During strike-slip fault dislocation,multiple fault planes are commonly observed.The resulting permanent ground deformation can lead to profound structural damage to tunnels.However,existing analytical models do not c...During strike-slip fault dislocation,multiple fault planes are commonly observed.The resulting permanent ground deformation can lead to profound structural damage to tunnels.However,existing analytical models do not consider multiple fault planes.Instead,they concentrate the entire fault displacement onto a single fault plane for analysis,thereby giving rise to notable errors in the calculated results.To address this issue,a refined nonlinear theoretical model was established to analyze the mechanical responses of the tunnels subjected to multiple strike-slip fault dislocations.The analytical model considers the number of fault planes,nonlinear soil‒tunnel interactions,geometric nonlinearity,and fault zone width,leading to a significant improvement in its range of applicability and calculation accuracy.The results of the analytical model are in agreement,both qualitatively and quantitatively,with the model test and numerical results.Then,based on the proposed theoretical model,a sensitivity analysis of parameters was conducted,focusing on the variables such as the number of fault planes,fault plane distance(d),fault displacement ratio(η),burial depth(C),crossing angle(β),tunnel diameter(D),fault zone width(Wf),and strike-slip fault displacement(Δfs).The results show that the peak shear force(Vmax),bending moment(Mmax),and axial force(Nmax)decrease with increasing d.The Vmax of the tunnel is found at the fault plane with the largest fault displacement.C,D,andΔfs contribute to the increases in Vmax,Mmax,and Nmax.Additionally,increasing the number of fault planes reduces Vmax and Mmax,whereas the variation in Nmax remains minimal.展开更多
Reconstruction during the oxygen evolution reaction(OER)significantly transforms the geometric structure of transition metal compounds,leading to enhanced catalytic performance.However,the resulting structural disorde...Reconstruction during the oxygen evolution reaction(OER)significantly transforms the geometric structure of transition metal compounds,leading to enhanced catalytic performance.However,the resulting structural disorder complicates the development of accurate theoretical models.In this study,CoS2 is used as a model system to establish a framework for rationally modeling reconstructed OER catalysts based on density functional theory(DFT).In the reconstruction process,sulfur atoms are likely to be substituted by oxygen atoms,leading to the formation of the CoOOH phase.Based on the difference in reconstruction degree,we constructed three types of models:doping,heterostructure,and fully reconstructed,representing the reconstruction degree from minimal to full phase transition,respectively.Fully reconstructed models,which account for strain and vacancy effects,effectively simulate the unique coordination environments of reconstructed catalysts.Model e-CoOOH achieves a theoretical overpotential of 0.38 V,outperforming pristine CoOOH(0.56 V),demonstrating that the unique structural features resulting from reconstruction improve OER performance.The doping model and the heterostructure model are helpful to explain the electronic structure and performance transformation of the reconstruction process.This work provides a rational theoretical modeling approach,which is conducive to improving the reliability of the theoretical OER performance of the reconstructed catalyst.展开更多
The photosynthetic oxygen-evolving center(OEC)is a unique Mn_(4)CaO_(5)cluster catalyzing the water oxidation into electrons,protons and O_(2)through a five-intermediate state cycle(Sn,n=0,1,2,3,4).The modeling of OEC...The photosynthetic oxygen-evolving center(OEC)is a unique Mn_(4)CaO_(5)cluster catalyzing the water oxidation into electrons,protons and O_(2)through a five-intermediate state cycle(Sn,n=0,1,2,3,4).The modeling of OEC is essential for understanding the water oxidation mechanism and developing high efficient water oxidation catalysts.Recently,a series of Mn_(4)CaO_(4)model complexes have been synthesized,which have very similar structures to OEC and also show reactivity of water oxidation.In this work,we employed DFT method to investigate the stability of Mn_(4)CaO_(4)model complex in oxidative conditions,aiming to figure out whether it decomposes itself to release O_(2)during the catalytic water oxidation process.We discovered that the barrier for the O−O bond formation is quite high in the S1 and S2 states,while decreases to 40.2 kcal/mol in the S3 state,indicating the good stability in all oxidation states under normal conditions.Acetonitrile and pyridine can effectively reduce the barrier to 36.5 kcal/mol and 29.9 kcal/mol,respectively.Therefore,strong Lewis base,such as pyridine,could be harmful to the stability of Mn_(4)CaO_(4)and shall be avoided when designing such a catalytic system.Once the O−O bond is formed,Mn_(4)CaO_(4)in the S3 state can readily decompose to O_(2),solvated Ca^(2+)and Mn_(4)O_(2)complex,with the assistance of acetonitrile or pyridine.As a comparison,the O_(2)decomposition in the S2 state is kinetically hindered and thermodynamically disfavored.The S4 state Mn_(4)CaO_(4)has a much lower barrier for O-O bond formation,and is unstable.However,the S4 state Mn_(4)CaO_(4)is difficult to achieve under water oxidation condition,as evidenced by the calculated redox potential of 2.3 V for S3→S4 transition.展开更多
Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to...Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to better implement advertising activities,this study intends to summarize the relevant research on advertising avoidance in recent years.The specific method is to use the core literature meta-analysis method to identify,filter,and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance.We review the collected articles from the following perspectives:the definition and classification,external stimulating factors,internal perception factors,and moderating factors of advertising avoidance.On this basis,the SOMR model of advertising avoidance is constructed according to the SOR model.Finally,some prospects for future related research are presented.展开更多
This article aims tomodel and analyze the heat and fluid flow characteristics of a carboxymethyl cellulose(CMC)nanofluid within a convergent-divergent shaped microchannel(Two-dimensional).The base fluid,water+CMC(0.5%...This article aims tomodel and analyze the heat and fluid flow characteristics of a carboxymethyl cellulose(CMC)nanofluid within a convergent-divergent shaped microchannel(Two-dimensional).The base fluid,water+CMC(0.5%),is mixed with CuO and Al2O3 nanoparticles at volume fractions of 0.5%and 1.5%,respectively.The research is conducted through the conjugate usage of experimental and theoretical models to represent more realistic properties of the non-Newtonian nanofluid.Three types of microchannels including straight,divergent,and convergent are considered,all having the same length and identical inlet cross-sectional area.Using ANSYS FLUENT software,Navier-Stokes equations are solved for the laminar flow of the non-Newtonian nanofluid.The study examines the effects of Reynolds number,nanoparticle concentration and type,and microchannel geometry on flow and heat transfer.The results prove that the alumina nanoparticles outperform copper oxide in increasing the Nusselt number at a 0.5% volume fraction,while copper oxide nanoparticles excel at a 1.5%volume fraction.Moreover,in the selected case study,as the Reynolds number increases from 100 to 500,the Nusselt number rises by 56.26% in straight geometry,52.93% in divergent geometry,and 59.10%in convergent geometry.Besides,the Nusselt number enhances by 18.75% when transitioning from straight to convergent geometry at a Reynolds number of 500,and by 19.81%at a Reynolds number of 1000.Finally,the results of the research depict that the use of thermophysical properties derived from the experimental achievements,despite creating complexity in the modeling and the solution method,leads to more accurate and realistic outputs.展开更多
Over the next 20 years,China's urban rail transit(hereinafter referred to as'urban rail')will face large-scalerenovation of existing line facilities and equipment,with more than 1000 km of renovated lines ...Over the next 20 years,China's urban rail transit(hereinafter referred to as'urban rail')will face large-scalerenovation of existing line facilities and equipment,with more than 1000 km of renovated lines to be added eachyear.In 2024,the China Association of Metros issued the Guiding Opinions on the Renovation of Existing UrbanRail Transit Lines in China,providing guiding opinions on norms,standards,and implementation approaches forthe renovation of existing lines in the coming period.In the practical work of renovating existing urban rail lines,it is necessary to continuously explore and refine relevant theoretical methods in line with industry developmenttrends and urban development requirements.The following are the author's recent reflections on theoreticalinnovation in this field.展开更多
