Ultra Reliable Load-Aware Connection Management(LACM)Algorithm in WIA-FA Systems

The increasing demand for industrial automation and intelligence has put forward higher requirements for the reliability of industrial wireless communication technology.As an international standard based on 802.11,Wireless networks for Industrial Automation-Factory Automation(WIA-FA)greatly improves the reliability in factory automation scenarios by Time Division Multiple Access(TDMA).However,in ultra-dense WIA-FA networks with mobile users,the basic connection management mechanism is inefficient.Most of the handover and resource management algorithms are all based on frequency division multiplexing,not suitable for the TDMA in the WIA-FA network.Therefore,we propose Load-aware Connection Management(LACM)algorithm to adjust the linkage and balance the load of access devices to avoid blocking and improve the reliability of the system.And then we simulate the algorithm to find the optimal settings of the parameters.After comparing with other existing algorithms,the result of the simulation proves that LACM is more efficient in reliability and maintains high reliability of more than 99.8%even in the ultra-dense moving scenario with 1500 field devices.Besides,this algorithm ensures that only a few signaling exchanges are required to ensure load bal-ancing,which is no more than 5 times,and less than half of the best state-of-the-art algorithm.

Seismic fragility analysis of three-tower cable-stayed bridges with different connection configurations

Seismic fragility analysis of three-tower cable-stayed bridges with three different structural systems,including rigid system(RS),floating system(FS),and passive energy dissipation system(PEDS),is conducted to study the effects of connection configurations on seismic responses and fragilities.Finite element models of bridges are established using OpenSees.A new ground motion screening method based on the statistical characteristic of the predominant period is proposed to avoid irregular behavior in the selection process of ground motions,and incremental dynamic analysis(IDA)is performed to develop components and systems fragility curves.The effects of damper failure on calculated results for PEDS are examined in terms of seismic response and fragility analysis.The results show that the bridge tower is the most affected component by different structural systems.For RS,the fragility of the middle tower is significantly higher than other components,and the bridge failure starts from the middle tower,exhibiting a characteristic of local failure.For FS and PEDS,the fragility of the edge tower is higher than the middle tower.The system fragility of RS is higher than FS and PEDS.Taking the failure of dampers into account is necessary to obtain reliable seismic capacity of cable-stayed bridges.

Electromechanical Transient Modeling Analysis of Large-Scale New Energy Grid Connection

The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous machine.It also has the same inertia,damping,frequency,voltage regulation,and other external performance as the generator.It is the key technology to realize new energy grid connections’stable and reliable operation.This project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor.A new energy storage method is proposed.The mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power,state of charge,operation efficiency,dead zone,and inverter constraint.The rapid conversion of energy storage devices absorbs the excess instantaneous kinetic energy caused by interference.The branch transient of the critical cut set in the system can be confined to a limited area.Thus,the virtual synchronizer’s kinetic and potential energy can be efficiently converted into an instantaneous state.The simulation of power system analysis software package(PSASP)verifies the correctness of the theory and algorithm in this paper.This paper provides a theoretical basis for improving the transient stability of new energy-connected power grids.

Cost Optimization of Steel Beam-to-Column Connections using AVOA

The joint-bolt-African Vulture optimization algorithm(AVOA)model is proposed for the design of building connections to improve the stability of steel beam-to-column connections.For this algorithm,the type of steel is first determined,and the number of bolts needed by the corresponding steel type is referenced in Eurocode 3.Then,the bearing capacity of the joint can be calculated.The joint-bolt-AVOA model is established by substituting the bolt number required by the steel into the algorithm to obtain the optimal bolt number required while ensuring joint stability.The results show that the number of bolts required by the joint-bolt-AVOA model based on the stability of steel is lower than that calculated by Eurocode 3.Therefore,AVOA can effectively optimize the number of bolts needed in building connections and save resources.

