In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random vari...In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.展开更多
Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although la...Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels.展开更多
In this correspondence paper, an equivalent stability criterion with minimal number of linear matrix inequality （LMI） variables is presented for a delay-dependent stability criterion reported recently in the Interna...In this correspondence paper, an equivalent stability criterion with minimal number of linear matrix inequality （LMI） variables is presented for a delay-dependent stability criterion reported recently in the International Journal of Automation and Computing for a class of linear discrete-time systems with additive time delays. The reported stability criterion for the additive timedelay systems has more number of matrix variables in the LMI and, hence, demand additional computational burden. The proposed equivalent stability criterion, unlike the reported one, does not involve free-weighing matrices and encompass only the matrix variables that are associated in the Lyapunov-Krasovskii functional, making the criterion mathematically less complex and computationally more effective.展开更多
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
Cold seeps are oases for biological communities on the sea floor around hydrocarbon emission pathways.Microbial utilization of methane and other hydrocarbons yield products that fuel rich chemosynthetic communities at...Cold seeps are oases for biological communities on the sea floor around hydrocarbon emission pathways.Microbial utilization of methane and other hydrocarbons yield products that fuel rich chemosynthetic communities at these sites.One such site in the cold seep ecosystem of Krishna-Godavari basin(K-G basin)along the east coast of India,discovered in Feb 2018 at a depth of 1800 m was assessed for its bacterial diversity.The seep bacterial communities were dominated by phylum Proteobacteria(57%),Firmicutes(16%)and unclassified species belonging to the family Helicobacteriaceae.The surface sediments of the seep had maximum OTUs(operational taxonomic units)(2.27×10^(3))with a Shannon alpha diversity index of 8.06.In general,environmental parameters like total organic carbon(p<0.01),sulfate(p<0.001),sulfide(p<0.05)and methane(p<0.01)were responsible for shaping the bacterial community of the cold seep ecosystem in the K-G Basin.Environmental parameters play a significant role in changing the bacterial diversity richness between different cold seep environments in the oceans.展开更多
Solving constrained multi-objective optimization problems(CMOPs)is a challenging task due to the presence of multiple conflicting objectives and intricate constraints.In order to better address CMOPs and achieve a bal...Solving constrained multi-objective optimization problems(CMOPs)is a challenging task due to the presence of multiple conflicting objectives and intricate constraints.In order to better address CMOPs and achieve a balance between objectives and constraints,existing constrained multi-objective evolutionary algorithms(CMOEAs)predominantly focus on devising various strategies by leveraging the relationships between objectives and constraints,and the designed strategies usually are effective for the problems with simple constraints.However,these methods most ignore the relationship between decision variables and constraints.In fact,the essence of optimization is to find appropriate decision variables to meet various complex constraints.Therefore,it is hoped that the problem can be analyzed from the perspective of decision variables,so as to obtain more excellent results.Based on the above motivation,this paper proposes a decision variables classification approach,according to the relationship between decision variables and constraints,variables are divided into constraint-related(CR)variables and constraintindependent(CI)variables.Consequently,by optimizing these two types of variables independently,the population can sustain a favorable balance between feasibility and diversity.Furthermore,specific offspring generation strategies are proposed for the two categories of decision variables in order to achieve rapid convergence while maintaining population diversity.Experimental results on 31 test problems as well as 20 real-world problems demonstrate that the proposed algorithm is competitive compared to some state-of-the-art constrained multi-objective optimization algorithms.展开更多
In this paper,we establish characterizations of α-Bloch functions and little α-Bloch functions on the unit ball as well as the unit polydisk of C^(m),which generalize and improve results of Aulaskari-Lappan,Minda,Au...In this paper,we establish characterizations of α-Bloch functions and little α-Bloch functions on the unit ball as well as the unit polydisk of C^(m),which generalize and improve results of Aulaskari-Lappan,Minda,Aulaskari-Wulan,and Wu.Some examples are also given to complement our theory.展开更多