[Objectives]To explore the effects of motivational interviewing intervention based on the transtheoretical model(TTM)on psychological resilience and self-management in patients undergoing finger reimplantation after a...[Objectives]To explore the effects of motivational interviewing intervention based on the transtheoretical model(TTM)on psychological resilience and self-management in patients undergoing finger reimplantation after amputation.[Methods]The patients with finger replantation due to fractures admitted from October 2024 to June 2025 were divided into either the control group or the observation group according to the random number table method,with 40 cases in each group.The control group received conventional perioperative care,while the observation group underwent motivational interviewing based on TTM framework on the basis of the control group.The psychological resilience and self-management levels of the two patient groups were then compared following their respective care interventions.[Results]The psychological resilience and self-management scores of the patients were significantly higher than those of the control group after the intervention,with the difference being statistically significant(P<0.05).[Conclusions]Motivational interviewing based on the TTM can effectively improve the psychological resilience and self-management in patients undergoing severed finger reimplantation,while effectively reducing the occurrence of vascular crisis.展开更多
Rock discontinuities such as joints widely exist in natural rock masses,and wave attenuation through rock masses is mainly caused by discontinuities.The displacement discontinuity model(DDM)has been widely used in the...Rock discontinuities such as joints widely exist in natural rock masses,and wave attenuation through rock masses is mainly caused by discontinuities.The displacement discontinuity model(DDM)has been widely used in theoretical and numerical analysis of wave propagation across rock discontinuity.However,the circumstance under which the DDM is applicable to predict wave propagation across rock discontinuity remains poorly understood.In this study,theoretical analysis and ultrasonic laboratory tests were carried out to examine the theoretical applicability of the DDM for wave propagation,where specimens with rough joints comprising regular rectangular asperities of different spacings and heights were prepared by 3D printing technology.It is found that the theoretical applicability of the DDM to predict wave propagation across rock discontinuity is determined by three joint parameters,i.e.the dimensionless asperity spacing(L),the dimensionless asperity height(H)and the groove density(D).Through theoretical analysis and laboratory tests,the conditions under which the DDM is applicable are derived as follows:and,.With increase in the groove density,the thresholds of the dimensionless asperity spacing and the dimensionless asperity height show a decreasing trend.In addition,the transmission coefficient in the frequency domain decreases with increasing groove density,dimensionless asperity spacing or dimensionless asperity height.The findings can facilitate our understanding of DDM for predicting wave propagation across rock discontinuity.展开更多
Industrial robots are integral to modern manufacturing systems,enabling high precision,high throughput,and flexibility.However,errors in accuracy and repeatability,which arise from a variety of sources such as mechani...Industrial robots are integral to modern manufacturing systems,enabling high precision,high throughput,and flexibility.However,errors in accuracy and repeatability,which arise from a variety of sources such as mechanical wear,calibration issues,and environmental factors,can significantly impact the performance of industrial robots.This paper aims to explore the theoretical modeling of errors in industrial robot systems and propose compensation strategies to enhance their accuracy and repeatability.Key factors contributing to errors,such as kinematic,dynamic,and environmental influences,are discussed in detail.Additionally,the paper explores various compensation techniques,including geometric error compensation,dynamic compensation,and adaptive control approaches.Through the integration of error modeling and compensation methods,industrial robots can achieve improved performance,ensuring higher operational efficiency and product quality.The paper concludes by highlighting the challenges and future research directions for improving the accuracy and repeatability of industrial robots in practical applications.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter per...The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
