Localized Mobility Management for SDN-Integrated LTE Backhaul Networks

Small cell (SCell) and Software Define Network (SDN) are two key enablers to meet the evolutional requirements of future telecommunication networks, but still on the initial study stage with lots of challenges faced. In this paper, the problem of mobility management in SDN-integrated LTE (Long Term Evolution) mobile backhaul network is investigated. An 802.1ad double tagging scheme is designed for traffic forwarding between Serving Gateway (S-GW) and SCell with QoS (Quality of Service) differentiation support. In addition, a dynamic localized forwarding scheme is proposed for packet delivery of the ongoing traffic session to facilitate the mobility of UE within a dense SCell network. With this proposal, the data packets of an ongoing session can be forwarded from the source SCell to the target SCell instead of switching the whole forwarding path, which can drastically save the path-switch signalling cost in this SDN network. Numerical results show that compared with traditional path switch policy, more than 50 signalling cost can be reduced, even considering the impact on the forwarding path deletion when session ceases. The performance of data delivery is also analysed, which demonstrates the introduced extra delivery cost is acceptable and even negligible in case of short forwarding chain or large backhaul latency

An Agent-based Modelling Framework for Driving Policy Learning in Connected and Autonomous Vehicles

Due to the complexity of the natural world, a programmer cannot foresee all possible situations, a connected and autonomous vehicle (CAV) will face during its operation, and hence, CAVs will need to learn to make decisions autonomously. Due to the sensing of its surroundings and information exchanged with other vehicles and road infrastructure, a CAV will have access to large amounts of useful data. While different control algorithms have been proposed for CAVs, the benefits brought about by connectedness of autonomous vehicles to other vehicles and to the infrastructure, and its implications on policy learning has not been investigated in literature. This paper investigates a data driven driving policy learning framework through an agent-based modelling approaches. The contributions of the paper are two-fold. A dynamic programming framework is proposed for in-vehicle policy learning with and without connectivity to neighboring vehicles. The simulation results indicate that while a CAV can learn to make autonomous decisions, vehicle-to-vehicle (V2V) communication of information improves this capability. Furthermore, to overcome the limitations of sensing in a CAV, the paper proposes a novel concept for infrastructure-led policy learning and communication with autonomous vehicles. In infrastructure-led policy learning, road-side infrastructure senses and captures successful vehicle maneuvers and learns an optimal policy from those temporal sequences, and when a vehicle approaches the road-side unit, the policy is communicated to the CAV. Deep-imitation learning methodology is proposed to develop such an infrastructure-led policy learning framework

Ultrathin MgB2 films fabricated on Al2O3 substrate by hybrid physical-chemical vapor deposition with high Tc and Jc

Ultrathin MgB2 superconducting films with a thickness down to 7.5 nm are epitaxially grown on (0001) Al2O3 substrate by hybrid physical-chemical vapor deposition method. The films are phase-pure, oxidation-free and continuous. The 7.5 nm thin film shows a Tc(0) of 34 K, which is so far the highest Tc(0) reported in MgB2 with the same thickness. The critical current density of ultrathin MgB2 films below 10 nm is demonstrated for the first time as Jc ~ 10^6 A cm^{-2} for the above 7.5 nm sample at 16 K. Our results reveal the excellent superconducting properties of ultrathin MgB2 films with thicknesses between 7.5 and 40 nm on Al2O3 substrate.Comment: 7 pages, 4 figures, 2 table

The effects of new urbanization pilot city policies on urban innovation: Evidence from China

The new urbanization city pilot policy is China’s most recent policy on urban urbanization. This paper uses new urbanization pilot policies as a quasi-natural experiment to empirically test the impact of new urbanization pilot policies on urban innovation through the difference-in-differences (DID) method using panel data from 199 cities in China from 2011 to 2019. The results show that: (1) The new urbanization city pilot policy has significantly enhanced urban innovation. (2) The theoretical mechanism test shows that the pilot policy of new urbanization promotes urban innovation through the level of human capital. (3) The results of the heterogeneity analysis show that the new urbanization pilot policies have obvious city-level heterogeneity and regional heterogeneity on the improvement of urban innovation levels. The impact effect of new urbanization pilot policies is higher in first-tier and second-tier cities than in fourth-tier and fifth-tier cities; the effect of new urbanization pilot policies is higher in western regions than in eastern and middle regions.National Natural Science Foundation of Chin

Cloud-Assisted Safety Message Dissemination in VANET-Cellular Heterogeneous Wireless Network

Abstract-In vehicular ad-hoc networks (VANETs), efficient message dissemination is critical to road safety and traffic efficiency. Since many VANET-based schemes suffer from high transmission delay and data redundancy, integrated VANETcellular heterogeneous network has been proposed recently and attracted significant attention. However, most existing studies focus on selecting suitable gateways to deliver safety message from the source vehicle to a remote server, while rapid safety message dissemination from the remote server to a targeted area has not been well studied. In this paper, we propose a framework for rapid message dissemination that combines the advantages of diverse communication and cloud computing technologies

Ultrasound microbubble-mediated delivery of the siRNAs targeting MDR1 reduces drug resistance of yolk sac carcinoma L2 cells

