Human adenovirus type 7 subunit vaccine induces dendritic cell maturation through the TLR4/NF-κB pathway is highly immunogenic

IntroductionHuman adenovirus type 7 (HAdv-7) infection is the main cause of upper respiratory tract infection, bronchitis and pneumonia in children. At present, there are no anti- adenovirus drugs or preventive vaccines in the market. Therefore, it is necessary to develop a safe and effective anti-adenovirus type 7 vaccine.MethodsIn this study, In this study, we used the baculovirus-insect cell expression system to design a recombinant subunit vaccine expressing adenovirus type 7 hexon protein (rBV-hexon) to induce high-level humoral and cellular immune responses. To evaluate the effectiveness of the vaccine, we first detected the expression of molecular markers on the surface of antigen presenting cells and the secretion of proinflammatory cytokines in vitro. We then measured the levels of neutralizing antibodies and T cell activation in vivo.ResultsThe results showed that the rBV-hexon recombinant subunit vaccine could promote DC maturation and improve its antigen uptake capability, including the TLR4/NF-κB pathway which upregulated the expression of MHCI, CD80, CD86 and cytokines. The vaccine also triggered a strong neutralizing antibody and cellular immune response, and activated T lymphocytes.DiscussionTherefore, the recombinant subunit vaccine rBV-hexon promoted promotes humoral and cellular immune responses, thereby has the potential to become a vaccine against HAdv-7

6G Network AI Architecture for Everyone-Centric Customized Services

Mobile communication standards were developed for enhancing transmission and network performance by using more radio resources and improving spectrum and energy efficiency. How to effectively address diverse user requirements and guarantee everyone's Quality of Experience (QoE) remains an open problem. The Sixth Generation (6G) mobile systems will solve this problem by utilizing heterogenous network resources and pervasive intelligence to support everyone-centric customized services anywhere and anytime. In this article, we first coin the concept of Service Requirement Zone (SRZ) on the user side to characterize and visualize the integrated service requirements and preferences of specific tasks of individual users. On the system side, we further introduce the concept of User Satisfaction Ratio (USR) to evaluate the system's overall service ability of satisfying a variety of tasks with different SRZs. Then, we propose a network Artificial Intelligence (AI) architecture with integrated network resources and pervasive AI capabilities for supporting customized services with guaranteed QoEs. Finally, extensive simulations show that the proposed network AI architecture can consistently offer a higher USR performance than the cloud AI and edge AI architectures with respect to different task scheduling algorithms, random service requirements, and dynamic network conditions

Low-Power CMOS Integrated Hall Switch Sensor

This paper presents an integrated Hall switch sensor based on SMIC 0.18 µm CMOS technology. The system includes a front-end Hall element and a back-end signal processing circuit. By optimizing the structure of the Hall element and using the orthogonal coupling and spinning current technology, the offset voltage can be suppressed effectively. The simulation results showed that the Hall switch can eliminate offset voltage greater than 1 mV at 3.3 V supply voltage. Two modes of the Hall switch circuit, the awake mode and the sleep mode, were realized by using clock logic signals without compromising the performance of the Hall switch, thereby reducing power consumption. The test results showed that the operate point and the release point of the switch were within the range of 3–7 mT at 3.3 V supply voltage. Meanwhile, the current consumption is 7.89 µA

Capacity and Delay Analysis for Large Social-Aware Mobile Ad Hoc Wireless Networks

Most mobile ad hoc wireless networks have social features. It is a fundamental problem how to understand the performances of social-aware mobile ad hoc wireless networks. In this paper, we consider a wireless network area, with restricted mobility model and rank-based social model. On this basis, we investigate the upper bound of throughput capacity in such networks using the protocol interference model. By tessellating the network area into cells spatially and dividing time into slots temporally, we propose a multi-hop relay and slots allocation scheduling strategy. Then, we derive the achieved throughput capacity under this strategy. Results show per-node throughput is related to parameter of social model and range of node motion. In addition, we also study the delay varies by queueing theory in such network. Finally, we discuss capacity-delay tradeoffs in such networks. These results are beneficial to the design of network protocols in large social-aware mobile ad hoc wireless networks

Intelligent Proportional Differential Neural Network Control for Unknown nonlinear systems

International audienc

Intelligent Proportional Differential Neural Network Control for Unknown nonlinear systems

International audienc

Active fault tolerance control of a wind turbine system using an unknown input observer with an actuator fault

International audienc

Robust unknown input observer design for state estimation and fault detection using linear parameter

International audienc

Active fault tolerance control of a wind turbine system using an unknown input observer with an actuator fault

International audienc

Direct power control of DFIG wind turbine systems based on an intelligent proportional-integral sliding mode control

International audienceThis paper presents an intelligent proportional-integral sliding mode control (iPISMC) for direct power control of variable speed-constant frequency wind turbine system. This approach deals with optimal power production (in the maximum power point tracking sense) under several disturbance factors such as turbulent wind. This controller is made of two sub-components: (i) an intelligent proportional-integral module for online disturbance compensation and (ii) a sliding mode module for circumventing disturbance estimation errors. This iPISMC method has been tested on FAST/Simulink platform of a 5 MW wind turbine system. The obtained results demonstrate that the proposed iPISMC method outperforms the classical PI and intelligent proportional-integral control (iPI) in terms of both active power and response time