356 research outputs found

    A novel multipath-transmission supported software defined wireless network architecture

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    The inflexible management and operation of today\u27s wireless access networks cannot meet the increasingly growing specific requirements, such as high mobility and throughput, service differentiation, and high-level programmability. In this paper, we put forward a novel multipath-transmission supported software-defined wireless network architecture (MP-SDWN), with the aim of achieving seamless handover, throughput enhancement, and flow-level wireless transmission control as well as programmable interfaces. In particular, this research addresses the following issues: 1) for high mobility and throughput, multi-connection virtual access point is proposed to enable multiple transmission paths simultaneously over a set of access points for users and 2) wireless flow transmission rules and programmable interfaces are implemented into mac80211 subsystem to enable service differentiation and flow-level wireless transmission control. Moreover, the efficiency and flexibility of MP-SDWN are demonstrated in the performance evaluations conducted on a 802.11 based-testbed, and the experimental results show that compared to regular WiFi, our proposed MP-SDWN architecture achieves seamless handover and multifold throughput improvement, and supports flow-level wireless transmission control for different applications

    Novobiocin, a Newly Found TRPV1 Inhibitor, Attenuates the Expression of TRPV1 in Rat Intestine and Intestinal Epithelial Cell Line IEC-6

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    Background and Purpose: Novobiocin (NOVO), an ABC transporter inhibitor, decreases intestinal wall permeability of capsaicin (CAP), an ABC transporter substrate. However, the mechanism of this effect is not consistent with the action of NOVO as an ABC transporter inhibitor. We previously found that CAP can also be transported via TRPV1, which was site-specific in the permeability of CAP across the intestine. We explored the regulation by NOVO of TRPV1 in the present study.Methods: Rats and transfected IEC-6 cells were used as the models to assess intestinal permeability and expression of TRPV1. Ussing chamber and intracellular accumulation were used to evaluate the influence of NOVO on the transport of CAP in vitro. The expression of TRPV1 was detected after administration of NOVO by qRT-PCR, western blot and immunofluorescent imaging. In addition, MTT and lactate dehydrogenase (LDH) were used to evaluate the cytotoxicity of NOVO in both rat and cell models. Finally, the effect of NOVO on the absorption of CAP in vivo was studied by LC-MS/MS.Results:In vitro data showed that there existed a dose-dependent relationship in the range of concentration between 5 and 50 μM, and even 5 μM NOVO could decrease intestinal permeability of CAP across the intestine. Meanwhile, cytosolic accumulation of CAP decreased when NOVO was used simultaneously or 24 h in advance. NOVO exhibited an inhibition level similar to that of ruthenium red (RR) or SB-705498, a TRPV1-specific inhibitor. NOVO down-regulated TRPV1 expression in the intestine and in transfected cells in a concentration-dependent fashion, hinting that its inhibition of the permeability of CAP is due to its inhibition of TRPV1 expression. Immunofluorescent imaging data showed that the fluorescence intensity of TRPV1 was reduced after pre-treatment with NOVO and SB-705498. In vivo data further demonstrated that oral co-administration of NOVO decreased Cmax and AUC of CAP in dosage-dependent ways, consistent with its role as a TRPV1 inhibitor.Conclusion: NOVO could be a potential TRPV1 inhibitor by attenuating the expression of TRPV1 and may be used to attenuate permeability of TRPV1 substrates

    Modeling and Identification of Podded Propulsion Unmanned Surface Vehicle and Its Course Control Research

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    The response model of podded propulsion unmanned surface vehicle (USV) is established and identified; then considering the USV has characteristic of high speed, the course controller with fast convergence speed is proposed. The idea of MMG separate modeling is used to establish three-DOF planar motion model of the podded propulsion USV, and then the model is simplified as a response model. Then based on field experiments, the parameters of the response model are obtained by the method of system identification. Unlike ordinary ships, USV has the advantages of fast speed and small size, so the controller needs fast convergence speed and strong robustness. Based on the theory of multimode control, a fast nonsingular terminal sliding mode (FNTSM) course controller is proposed. In order to reduce the chattering of system, disturbance observer is used to compensate the disturbance to reduce the control gain and RBF neural network is applied to approximate the symbolic function. At the same time, fuzzy algorithm is employed to realize the mode soft switching, which avoids the unnecessary chattering when the mode is switched. Finally the rapidity and robustness of the proposed control approach are demonstrated by simulations and comparison studies

    Increased fibroblast functionality on CNN2-loaded titania nanotubes

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    Infection and epithelial downgrowth are major problems associated with maxillofacial percutaneous implants. These complications are mainly due to the improper closure of the implant–skin interface. Therefore, designing a percutaneous implant that better promotes the formation of a stable soft tissue biologic seal around percutaneous sites is highly desirable. Additionally, the fibroblast has been proven to play an important role in the formation of biologic seals. In this study, titania nanotubes were filled with 11.2 kDa C-terminal CCN2 (connective tissue growth factor) fragment, which could exert full CCN2 activity to increase the biological functionality of fibroblasts. This drug delivery system was fabricated on a titanium implant surface. CCN2 was loaded into anodized titania nanotubes using a simplified lyophilization method and the loading efficiency was approximately 80%. Then, the release kinetics of CCN2 from these nanotubes was investigated. Furthermore, the influence of CCN2-loaded titania nanotubes on fibroblast functionality was examined. The results revealed increased fibroblast adhesion at 0.25, 0.5, 1, 2, 4, and 24 hours, increased fibroblast viability over the course of 5 days, as well as enhanced actin cytoskeleton organization on CCN2-loaded titania nanotubes surfaces compared to uncoated, unmodified counterparts. Therefore, the results from this in vitro study demonstrate that CCN2-loaded titania nanotubes have the ability to increase fibroblast functionality and should be further studied as a method of promoting the formation of a stable soft tissue biologic seal around percutaneous sites

    Efficient performance monitoring for ubiquitous virtual networks based on matrix completion

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    Inspired by the concept of software-defined network and network function virtualization, vast virtual networks are generated to isolate and share wireless resources for different network operators. To achieve fine-grained resource control and scheduling among virtual networks (VNs), network performance monitoring is essential. However, due to limitation of hardware, real-time performance monitoring is impossible for a complete virtual network. In this paper, taking advantage of the low-rank characteristic of 90 virtual access points (VAPs) measurement data, we propose an intelligent measurement scheme, namely, adaptive and sequential sampling based on matrix completion (MC), which exploits from the MC to construct the complete data of VN performance from a partial direct monitoring data. First, to construct the initial measurement matrix, we propose a sampling correction model based on dispersion and coverage. Second, a stopping condition for the sequential sampling is introduced, based on the stopping condition, the sampling process for a period can stop without waiting for the matrix reconstruction to reach certain of accuracy level. Finally, the sampled VAPs are determined by referring the back-forth completed matrixes\u27 normalized mean absolute error. The experiments show that our approach can achieve a constant network perception and maintain a relatively low error rate with a small sampling rate

    Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances

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    This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller