA gene were amplified using primers 338F and 806R on a GeneAmp 9700 PCR system. Sequencing was conducted on an Illumina MiSeq PE300 platform (Illumina, San Diego, USA) according to the standard protocols of Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). Alpha diversity indices (Chao, ACE, Shannon, Simpson) were calculated to assess within-sample diversity, and the coverage index was used to evaluate sequencing depth. Beta diversity (inter-individual variation) was analyzed via principal coordinates analysis (PCoA) and the Adonis test. Differentially abundant taxa between groups were identified using Linear Discriminant Analysis Effect Size (LEfSe).
DOI: 10.15468/dl.4733gs
title: Occurrence Download

description: A dataset listing the 20 species recorded in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Month is April",
 "TaxonKey is Puma concolor"
 ]
}

 The dataset's 20 records were derived from 92 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057342-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.awsfkh
title: Occurrence Download

description: A dataset listing the 12551 species recorded in GBIF matching the query:
{
 "PublishingOrg" : [
 "is cdef28b1-db4e-4c58-aa71-3c5238c2d0b5"
 ]
}

 The dataset's 12551 records were derived from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057345-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.stwftf
title: Occurrence Download

description: A dataset containing 598 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Psarisomus dalhousiae"
 ]
}

 The dataset includes 598 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057349-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gs3vmu
title: Occurrence Download

description: A dataset containing 30 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hippopus porcellanus)",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 30 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057350-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zea5xp
title: Occurrence Download

description: A dataset containing 56322 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rupicola peruvianus"
 ]
}

 The dataset includes 56322 records from 160 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057322-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14856123
title: MatchPlant: An Open-Source Pipeline for UAV-based Single-Plant Detection and Data Extraction

description: Description:

This dataset accompanies the research study “MatchPlant: An Open-Source Pipeline for UAV-Based Single-Plant Detection and Data Extraction.” It includes UAV (Unmanned Aerial Vehicle) images, annotated bounding boxes for plant detection, and a pre-trained Faster R-CNN model for detecting individual maize in UAV imagery. The dataset is designed to support research in high-throughput plant phenotyping, plant genetics research, and agricultural computer vision applications.

Dataset Content:



UAV images: Undistorted images created by OpenDroneMap software based on high-resolution RGB (Red-Green-Blue) images collected by UAV during the 2021 growing seasons. The images contain a maize field for plant genetics research.

Annotation file: Bounding box annotations in COCO (Common Objects in Context) format (.json files). The bounding boxes were drawn on the UAV images.

Pre-trained model: The Faster R-CNN (Faster Region-based Convolutional Neural Network) model was trained on the UAV images and the annotation file dataset to detect individual maize in plant genetics research.


Data Collection and Processing:



UAV images were captured at nadir angles using a high-resolution RGB camera (20 megapixels) mounted on a UAV.

Orthorectification and preprocessing were conducted using OpenDroneMap software.

Bounding boxes were manually created using developed by Python software (Module "4_bbox_drawer": GitHub: https://github.com/JacobWashburn-USDA/MatchPlant) and verified for individual plant detection.

The Faster R-CNN model was trained on undistorted images to improve detection accuracy.


Usage:

This dataset can be used to train, validate, and test deep learning models for single-maize detection in agricultural fields. It also supports research in high-throughput plant phenotyping and UAV-based plant monitoring.

Acknowledgments:

This research was supported in part by an appointment to the Agricultural Research Service (ARS) Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the U.S. Department of Energy (DOE) and the U.S. Department of Agriculture (USDA). ORISE is managed by ORAU under DOE contract number DE-SC0014664. Funding was provided by the United States Department of Agriculture, Agricultural Research Service, and SCINet Postdoctoral Fellows Program. All opinions expressed in this publication are the author’s and do not necessarily reflect the policies and views of USDA, DOE, or ORAU/ORISE.

Contact Information:For further inquiries regarding this dataset, please contact Jacob D. Washburn at jacob.washburn@usda.gov.
DOI: 10.5281/zenodo.14856122
title: MatchPlant: An Open-Source Pipeline for UAV-based Single-Plant Detection and Data Extraction

description: Description:

This dataset accompanies the research study “MatchPlant: An Open-Source Pipeline for UAV-Based Single-Plant Detection and Data Extraction.” It includes UAV (Unmanned Aerial Vehicle) images, annotated bounding boxes for plant detection, and a pre-trained Faster R-CNN model for detecting individual maize in UAV imagery. The dataset is designed to support research in high-throughput plant phenotyping, plant genetics research, and agricultural computer vision applications.

Dataset Content:



UAV images: Undistorted images created by OpenDroneMap software based on high-resolution RGB (Red-Green-Blue) images collected by UAV during the 2021 growing seasons. The images contain a maize field for plant genetics research.

Annotation file: Bounding box annotations in COCO (Common Objects in Context) format (.json files). The bounding boxes were drawn on the UAV images.

Pre-trained model: The Faster R-CNN (Faster Region-based Convolutional Neural Network) model was trained on the UAV images and the annotation file dataset to detect individual maize in plant genetics research.


Data Collection and Processing:



UAV images were captured at nadir angles using a high-resolution RGB camera (20 megapixels) mounted on a UAV.

Orthorectification and preprocessing were conducted using OpenDroneMap software.

