cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.10247603
title: V-shaped Schiff’s base liquid crystals based on resorcinol: synthesis and characterisation

description: This paper designed and synthesised a series of V-shaped liquid crystal molecules (<b>X-SBA<sub>n</sub>E</b>) with resorcinol as the core and Schiff base as the mesogenic arms (<b>X-SBAA</b><sub><b>n</b></sub>). The effects of polarity of terminal groups (X=-CH<sub>3</sub>O,-CH<sub>3</sub>,-Cl) and length of flexible chain (n = 4,6,8) on mesogenic ranges were discussed. The chemical structure of <b>X-SBAA</b><sub><b>n</b></sub> and <b>X-SBA<sub>n</sub>E</b> was studied using FT-IR and <sup>1</sup>H-NMR while their thermal behaviour and mesogenic ranges were investigated via differential scanning calorimetry (DSC) and polarising optical microscopy (POM). The results indicated that <b>X-SBAA</b><sub><b>n</b></sub> containing OCH<sub>3</sub> and Cl substituents exhibited mesophase except for the analogue having CH<sub>3</sub> substituent which was found to be non-mesogenic. All of the synthesised <b>X-SBA<sub>n</sub>E</b> had liquid crystal properties and exhibited nematic phases in heating and cooling. The length of the flexible spacers and terminal groups significantly influenced their mesogenic ranges.
DOI: 10.6084/m9.figshare.10247594
title: Influences of melatonin and endotoxin lipopolysaccharide on goose productive performance and gut microbiota

description: 1. This study investigated the impact of melatonin and LPS on goose growth and the intestinal microbiome. 2. Geese were injected with a control solution (C), LPS solution (L), melatonin solution (M), and both LPS and melatonin solution (LM), respectively. Faecal samples from each group were used to analyse microbial diversity and function for geese with different treatments. 3. The results showed that the M group had a little improvement in growth compared with the C group, but were much higher than the L and LM groups. A clear distinction between M and other groups was seen with regard to alpha and beta diversity in the biome. The dominant bacteria phyla were <i>Firmicutes, Proteobacteria</i>, and <i>Actinobacteria spp</i>. in all groups. Unclassified bacteria were dominant in all groups at the genus level. Significant KEGG enrichment pathways in the M group were involved in processing metabolism and genetic information, while the L group was related to processing metabolism and environmental information. 4. This study provided a foundation for future studies targeting the specific effect of important bacterial populations on goose growth performance.
DOI: 10.6084/m9.figshare.10247600
title: en.2019-00670 supplement

description: Supplemental materials and methods, generation of the βmiR-221/222 and βmiR-221/222-TG mice, metabolic phenotypes and hormone levels of miR-221/222 mouse models. The predicted target genes of hsa-miR-221/222 and mus-miR-221/222 by TargetScan.
DOI: 10.6084/m9.figshare.10247603.v1
title: V-shaped Schiff’s base liquid crystals based on resorcinol: synthesis and characterisation

description: This paper designed and synthesised a series of V-shaped liquid crystal molecules (<b>X-SBA<sub>n</sub>E</b>) with resorcinol as the core and Schiff base as the mesogenic arms (<b>X-SBAA</b><sub><b>n</b></sub>). The effects of polarity of terminal groups (X=-CH<sub>3</sub>O,-CH<sub>3</sub>,-Cl) and length of flexible chain (n = 4,6,8) on mesogenic ranges were discussed. The chemical structure of <b>X-SBAA</b><sub><b>n</b></sub> and <b>X-SBA<sub>n</sub>E</b> was studied using FT-IR and <sup>1</sup>H-NMR while their thermal behaviour and mesogenic ranges were investigated via differential scanning calorimetry (DSC) and polarising optical microscopy (POM). The results indicated that <b>X-SBAA</b><sub><b>n</b></sub> containing OCH<sub>3</sub> and Cl substituents exhibited mesophase except for the analogue having CH<sub>3</sub> substituent which was found to be non-mesogenic. All of the synthesised <b>X-SBA<sub>n</sub>E</b> had liquid crystal properties and exhibited nematic phases in heating and cooling. The length of the flexible spacers and terminal groups significantly influenced their mesogenic ranges.
DOI: 10.5522/04/10247612.v2
title: Pupillometry as an Objective Measure of Sustained Attention in Young and Older Listeners, Trends in Hearing [Dataset]

description: Data files corresponding to paper of the same title. A Read Me guide to the data files is provided. For further questions please contact the corresponding authors.
DOI: 10.5522/04/10247612.v1
title: Pupillometry as an Objective Measure of Sustained Attention in Young and Older Listeners, Trends in Hearing [Dataset]

