Nematodes play an important role in ecosystems;however,very little is known about their assembly processes and the factors influencing them.We studied nematode communities in bulk soils from three Asian mountain ecosy...Nematodes play an important role in ecosystems;however,very little is known about their assembly processes and the factors influencing them.We studied nematode communities in bulk soils from three Asian mountain ecosystems to determine the assembly processes of free-living nematode metacommunities and their driving factors.On each mountain,elevations span a range of climatic conditions with the potential to reveal assembly processes that predominate across multiple biomes.A phylogenetic null modeling framework was used to analyze 18S rRNA gene amplicons to quantify various assembly processes.We found that phylogenetic turnover between nematode communities on all mountains was dominated by stochastic processes,with“undominated processes”being the most predominant stochastic factor.Elevation has a significant impact on the relative importance of deterministic and stochastic processes.A variety of climatic and edaphic variables significantly influenced the variations in community assembly processes with elevation,even though their impacts were not consistent between the mountains.Overall,our results indicate that free-living nematode metacommunities in a wide range of environments are largely structured by stochastic processes rather than by niche-based deterministic processes,suggesting that metacommunities of soil free-living nematodes may respond to climate change in a largely unpredictable way.展开更多
We report stochastic simulations of the yeast mating signal transduction pathway. The effects of intrinsic and external noise, the influence of cell-to-cell difference in the pathway capacity, and noise propagation in...We report stochastic simulations of the yeast mating signal transduction pathway. The effects of intrinsic and external noise, the influence of cell-to-cell difference in the pathway capacity, and noise propagation in the pathway have been examined. The stochastic temporal behaviour of the pathway is found to be robust to the influence of inherent fluctuations, and intrinsic noise propagates in the pathway in a uniform pattern when the yeasts are treated with pheromones of different stimulus strengths and of varied fluctuations. In agreement with recent experimental findings, extrinsic noise is found to play a more prominent role than intrinsic noise in the variability of proteins. The occurrence frequency for the reactions in the pathway are also examined and a more compact network is obtained by dropping most of the reactions of least occurrence.展开更多
This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic diff...This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic differential equations.Then we obtain a comparison theorem in one-dimensional situation.展开更多
Living cells are open systems that exist far away from a state of thermodynamical equilibrium. They utilize the high-grade chemical energy provided by food to produce ATP and re- lease ADP and Pi together with heat di...Living cells are open systems that exist far away from a state of thermodynamical equilibrium. They utilize the high-grade chemical energy provided by food to produce ATP and re- lease ADP and Pi together with heat dissipation. Living cells exist in a non-equilibrium steady state （NESS）, they replicate themselves and respond to various environmental changes via signal transduction pathways. Because the majority of cells exist at room temperature, the stochasticity of chemical reac- tions in the cells is unavoidable. Recent research into fluores- cent proteins and microscopy techniques have enabled us to observe the dynamic process of mRNA and proteins in single living bacterial cells [1], and these have resulted in new in- sights into regulation mechanisms in molecular biology, i.e., in cellular signal transduction pathways.展开更多
In this paper,we investigate a two-dimensional avian influenza model with Allee effect and stochasticity.We first show that a unique global positive solution always exists to the stochastic system for any positive ini...In this paper,we investigate a two-dimensional avian influenza model with Allee effect and stochasticity.We first show that a unique global positive solution always exists to the stochastic system for any positive initial value.Then,under certain conditions,this solution is proved to be stochastically ultimately bounded.Furthermore,by constructing a suitable Lyapunov function,we obtain sufficient conditions for the existence of stationary distribution with ergodicity.The conditions for the extinction of infected avian population are also analytically studied.These theoretical results are conformed by computational simulations.We numerically show that the environmental noise can bring different dynamical outcomes to the stochastic model.By scanning different noise intensities,we observe that large noise can cause extinction of infected avian population,which suggests the repression of noise on the spread of avian virus.展开更多
