Lightweight Design and Verification of Gantry Machining Center Crossbeam Based on Structural Bionics

The lightweight and high efficiency of natural structures are the inexhaustible sources for engineering improvements. The goal of the study is to find innovative solutions for mechanical lightweight design through the application of structural bionic approaches. Giant waterlily leaf ribs and cactus stem are investigated for their optimal framework and superior performance. Their structural characteristics are extracted and used in the bio-inspired design of Lin MC6000 gantry machining center crossbeam. By mimicking analogous network structure, the bionic model is established, which has better load-carrying capacity than conventional distribution. Finite Element Method （FEM） is used for numerical simulation. Results show better specific stiffness of the bionic model, which is increased by 17.36%. Finally the scaled models are fabricated by precision casting for static and dynamic tests. The physical experiments are compared to numerical simulation. The results show that the maximum static deformation of the bionic model is reduced by about 16.22%, with 3.31% weight reduction. In addition, the first four natural frequencies are improved obviously. The structural bionic design is a valuable reference for updating conventional mechanical structures with better performance and less material consumption.

Emodin prevents hypoxic-ischemic neuronal injury Involvement of the activin A pathway

Emodin, an extract of dried rhizomes and the root of the Rhizoma Polygoni Cuspidati, can protect neurons from hypoxic-ischemic brain damage. This study aimed to verify the underlying mechanism After PC12 cells had differentiated into neuron-like cells under the induction of mouse nerve growth factor, cells were subjected to oxygen-glucose deprivation and treated with emodin. Results shewed that the viability of neuron-like cells cultured under an ischemia-hypoxia environment decreased, while the expression of activin A and caspase-3 in cells increased. Emodin raised the survival rate of oxygen-glucose deprived neuron-like cells~ increased activin A expression, and decreased caspase-3 expression. Experimental findings indicate that emodin can inhibit neuronal apoptosis and alleviate the injury of nerve cells after oxygen-glucose deprivation through the activin A pathway.

Activin A prevents neuron-like PC12 cell apoptosis after oxygen-glucose deprivation

In this study, PC12 cells were induced to differentiate into neuron-like cells using nerve growth factor, and were subjected to oxygen-glucose deprivation. Cells were treated with 0, 10, 20, 30, 50, 100 ng/mL exogenous Activin A. The 3-（4,5-dimethyl-2-thiazolyl）-2,5-diphenyl tetrazolium bromide assay and Hoechst 33324 staining showed that the survival percentage of PC12 cells significantly decreased and the rate of apoptosis significantly increased after oxygen-glucose deprivation. Exogenous Activin A significantly increased the survival percentage of PC12 cells in a dose-dependent manner. Reverse transcription-PCR results revealed a significant increase in Activin receptor IIA, Smad3 and Smad4 mRNA levels, which are key sites in the Activin A/Smads signaling pathway, in neuron-like cells subjected to oxygen-glucose deprivation, while mRNA expression of the apoptosis-regulation gene caspase-3 decreased. Our experimental findings indicate that exogenous Activin A plays an anti-apoptotic role and protects neurons by means of activating the Activin A/Smads signaling pathway.

Use of RNAi silencing to target preconditioned glial cell line-derived neurotrophic factor in neuronal apoptosis

Several studies have suggested that exogenous glial cell line-derived neurotrophic factor may pro-tect neurons from cerebral ischemic injury. However, the mechanisms underlying the neuroprotec-tive effects of endogenous glial cell line-derived neurotrophic factor remain unclear. The present experiments sought to elucidate the influence of various conditioned media on neuronal apoptosis, using a normal culture medium for astrocytes, an astrocyte medium highly expressing glial cell line-derived neurotrophic factor, and an astrocyte medium in which glial cell line-derived neurotro-phic factor expression was silenced using RNAi technology. The results confirmed that the use of RNAi silencing to target pretreated glial cell line-derived neurotrophic factor expression promoted neuronal apoptosis. In addition, oxygen and glucose deprivation preconditioning was found to upregulate glial cell line-derived neurotrophic factor expression, and significantly reduce neuronal apoptosis.

A PageRank-Based WeChat User Impact Assessment Algorithm

In recent years,the mobile Internet has developed rapidly,and the network social platform has emerged as the times require,and more people make friends,chat and share dynamics through the network social platform.The network social platform is the virtual embodiment of the social network,each user represents a node in the directed graph of the social network.As the most popular online social platform in China,WeChat has developed rapidly in recent years.Large user groups,powerful mobile payment capabilities,and massive amounts of data have brought great influence to it.At present,the research on WeChat network at home and abroad mainly focuses on communication and sociology,but the research from the angle of influence is scarce.Therefore,based on the basic principle of PageRank,this paper proposes an influence evaluation model WURank algorithm suitable for WeChat network users.This algorithm takes into account the shortcomings of the traditional PageRank algorithm,and objectively evaluates the real-time influence of WeChat users from the perspective of WeChat user behavior(including:sharing,commenting,mentioning,collecting,likes)and time factors.