Objective:To investigate the impact of health education nursing based on the Transtheoretical Model of Behavior Change on self-efficacy in osteoporosis patients with low bone mass.Methods:A total of 91 osteoporosis pa...Objective:To investigate the impact of health education nursing based on the Transtheoretical Model of Behavior Change on self-efficacy in osteoporosis patients with low bone mass.Methods:A total of 91 osteoporosis patients with low bone mass admitted to our hospital from June 2000 to the end of June 2023 were selected and randomly divided into an observation group and a control group using the envelope method,with 46 and 45 cases in each group,respectively.The control group received routine nursing care,while the observation group received health education nursing based on the Transtheoretical Model of Behavior Change.Bone mineral density(lumbar spine L1-L4,femoral neck),disease awareness(Osteoporosis Knowledge Test Questionnaire,OKT-Q),and self-efficacy(Adult Health Self-Management Skills Rating Scale,AHSMSRS)were compared between the two groups.Results:After the intervention,bone mineral density levels,disease awareness levels,and self-efficacy levels significantly increased in both groups,with the observation group showing greater improvements in all indicators compared to the control group(p<0.05).Conclusion:Interventions based on the Transtheoretical Model of Behavior Change effectively enhance patient self-efficacy and bone health by precisely matching behavioral stages,strengthening social support,and regulating neurobehavioral factors.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to use...This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.展开更多
Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy...Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.展开更多
Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we ...Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we developed the BETR-Urban-Rural-Veg model to quantitatively evaluate the influences of both natural vegetation and crops on the multimedia transport processes of Phenanthrene(PHE)and Benzo(a)pyrene(BaP)in mainland of China.The geographic distribution of polycyclic aromatic hydrocarbon(PAH)emissions and concentrations were consistent,displaying higher levels in northern China while lower levels in southern China.Under seasonal simulations,for both natural vegetation and crops,PAH concentrations in winter and spring were 1.5 to 27-fold higher than in summer and autumn,especially for PHE.Owing to the higher leaf area index(LAI)of natural vegetation and harvesting of crops,the filter and sequestration effect of natural vegetation was stronger than crops,while the seasonal changes of PAH concentrations in crops were more significant than natural vegetation.Temperature,precipitation rates and LAI might have important influences on seasonal concentrations and overall persistence of PAHs.PHE was more sensitive to the impacts of seasonal environmental parameters.Under different landscape scenarios,average annual PAH concentrations in natural vegetation were always a little higher than those in crops,and the overall persistence of BaP was greatly affected increasing by 15.15%-16.47%.This improved model provides a useful tool for environmental management.The results of this study are expected to support land use plans and decision-making in China's mainland.展开更多
Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiote...Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.展开更多
基金support from the National Natural Science Foundation of China(Grant Nos.52378411,52208404)China National Railway Group Limited Science and Technology Research and Development Program(Grant No.K2023G041).
文摘During strike-slip fault dislocation,multiple fault planes are commonly observed.The resulting permanent ground deformation can lead to profound structural damage to tunnels.However,existing analytical models do not consider multiple fault planes.Instead,they concentrate the entire fault displacement onto a single fault plane for analysis,thereby giving rise to notable errors in the calculated results.To address this issue,a refined nonlinear theoretical model was established to analyze the mechanical responses of the tunnels subjected to multiple strike-slip fault dislocations.The analytical model considers the number of fault planes,nonlinear soil‒tunnel interactions,geometric nonlinearity,and fault zone width,leading to a significant improvement in its range of applicability and calculation accuracy.The results of the analytical model are in agreement,both qualitatively and quantitatively,with the model test and numerical results.Then,based on the proposed theoretical model,a sensitivity analysis of parameters was conducted,focusing on the variables such as the number of fault planes,fault plane distance(d),fault displacement ratio(η),burial depth(C),crossing angle(β),tunnel diameter(D),fault zone width(Wf),and strike-slip fault displacement(Δfs).The results show that the peak shear force(Vmax),bending moment(Mmax),and axial force(Nmax)decrease with increasing d.The Vmax of the tunnel is found at the fault plane with the largest fault displacement.C,D,andΔfs contribute to the increases in Vmax,Mmax,and Nmax.Additionally,increasing the number of fault planes reduces Vmax and Mmax,whereas the variation in Nmax remains minimal.
