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)     

Ring‐opening polymerization of lactones initiated by diphenylzinc–coinitiator systems

Diphenylzinc, alone or in combination with water and butanone as coinitiators, was used as a polymerization initiator system for a variety of lactones at varying temperatures. The resulting data indicate that the course of the polymerization is greatly influenced by the lactone structure, as well as by the molar ratio of coinitiator to diphenylzinc. When used alone, diphenylzinc exhibited high activity as an initiator in δ‐valerolactone polymerizations, although it was less efficient when used in the β‐butyrolactone and the β‐propiolactone polymerizations. Activity in the polymerization of β‐lactones was increased by adding small amounts of butanone or water. It was also observed that the diphenylzinc–butanone combination was more effective than the diphenylzinc–water mixture in the polymerizations of β‐butyrolactone and β‐propiolactone. Copyright © 2003 Society of Chemical Industry     

Nonlinearity analysis and optimization of HBTs for optical mixer designs

Two types of photo heterojunction bipolar transistor (HBT) to directly down-convert optical signals to electronic signals have been reported in the literature: a conventional photo-HBT in which light penetrates through the area of the base-collector junction and an HBT where light shines through the base-collector edge for higher conversion efficiency. Although the performance in relation to bias conditions has been published, the detailed analyses for identifying the parameters and bias conditions that provide optimum direct down-conversion have not been examined. This paper provides a full explanation of the operation of the down-conversion for both HBT configurations based on low-frequency analyses. Such information is useful for both understanding the nonlinear mechanisms involved and designing for maximum efficiency. In addition, a new circuit has been developed from the basic HBT down-conversion circuit that provides improved performance.     

Radiometric sensor for temperature control of food processing

This paper describes a novel planar antenna sensor created for the purpose of noninvasive temperature measurements using microwave radiometry. In order to improve radiometric measurements in industrial applications, a new generation of sensors is introduced, composed of a metallic sheet. Simulations based upon the method of moments is used both to design and to determine their electromagnetic performances. This paper also describes a radiometric device using these sensors to measure and control the temperature of food products during deep freezing processes. The results and discussions are presented.     

Mass Transfer in a Flat Gas/Liquid Interface using non‐Newtonian Media

Gas/liquid mass transfer has been investigated using a stirred vessel gas/liquid contactor using non‐Newtonian media and carbon dioxide as absorbent and gas phase, respectively. The volumetric mass transfer coefficients at different operational variables have been determined. Non‐Newtonian media (liquid phase) were prepared as aqueous solutions of sodium carboxymethyl cellulose salt. The influence of the rheological properties, polymer concentration, stirring rate, and gas flow rate on mass transfer was studied for these liquid phases. Kinematic viscosity and density experimental data were used to calculate the average molecular weight corresponding to the polymer employed. The Ostwald model has been used to fit the rheological behavior of aqueous solutions of the polymer employed as absorbent phase. Reasonably good agreement was found between the predictions of the proposed models and the experimental data of mass transfer coefficients.     

Fracture response of fibre-reinforced materials with macro/microcrack damage using the Boundary Element Technique

The Boundary Element Method (BEM) incorporating the Embedded Cell Approach (ECA) has been used to analyse the effects of constituent material properties, fibre spatial distribution and microcrack damage on the localised behaviour of transversely fractured, unidirectional fibre-reinforced composites. Three specific composites, i.e., glass fibre reinforced polyester, carbon fibre reinforced epoxy and a glass-carbon hybrid, are considered. The geometrical structures examined were perfectly periodic, uniformly spaced fibre arrangements in square and hexagonal embedded cells. In addition, numerical simulations were also conducted using embedded cells containing randomly distributed fibres. The models involve both elastic fibres and matrix, with the interfaces between the different phases being fully bonded. The results indicate that the constituent material properties (two phase composite) and spatial distribution have a significant effect on the localised stress distributions around the primary crack tip. However, the strain energy release rate associated with crack propagation is predominantly influenced by the material composition. The three-phase hybrid composite exhibited an apparent intermediate fracture toughness value, compared to the all-glass and all-carbon models. Furthermore, the strain energy release rate for the macrocrack lowers as it enters a zone of localised damage (microcracking). The presence of microcracks relaxes the stress field, which can result in a significant reduction in the energetics of the primary crack.     

An introduction of the condition class space with continuous value discretization and rough set theory

The granularity of an information system has an incumbent effect on the efficacy of the analysis from many machine learning algorithms. An information system contains a universe of objects characterized and categorized by condition and decision attributes. To manage the concomitant granularity, a level of continuous value discretization (CVD) is often undertaken. In the case of the rough set theory (RST) methodology for object classification, the granularity contributes to the grouping of objects into condition classes with the same condition attribute values. This article exposits the effect of a level of CVD on the subsequent condition classes constructed, with the introduction of the condition class space—the domain within which the condition classes exist. This domain elucidates the association of the condition classes to the related decision outcomes—reflecting the inexactness incumbent when a level of CVD is undertaken. A series of measures is defined that quantify this association. Throughout this study and without loss of generality, the findings are made through the RST methodology. This further offers a novel exposition of the relationship between all the condition attributes and the RST‐related reducts (subsets of condition attributes). © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 173–191, 2006.     

Fault detection for control of wastewater treatment plants.

Interest in real-time model-based control is increasing as more and more facilities are being asked to meet stricter effluent requirements while at the same time minimizing costs. It has been identified that biological process models and automated process control technologies are being used at wastewater treatments plants throughout the world and that great potential for optimising biotreatment may exist with the integration of these two technology areas. According to our experience, wastewater treatment plants are indeed looking for ways to successfully integrate their modelling knowledge into their process control structure; however, there are practical aspects of this integration that must be addressed if the benefits of this integration are to be realised. This paper discusses the practical aspects of monitoring, filtering and analysing real sensor data with an aim to produce a reliable real-time data stream that might be used within a model-based control structure. Several real case study examples are briefly discussed in this paper.