改进RRT-Connect与DWA算法的巡检机器人路径规划研究

针对传统RRT-Connect算法在密集复杂环境中路径规划效率低、动态避障效果差等问题,提出一种改进RRT-Connect与DWA融合算法。该算法通过改进采样策略、动态步长优化和碰撞检测引导随机树生长;在随机树中采用贪心策略和角度约束优化路径。基于巡检机器人建立运动学模型,通过速度采样空间生成轨迹簇;建立模糊逻辑系统自适应调整DWA算法评价函数的权重系数,将全局最优路径点融入DWA算法中实现全局最优路径和实时避障。仿真结果表明,在油气站场密集复杂环境中,改进RRT-Connect算法较传统算法路径缩短约27.09%,平滑度提高约84.6%,碰撞距离提高约18.75%;改进融合算法路径减少约2.97%,平滑度提高约78.8%,碰撞距离提高约30.6%,验证了提出算法的有效性。

基于逆向重布线改进RRT-Connect算法的机械臂路径规划

为解决RRT-Connect算法在复杂非结构环境下规划出的路径成本较长、有效节点数过多、曲折不平滑等问题,提出了一种基于逆向重布线的改进RRT-Connect算法(Improved-RRT-Connect).首先,在算法的起始位置加入碰撞检测函数,当起点和终点之间不存在障碍物时,能够快速生成一条路径;其次,通过对生成的路径采取逆向重布线的措施,对生成的路径中的节点进行重新筛选布线,达到缩短生成路径长度,减少有效节点数量的目的;最后,通过结合B样条曲线对生成的路径进行拟合处理,得到一条平滑连续的路径.通过Improved-RRT-Connect算法与RRT、RRT^(*)-Smart、RRT-Connect等算法的对比实验表明,在规划时间上,Improved-RRT-Connect算法比RRT、RRT^(*)-Smart算法减少了52.14%、98.53%,在路径成本上比RRT、RRT-Connect算法减少了19.39%、17.15%,阐明了提出的Improved-RRT-Connect算法的优越性.

基于改进RRT-Connect算法的全局路径规划

针对RRT-Connect算法在复杂环境内的路径规划中存在探索性弱、收敛速度慢、冗余节点多、搜索路径较长等问题,提出一种改进的RRT-Connect算法。通过引入高质量随机点和动态步长的方法,提高了生成随机树的质量并减少了冗余节点数量;采用正向寻优和逆向贪婪的方式,改善了搜索路径较长的问题。实验结果表明,改进RRT-Connect算法平均路径规划时间缩短26.41%,平均路径规划长度缩短19.05%,平均路径规划节点个数减少41.91%,证明了改进RRT-Connect算法相比于原算法规划效率更高,规划时间更少,规划路径质量更优。

Approximately Bi-Similar Symbolic Model for Discretetime Interconnected Switched System

Dear Editor,This letter concerns the development of approximately bi-similar symbolic models for a discrete-time interconnected switched system(DT-ISS).The DT-ISS under consideration is formed by connecting multiple switched systems known as component switched systems(CSSs).Although the problem of constructing approximately bi-similar symbolic models for DT-ISS has been addressed in some literature,the previous works have relied on the assumption that all the subsystems of CSSs are incrementally input-state stable.

Research on Quantitative Identification of Three-Dimensional Connectivity of Fractured-Vuggy Reservoirs

The fractured-vuggy carbonate oil resources in the western basin of China are extremely rich.The connectivity of carbonate reservoirs is complex,and there is still a lack of clear understanding of the development and topological structure of the pore space in fractured-vuggy reservoirs.Thus,effective prediction of fractured-vuggy reservoirs is difficult.In view of this,this work employs adaptive point cloud technology to reproduce the shape and capture the characteristics of a fractured-vuggy reservoir.To identify the complex connectivity among pores,fractures,and vugs,a simplified one-dimensional connectivity model is established by using the meshless connection element method(CEM).Considering that different types of connection units have different flow characteristics,a sequential coupling calculation method that can efficiently calculate reservoir pressure and saturation is developed.By automatic history matching,the dynamic production data is fitted in real-time,and the characteristic parameters of the connection unit are inverted.Simulation results show that the three-dimensional connectivity model of the fractured-vuggy reservoir built in this work is as close as 90%of the fine grid model,while the dynamic simulation efficiency is much higher with good accuracy.

