cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14738031.v1
title: Absorption spectra of soybean measured in situ at two different temperatures

description: The dataset was collected using the leaf chamber spectrometer connected to an infrared greenhouse gas analyser (Li-6400) on soybean (<i>Glycine max</i> L. Merr.) cultivar (Williams 82) third trifoliate leaves on 3-week old plants (vegetative growth stages V3 and V4). Seeds were sourced from Iowa State University, USA. Plants were grown in pots in the controlled environment facility in the Faculty of Biological Sciences, Plant Growth Suite, University of Leeds. The growth conditions were 25C day/night temperatures, 50% relative humidity, with a 16 h photoperiod at an irradiance of 400–600 μmol photons /m<sup>2</sup>/s.
DOI: 10.21227/2mp5-3p65
title: Location dependent performance on a circular EIT sensor

description: The technique of electrical impedance tomography (EIT) has been recognized as a promising method to design tactile sensors with continuous sensing capability over a large area. The mechanism of electrical impedance tomography allows reconstructing tactile information within the sensing area based on measurements made only at the boundary. However, spatial performance of EIT-based tactile sensors has demonstrated location dependency in previous reports, which severely affects correct interpretation of tactile stimuli. Here, we analyzed the effect of hyperparameter on spatial performance, in terms of amplitude, size, position error, and shape deformation in reconstructed images. To obtain uniform sensitivity throughout the entire sensing area, we developed an intensity scaling method to correct reconstructed amplitudes based on simulation studies. A diagonal scaling matrix was developed for a symmetric circular sensing area, and the scaling value were constructed according to the radial positions of the finite elements. The correction method was further evaluated on a compliant EIT-based touch sensor made of polymer filled composites with underlying paddings. We found that the developed method effectively produced a more uniform sensitivity distribution, and improved spatial profiles of shape deformation. The findings shown here help better interpret strength information of tactile stimuli located at different positions over large area EIT-based sensors.
DOI: 10.15468/8av6sc
title: First New Zealand record of the Australian species Hemiodoecus leai China, 1924 (Hemiptera: Peloridiidae); a hitchhiker on moss

description: This dataset contains the digitized treatments in Plazi based on the original journal article Wakelin, Michael D., Larivière, Marie-Claude (2014): First New Zealand record of the Australian species Hemiodoecus leai China, 1924 (Hemiptera: Peloridiidae); a hitchhiker on moss. Zootaxa 3884 (1): 95-100, DOI: http://dx.doi.org/10.11646/zootaxa.3884.1.9
DOI: 10.15468/yvd8p2
title: Biology, early stages and description of a new species of Adelognathus Holmgren (Hymenoptera: Ichneumonidae: Adelognathinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Shaw, Mark R., Wahl, David B. (2014): Biology, early stages and description of a new species of Adelognathus Holmgren (Hymenoptera: Ichneumonidae: Adelognathinae). Zootaxa 3884 (3): 235-252, DOI: http://dx.doi.org/10.11646/zootaxa.3884.3.3
DOI: 10.25345/c54f9n
title: MassIVE MSV000087621 - Phosphate-limited proteome of Methanococcus maripaludis
title: Lorem ipsum dolor sit amet, consectetur adipiscing elit. In consectetur laoreet odio in convallis. Maecenas vel risus consectetur erat aliquet aliquam. Vestibulum tempus ipsum risus, et dictum magna vehicula at. Praesent quis mi massa. Nullam metus leo, ornare ut consectetur et, facilisis vitae odio. Suspendisse diam tellus, venenatis a porta nec, viverra et massa. Fusce est ex, scelerisque eget odio quis, blandit ullamcorper tortor. Curabitur blandit nibh luctus magna blandit ullamcorper. Proin consequat vehicula turpis vitae aliquam. Donec tristique, urna et ultricies fringilla, dui sem consequat dui, sed dignissim neque magna ac ipsum. Vestibulum ut nulla pharetra, vehicula nunc eu, tincidunt orci. Suspendisse vitae pretium justo. Etiam vehicula turpis quam, non vulputate mauris pharetra at. Phasellus dapibus quam eget ornare dignissim.
DOI: 10.15468/j9vprc
title: The genus Sitothrips (Thysanoptera: Thripidae) with a new grass-living species from southern Iran

