Th17 Cells as Potential Probiotic Therapeutic Targets in Inflammatory Bowel Diseases

Inflammatory bowel diseases (IBD) are characterized by wasting and chronic intestinal inflammation triggered by various cytokine-mediated pathways. In recent years, it was shown that T helper 17 (Th17) cells are involved in the pathogenesis of IBD, which makes them an attractive therapeutic target. Th17 cells preferentially produce interleukin (IL)-17A–F as signature cytokines. The role of the interplay between host genetics and intestinal microbiota in the pathogenesis of IBD was demonstrated. Probiotics are live microorganisms that when orally ingested in adequate amounts, confer a health benefit to the host by modulating the enteric flora or by stimulating the local immune system. Several studies indicated the effectiveness of probiotics in preventing and treating IBD (ulcerative colitis, and Crohn’s disease). Furthermore, there is mounting evidence of probiotics selectively targeting the Th17 lineage in the prevention and management of inflammatory and autoimmune diseases such as IBD. This review highlights critical roles of Th17 cells in the pathogenesis of IBD and the rationale for using probiotics as a novel therapeutic approach for IBD through manipulation of Th17 cells. The potential molecular mechanisms by which probiotics modulate Th17 cells differentiation and production are also discussed.     

Parametric Programming Applied to Reliability Optimization Problems

In practical reliability optimization models, finding an optimal solution to the model is not the only requirement. One may also be interested in solutions that are close to optimum, or one may want to know what happens if a change is made in the model. This paper presents new reliability optimization models which can be formulated as parametric nonlinear integer programming problems. Solution methods are illustrated with examples and flow charts.     

A factoring approach for the Steiner tree problem in undirected networks

In communication networks, many applications, such as video on demand and video conferencing, must establish a communications tree that spans a subset K in a vertex set. The source node can then send identical data to all nodes in set K along this tree. This kind of communication is known as multicast communication. A network optimization problem, called the Steiner tree problem (STP), is presented to find a least cost multicasting tree. In this paper, an O(|E|) algorithm is presented to find a minimum Steiner tree for series-parallel graphs where |E| is the number of edges. Based on this algorithm, we proposed an O(2^2c·|E|) algorithm to solve the Steiner tree problem for general graphs where c is the number of applied factoring procedures. The c value is strongly related to the topology of a given graph. This is quite different from other algorithms with exponential time complexities in |K|.     

医疗服务机器人应用与发展研究报告

论文介绍了医疗服务机器人的基本概念、特点、应用与发展,重点阐述了手术机器人、康复机器人、护理机器人、救援机器人与转运机器人的发展与应用.     

The r-Neighborhood Graph: An Adjustable Structure for Topology Control in Wireless Ad Hoc Networks

In wireless ad hoc networks, constructing and maintaining a topology with lower node degrees is usually intended to mitigate excessive traffic load on wireless nodes. However, keeping lower node degrees often prevents nodes from choosing better routes that consume less energy. Therefore, the trade-off is between the node degree and the energy efficiency. In this paper, an adjustable structure, named the r-neighborhood graph, is proposed to control the topology. This structure has the flexibility to be adjusted between the two objectives through a parameter r, 0lesrles1. More explicitly, for any set of n nodes, the maximum node degree and power stretch factor can be bounded from above by some decreasing and increasing functions of r, respectively. Specifically, the bounds can be constants in some ranges of r. Even more, the r-neighborhood graph is a general structure of both RNG and GG, two well-known structures in topology control. Compared with YG_k, another famous adjustable structure, our method always results in a connected planar with symmetric edges. To construct this structure, we investigate a localized algorithm, named PLA, which consumes less transmitting power during construction and executes efficiently in O(n logn) time     

A GPS-less, outdoor, self-positioning method for wireless sensor networks

One challenging issue in sensor networks is to determine where a given sensor node is physically located. This problem is especially crucial for very small sensor nodes. This paper presents a GPS-less, outdoor, self-positioning method for wireless sensor networks. In our method, a set of nodes, called reference points (RPs), are deployed in the sensor network with overlapping regions of coverage. The RP periodically broadcasts beacon frames which contain localization data. The sensor node collects the beacon frames from RPs and process the data in the frame; it can then easily localize itself. The analysis of positioning accuracy is given to show how well a sensor node can correctly localize itself. In the optimal transmitting power, the worst-case accuracy for all data points is within 28.87% of the separation-distance between two adjacent RPs and the average accuracy is within 15.51%. The simulation results also show the robustness of the proposed method. Finally, we have implemented our positioning method on a sensor network test bed and the actual measurement show that the method can achieve average accuracy within 17.9% of the separation-distance between two adjacent RPs in an outdoor environment.     

Topological optimization of a communication network subject to areliability constraint

Network topological optimization with a reliability constraint is considered. The objective is to find the topological layout of links, at a minimal cost, under the constraint that the network reliability is not less than a given level of system reliability. A decomposition method, based on branch and bound, is used for solving the problem. In order to speed up the procedure, an upper bound on system reliability, in terms of node degrees, is applied. A numerical example illustrates the effectiveness of the method     

System reliability design with deteriorative components

In constrained optimum system reliability problems, the reliability of each component is usually assumed to be fixed, and the optimal number of redundancies at each stage is determined. However, in real world the component reliability decreases as component deteriorates; i.e. the component reliability is dependent on its age. This paper presents a system reliability optimization problem with deteriorative components. We formulate this problem as a parametric nonlinear integer programming problem where the objective function has a time parameter t. A solution method is proposed for solving it. We believe that this model can provide very useful information for decision makers and reliability designers.