A specialized computer named as the Electronic Probe Computer(EPC)has been developed to address large-scale NP-complete problems.The EPC employs a hybrid serial/parallel computational model,structured around four main...A specialized computer named as the Electronic Probe Computer(EPC)has been developed to address large-scale NP-complete problems.The EPC employs a hybrid serial/parallel computational model,structured around four main subsystems:a converting system,an input/output system,and an operating system.The converting system is a software component that transforms the target problem into the graph coloring problem,while the operating system is designed to solve these graph coloring challenges.Comprised of 60 probe computing cards,this system is referred to as EPC60.In tackling large-scale graph coloring problems with EPC60,1003-colorable graphs were randomly selected,each consisting of 2,000 vertices.The state-of-the-art mathematical optimization solver achieved a success rate of only 6%,while EPC60 excelled with a remarkable 100%success rate.Additionally,EPC60 successfully solved two 3-colorable graphs with 1,500 and 2,000 vertices,which had eluded Gurobi’s attempts for 15 days on a standard workstation.Given the mutual reducibility of NP-complete problems in polynomial time theoretically,the EPC stands out as a universal solver for NP-complete problem.The EPC can be applied to various problems that can be abstracted as combinatorial optimization issues,making it relevant across multiple domains,including supply chain management,financial services,telecommunications,energy systems,manufacturing,and beyond.展开更多
This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theo...This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results.展开更多
This study examines the mediating role of positive psychological capital and the moderating role of ethnicity in the relationship between mindfulness and internalizing/externalizing problems among adolescents.The stud...This study examines the mediating role of positive psychological capital and the moderating role of ethnicity in the relationship between mindfulness and internalizing/externalizing problems among adolescents.The study sample comprized Chinese adolescents(N=637 ethnic minority;females=40.97%,meam age=12.68,SD=0.49 years;N=636 Han;females=49.06%,mean age=12.71,SD=0.47 years).The participants completed the Child and Adolescent Mindfulness Measure,the Positive Psycap Questionnaire,and the Youth Self-Report.Results from the moderated mediation analysis showed mindfulness was negatively associated with both internalizing and externalizing problems.Ethnicity moderated the relationship between mindfulness and internalizing problems to be stronger for Han adolescents compared to ethnic minority adolescents.Psychological capital mediated the relationship between mindfulness and internalizing problems in both groups,with a negative direction.Findings support the Conservation of Resources theory and highlight mindfulness as a personal resource fostering adolescent well-being in multicultural contexts.展开更多
This paper is concerned with the following nonlinear Steklov problemΔu=0 in D,∂vu=λf(u)on∂D,where D is the unit disk in the plane,∂v denotes the unit outward normal derivative.For each k∈N,under some natural condit...This paper is concerned with the following nonlinear Steklov problemΔu=0 in D,∂vu=λf(u)on∂D,where D is the unit disk in the plane,∂v denotes the unit outward normal derivative.For each k∈N,under some natural conditions on f,using the Crandall-Rabinowitz bifurcation theorem,we obtain a bifurcation curve emanating from(k,0).Furthermore,we also analyze the local structure of bifurcation curves and stability of solutions on them.Specifically,our results indicate the bifurcation is critical for each k and is subcritical(supercritical)if f'''(0)>0(f'''(0)<0).展开更多
Background:The growing parenting stress among Chinese mothers in recent years raises concerns about its impact on adolescent internalizing problems.The purpose of this study was to examine the curvilinear relationship...Background:The growing parenting stress among Chinese mothers in recent years raises concerns about its impact on adolescent internalizing problems.The purpose of this study was to examine the curvilinear relationship between maternal parenting stress and internalizing problems in adolescents,and further explore the moderating effects of family socioeconomic status(SES)and adolescent gender.Methods:Data were collected from 405 mothers and adolescents(203 boys,Meanage=12.23)across five cities(Beijing,Hebei,Shanxi,Shenzhen,and Shandong)in China,who completed self-report measures of maternal parenting stress and internalizing problems.Descriptive statistics and multiple regression analyses were conducted using SPSS 27.0.Results:Multiple regression analyses indicated that the association between maternal parenting stress2 and adolescents’internalizing problems was moderated by the interaction between gender and SES(b=−0.03,p<0.01).Specifically,a significant U-shaped relationship was observed among high-SES boys(b=0.12,t=3.89,p<0.001),with internalizing problems peaking at both low and high levels of maternal parenting stress,whereas the moderating effect of SES was not significant among girls.Conclusion:The study highlights that moderate maternal parenting stress is associated with lower internalizing problems among adolescents,particularly among high-SES boys,indicating that interventions should consider the optimal balance of parental stress and account for family socioeconomic and adolescent gender differences.展开更多
Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emoti...Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emotional intelligence,and perceived social support.This study examined how gender,relational trauma,attachment dimensions,resilience,and emotional intelligence contribute to the presence of somatic and eating difficulties in this population.Methods:The sample included 46 adolescents(63%female;ages 12–17,Mean=14.85,Standard Deviation(SD)=1.49)residing in child protection institutions in Uruguay.Participants completed self-report measures assessing childhood relational trauma(CaMir),attachment dimensions(anxiety and avoidance),resilience,emotional intelligence(adaptability and stress management),social support(MOS),and psychosocial adjustment(SENA subscales of somatization and eating problems).Using a fuzzy-set Qualitative Comparative Analysis(fsQCA)approach,distinct configurations of risk and protective factors associated with elevated levels of somatization and eating problems were identified.Results:Relational trauma and attachment anxiety showed moderate associations with both somatization and eating problems(r=0.52–0.57,p<0.01),whereas stress management was negatively associated with both outcomes(r=−0.37 to−0.47,p<0.05).FsQCA revealed multiple configurations of risk and protective factors explaining 81–90%of cases,with solution consistencies ranging from 0.83 to 0.87.Results suggest that relational trauma and attachment anxiety are key risk conditions,whereas resilience,emotional regulation,and perceived social support function as protective factors.Conclusions:Findings highlight the importance of considering multifactorial patterns of vulnerability and protection rather than single predictors and underscore the need for tailored interventions that strengthen resilience and emotional skills while addressing the impact of early relational trauma.展开更多
In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zer...In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zero-points distribution of the solutions and separate the single valued analytic branch of the solutions with square roots,then convert the problem to a Riemann boundary value problem in variable exponent Lebesgue spaces and discuss the singularity of solutions at individual zeros belonging to curve.We consider two types of cases those where the coefficient is Hölder and those where it is piecewise Hölder.Then we solve the Hilbert boundary value problem with square roots in variable exponent Lebesgue spaces.By discussing the distribution of the odd-order zero-points for solutions and the method of symmetric extension,we convert the Hilbert problem to a Riemann boundary value problem.The equivalence of the transformation is discussed.Finally,we get the solvable conditions and the direct expressions of the solutions in variable exponent Lebesgue spaces.展开更多
Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN mode...Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN models are limited in their ability to actively suppress noise,which constrains their robustness and precision in solving time-varying problems.This paper introduces a novel active noise rejection ZNN(ANR-ZNN)design that enhances noise suppression by integrating computational error dynamics and harmonic behaviour.Through rigorous theoretical analysis,we demonstrate that the proposed ANR-ZNN maintains robust convergence in computational error performance under environmental noise.As a case study,the ANR-ZNN model is specifically applied to time-varying matrix inversion.Comprehensive computer simulations and robotic experiments further validate the ANR-ZNN's effectiveness,emphasising the proposed design's superiority and potential for solving time-varying problems.展开更多
Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when ta...Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.展开更多
Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicate...Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.展开更多
THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-...THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4].展开更多
Nondeterministic-polynomial-time(NP)-complete problems are widely involved in various reallife scenarios but are still intractable in being solved efficiently on conventional computers.It is of great practical signifi...Nondeterministic-polynomial-time(NP)-complete problems are widely involved in various reallife scenarios but are still intractable in being solved efficiently on conventional computers.It is of great practical significance to construct versatile computing architectures that solve NP-complete problems with computational advantage.Here,we present a reconfigurable integrated photonic processor to efficiently solve a benchmark NP-complete problem,the subset sum problem.We show that in the case of successive primes,the photonic processor has genuinely surpassed electronic processors launched recently by taking advantage of the high propagation speed and vast parallelism of photons and state-of-the-art integrated photonic technology.Moreover,we are able to program the photonic processor to tackle different problem instances,relying on the tunable integrated modules,variable split junctions,which can be used to build a fully reconfigurable architecture potentially allowing 2^(N) configurations at most.Our experiments confirm the potential of the photonic processor as a versatile and efficient computing platform,suggesting a possible practical route to solving computationally hard problems at a large scale.展开更多
We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for ...We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for polynomial transformations, is more robust, more practical, and faster to apply to real problems than the theory of polynomial transformations. In this paper we propose a methodology for transforming instances between NP-complete problems, which differs from Garey and Johnson's. Unlike most transformations which are used for proving that a problem is NP-complete based on the NP-completeness of another problem, the proposed approach is intended for extrapolating some known characteristics, phenomena, or behaviors from a problem A to another problem B. This extrapolation could be useful for predicting the performance of an algorithm for solving B based on its known performance for problem A, or for taking an algorithm that solves A and adapting it to solve B.展开更多