description: This dataset contains the digitized treatments in Plazi based on the original journal article Minaei, Kambiz, Mound, Laurence (2014): The genus Sitothrips (Thysanoptera: Thripidae) with a new grass-living species from southern Iran. Zootaxa 3884 (6): 594-596, DOI: http://dx.doi.org/10.11646/zootaxa.3884.6.7
DOI: 10.6084/m9.figshare.13379000.v1
title: Effects of a groin pain prevention program for male high school soccer players: a cluster-randomised controlled trial

description: Groin pain (GP) is one of the most common pain conditions reported by soccer players, but few reports have examined the effects of preventive exercise interventions on high school soccer players. In addition, there is a Copenhagen adduction exercise (CAE) as a preventive exercise for GP, but there is no report that examined the combined intervention effect with the Nordic hamstrings exercise(NHE). The purpose of this study was to investigate the preventive exercise effects in high school soccer players.
DOI: 10.6084/m9.figshare.13379000
title: Effects of a groin pain prevention program for male high school soccer players: a cluster-randomised controlled trial

description: Groin pain (GP) is one of the most common pain conditions reported by soccer players, but few reports have examined the effects of preventive exercise interventions on high school soccer players. In addition, there is a Copenhagen adduction exercise (CAE) as a preventive exercise for GP, but there is no report that examined the combined intervention effect with the Nordic hamstrings exercise(NHE). The purpose of this study was to investigate the preventive exercise effects in high school soccer players.
DOI: 10.6084/m9.figshare.13379000.v3
title: Effects of a groin pain prevention program for male high school soccer players: a cluster-randomised controlled trial

description: Groin pain (GP) is one of the most common pain conditions reported by soccer players, but few reports have examined the effects of preventive exercise interventions on high school soccer players. In addition, there is a Copenhagen adduction exercise (CAE) as a preventive exercise for GP, but there is no report that examined the combined intervention effect with the Nordic hamstrings exercise(NHE). The purpose of this study was to investigate the preventive exercise effects in high school soccer players.
DOI: 10.6084/m9.figshare.13379000.v2
title: Effects of a groin pain prevention program for male high school soccer players: a cluster-randomised controlled trial

description: Groin pain (GP) is one of the most common pain conditions reported by soccer players, but few reports have examined the effects of preventive exercise interventions on high school soccer players. In addition, there is a Copenhagen adduction exercise (CAE) as a preventive exercise for GP, but there is no report that examined the combined intervention effect with the Nordic hamstrings exercise(NHE). The purpose of this study was to investigate the preventive exercise effects in high school soccer players.
DOI: 10.6084/m9.figshare.14738031
title: This is an accidental entry - the actual data is in the next entry

description: This was an accidental entry.
DOI: 10.6084/m9.figshare.14738031.v3
title: This is an accidental entry - the actual data is in the next entry

description: This was an accidental entry.
DOI: 10.6084/m9.figshare.14738031.v2
title: This

description: The dataset was collected using the leaf chamber spectrometer connected to an infrared greenhouse gas analyser (Li-6400) on soybean (<i>Glycine max</i> L. Merr.) cultivar (Williams 82) third trifoliate leaves on 3-week old plants (vegetative growth stages V3 and V4). Seeds were sourced from Iowa State University, USA. Plants were grown in pots in the controlled environment facility in the Faculty of Biological Sciences, Plant Growth Suite, University of Leeds. The growth conditions were 25C day/night temperatures, 50% relative humidity, with a 16 h photoperiod at an irradiance of 400–600 μmol photons /m<sup>2</sup>/s.
DOI: 10.5281/zenodo.4737593
title: A 4D Single-Cell Protein Atlas of Transcription Factors Delineates Spatiotemporal Patterning During Embryogenesis

description: Each csv file shows the unprocessed and processed expression of a TF-reporter strain in each traced cell at each time point.
DOI: 10.5281/zenodo.4737592
title: A 4D Single-Cell Protein Atlas of Transcription Factors Delineates Spatiotemporal Patterning During Embryogenesis

description: Each csv file shows the unprocessed and processed expression of a TF-reporter strain in each traced cell at each time point.
DOI: 10.6084/m9.figshare.14782864.v1
title: Additional file 2 of Diversity and metagenome analysis of a hydrocarbon-degrading bacterial consortium from asphalt lakes located in Wietze, Germany