Time-delay effects on the dynamics of Li^nard type equation with one fast variable and one slow variable are investigated in the present paper. By using the methods of stability switch and geometric singular perturbat...Time-delay effects on the dynamics of Li^nard type equation with one fast variable and one slow variable are investigated in the present paper. By using the methods of stability switch and geometric singular perturbation, time-delay-induced complex oscillations and bursting are investigated, and in several case studies, the mechanism of the generation of the complex oscillations and bursting is illuminated. Numerical results demonstrate the validity of the theoretical results.展开更多
Assume that{a_(i),−∞<i<∞}is an absolutely summable sequence of real numbers.We establish the complete q-order moment convergence for the partial sums of moving average processes{X_(n)=Σ_(i=−∞)^(∞)a_(i)Y_(i+...Assume that{a_(i),−∞<i<∞}is an absolutely summable sequence of real numbers.We establish the complete q-order moment convergence for the partial sums of moving average processes{X_(n)=Σ_(i=−∞)^(∞)a_(i)Y_(i+n),n≥1}under some proper conditions,where{Yi,-∞<i<∞}is a doubly infinite sequence of negatively dependent random variables under sub-linear expectations.These results extend and complement the relevant results in probability space.展开更多
In this paper,the author obtains complete convergence for the maximum partial sums of m-widely orthant dependent(m-WOD)random variables sequences under some general conditions.The results extend the complete convergen...In this paper,the author obtains complete convergence for the maximum partial sums of m-widely orthant dependent(m-WOD)random variables sequences under some general conditions.The results extend the complete convergence for m-WOD random variables to a much more general type complete convergence.As the sequences of m-WOD random variables represent a very broad class of dependent sequences,the results improve and generalize the corresponding ones in the literature.展开更多
Accurately mapping the spatial distribution of soil organic carbon(SOC)is crucial for guiding agricultural management and improving soil carbon sequestration,especially in fragmented agricultural landscapes.Although r...Accurately mapping the spatial distribution of soil organic carbon(SOC)is crucial for guiding agricultural management and improving soil carbon sequestration,especially in fragmented agricultural landscapes.Although remote sensing provides spatially continuous environmental information about heterogeneous agricultural landscapes,its relationship with SOC remains unclear.In this study,we hypothesized that multi-category remote sensing-derived variables can enhance our understanding of SOC variation within complex landscape conditions.Taking the Qilu Lake watershed in Yunnan,China,as a case study area and based on 216 topsoil samples collected from irrigation areas,we applied the extreme gradient boosting(XGBoost)model to investigate the contributions of vegetation indices(VI),brightness indices(BI),moisture indices(MI),and spectral transformations(ST,principal component analysis and tasseled cap transformation)to SOC mapping.The results showed that ST contributed the most to SOC prediction accuracy,followed by MI,VI,and BI,with improvements in R2 of 29.27,26.83,19.51,and 14.43%,respectively.The dominance of ST can be attributed to the fact that it contains richer remote sensing spectral information.The optimal SOC prediction model integrated soil properties,topographic factors,location factors,and landscape metrics,as well as remote sensing-derived variables,and achieved RMSE and MAE of 15.05 and 11.42 g kg-1,and R2 and CCC of 0.57 and 0.72,respectively.The Shapley additive explanations deciphered the nonlinear and threshold effects that exist between soil moisture,vegetation status,soil brightness and SOC.Compared with traditional linear regression models,interpretable machine learning has advantages in prediction accuracy and revealing the influences of variables that reflect landscape characteristics on SOC.Overall,this study not only reveals how remote sensing-derived variables contribute to our understanding of SOC distribution in fragmented agricultural landscapes but also clarifies their efficacy.Through interpretable machine learning,we can further elucidate the causes of SOC variation,which is important for sustainable soil management and agricultural practices.展开更多
In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence...In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence,asymptotic behavior and blow-up of solutions with initial energy J(u_(0))≤d.Moreover,we estimate the upper bound of the blow-up time for J(u_(0))≤0.展开更多
