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)     

Prediction of brittle-to-ductile transitions in polystyrene

In this study it is attempted to predict brittle-to-ductile transitions (BDTs) in polystyrene blends, induced either by an increase in temperature or by a decrease in inter-particle distance. A representative, two-dimensional volume element (RVE) of a polystyrene matrix with 20% circular voids, is deformed in tension. During deformation a hydrostatic-stress based craze-nucleation criterion [1] is evaluated. The simulations demonstrate that crazes initiate at low temperatures while a transition from crazing to shear yielding (BDT) is found around 75 °C. The numerical results correlate well with tensile tests on similar heterogeneous polystyrene. The presence of an absolute length, as experimentally found, is more difficult to explain. Near a free surface a T_g-depression is measured for polystyrene and also the resistance to indentation in polystyrene is lower than expected from bulk properties. Both observations are rationalised by an enhanced segmental mobility of chains near a free surface. As a consequence of these findings, an absolute length-scale could be incorporated in the numerical simulations. For simplicity, the length-scale is modelled by taking a temperature gradient over a thin layer near the internal free surfaces of the RVE. Deformation of the RVE with different absolute length-scales shows that indeed also the experimentally found brittle-to-ductile transition can be predicted if the ligament thickness between the inclusions (‘voids’) in polystyrene is below a critical value of ca. 15 nm.     

Practical OSPF traffic engineering

Open Shortest Path First (OSPF) traffic engineering (TE) is intended to bring long-awaited traffic management capabilities into IP networks, which still rely on today's prevailing routing protocols: OSPF or IS-IS. In OSPF, traffic is forwarded along, and split equally between, equal cost shortest paths. In this letter, we formulate the basic requirements placed on a practical TE architecture built on top of OSPF and present a theoretical framework meeting these requirements of practicality. The main contribution of our work comes from the recognition that coupled with an instance of the maximum throughput problem there exists a related inverse shortest-path problem yielding optimal OSPF link weights.     

Techniques for high-frequency integrated test and measurement

This paper describes techniques for the on-chip measurement of high-frequency and/or high-bandwidth electrical phenomena in ultra large-scale integration environments. The techniques rely on the integration of multiple compact and robust electronic test devices, or cores, at various locations within an integrated circuit. The cores consist primarily of signal generators that approximate the output of a sigma-delta modulator using finite repetitious bit patterns and a small set of highly robust analog components. They are capable of digitizing on-chip signals at gigahertz rates even using low-cost manufacturing processes. Simple communication between the multiple cores enables the migration of many "board-level" type measurements down to the chip level.     

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.     

PNNI-based control plane for automatically switched optical networks

Much effort has been spent on the definition of control plane protocols for automatically switched optical networks (ASON). Most of the proposals brought into the standardization for an International Telecommunications Union-Telecommunication Sector, Internet Engineering Task Force, and Optical Internetworking Forum are based on Internet protocol concepts. One such proposal is the generalized multi-protocol label switching (GMPLS), an extension of the MPLS traffic engineering control plane model that includes nonpacket switched technologies (time, wavelength, and fiber switching). Recently, the potential use of private network-network interface (PNNI) in ASONs has been discussed as an alternative proposal by the standardization bodies. The goal of this paper is to appropriately adapt asynchronous transfer mode into an optical PNNI (O-PNNI) protocol that can be used as the control plane of ASONs. The paper also provides a critical viewpoint on the potential usage of either O-PNNI or GMPLS control plane and analyzes the pros and cons of each. The methodology adopted toward devising O-PNNI hinges on reviewing PNNI along with ASON recommendations in order to determine the set of PNNI features that require adaptation. Having identified these features we engineer and present appropriate solutions relating to routing, signaling and addressing aspects.     

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.