cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.23668730
title: Adaptive autonomous emergency braking model based on weather conditions

description: Vehicle active safety systems can improve vehicle security by avoiding collisions. An autonomous emergency braking (AEB) system’s safety distance calculation is usually based on normal weather conditions. The AEB system’s early warning capabilities decrease during adverse weather conditions. A multilayer perceptron (MLP) model is used to obtain data from accident and weather data sets. The MLP model is trained and the severity of accidents is predicted. The severity is used as a parameter to build an adaptive AEB system algorithm that considers adverse weather conditions. The adaptive AEB system algorithm increases safety and reliability under adverse weather conditions. Prescan and a driver-in-the-loop system are used to test the adaptive AEB model. Both tests show that the adaptive AEB model has better performance under adverse weather than the traditional AEB model. The experimental results demonstrate that the adaptive AEB system can increase the safety distance in rainy weather and avoid collisions under hazy conditions.
DOI: 10.6084/m9.figshare.23668730.v1
title: Adaptive autonomous emergency braking model based on weather conditions

description: Vehicle active safety systems can improve vehicle security by avoiding collisions. An autonomous emergency braking (AEB) system’s safety distance calculation is usually based on normal weather conditions. The AEB system’s early warning capabilities decrease during adverse weather conditions. A multilayer perceptron (MLP) model is used to obtain data from accident and weather data sets. The MLP model is trained and the severity of accidents is predicted. The severity is used as a parameter to build an adaptive AEB system algorithm that considers adverse weather conditions. The adaptive AEB system algorithm increases safety and reliability under adverse weather conditions. Prescan and a driver-in-the-loop system are used to test the adaptive AEB model. Both tests show that the adaptive AEB model has better performance under adverse weather than the traditional AEB model. The experimental results demonstrate that the adaptive AEB system can increase the safety distance in rainy weather and avoid collisions under hazy conditions.
DOI: 10.6084/m9.figshare.21571608
title: Enhancing performance of multi-temporal tropical river landform classification through downscaling approaches

description: Multi-temporal remote sensing imagery has the potential to classify river landforms to reconstruct the evolutionary trajectory of river morphologies. Whilst open-access archives of high spatial resolution imagery are increasingly available from satellite sensors, such as Sentinel-2, there remains a fundamental challenge of maximising the utility of information in each band whilst maintaining a sufficiently fine resolution to identify landforms. Although image fusion and downscaling methods on Sentinel-2 imagery have been investigated for many years, there is a need to assess their performance for multi-temporal object-based river landform classification. This investigation first compared three downscaling methods: area to point regression kriging (ATPRK), super-resolution based on Sen2Res, and nearest neighbour resampling. We assessed performance of the three downscaling methods by accuracy, precision, recall and F1-score. ATPRK was the optimal downscaling approach, achieving an overall accuracy of 0.861. We successively engaged a set of experiments to determine an optimal training model, exploring single and multi-date scenarios. We find that not only does remote sensing imagery with better quality improve river landform classification performance, but multi-date datasets for establishing machine learning models should be considered for contributing higher classification accuracy. This paper presents a workflow for automated river landform recognition that could be applied to other tropical rivers with similar hydro-geomorphological characteristics. Choice of downscaling approach influences the performance of river landform classification from satellite imagery and should be considered in river and flood management.An efficient and straightforward operating workflow was developed for automated river landform classification with high accuracy that supports an improved understanding of the use of machine learning approaches in river landform recognition.Freely available and easy-to-access remote sensing datasets can help extend the operating workflow to difficult-to-access or remote regions and allow for complete regional and/or national coverage. Choice of downscaling approach influences the performance of river landform classification from satellite imagery and should be considered in river and flood management. An efficient and straightforward operating workflow was developed for automated river landform classification with high accuracy that supports an improved understanding of the use of machine learning approaches in river landform recognition. Freely available and easy-to-access remote sensing datasets can help extend the operating workflow to difficult-to-access or remote regions and allow for complete regional and/or national coverage.
DOI: 10.6084/m9.figshare.21571608.v1
title: Enhancing performance of multi-temporal tropical river landform classification through downscaling approaches