In this paper we hybridize ant colony optimiza- tion （ACt） and river formation dynamics （RFD）, two related swarm intelligence methods. In ACt, ants form paths （prob- lem solutions） by following each other＇s phe...In this paper we hybridize ant colony optimiza- tion （ACt） and river formation dynamics （RFD）, two related swarm intelligence methods. In ACt, ants form paths （prob- lem solutions） by following each other＇s pheromone trails and reinforcing trails at best paths until eventually a single path is followed. On the other hand, RFD is based on copy- ing how drops form rivers by eroding the ground and de- positing sediments. In a rough sense, RFD can be seen as a gradient-oriented version of ACt. Several previous experi- ments have shown that the gradient orientation of RFD makes this method solve problems in a different way as ACt. In particular, RFD typically performs deeper searches, which in turn makes it find worse solutions than ACt in the first exe- cution steps in general, though RFD solutions surpass ACt solutions after some more time passes. In this paper we try to get the best features of both worlds by hybridizing RFD and ACt. We use a kind of ant-drop hybrid and consider both pheromone trails and altitudes in the environment. We apply the hybrid method, as well as ACt and RFD, to solve two NP-hard problems where ACt and RFD fit in a different manner： the traveling salesman problem （TSP） and the prob- lem of the minimum distances tree in a variable-cost graph （MDV）. We compare the results of each method and we an- alyze the advantages of using the hybrid approach in each case.展开更多
The modern information society is enabled by photonic fiber networks characterized by huge coverage and great complexity and ranging in size from transcontinental submarine telecommunication cables to fiber to the hom...The modern information society is enabled by photonic fiber networks characterized by huge coverage and great complexity and ranging in size from transcontinental submarine telecommunication cables to fiber to the home and local segments.This world-wide network has yet to match the complexity of the human brain,which contains a hundred billion neurons,each with thousands of synaptic connections on average.However,it already exceeds the complexity of brains from primitive organisms,i.e.,the honey bee,which has a brain containing approximately one million neurons.In this study,we present a discussion of the computing potential of optical networks as information carriers.Using a simple fiber network,we provide a proof-of-principle demonstration that this network can be treated as an optical oracle for the Hamiltonian path problem,the famous mathematical complexity problem of finding whether a set of towns can be travelled via a path in which each town is visited only once.Pronouncement of a Hamiltonian path is achieved by monitoring the delay of an optical pulse that interrogates the network,and this delay will be equal to the sum of the travel times needed to visit all of the nodes(towns).We argue that the optical oracle could solve this NP-complete problem hundreds of times faster than brute-force computing.Additionally,we discuss secure communication applications for the optical oracle and propose possible implementation in silicon photonics and plasmonic networks.展开更多
Background:Parenting exerts a profound influence on children’s mental health and behavioral development.Despite the high prevalence of children’s emotional and behavioral problems(CEBP)in China,evidence-based parent...Background:Parenting exerts a profound influence on children’s mental health and behavioral development.Despite the high prevalence of children’s emotional and behavioral problems(CEBP)in China,evidence-based parenting interventions remain scarcely investigated as preventive public health strategies.This pilot study evaluated a school-based intervention for preventing CEBP.Methods:We employed a quasi-experimental design with propensity score matching(PSM)to select 28 families(intervention:n=13;control:n=15)from two matched urban primary schools.Quantitative data from seven validated scales were analyzed using t-tests and ANCOVA.Qualitative insights were derived from 10 semi-structured interviews via thematic analysis.Results:Compared to the control group,the intervention group demonstrated significantly greater improvements in CEBP(p=0.020,Cohen’s d=0.92),parental adjustment(p=0.031,Cohen’s d=0.80),parenting confidence(p=0.003,Cohen’s d=1.04),and parentchild relationships(p=0.001,Cohen’s d=1.46).Non-significant effects were observed for parenting style,parental relationship,and parenting conflict(p>0.05).Qualitative analysis corroborated these findings and further identified contributing factors for non-significant outcomes,including challengeswithmeasurement adaptability and inconsistent co-parenting practices.Conclusions:This pilot study suggests that an authoritative parenting style may be effective and culturally adaptable in China.Positive parenting interventions appear to mitigate CEBP by reducing risk factors and enhancing protective factors.However,improving parental relationships and parenting conflict may require targeted strategies.Given the pilot nature of this PSM-matched study(n=28),the findings should be interpreted as exploratory and used primarily for intervention refinement.展开更多
Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the fo...Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the following issues:Models relying on such structures exhibit fixed-order reasoning(e.g.,left-to-right),limiting flexibility and increasing error susceptibility;prior models rely on autoregressive reasoning in a single pass,accumulating minor errors(e.g.,incorrect math symbols)during generation,resulting in reduced accuracy.To address the above issues,we emulate the human“check and modify”process in reasoning and propose a unified M-tree self-correction solver(UTSCSolver)by iterative inference with self-correction mechanism.First,we use an iterative,non-autoregressive process for generating mathematical expressions,free from fixed generation orders to handle complex and diverse problems.Additionally,we design a self-correction mechanism based on alternating execution between a generator and a discriminator.This module iteratively detects and rectifies errors in generated expressions,leveraging previous iteration information for subsequent generation guidance.Experimental results show that our UTSC-Solver outperforms traditional models in accuracy on two popular datasets,while it improves the interpretability of mathematical reasoning.展开更多
