This paper takes the synthesizing evaluation about industrial economic benefits by examples and proposes a new method named maximizing deviation method for multiindices decision. The new method can automatically deter...This paper takes the synthesizing evaluation about industrial economic benefits by examples and proposes a new method named maximizing deviation method for multiindices decision. The new method can automatically determine the weight coefficients among the multiindices and also can obtain the exact and reliable evaluation results without subjectivity.展开更多
Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generaliz...Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generalization of intuitionistic fuzzy set(IFSs)and Pythagoras fuzzy set(PFSs),q-rung orthopair fuzzy set(q-ROFS)is more suitable for expressing fuzzy and uncertain information.But,in actual multiple attribute decision making(MADM)problems,the weights of DMs and attributes are always completely unknown or partly known,to date,the maximizing deviation method is a good tool to deal with such issues.Thus,combine the q-ROFS and conventional maximizing deviation method,we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper.Firstly,we briefly introduce the basic concept of q-rung orthopair fuzzy sets(q-ROFSs)and q-rung interval-valued orthopair fuzzy sets(q-RIVOFSs).Then,combine the maximizing deviation method with q-rung orthopair fuzzy information,we establish two new decision making models.On this basis,the proposed models are applied to MADM problems with q-rung orthopair fuzzy information.Compared with existing methods,the effectiveness and superiority of the new model are analyzed.This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers(q-ROFNs)and whose attributes are incomplete.展开更多
Energy efficiency is an important criterion for routing algorithms in the wireless sensor network. Cooperative routing can reduce energy consumption effectively stemming from its diversity gain advantage. To solve the...Energy efficiency is an important criterion for routing algorithms in the wireless sensor network. Cooperative routing can reduce energy consumption effectively stemming from its diversity gain advantage. To solve the energy consumption problem and maximize the network lifetime, this paper proposes a Virtual Multiple Input Multiple Output based Cooperative Routing algorithm(VMIMOCR). VMIMOCR chooses cooperative relay nodes based on Virtual Multiple Input Multiple Output Model, and balances energy consumption by reasonable power allocation among transmitters, and decides the forwarding path finally. The experimental results show that VMIMOCR can improve network lifetime from 37% to 348% in the medium node density, compared with existing routing algorithms.展开更多
In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged withi...In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.展开更多
A unique challenge in P2P network is that the peer dynamics (departure or failure) cause unavoidable disruption to the downstream peers. While many works have been dedicated to consider fault resilience in peer select...A unique challenge in P2P network is that the peer dynamics (departure or failure) cause unavoidable disruption to the downstream peers. While many works have been dedicated to consider fault resilience in peer selection, little understanding is achieved regarding the solvability and solution complexity of this problem from the optimization perspective. To this end, we propose an optimization framework based on the generalized flow theory. Key concepts introduced by this framework include resilience factor, resilience index, and generalized throughput, which collectively model the peer resilience in a probabilistic measure. Under this framework, we divide the domain of optimal peer selection along several dimensions including network topology, overlay organization, and the definition of resilience factor and generalized flow. Within each sub-problem, we focus on studying the problem complexity and finding optimal solutions. Simulation study is also performed to evaluate the effectiveness of our model and performance of the proposed algorithms.展开更多
The subdistrict office is the most grass-roots government organization, and is also the main unit providing services for the masses at the grass-roots level. In order to ensure the work efficiency of the subdistrict o...The subdistrict office is the most grass-roots government organization, and is also the main unit providing services for the masses at the grass-roots level. In order to ensure the work efficiency of the subdistrict office, it is necessary to strengthen the modernization of the subdistrict office. However, due to the influence of traditional management concepts for a long time, the street offices in many areas of our country still adopt traditional management methods when carrying out human resources management, which is difficult to motivate the staff. If this situation cannot be changed in time, it will affect the service efficiency of the street offices and the grassroots will be full of complaints, which will not only affect the image of the national government agencies, but also affect the stability of the street residents.展开更多
Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most exi...Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most existing studies on the IM problem focus on static social network features,while neglecting the features of temporal social networks.To bridge this gap,we focus on node features reflected by their historical interaction behavior in temporal social networks,i.e.,interaction attributes and self-similarity,and incorporate them into the influence maximization algorithm and information propagation model.Firstly,we propose a node feature-aware voting algorithm,called ISVoteRank,for seed nodes selection.Specifically,before voting,the algorithm sets the initial voting ability of nodes in a personalized manner by combining their features.During the voting process,voting weights are set based on the interaction strength between nodes,allowing nodes to vote at different extents and subsequently weakening their voting ability accordingly.The process concludes by selecting the top k nodes with the highest voting scores as seeds,avoiding the inefficiency of iterative seed selection in traditional voting-based algorithms.Secondly,we extend the Independent Cascade(IC)model and propose the Dynamic Independent Cascade(DIC)model,which aims to capture the dynamic features in the information propagation process by combining node features.Finally,experiments demonstrate that the ISVoteRank algorithm has been improved in both effectiveness and efficiency compared to baseline methods,and the influence spread through the DIC model is improved compared to the IC model.展开更多
In this work,we focus on maximizing the ratio of two monotone DR-submodular functions on the integer lattice.It is neither submodular nor supermodular.We prove that the Threshold Decrease Algorithm is a 1-e^(1-kg)-εa...In this work,we focus on maximizing the ratio of two monotone DR-submodular functions on the integer lattice.It is neither submodular nor supermodular.We prove that the Threshold Decrease Algorithm is a 1-e^(1-kg)-εapproximation ratio algorithm.Additionally,we construct the relationship between maximizing the ratio of two monotone DR-submodular functions and maximizing the difference of two monotone DR-submodular functions on the integer lattice.Based on this relationship,we combine the dichotomy technique and Threshold Decrease Algorithm to solve maximizing the difference of two monotone DR-submodular functions on the integer lattice and prove its approximation ratio is f(x)-g(x)≥1-e^(1-kg)f(X^(*))-g(X^(*)).To the best of our knowledge,before us,there was no work to focus on maximizing the ratio of two monotone DR-submodular functions on integer lattice by using the Threshold Decrease Algorithm.展开更多
Submodular optimization is widely used in large datasets.In order to speed up the problems solving,it is essential to design low-adaptive algorithms to achieve acceleration in parallel.In general,the function values a...Submodular optimization is widely used in large datasets.In order to speed up the problems solving,it is essential to design low-adaptive algorithms to achieve acceleration in parallel.In general,the function values are given by a value oracle,but in practice,the oracle queries may consume a lot of time.Hence,how to strike a balance between optimizing them is important.In this paper,we focus on maximizing a normalized and strictly monotone set function with the diminishing-return ratio under a cardinality constraint,and propose two algorithms to deal with it.We apply the adaptive sequencing technique to devise the first algorithm,whose approximation ratio is arbitrarily close to 1-e^(-γ)in O(logn·log(log k/γ)) adaptive rounds,and requires O(logn^(2)·log(log k/γ)) queries.Then by adding preprocessing and parameter estimation steps to the first algorithm,we get the second one.The second algorithm trades a small sacrifice in adaptive complexity for a significant improvement in query complexity.With the same approximation and adaptive complexity,the query complexity is improved to.To the best of our knowledge,this is the first paper of designing adaptive algorithms for maximizing a monotone function using the diminishing-return ratio.展开更多
In this paper,we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular(DR-submodular)function and a nonnegative linear function on the integer lattice.As it is al...In this paper,we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular(DR-submodular)function and a nonnegative linear function on the integer lattice.As it is almost unapproximable for maximizing a submodular function without the condition of nonnegative,we provide weak(bifactor)approximation algorithms for this problem in two online settings,respectively.For the unconstrained online model,we combine the ideas of single-threshold greedy,binary search and function scaling to give an efficient algorithm with a 1/2 weak approximation ratio.For the online streaming model subject to a cardinality constraint,we provide a one-pass(3-√5)/2 weak approximation ratio streaming algorithm.Its memory complexity is(k log k/ε),and the update time for per element is(log^(2)k/ε).展开更多
Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1...Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1].Thus,highdensity multiphase DC−DC converters are pivotal for implementing vertical power delivery(VPD)architectures in XPU platforms.Strategically positioning these converters beneath processors and maximizing spatial utilization enables core rail currents exceeding 2 kA while significantly reducing the power distribution network(PDN)losses compared to conventional solutions.The VPD configuration elevates system-level energy efficiency with>100 W power saving per processor,yielding megawatt-scale savings in a datacenter that uses~100000 processors.The synergy of 48 V power conversion architectures and advanced packaging techniques enables the industry’s commitment to balancing computational demands with CO_(2)emission reduction and environmental sustainability.展开更多
We discuss a variant of the multi-task n-vehicle exploration problem. Instead of requiring an optimal permutation of vehicles in every group, the new problem requires all vehicles in a group to arrive at the same dest...We discuss a variant of the multi-task n-vehicle exploration problem. Instead of requiring an optimal permutation of vehicles in every group, the new problem requires all vehicles in a group to arrive at the same destination. Given n tasks with assigned consume-time and profit, it may also be viewed as a maximization of every processor＇s average profit. Further, we propose a new kind of partition problem in fractional form and analyze its computational complexity. By regarding fractional partition as a special case, we prove that the average profit maximization problem is NP-hard when the number of processors is fixed and it is strongly NP- hard in general. At last, a pseudo-polynomial time algorithm for the average profit maximization problem and the fractional partition problem is presented, using the idea of the pseudo-polynomial time algorithm for the classical partition problem.展开更多
In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(...In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.展开更多
The purpose of this article is to introduce a new method with a self-adaptive stepsize for approximating a common solution of monotone inclusion problems and variational inequality problems in reflexive Banach spaces....The purpose of this article is to introduce a new method with a self-adaptive stepsize for approximating a common solution of monotone inclusion problems and variational inequality problems in reflexive Banach spaces.The strong convergence result for our method is established under some standard assumptions without any requirement of the knowledge of the Lipschitz constant of the mapping.Several numerical experiments are provided to verify the advantages and efficiency of proposed algorithms.展开更多
BACKGROUND Epilepsy impacts millions of people,with many not responding to existing treatments.Some evidence links neuroinflammatory processes to epilepsy.Statins exhibit anti-inflammatory and neuroprotective properti...BACKGROUND Epilepsy impacts millions of people,with many not responding to existing treatments.Some evidence links neuroinflammatory processes to epilepsy.Statins exhibit anti-inflammatory and neuroprotective properties,potentially offering antiepileptic effects.AIM To evaluate the anticonvulsant effects of rosuvastatin in animal models of epilepsy.METHODS Ninety-six albino mice were divided into 16 groups.In the maximal electroshock seizure(MES)model,eight groups received intraperitoneal vehicle,carbama-zepine,rosuvastatin,or a combination.Outcomes measured included seizure protection[tonic hind limb extension(THLE)],duration of THLE,seizure duration,and mortality.In the pentylenetetrazol(PTZ)model,eight groups were pretreated with vehicle,valproate,rosuvastatin,or a combination,with outcomes measured as seizure latency,seizure duration,and mortality.RESULTS In the MES model,rosuvastatin exhibited protection against THLE in a small percentage of mice.Rosuvastatin shortens the duration of THLE in a dose-dependent manner.However,none of these were statistically significant com-pared to the control group.The combination of rosuvastatin 10 mg/kg with carbamazepine 4 mg/kg resulted in a significant reduction in seizure duration compared to the control group,better than carbamazepine alone at 4 mg/kg and 6 mg/kg.In the PTZ model,rosuvastatin alone showed no significant effects on latency,duration of seizure,or mortality.However,rosuvastatin 10 mg/kg combined with valproate 100 mg/kg significantly delayed the onset of seizures,seizure duration and mortality percentage,better than valproate alone at 100 mg/kg.CONCLUSION Rosuvastatin enhanced the anticonvulsant effects of carbamazepine and valproate.Further studies are required to explore the antiepileptic potential of rosuvastatin at various doses,durations,dosage forms,routes and models.展开更多
