Optimum steering input determination and path-tracking of all-wheel steer vehicles on uneven terrains based on constrained optimization

In this paper we propose a framework for optimum steering input determination of all-wheel steer vehicles (AWSV) on rough terrains. The framework computes the steering input which minimizes the tracking error for a given trajectory. Unlike previous methodologies of computing steering inputs of car-like vehicles, the proposed methodology depends explicitly on the vehicle dynamics and can be extended to vehicle having arbitrary number of steering inputs. A fully generic framework has been used to derive the vehicle dynamics and a non-linear programming based constrained optimization approach has been used to compute the steering input considering the instantaneous vehicle dynamics, no-slip and contact constraints of the vehicle. All Wheel steer Vehicles have a special parallel steering ability where the instantaneous centre of rotation (ICR) is at infinity. The proposed framework automatically enables the vehicle to choose between parallel steer and normal operation depending on the error with respect to the desired trajectory. The efficacy of the proposed framework is proved by extensive uneven terrain simulations, for trajectories with continuous or discontinuous velocity profile.

A cationic cholesterol based nanocarrier for the delivery of p53-EGFP-C3 plasmid to cancer cells

The p53 protein mediated anti-tumor strategy is limited due to the lack of suitable delivery agent with insignificant immunogenic response, serum compatibility, and early and easy detection of the transfected cell population. To overcome these problems, we generated a p53-EGFP-C3 fusion construct which expressed easily detectable green fluorescence protein (GFP) and allowed an estimation of p53 mediated anti-tumor activity. A mixture of cationic cholesterol gemini (Choi-5L) with natural lipid, DOPE (molar ratio 1:4), acronymed as Chol-5LD, formed a nano-liposome as characterized by various physical methods. The prepared clone was evaluated for the expression of GFP and functional p53 in HeLa and two additional cell lines with varied p53 status namely, H1299 (p53(-/-)) and HEK293T (p53(+/+)). Transfected cells were screened using RT-PCR, Western blotting, FACS analysis, MTT, Trypan blue assay and visualized under a fluorescence microscope. The p53-EGFP-C3 fusion protein induced apoptosis in cancer cells as evident from DNA fragmentation, cell cycle analysis, Annexin-V staining and PARP cleavage assays. The transfection and apoptosis induction efficiency of Chol-5LD was significantly higher than commercial reagents Lipofectamine2000 and Effectene irrespective of the cell lines examined. Further it significantly decreases the xenograft tumor volume in nude mice tumors via apoptosis as observed in H&E staining. (C) 2013 Elsevier Ltd. All rights reserved.

A rapid, efficient, and economical inverse polymerase chain reaction-based method for generating a site saturation mutant library

With the development of deep sequencing methodologies, it has become important to construct site saturation mutant (SSM) libraries in which every nucleotide/codon in a gene is individually randomized. We describe methodologies for the rapid, efficient, and economical construction of such libraries using inverse polymerase chain reaction (PCR). We show that if the degenerate codon is in the middle of the mutagenic primer, there is an inherent PCR bias due to the thermodynamic mismatch penalty, which decreases the proportion of unique mutants. Introducing a nucleotide bias in the primer can alleviate the problem. Alternatively, if the degenerate codon is placed at the 5' end, there is no PCR bias, which results in a higher proportion of unique mutants. This also facilitates detection of deletion mutants resulting from errors during primer synthesis. This method can be used to rapidly generate SSM libraries for any gene or nucleotide sequence, which can subsequently be screened and analyzed by deep sequencing. (C) 2013 Elsevier Inc. All rights reserved.