This case study explores the efficacy of school-based intervention to address psychosocial challenges faced by an 11-year-old adolescent. The case study aimed to decrease the agression and acting out behavior as resul...This case study explores the efficacy of school-based intervention to address psychosocial challenges faced by an 11-year-old adolescent. The case study aimed to decrease the agression and acting out behavior as result of being victimized at school by the peers. The aim was to assess and manage the child’s aggressive behavior and academic underperformance which played a significant role in the child’s low self-esteem and emotional regulation. A comprehensive assessment was conducted to rule out the difficulties and a multi-faceted intervention strategy was utilized including anger management and structured activity scheduling that helped that child to improve his academic performance as well as to learn to manage his emotional expression. Throughout 16 sessions, the intervention targeted key behavioural indicators such as emotional expression, and aggression;post-assessment results demonstrated a 22% improvement in the child’s behavioral and academic challenges. The findings suggest that a multi-faceted therapeutic approach can be effective in addressing complex issues of aggression and academic underperformance in children, highlighting the importance of integrated psychological and educational interventions.展开更多
BACKGROUND Emotional reactions,such as anxiety,irritability,and aggressive behavior,have attracted clinical attention as behavioral and emotional problems in preschool-age children.AIM To investigate the current statu...BACKGROUND Emotional reactions,such as anxiety,irritability,and aggressive behavior,have attracted clinical attention as behavioral and emotional problems in preschool-age children.AIM To investigate the current status of family rearing,parental stress,and behavioral and emotional problems of preschool children and to analyze the mediating effect of the current status of family rearing on parental stress and behavioral/emo-tional problems.METHODS We use convenience sampling to select 258 preschool children in the physical examination center of our hospital from October 2021 to September 2023.The children and their parents were evaluated using a questionnaire survey.Pearson's correlation was used to analyze the correlation between child behavioral and emotional problems and parental stress and family rearing,and the structural equation model was constructed to test the mediating effect.RESULTS The score for behavioral/emotional problems of 258 preschool children was(27.54±3.63),the score for parental stress was(87.64±11.34),and the score for parental family rearing was(31.54±5.24).There was a positive correlation between the behavioral and emotional problems of the children and the“hostile/mandatory”parenting style;meanwhile,showed a negative correlation with the“support/participation”parenting style(all P<0.05).The intermediary effect value between the family upbringing of parents in parental stress and children's behavior problems was 29.89%.CONCLUSION Parental family upbringing has a mediating effect between parental stress and behavioral and emotional problems of children.Despite paying attention to the behavioral and emotional problems of preschool-age children,clinical medical staff should provide correct and reasonable parenting advice to their parents to promote the mental health of preschool-age children.展开更多
Constraint satisfaction problems(CSPs)are a class of problems that are ubiquitous in science and engineering.They feature a collection of constraints specified over subsets of variables.A CSP can be solved either dire...Constraint satisfaction problems(CSPs)are a class of problems that are ubiquitous in science and engineering.They feature a collection of constraints specified over subsets of variables.A CSP can be solved either directly or by reducing it to other problems.This paper introduces the Julia ecosystem for solving and analyzing CSPs with a focus on the programming practices.We introduce some important CSPs and show how these problems are reduced to each other.We also show how to transform CSPs into tensor networks,how to optimize the tensor network contraction orders,and how to extract the solution space properties by contracting the tensor networks with generic element types.Examples are given,which include computing the entropy constant,analyzing the overlap gap property,and the reduction between CSPs.展开更多
基金supported by the National Major Research Instrument Development Project(62427811)the Key Program of the National Natural Science Foundation of China(62332006)the General Program of the National Natural Science Foundation of China(62172014).
文摘A specialized computer named as the Electronic Probe Computer(EPC)has been developed to address large-scale NP-complete problems.The EPC employs a hybrid serial/parallel computational model,structured around four main subsystems:a converting system,an input/output system,and an operating system.The converting system is a software component that transforms the target problem into the graph coloring problem,while the operating system is designed to solve these graph coloring challenges.Comprised of 60 probe computing cards,this system is referred to as EPC60.In tackling large-scale graph coloring problems with EPC60,1003-colorable graphs were randomly selected,each consisting of 2,000 vertices.The state-of-the-art mathematical optimization solver achieved a success rate of only 6%,while EPC60 excelled with a remarkable 100%success rate.Additionally,EPC60 successfully solved two 3-colorable graphs with 1,500 and 2,000 vertices,which had eluded Gurobi’s attempts for 15 days on a standard workstation.Given the mutual reducibility of NP-complete problems in polynomial time theoretically,the EPC stands out as a universal solver for NP-complete problem.The EPC can be applied to various problems that can be abstracted as combinatorial optimization issues,making it relevant across multiple domains,including supply chain management,financial services,telecommunications,energy systems,manufacturing,and beyond.
基金Supported by the National Natural Science Foundation of China(11361047)Fundamental Research Program of Shanxi Province(20210302124529)。
文摘This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results.
基金supported by the Guizhou Provincial Science and Technology Projects[Basic Science of Guizhou-[2024]Youth 309,Guizhou Platform Talents[2021]1350-046]Zunyi Science and Technology Cooperation[HZ(2024)311]+3 种基金Funding of the Chinese Academy of Social Sciences(2024SYZH005)Peking University Longitudinal Scientific Research Technical Service Project(G-252)Guizhou Provincial Graduate Student Research Fund Project(2024YJSKYJJ339)Zunyi Medical University Graduate Research Fund Project(ZYK206).
