Evolutionary game dynamics of combining two different aspiration-driven update rules in structured populations

In evolutionary games,most studies on finite populations have focused on a single updating mechanism.However,given the differences in individual cognition,individuals may change their strategies according to different updating mechanisms.For this reason,we consider two different aspiration-driven updating mechanisms in structured populations:satisfied-stay unsatisfied shift(SSUS)and satisfied-cooperate unsatisfied defect(SCUD).To simulate the game player’s learning process,this paper improves the particle swarm optimization algorithm,which will be used to simulate the game player’s strategy selection,i.e.,population particle swarm optimization(PPSO)algorithms.We find that in the prisoner’s dilemma,the conditions that SSUS facilitates the evolution of cooperation do not enable cooperation to emerge.In contrast,SCUD conditions that promote the evolution of cooperation enable cooperation to emerge.In addition,the invasion of SCUD individuals helps promote cooperation among SSUS individuals.Simulated by the PPSO algorithm,the theoretical approximation results are found to be consistent with the trend of change in the simulation results.

Resilient TCP Variant Enabling Smooth Network Updates for Software-Defined Data Center Networks

Network updates have become increasingly prevalent since the broad adoption of software-defined networks(SDNs)in data centers.Modern TCP designs,including cutting-edge TCP variants DCTCP,CUBIC,and BBR,however,are not resilient to network updates that provoke flow rerouting.In this paper,we first demonstrate that popular TCP implementations perform inadequately in the presence of frequent and inconsistent network updates,because inconsistent and frequent network updates result in out-of-order packets and packet drops induced via transitory congestion and lead to serious performance deterioration.We look into the causes and propose a network update-friendly TCP(NUFTCP),which is an extension of the DCTCP variant,as a solution.Simulations are used to assess the proposed NUFTCP.Our findings reveal that NUFTCP can more effectively manage the problems of out-of-order packets and packet drops triggered in network updates,and it outperforms DCTCP considerably.

An Updated Lagrangian Particle Hydrodynamics (ULPH)-NOSBPD Coupling Approach forModeling Fluid-Structure Interaction Problem

A fluid-structure interaction approach is proposed in this paper based onNon-Ordinary State-Based Peridynamics(NOSB-PD)and Updated Lagrangian Particle Hydrodynamics(ULPH)to simulate the fluid-structure interaction problem with large geometric deformation and material failure and solve the fluid-structure interaction problem of Newtonian fluid.In the coupled framework,the NOSB-PD theory describes the deformation and fracture of the solid material structure.ULPH is applied to describe the flow of Newtonian fluids due to its advantages in computational accuracy.The framework utilizes the advantages of NOSB-PD theory for solving discontinuous problems and ULPH theory for solving fluid problems,with good computational stability and robustness.A fluidstructure coupling algorithm using pressure as the transmission medium is established to deal with the fluidstructure interface.The dynamic model of solid structure and the PD-ULPH fluid-structure interaction model involving large deformation are verified by numerical simulations.The results agree with the analytical solution,the available experimental data,and other numerical results.Thus,the accuracy and effectiveness of the proposed method in solving the fluid-structure interaction problem are demonstrated.The fluid-structure interactionmodel based on ULPH and NOSB-PD established in this paper provides a new idea for the numerical solution of fluidstructure interaction and a promising approach for engineering design and experimental prediction.

Updated Lagrangian Particle Hydrodynamics (ULPH)Modeling of Natural Convection Problems

Natural convection is a heat transfer mechanism driven by temperature or density differences,leading to fluid motion without external influence.It occurs in various natural and engineering phenomena,influencing heat transfer,climate,and fluid mixing in industrial processes.This work aims to use the Updated Lagrangian Particle Hydrodynamics(ULPH)theory to address natural convection problems.The Navier-Stokes equation is discretized using second-order nonlocal differential operators,allowing a direct solution of the Laplace operator for temperature in the energy equation.Various numerical simulations,including cases such as natural convection in square cavities and two concentric cylinders,were conducted to validate the reliability of the model.The results demonstrate that the proposed model exhibits excellent accuracy and performance,providing a promising and effective numerical approach for natural convection problems.