The work presents new methods for selecting adaptive artificial viscosity(AAV)in iterative algorithms of completely conservative difference schemes(CCDS)used to solve gas dynamics equations in Euler variables.These me...The work presents new methods for selecting adaptive artificial viscosity(AAV)in iterative algorithms of completely conservative difference schemes(CCDS)used to solve gas dynamics equations in Euler variables.These methods allow to effectively suppress oscillations,including in velocity profiles,as well as computational instabilities in modeling gas-dynamic processes described by hyperbolic equations.The methods can be applied both in explicit and implicit(method of separate sweeps)iterative processes in numerical modeling of gas dynamics in the presence of heat and mass transfer,as well as in solving problems of magnetohydrodynamics and computational astrophysics.In order to avoid loss of solution accuracy on spatially non-uniform grids,in this work an algorithm of grid embeddings is developed,which is applied near transition points between cells of different sizes.The developed algorithms of CCDS using the methods for AAV selection and the algorithm of grid embeddings are implemented for various iterative processes.Calculations are performed for the classical problem of decay of an arbitrary discontinuity(Sod’s problem)and the problem of propagation of two symmetric rarefaction waves in opposite directions(Einfeldt’s problem).In the case of using different methods for selecting the AAV,a comparison of the solutions of the Sod’s problem on uniform and non-uniform grids and a comparison of the solutions of the Einfeldt’s problem on a uniform grid are performed.As a result of the comparative analysis,the applicability of these methods is shown in the spatially one-dimensional case(explicit and implicit iterative processes).The obtained results are compared with the data from the literature.The results coincide with analytical solutions with high accuracy,where the relative error does not exceed 0.1%,which demonstrates the effectiveness of the developed algorithms and methods.展开更多
We present 17 cataclysmic variables(CVs) obtained from the crossmatch between the Sloan Digital Sky Survey(SDSS) and eROSITA Final Equatorial Depth Survey(eFEDS),including eight known CVs before eFEDS and nine identif...We present 17 cataclysmic variables(CVs) obtained from the crossmatch between the Sloan Digital Sky Survey(SDSS) and eROSITA Final Equatorial Depth Survey(eFEDS),including eight known CVs before eFEDS and nine identified from eFEDS.The photometric periods of four CVs are derived from the Zwicky Transient Facility and Catalina Real-Time Transient Survey.We focus on two CVs,SDSS J084309.3-014858 and SDSS J093555.0+042916,and confirm that their photometric periods correspond to the orbital periods by fitting the radial velocity curves.Furthermore,by the combination of the Gaia distance,the spectral energy distribution,and the variations of Ha emission lines,the masses of the white dwarf and the visible star can be well constrained.展开更多
Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harve...Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harvesting performance,time-delayed feedback control is widely used in an energy-regenerative suspension system under different external disturbances in this paper.Meanwhile,limited research has addressed the stochastic dynamics of time-delayed nonlinear energy-regenerative suspension systems.Different from previous studies,this work studies the stochastic response and P-bifurcation of the nonlinear energy-regenerative suspension system with time-delayed feedback control.Firstly,an approximately equivalent dimension reduction system is established by the variable transformation method,and then the stationary probability density function of amplitude is obtained by the stochastic averaging method.Secondly,the precision of the method used in this work is verified by comparing the numerical solutions with the analytical results.Finally,based on the stationary probability density function,the influence of system parameters on stochastic P-bifurcation and the mean output power is discussed.展开更多
Existing rehabilitation exoskeleton robots suffer from poor compatibility with the human limb coupling method,large internal power loss,and poor wearable performance,which seriously affect the rehabilitation ability o...Existing rehabilitation exoskeleton robots suffer from poor compatibility with the human limb coupling method,large internal power loss,and poor wearable performance,which seriously affect the rehabilitation ability of these robots.Therefore,this study proposes a variable stiffness humancomputer interaction contact unit module(VSHCUM)based on the granular jamming mechanism.It is characterized by a double-layer chamber structure:the inner layer is a granular chamber,and the outer layer is an air chamber.The interaction force is transmitted by embedding a rigid support in the inner layer.Unlike the common flexible-belt interactive contact unit,when the exoskeleton is bound to the patient's limb,vSHCUM can realize adaptive fitting of the patient's limb shape using the pressure change in the double-chamber structure.Simultaneously,by adjusting the vacuum level of the granular chamber,the stiffness of the interactive contact unit can be adjusted by a factor of more than five,and the internal work loss caused by self-pulling deformation during the auxiliary force transfer process can be reduced.展开更多