description: Data files corresponding to paper of the same title. A Read Me guide to the data files is provided. For further questions please contact the corresponding authors.
DOI: 10.6084/m9.figshare.10247582
title: Microscale Mineral Identification from SEM Images Using Semantic Segmentation with Deep Learning

description: Data used in paper 'Microscale Mineral Identification from SEM Images Using Semantic Segmentation with Deep Learning'
DOI: 10.6084/m9.figshare.10247585
title: Deformation of intrasalt beds recorded by magnetic fabrics

description: data for the JGR (2019) manuscript entitled: "Deformation of intrasalt beds recorded by magnetic fabrics"
DOI: 10.6084/m9.figshare.10247594.v2
title: Influences of melatonin and endotoxin lipopolysaccharide on goose productive performance and gut microbiota

description: 1. This study investigated the impact of melatonin and LPS on goose growth and the intestinal microbiome. 2. Geese were injected with a control solution (C), LPS solution (L), melatonin solution (M), and both LPS and melatonin solution (LM), respectively. Faecal samples from each group were used to analyse microbial diversity and function for geese with different treatments. 3. The results showed that the M group had a little improvement in growth compared with the C group, but were much higher than the L and LM groups. A clear distinction between M and other groups was seen with regard to alpha and beta diversity in the biome. The dominant bacteria phyla were <i>Firmicutes, Proteobacteria</i>, and <i>Actinobacteria spp</i>. in all groups. Unclassified bacteria were dominant in all groups at the genus level. Significant KEGG enrichment pathways in the M group were involved in processing metabolism and genetic information, while the L group was related to processing metabolism and environmental information. 4. This study provided a foundation for future studies targeting the specific effect of important bacterial populations on goose growth performance.
DOI: 10.6084/m9.figshare.10247585.v1
title: Deformation of intrasalt beds recorded by magnetic fabrics

description: data for the JGR (2019) manuscript entitled: "Deformation of intrasalt beds recorded by magnetic fabrics"
DOI: 10.6084/m9.figshare.10247582.v1
title: Microscale Mineral Identification from SEM Images Using Semantic Segmentation with Deep Learning

description: Data used for JGR-Solid Earth journal:'Microscale Mineral Identification from SEM Images Using Semantic Segmentation with Deep Learning'.
DOI: 10.6084/m9.figshare.10247555
title: Graphs - polybench

description: Graphs generated with the polybench package.<br>
DOI: 10.6084/m9.figshare.10247552
title: Graphs - created with Dagpar

description: Graph generated with the createdag tool from dagpar.<br>
DOI: 10.6084/m9.figshare.10247543
title: Graphs - daggen

description: Graphs generated by the DAG gen application.<br>
DOI: 10.6084/m9.figshare.10247552.v1
title: Graphs - created with Dagpar

description: Graph generated with the createdag tool from dagpar.<br>
DOI: 10.6084/m9.figshare.10247531
title: CytoData-2019 original challenge raw data

description: All data was originally published in: Breinig et al. Molcular System Biology, 2015<br>The data was re-analyzed from raw images and split into training and validation data.<br>EBImage was used to segement cells and extract features.<br>Segemented cells were cropped. <br><br>Validation cells were anonymyzed.<br>The task was to learn the annotated Mode of action (MOA) or target of the chemcial that each validation cells was treated with after learning from the training cells. MOA is coded by folder name in the image and the "target" column in the csv files.<br>Cells in the same well were targeted by the same chemcial and thus share their MOA. This information can be used to solve the challenge, however the more interesting/challenging part is the classification of MOA from looking at a single cell only.<br><br>Files and rows in feature space data are mapped 1:1 by their barcodes.<br>
DOI: 10.6084/m9.figshare.10247537
title: Graphs - Chukrut

description: Collection of graphs (DAG) of parallel programs.<br>
DOI: 10.6084/m9.figshare.10247537.v1
title: Graphs - Chukrut

description: Collection of graphs (DAG) of parallel programs.<br>
DOI: 10.6084/m9.figshare.10247543.v1
title: Graphs - daggen

description: Graphs generated by the DAG gen application.<br>
DOI: 10.6084/m9.figshare.10247501
title: The SUSTech-SYSU dataset for automatically segmenting and classifying corneal ulcers