Snowfall Update

Julie:What are you looking at,Sam?Sam:Oh,hi,Julie.I'm looking at Fairview City's weekly snowfall update.Julie:But it's only Monday.Sam:I know.The update is for last week's snowfall.Julie:I see.It'sforthesecond weekofthis month,then.Sam:That's right.The datesare from December 8 to December 14.

Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

Scoping review update on somatic symptom disorder that includes additional Chinese data

Somatic symptom disorder(SSD)is a new diagnosis introduced into the Diagnostic and Statistical Manual of Mental Disorders,Fifth Edition(DSM-5),which is expected to solve the diagnostic difficulties of patients with medically unexplained symptoms.Based on the previous work,this review aims to comprehensively synthesise updated evidence related to SSD from recent years in English publications and,more extensively,from data published in Chinese language journals.The scoping review update was based on an earlier scoping review and included Chinese language publication data from China National Knowledge Internet(CNKI),WANFANG and WEIPU between January 2013 and May 2022 and data from PubMed,PsyclNFO,and Cochrane Library between June 2020 and May 2022.Initially,2984 articles were identified,of which 63 full texts were included for analysis.In China,SSD is mainly applied in scientific research,but it also shows good predictive validity and clinical application potential.The mean frequency of SSD was 4.5%in the general population,25.2%in the primary care population and 33.5%in diverse specialised care settings.Biological factors,such as brain region changes and heart rate variability,are associated with the onset of sSD.Psychological impairment related to somatic symptoms is the best predictor of prognosis.While adolescent SSD is significantly associated with family function,SSD overall is associated with an increased dysfunction of cognition and emotion,decreased quality of life,and high comorbidity with anxiety and depressive disorders.Further research is needed on suicide risk and cultural and gender-related issues.Updating the data of Chinese language studies,our research enriches the evidence-based findings related to the topics addressed in the text sections of the SSD chapter of DSM-5.However,research gaps remain about SSD reliability,population-based prevalence,suicide risk,and cultural and gender-related issues.

Health Data Availability Protection:Delta-XOR-Relay Data Update in Erasure-Coded Cloud Storage Systems

To achieve the high availability of health data in erasure-coded cloud storage systems,the data update performance in erasure coding should be continuously optimized.However,the data update performance is often bottlenecked by the constrained cross-rack bandwidth.Various techniques have been proposed in the literature to improve network bandwidth efficiency,including delta transmission,relay,and batch update.These techniques were largely proposed individually previously,and in this work,we seek to use them jointly.To mitigate the cross-rack update traffic,we propose DXR-DU which builds on four valuable techniques:(i)delta transmission,(ii)XOR-based data update,(iii)relay,and(iv)batch update.Meanwhile,we offer two selective update approaches:1)data-deltabased update,and 2)parity-delta-based update.The proposed DXR-DU is evaluated via trace-driven local testbed experiments.Comprehensive experiments show that DXR-DU can significantly improve data update throughput while mitigating the cross-rack update traffic.

System Reliability Analysis for Truss Structures Based on Automatic Updated Model

Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.

Inference of interactions between players based on asynchronously updated evolutionary game data

The interactions between players of the prisoner's dilemma game are inferred using observed game data.All participants play the game with their counterparts and gain corresponding rewards during each round of the game.The strategies of each player are updated asynchronously during the game.Two inference methods of the interactions between players are derived with naive mean-field(n MF)approximation and maximum log-likelihood estimation(MLE),respectively.Two methods are tested numerically also for fully connected asymmetric Sherrington-Kirkpatrick models,varying the data length,asymmetric degree,payoff,and system noise(coupling strength).We find that the mean square error of reconstruction for the MLE method is inversely proportional to the data length and typically half(benefit from the extra information of update times)of that by n MF.Both methods are robust to the asymmetric degree but work better for large payoffs.Compared with MLE,n MF is more sensitive to the strength of couplings and prefers weak couplings.