Backgrounds In this work, we study two seemingly unrelated aspects of core genetic nonlinear dynamical control of the competence phenotype in Bacillus subtilis, a common Gram-positive bacterium living in the soil. Met...Backgrounds In this work, we study two seemingly unrelated aspects of core genetic nonlinear dynamical control of the competence phenotype in Bacillus subtilis, a common Gram-positive bacterium living in the soil. Methods: We focus on hitherto unchartered aspects of the dynamics by exploring the effect of time-scale separation between transcription and translation and, as well, the effect of intrinsic molecular stochasticity. We consider these aspects of regulatory control as two possible evolutionary handles. Results: Hence, using theory and computations, we study how the onset of oscillations breaks the excitability-based competence phenotype in two topologically close evolutionary-competing circuits: the canonical "wild-type" regulation circuit selected by Evolution and the corresponding indirect-feedback inverted circuit that failed to be selected by Evolution, as was shown elsewhere, due to dynamical reasons. Conclusions^ Relying on in-silico perturbation of the living state, we show that the canonical core genetic regulation of excitability-based competence is more robust against switching to phenotype-breaking oscillations than the inverted feedback organism. We show how this is due to time-scale separation and stochasticity.展开更多
Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality ...Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions.While heuristic optimization algorithms vary in their specific details,they often exhibit common patterns that are essential to their effectiveness.This paper aims to analyze and explore common patterns in heuristic optimization algorithms.Through a comprehensive review of the literature,we identify the patterns that are commonly observed in these algorithms,including initialization,local search,diversity maintenance,adaptation,and stochasticity.For each pattern,we describe the motivation behind it,its implementation,and its impact on the search process.To demonstrate the utility of our analysis,we identify these patterns in multiple heuristic optimization algorithms.For each case study,we analyze how the patterns are implemented in the algorithm and how they contribute to its performance.Through these case studies,we show how our analysis can be used to understand the behavior of heuristic optimization algorithms and guide the design of new algorithms.Our analysis reveals that patterns in heuristic optimization algorithms are essential to their effectiveness.By understanding and incorporating these patterns into the design of new algorithms,researchers can develop more efficient and effective optimization algorithms.展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan ...Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.展开更多
BACKGROUND Acute appendicitis(AAp)is a prevalent medical condition characterized by inflammation of the appendix that frequently necessitates urgent surgical procedures.Approximately two-thirds of patients with AAp ex...BACKGROUND Acute appendicitis(AAp)is a prevalent medical condition characterized by inflammation of the appendix that frequently necessitates urgent surgical procedures.Approximately two-thirds of patients with AAp exhibit characteristic signs and symptoms;hence,negative AAp and complicated AAp are the primary concerns in research on AAp.In other terms,further investigations and algorithms are required for at least one third of patients to predict the clinical condition and distinguish them from uncomplicated patients with AAp.AIM To use a Stochastic Gradient Boosting(SGB)-based machine learning(ML)algorithm to tell the difference between AAp patients who are complicated and those who are not,and to find some important biomarkers for both types of AAp by using modeling to get variable importance values.METHODS This study analyzed an open access data set containing 140 people,including 41 healthy controls,65 individuals with uncomplicated AAp,and 34 individuals with complicated AAp.We analyzed some demographic data(age,sex)of the patients and the following biochemical blood parameters:White blood cell(WBC)count,neutrophils,lymphocytes,monocytes,platelet count,neutrophil-tolymphocyte ratio,lymphocyte-to-monocyte ratio,mean platelet volume,neutrophil-to-immature granulocyte ratio,ferritin,total bilirubin,immature granulocyte count,immature granulocyte percent,and neutrophil-to-immature granulocyte ratio.We tested the SGB model using n-fold cross-validation.It was implemented with an 80-20 training-test split.We used variable importance values to identify the variables that were most effective on the target.RESULTS The SGB model demonstrated excellent performance in distinguishing AAp from control patients with an accuracy of 96.3%,a micro aera under the curve(AUC)of 94.7%,a sensitivity of 94.7%,and a specificity of 100%.In distinguishing complicated AAp patients from uncomplicated ones,the model achieved an accuracy of 78.9%,a micro AUC of 79%,a sensitivity of 83.3%,and a specificity of 76.9%.The most useful biomarkers for confirming the AA diagnosis were WBC(100%),neutrophils(95.14%),and the lymphocyte-monocyte ratio(76.05%).On the other hand,the most useful biomarkers for accurate diagnosis of complicated AAp were total bilirubin(100%),WBC(96.90%),and the neutrophil-immature granulocytes ratio(64.05%).CONCLUSION The SGB model achieved high accuracy rates in identifying AAp patients while it showed moderate performance in distinguishing complicated AAp patients from uncomplicated AAp patients.Although the model's accuracy in the classification of complicated AAp is moderate,the high variable importance obtained is clinically significant.We need further prospective validation studies,but the integration of such ML algorithms into clinical practice may improve diagnostic processes.展开更多
Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution mismatch.However,current copy-paste methods have three limitations:(1)t...Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution mismatch.However,current copy-paste methods have three limitations:(1)training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information;(2)low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data;(3)the segmentation performance in low-contrast and local regions is less than optimal.We design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy(SADT),which enhances feature diversity and learns high-quality features to overcome these problems.To be more precise,SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data,which prevents the loss of rare labeled data.We introduce a bi-directional copy-pastemask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in pseudo-supervision.For the mixed images,Deep-Shallow Spatial Contrastive Learning(DSSCL)is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local areas.In this procedure,the features retrieved by the Student Network are subjected to a random feature perturbation technique.On two openly available datasets,extensive trials show that our proposed SADT performs much better than the state-ofthe-art semi-supervised medical segmentation techniques.Using only 10%of the labeled data for training,SADT was able to acquire a Dice score of 90.10%on the ACDC(Automatic Cardiac Diagnosis Challenge)dataset.展开更多
The article studies the evolutionary dynamics of two-population two-strategy game models with and without impulses. First, the payment matrix is given and two evolutionary dynamics models are established by adding sto...The article studies the evolutionary dynamics of two-population two-strategy game models with and without impulses. First, the payment matrix is given and two evolutionary dynamics models are established by adding stochastic and impulse. For the stochastic model without impulses, the existence and uniqueness of solution, and the existence of positive periodic solutions are proved, and a sufficient condition for strategy extinction is given. For the stochastic model with impulses, the existence of positive periodic solutions is proved. Numerical results show that noise and impulses directly affect the model, but the periodicity of the model does not change.展开更多
Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical...Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical guarantees.In this pa-per,we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics.We consider several risk metrics and study decision models that involve the metrics,with a main focus on the related com-puting techniques and theoretical properties.We show that stochastic optimization,as a powerful tool,can be leveraged to effectively address these problems.展开更多
A stochastic stage-structure predator-prey system with impulsive effect is investigated.First,we build the corresponding system without impulse in order to demonstrate the existence and uniqueness of the global positi...A stochastic stage-structure predator-prey system with impulsive effect is investigated.First,we build the corresponding system without impulse in order to demonstrate the existence and uniqueness of the global positive solution.Second,by selecting an appropriate Lyapunov function,we provide the sufficient condition for the existence of a positive T-periodic solution.Finally,numerical simulations illustrate our theoretical results,which show that the impulse or the white noises can result in the extinction of the predator in a certain condition.展开更多
In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained f...In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.展开更多
This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field.We show that the approximation holds for the drift-implicit Euler–M...This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field.We show that the approximation holds for the drift-implicit Euler–Maruyama discretization and derive its convergence rate.In particular,the solution of the discretized system converges to the solution of the first-order limit equation in the mean-square sense,and this convergence is independent of the order in which the mass parameterμand the step size h tend to zero.展开更多
The two-player nonzero-sum linear-exponential-quadratic stochastic differential game is studied.The game takes into account the players'attitudes to risk.The nonlinear transformations and change of probability mea...The two-player nonzero-sum linear-exponential-quadratic stochastic differential game is studied.The game takes into account the players'attitudes to risk.The nonlinear transformations and change of probability measure techniques are used to study the existence of both open-loop and closed-loop Nash equilibria for the game.Some examples are constructed to illustrate their differences.Furthermore,theoretical results are applied to solve the risk-sensitive portfolio game problem in the financial market and show the effects of risk attitudes and economic performance on equilibria.展开更多
