With the implementation of General Senior High School Mathematics Curriculum Standards(2017 Edition,Revised in 2020),probability and statistics,as important carriers of the core mathematical competencies“mathematical...With the implementation of General Senior High School Mathematics Curriculum Standards(2017 Edition,Revised in 2020),probability and statistics,as important carriers of the core mathematical competencies“mathematical modeling”and“data analysis,”have increasingly highlighted their educational value.By summarizing the historical evolution of probability and statistics thinking and combining with teaching practice cases,this study explores its unique role in cultivating students’core mathematical competencies.The research proposes a project-based teaching strategy relying on real scenarios and empowered by technology.Through cases,it demonstrates how to use modern educational technology to realize the whole-process exploration of data collection,model construction,and conclusion verification,so as to promote the transformation of middle school probability and statistics teaching from knowledge imparting to competency development,and provide a practical reference for curriculum reform.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
This study focuses on the "Yuyue Brewing" brand and employs grounded theory in conjunction with NVivo 11 software analysis to identify the key factors and dimensions influencing the cultivation of customer m...This study focuses on the "Yuyue Brewing" brand and employs grounded theory in conjunction with NVivo 11 software analysis to identify the key factors and dimensions influencing the cultivation of customer mindset, thereby constructing a theoretical model. The findings suggest that the three fundamental components of an entrepreneur s personal mindset—energy, ability, and wisdom—collectively constitute the foundation of entrepreneurial leadership. Establishing a clear brand positioning and developing its core values accordingly are essential aspects of the brand mindset. Furthermore, articulating the customer mindset involves comprehending the emotions and perspectives of target customers within specific contexts. The success of a brand depends not only on the product itself but also on the synergistic interaction among the entrepreneur s personal mindset, the brand mindset, and the customer mindset.展开更多
The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and e...The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.展开更多
In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocal...In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.展开更多
Loday introduced di-associative algebras and tri-associative algebras motivated by periodicity phenomena in algebraic K-theory.The purpose of this paper is to study the splittings of operations on di-associative algeb...Loday introduced di-associative algebras and tri-associative algebras motivated by periodicity phenomena in algebraic K-theory.The purpose of this paper is to study the splittings of operations on di-associative algebras and tri-associative algebras.We introduce the notion of a quad-dendriform algebra,which is a splitting of a di-associative algebra.We show that a relative averaging operator on dendriform algebras gives rise to a quad-dendriform algebra.Furthermore,we introduce the notion of six-dendriform algebras,which are splittings of the tri-associative algebras,and demonstrate that homomorphic relative averaging operators induce six-dendriform algebras.展开更多
An atmospheric general circulation model(AGCM)is used to analyze the different impact on the Barents Sea(BS)and Greenland Sea(GS)for a perturbation of sea-to-air DMS flux.We compare contemporary anthropogenic S and co...An atmospheric general circulation model(AGCM)is used to analyze the different impact on the Barents Sea(BS)and Greenland Sea(GS)for a perturbation of sea-to-air DMS flux.We compare contemporary anthropogenic S and contemporary DMS sea-to-air flux(as baseline,B00)sulfur emissions,with contemporary anthropogenic S and a perturbed DMS flux(as modified,B01)sulfur emissions.Results show that the global mean surface DMS and DMS vertically integrated concentration all peaked in June and increases more than 63%in BS and increases about 58%in GS.The concentrations of atmospheric sulfur dioxide vertical integral(SO_(2))and sulfate vertical integral(SO_(4))only increase less than 12%in both regions.Sulfur emission(SEM)peaked in June and increased about 67%and 41%in GS and BS,respectively.Aerosol optical depth(AOD)increases less than 4%in GS and in BS.Surface temperature(TSC)peaked in July and reduces 0.25 K and 0.8 K in GS and BS,respectively.Satellite data from 2003 to 2023show that chlorophyll(CHL)concentration in BS exceeds that of GS by 51%.The AOD in GS is only 0.6%higher than in BS.The recent increased rate of DMS surface concentration in BS(from 6%during 1981–2002 to 18.8%in 2003–2023)is mainly caused by elevated CHL concentrations in BS.Finally,the perturbation on DMS flux leads to increase rate of DMS and related sulfur emissions especially in the BS,this tendency will have an offsetting effect on regional warming.展开更多
Efficient thermal management in porous media is essential for advanced engineering applications,including solar energy systems,electronic cooling,and aerospace thermal control.This study presents a comprehensive analy...Efficient thermal management in porous media is essential for advanced engineering applications,including solar energy systems,electronic cooling,and aerospace thermal control.This study presents a comprehensive analysis of ternary hybrid nanofluids,TiO_(2)-CdTe-MoS_(2) dispersed in water,flowing over a vertical stretching or shrinking surface in a Darcy-Brinkman porous medium.The investigation accounts for the combined effects of magnetohydrodynamics,thermal radiation,viscous dissipation,and internal heat generation.In contrast to previous studies that predominantly focused on single or binary nanofluids,the present work systematically examines the thermal and hydrodynamic performance of ternary hybrid nanofluids,highlighting their enhanced heat transport capabilities in porous structures.The governing momentum and energy equations are formulated in nondimensional form and solved numerically using the shifted Legendre collocation method.The results show that increasing the magnetic parameter,M=0-4,suppresses the fluid velocity by up to 28%,while stronger thermal radiation,R=0-5,raises the near-surface temperature by approximately 32%.Viscous dissipation and internal heat generation further enhance the Nusselt number,indicating improved heat transfer performance.Overall,the findings demonstrate the synergistic influence of the three nanoparticles in optimizing flow behavior and thermal characteristics,offering valuable insights for the design of high-performance thermal management systems in energy and aerospace applications.展开更多
In the references[4,11,12],the authors gave some modular forms overΓ^(0)(2).In this note,we proceed with the study of cancellation formulas relating to the modular forms.
Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces.The trapezoidal cavity form is compared with its thermal and flow performance,and it is reveal...Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces.The trapezoidal cavity form is compared with its thermal and flow performance,and it is revealed that trapezoidal fins tend to be more efficient,particularly when material optimization is critical.Motivated by the increasing need for sustainable energy management,this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid.The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties;hence,optimising these properties can significantly improve overall performance.This study considers the dispersion of Graphene Oxide(GO)and Molybdenum Disulfide in the base fluid,engine oil.Temperature profiles are analysed by altering the radiative,porosity,wet porous,and angle of inclination parameters.Surface and contour plots are constructed by using the Lobatto IIIa Collocation Method with BVP5C solver in MATLAB and Gradient Descent Optimisation to predict the combined heat transfer rate.According to the study,fluid temperature consistently decreases when the angle of inclination,wet porous parameter,porosity parameter,and radiative parameter increase,suggesting significantly improved heat dissipation.The trapezoidal fin consistently exhibits a superior heat transfer mechanism than a rectangular fin.It is found that the trapezoidal fin transmits heat at a rate that is 0.05%higher than that of the rectangular fin.Validation of the present study is done through the comparison of previous studies.This research provides useful design insights for sophisticated engineering uses,including electrical cooling devices,heat exchangers,radiators,and solar heaters.展开更多
A high-order hybrid numerical framework is developed by coupling a three-stage exponential time integrator with a Runge–Kutta scheme for the efficient solution of partial differential equations involving first-order ...A high-order hybrid numerical framework is developed by coupling a three-stage exponential time integrator with a Runge–Kutta scheme for the efficient solution of partial differential equations involving first-order time derivatives.The proposed scheme attains third-order temporal accuracy and is rigorously validated through stability and convergence analyses for both scalar and coupled systems.Its effectiveness is demonstrated by simulating unsteady Eyring-Prandtl non-Newtonian nanofluid flow over a Riga plate with coupled heat and mass transfer under electromagnetic actuation.The physical model accounts for Brownian motion and thermophoresis,and the nanofluid considered is a Prandtl-type non-Newtonian base fluid containing suspended nanoparticles,with heat and mass transport governed by coupled momentum,energy,and concentration equations.Numerical simulations are performed over practically relevant parameter ranges,with the Reynolds number fixed at Re=5 and the Prandtl number set to Pr=3 to represent moderate inertial and thermal diffusion effects typical of nanofluid transport systems.To enhance computational efficiency,an artificial neural network(ANN)-based surrogate model is developed to predict the skin friction coefficient and local Sherwood number as functions of Reynolds number,Prandtl number,Schmidt number,Brownian motion,and thermophoresis parameters.The training dataset is generated entirely from high-fidelity numerical simulations produced by the proposed hybrid scheme.The data are systematically partitioned into 70%for training,15%for validation,and 15%for testing,ensuring reliable generalization.Regression analysis yields a near-unity correlation coefficient(R≈0.99),while error histograms exhibit tightly clustered residuals around zero,confirming high predictive accuracy.Furthermore,a benchmark convergence study using Stokes’first problem demonstrates that the proposed scheme consistently achieves lower global error norms than the classical Runge–Kutta method for identical spatial and temporal resolutions.Overall,this study introduces a novel computational intelligence framework that integrates high-order numerical solvers with machine learning,offering a robust and time-efficient tool for advanced modeling and real-time prediction of non-Newtonian nanofluid transport phenomena under electromagnetic flow control.展开更多
Overcoming the strength-ductility trade-off in alloys without complex post-processing remains a critical challenge.Here,we designed a hierarchical heterostructure of micro-cellular segregation(MCS)and supranano precip...Overcoming the strength-ductility trade-off in alloys without complex post-processing remains a critical challenge.Here,we designed a hierarchical heterostructure of micro-cellular segregation(MCS)and supranano precipitates(SNPs)in the directly cast medium-entropy alloy(MEA),achieving higher strength without a significant loss of plasticity.This MCS-SNP alloy exhibits a superior combination of tensile strength(~922 MPa)and elongation(~32%)compared with most traditional ascast face-centered cubic(FCC)alloys.The MCS impedes the movement of the slip bands and maintains the flow stress in the work-hardening process.The SNPs enhance the pinning effect of dislocations,providing an additional source of work hardening together with microbands.The synergistic effect of MCS and SNP generates significant back stress at both micro and nano scales.The findings of this study provide a promising strategy for designing high-performance casting alloys with integrated microscale cellular segregation and supranano precipitate structures.展开更多
This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state obs...This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state observer(ARESO)is constructed to estimate the unmeasured states,the total disturbance,and its derivatives.Compared to conventional ESOs,the proposed ARESO can enhance the estimation performance by actively estimating the derivatives of the total disturbance.In the time domain,by an inductive decoupling-based bound analysis method,this paper rigorously investigates the closed-loop transient performance without the prior assumption on the boundedness of derivatives of nonlinear uncertainties.In the frequency domain,a comparative analysis demonstrates the superiority of ARADRC in both disturbance estimation and rejection.Finally,the magnetic levitation experiments validate the effectiveness of the proposed method.展开更多