description: Additional file 2. Table S2: Metagenome-assembled genomes (MAGs) from both the soil and the enrichment metagenomes.
DOI: 10.6084/m9.figshare.14782840.v1
title: Additional file 6 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 6. Data extraction tool for associated factors with NTDs.
DOI: 10.6084/m9.figshare.14782837.v1
title: Additional file 5 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 5. Data extraction tool for magnitude of NTDs.
DOI: 10.6084/m9.figshare.14782834.v1
title: Additional file 4 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 4. Risk of bias assesement tool for case-control studies.
DOI: 10.6084/m9.figshare.14782828.v1
title: Additional file 3 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 3. Risk of bias assesement tool for cross-sectional studies.
DOI: 10.21227/xxvv-3135
title: ncRNA-protein interactions generated by negative sample selection

description: The original datasets are NPInter4158 [1], NPInter10412 [2], RPI7317 [3], RPI2241 [4], and RPI369 [4]. Only positive samples of them were used in our work.We used a different strategy to select more reliable negative samples rather than randomly pairing, which was originally introduced by Zhang et al. in the LPI-CNNCP [5] study.First, we calculated the Smith-Waterman similarity between each pair of proteins. Next, wecalculated interaction scores between each pair of protein and RNA based on the known interaction pairs and protein similarities. Then,we sorted the interaction scores of all pairs in an ascending order. Finally, negative samples were selected sequentially from the head of the sorted list with the same number as positives.[1]H. Zhang, Z. Ming, C. Fan, Q. Zhao, and H. Liu, “A path-based computational model for long non-coding RNA-protein interaction prediction,” Genomics, vol. 112, no. 2, pp. 1754–1760, Mar. 2020, doi: 10.1016/j.ygeno.2019.09.018.[2] J. Yuan, W. Wu, C. Xie, G. Zhao, Y. Zhao, and R. Chen, “NPInter v2.0: an updated database of ncRNA interactions,” Nucl. Acids Res., vol. 42, no. D1, pp. D104–D108, Jan. 2014, doi: 10.1093/nar/gkt1057.[3]X.-N. Fan and S.-W. Zhang, “LPI-BLS: Predicting lncRNA–protein interactions with a broad learning system-based stacked ensemble classifier,” Neurocomputing, vol. 370, pp. 88–93, Dec. 2019, doi: 10.1016/j.neucom.2019.08.084.[4]U. K. Muppirala, V. G. Honavar, and D. Dobbs, “Predicting RNA-Protein Interactions Using Only Sequence Information,” BMC Bioinformatics, vol. 12, no. 1, p. 489, Dec. 2011, doi: 10.1186/1471-2105-12-489.[5] S.-W. Zhang, X.-X. Zhang, X.-N. Fan, and W.-N. Li, “LPI-CNNCP: Prediction of lncRNA-protein interactions by using convolutional neural network with the copy-padding trick,” Analytical Biochemistry, vol. 601, p. 113767, Jul. 2020, doi: 10.1016/j.ab.2020.113767.
DOI: 10.21227/qg28-fk76
title: ncRNA-protein interactions generated by negative sample selection

description: The original datasets are NPInter4158 [1], NPInter10412 [2], RPI7317 [3], RPI2241 [4], and RPI369 [4]. Only positive samples of them were used in our work.We used a different strategy to select more reliable negative samples rather than randomly pairing, which was originally introduced by Zhang et al. in the LPI-CNNCP [5] study.First, we calculated the Smith-Waterman similarity between each pair of proteins. Next, wecalculated interaction scores between each pair of protein and RNA based on the known interaction pairs and protein similarities. Then,we sorted the interaction scores of all pairs in an ascending order. Finally, negative samples were selected sequentially from the head of the sorted list with the same number as positives.[1]H. Zhang, Z. Ming, C. Fan, Q. Zhao, and H. Liu, “A path-based computational model for long non-coding RNA-protein interaction prediction,” Genomics, vol. 112, no. 2, pp. 1754–1760, Mar. 2020, doi: 10.1016/j.ygeno.2019.09.018.[2] J. Yuan, W. Wu, C. Xie, G. Zhao, Y. Zhao, and R. Chen, “NPInter v2.0: an updated database of ncRNA interactions,” Nucl. Acids Res., vol. 42, no. D1, pp. D104–D108, Jan. 2014, doi: 10.1093/nar/gkt1057.[3]X.-N. Fan and S.-W. Zhang, “LPI-BLS: Predicting lncRNA–protein interactions with a broad learning system-based stacked ensemble classifier,” Neurocomputing, vol. 370, pp. 88–93, Dec. 2019, doi: 10.1016/j.neucom.2019.08.084.[4]U. K. Muppirala, V. G. Honavar, and D. Dobbs, “Predicting RNA-Protein Interactions Using Only Sequence Information,” BMC Bioinformatics, vol. 12, no. 1, p. 489, Dec. 2011, doi: 10.1186/1471-2105-12-489.[5] S.-W. Zhang, X.-X. Zhang, X.-N. Fan, and W.-N. Li, “LPI-CNNCP: Prediction of lncRNA-protein interactions by using convolutional neural network with the copy-padding trick,” Analytical Biochemistry, vol. 601, p. 113767, Jul. 2020, doi: 10.1016/j.ab.2020.113767.
DOI: 10.6084/m9.figshare.14782774.v1
title: Additional file 2 of Landscape and selection of vaccine epitopes in SARS-CoV-2

