The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have ...Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have read‘SCRs’.In Table 7 of this article,the column header ρ_fuel was incorrect and should have read CPv_fuel.For completeness and transparency,the old incorrect version and the corrected version of Table 7 are displayed below.展开更多
It is known that correlation does not imply causality.Some relationships identified in the analysis of data are coincidental or unknown,and some are produced by real-world causality of the situation,which is problemat...It is known that correlation does not imply causality.Some relationships identified in the analysis of data are coincidental or unknown,and some are produced by real-world causality of the situation,which is problematic,since there is a need to differentiate between these two scenarios.Until recently,the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data.This has changed with the advance of large language models,which are often utilized as surrogates for such human experts,making the process automated and readily available to all data analysts.This motivates the main objective of this work,which is to introduce the design and implementation of a large language model-based semantic causality evaluator based on correlation analysis,together with its visual analysis model called Causal heatmap.After the implementation itself,the model is evaluated from the point of view of the quality of the visual model,from the point of view of the quality of causal evaluation based on large language models,and from the point of view of comparative analysis,while the results reached in the study highlight the usability of large language models in the task and the potential of the proposed approach in the analysis of unknown datasets.The results of the experimental evaluation demonstrate the usefulness of the Causal heatmap method,supported by the evident highlighting of interesting relationships,while suppressing irrelevant ones.展开更多
To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains i...To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.展开更多
Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may po...Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.展开更多
Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces th...Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces the accuracy of conventional methods.This article proposes a user-friendly software for PSD analysis,GranuSAS,which employs an algorithm that integrates truncated singular value decomposition(TSVD)with the Chahine method.This approach employs TSVD for data preprocessing,generating a set of initial solutions with noise suppression.A high-quality initial solution is subsequently selected via the L-curve method.This selected candidate solution is then iteratively refined by the Chahine algorithm,enforcing constraints such as non-negativity and improving physical interpretability.Most importantly,GranuSAS employs a parallel architecture that simultaneously yields inversion results from multiple shape models and,by evaluating the accuracy of each model's reconstructed scattering curve,offers a suggestion for model selection in material systems.To systematically validate the accuracy and efficiency of the software,verification was performed using both simulated and experimental datasets.The results demonstrate that the proposed software delivers both satisfactory accuracy and reliable computational efficiency.It provides an easy-to-use and reliable tool for researchers in materials science,helping them fully exploit the potential of SAXS in nanoparticle characterization.展开更多
Background:Epidemiological studies have confirmed that longer exposure to insecticides like cypermethrin(CYP)significantly increases the risk of male reproductive toxicity.Crocus sativus L.has been recognized due to i...Background:Epidemiological studies have confirmed that longer exposure to insecticides like cypermethrin(CYP)significantly increases the risk of male reproductive toxicity.Crocus sativus L.has been recognized due to its therapeutic properties,but its exact role and molecular mechanisms in treatment of reproductive dysfunction remain unclear.Methods:During this study,36 rats were randomly divided into six groups(n=6):control,CYP-induced(60 mg/kg),standard(leuprolide 3 mg/kg)and three treatment groups receiving aqueous,ethanolic,and oil extracts(50 mg/kg or 20 mL/kg)for post-toxicity induction.Results:The finding represented that exposure of CYP significantly increased oxidative stress,disrupted testicular architecture,and markedly reduced testosterone levels(P<0.05).Importantly,Crocus sativus L.treatment alleviated these changes by increasing the expression of Nrf2(nuclear factor erythroid 2-related factor 2),restoring the activity of antioxidant enzymes,and enhancing testicular histomorphology.Surprisingly,molecular docking established a high binding affinity of Crocus sativus L.phytoconstituents such as gallic acid,cinnamic acid and quercetin to the Nrf2-Keap1 complex.It is worth noting that,Crocus sativus L.exhibited a high level of protection against reproductive toxicity caused by CYP in male rats,which was mediated by the activation of Nrf2 pathway,reduction of oxidative damage,and favorable ADMET characteristics.Conclusion:Notably,this research provides a more valid,safe,and effective method of developing new drugs for reproductive disorders,however,further investigation is needed to support the research findings and implement it in clinical practice.展开更多
