cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57760/sciencedb.37160
title: A dataset of shear strength of soy-protein adhesive
title: A dataset of shear strength of soy-protein adhesive

description: Bonding strength evaluation: The shear strength and tensile strength of the plywood was tested using a universal testing machine at a rate of 5 mm/min through the system project “Plastics-Determination of tensile properties”. Because the maximum tensile force limit of the machine is 5000 N, the adhesion area of plywood is set at 3cm² or 1cm2. The maximum force (F) applied to joints before failure was recorded. The resulting shear strength was calculated by dividing the F by the joint overlap area (A). The number of test samples for each data point is at least 10, ensuring that the fracture of each sample is caused by the adhesive layer rather than the substrate, and discarding any outliers that deviate from the average value by more than 3 MPa.
description: Bonding strength evaluation: The shear strength and tensile strength of the plywood was tested using a universal testing machine at a rate of 5 mm/min through the system project “Plastics-Determination of tensile properties”. Because the maximum tensile force limit of the machine is 5000 N, the adhesion area of plywood is set at 3cm² or 1cm2. The maximum force (F) applied to joints before failure was recorded. The resulting shear strength was calculated by dividing the F by the joint overlap area (A). The number of test samples for each data point is at least 10, ensuring that the fracture of each sample is caused by the adhesive layer rather than the substrate, and discarding any outliers that deviate from the average value by more than 3 MPa.
DOI: 10.17182/hepdata.165422.v1/t1
title: "Figure 3-a" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit VBF off-shell DNN output distribution in the VBF off-shell SR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t2
title: "Figure 3-b" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit ggF off-shell DNN output distribution in the 2-jets ggF off-shell SR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t3
title: "Figure 3-c" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit ggF off-shell DNN output distribution in the 1-jet ggF off-shell SR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t4
title: "Figure 3-d" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit ggF off-shell DNN output distribution in the 0-jets ggF off-shell SR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t5
title: "Figure 4-a" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit VBF on-shell DNN output distribution in the VBF on-shell CR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t6
title: "Figure 4-b" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit ggF on-shell DNN output distribution in the 2-jets ggF on-shell CR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t7
title: "Figure 4-c" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit ggF on-shell DNN output distribution in the 1-jet ggF on-shell CR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t8
title: "Figure 4-d" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Post-fit ggF on-shell DNN output distribution in the 0-jets ggF on-shell CR. Different contributions to background are indicated by the colour-filled histograms. The grey-hatched error band shows total uncertainties. The ratio of observations to total expectations is given in the lower panel, together with the total uncertainties after fitting, indicated by the grey-hatched band.
description: No data abstract available.
DOI: 10.17182/hepdata.165422.v1/t9
title: "Table 1" of "Measurement of the Higgs boson total decay width using the H $\to$ WW $\to$ e$νμν$ decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV"

description: Measurements of off-shell signal strengths $\mu$ and $\Gamma_H$. Listed are the measurements of the \PH $\to \PW\PW$, $\mu_{\text{off-shell}}$ and $\Gamma_H$ in the $2\Pl 2\PGn$ channel. The central value (c.v.) is reported together with the 68\% and 95\% confidence levels.
description: No data abstract available.
DOI: 10.57760/sciencedb.37175
title: Single-atom Cu1/ZrO2 Coupled with SAPO-34 Enhances CO2 Hydrogenation to Light Olefins
title: Single-atom Cu1/ZrO2 Coupled with SAPO-34 Enhances CO2 Hydrogenation to Light Olefins

description: This is the data for the manuscript with title of Single-atom Cu1/ZrO2 Coupled with SAPO-34 Enhances CO2 Hydrogenation to Light Olefins. 
description: This is the data for the manuscript with title of Single-atom Cu1/ZrO2 Coupled with SAPO-34 Enhances CO2 Hydrogenation to Light Olefins.
DOI: 10.57760/sciencedb.37072
title: Determination of ITS full length of soil standard fungi
title: Determination of ITS full length of soil standard fungi

description: Soil standard fungal ITS full-length 
description: Soil standard fungal ITS full-length
DOI: 10.57760/sciencedb.37071
title: 16S full-length determination of soil standard bacteria
title: 土壤标准细菌16S全长测定

description: Soil sample - standard bacterial 16S full-length complete set 
description: Soil sample - standard bacterial 16S full-length complete set
DOI: 10.57760/sciencedb.37121
title: SEVENTY YEARS OF RESEARCH ADVANCES IN MOLECULAR EPIDEMIOLOGY OF GRASS CARP REOVIRUS IN CHINA
title: 我国草鱼呼肠孤病毒分子流行病学70年研究进展