文摘This study examines the mediating role of positive psychological capital and the moderating role of ethnicity in the relationship between mindfulness and internalizing/externalizing problems among adolescents.The study sample comprized Chinese adolescents(N=637 ethnic minority;females=40.97%,meam age=12.68,SD=0.49 years;N=636 Han;females=49.06%,mean age=12.71,SD=0.47 years).The participants completed the Child and Adolescent Mindfulness Measure,the Positive Psycap Questionnaire,and the Youth Self-Report.Results from the moderated mediation analysis showed mindfulness was negatively associated with both internalizing and externalizing problems.Ethnicity moderated the relationship between mindfulness and internalizing problems to be stronger for Han adolescents compared to ethnic minority adolescents.Psychological capital mediated the relationship between mindfulness and internalizing problems in both groups,with a negative direction.Findings support the Conservation of Resources theory and highlight mindfulness as a personal resource fostering adolescent well-being in multicultural contexts.
基金Supported by the National Natural Science Foundation of China(Grant No.12371110).
文摘This paper is concerned with the following nonlinear Steklov problemΔu=0 in D,∂vu=λf(u)on∂D,where D is the unit disk in the plane,∂v denotes the unit outward normal derivative.For each k∈N,under some natural conditions on f,using the Crandall-Rabinowitz bifurcation theorem,we obtain a bifurcation curve emanating from(k,0).Furthermore,we also analyze the local structure of bifurcation curves and stability of solutions on them.Specifically,our results indicate the bifurcation is critical for each k and is subcritical(supercritical)if f'''(0)>0(f'''(0)<0).
基金supported by the National Natural Science Foundation of China(32171069).
文摘Background:The growing parenting stress among Chinese mothers in recent years raises concerns about its impact on adolescent internalizing problems.The purpose of this study was to examine the curvilinear relationship between maternal parenting stress and internalizing problems in adolescents,and further explore the moderating effects of family socioeconomic status(SES)and adolescent gender.Methods:Data were collected from 405 mothers and adolescents(203 boys,Meanage=12.23)across five cities(Beijing,Hebei,Shanxi,Shenzhen,and Shandong)in China,who completed self-report measures of maternal parenting stress and internalizing problems.Descriptive statistics and multiple regression analyses were conducted using SPSS 27.0.Results:Multiple regression analyses indicated that the association between maternal parenting stress2 and adolescents’internalizing problems was moderated by the interaction between gender and SES(b=−0.03,p<0.01).Specifically,a significant U-shaped relationship was observed among high-SES boys(b=0.12,t=3.89,p<0.001),with internalizing problems peaking at both low and high levels of maternal parenting stress,whereas the moderating effect of SES was not significant among girls.Conclusion:The study highlights that moderate maternal parenting stress is associated with lower internalizing problems among adolescents,particularly among high-SES boys,indicating that interventions should consider the optimal balance of parental stress and account for family socioeconomic and adolescent gender differences.
文摘Backgrounds:Somatization and eating-related problems in adolescents living in residential care may be shaped by the interplay of risk and protective factors,including gender,relational trauma,attachment patterns,emotional intelligence,and perceived social support.This study examined how gender,relational trauma,attachment dimensions,resilience,and emotional intelligence contribute to the presence of somatic and eating difficulties in this population.Methods:The sample included 46 adolescents(63%female;ages 12–17,Mean=14.85,Standard Deviation(SD)=1.49)residing in child protection institutions in Uruguay.Participants completed self-report measures assessing childhood relational trauma(CaMir),attachment dimensions(anxiety and avoidance),resilience,emotional intelligence(adaptability and stress management),social support(MOS),and psychosocial adjustment(SENA subscales of somatization and eating problems).Using a fuzzy-set Qualitative Comparative Analysis(fsQCA)approach,distinct configurations of risk and protective factors associated with elevated levels of somatization and eating problems were identified.Results:Relational trauma and attachment anxiety showed moderate associations with both somatization and eating problems(r=0.52–0.57,p<0.01),whereas stress management was negatively associated with both outcomes(r=−0.37 to−0.47,p<0.05).FsQCA revealed multiple configurations of risk and protective factors explaining 81–90%of cases,with solution consistencies ranging from 0.83 to 0.87.Results suggest that relational trauma and attachment anxiety are key risk conditions,whereas resilience,emotional regulation,and perceived social support function as protective factors.Conclusions:Findings highlight the importance of considering multifactorial patterns of vulnerability and protection rather than single predictors and underscore the need for tailored interventions that strengthen resilience and emotional skills while addressing the impact of early relational trauma.
基金supported by the National Natural Science Foundation of China(11601525)the Natural Science Foundation of Hunan Province(2024JJ5412),the Changsha Municipal Natural Science Foundation(kq2402193).
文摘In this paper,we study the nonlinear Riemann boundary value problem with square roots that is represented by a Cauchy-type integral with kernel density in variable exponent Lebesgue spaces.We discuss the odd-order zero-points distribution of the solutions and separate the single valued analytic branch of the solutions with square roots,then convert the problem to a Riemann boundary value problem in variable exponent Lebesgue spaces and discuss the singularity of solutions at individual zeros belonging to curve.We consider two types of cases those where the coefficient is Hölder and those where it is piecewise Hölder.Then we solve the Hilbert boundary value problem with square roots in variable exponent Lebesgue spaces.By discussing the distribution of the odd-order zero-points for solutions and the method of symmetric extension,we convert the Hilbert problem to a Riemann boundary value problem.The equivalence of the transformation is discussed.Finally,we get the solvable conditions and the direct expressions of the solutions in variable exponent Lebesgue spaces.