In this paper,we provide an alternative proof of the weak type(1,n/n-a)inequality for the fractional maximal operators.By using the discretization technique,we can get the main result,which shows that the weak type(1,...In this paper,we provide an alternative proof of the weak type(1,n/n-a)inequality for the fractional maximal operators.By using the discretization technique,we can get the main result,which shows that the weak type(1,n/n-a)bound of M_(α)is at worst 2^(n-a).The weak type(1,n/n-a)bound of M_(α)can be estimated more directly and easily in this method,which is different from the usual ways.展开更多
[Objectives]Epimedium brevicornu Maxim is a well-known plant having the concomitant function of both medicine and foodstuff with the bioactivity of anti-inflammatory and cardiovascular protection.It has important ther...[Objectives]Epimedium brevicornu Maxim is a well-known plant having the concomitant function of both medicine and foodstuff with the bioactivity of anti-inflammatory and cardiovascular protection.It has important therapeutic effects and health benefits for various chronic diseases.This study aimed to analyze the studies on E.brevicornu Maxim from 2003 to 2022 with bibliometric analysis.[Methods]Publications related to E.brevicornu Maxim was retrieved in Web of Science Core Collection(WoSCC)from January 1,2003 to November 19,2022,and analyzed in Microsoft Excle,CiteSpace,and VOSviewer.[Results]In total,1317 documents were extracted from the WoSCC database.The growth rate of the publications showed a rapid increase from 2017.China provided the most documents,and Chinese Academy of Medical Sciences,Fudan University and Chinese Academy of Sciences contributed more papers.Wang Ying from Chinese Academy of Sciences was the most productive author,and the Journal of Ethnopharmacology was the most co-cited journal.The words"icariin","activation","oxidative stress","apoptosis","proliferation","osteogenic differentiation"and"flavonoid"were frequently occurred in the abstract and title of articles.Cluster analysis of keywords demonstrated"hippocampal neuron","efficient production","liquid extraction","bone regeneration"and"leukemia cell growth"were the hot topics from 2003 to 2022.The focus of the research has changed from the liquid extraction of flavonoids to the inflammatory response and metabolism,while cognitive deficit has emerged as a recent research hotspot.[Conclusions]The research on E.brevicornu Maxim has been expanding,and more studies are related to signaling pathways and metabolism diseases.展开更多
In this paper,we introduce the set of maximal subgroups with non-trivial core and their corresponding second maximal subgroups.A correlation characterization of the group class J_(pr)is presented by establishing the r...In this paper,we introduce the set of maximal subgroups with non-trivial core and their corresponding second maximal subgroups.A correlation characterization of the group class J_(pr)is presented by establishing the relationship between the core and the second maximal subgroups in these classifications.展开更多
文摘This paper takes the synthesizing evaluation about industrial economic benefits by examples and proposes a new method named maximizing deviation method for multiindices decision. The new method can automatically determine the weight coefficients among the multiindices and also can obtain the exact and reliable evaluation results without subjectivity.
基金supported by the National Natural Science Foundation of China under Grant No.71571128the Humanities and Social Sciences Foundation of Ministry of Education of the People’s Republic of China(No.17XJA630003).
文摘Because of the uncertainty and subjectivity of decision makers in the complex decision-making environment,the evaluation information of alternatives given by decision makers is often fuzzy and uncertain.As a generalization of intuitionistic fuzzy set(IFSs)and Pythagoras fuzzy set(PFSs),q-rung orthopair fuzzy set(q-ROFS)is more suitable for expressing fuzzy and uncertain information.But,in actual multiple attribute decision making(MADM)problems,the weights of DMs and attributes are always completely unknown or partly known,to date,the maximizing deviation method is a good tool to deal with such issues.Thus,combine the q-ROFS and conventional maximizing deviation method,we will study the maximizing deviation method under q-ROFSs and q-RIVOFSs in this paper.Firstly,we briefly introduce the basic concept of q-rung orthopair fuzzy sets(q-ROFSs)and q-rung interval-valued orthopair fuzzy sets(q-RIVOFSs).Then,combine the maximizing deviation method with q-rung orthopair fuzzy information,we establish two new decision making models.On this basis,the proposed models are applied to MADM problems with q-rung orthopair fuzzy information.Compared with existing methods,the effectiveness and superiority of the new model are analyzed.This method can effectively solve the MADM problem whose decision information is represented by q-rung orthopair fuzzy numbers(q-ROFNs)and whose attributes are incomplete.