description: Additional file 2: Table S1. All SARS-CoV-2 MHC-I ligands contained in the top 5% of U.S. HLA alleles. Table S2. All SARS-CoV-2 MHC-II ligands contained in the top 5% of U.S. HLA alleles. Table S3. All SARS-CoV-2 MHC-I ligands contained in the top 5% of worldwide HLA alleles. Table S4. All SARS-CoV-2 MHC-II ligands contained in the top 5% of worldwide HLA alleles. Table S5. Summary of SARS-CoV-1 MHC ligands previously described in the literature. Table S6. SARS-CoV-2 B cell linear epitopes from array/mapping studies. Table S7. SARS-CoV-2 T cell epitopes within S, M, and N proteins. Table S8. SARS-CoV-2 T cell epitopes within all proteins. Table S9. Curated a dataset of published T cell epitope mapping studies.
DOI: 10.6084/m9.figshare.14782663.v1
title: Additional file 1 of The role of a virtual avatar in attention and memory tasks in Rett syndrome

description: Additional file 1:.
DOI: 10.6084/m9.figshare.14782636.v1
title: Additional file 2 of Breath-holding as a novel approach to risk stratification in COVID-19

description: Additional file 2: Tool to assess probability of the primary adverse outcome (for academic evaluation).
DOI: 10.6084/m9.figshare.14782605.v1
title: Additional file 1 of Impact of the COVID-19 pandemic on UK medical school widening access schemes: disruption, support and a virtual student led initiative

description: Additional file 1: Pre-conference Questionnaire. Post-conference Questionnaire
DOI: 10.6084/m9.figshare.14782512.v1
title: Additional file 2 of Parkinson’s disease–associated VPS35 mutant reduces mitochondrial membrane potential and impairs PINK1/Parkin-mediated mitophagy

description: Additional file 2: Table S1. Primers used for creating VPS35D620N clones using CRISPR-Cas9. Abbreviation: sgRNA: single guide RNA. * indicates phosphorothioate bonds between nucleotides.
DOI: 10.6084/m9.figshare.14782456.v1
title: Additional file 2 of Characterizing the properties of bisulfite sequencing data: maximizing power and sensitivity to identify between-group differences in DNA methylation

description: Additional file 2. RRBS information on total number of reads aligned, unaligned ambiguously aligned, and total number of reads, as well as the number of methylated and unmethylated CpGs, CpH, and CHH’s, and total number of cytosines.
DOI: 10.6084/m9.figshare.14782428.v1
title: Additional file 5 of Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

description: Additional file 5: Table S3. QTL regions detected with the three groups of association studies. These QTL regions were found from the full population (Global-GWAS) and from each line separately (HRFI-GWAS and LRFI-GWAS). DFI: daily feed intake; ADG: average daily gain; FCR: feed conversion ratio; RFI: residual feed intake; carcBFT: backfat thickness measured on carcass; a*_GM: a* measured on the gluteus medius muscle; a*_GS: a* measured on the gluteus superficialis muscle; b*_GM: b* measured on the gluteus medius muscle; b*_GS: b* measured on the gluteus superficialis muscle; L*_GM: L* measured on the gluteus medius muscle; L*_GS: L* measured on the gluteus superficialis muscle; pH24h_AD: pH 24 h after slaughter measured on the adductor femoris muscle; pH24h_GS: pH 24 h after slaughter measured on the gluteus superficialis muscle; pH24h_LM: pH 24 h after slaughter measured on the longissimus dorsi muscle; pH24h_SM: pH 24 h after slaughter measured on the semimembranosus muscle; WHC: water holding capacity of the gluteus superficialis muscle; MQI: meat quality index; LMCcalc: lean meat content of the carcass; DP: carcass dressing percentage; Belly_W: belly weight; BF_W: backfat weight; Ham_W: ham weight; Loin_W: loin weight; Shoulder_W: shoulder weight
DOI: 10.6084/m9.figshare.14782419.v1
title: Additional file 2 of Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