Fast Verification of Network Configuration Updates

With the expansion of network services,large-scale networks have progressively become common.The network status changes rapidly in response to customer needs and configuration changes,so network configuration changes are also very frequent.However,no matter what changes,the network must ensure the correct conditions,such as isolating tenants from each other or guaranteeing essential services.Once changes occur,it is necessary to verify the after-changed network.Whereas,for the verification of large-scale network configuration changes,many current verifiers show poor efficiency.In order to solve the problem ofmultiple global verifications caused by frequent updates of local configurations in large networks,we present a fast configuration updates verification tool,FastCUV,for distributed control planes.FastCUV aims to enhance the efficiency of distributed control plane verification for medium and large networks while ensuring correctness.This paper presents a method to determine the network range affected by the configuration change.We present a flow model and graph structure to facilitate the design of verification algorithms and speed up verification.Our scheme verifies the network area affected by obtaining the change of the Forwarding Information Base(FIB)before and after.FastCUV supports rich network attributes,meanwhile,has high efficiency and correctness performance.After experimental verification and result analysis,our method outperforms the state-of-the-art method to a certain extent.

Multi-scale Incremental Analysis Update Scheme and Its Application to Typhoon Mangkhut(2018)Prediction

In the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in a model’s prognostic equations over a certain time window.This approach effectively reduces high-frequency oscillations introduced by data assimilation.However,as different scales of increments have unique evolutionary speeds and life histories in a numerical model,the traditional IAU scheme cannot fully meet the requirements of short-term forecasting for the damping of high-frequency noise and may even cause systematic drifts.Therefore,a multi-scale IAU scheme is proposed in this paper.Analysis increments were divided into different scale parts using a spatial filtering technique.For each scale increment,the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results.Finally,different scales of analysis increments were added to the model integration during their optimal relaxation time.The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale and small-scale increments in the model initialization stage.To evaluate its performance,several numerical experiments were conducted to simulate the path and intensity of Typhoon Mangkhut(2018)and showed that:(1)the multi-scale IAU scheme had an obvious effect on noise control at the initial stage of data assimilation;(2)the optimal relaxation time for large-scale and small-scale increments was estimated as 6 h and 3 h,respectively;(3)the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that of the traditional IAU scheme.The results demonstrate the superiority of the multi-scale IAU scheme.

Updates in the Diagnosis of Gestational Trophoblast Disease

GTD (Gestational Trophoblastic Disease) is a pathology that encompasses benign and malignant clinical forms, affects women of childbearing age, has a variable incidence and is more frequent in developing or underdeveloped countries, colliding with the economic barrier. The frequent absence of clear protocols and guidelines for the correct diagnosis of the pathology results in inadequate classification, imprecise treatment and failed post-therapeutic observation, increasing the risk of relapses, morbidity and mortality. The present study aims to point out updated national and international practice protocols of diagnosis of GTD, through an integrative review. Seven articles were selected and it was observed that the main international reference centers are agreed with the management suggested by the IFGO (International Federation of Gynecology and Obstetrics), being the conduct in the Hydatidiform Mole (HM): evacuation by suction and curettage under ultrasound guidance, followed by hCG monitoring every 1 - 2 weeks until normalized (usually one month for Partial Hydatidiform Mole six months for Complete Hydatidiform Mole and one year for Gestational Trophoblastic Neoplasia). Unfortunately, regarding the diagnosis of MH, the guidelines of some countries show the absence or difficulty of access to the karyotype test and ploid p57 or pelvic ultrasound accompanying the uterine curettage, contrary to what is proposed by the IFGO guideline. Establishing and complying with consistent guidelines can improve patient care, with early diagnosis of the pathology and its complications, reducing the rate of recurrence, morbidity and mortality, especially in less developed countries.