基金supported by the National Science and Technology Major Project(2022ZD0119901)the National Natural Science Foundation of China under Grant(U2141234,62463004 and U24A20260)+1 种基金the Hainan Province Science and Technology Special Fund(ZDYF2024GXJS003)the Scientific Research Fund of Hainan University(KYQD(ZR)23025).
文摘Recently,the zeroing neural network(ZNN)has demonstrated remarkable effectiveness in tackling time-varying problems,delivering robust performance across both noise-free and noisy environments.However,existing ZNN models are limited in their ability to actively suppress noise,which constrains their robustness and precision in solving time-varying problems.This paper introduces a novel active noise rejection ZNN(ANR-ZNN)design that enhances noise suppression by integrating computational error dynamics and harmonic behaviour.Through rigorous theoretical analysis,we demonstrate that the proposed ANR-ZNN maintains robust convergence in computational error performance under environmental noise.As a case study,the ANR-ZNN model is specifically applied to time-varying matrix inversion.Comprehensive computer simulations and robotic experiments further validate the ANR-ZNN's effectiveness,emphasising the proposed design's superiority and potential for solving time-varying problems.
基金funded by National Natural Science Foundation of China(Nos.12402142,11832013 and 11572134)Natural Science Foundation of Hubei Province(No.2024AFB235)+1 种基金Hubei Provincial Department of Education Science and Technology Research Project(No.Q20221714)the Opening Foundation of Hubei Key Laboratory of Digital Textile Equipment(Nos.DTL2023019 and DTL2022012).
文摘Owing to their global search capabilities and gradient-free operation,metaheuristic algorithms are widely applied to a wide range of optimization problems.However,their computational demands become prohibitive when tackling high-dimensional optimization challenges.To effectively address these challenges,this study introduces cooperative metaheuristics integrating dynamic dimension reduction(DR).Building upon particle swarm optimization(PSO)and differential evolution(DE),the proposed cooperative methods C-PSO and C-DE are developed.In the proposed methods,the modified principal components analysis(PCA)is utilized to reduce the dimension of design variables,thereby decreasing computational costs.The dynamic DR strategy implements periodic execution of modified PCA after a fixed number of iterations,resulting in the important dimensions being dynamically identified.Compared with the static one,the dynamic DR strategy can achieve precise identification of important dimensions,thereby enabling accelerated convergence toward optimal solutions.Furthermore,the influence of cumulative contribution rate thresholds on optimization problems with different dimensions is investigated.Metaheuristic algorithms(PSO,DE)and cooperative metaheuristics(C-PSO,C-DE)are examined by 15 benchmark functions and two engineering design problems(speed reducer and composite pressure vessel).Comparative results demonstrate that the cooperative methods achieve significantly superior performance compared to standard methods in both solution accuracy and computational efficiency.Compared to standard metaheuristic algorithms,cooperative metaheuristics achieve a reduction in computational cost of at least 40%.The cooperative metaheuristics can be effectively used to tackle both high-dimensional unconstrained and constrained optimization problems.
基金Project supported by the Basic Science Research Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT(No.RS-2024-00337001)。
文摘Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.
基金partially supported by the National Natural Science Foundation of China(62293500,62293505,62233010,62503240)Natural Science Foundation of Jiangsu Province(BK20250679)。
文摘THE power industrial control system(power ICS)is thecore infrastructure that ensures the safe,stable,and efficient operation of power systems.Its architecture typi-cally adopts a hierarchical and partitioned end-edge-cloud collaborative design.However,the large-scale integration ofdistributed renewable energy resources,coupled with the extensivedeployment of sensing and communication devices,has resulted inthe new-type power system characterized by dynamic complexityand high uncertainty[1]-[4].
基金supported by the National Key R&D Program of China (Grants Nos. 2019YFA0308703, 2019YFA07063022017YFA0303700)+7 种基金the National Natural Science Foundation of China (NSFC)(Grant Nos. 62235012, 12104299,61734005, 11761141014, 11690033, 11904299, and 12304342)the Innovation Program for Quantum Science and Technology(Grant Nos. 2021ZD0301500 and 2021ZD0300700)the Science and Technology Commission of Shanghai Municipality(STCSM)(Grant Nos. 20JC1416300, 2019SHZDZX01,21ZR1432800, and 22QA1404600)the Shanghai Municipal Education Commission (SMEC)(Grant No. 2017-01-07-00-02-E00049)the China Postdoctoral Science Foundation (Grant Nos. 2022T150415, 2021M692094, and 2020M671091)the Startup Fund for Young Faculty at SJTU (SFYF at SJTU)additional support from a Shanghai Talent Programsupport from the Zhiyuan Innovative Research Center of Shanghai Jiao Tong University
文摘Nondeterministic-polynomial-time(NP)-complete problems are widely involved in various reallife scenarios but are still intractable in being solved efficiently on conventional computers.It is of great practical significance to construct versatile computing architectures that solve NP-complete problems with computational advantage.Here,we present a reconfigurable integrated photonic processor to efficiently solve a benchmark NP-complete problem,the subset sum problem.We show that in the case of successive primes,the photonic processor has genuinely surpassed electronic processors launched recently by taking advantage of the high propagation speed and vast parallelism of photons and state-of-the-art integrated photonic technology.Moreover,we are able to program the photonic processor to tackle different problem instances,relying on the tunable integrated modules,variable split junctions,which can be used to build a fully reconfigurable architecture potentially allowing 2^(N) configurations at most.Our experiments confirm the potential of the photonic processor as a versatile and efficient computing platform,suggesting a possible practical route to solving computationally hard problems at a large scale.