description: Multi-temporal remote sensing imagery has the potential to classify river landforms to reconstruct the evolutionary trajectory of river morphologies. Whilst open-access archives of high spatial resolution imagery are increasingly available from satellite sensors, such as Sentinel-2, there remains a fundamental challenge of maximising the utility of information in each band whilst maintaining a sufficiently fine resolution to identify landforms. Although image fusion and downscaling methods on Sentinel-2 imagery have been investigated for many years, there is a need to assess their performance for multi-temporal object-based river landform classification. This investigation first compared three downscaling methods: area to point regression kriging (ATPRK), super-resolution based on Sen2Res, and nearest neighbour resampling. We assessed performance of the three downscaling methods by accuracy, precision, recall and F1-score. ATPRK was the optimal downscaling approach, achieving an overall accuracy of 0.861. We successively engaged a set of experiments to determine an optimal training model, exploring single and multi-date scenarios. We find that not only does remote sensing imagery with better quality improve river landform classification performance, but multi-date datasets for establishing machine learning models should be considered for contributing higher classification accuracy. This paper presents a workflow for automated river landform recognition that could be applied to other tropical rivers with similar hydro-geomorphological characteristics. Choice of downscaling approach influences the performance of river landform classification from satellite imagery and should be considered in river and flood management.An efficient and straightforward operating workflow was developed for automated river landform classification with high accuracy that supports an improved understanding of the use of machine learning approaches in river landform recognition.Freely available and easy-to-access remote sensing datasets can help extend the operating workflow to difficult-to-access or remote regions and allow for complete regional and/or national coverage. Choice of downscaling approach influences the performance of river landform classification from satellite imagery and should be considered in river and flood management. An efficient and straightforward operating workflow was developed for automated river landform classification with high accuracy that supports an improved understanding of the use of machine learning approaches in river landform recognition. Freely available and easy-to-access remote sensing datasets can help extend the operating workflow to difficult-to-access or remote regions and allow for complete regional and/or national coverage.
DOI: 10.6084/m9.figshare.20521379.v1
title: Additional file 2 of Comparative transcriptome analysis of rice cultivars resistant and susceptible to Rhizoctonia solani AG1-IA

description: Additional file 2. Number of expressed genes in all samples (FPKM&gt;0.5).
DOI: 10.6084/m9.figshare.23668811
title: A real-world data analysis of acetylsalicylic acid in FDA Adverse Event Reporting System (FAERS) database

description: Acetylsalicylic acid (Aspirin), one of the oldest medicines, is widely used in various clinical fields. However, numerous adverse events (AEs) have been reported. In this study, we aimed to investigate adverse drug reactions (ADRs) of aspirin using real-worlddata from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. We assessed the disproportionality of aspirin-related AEs by calculating measures such as reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagationneural network (BCPNN), and Gamma-Poisson Shrinker (GPS). Out of 7,510,564 casereports in the FAERS database, 18644 reports of aspirin as the ‘primary suspected (PS)’ AEs were recorded. Disproportionality analyses identified 493 aspirin-related preferred terms (PTs) across 25 organ systems. Notably, unexpected significant AEs such as pallor (<i>p</i>=5.66E–33), dependence (<i>p</i>=6.45E–67), and compartment syndrome (<i>p</i>=1.95E–28) were observed, which were not mentioned in the drug’s instructions. Our findings align with clinical observations, highlighting potential new and unexpected ADR signals associated with aspirin. Further prospective clinical studies are necessary to confirm and elucidate the relationship between aspirin and these ADRs. This study offers a fresh and unique perspective for studying drug-AEs.
DOI: 10.6084/m9.figshare.23668811.v1
title: A real-world data analysis of acetylsalicylic acid in FDA Adverse Event Reporting System (FAERS) database