Based on reanalysis data from 1979 to 2021,this study explores the spatial distribution of the Southern Indian Ocean Dipole(SIOD)and its individual and synergistic effects with the El Niño-Southern Oscillation(EN...Based on reanalysis data from 1979 to 2021,this study explores the spatial distribution of the Southern Indian Ocean Dipole(SIOD)and its individual and synergistic effects with the El Niño-Southern Oscillation(ENSO)on summer precipitation in China.The inverse phase spatial distribution of sea surface temperature anomalies(SSTAs)in the southwest and northeast of the southern Indian Ocean is defined as the SIOD.Positive SIOD events(positive SSTAs in the southwest,negative SSTAs in the northeast)are associated with La Niña events(Central Pacific(CP)type),while negative SIOD events(negative SSTAs in the southwest,positive SSTAs in the northeast)are associated with El Niño events(Eastern Pacific(EP)type).Both SIOD and ENSO have certain impacts on summer precipitation in China.Precipitation in the Yangtze River basin decreases,while precipitation in southern China increases during pure positive SIOD(P_PSIOD)events.During pure negative SIOD(P_NSIOD)events,the changes in precipitation are exactly the opposite of those during P_PSIOD events,which may be due to differences in the cross-equatorial flow in the southern Indian Ocean,particularly in low-level Australian cross-equatorial flow.When positive SIOD and CP-type La Niña events occur simultaneously(PSIOD+La_Niña),precipitation increases in the Yangtze-Huaihe River basin,while it decreases in northern China.When negative SIOD and EP-type El Niño events occur simultaneously(NSIOD+El_Niño),precipitation in the Yangtze-Huaihe River basin is significantly lower than during P_NSIOD events.This is caused by differences in water vapor originating from the Pacific Ocean during different events.展开更多
The node labels collected from real-world applications are often accompanied by the occurrence of in-distribution noise(seen class nodes with wrong labels) and out-of-distribution noise(unseen class nodes with seen cl...The node labels collected from real-world applications are often accompanied by the occurrence of in-distribution noise(seen class nodes with wrong labels) and out-of-distribution noise(unseen class nodes with seen class labels), which significantly degrade the superior performance of recently emerged open-set graph neural networks(GNN). Nowadays, only a few researchers have attempted to introduce sample selection strategies developed in non-graph areas to limit the influence of noisy node labels. These studies often neglect the impact of inaccurate graph structure relationships, invalid utilization of noisy nodes and unlabeled nodes self-supervision information for noisy node labels constraint. More importantly, simply enhancing the accuracy of graph structure relationships or the utilization of nodes' self-supervision information still cannot minimize the influence of noisy node labels for open-set GNN. In this paper, we propose a novel RT-OGNN(robust training of open-set GNN) framework to solve the above-mentioned issues. Specifically, an effective graph structure learning module is proposed to weaken the impact of structure noise and extend the receptive field of nodes. Then, the augmented graph is sent to a pair of peer GNNs to accurately distinguish noisy node labels of labeled nodes. Third, the label propagation and multilayer perceptron-based decoder modules are simultaneously introduced to discover more supervision information from remaining nodes apart from clean nodes. Finally, we jointly optimize the above modules and open-set GNN in an end-to-end way via consistency regularization loss and cross-entropy loss, which minimizes the influence of noisy node labels and provides more supervision guidance for open-set GNN optimization.Extensive experiments on three benchmarks and various noise rates validate the superiority of RT-OGNN over state-of-the-art models.展开更多
Predator–prey interactions are fundamental to understanding ecosystem stability and biodiversity.In this study,we propose and analyze a stochastic predator–prey model that incorporates two critical ecological factor...Predator–prey interactions are fundamental to understanding ecosystem stability and biodiversity.In this study,we propose and analyze a stochastic predator–prey model that incorporates two critical ecological factors:prey refuge and harvesting.The model also integrates disease transmission within the predator population,adding an important layer of realism.Using rigorous mathematical techniques,we demonstrate the existence and uniqueness of a global positive solution,thereby confirming the model's biological feasibility.We further derive sufficient conditions for two key ecological scenarios:stochastic permanence,which ensures the sustained co-existence of prey and predators over time,and extinction,where one or both populations decline to zero.The interplay between prey refuge and harvesting is thoroughly examined to understand their combined impact on population dynamics.All theoretical results are validated by detailed numerical simulations,highlighting the applicability of the model to real-world ecological systems.From the simulation results,we observed that with an adequate level of prey refuge and predator harvesting,the susceptible predator and prey coexist with extensive oscillations,while the infected predator population was moving towards extinction.In addition,we have investigated the effect of disease transmission on system dynamics.Our results show that,as the transmission rate of disease increases,the susceptible predator approaches extinction,whereas,on the other hand,when it declines,the susceptible predator shows robust oscillations while the infected approaches extinction.In both cases,the prey population demonstrates robust stability due to the prey refuge.Our findings show that the management of harvesting and the prey refuge can be effective ecological tactics for disease control and species protection under stochastic environmental effects.展开更多
Colorectal cancer is the third most diagnosed cancer worldwide,and immune checkpoint inhibitors have shown promising therapeutic outcomes in selected patient groups.This study performed a comprehensive analysis of mul...Colorectal cancer is the third most diagnosed cancer worldwide,and immune checkpoint inhibitors have shown promising therapeutic outcomes in selected patient groups.This study performed a comprehensive analysis of multi-omics data from The Cancer Genome Atlas colorectal adenocarcinoma cohort(TCGA-COADREAD),accessed through cBioPortal,to develop machine learning models for predicting progression-free survival(PFS)following immunotherapy.The dataset included clinical variables,genomic alterations in Kirsten Rat Sarcoma Viral Oncogene Homolog(KRAS),B-Raf Proto-Oncogene(BRAF),and Neuroblastoma RAS Viral Oncogene Homolog(NRAS),microsatellite instability(MSI)status,tumor mutation burden(TMB),and expression of immune checkpoint genes.Kaplan–Meier analysis showed that KRAS mutations were significantly associated with reduced PFS,while BRAF and NRAS mutations had no significant impact.MSI-high tumors exhibited elevated TMB and increased immune checkpoint expression,reflecting their immunologically active phenotype.We developed both survival and classification models,with the Extra Trees classifier achieving the best performance(accuracy=0.86,precision=0.67,recall=0.70,F1-score=0.68,AUC=0.84).These findings highlight the potential of combining genomic and immune biomarkers with machine learning to improve patient stratification and guide personalized immunotherapy decisions.An interactive web application was also developed to enable clinicians to input patient-specific molecular and clinical data and visualize individualized PFS predictions,supporting timely,data-driven treatment planning.展开更多
