Optimal path and gait generations simultaneously of a six-legged robot using a GA-Fuzzy approach

This paper describes a new method for generating optimal path and gait simultaneously of a six-legged robot using a combined GA-fuzzy approach. The problem of combined path and gait generations involves three steps, namely determination of vehicle's trajectory, foothold selection and design of a sequence of leg movements. It is a complicated task and no single traditional approach is found to be successful in handling this problem. Moreover, the traditional approaches do not consider optimization issues, yet they are computationally expensive. Thus, the generated path and gaits may not be optimal in any sense. To solve such problems optimally, there is still a need for the development of an efficient and computationally faster algorithm. In the proposed genetic-fuzzy approach, optimal path and gaits are generated by using fuzzy logic controllers (FLCs) and genetic algorithms (GAs) are used to find optimized FLCs. The optimization is done off-line on a number of training scenarios and optimal FLCs are found. The hexapod can then use these GA-tuned FLCs to navigate in test-case scenarios

Design of a genetic-fuzzy system for planning optimal path and gait simultaneously of a six-legged robot

This paper describes a genetic-fuzzy system used for generating optimal path and gait simultaneously of a six-legged robot. No single traditional approach is found to be successful in handling this complicated task. Moreover, the conventional methods are computationally expensive and the generated path and gaits may not be optimal in any sense. Thus, there is still a need for the development of an efficient and computationally faster algorithm for solving this problem. In the proposed algorithm, optimal path and gaits are generated by fuzzy logic controllers (FLCs) and optimized FLCs are found by genetic algorithms (GAs). Design of an optimized FLC (only rule base optimization) involves the problem of dealing with discrete variables and GA is an efficient tool for this purpose. The actual optimization is done off-line and the hexapod can use these GA-tuned FLCs to navigate in real-world scenarios, in an optimal sense

Flagellin Acting Via TLR5 is the Major Activator of Key Signaling Pathways Leading to NF-kappa B and Proinflammatory Gene Program activation in intestinal epithelial cells

BACKGROUND: Infection of intestinal epithelial cells by pathogenic Salmonella leads to activation of signaling cascades that ultimately initiate the proinflammatory gene program. The transcription factor NF-kappa B is a key regulator/activator of this gene program and is potently activated. We explored the mechanism by which Salmonella activates NF-kappa B during infection of cultured intestinal epithelial cells and found that flagellin produced by the bacteria and contained on them leads to NF-kappa B activation in all the cells; invasion of cells by the bacteria is not required to activate NF-kappa B. RESULTS: Purified flagellin activated the mitogen activated protein kinase (MAPK), stress-activated protein kinase (SAPK) and I kappa B kinase (IKK) signaling pathways that lead to expression of the proinflammatory gene program in a temporal fashion nearly identical to that of infection of intestinal epithelial cells by Salmonella. Flagellin expression was required for Salmonella invasion of host cells and it activated NF-kappa B via toll-like receptor 5 (TLR5). Surprisingly, a number of cell lines found to be unresponsive to flagellin express TLR5 and expression of exogenous TLR5 in these cells induces NF-kappa B activity in response to flagellin challenge although not robustly. Conversely, overexpression of dominant-negative TLR5 alleles only partially blocks NF-kappa B activation by flagellin. These observations are consistent with the possibility of either a very stable TLR5 signaling complex, the existence of a low abundance flagellin co-receptor or required adapter, or both. CONCLUSION: These collective results provide the evidence that flagellin acts as the main determinant of Salmonella mediated NF-kappa B and proinflammatory signaling and gene activation by this flagellated pathogen. In addition, expression of the fli C gene appears to play an important role in the proper functioning of the TTSS since mutants that fail to express fli C are defective in expressing a subset of Sip proteins and fail to invade host cells. Flagellin added in trans cannot restore the ability of the fli C mutant bacteria to invade intestinal epithelial cells. Lastly, TLR5 expression in weak and non-responding cells indicates that additional factors may be required for efficient signal propagation in response to flagellin recognition

Flagellin acting via TLR5 is the major activator of key signaling pathways leading to NF-κB and proinflammatory gene program activation in intestinal epithelial cells

BACKGROUND: Infection of intestinal epithelial cells by pathogenic Salmonella leads to activation of signaling cascades that ultimately initiate the proinflammatory gene program. The transcription factor NF-κB is a key regulator/activator of this gene program and is potently activated. We explored the mechanism by which Salmonella activates NF-κB during infection of cultured intestinal epithelial cells and found that flagellin produced by the bacteria and contained on them leads to NF-κB activation in all the cells; invasion of cells by the bacteria is not required to activate NF-κB. RESULTS: Purified flagellin activated the mitogen activated protein kinase (MAPK), stress-activated protein kinase (SAPK) and Ikappa B kinase (IKK) signaling pathways that lead to expression of the proinflammatory gene program in a temporal fashion nearly identical to that of infection of intestinal epithelial cells by Salmonella. Flagellin expression was required for Salmonella invasion of host cells and it activated NF-κB via toll-like receptor 5 (TLR5). Surprisingly, a number of cell lines found to be unresponsive to flagellin express TLR5 and expression of exogenous TLR5 in these cells induces NF-κB activity in response to flagellin challenge although not robustly. Conversely, overexpression of dominant-negative TLR5 alleles only partially blocks NF-κB activation by flagellin. These observations are consistent with the possibility of either a very stable TLR5 signaling complex, the existence of a low abundance flagellin co-receptor or required adapter, or both. CONCLUSION: These collective results provide the evidence that flagellin acts as the main determinant of Salmonella mediated NF-κB and proinflammatory signaling and gene activation by this flagellated pathogen. In addition, expression of the fli C gene appears to play an important role in the proper functioning of the TTSS since mutants that fail to express fli C are defective in expressing a subset of Sip proteins and fail to invade host cells. Flagellin added in trans cannot restore the ability of the fli C mutant bacteria to invade intestinal epithelial cells. Lastly, TLR5 expression in weak and non-responding cells indicates that additional factors may be required for efficient signal propagation in response to flagellin recognition