As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal vari...As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.展开更多
App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While t...App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.展开更多
In this paper,we develop a multi-scalar auxiliary variables(MSAV)scheme for the Cahn-Hilliard Magnetohydrodynamics system by introducing two scalar auxiliary variables(SAV).This scheme is linear,fully decoupled and un...In this paper,we develop a multi-scalar auxiliary variables(MSAV)scheme for the Cahn-Hilliard Magnetohydrodynamics system by introducing two scalar auxiliary variables(SAV).This scheme is linear,fully decoupled and unconditionally stable in energy.Subsequently,we provide a detailed implementation procedure for full decoupling.Thus,at each time step,only a series of linear differential equations with constant coefficients need to be solved.To validate the effectiveness of our approach,we conduct an error analysis for this first-order scheme.Finally,some numerical experiments are provided to verify the energy dissipation of the system and the convergence of the proposed approach.展开更多
Molten salt reactors(MSRs)are a promising candidate for Generation IV reactor technologies,and the small modular molten salt reactor(SM-MSR),which utilizes low-enriched uranium and thorium fuels,is regarded as a wise ...Molten salt reactors(MSRs)are a promising candidate for Generation IV reactor technologies,and the small modular molten salt reactor(SM-MSR),which utilizes low-enriched uranium and thorium fuels,is regarded as a wise development path to accelerate deployment time.Uncertainty and sensitivity analyses of accidents guide nuclear reactor design and safety analyses.Uncertainty analysis can ascertain the safety margin,and sensitivity analysis can reveal the correlation between accident consequences and input parameters.Loss of forced cooling(LOFC)represents an accident scenario of the SM-MSR,and the study of LOFC could offer useful information to improve physical thermohydraulic and structural designs.Therefore,this study investigates the uncertainty of LOFC consequences and the sensitivity of related parameters.The uncertainty of the LOFC consequences was analyzed using the Monte Carlo method,and multiple linear regression was employed to analyze the sensitivity of the input parameters.The uncertainty and sensitivity analyses showed that the maximum reactor outlet fuel salt temperature was 725.5℃,which is lower than the acceptable criterion,and five important parameters influencing LOFC consequences were identified.展开更多
In this paper,Isogeometric analysis(IGA)is effectively integrated with machine learning(ML)to investigate the bearing capacity of strip footings in layered soil profiles,with a focus on a sand-over-clay configuration....In this paper,Isogeometric analysis(IGA)is effectively integrated with machine learning(ML)to investigate the bearing capacity of strip footings in layered soil profiles,with a focus on a sand-over-clay configuration.The study begins with the generation of a comprehensive dataset of 10,000 samples from IGA upper bound(UB)limit analyses,facilitating an in-depth examination of various material and geometric conditions.A hybrid deep neural network,specifically the Whale Optimization Algorithm-Deep Neural Network(WOA-DNN),is then employed to utilize these 10,000 outputs for precise bearing capacity predictions.Notably,the WOA-DNN model outperforms conventional ML techniques,offering a robust and accurate prediction tool.This innovative approach explores a broad range of design parameters,including sand layer depth,load-to-soil unit weight ratio,internal friction angle,cohesion,and footing roughness.A detailed analysis of the dataset reveals the significant influence of these parameters on bearing capacity,providing valuable insights for practical foundation design.This research demonstrates the usefulness of data-driven techniques in optimizing the design of shallow foundations within layered soil profiles,marking a significant stride in geotechnical engineering advancements.展开更多
Based on the site investigation of a lightning stroke accident in a coal mine in Weiyuan County during a strong thunderstorm process on the night of August 10,2024,combined with the investigation data of the accident ...Based on the site investigation of a lightning stroke accident in a coal mine in Weiyuan County during a strong thunderstorm process on the night of August 10,2024,combined with the investigation data of the accident site,the causes of the lightning stroke accident were analyzed,and the corresponding rectification suggestions were put forward.展开更多
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
文摘Correction to:Nuclear Science and Techniques(2025)36:111 https://doi.org/10.1007/s41365-025-01681-9.In the sentence beginning‘The weights of the parameters used for the…’in this article,the text‘RCSs’should have read‘SCRs’.In Table 7 of this article,the column header ρ_fuel was incorrect and should have read CPv_fuel.For completeness and transparency,the old incorrect version and the corrected version of Table 7 are displayed below.