description: Abstract: Grass carp reovirus (GCRV) is a double-stranded RNA (dsRNA) virus that causes grass carp hemorrhagic disease (GCHD), resulting in substantial economic losses in aquaculture. Based on genomic and epidemiological char acteristics, GCRV strains are classified into three genotypes (GCRV-Ⅰ—Ⅲ), among which genotype Ⅱ (GCRV-Ⅱ) being the predominant causative agent of GCHD outbreaks. Although GCRV-Ⅱ strains share over 95% nucleotide and protein sequence similarity, they exhibit marked differences in virulence and pathogenic effects on host metabolism. This review summarizes recent advances in the molecular and epidemiological characteristics of GCRV-Ⅱ, highlights key findings on strains with varying virulence, and discusses progress in diagnostic techniques and vaccine develop ment. Future research directions are proposed to facilitate effective prevention and control strategies for GCHD.
description: Abstract: Grass carp reovirus (GCRV) is a double-stranded RNA (dsRNA) virus that causes grass carp hemorrhagic disease (GCHD), resulting in substantial economic losses in aquaculture. Based on genomic and epidemiological char acteristics, GCRV strains are classified into three genotypes (GCRV-Ⅰ—Ⅲ), among which genotype Ⅱ (GCRV-Ⅱ) being the predominant causative agent of GCHD outbreaks. Although GCRV-Ⅱ strains share over 95% nucleotide and protein sequence similarity, they exhibit marked differences in virulence and pathogenic effects on host metabolism. This review summarizes recent advances in the molecular and epidemiological characteristics of GCRV-Ⅱ, highlights key findings on strains with varying virulence, and discusses progress in diagnostic techniques and vaccine develop ment. Future research directions are proposed to facilitate effective prevention and control strategies for GCHD.
DOI: 10.15468/dl.qxhe9j
title: Occurrence Download

description: A dataset containing 7801 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is THA",
 "TaxonKey is Cyprinidae"
 ]
}

 The dataset includes 7801 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010847-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57760/sciencedb.37075
title: Original files of Figures 1-12 for manuscript 2025-0646 in Chinese Journal of Rock Mechanics and Engineering Journal.
title: 岩石力学与工程学报2025-0646稿件图片1-12的原始文件

description: Original files of Figures 1-12 for manuscript 2025-0646 in Chinese Journal of Rock Mechanics and Engineering Journal.They are named Figures 1-12.
description: Original files of Figures 1-12 for manuscript 2025-0646 in Chinese Journal of Rock Mechanics and Engineering Journal.They are named Figures 1-12.
DOI: 10.26180/5619481
title: Particle swarm optimization for MEG source localization

description: The estimation of three-dimension neural active sources from the magnetoencephalography (MEG) record is a very critical issue for both clinical neurology and brain functions research. Nowadays multiple signal classification (MUSIC) algorithm and recursive MUSIC algorithm are widely used to locate dipolar sources from MEG data. The drawback of these algorithms is that they need excessive calculation and is quite time-consuming when scanning a three-dimensional space. In order to solve this problem, we propose a MEG sources localization scheme based on an improved Particle Swarm Optimization (PSO). This scheme uses the advantage of global searching ability of PSO to estimate the rough source location. Then combining with grids search in small area, the accurate dipolar source localization is performed. In addition, we compare the results of our method with those based on Genetic Algorithm (GA). Computer simulation results show that our PSO strategy is an effective and precise approach to dipole localization which can improve the speed greatly and localize the sources accurately. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.26180/5619481.v1
title: Particle swarm optimization for MEG source localization

description: The estimation of three-dimension neural active sources from the magnetoencephalography (MEG) record is a very critical issue for both clinical neurology and brain functions research. Nowadays multiple signal classification (MUSIC) algorithm and recursive MUSIC algorithm are widely used to locate dipolar sources from MEG data. The drawback of these algorithms is that they need excessive calculation and is quite time-consuming when scanning a three-dimensional space. In order to solve this problem, we propose a MEG sources localization scheme based on an improved Particle Swarm Optimization (PSO). This scheme uses the advantage of global searching ability of PSO to estimate the rough source location. Then combining with grids search in small area, the accurate dipolar source localization is performed. In addition, we compare the results of our method with those based on Genetic Algorithm (GA). Computer simulation results show that our PSO strategy is an effective and precise approach to dipole localization which can improve the speed greatly and localize the sources accurately. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.26180/5619478
title: PSOMF: An algorithm for pattern discovery using PSO

