cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.17012360.v2
title: Han et al., ms. 2 raw data (Figshare).xlsx

description: Raw data on elemental, isotopic and optical compositions of dissolved organic matter and particulate organic matter in surface sediments and waters from different seasons in the Yangtze River margin and adjancenet sea. <br>
DOI: 10.6084/m9.figshare.17012360.v1
title: Han et al., ms. 2 raw data (Figshare).xlsx

description: Raw data on elemental, isotopic and optical compositions of dissolved organic matter and particulate organic matter in surface sediments and waters from different seasons in the Yangtze River margin and adjancenet sea. <br>
DOI: 10.6084/m9.figshare.13892861
title: Appendix I

description: Appendix I: Genes that significantly changed in frequency during domestication.
DOI: 10.6084/m9.figshare.13892861.v3
title: Appendix I

description: Appendix I: Genes that significantly changed in frequency during domestication.
DOI: 10.6084/m9.figshare.13892861.v2
title: Appendix I

description: Appendix H: Genes that significantly changed in frequency during domestication.
DOI: 10.6084/m9.figshare.13893887
title: Appendix K

description: Appendix K Genes that significantly changed in frequency during breeding.
DOI: 10.6084/m9.figshare.13893887.v2
title: Appendix K

description: Appendix K Genes that significantly changed in frequency during breeding.
DOI: 10.6084/m9.figshare.17009831.v2
title: SCA1Bdata

description: The GRACE-FO SCA1B data product is obtained by combining the SCA1A data and IMU1A data through the Kalman filter. The date of the solution is 2018.06-2020.12.
DOI: 10.6084/m9.figshare.17019998
title: Appendix E

description: Appendix E: A list of PAV genes with 25 genes functionally characterised and genetically verified in soybean
DOI: 10.6084/m9.figshare.17019998.v1
title: Appendix E

description: Appendix E: A list of PAV genes with 25 genes functionally characterised and genetically verified in soybean
DOI: 10.6084/m9.figshare.17020004
title: Appendix N

description: Appendix N: The website link of the bioinformatics tools and online resources used in this thesis were summarised
DOI: 10.6084/m9.figshare.17020004.v1
title: Appendix N

description: Appendix N: The website link of the bioinformatics tools and online resources used in this thesis were summarised
DOI: 10.5281/zenodo.5638201
title: Chula-RBC-12-Dataset

description: Chula-RBC-12 Dataset is a dataset of red blood cell (RBC) blood smear images used in "<strong>Red Blood Cell Segmentation with Overlapping Cell Separation and Classification from an Imbalanced Dataset</strong>", containing 12 classes of RBC types consisting of 706 smear images that contain over 20,000 RBC cells. The dataset was collected at the Oxidation in Red Cell Disorders Research Unit, Chulalongkorn University in 2019 using a DS-Fi2-L3 Nikon microscope at 1000x magnification. The "Dataset" folder contains 706 RBC blood smear images with 640*480 resolution. The "Label" folder contains label data with the name of the corresponding image. The file can contain multiple lines. Each line is a label for a single RBC and stored in the following sequence: x coordinate y coordinate type of RBC in number RBC Types 0 Normal cell 1 Macrocyte 2 Microcyte 3 Spherocyte 4 Target cell 5 Stomatocyte 6 Ovalocyte 7 Teardrop 8 Burr cell 9 Schistocyte 10 uncategorized 11 Hypochromia If you use this dataset, please cite the following paper: <pre><code>@misc{naruenatthanaset2021red, title={Red Blood Cell Segmentation with Overlapping Cell Separation and Classification on Imbalanced Dataset}, author={Korranat Naruenatthanaset and Thanarat H. Chalidabhongse and Duangdao Palasuwan and Nantheera Anantrasirichai and Attakorn Palasuwan}, year={2021}, eprint={2012.01321}, archivePrefix={arXiv}, primaryClass={eess.IV} }</code></pre>
DOI: 10.5281/zenodo.5703785
title: 2020 Winter Gucheng Data

