Quantification of multiple bioagents with wireless, remote-query magnetoelastic microsensors

This paper presents a micromagnetoelastic sensor array for simultaneously monitoring multiple biological agents. Magnetoelastic sensors, made of low-cost amorphous ferromagnetic ribbons, are analogous and complementary to piezoelectric acoustic wave sensors, which track parameters of interest via changes in resonance behavior. Magnetoelastic sensors are excited with magnetic ac fields, and, in turn, they generate magnetic fluxes that can be detected with a sensing coil from a distance. As a result, these sensors are highly attractive, not only due to their small size and low cost, but also because of their passive and wireless nature. Magnetoelastic sensors have been applied for monitoring pressure, temperature, liquid density, and viscosity, fluid How velocity and direction, and with chemical/biological responsive coatings that change mass or elasticity, various biological and chemical agents. In this paper, we report the fabrication and application of a six-sensor array for simultaneous measurement of Escherichia coli O157:H7, staphylococcal enterotoxin B, and ricin. In addition, the sensor array also monitors temperature and pH so the measurements are independent from these two parameters.     

Unstructured Grid-Based Discontinuous Galerkin Method for Broadband Electromagnetic Simulations

A parallel, unstructured, high-order discontinuous Galerkin method is developed for the time-dependent Maxwell's equations, using simple monomial polynomials for spatial discretization and a fourth-order Runge–Kutta scheme for time marching. Scattering results for a number of validation cases are computed employing polynomials of up to third order. Accurate solutions are obtained on coarse meshes and grid convergence is achieved, demonstrating the capabilities of the scheme for time-domain electromagnetic wave scattering simulations.     

MARKOV DECISION PROCESSES WITH UNCERTAIN TRANSITION RATES: SENSITIVITY AND MAX HYPHEN MIN CONTROL

Solution techniques for Markov decision problems rely on exact knowledge of the transition rates, which may be difficult or impossible to obtain. In this paper, we consider Markov decision problems with uncertain transition rates represented as compact sets. We first consider the problem of sensitivity analysis where the aim is to quantify the range of uncertainty of the average per‐unit‐time reward given the range of uncertainty of the transition rates. We then develop solution techniques for the problem of obtaining the max‐min optimal policy, which maximizes the worst‐case average per‐unit‐time reward. In each of these problems, we distinguish between systems that can have their transition rates chosen independently and those where the transition rates depend on each other. Our solution techniques are applicable to Markov decision processes with fixed but unknown transition rates and to those with time‐varying transition rates.     

Design of Dual-Band Beam Switching Array for Adaptive Antenna Applications Using Hybrid Directional Coupler and E-Shape Slot Radiator

Wireless Personal Communications - Applications of wireless sensor networks (WSNs) are increasing tremendously to facilitate and establish a link between the physical world and information system....     

A two stage neural network for choosing optimal ejection parameters in low altitude seat ejection based on novel injury parameter

Optimization and Engineering - Aircraft ejection systems are lifesaving devices used, in case of emergencies for military pilots. As per current literature the success rate of ejections happening...     

A transiently chaotic neural network approach to the design of cellular manufacturing

The design of Cellular Manufacturing Systems (CMS) has attained the significant attention of academicians and practitioners over the last three decades. Minimizing intercellular movements while maximizing utilization of machines are the main objectives of interest in designing CMS and are considered in present research. In this paper, the drawbacks of former neural networks-based approaches to cell formation are discussed. The standard version of cell formation problem is formulated and a 'Transiently Chaotic Neural Network' (TCNN) with supplementary procedures is introduced as a powerful rival. A simplified network is constructed. After developing the related equations the approach is tested using the proposed algorithm with 18 problems selected from literature. The results are compared with various other approaches including ART1, Extended-ART1, Ortho-Synapse Hopfield Neural Network (OSHN), etc. The main advantages of our proposed method are: (1) the ability to avoid the local optima trap, (2) the ability to solve problems of different sizes with the same set of values for parameters, and (3) the less computation time. The results also indicate considerable improvement in grouping efficiency through the proposed approach.     

Residence time distribution and oxygen transfer in a novel constructed soil filter

BACKGROUND: The constructed soil filter (CSF), also known as soil biotechnology is a system for water renovation, which makes use of formulated media, culture of soil micro‐ and macro‐organisms, additives and plantation to purify water and wastewater. The process gives benefits in terms of applicability across very small to large scale, natural aeration, absence of moving parts, no biological sludge generation, odor free green aesthetic ambience. RESULTS: Residence time distribution (RTD) studies were carried out using laboratory scale CSF. Pulse potassium bromide tracer tests were carried out to determine RTD, and the Peclet number found to be 9–13 for a 2 m bed, and 2–3 for a 0.30 m bed with oxygen transfer of 0.08 h^?1. CONCLUSION: The two‐channel dispersion model for flow behavior shows a good fit to the experimental data, indicating a reactor Peclet number 9–13 for a 2 m bed and 2–3 for a 0.3m bed. Oxygen transfer studies carried out using various methods gave an oxygen transfer coefficient of about 0.08 h^?1. Wastewater purification studies indicate overall COD removal rate of around 50 mg L^?1 h^?1, suggesting that highly aerobic conditions are prevalent in the CSF system. Copyright © 2009 Society of Chemical Industry     

Iodine‐Mediated Copper‐Catalyzed Efficient α‐C(sp2)‐Thiomethylation of α‐Oxoketene Dithioacetals with Dimethyl Sulfoxide in One Pot

The direct α‐Csp² H functionalization and thiomethylation of α‐oxoketene dithioacetals (DTAs) has been accomplished with dimethyl sulfoxide (DMSO) in the presence of iodine and a copper(I) salt for the first time. A prerequisite is the in situ iodination of the α‐Csp² atom of dithioacetals that could offer other reaction channels. The operationally simple one‐pot protocol includes region‐defined consecutive iodination and sulfenylation of the challenging α‐Csp² H bond of dithioacetals employing cheap and readily available reagents. DMSO here plays a dual role as thiomethyl source and solvent.