Trauma, dissociation, and conflict: The space where neuroscience, cognitive science, and psychoanalysis overlap.

The authors describe their scientific and clinical interests in developing the panel Trauma, Dissociation, and Conflict: The Space Where Neuroscience, Cognitive Science, and Psychoanalysis Overlap, given at the 22nd Annual Spring Meeting of the Division of Psychoanalysis of the American Psychological Association. They cite the influence of the panelists, Philip M. Bromberg, Wilma Bucci, and Joseph LeDoux, on their own work. Specializing in the treatment of chronic pain, Anderson has developed a relational intersubjective technique informed by this interdisciplinary approach. Gold's work has focused on the distinction between dissociative processes and repression in traumatic memory. The relevance of trauma, dissociation, and conflict, heightened since September 11, 2001, could not have been anticipated in the planning of the panel. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of stimulus emotionality and sentence generation on memory for words in adults with unilateral brain damage.

Does sentence generation and/or stimulus emotionality enhance verbal memory in patients with neurological impairment? This question was addressed by testing 40 patients with unilateral stroke (20 with left-brain and 20 with right-brain damage) and 20 healthy control participants for recall and recognition of 48 target words. During encoding, emotional and nonemotional words were either presented in sentences (read condition) or used to form sentences (generate condition). Both word emotionality and generative processing improved memory performance in all groups. The authors suggest that a similar influence (i.e., cognitive activation) underlies both of these memory-enhancing effects, although the putative origins of the 2 effects are quite different. Neuropsychological underpinnings and clinical implications of these phenomena are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Eye movements of young and older adults during reading.

The eye movements of young and older adults were tracked as they read sentences varying in syntactic complexity. In Experiment 1, cleft object and object relative clause sentences were more difficult to process than cleft subject and subject relative clause sentences; however, older adults made many more regressions, resulting in increased regression path fixation times and total fixation times, than young adults while processing cleft object and object relative clause sentences. In Experiment 2, older adults experienced more difficulty than young adults while reading cleft and relative clause sentences with temporary syntactic ambiguities created by deleting the that complementizers. Regression analyses indicated that readers with smaller working memories need more regressions and longer fixation times to process cleft object and object relative clause sentences. These results suggest that age-associated declines in working memory do affect syntactic processing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Beyond Boundary Objects: Collaborative Reuse in Aircraft Technical Support

Boundary objects are a critical, but understudied, theoretical construct in CSCW. Through a field study of aircraft technical support, we examined the role of boundary objects in the practical achievement of safety by service engineers. Their resolution of repair requests was preserved in the organization’s memory via three compound boundary objects. These crystallizations did not manifest a static interpretation, but instead were continually reinterpreted in light of meta-negotiations. This suggests design implications for organizational memory systems which can more fluidly represent the meta-negotiations surrounding boundary objects.     

TMS320 F206定点DSP芯片开发实践

以TMS320F206为例,着重探讨了DSP系统开发过程中的硬件设计与调试、软件设计中的流水线冲突、等待状态设置以及如何利用闪速存储器等相关问题.     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

离散Hopfield神经网络和联想记忆的开关电流技术实现

研究了离散Ｈｏｐｆｉｅｌｄ神经网络（ＤＨＮＮ）和联想记忆神经网络的开关电流技术实现，利用多权输入跨导，开关电流延迟器（ＳＩＤ）和可编程电流比较器（ＰＣＣ）实现了离散Ｈｏｐｉｅｌｄ神经网络，并提出了利用离散Ｈｏｐｆｉｅｌｄ神经网络实现自联想记忆时相应的开关电流电路，所提出了开关电流神经网络适宜于超大规模集成，能在低电压（如３．３Ｖ）下工作。     

Drugs, memory, and metamemory: A dose-effect study with lorazepam and scopolamine.

This experiment was designed to use the graded dose-related amnesia produced by the benzodiazepine lorazepam (1.0, 2.0 mg/70 kg, oral) and the anticholinergic scopolamine (0.3, 0.6 mg/70 kg, subcutaneous) as a tool to explore the cognitive and neurochemical mechanisms underlying metamemory in the judgment of learning paradigm, with a placebo-controlled independent groups design in healthy volunteers (n=12/group). Results provide evidence for a pharmacological dissociation between effects on memory versus metamemory (relative accuracy of item-by-item monitoring) across a range of levels of memory performance and suggest that the drugs selectively impair those aspects of metamnemonic monitoring that require participants' awareness of their overall current state of functioning (absolute accuracy of prospective item-by-item monitoring, prospective global monitoring) but not those that rely solely on assessment of individual item characteristics (relative accuracy of item-by-item monitoring). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Network traffic prediction based on a new time series model

Fast and accurate methods for predicting traffic properties and trend are essential for dynamic network resource management and congestion control. With the aim of performing online and feasible prediction of network traffic, this paper proposes a novel time series model, named adaptive autoregressive (AAR). This model is built upon an adaptive memory‐shortening technique and an adaptive‐order selection method originally developed by this study. Compared to the conventional one‐step ahead prediction using traditional Box–Jenkins time series models (e.g. AR, MA, ARMA, ARIMA and ARFIMA), performance results obtained from actual Internet traffic traces have demonstrated that the proposed AAR model is able to support online prediction of dynamic network traffic with reasonable accuracy and relatively low computation complexity. Copyright © 2005 John Wiley & Sons, Ltd.     

Influence of Missing Values on the Prediction of a Stationary Time Series

Abstract. The influence of missing observations on the linear prediction of a stationary time series is investigated. Simple bounds for the prediction error variance and asymptotic behaviours for short and long‐memory processes respectively are presented.