description: Additional file 2: Table S2. Number of SNPs used for the analyses after quality control. Details of the number of SNPs before and after application of filters on the call frequency (CF) and the frequency of minor allele (MAF) were given for chips (60K, 70K and 650K SNPs chips), imputation levels (MD imputation and HD imputation) and average genotypes calculated from the genotypes of both parents (HD predicted).
DOI: 10.6084/m9.figshare.14782416.v1
title: Additional file 1 of Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

description: Additional file 1: Table S1. Number of animals used for the analyses after quality control. Details of the number of animals before and after application of a filter on the call rate (CR) were given for chips (60K, 70K and 650K SNPs chips), imputation levels (MD/HD imputation) and average genotypes calculated from the genotypes of both parents (HD predicted).
DOI: 10.6084/m9.figshare.14782864
title: Additional file 2 of Diversity and metagenome analysis of a hydrocarbon-degrading bacterial consortium from asphalt lakes located in Wietze, Germany

description: Additional file 2. Table S2: Metagenome-assembled genomes (MAGs) from both the soil and the enrichment metagenomes.
DOI: 10.6084/m9.figshare.14782840
title: Additional file 6 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 6. Data extraction tool for associated factors with NTDs.
DOI: 10.6084/m9.figshare.14782837
title: Additional file 5 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 5. Data extraction tool for magnitude of NTDs.
DOI: 10.6084/m9.figshare.14782834
title: Additional file 4 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 4. Risk of bias assesement tool for case-control studies.
DOI: 10.6084/m9.figshare.14782828
title: Additional file 3 of Magnitude and determinants of neural tube defect in Africa: a systematic review and meta-analysis

description: Additional file 3. Risk of bias assesement tool for cross-sectional studies.
DOI: 10.6084/m9.figshare.14782774
title: Additional file 2 of Landscape and selection of vaccine epitopes in SARS-CoV-2

description: Additional file 2: Table S1. All SARS-CoV-2 MHC-I ligands contained in the top 5% of U.S. HLA alleles. Table S2. All SARS-CoV-2 MHC-II ligands contained in the top 5% of U.S. HLA alleles. Table S3. All SARS-CoV-2 MHC-I ligands contained in the top 5% of worldwide HLA alleles. Table S4. All SARS-CoV-2 MHC-II ligands contained in the top 5% of worldwide HLA alleles. Table S5. Summary of SARS-CoV-1 MHC ligands previously described in the literature. Table S6. SARS-CoV-2 B cell linear epitopes from array/mapping studies. Table S7. SARS-CoV-2 T cell epitopes within S, M, and N proteins. Table S8. SARS-CoV-2 T cell epitopes within all proteins. Table S9. Curated a dataset of published T cell epitope mapping studies.
DOI: 10.48425/0031008
title: V_rodents_snaptrapping_individuals_regional

description: Snap trapping data of rodents on the Varanger peninsula. This dataset has data from the COAT regional study design. Each entry corresponds to a trapped individual. Two related datasets have information on i) site-based abundances and ii) trap status, i.e. missing and closed traps. \r\n\r\nThe dataset includes four different types of files and all files are saved as ;-separated txt-files:\r\n\r\n* One data file per year (_YEAR.txt)\r\n* One coordinate file with coordinates of all sites (_coordinates.txt)\r\n* One auxiliary file with information about which sites are included in the study design (_aux.txt)\r\n* One readme file with additional information (_readme.pdf)\r\n\r\nThe dataset has a two-year embargo, older versions of the dataset are publicly available for download.
DOI: 10.6084/m9.figshare.14782663
title: Additional file 1 of The role of a virtual avatar in attention and memory tasks in Rett syndrome

description: Additional file 1:.
DOI: 10.6084/m9.figshare.14782636
title: Additional file 2 of Breath-holding as a novel approach to risk stratification in COVID-19

description: Additional file 2: Tool to assess probability of the primary adverse outcome (for academic evaluation).
DOI: 10.6084/m9.figshare.14782605
title: Additional file 1 of Impact of the COVID-19 pandemic on UK medical school widening access schemes: disruption, support and a virtual student led initiative

description: Additional file 1: Pre-conference Questionnaire. Post-conference Questionnaire