description: The task of transcription factor binding sites discovery from the upstream region of gene, without any prior knowledge of what look likes, is very challenging. In this paper we propose an algorithm based on Particle Swarm Optimization (PSO) to identify motif instances in multiple biological sequences. The experimental results on yeast sac-choromyces Cerevisae transcription factor binding sites, demonstrate that the proposed method is working analogous to YMF, MEME and AlignACE algorithms. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.57760/sciencedb.16728
title: SuperBand: Superconductor's energy band
title: SuperBand 超导材料能带数据库

description: In comparison to simpler data such as chemical formulas and lattice structures, energy band structure data provide a more fundamental and intuitive insight into superconducting phenomena. In this work, we generate superconductor's lattice structure files optimized for density functional theory (DFT) calculations. Through DFT, we obtain key electronic properties for experimentally confirmed superconductors, including band structures, density of states (DOS), and Fermi surface data. Additionally, we outline efficient methodologies for acquiring structural data, establish high-throughput DFT computational protocols, and introduce tools for extracting this data from large-scale DFT calculations. As an example, we have curated a dataset containing information on 2474 superconductors along with their experimentally determined superconducting transition temperatures (Tc), which is well-suited for machine learning applications. This work also provides guidelines for accessing and utilizing this dataset. Furthermore, we present a neural network model designed for training with this data. All the aforementioned data and code are publicly available at http://www.superband.work.
description: In comparison to simpler data such as chemical formulas and lattice structures, energy band structure data provide a more fundamental and intuitive insight into superconducting phenomena. In this work, we generate superconductor's lattice structure files optimized for density functional theory (DFT) calculations. Through DFT, we obtain key electronic properties for experimentally confirmed superconductors, including band structures, density of states (DOS), and Fermi surface data. Additionally, we outline efficient methodologies for acquiring structural data, establish high-throughput DFT computational protocols, and introduce tools for extracting this data from large-scale DFT calculations. As an example, we have curated a dataset containing information on 2474 superconductors along with their experimentally determined superconducting transition temperatures (Tc), which is well-suited for machine learning applications. This work also provides guidelines for accessing and utilizing this dataset. Furthermore, we present a neural network model designed for training with this data. All the aforementioned data and code are publicly available at http://www.superband.work.
DOI: 10.26180/5619478.v1
title: PSOMF: An algorithm for pattern discovery using PSO

description: The task of transcription factor binding sites discovery from the upstream region of gene, without any prior knowledge of what look likes, is very challenging. In this paper we propose an algorithm based on Particle Swarm Optimization (PSO) to identify motif instances in multiple biological sequences. The experimental results on yeast sac-choromyces Cerevisae transcription factor binding sites, demonstrate that the proposed method is working analogous to YMF, MEME and AlignACE algorithms. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.26180/5619475
title: A novel protein motif finding algorithm for classification of the ligase subfamilies

description: The algorithm of extracting motifs from a family or subfamily is still a hot spot in bioinformatics. It not only contributes to understand functions of proteins and predicts the classification which a unknown protein sequence belongs to, but also helps to study the protein-protein interaction. In this paper, we present a novel algorithm to extract motifs of a subfamily, which is based on feature selection and position connection. Position connection is applied to generate motifs, which is the hybrid method with mechanism of vote decision-making to construct the classifier of the ligase subfamilies. Through testing in the database, more than 95.87% predictive accuracy is achieved. The result demonstrates that this novel method is practical. In addition, the method illuminates that motifs play an important role to classify proteins and research the characteristics of the subfamilies or families of protein database. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.26180/5619475.v1
title: A novel protein motif finding algorithm for classification of the ligase subfamilies

description: The algorithm of extracting motifs from a family or subfamily is still a hot spot in bioinformatics. It not only contributes to understand functions of proteins and predicts the classification which a unknown protein sequence belongs to, but also helps to study the protein-protein interaction. In this paper, we present a novel algorithm to extract motifs of a subfamily, which is based on feature selection and position connection. Position connection is applied to generate motifs, which is the hybrid method with mechanism of vote decision-making to construct the classifier of the ligase subfamilies. Through testing in the database, more than 95.87% predictive accuracy is achieved. The result demonstrates that this novel method is practical. In addition, the method illuminates that motifs play an important role to classify proteins and research the characteristics of the subfamilies or families of protein database. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.26180/5619472
title: Minimal siRNA set cover heuristic for gene family knockdown

description: PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
DOI: 10.26180/5619472.v1
title: Minimal siRNA set cover heuristic for gene family knockdown

description: PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1

Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; 
Chetty, Madhu ; 
Ahmad, Shandar ; 
Ngom, Alioune ; 
Teng, Shyh Wei ; 
Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; 
Coverage: 
Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.