Aberrant activation of Receptor Tyrosine Kinases(RTKs)is a well-established trigger of tumorigenesis,and the over-use of RTK inhibitors often leads to drug resistance and tumor recurrence.While current Drug-Target Int...Aberrant activation of Receptor Tyrosine Kinases(RTKs)is a well-established trigger of tumorigenesis,and the over-use of RTK inhibitors often leads to drug resistance and tumor recurrence.While current Drug-Target Interaction(DTI)prediction methods(including those based on heterogeneous information networks)have shown promise,they remain limited in their ability to fully capture the nature of DTIs and often lack interpretability.To overcome these limitations,this study introduces a novel hybrid optimization model termed MDBO-RF,which integrates a Modified Dung Beetle Optimizer(MDBO)with Random Forest(RF).The key innovation lies in the enhancement of the DBO algorithm through a quaternion-based learning mechanism and the Cauchy mutation strategy,specifically designed to overcome the slow convergence and susceptibility to local optima that plague traditional metaheuristic algorithms used for hyperparameter tuning.The model leverages commonly used molecular descriptors to enhance the prediction of Tyrosine Kinase(TK)inhibitory activity and enable efficient compound screening.Our results demonstrate that MDBO-RF achieves a 3.41%increase in prediction accuracy compared to the standard RF model and outperforms several other contemporary machine learning approaches.The model effectively streamlines the RTK inhibitor screening process by improving prediction accuracy in multi-target competitive binding scenarios and reducing false-positive screening due to off-target effects.This work underscores the value of hybrid optimization strategies in bioinformatics and provides a robust,interpretable tool for accelerating drug discovery.展开更多
The Yuncheng Basin,located in the southern part of the Fenwei Rift,North China,exhibits obvious crust thinning(Moho uplift of 6-8 km)and shallow Curie point depth(less than 18 km)and hence holds great potential for ge...The Yuncheng Basin,located in the southern part of the Fenwei Rift,North China,exhibits obvious crust thinning(Moho uplift of 6-8 km)and shallow Curie point depth(less than 18 km)and hence holds great potential for geothermal resources.However,geothermal exploration within the Yuncheng Basin typically faces significant challenges due to civil and industrial noise from dense populations and industrial activities.To address these challenges,both Controlled-Source Audio-frequency Magnetotellurics(CSAMT)and radon measurements were employed in Baozigou village to investigate the geothermal structures and identify potential geothermal targets.The CSAMT method effectively delineated the structure of the subsurface hydrothermal system,identifying the reservoir as Paleogene sandstones and Ordovician and Cambrian limestones at elevations ranging from−800 m to−2500 m.In particular,two concealed normal faults(F_(a)and F_(b))were newly revealed by the combination of CSAMT and radon profiling;these previously undetected faults,which exhibit different scales and opposing dips,are likely to be responsible for controlling the convection of thermal water within the Basin’s subsurface hydrothermal system.Moreover,this study developed a preliminary conceptual geothermal model for the Fen River Depression within the Yuncheng Basin,which encompasses geothermal heat sources,cap rocks,reservoirs,and fluid pathways,providing valuable insights for future geothermal exploration.In conjunction with the 3D geological model constructed from CSAMT resistivity structures beneath Baozigou village,test drilling is recommended in the northwestern region of the Baozigou area to intersect the potentially deep fractured carbonates that may contain temperature-elevated geothermal water.This study establishes a good set of guidelines for future geothermal exploration in this region,indicating that high-permeability faults in the central segments of the Fen River Depression are promising targets.展开更多
Teaching goal design is an important link of teaching design, which has the teaching, learning and measurement function. How to establish the appropriate teaching goal and properly state to enhance its guidance and de...Teaching goal design is an important link of teaching design, which has the teaching, learning and measurement function. How to establish the appropriate teaching goal and properly state to enhance its guidance and detection function are the important tasks of teaching design. This paper makes a programming and systematic analysis on the aspects of teaching goal design theory, teaching goal statement mode and technology, teaching goal statement and design and teaching goal design detection.展开更多
基金2021 Annual Research Project of Yili Normal University(2021YSBS012)。
文摘With the implementation of General Senior High School Mathematics Curriculum Standards(2017 Edition,Revised in 2020),probability and statistics,as important carriers of the core mathematical competencies“mathematical modeling”and“data analysis,”have increasingly highlighted their educational value.By summarizing the historical evolution of probability and statistics thinking and combining with teaching practice cases,this study explores its unique role in cultivating students’core mathematical competencies.The research proposes a project-based teaching strategy relying on real scenarios and empowered by technology.Through cases,it demonstrates how to use modern educational technology to realize the whole-process exploration of data collection,model construction,and conclusion verification,so as to promote the transformation of middle school probability and statistics teaching from knowledge imparting to competency development,and provide a practical reference for curriculum reform.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金Supported by The 23 rd Batch of Undergraduate Innovation Training Program Projects of Shanxi Provincial Department of Education"Research on the Path for Enhancing Customer Loyalty of Time-honored Chinese Brands from the Perspective of New Quality Productive Forces:A Case Study of Yuyue Brewing"(S202510108074).
