Blocking central opiate function modulates hedonic impact and anterior cingulate response to rewards and losses.

Reward processing is linked to specific neuromodulatory systems with a dopaminergic contribution to reward learning and motivational drive being well established. Neuromodulatory influences on hedonic responses to actual receipt of reward, or punishment, referred to as experienced utility are less well characterized, although a link to the endogenous opioid system is suggested. Here, in a combined functional magnetic resonance imaging-psychopharmacological investigation, we used naloxone to block central opioid function while subjects performed a gambling task associated with rewards and losses of different magnitudes, in which the mean expected value was always zero. A graded influence of naloxone on reward outcome was evident in an attenuation of pleasure ratings for larger reward outcomes, an effect mirrored in attenuation of brain activity to increasing reward magnitude in rostral anterior cingulate cortex. A more striking effect was seen for losses such that under naloxone all levels of negative outcome were rated as more unpleasant. This hedonic effect was associated with enhanced activity in anterior insula and caudal anterior cingulate cortex, areas implicated in aversive processing. Our data indicate that a central opioid system contributes to both reward and loss processing in humans and directly modulates the hedonic experience of outcomes.

Quantitative convergence analysis of multi-agent systems

We introduce a characterization of contraction for bounded convex sets. For discrete-time multi-agent systems we provide an explicit upperbound on the rate of convergence to a consensus under the assumptions of contractiveness and (weak) connectedness (across an interval.) Convergence is shown to be exponential when either the system or the function characterizing the contraction is linear. Copyright © 2007 IFAC.

Low-threshold-current and high-out-power 660 nm laser diodes with a p-GaAs current blocking layer for DVD-RAM/R

We investigate a new structure of high-power 660-nm AlGaInP laser diodes. In the structure, a p-GaAs layer is grown on the ridge waveguide serving as the current-blocking layer, and nonabsorbing windows are only fabricated near the cavity facets to increase the catastrophic-optical-damage level. Stable fundamental mode operation was achieved at up to 80 mW without kinks, and the maximum output power was 184 mW at 22 degrees C. The threshold current was 40 mA.

Blocking of the polaron effect and spin-split cyclotron resonance in a two-dimensional electron gas

Cyclotron resonance (CR) of high density GaAs quantum wells exhibits well-resolved spin splitting above the LO-phonon frequency. The spin-up and spin-down CR frequencies are reversed relative to the order expected from simple band nonparabolicity. We demonstrate that this is a consequence of the blocking of the polaron interaction which is a sensitive function of the filling of the Landau levels.

Native-oxidized InAlAs blocking layer buried heterostructure InGaAsP-InP MQW laser for high-temperature operation

A novel idea of InAlAs native oxide utilized to replace the p-n-p-n thyristor blocking layer and improve the high-temperature performance of buried heterostructure InGaAsP-InP laser is first proposed and demonstrated. A characteristic temperature (T-0) of 50 K is achieved from an InA1As native oxide buried heterostructure (NOBH) InGaAsP-InP multiquantum-well laser with 1.5-mu m-wide diode leakage passage path. The threshold current and slope efficiency of NOBH laser changes from 5.6 mA, 0.23 mW/mA to 28 mA, 0.11 mW/mA with the operating temperature changing from 20 degrees C to 100 degrees C. It is comparable to conventional p-n reverse biased junction BH laser with minimized diode leakage current, and is much better than the buried ridge strip with proton implanted laterally confinement laser.

Buried heterostructure InGaAsP/InP strain-compensated multiple quantum well laser with a native-oxidized InAlAs current blocking layer

An InAlAs native oxide is used to replace the p-n reverse-biased junction in a conventional buried heterostructure InP-based laser. This technique reduces the number of regrowth steps and eliminates leakage current under high-temperature operation. The InAlAs native oxide buried heterostructure (NOBH) laser with strain-compensated InGaAsP/InP multiple quantum well active layers has a threshold current of 5.6 mA, a slope efficiency of 0.23 mW/mA, and a linear power up to 22.5 mW with a HR-coated facet. It exhibits single transverse mode with lasing wavelength at 1.532 mu m. A characteristic temperature (T-0) of 50 K is obtained from the NOBH laser with a nonoptimized oxide layer width. (C) 1998 American Institute of Physics. [S0003-6951(98)01352-7].

mobile agent system model based on servlet technology

A mobile agent system model based on the servlet technology is presented, the constitution and working process of the system are analyzed. The implementation of key parts of this model and the current development situation as well as the development trend of mobile agent technology are introduced. The mobile agent system model enhances its internal structure recognition and facilitates the system expansion and reformation. The remotely mobile agent control method by means of the protocol modification is presented.

一种基于Agent的自适应的分布式入侵检测系统

针对传统分布式入侵检测系统组件之间依赖程度大、系统不够健壮且入侵检测系统自身结构固定不能适应入侵的变化的问题,提出了一种基于Agent的自适应的分布式入侵检测系统(简称AAA-DIDS)·AAADIDS采用Agent概念重新构造系统的组件,改进了分布式入侵检测系统由于高层节点单一无冗余而产生的可靠性差的缺陷,从构造上克服了分布式入侵检测系统的脆弱性·同时,AAADIDS系统采用智能技术构建了自适应的入侵检测系统模型,增加了系统应对入侵行为变化的智能性·AAA-DIDS系统相对于传统的分布式入侵检测系统有效地提高了系统自身的可靠性和针对外界变化的适应能力·

一种用于软件过程建模的适应性Agent协商

大多软件过程模型是预定义的.在变化的应用环境中,需要由相应人员进行适应性调整.提出一种用于软件过程建模的适应性多边协商模型——AMNM-PA,其采用Agent封装软件过程中所涉及的个体,包含组织、团队、个人等,通过Agent间的协商动态、适应地建立针对给定软件项目的软件过程模型.AMNM-PA基于非静态有限阶段Markov决策过程,采用模型无关的Q学习算法选取协商策略,因此能够支持动态、非预知环境下的适应性协商,从而满足软件过程建模对环境的适应性需求.AMNM-PA已经实施于软件过程管理系统——SoftPM.

一种基于Agent的自适应软件过程模型

传统的软件过程模型大多是静态的、机械的、被动的,它们要求软件工程人员在描述软件过程时预期所有可能发生的情况,并且显式地定义这些问题的解决方案.当软件过程所处的环境发生变化时,软件过程无法自适应地对这些变更作出相应的调整.提出了一种基于Agent的自适应软件过程模型.在这种软件过程模型中,软件过程被描述为一组相互独立而对等的实体——软件过程Agent.这些软件过程Agent能够对软件过程环境的变化主动地、自治地作出反应,动态地确定和变更其行为以实现软件开发的目标.