基金supported by the National Key Research and Development program(2022YFA1504000)the National Natural Science Foundation of China(22302101)+4 种基金the Fundamental Research Funds for the Central Universities(63185015)Shenzhen Science and Technology Program(JCYJ20210324121002007,JCYJ20230807151503007)Yunnan Provincial Science and Technology Project at Southwest United Graduate School(202402AO370001)China Postdoctoral Science Foundation(2022M721699)Guangdong Basic and Applied Basic Research Foundation(2024A1515010347).
文摘Reconstruction during the oxygen evolution reaction(OER)significantly transforms the geometric structure of transition metal compounds,leading to enhanced catalytic performance.However,the resulting structural disorder complicates the development of accurate theoretical models.In this study,CoS2 is used as a model system to establish a framework for rationally modeling reconstructed OER catalysts based on density functional theory(DFT).In the reconstruction process,sulfur atoms are likely to be substituted by oxygen atoms,leading to the formation of the CoOOH phase.Based on the difference in reconstruction degree,we constructed three types of models:doping,heterostructure,and fully reconstructed,representing the reconstruction degree from minimal to full phase transition,respectively.Fully reconstructed models,which account for strain and vacancy effects,effectively simulate the unique coordination environments of reconstructed catalysts.Model e-CoOOH achieves a theoretical overpotential of 0.38 V,outperforming pristine CoOOH(0.56 V),demonstrating that the unique structural features resulting from reconstruction improve OER performance.The doping model and the heterostructure model are helpful to explain the electronic structure and performance transformation of the reconstruction process.This work provides a rational theoretical modeling approach,which is conducive to improving the reliability of the theoretical OER performance of the reconstructed catalyst.
基金supported by the National Natural Science Foundation of China(No.92061114)Chinese Academy of Sciences(XDB17010000)。
文摘The photosynthetic oxygen-evolving center(OEC)is a unique Mn_(4)CaO_(5)cluster catalyzing the water oxidation into electrons,protons and O_(2)through a five-intermediate state cycle(Sn,n=0,1,2,3,4).The modeling of OEC is essential for understanding the water oxidation mechanism and developing high efficient water oxidation catalysts.Recently,a series of Mn_(4)CaO_(4)model complexes have been synthesized,which have very similar structures to OEC and also show reactivity of water oxidation.In this work,we employed DFT method to investigate the stability of Mn_(4)CaO_(4)model complex in oxidative conditions,aiming to figure out whether it decomposes itself to release O_(2)during the catalytic water oxidation process.We discovered that the barrier for the O−O bond formation is quite high in the S1 and S2 states,while decreases to 40.2 kcal/mol in the S3 state,indicating the good stability in all oxidation states under normal conditions.Acetonitrile and pyridine can effectively reduce the barrier to 36.5 kcal/mol and 29.9 kcal/mol,respectively.Therefore,strong Lewis base,such as pyridine,could be harmful to the stability of Mn_(4)CaO_(4)and shall be avoided when designing such a catalytic system.Once the O−O bond is formed,Mn_(4)CaO_(4)in the S3 state can readily decompose to O_(2),solvated Ca^(2+)and Mn_(4)O_(2)complex,with the assistance of acetonitrile or pyridine.As a comparison,the O_(2)decomposition in the S2 state is kinetically hindered and thermodynamically disfavored.The S4 state Mn_(4)CaO_(4)has a much lower barrier for O-O bond formation,and is unstable.However,the S4 state Mn_(4)CaO_(4)is difficult to achieve under water oxidation condition,as evidenced by the calculated redox potential of 2.3 V for S3→S4 transition.