description: In this zip folder, all the original ocular staining images, the associated cornea labels, and the associated flaky ulcer segmentation labels (images with point-like corneal ulcers do not have such segmentation labels) are provided as three folders, named respectively as "rawImages", "corneaLabels", and "ulcerLabels" (Data Citation 1). Results of superimposing cornea and flaky corneal ulcer segmentation masks on the associated ocular staining images are also provided in the "corneaOverlay" and "ulcerOverlay" folders. In the "rawImages" folder, files are named as "n.jpg", with n ranging between 1 and 712 denoting the nth sample. All images in this folder are saved in the JPG format. The segmentation label images of the cornea and the flaky ulcer area are saved as binary images in the PNG format, having the same size as the corresponding ocular staining image. An excel file was also provided, with the first column denoting the sample ID, the second column denoting the general pattern category (0 to 2, with 0 representing a point-like corneal ulcer, 1 representing a point-flaky mixed corneal ulcer, and 2 representing a flaky corneal ulcer), the third column denoting the type grading (0 to 4), and the fourth column denoting the grade grading (0 to 4). Two videos respectively demonstrating the semi-automatic segmentation process and the subsequent manual correction process were also provided in the zip folder.
DOI: 10.6084/m9.figshare.10247474
title: raw data

description: Raw data used for the publication<br>
DOI: 10.6084/m9.figshare.10247111
title: MOESM1 of Calculation method to predict postoperative limb length in patients undergoing THA following developmental dysplasia of hips

description: Additional file 1. The excel file which can help related calculation.
DOI: 10.6084/m9.figshare.10247114
title: MOESM2 of Calculation method to predict postoperative limb length in patients undergoing THA following developmental dysplasia of hips

description: Additional file 2. Raw data.
DOI: 10.6084/m9.figshare.10247111.v1
title: MOESM1 of Calculation method to predict postoperative limb length in patients undergoing THA following developmental dysplasia of hips

description: Additional file 1. The excel file which can help related calculation.
DOI: 10.6084/m9.figshare.10247114.v1
title: MOESM2 of Calculation method to predict postoperative limb length in patients undergoing THA following developmental dysplasia of hips

description: Additional file 2. Raw data.
DOI: 10.6084/m9.figshare.10247075
title: Car Price Data Collection and Statistical Testing

description: In a group of 4, we were randomly assigned to one parking site where we randomly sampled 10 cars with transponders and 10 cars without transponders. This was completed 4 times at each parking site within a span of 2 weeks. The prices of the cars were determined after each visit using Kelley Blue Book.
DOI: 10.6084/m9.figshare.10247069
title: Journal sentiment data for 3728 Scopus journals

description: This data set contains citation sentiment data for 3728 journals in Scopus. A sentiment classifier was used to measure the sentiment score of each citance. The sentiment score is between -1 and 1 in which 1 indicates the strongest positive sentiment. All together, more than 32 million citances were identified from the PubMed Central OA subset and each received a sentiment score. Citances were aggregated into cited journals. A journal is assigned into one of the 27 domains in Scopus. Because one journal can have multiple domain assignments, there are more than 8000 entries in this data set. One for each journal-domain assignment.
DOI: 10.17608/k6.auckland.10247057
title: COMBINE archive of Brännmark et al, 2013 (BIOMD0000000448)

description: This is a COMBINE archive of Brännmark et al, 2013 (BIOMD0000000448), consisting the original SBML model as well as SED-ML model which recreates some of the results of the original paper. <br>
DOI: 10.6084/m9.figshare.10247054
title: Supplement2.xlsx

description: The annotation and TPM of genes detected in the brain RNAseq of grass carp during low temperature<br>
DOI: 10.17608/k6.auckland.10247057.v1
title: COMBINE archive of Brännmark et al, 2013 (BIOMD0000000448)

description: This is a COMBINE archive of Brännmark et al, 2013 (BIOMD0000000448), consisting the original SBML model as well as SED-ML model which recreates some of the results of the original paper. <br>
DOI: 10.6084/m9.figshare.10247054.v1
title: Supplement2.xlsx

description: The annotation and TPM of genes detected in the brain RNAseq of grass carp during low temperature<br>
DOI: 10.6084/m9.figshare.10247051
title: supplement_TableS1-3.xlsx

description: The tables<br>
DOI: 10.6084/m9.figshare.10247075.v1
title: Car Price Data Collection

description: In a group of 4, we were randomly assigned to one parking site where we randomly sampled 10 cars with transponders and 10 cars without transponders. This was completed 4 times at each parking site within a span of 2 weeks. The prices of the cars were determined after each visit using Kelley Blue Book.
DOI: 10.6084/m9.figshare.10247051.v1
title: supplement_TableS1-3.xlsx