WITHDRAWN: A PageRank-Based WeChat User Impact Assessment Algorithm

The publisher regrets that a technical error occurred,which led to the duplicate publication.We apologize to the authors and the readers for this unfortunate error and any inconvenience this may have caused.

Withdrawal notice to: A PageRank-Based WeChat User Impact Assessment Algorithm

The publisher regrets that a technical error occurred,which led to the duplicate publication.We apologize to the authors and the readers for this unfortunate error and any inconvenience this may have caused.

Real‑Time Optimal Trajectory Planning for Autonomous Driving with Collision Avoidance Using Convex Optimization

An online trajectory planning method for collision avoidance is proposed to improve vehicle driving safety and comfort simultaneously.The collision-free trajectory for autonomous driving is formulated as a nonlinear optimization problem.A novel approximate convex optimization approach is developed for the online optimal trajectory in both longitudinal and lateral directions.First,a dual variable is used to model the non-convex collision-free constraint for driving safety and is calculated by solving a dual problem of the relative distance between vehicles.Second,the trajectory is further optimized in a model predictive control framework considering the safety.It realizes continuous-time and dynamic feasible motion with collision avoidance.The geometry of object vehicles is described by polygons instead of circles or ellipses in traditional methods.In order to avoid aggressive maneuver in the longitudinal and lateral directions for driving comfort,rates of the acceleration and the steering angle are restricted.The final formulated optimization problem is convex,which can be solved by using quadratic programming solvers and is computationally efficient for online application.Simulation results show that this approach can obtain similar driving performance compared to a state-of-the-art nonlinear optimization method.Furthermore,various driving scenarios are tested to evaluate the robustness and the ability for handling complex driving tasks.

Analysis and mitigation of bump magnetic field tracking errors in a multiturn injection system

Purpose The Space Environment Simulation and Research Infrastructure(SESRI)is a cluster of accelerators designed to simulate the cosmic radiation environment by generating particles of various types and energies.Among these accelerators,a synchrotron in the 300 MeV proton and heavy ion accelerator complex utilizes a multiturn injection scheme with four bump magnets to accumulate proton and heavy ion beams effectively.However,the bump magnetic field experiences a rapid drop rate of up to 1000 T/s,inevitably leading to a deviation(field tracking error)from the ideal magnetic field.The injection efficiency and particle distribution are significantly affected by this field tracking error,as evaluated by the ACCSIM code.Method During the device testing stage,the sources of field tracking errors were identified by analysis of the bump power supplies and the field of the magnets.Mitigation techniques were then implemented to reduce the field tracking error from[Math Processing Error]to[Math Processing Error]throughout the entire power supply,transmission cable,and magnet chain.Results Moreover,the successful injection and accumulation of beams during the operational phase of the synchrotron confirmed the effectiveness of the proposed mitigation methods.Additionally,a magnetic field measurement system was developed to monitor the magnetic field tracking error online.Conclusion The combination of the field tracking error mitigation methods and the measurement system provides valuable guidance for optimizing the magnetic fields with rapid drop rates.

Survey on Artificial Intelligence for Vehicles

With the ever-increasing demand in urban mobility and modern logistics sector,the vehicle population has been steadily growing over the past several decades.One natural consequence of the vehicle population growth is the increase in traffic congestion.Almost all(metropolitan)cities including the major ones,like Los Angeles,Beijing,New York,are suffering from heavy traffic congestion.Statistics show that,in 2015,43 cities in China are suffering a prolonged travel time of more than 1.5 h every day during rush hours.In the meanwhile,traffic accidents are plaguing the economic development as well.

Correction to:Survey on Artificial Intelligence for Vehicles

This paper surveys the literature of Artificial Intelligence for Vehicles(AIV)and gives out the current status and next generation of AIV.The two branches of artificial intelligence,namely Practical Artificial Intelligence(PAI)and Advanced Artificial Intelligence(AAI)are rigorously reviewed.Two of the currently prevailing AIV use cases such as autonomous vehicles and connected vehicles are reviewed,and the key technologies in AIV such as world model,planner and decision maker,computing platform and canonical AV use cases are presented in the paper.The paper also serves as a guidance for the future development of artificial intelligence for vehicles.