基金supported by the National Basic Research Program of China (973 program) (Grant No.2012CB315805)the National Natural Science Foundation of China (Grant No.61472130 and 61572184)
文摘Energy efficiency is an important criterion for routing algorithms in the wireless sensor network. Cooperative routing can reduce energy consumption effectively stemming from its diversity gain advantage. To solve the energy consumption problem and maximize the network lifetime, this paper proposes a Virtual Multiple Input Multiple Output based Cooperative Routing algorithm(VMIMOCR). VMIMOCR chooses cooperative relay nodes based on Virtual Multiple Input Multiple Output Model, and balances energy consumption by reasonable power allocation among transmitters, and decides the forwarding path finally. The experimental results show that VMIMOCR can improve network lifetime from 37% to 348% in the medium node density, compared with existing routing algorithms.
文摘In past years,growing efforts have been made to the rapid interpretation of magnetic field data acquired by a sparse synthetic or real magnetic sensor array.An appealing requirement on such sparse array arranged within a specified survey region is that to make the number of sensor elements as small as possible,meanwhile without deteriorating imaging quality.For this end,we propose a novel methodology of arranging sensors in an optimal manner,exploring the concept of information capacity developed originally in the communication society.The proposed scheme reduces mathematically the design of a sparse sensor array into solving a combinatorial optimization problem,which can be resolved efficiently using widely adopted Simultaneous Perturbation and Statistical Algorithm(SPSA).Three sets of numerical examples of designing optimal sensor array are provided to demonstrate the performance of proposed methodology.
文摘A unique challenge in P2P network is that the peer dynamics (departure or failure) cause unavoidable disruption to the downstream peers. While many works have been dedicated to consider fault resilience in peer selection, little understanding is achieved regarding the solvability and solution complexity of this problem from the optimization perspective. To this end, we propose an optimization framework based on the generalized flow theory. Key concepts introduced by this framework include resilience factor, resilience index, and generalized throughput, which collectively model the peer resilience in a probabilistic measure. Under this framework, we divide the domain of optimal peer selection along several dimensions including network topology, overlay organization, and the definition of resilience factor and generalized flow. Within each sub-problem, we focus on studying the problem complexity and finding optimal solutions. Simulation study is also performed to evaluate the effectiveness of our model and performance of the proposed algorithms.
文摘The subdistrict office is the most grass-roots government organization, and is also the main unit providing services for the masses at the grass-roots level. In order to ensure the work efficiency of the subdistrict office, it is necessary to strengthen the modernization of the subdistrict office. However, due to the influence of traditional management concepts for a long time, the street offices in many areas of our country still adopt traditional management methods when carrying out human resources management, which is difficult to motivate the staff. If this situation cannot be changed in time, it will affect the service efficiency of the street offices and the grassroots will be full of complaints, which will not only affect the image of the national government agencies, but also affect the stability of the street residents.
基金supported by the Fundamental Research Funds for the Universities of Heilongjiang(Nos.145109217,135509234)the Youth Science and Technology Innovation Personnel Training Project of Heilongjiang(No.UNPYSCT-2020072)the Innovative Research Projects for Postgraduates of Qiqihar University(No.YJSCX2022048).
文摘Influence Maximization(IM)aims to select a seed set of size k in a social network so that information can be spread most widely under a specific information propagation model through this set of nodes.However,most existing studies on the IM problem focus on static social network features,while neglecting the features of temporal social networks.To bridge this gap,we focus on node features reflected by their historical interaction behavior in temporal social networks,i.e.,interaction attributes and self-similarity,and incorporate them into the influence maximization algorithm and information propagation model.Firstly,we propose a node feature-aware voting algorithm,called ISVoteRank,for seed nodes selection.Specifically,before voting,the algorithm sets the initial voting ability of nodes in a personalized manner by combining their features.During the voting process,voting weights are set based on the interaction strength between nodes,allowing nodes to vote at different extents and subsequently weakening their voting ability accordingly.The process concludes by selecting the top k nodes with the highest voting scores as seeds,avoiding the inefficiency of iterative seed selection in traditional voting-based algorithms.Secondly,we extend the Independent Cascade(IC)model and propose the Dynamic Independent Cascade(DIC)model,which aims to capture the dynamic features in the information propagation process by combining node features.Finally,experiments demonstrate that the ISVoteRank algorithm has been improved in both effectiveness and efficiency compared to baseline methods,and the influence spread through the DIC model is improved compared to the IC model.