文摘Advertising avoidance is resistance to advertising intrusion.This issue has been the subject of much academic research in recent years.To guide scholars to better carry out relevant research and promote enterprises to better implement advertising activities,this study intends to summarize the relevant research on advertising avoidance in recent years.The specific method is to use the core literature meta-analysis method to identify,filter,and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance.We review the collected articles from the following perspectives:the definition and classification,external stimulating factors,internal perception factors,and moderating factors of advertising avoidance.On this basis,the SOMR model of advertising avoidance is constructed according to the SOR model.Finally,some prospects for future related research are presented.
文摘This article aims tomodel and analyze the heat and fluid flow characteristics of a carboxymethyl cellulose(CMC)nanofluid within a convergent-divergent shaped microchannel(Two-dimensional).The base fluid,water+CMC(0.5%),is mixed with CuO and Al2O3 nanoparticles at volume fractions of 0.5%and 1.5%,respectively.The research is conducted through the conjugate usage of experimental and theoretical models to represent more realistic properties of the non-Newtonian nanofluid.Three types of microchannels including straight,divergent,and convergent are considered,all having the same length and identical inlet cross-sectional area.Using ANSYS FLUENT software,Navier-Stokes equations are solved for the laminar flow of the non-Newtonian nanofluid.The study examines the effects of Reynolds number,nanoparticle concentration and type,and microchannel geometry on flow and heat transfer.The results prove that the alumina nanoparticles outperform copper oxide in increasing the Nusselt number at a 0.5% volume fraction,while copper oxide nanoparticles excel at a 1.5%volume fraction.Moreover,in the selected case study,as the Reynolds number increases from 100 to 500,the Nusselt number rises by 56.26% in straight geometry,52.93% in divergent geometry,and 59.10%in convergent geometry.Besides,the Nusselt number enhances by 18.75% when transitioning from straight to convergent geometry at a Reynolds number of 500,and by 19.81%at a Reynolds number of 1000.Finally,the results of the research depict that the use of thermophysical properties derived from the experimental achievements,despite creating complexity in the modeling and the solution method,leads to more accurate and realistic outputs.
文摘Over the next 20 years,China's urban rail transit(hereinafter referred to as'urban rail')will face large-scalerenovation of existing line facilities and equipment,with more than 1000 km of renovated lines to be added eachyear.In 2024,the China Association of Metros issued the Guiding Opinions on the Renovation of Existing UrbanRail Transit Lines in China,providing guiding opinions on norms,standards,and implementation approaches forthe renovation of existing lines in the coming period.In the practical work of renovating existing urban rail lines,it is necessary to continuously explore and refine relevant theoretical methods in line with industry developmenttrends and urban development requirements.The following are the author's recent reflections on theoreticalinnovation in this field.
基金Supported by 2023 Shiyan Taihe Hospital Fund Project(2023JJXM024).
文摘[Objectives]To explore the effects of motivational interviewing intervention based on the transtheoretical model(TTM)on psychological resilience and self-management in patients undergoing finger reimplantation after amputation.[Methods]The patients with finger replantation due to fractures admitted from October 2024 to June 2025 were divided into either the control group or the observation group according to the random number table method,with 40 cases in each group.The control group received conventional perioperative care,while the observation group underwent motivational interviewing based on TTM framework on the basis of the control group.The psychological resilience and self-management levels of the two patient groups were then compared following their respective care interventions.[Results]The psychological resilience and self-management scores of the patients were significantly higher than those of the control group after the intervention,with the difference being statistically significant(P<0.05).[Conclusions]Motivational interviewing based on the TTM can effectively improve the psychological resilience and self-management in patients undergoing severed finger reimplantation,while effectively reducing the occurrence of vascular crisis.
基金supported by the National Key R&D Program of China (No.2022YFC3004602)the National Natural Science Foundation of China (No.52325404)the Shenzhen Science and Technology Program (No.JCYJ20220818095605012).