文摘This study focuses on the "Yuyue Brewing" brand and employs grounded theory in conjunction with NVivo 11 software analysis to identify the key factors and dimensions influencing the cultivation of customer mindset, thereby constructing a theoretical model. The findings suggest that the three fundamental components of an entrepreneur s personal mindset—energy, ability, and wisdom—collectively constitute the foundation of entrepreneurial leadership. Establishing a clear brand positioning and developing its core values accordingly are essential aspects of the brand mindset. Furthermore, articulating the customer mindset involves comprehending the emotions and perspectives of target customers within specific contexts. The success of a brand depends not only on the product itself but also on the synergistic interaction among the entrepreneur s personal mindset, the brand mindset, and the customer mindset.
基金Supported by the National Natural Science Foundation of China(Grant Nos.11961059,1210502)the University Innovation Project of Gansu Province(Grant No.2023B-062)the Gansu Province Basic Research Innovation Group Project(Grant No.23JRRA684).
文摘The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.
基金Supported by the National Natural Science Foundation of China(Grant No.12261081).
文摘In this paper,we are concerned with the stability of traveling wavefronts of a Belousov-Zhabotinsky model with mixed nonlocal and degenerate diffusions.Such a system can be used to study the competition among nonlocally diffusive species and degenerately diffusive species.We prove that the traveling wavefronts are exponentially stable,when the initial perturbation around the traveling waves decays exponentially as x→-∞,but in other locations,the initial data can be arbitrarily large.The adopted methods are the weighted energy with the comparison principle and squeezing technique.
基金Supported by the Science and Technology Program of Guizhou Province(Grant No.QKHJC QN[2025]362)the National Natural Science Foundation of China(Grant No.12361005).
文摘Loday introduced di-associative algebras and tri-associative algebras motivated by periodicity phenomena in algebraic K-theory.The purpose of this paper is to study the splittings of operations on di-associative algebras and tri-associative algebras.We introduce the notion of a quad-dendriform algebra,which is a splitting of a di-associative algebra.We show that a relative averaging operator on dendriform algebras gives rise to a quad-dendriform algebra.Furthermore,we introduce the notion of six-dendriform algebras,which are splittings of the tri-associative algebras,and demonstrate that homomorphic relative averaging operators induce six-dendriform algebras.
文摘An atmospheric general circulation model(AGCM)is used to analyze the different impact on the Barents Sea(BS)and Greenland Sea(GS)for a perturbation of sea-to-air DMS flux.We compare contemporary anthropogenic S and contemporary DMS sea-to-air flux(as baseline,B00)sulfur emissions,with contemporary anthropogenic S and a perturbed DMS flux(as modified,B01)sulfur emissions.Results show that the global mean surface DMS and DMS vertically integrated concentration all peaked in June and increases more than 63%in BS and increases about 58%in GS.The concentrations of atmospheric sulfur dioxide vertical integral(SO_(2))and sulfate vertical integral(SO_(4))only increase less than 12%in both regions.Sulfur emission(SEM)peaked in June and increased about 67%and 41%in GS and BS,respectively.Aerosol optical depth(AOD)increases less than 4%in GS and in BS.Surface temperature(TSC)peaked in July and reduces 0.25 K and 0.8 K in GS and BS,respectively.Satellite data from 2003 to 2023show that chlorophyll(CHL)concentration in BS exceeds that of GS by 51%.The AOD in GS is only 0.6%higher than in BS.The recent increased rate of DMS surface concentration in BS(from 6%during 1981–2002 to 18.8%in 2003–2023)is mainly caused by elevated CHL concentrations in BS.Finally,the perturbation on DMS flux leads to increase rate of DMS and related sulfur emissions especially in the BS,this tendency will have an offsetting effect on regional warming.
文摘Efficient thermal management in porous media is essential for advanced engineering applications,including solar energy systems,electronic cooling,and aerospace thermal control.This study presents a comprehensive analysis of ternary hybrid nanofluids,TiO_(2)-CdTe-MoS_(2) dispersed in water,flowing over a vertical stretching or shrinking surface in a Darcy-Brinkman porous medium.The investigation accounts for the combined effects of magnetohydrodynamics,thermal radiation,viscous dissipation,and internal heat generation.In contrast to previous studies that predominantly focused on single or binary nanofluids,the present work systematically examines the thermal and hydrodynamic performance of ternary hybrid nanofluids,highlighting their enhanced heat transport capabilities in porous structures.The governing momentum and energy equations are formulated in nondimensional form and solved numerically using the shifted Legendre collocation method.The results show that increasing the magnetic parameter,M=0-4,suppresses the fluid velocity by up to 28%,while stronger thermal radiation,R=0-5,raises the near-surface temperature by approximately 32%.Viscous dissipation and internal heat generation further enhance the Nusselt number,indicating improved heat transfer performance.Overall,the findings demonstrate the synergistic influence of the three nanoparticles in optimizing flow behavior and thermal characteristics,offering valuable insights for the design of high-performance thermal management systems in energy and aerospace applications.
文摘In the references[4,11,12],the authors gave some modular forms overΓ^(0)(2).In this note,we proceed with the study of cancellation formulas relating to the modular forms.