文摘We propose the usage of formal languages for expressing instances of NP-complete problems for their application in polynomial transformations. The proposed approach, which consists of using formal language theory for polynomial transformations, is more robust, more practical, and faster to apply to real problems than the theory of polynomial transformations. In this paper we propose a methodology for transforming instances between NP-complete problems, which differs from Garey and Johnson's. Unlike most transformations which are used for proving that a problem is NP-complete based on the NP-completeness of another problem, the proposed approach is intended for extrapolating some known characteristics, phenomena, or behaviors from a problem A to another problem B. This extrapolation could be useful for predicting the performance of an algorithm for solving B based on its known performance for problem A, or for taking an algorithm that solves A and adapting it to solve B.
文摘In this paper we hybridize ant colony optimiza- tion （ACt） and river formation dynamics （RFD）, two related swarm intelligence methods. In ACt, ants form paths （prob- lem solutions） by following each other＇s pheromone trails and reinforcing trails at best paths until eventually a single path is followed. On the other hand, RFD is based on copy- ing how drops form rivers by eroding the ground and de- positing sediments. In a rough sense, RFD can be seen as a gradient-oriented version of ACt. Several previous experi- ments have shown that the gradient orientation of RFD makes this method solve problems in a different way as ACt. In particular, RFD typically performs deeper searches, which in turn makes it find worse solutions than ACt in the first exe- cution steps in general, though RFD solutions surpass ACt solutions after some more time passes. In this paper we try to get the best features of both worlds by hybridizing RFD and ACt. We use a kind of ant-drop hybrid and consider both pheromone trails and altitudes in the environment. We apply the hybrid method, as well as ACt and RFD, to solve two NP-hard problems where ACt and RFD fit in a different manner： the traveling salesman problem （TSP） and the prob- lem of the minimum distances tree in a variable-cost graph （MDV）. We compare the results of each method and we an- alyze the advantages of using the hybrid approach in each case.
基金This work was supported by the Singapore Ministry of Education Academic Research Fund Tier 3(Grant No.MOE2011-T3-1-005)the Singapore Agency for Science,Technology and Research(A*STAR,SERC Project No.1223600007)EPSRC(UK)via the Programme on Nanostructured Photonic Metamaterials.
文摘The modern information society is enabled by photonic fiber networks characterized by huge coverage and great complexity and ranging in size from transcontinental submarine telecommunication cables to fiber to the home and local segments.This world-wide network has yet to match the complexity of the human brain,which contains a hundred billion neurons,each with thousands of synaptic connections on average.However,it already exceeds the complexity of brains from primitive organisms,i.e.,the honey bee,which has a brain containing approximately one million neurons.In this study,we present a discussion of the computing potential of optical networks as information carriers.Using a simple fiber network,we provide a proof-of-principle demonstration that this network can be treated as an optical oracle for the Hamiltonian path problem,the famous mathematical complexity problem of finding whether a set of towns can be travelled via a path in which each town is visited only once.Pronouncement of a Hamiltonian path is achieved by monitoring the delay of an optical pulse that interrogates the network,and this delay will be equal to the sum of the travel times needed to visit all of the nodes(towns).We argue that the optical oracle could solve this NP-complete problem hundreds of times faster than brute-force computing.Additionally,we discuss secure communication applications for the optical oracle and propose possible implementation in silicon photonics and plasmonic networks.
基金supported by the National Social Science Fund of China[18BSH146].
文摘Background:Parenting exerts a profound influence on children’s mental health and behavioral development.Despite the high prevalence of children’s emotional and behavioral problems(CEBP)in China,evidence-based parenting interventions remain scarcely investigated as preventive public health strategies.This pilot study evaluated a school-based intervention for preventing CEBP.Methods:We employed a quasi-experimental design with propensity score matching(PSM)to select 28 families(intervention:n=13;control:n=15)from two matched urban primary schools.Quantitative data from seven validated scales were analyzed using t-tests and ANCOVA.Qualitative insights were derived from 10 semi-structured interviews via thematic analysis.Results:Compared to the control group,the intervention group demonstrated significantly greater improvements in CEBP(p=0.020,Cohen’s d=0.92),parental adjustment(p=0.031,Cohen’s d=0.80),parenting confidence(p=0.003,Cohen’s d=1.04),and parentchild relationships(p=0.001,Cohen’s d=1.46).Non-significant effects were observed for parenting style,parental relationship,and parenting conflict(p>0.05).Qualitative analysis corroborated these findings and further identified contributing factors for non-significant outcomes,including challengeswithmeasurement adaptability and inconsistent co-parenting practices.Conclusions:This pilot study suggests that an authoritative parenting style may be effective and culturally adaptable in China.Positive parenting interventions appear to mitigate CEBP by reducing risk factors and enhancing protective factors.However,improving parental relationships and parenting conflict may require targeted strategies.Given the pilot nature of this PSM-matched study(n=28),the findings should be interpreted as exploratory and used primarily for intervention refinement.