In this paper we study the Freidlin-Wentzell's large deviation principle for the following nonlinear fractional stochastic heat equation driven by Gaussian noise∂/∂tu^(ε)=D_(δ)^(α)(t,x)+√εσ(u^(ε)(t,x))W(t,x...In this paper we study the Freidlin-Wentzell's large deviation principle for the following nonlinear fractional stochastic heat equation driven by Gaussian noise∂/∂tu^(ε)=D_(δ)^(α)(t,x)+√εσ(u^(ε)(t,x))W(t,x),(t,x)∈[0,T]×R,where D_(δ)^(α)is a nonlocal fractional differential operator and W is the Gaussian noise which is white in time and behaves as a fractional Brownian motion with Hurst index H satisfying 3-α/4<H<1/2,in the space variable.The weak convergence approach plays an important role.展开更多
In this paper,we prove the transportation cost-information inequalities on the space of continuous paths with respect to the L~2-metric and the uniform metric for the law of the mild solution to the stochastic heat eq...In this paper,we prove the transportation cost-information inequalities on the space of continuous paths with respect to the L~2-metric and the uniform metric for the law of the mild solution to the stochastic heat equation defined on[0,T]×[0,1]driven by double-parameter fractional noise.展开更多
Prediction of water inflow into a tunnel is a crucial prerequisite for the waterproof and drainage design of mountain tunnels in water-rich areas.Based on the proposed Baiyun Mountain Tunnel project in Guangzhou,a num...Prediction of water inflow into a tunnel is a crucial prerequisite for the waterproof and drainage design of mountain tunnels in water-rich areas.Based on the proposed Baiyun Mountain Tunnel project in Guangzhou,a numerical percolation model of random fractured rock of a tunnel underpassing a water reservoir is established to study the seepage characteristics of surrounding rock,the law of water inflow,and the change of lining water pressure,considering the local artificial boundary conditions for seepage in large rock mass,.In addition,the influences of rock permeability,fracture aperture,grouting circle thickness,and penetration are analyzed.The results show that:(1)Only fractures with aperture wider than 0.1 mm can play a significant role in water conduction in rocks with the permeability lower than 10^(-11)m^(2);(2)The greater the permeability difference between the fractures and rocks,the more remarkable the effects of fractures on the surrounding rock seepage field and cavern water inflow;(3)The sensitivity of grouting waterproof function to grouting circle thickness,grouting ring penetration,and rock permeability is significantly higher than that of tunnel buried depth and fracture aperture;(4)The lining water head is much more sensitive to the grouting circle thickness and penetration than to the tunnel buried depth;(5)With the grouting range enlarging,the impact of grouting circle permeability on the precipitation pressure role of the grouting ring increases;(6)For the interesting tunnel designed to be built at the depth of 70 m,the grouting circle with the thickness of 0.5 m and permeability of 10-^(14)m^(2)is recommended.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(No.NRF-2018R1C1B6007755)supported by a grant(No.20SCIPC158976-01)from the Construction Technology Research Program funded by the Ministry of Land,Infrastructure,and Transport of the Korean government+2 种基金the Natural Science Foundation of Guangxi,China(No.2018GXNSFDA 281006)the National Natural Science Foundation of China(No.41966005)the One Hundred Talents Project of Guangxi,China(No.6020303891251)。
文摘Nematodes play an important role in ecosystems;however,very little is known about their assembly processes and the factors influencing them.We studied nematode communities in bulk soils from three Asian mountain ecosystems to determine the assembly processes of free-living nematode metacommunities and their driving factors.On each mountain,elevations span a range of climatic conditions with the potential to reveal assembly processes that predominate across multiple biomes.A phylogenetic null modeling framework was used to analyze 18S rRNA gene amplicons to quantify various assembly processes.We found that phylogenetic turnover between nematode communities on all mountains was dominated by stochastic processes,with“undominated processes”being the most predominant stochastic factor.Elevation has a significant impact on the relative importance of deterministic and stochastic processes.A variety of climatic and edaphic variables significantly influenced the variations in community assembly processes with elevation,even though their impacts were not consistent between the mountains.Overall,our results indicate that free-living nematode metacommunities in a wide range of environments are largely structured by stochastic processes rather than by niche-based deterministic processes,suggesting that metacommunities of soil free-living nematodes may respond to climate change in a largely unpredictable way.