基金upported by the China Scholarship Council(No.202004910755)supported by the National Natural Science Foundation of China(Nos.12071459 and 11991022)+2 种基金the Fundamental Research Funds for Central Universities(No.E1E40107X2)supported by the Natural Sciences and Engineering Research Council of Canada(No.283106)the National Natural Science Foundation of China(Nos.11771386 and 11728104)。
文摘In this work,we focus on maximizing the ratio of two monotone DR-submodular functions on the integer lattice.It is neither submodular nor supermodular.We prove that the Threshold Decrease Algorithm is a 1-e^(1-kg)-εapproximation ratio algorithm.Additionally,we construct the relationship between maximizing the ratio of two monotone DR-submodular functions and maximizing the difference of two monotone DR-submodular functions on the integer lattice.Based on this relationship,we combine the dichotomy technique and Threshold Decrease Algorithm to solve maximizing the difference of two monotone DR-submodular functions on the integer lattice and prove its approximation ratio is f(x)-g(x)≥1-e^(1-kg)f(X^(*))-g(X^(*)).To the best of our knowledge,before us,there was no work to focus on maximizing the ratio of two monotone DR-submodular functions on integer lattice by using the Threshold Decrease Algorithm.
基金the National Natural Science Foundation of China(Nos.11971447 and 11871442)the Fundamental Research Funds for the Central Universities.
文摘Submodular optimization is widely used in large datasets.In order to speed up the problems solving,it is essential to design low-adaptive algorithms to achieve acceleration in parallel.In general,the function values are given by a value oracle,but in practice,the oracle queries may consume a lot of time.Hence,how to strike a balance between optimizing them is important.In this paper,we focus on maximizing a normalized and strictly monotone set function with the diminishing-return ratio under a cardinality constraint,and propose two algorithms to deal with it.We apply the adaptive sequencing technique to devise the first algorithm,whose approximation ratio is arbitrarily close to 1-e^(-γ)in O(logn·log(log k/γ)) adaptive rounds,and requires O(logn^(2)·log(log k/γ)) queries.Then by adding preprocessing and parameter estimation steps to the first algorithm,we get the second one.The second algorithm trades a small sacrifice in adaptive complexity for a significant improvement in query complexity.With the same approximation and adaptive complexity,the query complexity is improved to.To the best of our knowledge,this is the first paper of designing adaptive algorithms for maximizing a monotone function using the diminishing-return ratio.
基金supported by the National Natural Science Foundation of China(Nos.12001025 and 12131003)The second author is supported by the Natural Sciences and Engineering Research Council(No.06446),and the National Natural Science Foundation of China(Nos.11771386 and 11728104)+2 种基金The third author is supported by the National Natural Science Foundation of China(Nos.11501171 and 11771251)the Province Natural Science Foundation of Shandong(No.ZR2020MA028)The fourth author is supported by the National Natural Science Foundation of China(No.11701150)。
文摘In this paper,we investigate the maximization of the differences between a nonnegative monotone diminishing return submodular(DR-submodular)function and a nonnegative linear function on the integer lattice.As it is almost unapproximable for maximizing a submodular function without the condition of nonnegative,we provide weak(bifactor)approximation algorithms for this problem in two online settings,respectively.For the unconstrained online model,we combine the ideas of single-threshold greedy,binary search and function scaling to give an efficient algorithm with a 1/2 weak approximation ratio.For the online streaming model subject to a cardinality constraint,we provide a one-pass(3-√5)/2 weak approximation ratio streaming algorithm.Its memory complexity is(k log k/ε),and the update time for per element is(log^(2)k/ε).
文摘Motivation.As artificial intelligence(AI)workloads escalate exponentially,ultra-thin,high-efficiency voltage regulator modules(VRMs)with exceptional power density become essential for backside-mounted configurations[1].Thus,highdensity multiphase DC−DC converters are pivotal for implementing vertical power delivery(VPD)architectures in XPU platforms.Strategically positioning these converters beneath processors and maximizing spatial utilization enables core rail currents exceeding 2 kA while significantly reducing the power distribution network(PDN)losses compared to conventional solutions.The VPD configuration elevates system-level energy efficiency with>100 W power saving per processor,yielding megawatt-scale savings in a datacenter that uses~100000 processors.The synergy of 48 V power conversion architectures and advanced packaging techniques enables the industry’s commitment to balancing computational demands with CO_(2)emission reduction and environmental sustainability.