Joint Allocation of Computing and Connectivity Resources in Survivable Inter-Datacenter Elastic Optical Networks

Inter-datacenter elastic optical networks(EON)need to provide the service for the requests of cloud computing that require not only connectivity and computing resources but also network survivability.In this paper,to realize joint allocation of computing and connectivity resources in survivable inter-datacenter EONs,a survivable routing,modulation level,spectrum,and computing resource allocation algorithm(SRMLSCRA)algorithm and three datacenter selection strategies,i.e.Computing Resource First(CRF),Shortest Path First(SPF)and Random Destination(RD),are proposed for different scenarios.Unicast and manycast are applied to the communication of computing requests,and the routing strategies are calculated respectively.Simulation results show that SRMLCRA-CRF can serve the largest amount of protected computing tasks,and the requested calculation blocking probability is reduced by 29.2%,28.3%and 30.5%compared with SRMLSCRA-SPF,SRMLSCRA-RD and the benchmark EPS-RMSA algorithms respectively.Therefore,it is more applicable to the networks with huge calculations.Besides,SRMLSCRA-SPF consumes the least spectrum,thereby exhibiting its suitability for scenarios where the amount of calculation is small and communication resources are scarce.The results demonstrate that the proposed methods realize the joint allocation of computing and connectivity resources,and could provide efficient protection for services under single-link failure and occupy less spectrum.

MSADCN:Multi-Scale Attentional Densely Connected Network for Automated Bone Age Assessment

Bone age assessment(BAA)helps doctors determine how a child’s bones grow and develop in clinical medicine.Traditional BAA methods rely on clinician expertise,leading to time-consuming predictions and inaccurate results.Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations.This operation is costly and subjective.To address these problems,we propose a multi-scale attentional densely connected network(MSADCN)in this paper.MSADCN constructs a multi-scale dense connectivity mechanism,which can avoid overfitting,obtain the local features effectively and prevent gradient vanishing even in limited training data.First,MSADCN designs multi-scale structures in the densely connected network to extract fine-grained features at different scales.Then,coordinate attention is embedded to focus on critical features and automatically locate the regions of interest(ROI)without additional annotation.In addition,to improve the model’s generalization,transfer learning is applied to train the proposed MSADCN on the public dataset IMDB-WIKI,and the obtained pre-trained weights are loaded onto the Radiological Society of North America(RSNA)dataset.Finally,label distribution learning(LDL)and expectation regression techniques are introduced into our model to exploit the correlation between hand bone images of different ages,which can obtain stable age estimates.Extensive experiments confirm that our model can converge more efficiently and obtain a mean absolute error(MAE)of 4.64 months,outperforming some state-of-the-art BAA methods.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Soft connectivity of standards boosts high-quality Belt and Road development

Shaanxi province serves as an important part in the Belt and Road cooperation,which is also at the forefront of China’s westward opening up.It also shoulders the significant missions of implementing national strategies including the ecological protection and high-quality development of the Yellow River Basin and the Western Region Development Strategy.

The Gut Brain Connection

The gut-brain connection is a bidirectional communication system that links the gut microbiome to the central nervous system (CNS). The gut-brain axis communicates through a variety of mechanisms, including the release of hormones, neurotransmitters, and cytokines. These signaling molecules can travel from the gut to the brain and vice versa, influencing various physiological and cognitive functions. Emerging therapeutic strategies targeting the gut-brain connection include probiotics, prebiotics, and faecal microbiota transplantation (FMT). Probiotics are live microorganisms that are similar to the beneficial bacteria that are naturally found in the gut. Prebiotics are non-digestible fibers that feed the beneficial bacteria in the gut. FMT is a procedure in which faecal matter from a healthy donor is transplanted into the gut of a person with a diseased microbiome. Probiotics, prebiotics, and FMT have been shown to be effective in treating a variety of gastrointestinal disorders, and there is growing evidence that they may also be effective in treating neurological and psychiatric disorders. This review explores the emerging field of the gut-brain connection, focusing on the communication pathways between the gut microbiome and the central nervous system. We summarize the potential roles of gut dysbiosis in various neurological and psychiatric disorders. Additionally, we discuss potential therapeutic strategies, research limitations, and future directions in this exciting area of research. More research is needed to fully understand the mechanisms underlying the gut-brain connection and to develop safe and effective therapies that target this pathway. However, the findings to date are promising, and there is the potential to revolutionize the way we diagnose and treat a variety of neurological and psychiatric disorders.