High Value of Proton Relaxivity Achieved by Graphene Oxide-Cobalt Ferrite Nanoparticle Composite: A Potential Contrast Agent in Magnetic Resonance Imaging

This work investigates the potential of graphene oxide-cobalt ferrite nanoparticle (GO-CoFe2O4) composite as image contrast enhancing material in Magnetic Resonance Imaging (MRI). In the preset work, GO-CoFe2O4 composites were produced by a two-step synthesis process. In the first step, graphene oxide (GO) was synthesized, and in the second step CoFe2O4 nanoparticles were synthesized in a reaction mixture containing GO to yield graphene GO-CoFe2O4 composite. Proton relaxivity value obtained from the composite was 361 mM(-1)s(-1). This value of proton relaxivity is higher than a majority of reported relaxivity values obtained using several ferrite based contrast agents.

Multi-agent Reinforcement Learning for Traffic Signal Control

Optimal control of traffic lights at junctions or traffic signal control (TSC) is essential for reducing the average delay experienced by the road users amidst the rapid increase in the usage of vehicles. In this paper, we formulate the TSC problem as a discounted cost Markov decision process (MDP) and apply multi-agent reinforcement learning (MARL) algorithms to obtain dynamic TSC policies. We model each traffic signal junction as an independent agent. An agent decides the signal duration of its phases in a round-robin (RR) manner using multi-agent Q-learning with either is an element of-greedy or UCB 3] based exploration strategies. It updates its Q-factors based on the cost feedback signal received from its neighbouring agents. This feedback signal can be easily constructed and is shown to be effective in minimizing the average delay of the vehicles in the network. We show through simulations over VISSIM that our algorithms perform significantly better than both the standard fixed signal timing (FST) algorithm and the saturation balancing (SAT) algorithm 15] over two real road networks.

Accurate Indoor Positioning of Firefighters using Dual Foot-mounted Inertial Sensors and Inter-agent Ranging

A real-time cooperative localization system, utilizing dual foot-mounted low-cost inertial sensors and RF-based inter-agent ranging, has been developed. Scenario-based tests have been performed, using fully-equipped firefighters mimicking a search operation in a partly smoke-filled environment, to evaluate the performance of the TOR (Tactical lOcatoR) system. The performed tests included realistic firefighter movements and inter-agent distances, factors that are crucial in order to provide realistic evaluations of the expected performance in real-world operations. The tests indicate that the TOR system may be able to provide a position accuracy of approximately two to three meters during realistic firefighter operations, with only two smoke diving firefighters and one supervising firefighter within range.

Emergent Intelligence Based QoS Routing in MANET

Mobile Ad hoc Networks (MANETs) are self-organized, infrastructureless, decentralized wireless networks consist of a group of heterogeneous mobile devices. Due to the inherent characteristics of MANE -Ts, such as frequent change of topology, nodes mobility, resource scarcity, lack of central control, etc., makes QoS routing is the hardest task. QoS routing is the task of routing data packets from source to destination depending upon the QoS resource constraints, such as bandwidth, delay, packet loss rate, cost, etc. In this paper, we proposed a novel scheme of providing QoS routing in MANETs by using Emergent Intelligence (El). The El is a group intelligence, which is derived from the periodical interaction among a group of agents and nodes. We logically divide MANET into clusters by centrally located static agent, and in each cluster a mobile agent is deployed. The mobile agent interacts with the nodes, neighboring mobile agents and static agent for collection of QoS resource information, negotiations, finding secure and reliable nodes and finding an optimal QoS path from source to destination. Simulation and analytical results show that the effectiveness of the scheme. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.ore/licenscs/by-nc-nd/4.0/). Peer-review under responsibility of the Conference Program Chairs

Capability approach-based evaluation of a biomass cook-stove design

What is the scope and responsibilities of design? This work partially answers this by employing a normative approach to design of a biomass cook stove. This study debates on the sufficiency of existing design methodologies in the light of a capability approach. A case study of a biomass cook stove Astra Ole has elaborated the theoretical constructs of capability approach, which, in turn, has structured insights from field to evaluate the product. Capability approach based methodology is also prescriptively used to design the mould for rapid dissemination of the Astra Ole.