description: Aerosol composition, elemental composition, gaseous species and meteorological parameters measured at Gucheng in winter 2020.
DOI: 10.5281/zenodo.5703784
title: 2020 Winter Gucheng Data

description: Aerosol composition, elemental composition, gaseous species and meteorological parameters measured at Gucheng in winter 2020.
DOI: 10.6084/m9.figshare.17020028
title: The influence of the digital divide on emergency remote student-centred learning during the COVID-19 pandemic: A case study of journalism education

description: The data consists of vlogs created by second and third-year students from a university of technology over a month from June 1 to June 30, 2020. Vlogs are usually short videos produced by people as a means of articulating their reflections on an issue. They are a reflective tool that prompts oral self-evaluation (Brott 2021). They are also an archiving mechanism that allows one to observe how their reflections have changed over time. Every week for the first four weeks of online learning in 2020, the second and third-year students had to create vlogs where they reflected on teaching and learning during the pandemic and lockdown as a means of capturing their reflection-in-action (Little 2010). The vlogs were around a minute long to capture only those uppermost issues in the minds of students. The theme of the reflections was “Covid-19 and its impact on journalism and journalism education”.
DOI: 10.25345/c5v87p
title: MassIVE MSV000088386 - Proteomic changes associated with predator induced morphological defenses in Olympia oysters
title: Samples were collected and experiments performed by the laboratories of Tyler Evans and Eric Sanford. Samples represent a single biological replicate processed using an identical procedure, i.e., reduction/ alkylation and trypsin digestion as described in a previously published protocol (https://doi.org/10.1074/mcp.M113.029827). Data for each sample were acquired using regular bottom-up DDA proteomics. Biological mass spectrometry was performed and data analyzed using a workflow consisting of Compass Hystar 4.1, DataAnalysis 4.4, PEAKS Studio 8.5, Mascot 2.2.7, X!Tandem Alanine, and Scaffold 4.8 in the K&uumlltz laboratory.
DOI: 10.15473/1830229
title: RITE Gen5 KHPS Performance - Period A

description: Includes Kinetic Hydropower System (KHPS) Turbine performance data from the RITE Gen5 KHPS turbine at the 5 meter size. This data was collected over Period A which was a 39 day span ending on 11/12/2021. This data was collected under the European Marine Energy Centre (EMEC) power performance assessment. Along with performance data, the data includes setup data, project metadata, and characteristic data for RITE Gen5 KHPS (5m) turbine.
DOI: 10.25345/c5qc5q
title: MassIVE MSV000088387 - Human oocyte proteome and secretome
title: The proteome and secretome of human oocytes was studied by shotgun LCMSMS, starting from pools of 100 cells. Exploiting SP3, a novel technology for proteomic sample preparation using magnetic beads, we scaled down proteome analysis to single cells. Despite the low protein content of only ~100ng per cell, we consistently identified ~450 proteins from individual oocytes. When comparing proteomes of individual oocytes at the germinal vesicle (GV) and metaphase II (MII) stage by label-free quantification, we found several proteins preferentially expressed in matuare and immature cells. This study demonstrates that an innovative proteomics workflow facilitates analysis of single human oocytes to investigate human oocyte biology and pre-implantation development. The approach presented here paves the way for quantitative proteomics in other quantity-limited tissues and cell types.
DOI: 10.25505/fiz.icsd.cc2979b6
title: CSD 2122177: Experimental Crystal Structure Determination

description: Related Article: Xi Liu|2021|ICSD Communication|||
DOI: 10.25505/fiz.icsd.cc2979d8
title: CSD 2122179: Experimental Crystal Structure Determination

description: Related Article: Xi Liu|2021|ICSD Communication|||
DOI: 10.6084/m9.figshare.17020067
title: Dataset: Stakeholder questionnaire on Seychelles’ Blue Carbon context