基金supported by University Grant Agency of Matej Bel University in Banská Bystrica project number UGA-14-PDS-2025.
文摘It is known that correlation does not imply causality.Some relationships identified in the analysis of data are coincidental or unknown,and some are produced by real-world causality of the situation,which is problematic,since there is a need to differentiate between these two scenarios.Until recently,the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data.This has changed with the advance of large language models,which are often utilized as surrogates for such human experts,making the process automated and readily available to all data analysts.This motivates the main objective of this work,which is to introduce the design and implementation of a large language model-based semantic causality evaluator based on correlation analysis,together with its visual analysis model called Causal heatmap.After the implementation itself,the model is evaluated from the point of view of the quality of the visual model,from the point of view of the quality of causal evaluation based on large language models,and from the point of view of comparative analysis,while the results reached in the study highlight the usability of large language models in the task and the potential of the proposed approach in the analysis of unknown datasets.The results of the experimental evaluation demonstrate the usefulness of the Causal heatmap method,supported by the evident highlighting of interesting relationships,while suppressing irrelevant ones.
文摘To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.
基金supported by the National Natural Science Foundation of China(No.22176200)the Industrial Innovation Entrepreneurial Team Project of Ordos 2021.
文摘Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.
基金Project supported by the Project of the Anhui Provincial Natural Science Foundation(Grant No.2308085MA19)Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA0410401)+2 种基金the National Natural Science Foundation of China(Grant No.52202120)the National Key Research and Development Program of China(Grant No.2023YFA1609800)USTC Research Funds of the Double First-Class Initiative(Grant No.YD2310002013)。
文摘Small angle x-ray scattering(SAXS)is an advanced technique for characterizing the particle size distribution(PSD)of nanoparticles.However,the ill-posed nature of inverse problems in SAXS data analysis often reduces the accuracy of conventional methods.This article proposes a user-friendly software for PSD analysis,GranuSAS,which employs an algorithm that integrates truncated singular value decomposition(TSVD)with the Chahine method.This approach employs TSVD for data preprocessing,generating a set of initial solutions with noise suppression.A high-quality initial solution is subsequently selected via the L-curve method.This selected candidate solution is then iteratively refined by the Chahine algorithm,enforcing constraints such as non-negativity and improving physical interpretability.Most importantly,GranuSAS employs a parallel architecture that simultaneously yields inversion results from multiple shape models and,by evaluating the accuracy of each model's reconstructed scattering curve,offers a suggestion for model selection in material systems.To systematically validate the accuracy and efficiency of the software,verification was performed using both simulated and experimental datasets.The results demonstrate that the proposed software delivers both satisfactory accuracy and reliable computational efficiency.It provides an easy-to-use and reliable tool for researchers in materials science,helping them fully exploit the potential of SAXS in nanoparticle characterization.
文摘Background:Epidemiological studies have confirmed that longer exposure to insecticides like cypermethrin(CYP)significantly increases the risk of male reproductive toxicity.Crocus sativus L.has been recognized due to its therapeutic properties,but its exact role and molecular mechanisms in treatment of reproductive dysfunction remain unclear.Methods:During this study,36 rats were randomly divided into six groups(n=6):control,CYP-induced(60 mg/kg),standard(leuprolide 3 mg/kg)and three treatment groups receiving aqueous,ethanolic,and oil extracts(50 mg/kg or 20 mL/kg)for post-toxicity induction.Results:The finding represented that exposure of CYP significantly increased oxidative stress,disrupted testicular architecture,and markedly reduced testosterone levels(P<0.05).Importantly,Crocus sativus L.treatment alleviated these changes by increasing the expression of Nrf2(nuclear factor erythroid 2-related factor 2),restoring the activity of antioxidant enzymes,and enhancing testicular histomorphology.Surprisingly,molecular docking established a high binding affinity of Crocus sativus L.phytoconstituents such as gallic acid,cinnamic acid and quercetin to the Nrf2-Keap1 complex.It is worth noting that,Crocus sativus L.exhibited a high level of protection against reproductive toxicity caused by CYP in male rats,which was mediated by the activation of Nrf2 pathway,reduction of oxidative damage,and favorable ADMET characteristics.Conclusion:Notably,this research provides a more valid,safe,and effective method of developing new drugs for reproductive disorders,however,further investigation is needed to support the research findings and implement it in clinical practice.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the Ministry of Science and Technology(MOST)Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4)。
文摘As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.