Brain mechanism of acupuncture for children with anisometropic amblyopia: a resting functional magnetic resonance imaging study based on voxel-mirrored homotopic connectivity

AIM:To explore the brain mechanism of acupuncture for children with anisometropic amblyopia using the voxelmirror homotopic connectivity(VMHC)analysis method of resting functional magnetic resonance imaging(rs-fMRI)technology based on clinical effectiveness.METHODS:Eighty children with anisometropic monocular amblyopia were randomly divided into two groups:control(40 cases,1 case of shedding)and acupuncture(40 cases,1 case of shedding)groups.The control group was treated with glasses,red flash,grating,and visual stimulations,with each procedure conducted for 5min per time.Based on routine treatment,the acupuncture group underwent acupuncture of“regulating qi and unblocking meridians to bright eyes”,Jingming(BL1),Cuanzhu(BL2),Guangming(GB37),Fengchi(GB20)acupoints were taken on both sides,with the needle kept for 30min each time.Both groups were treated once every other day,three times per week,for a total of 4wk.After the treatment,the overall curative effect of the two groups and the latency and amplitude changes of P100 wave of pattern visual-evoked potential were counted.At the same time,nine children with left eye amblyopia were randomly selected from the two groups and were scanned with rsfMRI before and after treatment.The differences in the brain regions between the two groups were compared and analyzed with VMHC.RESULTS:Chi-square test showed a notable difference in the total efficiency rate between the acupuncture(94.87%)and control groups(79.49%).Regarding the P100 wave latency and amplitude,the acupuncture group had significantly shorter latency and higher amplitude of P100 wave than the control group.Moreover,the VMHC values of the bilateral temporal lobe,superior temporal gyrus,and middle temporal gyrus were notably increased in the acupuncture group after treatment.CONCLUSION:Acupuncture combined with conventional treatment can significantly improve the corrected visual acuity and optic nerve conduction in children with anisometropic amblyopia.Compared with the conventional treatment,the regulation of acupuncture on the functional activities of the relevant brain areas in the anterior cerebellum may be an effective acupuncture mechanism for anisometropic amblyopia.

The Launching Ceremony of the Silk Road People-to-People Connectivity Donation Activity"Care for the Future"Held in Yangon

The launching ceremony of the Silk Road Peopleto-People"Connectivity donation activity"Care for the Future was jointly held by China Foundation for Peace and Development and the Myanmar-Chinese Cooperation&Communication Centre in Yangon on January 16.The Yangjin Middle School in Yangon Province of Myanmar received football,volleyball,badminton,notebooks,LED lights and other school utensils and sporting goods.

Assessment of sediment connectivity using modelling and field-based approaches in the Slavíč River catchment(MoravskoslezskéBeskydy Mts,Czech Republic)

Mountain streams act as conveyors of sediments within the river continuum,where the physical transport of sediments between river reaches through the catchment or between individual parts(e.g.,between hillslopes and channels)of the catchment is assumed.This study focused on sediment connectivity analysis in the SlavíčRiver catchment in the MoravskoslezskéBeskydy Mts in the eastern part of the Czech Republic.The connectivity index and connectivity index target modelling were combined with an analysis of anthropogenic interventions.Additionally,field mapping,grain size of bed sediments and stream power analysis were used to obtain information about connectivity in the catchment.Based on the analysis and obtained results,terrain topography is the current main driving factor affecting the connectivity of sediment movement in the SlavíčRiver catchment.However,the modelling provided valuable information about high sediment connectivity despite different recent land use conditions(highly forested area of the catchment)than those in historical times from the 16th to 19th centuries when the SlavíčRiver catchment was highly deforested and sediment connectivity was probably higher.The analysis of anthropogenic interventions,field mapping,grain size of bed sediments and stream power analysis revealed more deceleration of sediment movement through the catchment,decreased sediment connectivity with bed erosion,and gradual river channel process transformation in some reaches.Field mapping has identified various natural formations and human-induced changes impacting the longitudinal and lateral connectivity in the SlavíčRiver.For instance,embankments along 48%of the river's length,both on the right and left banks,significantly hinder lateral sediment supply to the channel.Stream power index analysis indicates increased energy levels in the flowing water in the river's upper reaches(up to 404.8 W m^(-2)).This high energy is also observed in certain downstream sections(up to 337.6 W m^(-2)),where it is influenced by human activities.These conditions lead to intensified erosion processes,playing a crucial role in sediment connectivity.Similar observations were described in recent studies that pointed out the long-term human interventions on many streams draining European mountains,where a decrease in sediment connectivity in these streams is linked with sediment deficits and the transformation of processes forming channels.