Bounding boxes were manually created using developed by Python software (Module "4_bbox_drawer": GitHub: https://github.com/JacobWashburn-USDA/MatchPlant) and verified for individual plant detection.

The Faster R-CNN model was trained on undistorted images to improve detection accuracy.


Usage:

This dataset can be used to train, validate, and test deep learning models for single-maize detection in agricultural fields. It also supports research in high-throughput plant phenotyping and UAV-based plant monitoring.

Acknowledgments:

This research was supported in part by an appointment to the Agricultural Research Service (ARS) Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the U.S. Department of Energy (DOE) and the U.S. Department of Agriculture (USDA). ORISE is managed by ORAU under DOE contract number DE-SC0014664. Funding was provided by the United States Department of Agriculture, Agricultural Research Service, and SCINet Postdoctoral Fellows Program. All opinions expressed in this publication are the author’s and do not necessarily reflect the policies and views of USDA, DOE, or ORAU/ORISE.

Contact Information:For further inquiries regarding this dataset, please contact Jacob D. Washburn at jacob.washburn@usda.gov.
DOI: 10.14457/stou.the.2018.120
title: ผลของการให้การปรึกษาแบบรายบุคคลเพื่อส่งเสริมความคิดเชิงบวกแก่มารดาหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ในโรงพยาบาลสงขลา

description: การวิจัยครั้งนี้มีวัตถุประสงค์เพื่อ 1) เปรียบความคิดเชิงบวกของมารดากลุ่มทดลองหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ ก่อนและหลังการให้การปรึกษาแบบรายบุคคล และ2)เพื่อเปรียบเทียบความคิดเชิงบวกของมารดามารดาหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ กลุ่มทดลองที่ได้รับการให้การปรึกษาแบบรายบุคคลและกลุ่มควบคุมที่ได้รับการดูแลแบบปกติกลุ่มตัวอย่าง คือ มารดาหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ ในโรงพยาบาลสงขลา จำนวน14 คน โดยการเลือกแบบเจาะจง จากนั้นสุ่มอย่างง่ายเพื่อแบ่งเป็น 2 กลุ่ม คือกลุ่มควบคุม และกลุ่มทดลอง กลุ่มละ 7 คนเท่ากัน เครื่องมือที่ใช้ในการวิจัย ได้แก่ 1) แบบวัดความคิดเชิงบวกที่มีค่าความเที่ยงเท่ากับ .94 และ 2) โปรแกรมการให้การปรึกษาแบบรายบุคคลเพื่อส่งเสริมความคิดเชิงบวกแก่มารดาหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ ในโรงพยาบาลสงขลา สถิติที่ใช้ในการวิเคราะห์ข้อมูล ได้แก่ ค่ามัธยฐาน ส่วนเบี่ยงเบนควอไทล์ การทดสอบวิลคอกซันและการทดสอบแมนวิทนีย์ผลการวิจัย พบว่า 1) ภายหลังการให้การปรึกษา มารดากลุ่มทดลองหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ มีความคิดเชิงบวกสูงกว่าก่อนการทดลอง อย่างมีนัยสำคัญทางสถิติที่ระดับ .01 และ2) ภายหลังการให้การปรึกษา มารดากลุ่มทดลองหลังคลอดที่ตั้งครรภ์ไม่พึงประสงค์ มีความคิดเชิงบวก สูงกว่ากลุ่มควบคุม อย่างมีนัยสำคัญทางสถิติที่ระดับ.01 || This study aimed to 1) compare the positive thinking of Postpartum Motherswith Unwanted Pregnancy before and after individual counseling; and 2) compare thepositive thinking of Postpartum Mothers with Unwanted Pregnancy experimental groupand a control group after using the individual counseling.This research design was quasi-experimental. The samples were 14Postpartum Mothers with Unwanted Pregnancy in Songkhla Hospital who will have somany problems and will coping behaviors less than 50 percentile. Then, simplesampling was done to divide them into 2 groups, the experimental group and the controlgroup, 8 patients in each group. Research instruments were 1) the positive thinkingquestionnaires with Alpha’s Cronbach Coefficient reliability of .94, and 2) a individualcounseling program for enhancing Positive Thinking. The statistics were median,quartile deviation, Wilcoxon Matched Pairs Singed-Ranks Test and Mann-Whitney UTest.The results showed that 1) after receiving the individual counseling, theexperimental group of Postpartum Mothers with Unwanted Pregnancy had PositiveThinking higher than before with statistical significance at the level of 0.1, and 2) afterreceiving the individual counseling, the experimental group of Postpartum Motherswith Unwanted Pregnancy had Positive Thinking higher than the control group withstatistical significance at the 0.1 level
DOI: 10.14457/stou.the.2001.4
title: ความต้องการในการฝึกอบรมเพิ่มเติมของเกษตรกรผู้เลี้ยงโคนม ในจังหวัดอุดรธานี
DOI: 10.15468/dl.5d5rjc
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Keenocardium blandum, Cardium blandum, Cardium fucanum, Clinocardium blandum, Clinocardium fucanum, Clinocardium funcanum)",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1950"
 ]
}

 The dataset includes 36 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057351-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.92g5my
title: Occurrence Download

description: A dataset containing 160355 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cistus albidus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 160355 records from 355 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0057327-251120083545085/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/14203847
title: SOLANA Price Data Binance API (2020–Now)