文摘Rock discontinuities such as joints widely exist in natural rock masses,and wave attenuation through rock masses is mainly caused by discontinuities.The displacement discontinuity model(DDM)has been widely used in theoretical and numerical analysis of wave propagation across rock discontinuity.However,the circumstance under which the DDM is applicable to predict wave propagation across rock discontinuity remains poorly understood.In this study,theoretical analysis and ultrasonic laboratory tests were carried out to examine the theoretical applicability of the DDM for wave propagation,where specimens with rough joints comprising regular rectangular asperities of different spacings and heights were prepared by 3D printing technology.It is found that the theoretical applicability of the DDM to predict wave propagation across rock discontinuity is determined by three joint parameters,i.e.the dimensionless asperity spacing(L),the dimensionless asperity height(H)and the groove density(D).Through theoretical analysis and laboratory tests,the conditions under which the DDM is applicable are derived as follows:and,.With increase in the groove density,the thresholds of the dimensionless asperity spacing and the dimensionless asperity height show a decreasing trend.In addition,the transmission coefficient in the frequency domain decreases with increasing groove density,dimensionless asperity spacing or dimensionless asperity height.The findings can facilitate our understanding of DDM for predicting wave propagation across rock discontinuity.
文摘Industrial robots are integral to modern manufacturing systems,enabling high precision,high throughput,and flexibility.However,errors in accuracy and repeatability,which arise from a variety of sources such as mechanical wear,calibration issues,and environmental factors,can significantly impact the performance of industrial robots.This paper aims to explore the theoretical modeling of errors in industrial robot systems and propose compensation strategies to enhance their accuracy and repeatability.Key factors contributing to errors,such as kinematic,dynamic,and environmental influences,are discussed in detail.Additionally,the paper explores various compensation techniques,including geometric error compensation,dynamic compensation,and adaptive control approaches.Through the integration of error modeling and compensation methods,industrial robots can achieve improved performance,ensuring higher operational efficiency and product quality.The paper concludes by highlighting the challenges and future research directions for improving the accuracy and repeatability of industrial robots in practical applications.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金supported by the National Natural Science Foundation of China(52471240)the Natural Science Foundation of Zhejiang Province(LZ23B030003)+2 种基金the Fundamental Research Funds for the Central Universities(226-2024-00075)support from the Engineering and Physical Sciences Research Council(EPSRC,UK)RiR grant-RIR18221018-1EU COST CA23155。
文摘The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
基金National Key Research and Development Program of China(Project No.:2020YFC2004900)。
文摘Objective:To investigate the impact of health education nursing based on the Transtheoretical Model of Behavior Change on self-efficacy in osteoporosis patients with low bone mass.Methods:A total of 91 osteoporosis patients with low bone mass admitted to our hospital from June 2000 to the end of June 2023 were selected and randomly divided into an observation group and a control group using the envelope method,with 46 and 45 cases in each group,respectively.The control group received routine nursing care,while the observation group received health education nursing based on the Transtheoretical Model of Behavior Change.Bone mineral density(lumbar spine L1-L4,femoral neck),disease awareness(Osteoporosis Knowledge Test Questionnaire,OKT-Q),and self-efficacy(Adult Health Self-Management Skills Rating Scale,AHSMSRS)were compared between the two groups.Results:After the intervention,bone mineral density levels,disease awareness levels,and self-efficacy levels significantly increased in both groups,with the observation group showing greater improvements in all indicators compared to the control group(p<0.05).Conclusion:Interventions based on the Transtheoretical Model of Behavior Change effectively enhance patient self-efficacy and bone health by precisely matching behavioral stages,strengthening social support,and regulating neurobehavioral factors.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
基金funded by the Office of the Vice-President for Research and Development of Cebu Technological University.
文摘This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.