Thermal-mechanical damage and deformation at the interface between shotcrete linings and the surrounding rock of tunnels under high-temperature and variable-temperature conditions are critical to the safe construction...Thermal-mechanical damage and deformation at the interface between shotcrete linings and the surrounding rock of tunnels under high-temperature and variable-temperature conditions are critical to the safe construction and operation of tunnel engineering.This study investigated the thermo-mechanical damage behavior of the composite interface between alkali-resistant glass fiber-reinforced concrete(ARGFRC)and granite,focusing on a plateau railway tunnel.Laboratory triaxial tests,laser scanning,XRD analysis,numerical simulations,and theoretical analyses were employed to investigate how different initial curing temperatures and joint roughness coefficient(JRC)influence interfacial damage behavior.The results indicate that an increase in interface roughness exacerbates the structural damage at the interface.At a JRC of 19.9 and a temperature of 70℃,crack initiation in granite was notably restrained when the confining pressure rose from 7 MPa to 10 MPa.Roughness-induced stress distribution at the interface was notably altered,although this effect became less pronounced under high confining pressure conditions.Additionally,during high-temperature curing,thermal stress concentration at the tips of micro-convex protrusions on the granite surface induced microcracks in the adjacent ARGFRC matrix,followed by deformation.These findings provide practical guidelines for designing concrete support systems to ensure tunnel structural safety in high-altitude regions with harsh thermal environments.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
文摘In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.
基金supported by the Key Program of National Natural Science Foundation of China(Grant No.41930650)Young Scientists Fund of the National Natural Science Foundation of China(Grant No.42301310).
文摘Sustained and spatially explicit monitoring of the United Nations 2030 Agenda for Sustainable Development is critical for effectively tracking progress toward the global Sustainable Development Goals(SDGs).Although land cover information has long been recognized as an essential component for monitoring SDGs,a standardized scientific framework for identifying and prioritizing land cover related essential variables does not exist.Therefore,we propose a novel expert-and data-driven framework for identifying,refining,and selecting a priority list of Essential Land cover-related Variables for SDGs(ELcV4SDGs).This framework integrates methods including expert knowledge-based analysis,clustering of variables with similar attributes,and quantified index calculation to establish the priority list.Applying the framework to 15 specific SDG indicators,we found that the ELcV4SDGs priority list comprises three main categories,type and structure,pattern and intensity,and process and evolution of land cover,which are further divided into 19 subcategories and ultimately encompass 50 general variables.The ELcV4SDGs will support detailed spatial monitoring and enhance their scientific applications for SDG monitoring and assessment,thereby guiding future SDG priority actions and informing decision-making to advance the 2030 SDGs agenda at local,national,and global levels.
文摘In this correspondence paper, an equivalent stability criterion with minimal number of linear matrix inequality （LMI） variables is presented for a delay-dependent stability criterion reported recently in the International Journal of Automation and Computing for a class of linear discrete-time systems with additive time delays. The reported stability criterion for the additive timedelay systems has more number of matrix variables in the LMI and, hence, demand additional computational burden. The proposed equivalent stability criterion, unlike the reported one, does not involve free-weighing matrices and encompass only the matrix variables that are associated in the Lyapunov-Krasovskii functional, making the criterion mathematically less complex and computationally more effective.
基金supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
文摘Cold seeps are oases for biological communities on the sea floor around hydrocarbon emission pathways.Microbial utilization of methane and other hydrocarbons yield products that fuel rich chemosynthetic communities at these sites.One such site in the cold seep ecosystem of Krishna-Godavari basin(K-G basin)along the east coast of India,discovered in Feb 2018 at a depth of 1800 m was assessed for its bacterial diversity.The seep bacterial communities were dominated by phylum Proteobacteria(57%),Firmicutes(16%)and unclassified species belonging to the family Helicobacteriaceae.The surface sediments of the seep had maximum OTUs(operational taxonomic units)(2.27×10^(3))with a Shannon alpha diversity index of 8.06.In general,environmental parameters like total organic carbon(p<0.01),sulfate(p<0.001),sulfide(p<0.05)and methane(p<0.01)were responsible for shaping the bacterial community of the cold seep ecosystem in the K-G Basin.Environmental parameters play a significant role in changing the bacterial diversity richness between different cold seep environments in the oceans.