description: As part of the project '<b>Roadmap to blue carbon opportunities in Seychelles</b>’ funded by the Seychelles Conservation and Climate Adaptation Trust (SeyCCAT), this stakeholder questionnaire aimed to document the social, political, ecological, and scientific context of blue carbon ecosystems in Seychelles. The stakeholder questionnaire was delivered to over 200 stakeholders working in close connection to Seychelles’ coastal ecosystems. Stakeholder recruitment was a self-selection process, with invitations to participate in the survey distributed via direct email (by scientists from Deakin University and the James Michel Foundation) or disseminated through the internal and external communication outlets of SeyCCAT. The questionnaire was developed and delivered according to Deakin University’s Human Ethics guidelines (permit: SEBE-2020-45), with responses being non-identifiable and anonymous. Participation was voluntary, and consent implied through the completion of all the questions. Respondents were under no obligation to answer every question and were permitted to withdraw from the study at any time. The questionnaire was prepared in English and delivered online via the survey platform Qualtrics, between 03 Nov 2020 and 01 Sept 2021. Draft versions of the questionnaire were subjected to pre-tests and reviewed by scientists and members of SeyCCAT. The final questionnaire included a total of 34 questions and was structured into six sections: (1) Participant demography; (2) Ecological context; (3) Scientific context; (4) Society and Education; (5) Economic context; (6) Policy and Management.The survey was developed using conditional logic which automatically adjusted the questions displayed depending on the respondents’ profile. Hence, the number of questions displayed could range between 21 and 34. Sixty percent of the questions were closed and included pre-coded response options (e.g., multiple choice, ranking). Open questions were mainly used to capture additional information or request explanations for some of the pre-coded choices.Documents available in the repository include: (1) Readme; (2) Stakeholder_questionnaire (pdf); (3) Stakeholder_results (excel). Excludes any personal identifiers of the respondents (i.e., profession, role, and email) Results from this dataset have been submitted in a report to the Seychelles Conservation and Climate Adaptation Trust (SeyCCAT).
DOI: 10.5281/zenodo.5656057
title: Chula-RBC-12-Dataset

description: Chula-RBC-12 Dataset is a dataset of red blood cell (RBC) blood smear images used in "<strong>Red Blood Cell Segmentation with Overlapping Cell Separation and Classification from an Imbalanced Dataset</strong>", containing 12 classes of RBC types consisting of 706 smear images that contain over 20,000 RBC cells. The dataset was collected at the Oxidation in Red Cell Disorders Research Unit, Chulalongkorn University in 2019 using a DS-Fi2-L3 Nikon microscope at 1000x magnification. The "Dataset" folder contains 706 RBC blood smear images with 640*480 resolution. The "Label" folder contains label data with the name of the corresponding image. The file can contain multiple lines. Each line is a label for a single RBC and stored in the following sequence: x coordinate y coordinate type of RBC in number RBC Types 0 Normal cell 1 Macrocyte 2 Microcyte 3 Spherocyte 4 Target cell 5 Stomatocyte 6 Ovalocyte 7 Teardrop 8 Burr cell 9 Schistocyte 10 uncategorized 11 Hypochromia If you use this dataset, please cite the following paper: <pre><code>@misc{naruenatthanaset2021red, title={Red Blood Cell Segmentation with Overlapping Cell Separation and Classification on Imbalanced Dataset}, author={Korranat Naruenatthanaset and Thanarat H. Chalidabhongse and Duangdao Palasuwan and Nantheera Anantrasirichai and Attakorn Palasuwan}, year={2021}, eprint={2012.01321}, archivePrefix={arXiv}, primaryClass={eess.IV} }</code></pre>
DOI: 10.5281/zenodo.5638200
title: Chula-RBC-12-Dataset