基金supported by the National Natural Science Foundation of China(Grant No 10774008)National Key Basic Research Program of China(Grant Nos 2007CB814800 and 2006CB910706)the support of the National Funds for Fostering Talents in Basic Science of China(Grant No J0630311)
文摘We report stochastic simulations of the yeast mating signal transduction pathway. The effects of intrinsic and external noise, the influence of cell-to-cell difference in the pathway capacity, and noise propagation in the pathway have been examined. The stochastic temporal behaviour of the pathway is found to be robust to the influence of inherent fluctuations, and intrinsic noise propagates in the pathway in a uniform pattern when the yeasts are treated with pheromones of different stimulus strengths and of varied fluctuations. In agreement with recent experimental findings, extrinsic noise is found to play a more prominent role than intrinsic noise in the variability of proteins. The occurrence frequency for the reactions in the pathway are also examined and a more compact network is obtained by dropping most of the reactions of least occurrence.
基金Supported by the National Natural Science Foundation of China(12001074)the Research Innovation Program of Graduate Students in Hunan Province(CX20220258)+1 种基金the Research Innovation Program of Graduate Students of Central South University(1053320214147)the Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110025)。
文摘This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic differential equations.Then we obtain a comparison theorem in one-dimensional situation.
基金supported by the National Natural Science Foundation of China(Grant Nos.11174011,and 91130005)the National Key Basic Research Project of China(Grant No.2015CB910300)
文摘Living cells are open systems that exist far away from a state of thermodynamical equilibrium. They utilize the high-grade chemical energy provided by food to produce ATP and re- lease ADP and Pi together with heat dissipation. Living cells exist in a non-equilibrium steady state （NESS）, they replicate themselves and respond to various environmental changes via signal transduction pathways. Because the majority of cells exist at room temperature, the stochasticity of chemical reac- tions in the cells is unavoidable. Recent research into fluores- cent proteins and microscopy techniques have enabled us to observe the dynamic process of mRNA and proteins in single living bacterial cells [1], and these have resulted in new in- sights into regulation mechanisms in molecular biology, i.e., in cellular signal transduction pathways.
基金This study is supported by the National Key Research and Development Program of China(2018YFA0801103)the National Natural Science Foundation of China(Grant No.12071330 to Ling Yang,Grant No.11701405 to Jie Yan).
文摘In this paper,we investigate a two-dimensional avian influenza model with Allee effect and stochasticity.We first show that a unique global positive solution always exists to the stochastic system for any positive initial value.Then,under certain conditions,this solution is proved to be stochastically ultimately bounded.Furthermore,by constructing a suitable Lyapunov function,we obtain sufficient conditions for the existence of stationary distribution with ergodicity.The conditions for the extinction of infected avian population are also analytically studied.These theoretical results are conformed by computational simulations.We numerically show that the environmental noise can bring different dynamical outcomes to the stochastic model.By scanning different noise intensities,we observe that large noise can cause extinction of infected avian population,which suggests the repression of noise on the spread of avian virus.
文摘Backgrounds In this work, we study two seemingly unrelated aspects of core genetic nonlinear dynamical control of the competence phenotype in Bacillus subtilis, a common Gram-positive bacterium living in the soil. Methods: We focus on hitherto unchartered aspects of the dynamics by exploring the effect of time-scale separation between transcription and translation and, as well, the effect of intrinsic molecular stochasticity. We consider these aspects of regulatory control as two possible evolutionary handles. Results: Hence, using theory and computations, we study how the onset of oscillations breaks the excitability-based competence phenotype in two topologically close evolutionary-competing circuits: the canonical "wild-type" regulation circuit selected by Evolution and the corresponding indirect-feedback inverted circuit that failed to be selected by Evolution, as was shown elsewhere, due to dynamical reasons. Conclusions^ Relying on in-silico perturbation of the living state, we show that the canonical core genetic regulation of excitability-based competence is more robust against switching to phenotype-breaking oscillations than the inverted feedback organism. We show how this is due to time-scale separation and stochasticity.