基金financially supported by the National Key Research and Development Program of China (No. 2023YFB3812601)the National Natural Science Foundation of China (No. 51925401)the Young Elite Scientists Sponsorship Program by CAST, China (No. 2022QNRC001)。
文摘Machine learning-assisted methods for rapid and accurate prediction of temperature field,mushy zone,and grain size were proposed for the heating−cooling combined mold(HCCM)horizontal continuous casting of C70250 alloy plates.First,finite element simulations of casting processes were carried out with various parameters to build a dataset.Subsequently,different machine learning algorithms were employed to achieve high precision in predicting temperature fields,mushy zone locations,mushy zone inclination angle,and billet grain size.Finally,the process parameters were quickly optimized using a strategy consisting of random generation,prediction,and screening,allowing the mushy zone to be controlled to the desired target.The optimized parameters are 1234℃for heating mold temperature,47 mm/min for casting speed,and 10 L/min for cooling water flow rate.The optimized mushy zone is located in the middle of the second heat insulation section and has an inclination angle of roughly 7°.
基金supported by the National Natural Science Foundation of China(Nos.42107420,U23A20157,and U1910207)Shanxi Province Science Foundation for Young Scholars(No.20210302124363).
文摘Vegetation plays an important role in the environmental transport behavior of organic pollutants,however,the different roles of crops and natural vegetation have been ignored in most previous studies.In this study,we developed the BETR-Urban-Rural-Veg model to quantitatively evaluate the influences of both natural vegetation and crops on the multimedia transport processes of Phenanthrene(PHE)and Benzo(a)pyrene(BaP)in mainland of China.The geographic distribution of polycyclic aromatic hydrocarbon(PAH)emissions and concentrations were consistent,displaying higher levels in northern China while lower levels in southern China.Under seasonal simulations,for both natural vegetation and crops,PAH concentrations in winter and spring were 1.5 to 27-fold higher than in summer and autumn,especially for PHE.Owing to the higher leaf area index(LAI)of natural vegetation and harvesting of crops,the filter and sequestration effect of natural vegetation was stronger than crops,while the seasonal changes of PAH concentrations in crops were more significant than natural vegetation.Temperature,precipitation rates and LAI might have important influences on seasonal concentrations and overall persistence of PAHs.PHE was more sensitive to the impacts of seasonal environmental parameters.Under different landscape scenarios,average annual PAH concentrations in natural vegetation were always a little higher than those in crops,and the overall persistence of BaP was greatly affected increasing by 15.15%-16.47%.This improved model provides a useful tool for environmental management.The results of this study are expected to support land use plans and decision-making in China's mainland.
基金supported by the National Key Research and Development Program of China[grant number 2022YFE0106800]an Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 311024001]+3 种基金a project supported by the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number SML2023SP209]a Research Council of Norway funded project(MAPARC)[grant number 328943]a Nansen Center´s basic institutional funding[grant number 342624]the high-performance computing support from the School of Atmospheric Science at Sun Yat-sen University。
文摘Current shipping,tourism,and resource development requirements call for more accurate predictions of the Arctic sea-ice concentration(SIC).However,due to the complex physical processes involved,predicting the spatiotemporal distribution of Arctic SIC is more challenging than predicting its total extent.In this study,spatiotemporal prediction models for monthly Arctic SIC at 1-to 3-month leads are developed based on U-Net-an effective convolutional deep-learning approach.Based on explicit Arctic sea-ice-atmosphere interactions,11 variables associated with Arctic sea-ice variations are selected as predictors,including observed Arctic SIC,atmospheric,oceanic,and heat flux variables at 1-to 3-month leads.The prediction skills for the monthly Arctic SIC of the test set(from January 2018 to December 2022)are evaluated by examining the mean absolute error(MAE)and binary accuracy(BA).Results showed that the U-Net model had lower MAE and higher BA for Arctic SIC compared to two dynamic climate prediction systems(CFSv2 and NorCPM).By analyzing the relative importance of each predictor,the prediction accuracy relies more on the SIC at the 1-month lead,but on the surface net solar radiation flux at 2-to 3-month leads.However,dynamic models show limited prediction skills for surface net solar radiation flux and other physical processes,especially in autumn.Therefore,the U-Net model can be used to capture the connections among these key physical processes associated with Arctic sea ice and thus offers a significant advantage in predicting Arctic SIC.