基金supported by the“Regional Innovation System&Education(RISE)”through the Seoul RISE Center,funded by the Ministry of Education(MOE)and the Seoul Metropolitan Government(2025-RISE-01-027-04).
文摘Fluid dynamic research on rectangular and trapezoidal fins is aimed at increasing heat transfer by means of large surfaces.The trapezoidal cavity form is compared with its thermal and flow performance,and it is revealed that trapezoidal fins tend to be more efficient,particularly when material optimization is critical.Motivated by the increasing need for sustainable energy management,this work analyses the thermal performance of inclined trapezoidal and rectangular porous fins utilising a unique hybrid nanofluid.The effectiveness of nanoparticles in a working fluid is primarily determined by their thermophysical properties;hence,optimising these properties can significantly improve overall performance.This study considers the dispersion of Graphene Oxide(GO)and Molybdenum Disulfide in the base fluid,engine oil.Temperature profiles are analysed by altering the radiative,porosity,wet porous,and angle of inclination parameters.Surface and contour plots are constructed by using the Lobatto IIIa Collocation Method with BVP5C solver in MATLAB and Gradient Descent Optimisation to predict the combined heat transfer rate.According to the study,fluid temperature consistently decreases when the angle of inclination,wet porous parameter,porosity parameter,and radiative parameter increase,suggesting significantly improved heat dissipation.The trapezoidal fin consistently exhibits a superior heat transfer mechanism than a rectangular fin.It is found that the trapezoidal fin transmits heat at a rate that is 0.05%higher than that of the rectangular fin.Validation of the present study is done through the comparison of previous studies.This research provides useful design insights for sophisticated engineering uses,including electrical cooling devices,heat exchangers,radiators,and solar heaters.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2603).
文摘A high-order hybrid numerical framework is developed by coupling a three-stage exponential time integrator with a Runge–Kutta scheme for the efficient solution of partial differential equations involving first-order time derivatives.The proposed scheme attains third-order temporal accuracy and is rigorously validated through stability and convergence analyses for both scalar and coupled systems.Its effectiveness is demonstrated by simulating unsteady Eyring-Prandtl non-Newtonian nanofluid flow over a Riga plate with coupled heat and mass transfer under electromagnetic actuation.The physical model accounts for Brownian motion and thermophoresis,and the nanofluid considered is a Prandtl-type non-Newtonian base fluid containing suspended nanoparticles,with heat and mass transport governed by coupled momentum,energy,and concentration equations.Numerical simulations are performed over practically relevant parameter ranges,with the Reynolds number fixed at Re=5 and the Prandtl number set to Pr=3 to represent moderate inertial and thermal diffusion effects typical of nanofluid transport systems.To enhance computational efficiency,an artificial neural network(ANN)-based surrogate model is developed to predict the skin friction coefficient and local Sherwood number as functions of Reynolds number,Prandtl number,Schmidt number,Brownian motion,and thermophoresis parameters.The training dataset is generated entirely from high-fidelity numerical simulations produced by the proposed hybrid scheme.The data are systematically partitioned into 70%for training,15%for validation,and 15%for testing,ensuring reliable generalization.Regression analysis yields a near-unity correlation coefficient(R≈0.99),while error histograms exhibit tightly clustered residuals around zero,confirming high predictive accuracy.Furthermore,a benchmark convergence study using Stokes’first problem demonstrates that the proposed scheme consistently achieves lower global error norms than the classical Runge–Kutta method for identical spatial and temporal resolutions.Overall,this study introduces a novel computational intelligence framework that integrates high-order numerical solvers with machine learning,offering a robust and time-efficient tool for advanced modeling and real-time prediction of non-Newtonian nanofluid transport phenomena under electromagnetic flow control.
基金supported by the National Natural Science Foundation of China(Grant Nos.52401215,52271149,52301209,52401214,52201183)the Shanghai Magnolia Talent Plan Pujiang Project(Grant No.24PJD035)+3 种基金the Open Research Fund of Songshan Lake Materials Laboratory(Grant No.2023SLABFN07)the Technology Plan Program of Shanghai Municipal Commission of Science and Technology(Grant No.25CL2902300)the Shanghai Science and Technology Innovation Action Plan(Grant No.24CL2901500)the Shanghai Municipal Explorer Program(Grant No.25TS1401900)。
文摘Overcoming the strength-ductility trade-off in alloys without complex post-processing remains a critical challenge.Here,we designed a hierarchical heterostructure of micro-cellular segregation(MCS)and supranano precipitates(SNPs)in the directly cast medium-entropy alloy(MEA),achieving higher strength without a significant loss of plasticity.This MCS-SNP alloy exhibits a superior combination of tensile strength(~922 MPa)and elongation(~32%)compared with most traditional ascast face-centered cubic(FCC)alloys.The MCS impedes the movement of the slip bands and maintains the flow stress in the work-hardening process.The SNPs enhance the pinning effect of dislocations,providing an additional source of work hardening together with microbands.The synergistic effect of MCS and SNP generates significant back stress at both micro and nano scales.The findings of this study provide a promising strategy for designing high-performance casting alloys with integrated microscale cellular segregation and supranano precipitate structures.