description: Acetylsalicylic acid (Aspirin), one of the oldest medicines, is widely used in various clinical fields. However, numerous adverse events (AEs) have been reported. In this study, we aimed to investigate adverse drug reactions (ADRs) of aspirin using real-worlddata from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. We assessed the disproportionality of aspirin-related AEs by calculating measures such as reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagationneural network (BCPNN), and Gamma-Poisson Shrinker (GPS). Out of 7,510,564 casereports in the FAERS database, 18644 reports of aspirin as the ‘primary suspected (PS)’ AEs were recorded. Disproportionality analyses identified 493 aspirin-related preferred terms (PTs) across 25 organ systems. Notably, unexpected significant AEs such as pallor (<i>p</i>=5.66E–33), dependence (<i>p</i>=6.45E–67), and compartment syndrome (<i>p</i>=1.95E–28) were observed, which were not mentioned in the drug’s instructions. Our findings align with clinical observations, highlighting potential new and unexpected ADR signals associated with aspirin. Further prospective clinical studies are necessary to confirm and elucidate the relationship between aspirin and these ADRs. This study offers a fresh and unique perspective for studying drug-AEs.
DOI: 10.6084/m9.figshare.11610279
title: Additional file 2 of Early inoculation with caecal fermentation broth alters small intestine morphology, gene expression of tight junction proteins in the ileum, and the caecal metabolomic profiling of broilers

description: Additional file 2: Table S1. The hierarchical clustering data matrix for the C group and the F group on days 7 and 14.
DOI: 10.6084/m9.figshare.11610279.v1
title: MOESM2 of Early inoculation with caecal fermentation broth alters small intestine morphology, gene expression of tight junction proteins in the ileum, and the caecal metabolomic profiling of broilers

description: Additional file 2: Table S1. The hierarchical clustering data matrix for the C group and the F group on days 7 and 14.
DOI: 10.6084/m9.figshare.11610285
title: Additional file 3 of Early inoculation with caecal fermentation broth alters small intestine morphology, gene expression of tight junction proteins in the ileum, and the caecal metabolomic profiling of broilers

description: Additional file 3: Table S2. Significantly different metabolites between the C group and the F group. The red text indicates the significantly different metabolite that is more abundant in the F group, while the blue text represents the higher concentration of significantly different metabolite in the C group.
DOI: 10.6084/m9.figshare.11610285.v1
title: MOESM3 of Early inoculation with caecal fermentation broth alters small intestine morphology, gene expression of tight junction proteins in the ileum, and the caecal metabolomic profiling of broilers

description: Additional file 3: Table S2. Significantly different metabolites between the C group and the F group. The red text indicates the significantly different metabolite that is more abundant in the F group, while the blue text represents the higher concentration of significantly different metabolite in the C group.
DOI: 10.6084/m9.figshare.11610291
title: Additional file 4 of Early inoculation with caecal fermentation broth alters small intestine morphology, gene expression of tight junction proteins in the ileum, and the caecal metabolomic profiling of broilers

description: Additional file 4: Table S3. Pathway analysis for the C group and the F group on days 7 and 14.
DOI: 10.4121/88659ee9-8659-42d2-97f9-ec940f8f3b07
title: 20211109 20211215 Main deployment - lidar 1 - Nearshore - RealDune/REFLEX

description: Lidar 1 measurements of the main November - December deployment of the RealDune/REFLEX experiments at the Dutch coast in Autumn/Winter 2021/2022. This dataset is part of the data collection 'Nearshore coastal measurements of calm, moderate, and storm conditions at two artificial dunes along the Dutch Coast during the RealDune/REFLEX experiments'.
DOI: 10.4121/88659ee9-8659-42d2-97f9-ec940f8f3b07.v2
title: 20211109 20211215 Main deployment - lidar 1 - Nearshore - RealDune/REFLEX