description: Chula-RBC-12 Dataset is a dataset of red blood cell (RBC) blood smear images used in "<strong>Red Blood Cell Segmentation with Overlapping Cell Separation and Classification from an Imbalanced Dataset</strong>", containing 12 classes of RBC types consisting of 706 smear images that contain over 20,000 RBC cells. The dataset was collected at the Oxidation in Red Cell Disorders Research Unit, Chulalongkorn University in 2019 using a DS-Fi2-L3 Nikon microscope at 1000x magnification. The "Dataset" folder contains 706 RBC blood smear images with 640*480 resolution. The "Label" folder contains label data with the name of the corresponding image. The file can contain multiple lines. Each line is a label for a single RBC and stored in the following sequence: x coordinate y coordinate type of RBC in number RBC Types 0 Normal cell 1 Macrocyte 2 Microcyte 3 Spherocyte 4 Target cell 5 Stomatocyte 6 Ovalocyte 7 Teardrop 8 Burr cell 9 Schistocyte 10 uncategorized 11 Hypochromia If you use this dataset, please cite the following paper: <pre><code>@misc{naruenatthanaset2021red, title={Red Blood Cell Segmentation with Overlapping Cell Separation and Classification on Imbalanced Dataset}, author={Korranat Naruenatthanaset and Thanarat H. Chalidabhongse and Duangdao Palasuwan and Nantheera Anantrasirichai and Attakorn Palasuwan}, year={2021}, eprint={2012.01321}, archivePrefix={arXiv}, primaryClass={eess.IV} }</code></pre>
DOI: 10.6084/m9.figshare.17020719
title: Additional file 1 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 1. Averaged normalized read counts (RPM) for all annotated miRNAs detected in biological fluids and organs.
DOI: 10.6084/m9.figshare.17020719.v1
title: Additional file 1 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 1. Averaged normalized read counts (RPM) for all annotated miRNAs detected in biological fluids and organs.
DOI: 10.6084/m9.figshare.17020722
title: Additional file 2 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 2. Differentially expressed miRNAs between ovarian fluid and blood plasma samples.
DOI: 10.6084/m9.figshare.17020722.v1
title: Additional file 2 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 2. Differentially expressed miRNAs between ovarian fluid and blood plasma samples.
DOI: 10.6084/m9.figshare.17020725
title: Additional file 3 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 3. Differentially expressed miRNAs in blood plasma during reproductive cycle or in response to feeding rate.
DOI: 10.6084/m9.figshare.17020725.v1
title: Additional file 3 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 3. Differentially expressed miRNAs in blood plasma during reproductive cycle or in response to feeding rate.
DOI: 10.6084/m9.figshare.17020728
title: Additional file 4 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 4. Normalized and raw read counts in all analyzed libraries.
DOI: 10.6084/m9.figshare.17020728.v1
title: Additional file 4 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 4. Normalized and raw read counts in all analyzed libraries.
DOI: 10.6084/m9.figshare.17020734
title: Additional file 5 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 5. QPCR primer sequences.
DOI: 10.6084/m9.figshare.17020740
title: Additional file 6 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 6. Individual data used in Fig. 8 and 9.
DOI: 10.6084/m9.figshare.17020734.v1
title: Additional file 5 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 5. QPCR primer sequences.
DOI: 10.6084/m9.figshare.17020740.v1
title: Additional file 6 of Circulating miRNA repertoire as a biomarker of metabolic and reproductive states in rainbow trout

description: Additional file 6. Individual data used in Fig. 8 and 9.
DOI: 10.6084/m9.figshare.16900755
title: Additional file 1 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 1: Supplementary Table S1. Sequencing coverage and reads information for each sample.
DOI: 10.6084/m9.figshare.16900758
title: Additional file 2 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 2: Supplementary Table S2A. Gene lists; Hereditary cancer and Cancer driver. Supplementary Table S2B. Gene list; Scout HPO Neoplasia. Supplementary Table S2C. Gene list; Scout curated Clinical Genetics.
DOI: 10.6084/m9.figshare.16900761
title: Additional file 3 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 3: Supplementary Table S3. Genes targeted in extra analysis for each participant.
DOI: 10.6084/m9.figshare.16900755.v1
title: Additional file 1 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 1: Supplementary Table S1. Sequencing coverage and reads information for each sample.
DOI: 10.6084/m9.figshare.16900761.v2
title: Additional file 3 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 3: Supplementary Table S3. Genes targeted in extra analysis for each participant.
DOI: 10.6084/m9.figshare.16900758.v2
title: Additional file 2 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 2: Supplementary Table S2A. Gene lists; Hereditary cancer and Cancer driver. Supplementary Table S2B. Gene list; Scout HPO Neoplasia. Supplementary Table S2C. Gene list; Scout curated Clinical Genetics.
DOI: 10.6084/m9.figshare.16900758.v1
title: Additional file 2 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 2: Supplementary Table S2A. Gene lists; Hereditary cancer and Cancer driver. Supplementary Table S2B. Gene list; Scout HPO Neoplasia. Supplementary Table S2C. Gene list; Scout curated Clinical Genetics.
DOI: 10.6084/m9.figshare.16900761.v1
title: Additional file 3 of Massive parallel sequencing in individuals with multiple primary tumours reveals the benefit of re-analysis