description: The tables<br>
DOI: 10.6084/m9.figshare.10247024
title: The development and validation of the Planet Formation Concept Inventory

description: The discovery and characterisation of planets orbiting distant stars has shed light on the origin of our own Solar System. It is important that college-level introductory astronomy students have a general understanding of the planet formation process before they are able to draw parallels between extrasolar systems and our own Solar System. In this work, we introduce the Planet Formation Concept Inventory (PFCI), an educational research tool used to assess student learning on the topic of planet formation. The PFCI Version 3 was administered to <i>N</i> = 561 students pre-instruction and <i>N</i> = 374 students post-instruction. Here, we present a Classical Test Theory (CTT) analysis of the PFCI Version 3. Ultimately, we conclude that the PFCI is a reliable and valid instrument that can differentiate experts from novices, and can be used to assess college-level introductory astronomy students' learning on the topic of planet formation. Initial findings on class normalised gain scores indicate that the PFCI may be capable of assessing the effectiveness of different instructional models. In the future, we recommend a national study of the PFCI to discern its ability to provide insight regarding the ascribed characteristics of learners and the effectiveness of different instructional strategies being used to teach this topic.
DOI: 10.26180/5dbf8fc4e4ef0
title: Acknowledgement GISAID table. Emergence of Influenza A(H7N4) Virus, Cambodia.

description: Acknowledgement table from GISAID for samples included in the paper:<br><i>Vijaykrishna D, Deng YM, Grau ML, Kay M, Suttie A, Horwood PF, Kalpravidh W, Claes F, Osbjer K, Dussart P, Barr IG, Karlsson EA. Emergence of Influenza A(H7N4) Virus, Cambodia. Emerg Infect Dis. 2019 Oct;25(10):1988-1991. doi: 10.3201/eid2510.190506. Epub 2019 Oct 17. PMID: 31310233; PMCID: PMC6759271.</i>
DOI: 10.6084/m9.figshare.10247024.v2
title: The development and validation of the Planet Formation Concept Inventory

description: The discovery and characterisation of planets orbiting distant stars has shed light on the origin of our own Solar System. It is important that college-level introductory astronomy students have a general understanding of the planet formation process before they are able to draw parallels between extrasolar systems and our own Solar System. In this work, we introduce the Planet Formation Concept Inventory (PFCI), an educational research tool used to assess student learning on the topic of planet formation. The PFCI Version 3 was administered to <i>N</i> = 561 students pre-instruction and <i>N</i> = 374 students post-instruction. Here, we present a Classical Test Theory (CTT) analysis of the PFCI Version 3. Ultimately, we conclude that the PFCI is a reliable and valid instrument that can differentiate experts from novices, and can be used to assess college-level introductory astronomy students' learning on the topic of planet formation. Initial findings on class normalised gain scores indicate that the PFCI may be capable of assessing the effectiveness of different instructional models. In the future, we recommend a national study of the PFCI to discern its ability to provide insight regarding the ascribed characteristics of learners and the effectiveness of different instructional strategies being used to teach this topic.
DOI: 10.6084/m9.figshare.10247024.v1
title: The development and validation of the Planet Formation Concept Inventory

description: The discovery and characterisation of planets orbiting distant stars has shed light on the origin of our own Solar System. It is important that college-level introductory astronomy students have a general understanding of the planet formation process before they are able to draw parallels between extrasolar systems and our own Solar System. In this work, we introduce the Planet Formation Concept Inventory (PFCI), an educational research tool used to assess student learning on the topic of planet formation. The PFCI Version 3 was administered to <i>N</i> = 561 students pre-instruction and <i>N</i> = 374 students post-instruction. Here, we present a Classical Test Theory (CTT) analysis of the PFCI Version 3. Ultimately, we conclude that the PFCI is a reliable and valid instrument that can differentiate experts from novices, and can be used to assess college-level introductory astronomy students' learning on the topic of planet formation. Initial findings on class normalised gain scores indicate that the PFCI may be capable of assessing the effectiveness of different instructional models. In the future, we recommend a national study of the PFCI to discern its ability to provide insight regarding the ascribed characteristics of learners and the effectiveness of different instructional strategies being used to teach this topic.
DOI: 10.6084/m9.figshare.10246952
title: Phylogenetics Workflows