基金supported by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant no.(GPIP:13-612-2024).
文摘App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products.Automating the analysis of these reviews is vital for efficient review management.While traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior performance.This research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and satisfaction.We propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification accuracy.Comparative analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,respectively.Thesignificant contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews dataset.These advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.
基金Research Project Supported by Shanxi Scholarship Council of China(2021-029)International Cooperation Base and Platform Project of Shanxi Province(202104041101019)Basic Research Plan of Shanxi Province(202203021211129)。
文摘In this paper,we develop a multi-scalar auxiliary variables(MSAV)scheme for the Cahn-Hilliard Magnetohydrodynamics system by introducing two scalar auxiliary variables(SAV).This scheme is linear,fully decoupled and unconditionally stable in energy.Subsequently,we provide a detailed implementation procedure for full decoupling.Thus,at each time step,only a series of linear differential equations with constant coefficients need to be solved.To validate the effectiveness of our approach,we conduct an error analysis for this first-order scheme.Finally,some numerical experiments are provided to verify the energy dissipation of the system and the convergence of the proposed approach.
基金supported by the Youth Innovation Promotion Association(YIPA)(No.E329290101)of the Chinese Academy of Sciences。
文摘Molten salt reactors(MSRs)are a promising candidate for Generation IV reactor technologies,and the small modular molten salt reactor(SM-MSR),which utilizes low-enriched uranium and thorium fuels,is regarded as a wise development path to accelerate deployment time.Uncertainty and sensitivity analyses of accidents guide nuclear reactor design and safety analyses.Uncertainty analysis can ascertain the safety margin,and sensitivity analysis can reveal the correlation between accident consequences and input parameters.Loss of forced cooling(LOFC)represents an accident scenario of the SM-MSR,and the study of LOFC could offer useful information to improve physical thermohydraulic and structural designs.Therefore,this study investigates the uncertainty of LOFC consequences and the sensitivity of related parameters.The uncertainty of the LOFC consequences was analyzed using the Monte Carlo method,and multiple linear regression was employed to analyze the sensitivity of the input parameters.The uncertainty and sensitivity analyses showed that the maximum reactor outlet fuel salt temperature was 725.5℃,which is lower than the acceptable criterion,and five important parameters influencing LOFC consequences were identified.
文摘In this paper,Isogeometric analysis(IGA)is effectively integrated with machine learning(ML)to investigate the bearing capacity of strip footings in layered soil profiles,with a focus on a sand-over-clay configuration.The study begins with the generation of a comprehensive dataset of 10,000 samples from IGA upper bound(UB)limit analyses,facilitating an in-depth examination of various material and geometric conditions.A hybrid deep neural network,specifically the Whale Optimization Algorithm-Deep Neural Network(WOA-DNN),is then employed to utilize these 10,000 outputs for precise bearing capacity predictions.Notably,the WOA-DNN model outperforms conventional ML techniques,offering a robust and accurate prediction tool.This innovative approach explores a broad range of design parameters,including sand layer depth,load-to-soil unit weight ratio,internal friction angle,cohesion,and footing roughness.A detailed analysis of the dataset reveals the significant influence of these parameters on bearing capacity,providing valuable insights for practical foundation design.This research demonstrates the usefulness of data-driven techniques in optimizing the design of shallow foundations within layered soil profiles,marking a significant stride in geotechnical engineering advancements.
文摘Based on the site investigation of a lightning stroke accident in a coal mine in Weiyuan County during a strong thunderstorm process on the night of August 10,2024,combined with the investigation data of the accident site,the causes of the lightning stroke accident were analyzed,and the corresponding rectification suggestions were put forward.