description: Additional file 3: Supplementary Table S3. Genes targeted in extra analysis for each participant.
DOI: 10.6084/m9.figshare.14738640.v1
title: Additional file 2 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 2: Table S2. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PBMCs. In this Table all the results are compared to the Control, t = 0 sample.
DOI: 10.6084/m9.figshare.14738640
title: Additional file 2 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 2: Table S2. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PBMCs. In this Table all the results are compared to the Control, t = 0 sample.
DOI: 10.6084/m9.figshare.14738643
title: Additional file 3 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 3: Table S3. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PMNs. In this Table all the results are compared to the Control, t = 0 sample.
DOI: 10.6084/m9.figshare.14738643.v1
title: Additional file 3 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 3: Table S3. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PMNs. In this Table all the results are compared to the Control, t = 0 sample.
DOI: 10.6084/m9.figshare.14738646.v1
title: Additional file 4 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 4: Table S4. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PBMCs. In this Table the changes between subjects who received ivermectin and those who received a placebo are compared at 4 h and 24 h post-treatment.
DOI: 10.6084/m9.figshare.14738649
title: Additional file 5 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 5: Table S5. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PMNs. In this Table the changes between subjects who received ivermectin and those who received a placebo are compared at 4 h and 24 h post-treatment.
DOI: 10.6084/m9.figshare.14738646
title: Additional file 4 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 4: Table S4. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PBMCs. In this Table the changes between subjects who received ivermectin and those who received a placebo are compared at 4 h and 24 h post-treatment.
DOI: 10.6084/m9.figshare.14738649.v1
title: Additional file 5 of Lack of detectable short-term effects of a single dose of ivermectin on the human immune system

description: Additional file 5: Table S5. NanoString results for the changes in expression of the 770 genes of the myeloid gene panel in PMNs. In this Table the changes between subjects who received ivermectin and those who received a placebo are compared at 4 h and 24 h post-treatment.
DOI: 10.6084/m9.figshare.17020830
title: Additional file 2 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 1: Supplementary Table 1. Gene rhythm summary
DOI: 10.6084/m9.figshare.17020830.v1
title: Additional file 2 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 1: Supplementary Table 1. Gene rhythm summary
DOI: 10.6084/m9.figshare.17020848.v1
title: Additional file 5 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 4: Supplementary Table 4. MAG_DeSeq2
DOI: 10.6084/m9.figshare.17020848
title: Additional file 5 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 4: Supplementary Table 4. MAG_DeSeq2
DOI: 10.6084/m9.figshare.17020857
title: Additional file 7 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 6: Supplementary Table 6. ArgvCtl_Lefse
DOI: 10.6084/m9.figshare.17020857.v1
title: Additional file 7 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 6: Supplementary Table 6. ArgvCtl_Lefse
DOI: 10.6084/m9.figshare.17020862
title: Additional file 8 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 7: Supplementary Table 7. SEEDlvl3_DeSeq2
DOI: 10.6084/m9.figshare.17020862.v1
title: Additional file 8 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 7: Supplementary Table 7. SEEDlvl3_DeSeq2
DOI: 10.6084/m9.figshare.17020865
title: Additional file 9 of Circadian dynamics of the teleost skin immune-microbiome interface

description: Additional file 8: Supplementary Table 8. mic rhythm summary