"Silk Road People-to-People Connectivity"China-Myanmar Friendly Cultural and Educational Exchanges Held inYangon

On January 1Oth,at the invitation of the Yangon University of Foreign Languages for its Cultural Exchanges Week,the China Foundation for Peace and Development and the Myanmar Chinese Cooperation&Communication Centre,jointly organised the"Silk Road People-to-People Connectivity"China-Myanmar Friendly Cultural and Educational Exchange activity.U Soe Thein,Chief Minister of Yangon Province,Zaw Myint,Deputy Minister of Education of Myanmar,and Kyi Shwin,President of Yangon University of Foreign Languages,attended the activity and delivered speeches.

Age-related hearing loss accelerates the decline in fast speech comprehension and the decompensation of cortical network connections

Patients with age-related hearing loss face hearing difficulties in daily life.The causes of age-related hearing loss are complex and include changes in peripheral hearing,central processing,and cognitive-related abilities.Furthermore,the factors by which aging relates to hearing loss via changes in audito ry processing ability are still unclear.In this cross-sectional study,we evaluated 27 older adults(over 60 years old) with age-related hearing loss,21 older adults(over 60years old) with normal hearing,and 30 younger subjects(18-30 years old) with normal hearing.We used the outcome of the uppe r-threshold test,including the time-compressed thres h old and the speech recognition threshold in noisy conditions,as a behavioral indicator of auditory processing ability.We also used electroencephalogra p hy to identify presbycusis-related abnormalities in the brain while the participants were in a spontaneous resting state.The timecompressed threshold and speech recognition threshold data indicated significant diffe rences among the groups.In patients with age-related hearing loss,information masking(babble noise) had a greater effect than energy masking(speech-shaped noise) on processing difficulties.In terms of resting-state electroencephalography signals,we observed enhanced fro ntal lobe(Brodmann’s area,BA11) activation in the older adults with normal hearing compared with the younger participants with normal hearing,and greater activation in the parietal(BA7) and occipital(BA19) lobes in the individuals with age-related hearing loss compared with the younger adults.Our functional connection analysis suggested that compared with younger people,the older adults with normal hearing exhibited enhanced connections among networks,including the default mode network,sensorimotor network,cingulo-opercular network,occipital network,and frontoparietal network.These results suggest that both normal aging and the development of age-related hearing loss have a negative effect on advanced audito ry processing capabilities and that hearing loss accele rates the decline in speech comprehension,especially in speech competition situations.Older adults with normal hearing may have increased compensatory attentional resource recruitment represented by the to p-down active listening mechanism,while those with age-related hearing loss exhibit decompensation of network connections involving multisensory integration.

Topological Aspects of Dendrimers via Connection-Based Descriptors

Topological indices(TIs)have been practiced for distinct wide-ranging physicochemical applications,especially used to characterize and model the chemical structures of various molecular compounds such as dendrimers,nanotubes and neural networks with respect to their certain properties such as solubility,chemical stability and low cytotoxicity.Dendrimers are prolonged artificially synthesized or amalgamated natural macromolecules with a sequential layer of branches enclosing a central core.A present-day trend in mathematical and computational chemistry is the characterization of molecular structure by applying topological approaches,including numerical graph invariants.Among topological descriptors,Zagreb connection indices(ZCIs)have much importance.This manuscript involves the establishment of general results to calculate ZCIs,namely first ZCI(FZCI),second ZCI(SZCI),third ZCI(TZCI),modified FZCI,modified SZCI and modified TZCI of two special types of dendrimers nanostars,namely,poly propylene imine octamin(PPIO)dendrimer and poly(propyl)ether imine(PPEtIm)dendrimer.Furthermore,we provide the numerical and graphical comparative analysis of our calculated results for both types of dendrimers with each other.