文摘Heuristic optimization algorithms have been widely used in solving complex optimization problems in various fields such as engineering,economics,and computer science.These algorithms are designed to find high-quality solutions efficiently by balancing exploration of the search space and exploitation of promising solutions.While heuristic optimization algorithms vary in their specific details,they often exhibit common patterns that are essential to their effectiveness.This paper aims to analyze and explore common patterns in heuristic optimization algorithms.Through a comprehensive review of the literature,we identify the patterns that are commonly observed in these algorithms,including initialization,local search,diversity maintenance,adaptation,and stochasticity.For each pattern,we describe the motivation behind it,its implementation,and its impact on the search process.To demonstrate the utility of our analysis,we identify these patterns in multiple heuristic optimization algorithms.For each case study,we analyze how the patterns are implemented in the algorithm and how they contribute to its performance.Through these case studies,we show how our analysis can be used to understand the behavior of heuristic optimization algorithms and guide the design of new algorithms.Our analysis reveals that patterns in heuristic optimization algorithms are essential to their effectiveness.By understanding and incorporating these patterns into the design of new algorithms,researchers can develop more efficient and effective optimization algorithms.
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
基金supported in part by the High-tech ship scientific research project of the Ministry of Industry and Information Technology of the People’s Republic of China,and the National Nature Science Foundation of China(Grant No.71671113)the Science and Technology Department of Shaanxi Province(No.2020GY-219)the Ministry of Education Collaborative Project of Production,Learning and Research(No.201901024016).
文摘Ship outfitting is a key process in shipbuilding.Efficient and high-quality ship outfitting is a top priority for modern shipyards.These activities are conducted at different stations of shipyards.The outfitting plan is one of the crucial issues in shipbuilding.In this paper,production scheduling and material ordering with endogenous uncertainty of the outfitting process are investigated.The uncertain factors in outfitting equipment production are usually decision-related,which leads to difficulties in addressing uncertainties in the outfitting production workshops before production is conducted according to plan.This uncertainty is regarded as endogenous uncertainty and can be treated as non-anticipativity constraints in the model.To address this problem,a stochastic two-stage programming model with endogenous uncertainty is established to optimize the outfitting job scheduling and raw material ordering process.A practical case of the shipyard of China Merchants Heavy Industry Co.,Ltd.is used to evaluate the performance of the proposed method.Satisfactory results are achieved at the lowest expected total cost as the complete kit rate of outfitting equipment is improved and emergency replenishment is reduced.