架设局域网内的Update服务器

越来越多的病毒利用微软操作系统的漏洞传播,及时给系统升级打补丁成了计算机管理的一项重要工作。在局域网内架设软件升级服务器,可以提高升级系统的效率。为计算机系统的安全运行提供保障。

BGP协议中UPDATE报文的并行化处理方法

互联网的规模日益扩大,作为域间路由协议标准的BGP协议,其性能面临着前所未有的考验.而路由更新(UPDATE)报文仍采用串行化的方式来处理,处理速度慢,极大地影响了BGP协议的性能.为此,提出一种UPDATE报文的并行化处理方法来解决这个问题.该方法采用流水线技术和多线程技术,能够提高UPDATE报文的处理速度.为了进一步提高该方法的效率,我们在UPDATE报文的并行化处理过程中引入了垃圾回收机制和多线程动态调节策略.最后,我们在Quagga原型系统上对该并行化处理方法进行了仿真实现,并与Quagga中原始的BGPD模块的测试结果进行了对比分析,实验结果表明,本文设计的UPDATE报文的并行化处理方法是可行且有效的.

ORACLE游标中的多表UPDATE行锁讨论

介绍了Oracle中的封锁机制,分析了共享更新封锁的特点,并就游标中的多表更新行锁以及怎样避免死锁错误进行了讨论.

Prediction of Temperature Daily Profile by Stochastic Update of Backpropagation through Time Algorithm

The authors will examine prediction of temperature daily profile using various modifications of BPTT （backpropagation through time algorithm） done by stochastic update in the artificial RCNN （recurrent neural networks）. The general introduction was provided by Salvetti and Wilamowski in 1994 in order to improve probability of convergence and speed of convergence. This update method has also one another quality, its implementation is simple for arbitrary network topology. In stochastic update scenario, constant number of weights/neurons is randomly selected and updated. This is in contrast to classical ordered update, where always all weights/neurons are updated. Stochastic update is suitable to replace classical ordered update without any penalty on implementation complexity and with good chance without penalty on quality of convergence. They have provided first experiments with stochastic modification on BP （backpropagation algorithm） used for artificial FFNN （feed-forward neural network） in detail described in the article ＂Stochastic Weight Update in the Backpropagation Algorithm on Feed-Forward Neural Networks＂ presented on the conference IJCNN （International Joint Conference of Neural Networks） 2010 in Barcelona. The BPTT on RCNN uses the history of previous steps stored inside of the NN that can be used for prediction. They will describe exact implementation on the RCNN, and present experiment results on temperature prediction with recurrent neural network topology. The dataset used for temperature prediction consists of the measured temperature from the year 2000 till the end of February 2011. Dataset is split into two groups： training dataset, which is provided to network in learning phase, and testing dataset, which is unknown part of dataset to NN and used to test the ability of NN to predict the temperature and the ability of NN to generalize the model hidden in the temperature profile. The results show promising properties of stochastic weight update with toy-task data, and the higher complexity of the temperature daily profile prediction.

Realization of remote update technology for embedded equipment based on μC/OS-Ⅱ

Aiming at the inaccessible problem of remote embedded devices update and maintenance, this paper presents a method using general packet radio service （GPRS） to achieve update based on the embedded real-time operating system （RTOS） μC/OS-Ⅱ. It introduces architecture of the system first. And then it uses LPC1768 chip as the central processing unit, SIM900A module for data transmission, and SST25VF016B to store the data. To ensure accuracy of the data transmis- sion, cyclic redundancy code （CRC） is adopted. The software uses fixed bootstrap and mutable update program, and thus the embedded devices can still normally start in case of update failure. Finally, high stability and extensive adaptability of the system are verified by experimental data.

拯救被禁用的Update功能

单击“开始”菜单上的“Windows Update”命令系统就会自动运行IE来连接网络，帮我们及时发现Windows的最新更新以使计算机保持最新最安全状态，但有些朋友在使用了某些优化软件之后，发现Windows Update功能被禁用导致无法自动更新了，右击“我的电脑”，选择“属性”，在“属性”窗口的“自动更新”标签中各选项都是灰色不可用状态，无法进行设置，此时该怎么办呢？按照下面的方法进行操作就可以了。