基金supported by the National Natural Science Foundation of China(Grant Nos.62473344,92471204)the Natural Science Basic Research Program of Shaanxi(Grant No.2025JC-YBQN035)Ministry of Education's Industry School Cooperation Collaborative Education Project(Grant No.240704701190619)。
文摘This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state observer(ARESO)is constructed to estimate the unmeasured states,the total disturbance,and its derivatives.Compared to conventional ESOs,the proposed ARESO can enhance the estimation performance by actively estimating the derivatives of the total disturbance.In the time domain,by an inductive decoupling-based bound analysis method,this paper rigorously investigates the closed-loop transient performance without the prior assumption on the boundedness of derivatives of nonlinear uncertainties.In the frequency domain,a comparative analysis demonstrates the superiority of ARADRC in both disturbance estimation and rejection.Finally,the magnetic levitation experiments validate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China[grant numbers 41975087,U2242212,and 41975085]supported by the National Natural Science Foundation of China[grant number U2242212]。
文摘Based on reanalysis data from 1979 to 2021,this study explores the spatial distribution of the Southern Indian Ocean Dipole(SIOD)and its individual and synergistic effects with the El Niño-Southern Oscillation(ENSO)on summer precipitation in China.The inverse phase spatial distribution of sea surface temperature anomalies(SSTAs)in the southwest and northeast of the southern Indian Ocean is defined as the SIOD.Positive SIOD events(positive SSTAs in the southwest,negative SSTAs in the northeast)are associated with La Niña events(Central Pacific(CP)type),while negative SIOD events(negative SSTAs in the southwest,positive SSTAs in the northeast)are associated with El Niño events(Eastern Pacific(EP)type).Both SIOD and ENSO have certain impacts on summer precipitation in China.Precipitation in the Yangtze River basin decreases,while precipitation in southern China increases during pure positive SIOD(P_PSIOD)events.During pure negative SIOD(P_NSIOD)events,the changes in precipitation are exactly the opposite of those during P_PSIOD events,which may be due to differences in the cross-equatorial flow in the southern Indian Ocean,particularly in low-level Australian cross-equatorial flow.When positive SIOD and CP-type La Niña events occur simultaneously(PSIOD+La_Niña),precipitation increases in the Yangtze-Huaihe River basin,while it decreases in northern China.When negative SIOD and EP-type El Niño events occur simultaneously(NSIOD+El_Niño),precipitation in the Yangtze-Huaihe River basin is significantly lower than during P_NSIOD events.This is caused by differences in water vapor originating from the Pacific Ocean during different events.
基金supported by the General Program of the National Natural Science Foundation of China (Grant No.62575116)the National Natural Science Foundation of China (Grant No.62262005)+1 种基金the High-level Innovative Talents in Guizhou Province (Grant No.GCC[2023]033)the Open Project of the Text Computing and Cognitive Intelligence Ministry of Education Engineering Research Center(Grant No.TCCI250208)。
文摘The node labels collected from real-world applications are often accompanied by the occurrence of in-distribution noise(seen class nodes with wrong labels) and out-of-distribution noise(unseen class nodes with seen class labels), which significantly degrade the superior performance of recently emerged open-set graph neural networks(GNN). Nowadays, only a few researchers have attempted to introduce sample selection strategies developed in non-graph areas to limit the influence of noisy node labels. These studies often neglect the impact of inaccurate graph structure relationships, invalid utilization of noisy nodes and unlabeled nodes self-supervision information for noisy node labels constraint. More importantly, simply enhancing the accuracy of graph structure relationships or the utilization of nodes' self-supervision information still cannot minimize the influence of noisy node labels for open-set GNN. In this paper, we propose a novel RT-OGNN(robust training of open-set GNN) framework to solve the above-mentioned issues. Specifically, an effective graph structure learning module is proposed to weaken the impact of structure noise and extend the receptive field of nodes. Then, the augmented graph is sent to a pair of peer GNNs to accurately distinguish noisy node labels of labeled nodes. Third, the label propagation and multilayer perceptron-based decoder modules are simultaneously introduced to discover more supervision information from remaining nodes apart from clean nodes. Finally, we jointly optimize the above modules and open-set GNN in an end-to-end way via consistency regularization loss and cross-entropy loss, which minimizes the influence of noisy node labels and provides more supervision guidance for open-set GNN optimization.Extensive experiments on three benchmarks and various noise rates validate the superiority of RT-OGNN over state-of-the-art models.
基金supported by the National Natural Science Foundation of China(Grant No.32271554)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011501)。
文摘Predator–prey interactions are fundamental to understanding ecosystem stability and biodiversity.In this study,we propose and analyze a stochastic predator–prey model that incorporates two critical ecological factors:prey refuge and harvesting.The model also integrates disease transmission within the predator population,adding an important layer of realism.Using rigorous mathematical techniques,we demonstrate the existence and uniqueness of a global positive solution,thereby confirming the model's biological feasibility.We further derive sufficient conditions for two key ecological scenarios:stochastic permanence,which ensures the sustained co-existence of prey and predators over time,and extinction,where one or both populations decline to zero.The interplay between prey refuge and harvesting is thoroughly examined to understand their combined impact on population dynamics.All theoretical results are validated by detailed numerical simulations,highlighting the applicability of the model to real-world ecological systems.From the simulation results,we observed that with an adequate level of prey refuge and predator harvesting,the susceptible predator and prey coexist with extensive oscillations,while the infected predator population was moving towards extinction.In addition,we have investigated the effect of disease transmission on system dynamics.Our results show that,as the transmission rate of disease increases,the susceptible predator approaches extinction,whereas,on the other hand,when it declines,the susceptible predator shows robust oscillations while the infected approaches extinction.In both cases,the prey population demonstrates robust stability due to the prey refuge.Our findings show that the management of harvesting and the prey refuge can be effective ecological tactics for disease control and species protection under stochastic environmental effects.
基金funded by the Research,Development,and Innovation Authority(RDIA)—Kingdom of Saudi Arabia(Grant No.13292-psu-2023-PSNU-R-3-1-EF-).