文摘BACKGROUND Acute appendicitis(AAp)is a prevalent medical condition characterized by inflammation of the appendix that frequently necessitates urgent surgical procedures.Approximately two-thirds of patients with AAp exhibit characteristic signs and symptoms;hence,negative AAp and complicated AAp are the primary concerns in research on AAp.In other terms,further investigations and algorithms are required for at least one third of patients to predict the clinical condition and distinguish them from uncomplicated patients with AAp.AIM To use a Stochastic Gradient Boosting(SGB)-based machine learning(ML)algorithm to tell the difference between AAp patients who are complicated and those who are not,and to find some important biomarkers for both types of AAp by using modeling to get variable importance values.METHODS This study analyzed an open access data set containing 140 people,including 41 healthy controls,65 individuals with uncomplicated AAp,and 34 individuals with complicated AAp.We analyzed some demographic data(age,sex)of the patients and the following biochemical blood parameters:White blood cell(WBC)count,neutrophils,lymphocytes,monocytes,platelet count,neutrophil-tolymphocyte ratio,lymphocyte-to-monocyte ratio,mean platelet volume,neutrophil-to-immature granulocyte ratio,ferritin,total bilirubin,immature granulocyte count,immature granulocyte percent,and neutrophil-to-immature granulocyte ratio.We tested the SGB model using n-fold cross-validation.It was implemented with an 80-20 training-test split.We used variable importance values to identify the variables that were most effective on the target.RESULTS The SGB model demonstrated excellent performance in distinguishing AAp from control patients with an accuracy of 96.3%,a micro aera under the curve(AUC)of 94.7%,a sensitivity of 94.7%,and a specificity of 100%.In distinguishing complicated AAp patients from uncomplicated ones,the model achieved an accuracy of 78.9%,a micro AUC of 79%,a sensitivity of 83.3%,and a specificity of 76.9%.The most useful biomarkers for confirming the AA diagnosis were WBC(100%),neutrophils(95.14%),and the lymphocyte-monocyte ratio(76.05%).On the other hand,the most useful biomarkers for accurate diagnosis of complicated AAp were total bilirubin(100%),WBC(96.90%),and the neutrophil-immature granulocytes ratio(64.05%).CONCLUSION The SGB model achieved high accuracy rates in identifying AAp patients while it showed moderate performance in distinguishing complicated AAp patients from uncomplicated AAp patients.Although the model's accuracy in the classification of complicated AAp is moderate,the high variable importance obtained is clinically significant.We need further prospective validation studies,but the integration of such ML algorithms into clinical practice may improve diagnostic processes.
基金supported by the Natural Science Foundation of China(No.41804112,author:Chengyun Song).
文摘Existing semi-supervisedmedical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution mismatch.However,current copy-paste methods have three limitations:(1)training the model solely with copy-paste mixed pictures from labeled and unlabeled input loses a lot of labeled information;(2)low-quality pseudo-labels can cause confirmation bias in pseudo-supervised learning on unlabeled data;(3)the segmentation performance in low-contrast and local regions is less than optimal.We design a Stochastic Augmentation-Based Dual-Teaching Auxiliary Training Strategy(SADT),which enhances feature diversity and learns high-quality features to overcome these problems.To be more precise,SADT trains the Student Network by using pseudo-label-based training from Teacher Network 1 and supervised learning with labeled data,which prevents the loss of rare labeled data.We introduce a bi-directional copy-pastemask with progressive high-entropy filtering to reduce data distribution disparities and mitigate confirmation bias in pseudo-supervision.For the mixed images,Deep-Shallow Spatial Contrastive Learning(DSSCL)is proposed in the feature spaces of Teacher Network 2 and the Student Network to improve the segmentation capabilities in low-contrast and local areas.In this procedure,the features retrieved by the Student Network are subjected to a random feature perturbation technique.On two openly available datasets,extensive trials show that our proposed SADT performs much better than the state-ofthe-art semi-supervised medical segmentation techniques.Using only 10%of the labeled data for training,SADT was able to acquire a Dice score of 90.10%on the ACDC(Automatic Cardiac Diagnosis Challenge)dataset.
基金Supported by the National Natural Science Foundation of China(10671182)。
文摘The article studies the evolutionary dynamics of two-population two-strategy game models with and without impulses. First, the payment matrix is given and two evolutionary dynamics models are established by adding stochastic and impulse. For the stochastic model without impulses, the existence and uniqueness of solution, and the existence of positive periodic solutions are proved, and a sufficient condition for strategy extinction is given. For the stochastic model with impulses, the existence of positive periodic solutions is proved. Numerical results show that noise and impulses directly affect the model, but the periodicity of the model does not change.
文摘Risk management often plays an important role in decision making un-der uncertainty.In quantitative risk management,assessing and optimizing risk metrics requires eficient computing techniques and reliable theoretical guarantees.In this pa-per,we introduce several topics on quantitative risk management and review some of the recent studies and advancements on the topics.We consider several risk metrics and study decision models that involve the metrics,with a main focus on the related com-puting techniques and theoretical properties.We show that stochastic optimization,as a powerful tool,can be leveraged to effectively address these problems.