Multi-objective evolutionary algorithms for the risk-return trade-off in bank loan management

Abstract Multi-Criteria Decision Making is an increasingly accepted tool for decision making in management. In this work, we highlight the application of a novel Multi-Objective Evolutionary Algorithm, NSGA-II to the risk-return trade-off for a bank loan portfolio manager. The manager of a bank operating in a competitive environment faces the standard goal of maximizing shareholder wealth. Specifically, this attempts to maximize the net worth of the bank, which in turn involves maximizing the net interest margin of the bank (among other factors, such as non-interest income). At the same time, there are significant regulatory constraints placed on the bank, such as the maintenance of adequate capital, interest-rate risk exposure, etc. The Genetic Algorithm based technique used here obtains an approximation to the set of Pareto-optimal solutions which increases the decision flexibility available to the bank manager and provides a visualization tool for one of the tradeoffs involved. The algorithm is also computationally efficient and is contrasted with a traditional multi-objective function -the epsilon-constraint method

Antifertility activity of Oroxylum indicum (L.) Kurz:In vitro and in vivo study on human sperm and male wistar rats

Oroxylum indicum (L.) Kurz, commonly called as Broken bones tree or Indian trumpet flower, belonging to Fam. Bignoniaceae, is traditionally used as a contraceptive by ethnic people of Tripura, North-East India. Here, we investigated the scientific basis for use of O. indicum as male antifertility agent by folklore healers. In vitro spermicidal activity of aqueous (AEOI) and methanolic (MEOI) extracts of O. indicum stem bark were studied on human sperm. The in vivo activity was experimented on male albino rats. The treated animals were allowed to mate and the pups delivered by female rat partners were counted. Phytochemical estimation of test samples was done using HPLC. The AEOI and MEOI treatments significantly decreased human sperm motility and viability. Test extracts have increased the hypo-osmotic swelling of sperm. Both the extracts were significantly declined the weight of reproductive organ. The MEOI treated rats have shown significant decrease in sperm motility and sperm counts. AEOI and MEOI treatment significantly reduced level of testosterone, but sharply raised dihydrotestosterone and prostaglandin in rats. Results testified the traditional claim for use of O. indicum as a male contraceptive agent, where MEOI have shown reversible action on male reproductive system leading to contraception without harming the libido

Optimal turning gait of a six-legged robot using a GA-fuzzy approach

This paper describes a new method for generating the turning-gait of a six-legged robot using a combined genetic algorithm (GA)-Fuzzy approach. The main drawback of the traditional methods of gait generation is their high computational load. Thus, there is still a need for the development of a computationally tractable algorithm that can be implemented online to generate stable gait of a multilegged robot. In the proposed genetic-fuzzy system, the fuzzy logic controllers (FLCs) are used to generate the stable gait of a hexapod and a GA is used to improve the performance of the FLCs. The effectiveness of the proposed algorithm is tested on a number of turning-gait generation problems of a hexapod that involve translation as well as rotation of the vehicle. The hexapod will have to take a sharp circular turn (either clockwise or counter-clockwise) with minimum number of ground legs having the maximum average kinematic margin. Moreover, the stability margin should lie within a certain range to ensure static stability of the vehicle. Each leg of a six-legged robot is controlled by a separate FLC and the performance of the controllers is improved by using a GA. It is to be noted that the actual optimization is done off-line and the hexapod can use these optimized FLCs to navigate in real-world scenarios. As an FLC is computationally less expensive, the proposed algorithm will be faster compared with the traditional methods of gait-generation, which include both graphical as well as analytical methods. The GA-tuned FLCs are found to perform better than the author-defined FLCs

Learning to Avoid Moving Obstacles Optimally for Mobile Robots Using a Genetic-Fuzzy Approach

. The task in a motion planning problem for a mobile robot is to find an obstacle-free path between a starting and a destination point, which will require the minimum possible time of travel. Although there exists many studies involving classical methods and using fuzzy logic controllers (FLCs), they are either computationally extensive or they do not attempt to find optimal controllers. The proposed genetic-fuzzy approach optimizes the travel time of a robot off-line by simultanously finding an optimal fuzzy rule base and optimal membership function distributions describing various values of condition and action variables of fuzzy rules. A mobile robot can then use this optimal FLC on-line to navigate in the presence of moving obstacles. The results of this study on a number of problems show that the proposed genetic-fuzzy approach can produce efficient rules and membership functions of an FLC for controlling the motion of a robot among moving obstacles. 1 Introduction ..

Design of a Genetic-Fuzzy System for Planning Crab Gaits of a Six-legged Robot

This paper describes a genetic-fuzzy system in which a genetic algorithm (GA) is used to improve the performance of a fuzzy logic controller (FLC). The proposed algorithm is tested on a number of gait-generation problems of a hexapod for crossing a ditch while moving on flat terrain along a straight line path with minimum number of legs on the ground and with maximum average kinematic margin of the ground-legs. Moreover, the hexapod will have to maintain its static stability while crossing the ditch. The movement of each leg of the hexapod is controlled by a separate fuzzy logic controller and a GA is used to find a set of good rules for each FLC from the author-defined large rule base. The optimized FLCs are found to perform better than the author-designed FLCs. Although optimization is performed off-line, the hexapod can use these FLCs to navigate in real-world on-line scenarios. As an FLC is less expensive computationally, the computational complexity of the proposed algorithm will..