文摘Colorectal cancer is the third most diagnosed cancer worldwide,and immune checkpoint inhibitors have shown promising therapeutic outcomes in selected patient groups.This study performed a comprehensive analysis of multi-omics data from The Cancer Genome Atlas colorectal adenocarcinoma cohort(TCGA-COADREAD),accessed through cBioPortal,to develop machine learning models for predicting progression-free survival(PFS)following immunotherapy.The dataset included clinical variables,genomic alterations in Kirsten Rat Sarcoma Viral Oncogene Homolog(KRAS),B-Raf Proto-Oncogene(BRAF),and Neuroblastoma RAS Viral Oncogene Homolog(NRAS),microsatellite instability(MSI)status,tumor mutation burden(TMB),and expression of immune checkpoint genes.Kaplan–Meier analysis showed that KRAS mutations were significantly associated with reduced PFS,while BRAF and NRAS mutations had no significant impact.MSI-high tumors exhibited elevated TMB and increased immune checkpoint expression,reflecting their immunologically active phenotype.We developed both survival and classification models,with the Extra Trees classifier achieving the best performance(accuracy=0.86,precision=0.67,recall=0.70,F1-score=0.68,AUC=0.84).These findings highlight the potential of combining genomic and immune biomarkers with machine learning to improve patient stratification and guide personalized immunotherapy decisions.An interactive web application was also developed to enable clinicians to input patient-specific molecular and clinical data and visualize individualized PFS predictions,supporting timely,data-driven treatment planning.
基金National Key Research and Development Program of China(No.2022YFD1802104).
文摘Aberrant activation of Receptor Tyrosine Kinases(RTKs)is a well-established trigger of tumorigenesis,and the over-use of RTK inhibitors often leads to drug resistance and tumor recurrence.While current Drug-Target Interaction(DTI)prediction methods(including those based on heterogeneous information networks)have shown promise,they remain limited in their ability to fully capture the nature of DTIs and often lack interpretability.To overcome these limitations,this study introduces a novel hybrid optimization model termed MDBO-RF,which integrates a Modified Dung Beetle Optimizer(MDBO)with Random Forest(RF).The key innovation lies in the enhancement of the DBO algorithm through a quaternion-based learning mechanism and the Cauchy mutation strategy,specifically designed to overcome the slow convergence and susceptibility to local optima that plague traditional metaheuristic algorithms used for hyperparameter tuning.The model leverages commonly used molecular descriptors to enhance the prediction of Tyrosine Kinase(TK)inhibitory activity and enable efficient compound screening.Our results demonstrate that MDBO-RF achieves a 3.41%increase in prediction accuracy compared to the standard RF model and outperforms several other contemporary machine learning approaches.The model effectively streamlines the RTK inhibitor screening process by improving prediction accuracy in multi-target competitive binding scenarios and reducing false-positive screening due to off-target effects.This work underscores the value of hybrid optimization strategies in bioinformatics and provides a robust,interpretable tool for accelerating drug discovery.
基金supported by the Shanxi Province Basic Research Program(No.20210302123374)Yuncheng University Doctoral Research Initiation Fund(No.YQ-2021008)+3 种基金Excellent doctors come to Shanxi to reward scientific research projects(No.QZX-2023020)Open Fund of State Key Laboratory of Precision Geodesy(No.SKLPG2025-1-1)Joint Open Fund of the Research Platforms of School of Computer Science,China University of Geosciences,Wuhan(No.PTLH2024-B-03)Hubei Provincial Natural Science Foundation Project(No.2025AFC095).
文摘The Yuncheng Basin,located in the southern part of the Fenwei Rift,North China,exhibits obvious crust thinning(Moho uplift of 6-8 km)and shallow Curie point depth(less than 18 km)and hence holds great potential for geothermal resources.However,geothermal exploration within the Yuncheng Basin typically faces significant challenges due to civil and industrial noise from dense populations and industrial activities.To address these challenges,both Controlled-Source Audio-frequency Magnetotellurics(CSAMT)and radon measurements were employed in Baozigou village to investigate the geothermal structures and identify potential geothermal targets.The CSAMT method effectively delineated the structure of the subsurface hydrothermal system,identifying the reservoir as Paleogene sandstones and Ordovician and Cambrian limestones at elevations ranging from−800 m to−2500 m.In particular,two concealed normal faults(F_(a)and F_(b))were newly revealed by the combination of CSAMT and radon profiling;these previously undetected faults,which exhibit different scales and opposing dips,are likely to be responsible for controlling the convection of thermal water within the Basin’s subsurface hydrothermal system.Moreover,this study developed a preliminary conceptual geothermal model for the Fen River Depression within the Yuncheng Basin,which encompasses geothermal heat sources,cap rocks,reservoirs,and fluid pathways,providing valuable insights for future geothermal exploration.In conjunction with the 3D geological model constructed from CSAMT resistivity structures beneath Baozigou village,test drilling is recommended in the northwestern region of the Baozigou area to intersect the potentially deep fractured carbonates that may contain temperature-elevated geothermal water.This study establishes a good set of guidelines for future geothermal exploration in this region,indicating that high-permeability faults in the central segments of the Fen River Depression are promising targets.
文摘Teaching goal design is an important link of teaching design, which has the teaching, learning and measurement function. How to establish the appropriate teaching goal and properly state to enhance its guidance and detection function are the important tasks of teaching design. This paper makes a programming and systematic analysis on the aspects of teaching goal design theory, teaching goal statement mode and technology, teaching goal statement and design and teaching goal design detection.