基金Supported by Daqing oilfield company Project of PetroCHINA under Grant (dqc-2010-xdgl-ky-002)Key Laboratory of Management, Decision and Information Systems, Chinese Academy of SciencesBeijing Research Center of Urban System Engineering
文摘We discuss a variant of the multi-task n-vehicle exploration problem. Instead of requiring an optimal permutation of vehicles in every group, the new problem requires all vehicles in a group to arrive at the same destination. Given n tasks with assigned consume-time and profit, it may also be viewed as a maximization of every processor＇s average profit. Further, we propose a new kind of partition problem in fractional form and analyze its computational complexity. By regarding fractional partition as a special case, we prove that the average profit maximization problem is NP-hard when the number of processors is fixed and it is strongly NP- hard in general. At last, a pseudo-polynomial time algorithm for the average profit maximization problem and the fractional partition problem is presented, using the idea of the pseudo-polynomial time algorithm for the classical partition problem.
基金supported by the CAS Project for Young Scientists in Basic Research under Grant YSBR-035Jiangsu Provincial Key Research and Development Program under Grant BE2021013-2.
文摘In covert communications,joint jammer selection and power optimization are important to improve performance.However,existing schemes usually assume a warden with a known location and perfect Channel State Information(CSI),which is difficult to achieve in practice.To be more practical,it is important to investigate covert communications against a warden with uncertain locations and imperfect CSI,which makes it difficult for legitimate transceivers to estimate the detection probability of the warden.First,the uncertainty caused by the unknown warden location must be removed,and the Optimal Detection Position(OPTDP)of the warden is derived which can provide the best detection performance(i.e.,the worst case for a covert communication).Then,to further avoid the impractical assumption of perfect CSI,the covert throughput is maximized using only the channel distribution information.Given this OPTDP based worst case for covert communications,the jammer selection,the jamming power,the transmission power,and the transmission rate are jointly optimized to maximize the covert throughput(OPTDP-JP).To solve this coupling problem,a Heuristic algorithm based on Maximum Distance Ratio(H-MAXDR)is proposed to provide a sub-optimal solution.First,according to the analysis of the covert throughput,the node with the maximum distance ratio(i.e.,the ratio of the distances from the jammer to the receiver and that to the warden)is selected as the friendly jammer(MAXDR).Then,the optimal transmission and jamming power can be derived,followed by the optimal transmission rate obtained via the bisection method.In numerical and simulation results,it is shown that although the location of the warden is unknown,by assuming the OPTDP of the warden,the proposed OPTDP-JP can always satisfy the covertness constraint.In addition,with an uncertain warden and imperfect CSI,the covert throughput provided by OPTDP-JP is 80%higher than the existing schemes when the covertness constraint is 0.9,showing the effectiveness of OPTDP-JP.
基金Supported by NSFC(No.12171062)the Natural Science Foundation of Chongqing(No.CSTB2022NSCQ-JQX0004)+1 种基金the Chongqing Talent Support Program(No.cstc2024ycjh-bgzxm0121)Science and Technology Project of Chongqing Education Committee(No.KJZD-M202300503)。
文摘The purpose of this article is to introduce a new method with a self-adaptive stepsize for approximating a common solution of monotone inclusion problems and variational inequality problems in reflexive Banach spaces.The strong convergence result for our method is established under some standard assumptions without any requirement of the knowledge of the Lipschitz constant of the mapping.Several numerical experiments are provided to verify the advantages and efficiency of proposed algorithms.