基金supported in part by the National Natural Science Foundation of China(U23A20340,62176238,62476254,62106230)the Key Research and Development Projects of the Ministry of Science and Technology of China(2022YFD2001200)+3 种基金the Natural Science Foundation Project of Henan Province(242300420277)the Key Research and Development Program of Henan(251111113900)the Frontier Exploration Projects of Longmen Laboratory(LMQYTSKT031)Chongqing University of Posts and Telecommunications Key Laboratory of Big Data Open Fund Project(BDIC-2023-B-005).
文摘Solving constrained multi-objective optimization problems(CMOPs)is a challenging task due to the presence of multiple conflicting objectives and intricate constraints.In order to better address CMOPs and achieve a balance between objectives and constraints,existing constrained multi-objective evolutionary algorithms(CMOEAs)predominantly focus on devising various strategies by leveraging the relationships between objectives and constraints,and the designed strategies usually are effective for the problems with simple constraints.However,these methods most ignore the relationship between decision variables and constraints.In fact,the essence of optimization is to find appropriate decision variables to meet various complex constraints.Therefore,it is hoped that the problem can be analyzed from the perspective of decision variables,so as to obtain more excellent results.Based on the above motivation,this paper proposes a decision variables classification approach,according to the relationship between decision variables and constraints,variables are divided into constraint-related(CR)variables and constraintindependent(CI)variables.Consequently,by optimizing these two types of variables independently,the population can sustain a favorable balance between feasibility and diversity.Furthermore,specific offspring generation strategies are proposed for the two categories of decision variables in order to achieve rapid convergence while maintaining population diversity.Experimental results on 31 test problems as well as 20 real-world problems demonstrate that the proposed algorithm is competitive compared to some state-of-the-art constrained multi-objective optimization algorithms.
基金Supported by Natural Science Research Project for Colleges and Universities of Anhui Province(Grant No.2022AH050329)Yunnan Provincial Department of Education Fund(Grant No.2025J0376).
文摘In this paper,we establish characterizations of α-Bloch functions and little α-Bloch functions on the unit ball as well as the unit polydisk of C^(m),which generalize and improve results of Aulaskari-Lappan,Minda,Aulaskari-Wulan,and Wu.Some examples are also given to complement our theory.
基金supported by the National Natural Science Foundation of China(11102078 and 11032009)Foundation of Jiangxi Education Committee of China(GJJ1169)
文摘Time-delay effects on the dynamics of Li^nard type equation with one fast variable and one slow variable are investigated in the present paper. By using the methods of stability switch and geometric singular perturbation, time-delay-induced complex oscillations and bursting are investigated, and in several case studies, the mechanism of the generation of the complex oscillations and bursting is illuminated. Numerical results demonstrate the validity of the theoretical results.
基金Supported by the Academic Achievement Re-cultivation Projects of Jingdezhen Ceramic University(Grant Nos.215/20506341215/20506277)the Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)。
文摘Assume that{a_(i),−∞<i<∞}is an absolutely summable sequence of real numbers.We establish the complete q-order moment convergence for the partial sums of moving average processes{X_(n)=Σ_(i=−∞)^(∞)a_(i)Y_(i+n),n≥1}under some proper conditions,where{Yi,-∞<i<∞}is a doubly infinite sequence of negatively dependent random variables under sub-linear expectations.These results extend and complement the relevant results in probability space.
基金Supported by the Academic Funding Projects for Top Talents in Universities of Anhui Province(gxbjZD2022067)Talent Planning Project of Tongling University(2022tlxyrc32)the Key Grant Project for Academic Leaders of Tongling University(2020tlxyxs31)。
文摘In this paper,the author obtains complete convergence for the maximum partial sums of m-widely orthant dependent(m-WOD)random variables sequences under some general conditions.The results extend the complete convergence for m-WOD random variables to a much more general type complete convergence.As the sequences of m-WOD random variables represent a very broad class of dependent sequences,the results improve and generalize the corresponding ones in the literature.
基金supported by the National Key Research and Development Program of China(2022YFB3903302).