description: Lidar 1 measurements of the main November - December deployment of the RealDune/REFLEX experiments at the Dutch coast in Autumn/Winter 2021/2022. This dataset is part of the data collection 'Nearshore coastal measurements of calm, moderate, and storm conditions at two artificial dunes along the Dutch Coast during the RealDune/REFLEX experiments'.
DOI: 10.6084/m9.figshare.11610291.v1
title: MOESM4 of Early inoculation with caecal fermentation broth alters small intestine morphology, gene expression of tight junction proteins in the ileum, and the caecal metabolomic profiling of broilers

description: Additional file 4: Table S3. Pathway analysis for the C group and the F group on days 7 and 14.
DOI: 10.4121/3b7414be-cbb1-4451-888b-4cb28caf6bbc
title: 20211109 20211215 Main deployment - lidar 3 - Nearshore - RealDune/REFLEX

description: Lidar 3 measurements of the main November - December deployment of the RealDune/REFLEX experiments at the Dutch coast in Autumn/Winter 2021/2022. This dataset is part of the data collection 'Nearshore coastal measurements of calm, moderate, and storm conditions at two artificial dunes along the Dutch Coast during the RealDune/REFLEX experiments'.
DOI: 10.4121/3b7414be-cbb1-4451-888b-4cb28caf6bbc.v2
title: 20211109 20211215 Main deployment - lidar 3 - Nearshore - RealDune/REFLEX

description: Lidar 3 measurements of the main November - December deployment of the RealDune/REFLEX experiments at the Dutch coast in Autumn/Winter 2021/2022. This dataset is part of the data collection 'Nearshore coastal measurements of calm, moderate, and storm conditions at two artificial dunes along the Dutch Coast during the RealDune/REFLEX experiments'.
DOI: 10.6084/m9.figshare.5318980
title: An injectable <i>in situ</i> gel with cubic and hexagonal nanostructures for local treatment of chronic periodontitis

description: Periodontitis is a chronic bacterial infection, and its effective treatment is dependent on the retention of antibiotics of effective concentrations at the periodontal pockets. In this study, a solution–gel based inverse lyotropic liquid crystalline (LLC) system was explored to deliver metronidazole to the periodontal pockets for local treatment of periodontitis. It was found that the metronidazole-loaded LLC precursor spontaneously transformed into gel in the presence of water in the oral cavity. The low viscosity of the precursor would allow its penetration to the rather difficult to reach infection sites, while the adhesiveness and crystalline nanostructures (inverse bicontinuous cubic Pn3m phase and inverse hexagonal phase) of the formed gel would permit its firm adhesion to the periodontal pockets. The LLC system provided sustained drug release over one week <i>in vitro</i>. Results from <i>in vivo</i> study using a rabbit periodontitis model showed that the LLC system was able to maintain the metronidazole concentrations in the periodontal pockets above the minimum inhibition concentration for over 10 days without detectable drug concentration in the blood. Owing to the spontaneous solution–gel transition in the periodontal pockets and unique liquid crystalline nanostructures, the LLC <i>in situ</i> gel provided effective treatment of periodontitis for a prolonged period of time with reduced systematic side effects, compared to metronidazole suspension which was effective for 24 h with detectable metronidazole concentrations in the blood after 6 h.
DOI: 10.6084/m9.figshare.10037609
title: Additional file 1 of Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE)

description: Rdata-file with two lists. The list “Mouse_Data” contains a genotype matrix of 1298 individuals and 9265 markers as well as a matrix with records of 13 traits of the individuals. The list “Simulated_Data” offers the genotypes and phenotypes of the 20 simulations. Each entry of this list is a list of two elements representing genotypes and phenotypes of the respective simulation. Genotypes are given by a matrix of 1000 individuals with 9000 markers. Phenotypes are provided as a data.frame of the 1000 individuals and the 9 different phenotypes described in the Methods section. (RDATA 64512 kb)
DOI: 10.6084/m9.figshare.10037609.v1
title: Additional file 1 of Genomic prediction with epistasis models: on the marker-coding-dependent performance of the extended GBLUP and properties of the categorical epistasis model (CE)