基金supported by the National Natural Science Foundation of China(62106244)the Fundamental Research Funds for the Central Universities(WK2150110021)the University Synergy Innovation Program of Anhui Province(GXXT-2022-042).
文摘Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the following issues:Models relying on such structures exhibit fixed-order reasoning(e.g.,left-to-right),limiting flexibility and increasing error susceptibility;prior models rely on autoregressive reasoning in a single pass,accumulating minor errors(e.g.,incorrect math symbols)during generation,resulting in reduced accuracy.To address the above issues,we emulate the human“check and modify”process in reasoning and propose a unified M-tree self-correction solver(UTSCSolver)by iterative inference with self-correction mechanism.First,we use an iterative,non-autoregressive process for generating mathematical expressions,free from fixed generation orders to handle complex and diverse problems.Additionally,we design a self-correction mechanism based on alternating execution between a generator and a discriminator.This module iteratively detects and rectifies errors in generated expressions,leveraging previous iteration information for subsequent generation guidance.Experimental results show that our UTSC-Solver outperforms traditional models in accuracy on two popular datasets,while it improves the interpretability of mathematical reasoning.
文摘This case study explores the efficacy of school-based intervention to address psychosocial challenges faced by an 11-year-old adolescent. The case study aimed to decrease the agression and acting out behavior as result of being victimized at school by the peers. The aim was to assess and manage the child’s aggressive behavior and academic underperformance which played a significant role in the child’s low self-esteem and emotional regulation. A comprehensive assessment was conducted to rule out the difficulties and a multi-faceted intervention strategy was utilized including anger management and structured activity scheduling that helped that child to improve his academic performance as well as to learn to manage his emotional expression. Throughout 16 sessions, the intervention targeted key behavioural indicators such as emotional expression, and aggression;post-assessment results demonstrated a 22% improvement in the child’s behavioral and academic challenges. The findings suggest that a multi-faceted therapeutic approach can be effective in addressing complex issues of aggression and academic underperformance in children, highlighting the importance of integrated psychological and educational interventions.
基金Supported by the Shijiazhuang Science and Technology Research and Development Program,No.221460383.
文摘BACKGROUND Emotional reactions,such as anxiety,irritability,and aggressive behavior,have attracted clinical attention as behavioral and emotional problems in preschool-age children.AIM To investigate the current status of family rearing,parental stress,and behavioral and emotional problems of preschool children and to analyze the mediating effect of the current status of family rearing on parental stress and behavioral/emo-tional problems.METHODS We use convenience sampling to select 258 preschool children in the physical examination center of our hospital from October 2021 to September 2023.The children and their parents were evaluated using a questionnaire survey.Pearson's correlation was used to analyze the correlation between child behavioral and emotional problems and parental stress and family rearing,and the structural equation model was constructed to test the mediating effect.RESULTS The score for behavioral/emotional problems of 258 preschool children was(27.54±3.63),the score for parental stress was(87.64±11.34),and the score for parental family rearing was(31.54±5.24).There was a positive correlation between the behavioral and emotional problems of the children and the“hostile/mandatory”parenting style;meanwhile,showed a negative correlation with the“support/participation”parenting style(all P<0.05).The intermediary effect value between the family upbringing of parents in parental stress and children's behavior problems was 29.89%.CONCLUSION Parental family upbringing has a mediating effect between parental stress and behavioral and emotional problems of children.Despite paying attention to the behavioral and emotional problems of preschool-age children,clinical medical staff should provide correct and reasonable parenting advice to their parents to promote the mental health of preschool-age children.
基金funded by the National Key R&D Program of China(Grant No.2024YFE0102500)the National Natural Science Foundation of China(Grant No.12404568)+1 种基金the Guangzhou Municipal Science and Technology Project(Grant No.2023A03J00904)the Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area,China and the Undergraduate Research Project from HKUST(Guangzhou).
文摘Constraint satisfaction problems(CSPs)are a class of problems that are ubiquitous in science and engineering.They feature a collection of constraints specified over subsets of variables.A CSP can be solved either directly or by reducing it to other problems.This paper introduces the Julia ecosystem for solving and analyzing CSPs with a focus on the programming practices.We introduce some important CSPs and show how these problems are reduced to each other.We also show how to transform CSPs into tensor networks,how to optimize the tensor network contraction orders,and how to extract the solution space properties by contracting the tensor networks with generic element types.Examples are given,which include computing the entropy constant,analyzing the overlap gap property,and the reduction between CSPs.