文摘Accurately mapping the spatial distribution of soil organic carbon(SOC)is crucial for guiding agricultural management and improving soil carbon sequestration,especially in fragmented agricultural landscapes.Although remote sensing provides spatially continuous environmental information about heterogeneous agricultural landscapes,its relationship with SOC remains unclear.In this study,we hypothesized that multi-category remote sensing-derived variables can enhance our understanding of SOC variation within complex landscape conditions.Taking the Qilu Lake watershed in Yunnan,China,as a case study area and based on 216 topsoil samples collected from irrigation areas,we applied the extreme gradient boosting(XGBoost)model to investigate the contributions of vegetation indices(VI),brightness indices(BI),moisture indices(MI),and spectral transformations(ST,principal component analysis and tasseled cap transformation)to SOC mapping.The results showed that ST contributed the most to SOC prediction accuracy,followed by MI,VI,and BI,with improvements in R2 of 29.27,26.83,19.51,and 14.43%,respectively.The dominance of ST can be attributed to the fact that it contains richer remote sensing spectral information.The optimal SOC prediction model integrated soil properties,topographic factors,location factors,and landscape metrics,as well as remote sensing-derived variables,and achieved RMSE and MAE of 15.05 and 11.42 g kg-1,and R2 and CCC of 0.57 and 0.72,respectively.The Shapley additive explanations deciphered the nonlinear and threshold effects that exist between soil moisture,vegetation status,soil brightness and SOC.Compared with traditional linear regression models,interpretable machine learning has advantages in prediction accuracy and revealing the influences of variables that reflect landscape characteristics on SOC.Overall,this study not only reveals how remote sensing-derived variables contribute to our understanding of SOC distribution in fragmented agricultural landscapes but also clarifies their efficacy.Through interpretable machine learning,we can further elucidate the causes of SOC variation,which is important for sustainable soil management and agricultural practices.
基金Supported by NSFC(No.12101482)the Natural Science Foundation of Shaanxi Province,China(No.2018JQ1052)。
文摘In this paper,we consider the fourth-order parabolic equation with p(x)Laplacian and variable exponent source ut+∆^(2)u−div(|■u|^(p(x)−2■u))=|u|^(q(x))−1u.By applying potential well method,we obtain global existence,asymptotic behavior and blow-up of solutions with initial energy J(u_(0))≤d.Moreover,we estimate the upper bound of the blow-up time for J(u_(0))≤0.
基金carried out within the framework of the state assignment of KIAM RAS(No.125020701776-0).
文摘The work presents new methods for selecting adaptive artificial viscosity(AAV)in iterative algorithms of completely conservative difference schemes(CCDS)used to solve gas dynamics equations in Euler variables.These methods allow to effectively suppress oscillations,including in velocity profiles,as well as computational instabilities in modeling gas-dynamic processes described by hyperbolic equations.The methods can be applied both in explicit and implicit(method of separate sweeps)iterative processes in numerical modeling of gas dynamics in the presence of heat and mass transfer,as well as in solving problems of magnetohydrodynamics and computational astrophysics.In order to avoid loss of solution accuracy on spatially non-uniform grids,in this work an algorithm of grid embeddings is developed,which is applied near transition points between cells of different sizes.The developed algorithms of CCDS using the methods for AAV selection and the algorithm of grid embeddings are implemented for various iterative processes.Calculations are performed for the classical problem of decay of an arbitrary discontinuity(Sod’s problem)and the problem of propagation of two symmetric rarefaction waves in opposite directions(Einfeldt’s problem).In the case of using different methods for selecting the AAV,a comparison of the solutions of the Sod’s problem on uniform and non-uniform grids and a comparison of the solutions of the Einfeldt’s problem on a uniform grid are performed.As a result of the comparative analysis,the applicability of these methods is shown in the spatially one-dimensional case(explicit and implicit iterative processes).The obtained results are compared with the data from the literature.The results coincide with analytical solutions with high accuracy,where the relative error does not exceed 0.1%,which demonstrates the effectiveness of the developed algorithms and methods.
基金supported by the National Key R&D Program of China under grants 2023YFA1607901 and 2021YFA1600401the National Natural Science Foundation of China under grants 12433007, 11925301, 12033006, 12221003, and 12263003+1 种基金the fellowship of China National Postdoctoral Program for Innovation Talents under grant BX20230020the science research grants from the China Manned Space Project with No. CMS-CSST-2025-A13。
文摘We present 17 cataclysmic variables(CVs) obtained from the crossmatch between the Sloan Digital Sky Survey(SDSS) and eROSITA Final Equatorial Depth Survey(eFEDS),including eight known CVs before eFEDS and nine identified from eFEDS.The photometric periods of four CVs are derived from the Zwicky Transient Facility and Catalina Real-Time Transient Survey.We focus on two CVs,SDSS J084309.3-014858 and SDSS J093555.0+042916,and confirm that their photometric periods correspond to the orbital periods by fitting the radial velocity curves.Furthermore,by the combination of the Gaia distance,the spectral energy distribution,and the variations of Ha emission lines,the masses of the white dwarf and the visible star can be well constrained.
基金Project supported by the National Natural Science Foundation of China(Grant No.12002089)the Science and Technology Projects in Guangzhou(Grant No.2023A04J1323)UKRI Horizon Europe Guarantee(Marie SklodowskaCurie Fellowship)(Grant No.EP/Y016130/1)。
文摘Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harvesting performance,time-delayed feedback control is widely used in an energy-regenerative suspension system under different external disturbances in this paper.Meanwhile,limited research has addressed the stochastic dynamics of time-delayed nonlinear energy-regenerative suspension systems.Different from previous studies,this work studies the stochastic response and P-bifurcation of the nonlinear energy-regenerative suspension system with time-delayed feedback control.Firstly,an approximately equivalent dimension reduction system is established by the variable transformation method,and then the stationary probability density function of amplitude is obtained by the stochastic averaging method.Secondly,the precision of the method used in this work is verified by comparing the numerical solutions with the analytical results.Finally,based on the stationary probability density function,the influence of system parameters on stochastic P-bifurcation and the mean output power is discussed.
基金Supported by National Key R&D Program of China(Grant Nos.2022YFC3601704,2023YFB4706100)National Natural Science Foundation of China(Grant Nos.U23A20338,62203149).
文摘Existing rehabilitation exoskeleton robots suffer from poor compatibility with the human limb coupling method,large internal power loss,and poor wearable performance,which seriously affect the rehabilitation ability of these robots.Therefore,this study proposes a variable stiffness humancomputer interaction contact unit module(VSHCUM)based on the granular jamming mechanism.It is characterized by a double-layer chamber structure:the inner layer is a granular chamber,and the outer layer is an air chamber.The interaction force is transmitted by embedding a rigid support in the inner layer.Unlike the common flexible-belt interactive contact unit,when the exoskeleton is bound to the patient's limb,vSHCUM can realize adaptive fitting of the patient's limb shape using the pressure change in the double-chamber structure.Simultaneously,by adjusting the vacuum level of the granular chamber,the stiffness of the interactive contact unit can be adjusted by a factor of more than five,and the internal work loss caused by self-pulling deformation during the auxiliary force transfer process can be reduced.
基金funded by the National Natural Science Foundation of China(Nos.52209130 and 52379100)Shandong Provincial Natural Science Foundation(No.ZR2024ME112).
文摘Thermal-mechanical damage and deformation at the interface between shotcrete linings and the surrounding rock of tunnels under high-temperature and variable-temperature conditions are critical to the safe construction and operation of tunnel engineering.This study investigated the thermo-mechanical damage behavior of the composite interface between alkali-resistant glass fiber-reinforced concrete(ARGFRC)and granite,focusing on a plateau railway tunnel.Laboratory triaxial tests,laser scanning,XRD analysis,numerical simulations,and theoretical analyses were employed to investigate how different initial curing temperatures and joint roughness coefficient(JRC)influence interfacial damage behavior.The results indicate that an increase in interface roughness exacerbates the structural damage at the interface.At a JRC of 19.9 and a temperature of 70℃,crack initiation in granite was notably restrained when the confining pressure rose from 7 MPa to 10 MPa.Roughness-induced stress distribution at the interface was notably altered,although this effect became less pronounced under high confining pressure conditions.Additionally,during high-temperature curing,thermal stress concentration at the tips of micro-convex protrusions on the granite surface induced microcracks in the adjacent ARGFRC matrix,followed by deformation.These findings provide practical guidelines for designing concrete support systems to ensure tunnel structural safety in high-altitude regions with harsh thermal environments.
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.