description: Rdata-file with two lists. The list “Mouse_Data” contains a genotype matrix of 1298 individuals and 9265 markers as well as a matrix with records of 13 traits of the individuals. The list “Simulated_Data” offers the genotypes and phenotypes of the 20 simulations. Each entry of this list is a list of two elements representing genotypes and phenotypes of the respective simulation. Genotypes are given by a matrix of 1000 individuals with 9000 markers. Phenotypes are provided as a data.frame of the 1000 individuals and the 9 different phenotypes described in the Methods section. (RDATA 64512 kb)
DOI: 10.6084/m9.figshare.22618669.v1
title: Additional file 2 of GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

description: Additional file 2. FigS2. PCA plot of the data before and after the batch effect removal. (A) PCA results before the batch effect removal. (B) PCA results after the batch effect removal.
DOI: 10.6084/m9.figshare.8987129
title: Henoch-Schönlein purpura nephritis associated with monoclonal gammopathy of renal significance: a case report

description: Monoclonal gammopathy of renal significance (MGRS) can present with different morphologic features and lead to kidney failure. The Henoch-Schönlein purpura nephritis (HSPN) that cannot be relieved by treatment with glucocorticoid and immunosuppressive agents suggests the presence of monoclonal gammopathy in adult patients. The present study reports on a single case of HSPN associated with IgA-κMGRS. The patient who suffered from recurrent skin purpura for 6 months and nephrotic syndrome for 2 months was admitted to our hospital. Bone marrow biopsy showed monoclonal gammopathy of undetermined significance. Kidney biopsy indicated a Henoch-Schönlein purpura nephritis (HSPN, ISKDC classified as type III) with positive staining with κ-light chain in the glomeruli and renal tubular epithelial cells. Furthermore, skin biopsy showed leukocytoclastic vasculitis and negative staining for Congo red and light chain. Given both the renal and cutaneous involvement, the patient was considered to have HSPN associated with IgA-κMGRS. The patient experienced an exacerbation in his purpura-like lesions and clinical status after treatment with glucocorticoid and immunosuppressive agents. Consequently, the patient was put on a regimen that included dexamethasone (20 mg on the 1st, 4th, 8th, and 11th days of each month, iv) and bortezomib (2.4 mg on the 1st, 4th, 8th, and 11th days of each month, iv). Eight weeks after treatment, he had complete resolution of his cutaneous purpura and his biochemical parameters improved. The latent presence of MGRS in cases of HSPN should be considered in adult patients. Increased cognizance and correct treatment options could improve patient outcomes.
DOI: 10.6084/m9.figshare.22618675.v1
title: Additional file 4 of GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

description: Additional file 4. Differentially expressed mRNAs.
DOI: 10.6084/m9.figshare.22618678
title: Additional file 5 of GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

description: Additional file 5. GO enrichment analysis of the DEMs.
DOI: 10.6084/m9.figshare.25183763
title: 391 Metagenome Assembled Genomes (MAGs), taxonomic analysis and functional annotations from LDPE-contaminated paddy soils.

description: 391 Metagenome Assembled Genomes (MAGs) retrieved from 36 samples taken from LDPE-contaminated paddy soils. 353 bacterial MAGs and 38 archaeal MAGs. For MAGs taxonomic analysis and functional annotations are also included. If you do use our datasets in your research, please acknowledge the authors of the original study, and cite the work in which the datasets were first used.
DOI: 10.6084/m9.figshare.22618669
title: Additional file 2 of GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA

description: Additional file 2. FigS2. PCA plot of the data before and after the batch effect removal. (A) PCA results before the batch effect removal. (B) PCA results after the batch effect removal.
DOI: 10.25413/sun.25101698
title: In the Climate Change Fight: Open Access GIS and Earth Observation is might: Literature Review (LitRev) and Tools and application survey results.

description: This Excel dataset comprises surveyed information on the use of GIS and remote sensing platforms in climate justice initiatives, providing valuable insights from professionals and stakeholders in the field. This dataset forms the basis for the research paper, offering a comprehensive overview of current platforms / applications in addressing climate justice concerns.