文摘BACKGROUND Epilepsy impacts millions of people,with many not responding to existing treatments.Some evidence links neuroinflammatory processes to epilepsy.Statins exhibit anti-inflammatory and neuroprotective properties,potentially offering antiepileptic effects.AIM To evaluate the anticonvulsant effects of rosuvastatin in animal models of epilepsy.METHODS Ninety-six albino mice were divided into 16 groups.In the maximal electroshock seizure(MES)model,eight groups received intraperitoneal vehicle,carbama-zepine,rosuvastatin,or a combination.Outcomes measured included seizure protection[tonic hind limb extension(THLE)],duration of THLE,seizure duration,and mortality.In the pentylenetetrazol(PTZ)model,eight groups were pretreated with vehicle,valproate,rosuvastatin,or a combination,with outcomes measured as seizure latency,seizure duration,and mortality.RESULTS In the MES model,rosuvastatin exhibited protection against THLE in a small percentage of mice.Rosuvastatin shortens the duration of THLE in a dose-dependent manner.However,none of these were statistically significant com-pared to the control group.The combination of rosuvastatin 10 mg/kg with carbamazepine 4 mg/kg resulted in a significant reduction in seizure duration compared to the control group,better than carbamazepine alone at 4 mg/kg and 6 mg/kg.In the PTZ model,rosuvastatin alone showed no significant effects on latency,duration of seizure,or mortality.However,rosuvastatin 10 mg/kg combined with valproate 100 mg/kg significantly delayed the onset of seizures,seizure duration and mortality percentage,better than valproate alone at 100 mg/kg.CONCLUSION Rosuvastatin enhanced the anticonvulsant effects of carbamazepine and valproate.Further studies are required to explore the antiepileptic potential of rosuvastatin at various doses,durations,dosage forms,routes and models.
基金Supported by by Natural Science Foundation of Henan(202300410184 and242300421387)。
文摘In this paper,we provide an alternative proof of the weak type(1,n/n-a)inequality for the fractional maximal operators.By using the discretization technique,we can get the main result,which shows that the weak type(1,n/n-a)bound of M_(α)is at worst 2^(n-a).The weak type(1,n/n-a)bound of M_(α)can be estimated more directly and easily in this method,which is different from the usual ways.
基金Supported by The Scientific Research Program(B2021234)from Hubei Provincial Department of EducationKey Research and Development Program of Hubei Province(2022BCE013)+2 种基金Open fund of Hubei Key Laboratory of Economic Forest Germplasm Improvement and Resources Comprehensive Utilization(202303302)Scientific Research Foundation for Advanced Talents(2042021040)from Huanggang Normal UniversityChinese Foundation for Hepatitis Prevention and Control-Chinese Hepatitis B Research Fund(YGFK20220019).
文摘[Objectives]Epimedium brevicornu Maxim is a well-known plant having the concomitant function of both medicine and foodstuff with the bioactivity of anti-inflammatory and cardiovascular protection.It has important therapeutic effects and health benefits for various chronic diseases.This study aimed to analyze the studies on E.brevicornu Maxim from 2003 to 2022 with bibliometric analysis.[Methods]Publications related to E.brevicornu Maxim was retrieved in Web of Science Core Collection(WoSCC)from January 1,2003 to November 19,2022,and analyzed in Microsoft Excle,CiteSpace,and VOSviewer.[Results]In total,1317 documents were extracted from the WoSCC database.The growth rate of the publications showed a rapid increase from 2017.China provided the most documents,and Chinese Academy of Medical Sciences,Fudan University and Chinese Academy of Sciences contributed more papers.Wang Ying from Chinese Academy of Sciences was the most productive author,and the Journal of Ethnopharmacology was the most co-cited journal.The words"icariin","activation","oxidative stress","apoptosis","proliferation","osteogenic differentiation"and"flavonoid"were frequently occurred in the abstract and title of articles.Cluster analysis of keywords demonstrated"hippocampal neuron","efficient production","liquid extraction","bone regeneration"and"leukemia cell growth"were the hot topics from 2003 to 2022.The focus of the research has changed from the liquid extraction of flavonoids to the inflammatory response and metabolism,while cognitive deficit has emerged as a recent research hotspot.[Conclusions]The research on E.brevicornu Maxim has been expanding,and more studies are related to signaling pathways and metabolism diseases.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1237101812201236)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.B240201093/2013)the Natural Science Foundation of the Anhui Higher Education Institutions(Grant No.2022AH051907)。
文摘In this paper,we introduce the set of maximal subgroups with non-trivial core and their corresponding second maximal subgroups.A correlation characterization of the group class J_(pr)is presented by establishing the relationship between the core and the second maximal subgroups in these classifications.