<p>Abstract</p> <p>Background</p> <p>MDR1 gene encoding P-glycoprotein is an ATP-dependent drug efflux transporter and related to drug resistance of yolk sac carcinoma. Ultrasound microbubble-mediated delivery has been used as a novel and effective gene delivery method. We hypothesize that small interfering RNA (siRNA) targeting MDR1 gene (siMDR1) delivery with microbubble and ultrasound can down-regulate MDR1 expression and improve responsiveness to chemotherapeutic drugs for yolk sac carcinoma <it>in vitro</it>.</p> <p>Methods</p> <p>Retroviral knockdown vector pSEB-siMDR1s containing specific siRNA sites targeting rat MDR1 coding region were constructed and sequence verified. The resultant pSEB-siMDR1 plasmids DNA were encapsulated with lipid microbubble and the DNA release were triggered by ultrasound when added to culture cells. GFP positive cells were counted by flow cytometry to determine transfection efficiency. Quantitative real-time PCR and western blot were performed to determine the mRNA and protein expression of MDR1. P-glycoprotein function and drug sensitivity were analyzed by Daunorubicin accumulation and MTT assays.</p> <p>Results</p> <p>Transfection efficiency of pSEB-siMDR1 DNA was significantly increased by ultrasound microbubble-mediated delivery in rat yolk sac carcinoma L2 (L2-RYC) cells. Ultrasound microbubble-mediated siMDR1s delivery effectively inhibited MDR1 expression at both mRNA and protein levels and decreased P-glycoprotein function. Silencing MDR1 led to decreased cell viability and IC₅₀of Vincristine and Dactinomycin.</p> <p>Conclusions</p> <p>Our results demonstrated that ultrasound microbubble-mediated delivery of MDR1 siRNA was safe and effective in L2-RYC cells. MDR1 silencing led to decreased P-glycoprotein activity and drug resistance of L2-RYC cells, which may be explored as a novel approach of combined gene and chemotherapy for yolk sac carcinoma.</p

Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication are emerging components of intelligent transport systems (ITS) based on which vehicles can drive in a cooperative way and, hence, significantly improve traffic flow efficiency. However, due to the high vehicle mobility, the unreliable vehicular communications such as packet loss and transmission delay can impair the performance of the cooperative driving system (CDS). In addition, the downstream traffic information collected by roadside sensors in the V2I communication may introduce measurement errors, which also affect the performance of the CDS. The goal of this paper is to bridge the gap between traffic flow modelling and communication approaches in order to build up better cooperative traffic systems. To this end, we aim to develop an enhanced cooperative microscopic (car-following) traffic model considering V2V and V2I communication (or V2X for short), and investigate how vehicular communications affect the vehicle cooperative driving, especially in traffic disturbance scenarios. For these purposes, we design a novel consensus-based vehicle control algorithm for the CDS, in which not only the local traffic flow stability is guaranteed, but also the shock waves are supposed to be smoothed. The IEEE 802.11p, the defacto vehicular networking standard, is selected as the communication protocols, and the roadside sensors are deployed to collect the average speed in the targeted area as the downstream traffic reference. Specifically, the imperfections of vehicular communication as well as the measured information noise are taken into account. Numerical results show the efficiency of the proposed scheme. This paper attempts to theoretically investigate the relationship between vehicular communications and cooperative driving, which is needed for the future deployment of both connected vehicles and infrastructure (i.e. V2X

Improvement of type declaration of the IEC 61499 basic function block for developing applications of cyber-physical system

The cyber-physical system relies on a network of physical devices. The IEC 61499 standard entails a systematic solution to distributed system development. The basic function block (BFB) is the essential construct of the IEC 61499 architecture. However, the execution semantics of the BFB is not well defined by the standard, which leads to a part of the semantic ambiguity. In this paper, we contribute to improve BFB type declaration by proposing a compact interface model and a strict execution control chart (ECC) model. The improved BFB exhibits less semantic ambiguity, is easier to be created, and is more convenient to be applied in a function block network than the standard BFB

Study on Damage Evaluation and Machinability of UD-CFRP for the Orthogonal Cutting Operation Using Scanning Acoustic Microscopy and the Finite Element Method

Owing to high specific strength and designability, unidirectional carbon fiber reinforced polymer (UD-CFRP) has been utilized in numerous fields to replace conventional metal materials. Post machining processes are always required for UD-CFRP to achieve dimensional tolerance and assembly specifications. Due to inhomogeneity and anisotropy, UD-CFRP differs greatly from metal materials in machining and failure mechanism. To improve the efficiency and avoid machining-induced damage, this paper undertook to study the correlations between cutting parameters, fiber orientation angle, cutting forces, and cutting-induced damage for UD-CFRP laminate. Scanning acoustic microscopy (SAM) was employed and one-/two-dimensional damage factors were then created to quantitatively characterize the damage of the laminate workpieces. According to the 3D Hashin’s criteria a numerical model was further proposed in terms of the finite element method (FEM). A good agreement between simulation and experimental results was validated for the prediction and structural optimization of the UD-CFRP