description: The dataset presents input/output data of the TGOWLeR framework. TGOWLeR abstracts general patterns from workflow sequences previously extracted from texts. It comprises two modules –a workflow extractor and a pattern miner– both relying on a specific domain ontology.<br>The <em>input</em> of the first module is an RDF/ZIPPED ontology (<b>tgowler_resource_ontologies_PHAGE_1.0.rdf.zip</b>) and a set of un-annotated articles (<em>e.g.</em>, <b>datastore_2018_2019.zip</b>). The proposed pipeline (implemented in GATE 8.1) <em>produces</em> annotated texts (<em>e.g.</em>, <b>annotated_2018_2019.zip</b>) and their corresponding workflows (<em>e.g.</em>, <b>WFMiner_WF_2018_2019.xml</b>).<br>The <em>input</em> of the second module is the serialized ontology ... <br><b>Publications:</b><i>Halioui, Ahmed, et al. "Ontology-based workflow pattern mining: Application to bioinformatics expertise acquisition." Proceedings of the Symposium on Applied Computing. ACM, 2017.</i><br><br><i>Halioui, Ahmed, Petko Valtchev, and Abdoulaye Baniré Diallo. "Bioinformatic Workflow Extraction from Scientific Texts based on Word Sense Disambiguation." IEEE/ACM transactions on computational biology and bioinformatics 15.6 (2018): 1979-1990.</i><br>
DOI: 10.6084/m9.figshare.10246958
title: The Cue-Recalled Autobiographical Memory Test DATASET

description: The CRAM (Cue-Recalled Autobiographical Memory) test prompts autobiographical memories (AMs) using naturalistic word-cues. Participants date the memories to life periods and subsequently report the numbers of details remembered across eight content categories or features (e.g., spatial detail, temporal detail, emotions, objects, and people). The test collected AMs from the local George Mason University community and as it was made available online, from internet-browsing individuals. The dataset provided herein for public data mining contains 14,242 AMs scored for content from 4,244 users. The full set of raw data is uploaded as an Excel file and as a CSV file..<br>See Gardner et al., 2012 (https://doi.org/10.1371/journal.pone.0044809) and Gardner et al., 2015 (https://doi.org/10.3389.fpsyg.2015.00631) for full detail.
DOI: 10.6084/m9.figshare.10246958.v1
title: The Cue-Recalled Autobiographical Memory Test DATASET

description: The CRAM (Cue-Recalled Autobiographical Memory) test prompts autobiographical memories (AMs) using naturalistic word-cues. Participants date the memories to life periods and subsequently report the numbers of details remembered across eight content categories or features (e.g., spatial detail, temporal detail, emotions, objects, and people). The test collected AMs from the local George Mason University community and as it was made available online, from internet-browsing individuals. The dataset provided herein for public data mining contains 14,242 AMs scored for content from 4,244 users. The full set of raw data is uploaded.<br>See Gardner et al., 2012 (https://doi.org/10.1371/journal.pone.0044809) and Gardner et al., 2015 (https://doi.org/10.3389.fpsyg.2015.00631) for full detail.
DOI: 10.6084/m9.figshare.10246952.v1
title: datastore_2018_2019.zip

description: GATE input: raw phylogenetic analyses texts extracted from PubMed published articles from 2018-01-01 to 2019-10-01
DOI: 10.6084/m9.figshare.10246952.v3
title: Phylogenetics Workflows

description: The dataset presents input/output data of the TGOWLeR framework. TGOWLeR abstracts general patterns from workflow sequences previously extracted from texts. It comprises two modules –a workflow extractor and a pattern miner– both relying on a specific domain ontology.<br>The <em>input</em> of the first module is an RDF/ZIPPED ontology (<b>tgowler_resource_ontologies_PHAGE_1.0.rdf.zip</b>) and a set of un-annotated articles (<em>e.g.</em>, <b>datastore_2018_2019.zip</b>). The proposed pipeline (implemented in GATE 8.1) <em>produces</em> annotated texts (<em>e.g.</em>, <b>annotated_2018_2019.zip</b>) and their corresponding workflows (<em>e.g.</em>, <b>WFMiner_WF_2018_2019.xml</b>).<br>The <em>input</em> of the second module is the serialized ontology ... <br><b>Publications:</b><i>Halioui, Ahmed, et al. "Ontology-based workflow pattern mining: Application to bioinformatics expertise acquisition." Proceedings of the Symposium on Applied Computing. ACM, 2017.</i><br><br><i>Halioui, Ahmed, Petko Valtchev, and Abdoulaye Baniré Diallo. "Bioinformatic Workflow Extraction from Scientific Texts based on Word Sense Disambiguation." IEEE/ACM transactions on computational biology and bioinformatics 15.6 (2018): 1979-1990.</i><br>