Tri-axial sensors and actuators made of a single piezoelectric cylindrical shell

Electromechanical transducers for sensing and actuating disturbances or vibrations have been used in many fields of applications. There have been transducers of different configuration developed for the unidirectional transduction. This paper demonstrates a single element transducer for tri-axial components made of a piezoelectric cylindrical shell. The separation of the tri-axial transductions is achieved by devising a proper electrode arrangement. The structure and the fundamental idea are first presented, and then the numerical analysis by means of the finite element modeling follows, and their characteristics and behaviors are then experimentally verified.     

Fast Positive Feedback Between the Adrenocortical Stress Response and a Brain Mechanism Involved in Aggressive Behavior.

Aggressive behavior induces an adrenocortical stress response, and sudden stressors often precipitate violent behavior. Experiments in rats revealed a fast, mutual, positive feedback between the adrenocortical stress response and a brain mechanism controlling aggression. Stimulation of the aggressive area in the hypothalamus rapidly activated the adrenocortical response, even in the absence of an opponent and fighting. Hypothalamic aggression, in turn, was rapidly facilitated by a corticosterone injection in rats in which the natural adrenocortical stress response was prevented by adrenalectomy. The rapidity of both effects points to a fast, mutual, positive feedback of the controlling mechanisms within the time frame of a single conflict. Such a mutual facilitation may contribute to the precipitation and escalation of violent behavior under stressful conditions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Formulation of a ceramic ink for a wide-array drop-on-demand ink-jet printer

This paper describes the methodology for simulating a reprographic ink with a ceramic ink based on a commercially available zirconia powder for direct ceramic ink-jet printing. Of over-riding importance was matching viscosity and this was tested systematically by using a mineral oil–hexane binary system. Of secondary importance was adjustment of the pressure defect behind the nozzle to compensate for small differences in surface tension. The inks tested in the wide array print-head were based on low electrical conductivity liquids to avoid damage to the electroding system. The organic binder for the zirconia ink was paraffin wax and the dispersant was a hydroxystearic acid based polyester.     

Finite element analysis of advanced multilayer capacitors

We establish a systematic methodology to design and analyse electromagnetic components such as advanced multilayer ceramic capacitors (MLCCs) using the finite element (FE) method. We employ a coupled formulation to compute the interaction between the electric and magnetic fields. Unlike a linear distribution of current assumed in the circuit model, an accurate electrostatic solution to model the entire advanced MLCCs (4 × 4 × 27 = 432 cells) is presented. The FE solution is used to compute the lumped parameters for a range of frequencies. These lumped parameters are then used to compute the parasitic elements of the MLCCs. We introduce two algorithms to efficiently analyse the behaviour of a capacitor with changing frequency. The lower frequency (much below the self‐resonant frequency of the capacitor) algorithm separates the effect of the electric and magnetic fields and reduces the computational effort required to solve the FE problem, whereas, the high‐frequency algorithm couples the effect between the electric and the magnetic fields. We use these algorithms in conjunction with a new multiple scale technique to effectively determine the small values of R, L and C in MLCCs. The formulation, the implementation, and the numerical results demonstrate the efficacy of the present FE formulation and establish a systematic methodology to design and analyse advanced electromagnetic components. Copyright © 2003 John Wiley & Sons, Ltd.     

Optimal mean-square prediction of the mobile-radio fading envelope

Long-range prediction of the mobile-radio fading envelope is an enabling technology for many fading compensation approaches. Because the fading envelope is well modeled as a bandlimited process, it has special predictability properties. In this paper, we find a linear predictor that is optimal in the mean-square sense when the predictor impulse response is energy constrained. This solution may be used to determine the minimum mean squared error of a prediction based on past values that are corrupted with estimation errors.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.