基金Supported by NSFC(Nos.10671182,12061020)NSF of Guizhou Province(Nos.QKH[2019]1123,QKHKY[2021]088,QKHKY[2022]301,QKH-ZK[2021]331)the Ph.D.Project of Guizhou Education University(No.2021BS005)。
文摘A stochastic stage-structure predator-prey system with impulsive effect is investigated.First,we build the corresponding system without impulse in order to demonstrate the existence and uniqueness of the global positive solution.Second,by selecting an appropriate Lyapunov function,we provide the sufficient condition for the existence of a positive T-periodic solution.Finally,numerical simulations illustrate our theoretical results,which show that the impulse or the white noises can result in the extinction of the predator in a certain condition.
基金Supported by the National Natural Science Foundation of China(11971458,11471310)。
文摘In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.
基金supported by the PhD Research Startup Foundation of Hubei University of Economics(Grand No.XJ23BS42).
文摘This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field.We show that the approximation holds for the drift-implicit Euler–Maruyama discretization and derive its convergence rate.In particular,the solution of the discretized system converges to the solution of the first-order limit equation in the mean-square sense,and this convergence is independent of the order in which the mass parameterμand the step size h tend to zero.
文摘The two-player nonzero-sum linear-exponential-quadratic stochastic differential game is studied.The game takes into account the players'attitudes to risk.The nonlinear transformations and change of probability measure techniques are used to study the existence of both open-loop and closed-loop Nash equilibria for the game.Some examples are constructed to illustrate their differences.Furthermore,theoretical results are applied to solve the risk-sensitive portfolio game problem in the financial market and show the effects of risk attitudes and economic performance on equilibria.
基金Partially supported by NSFC(No.11701304)the K.C.Wong Education Foundation。
文摘In this paper we study the Freidlin-Wentzell's large deviation principle for the following nonlinear fractional stochastic heat equation driven by Gaussian noise∂/∂tu^(ε)=D_(δ)^(α)(t,x)+√εσ(u^(ε)(t,x))W(t,x),(t,x)∈[0,T]×R,where D_(δ)^(α)is a nonlocal fractional differential operator and W is the Gaussian noise which is white in time and behaves as a fractional Brownian motion with Hurst index H satisfying 3-α/4<H<1/2,in the space variable.The weak convergence approach plays an important role.
基金Partially supported by Postgraduate Research and Practice Innovation Program of Jiangsu Province(Nos.KYCX22-2211,KYCX22-2205)。
文摘In this paper,we prove the transportation cost-information inequalities on the space of continuous paths with respect to the L~2-metric and the uniform metric for the law of the mild solution to the stochastic heat equation defined on[0,T]×[0,1]driven by double-parameter fractional noise.
文摘Prediction of water inflow into a tunnel is a crucial prerequisite for the waterproof and drainage design of mountain tunnels in water-rich areas.Based on the proposed Baiyun Mountain Tunnel project in Guangzhou,a numerical percolation model of random fractured rock of a tunnel underpassing a water reservoir is established to study the seepage characteristics of surrounding rock,the law of water inflow,and the change of lining water pressure,considering the local artificial boundary conditions for seepage in large rock mass,.In addition,the influences of rock permeability,fracture aperture,grouting circle thickness,and penetration are analyzed.The results show that:(1)Only fractures with aperture wider than 0.1 mm can play a significant role in water conduction in rocks with the permeability lower than 10^(-11)m^(2);(2)The greater the permeability difference between the fractures and rocks,the more remarkable the effects of fractures on the surrounding rock seepage field and cavern water inflow;(3)The sensitivity of grouting waterproof function to grouting circle thickness,grouting ring penetration,and rock permeability is significantly higher than that of tunnel buried depth and fracture aperture;(4)The lining water head is much more sensitive to the grouting circle thickness and penetration than to the tunnel buried depth;(5)With the grouting range enlarging,the impact of grouting circle permeability on the precipitation pressure role of the grouting ring increases;(6)For the interesting tunnel designed to be built at the depth of 70 m,the grouting circle with the thickness of 0.5 m and permeability of 10-^(14)m^(2)is recommended.
