Study of interaction between drug enantiomers and serum albumin by capillary electrophoresis

The interaction between drugs and human serum albumin (HSA) was investigated by capillary electrophoresis (CE). It involves stereoselectivity, drug displacement and synergism effects. Under protein-drug binding equilibrium, the unbound concentrations of drug enantiomers were measured by frontal analysis (FA). The stereoselectivity of verapamil (VER) binding to HSA was proved by the different free fractions of two enantiomers. In physiological pH (7.4, ionic strength 0.17 phosphate buffer) when 300 mu M (+/-) VER were equilibrated with 500 mu M HSA, the concentration of unbound S-VER was about 1.7 times its antipode. The binding constants of two enantiomers, KR-VER and KS-VER, were 2670 and 850 M-1, respectively. However, no obvious stereoselective binding of propranolol (PRO) to HSA was observed. Trimethyl-beta-cyclodextrin (45 mM) was used as a chiral selector in pH 2.5 phosphate buffer. Several drug systems were studied by the method. When ibuprofen (IBU) was added into VER-HSA solution. R-VER was partially displaced while S-VER was not displaced at all. A binding synergism effect between bupivacaine (BUP) and verapamil was observed and further study suggested that verapamil and bupivacaine occupy different binding site of HSA (site II and site III, respectively).

空间及言语工作记忆任务的情绪效应：来自ERP/ fMRI的证据

In the present study, based on processing efficiency theory, we used the event-related potentials (ERP) and functional magnetic resonance image (fMRI) techniques to explore the underlying neutral mechanism of influences of negative emotion on three subsystems of working memory, phonological loop、 visuospatial sketh pad and the central executive. The modified DSMT (delayed matching-to-sample task) and n-back tasks were adopted and IAPS (International Affective Picture System) pictures were employed to induce the expected emotional state of subjects. The main results and conclusions obtained in the series of experiments are as the following: 1. In DSM tasks, we found P200 and P300 were reduced by negative emotion in both spatial and verbal tasks, however the increased negative slow wave were only observed in spatial tasks, not in verbal tasks. 2. In n-back tasks, the updating function of WM associated P300 was affected by negative emotion only in spatial tasks, not in verbal tasks. Current density analysis revealed strong current density in the fronto-parietal cortex only in the spatial tasks as well. 3. We adopted fMRI-block design and ROIs analysis, and found significant emotion and task effects in spatial WM-associated right superior parietal cortex; only emotion effect in verbal WM-associated Broca’s area; the interaction effect in attention-associated medial prefrontal area and bilateral inferior parietal cortex. These results implied the negative emotion mainly disturbed the spatial WM-related areas, and the attention control system play a key role in the interaction of spatial WM and negative emotion. 4. to further examine the effects of positive、negative and neutral emotion on tasks with different cognitive loads, the selective effect of emotion on the ERP components of spatial WM was only found in 2-back tasks, not in visual searching tasks. So, firstly the positive emotion as well as negative emotion selectively disturbed on spatial WM in light of the attention resource competition mechanism. Secondly, the selective influences based on the different WM systems, not the properties of spatial and verbal information. At last, the manner of the interaction of emotion and cognition is correlated with the cognitive load.

A Lifetime-based Garbage Collector for LISP Systems on General-Purpose Computers

Garbage collector performance in LISP systems on custom hardware has been substantially improved by the adoption of lifetime-based garbage collection techniques. To date, however, successful lifetime-based garbage collectors have required special-purpose hardware, or at least privileged access to data structures maintained by the virtual memory system. I present here a lifetime-based garbage collector requiring no special-purpose hardware or virtual memory system support, and discuss its performance.

Meta-stable memory in an artificial immune network

Neal, M., Meta-stable memory in an artificial immune network, Proceedings of the 2nd International Conference on Artificial Immune Systems {ICARIS}, Springer, 168-180, 2003,LNCS 2787/2003

Diminishing Returns of Engineering Effort in Telerobotic Systems

Wilson, M.S. and Neal, M.J., 'Diminishing Returns of Engineering Effort in Telerobotic Systems', IEEE Transactions on Systems, Man and Cybernetics - Part A:Systems and Humans, 2001, September, volume 31, number 5, pp 459-465, IEEE Robotics and Automation Society, ed. Dautenhahn,K., Special Issue on Socially Intelligent Agents - The Human in the Loop

Interaction between coronal mass ejections and the solar wind

Jones, R. A.; Breen, A. R.; Fallows, R. A.; Canals, A.; Bisi, M. M.; Lawrence, G. (2007). Interaction between coronal mass ejections and the solar wind, Journal of Geophysical Research, 112, Issue A8 RAE2008

ROSSI: Emergence of communication in Robots through Sensorimotor and Social Interaction

ROSSI: Emergence of communication in Robots through Sensorimotor and Social Interaction, T. Ziemke, A. Borghi, F. Anelli, C. Gianelli, F. Binkovski, G. Buccino, V. Gallese, M. Huelse, M. Lee, R. Nicoletti, D. Parisi, L. Riggio, A. Tessari, E. Sahin, International Conference on Cognitive Systems (CogSys 2008), University of Karlsruhe, Karlsruhe, Germany, 2008 Sponsorship: EU-FP7

Trauma and the Memory of Politics

Edkins, Jenny, Trauma and the Memory of Politics (Cambridge: Cambridge University Press, 2003), pp.xvii+265 RAE2008

Mermera: Non-Coherent Distributed Shared Memory for Parallel Computing

The proliferation of inexpensive workstations and networks has prompted several researchers to use such distributed systems for parallel computing. Attempts have been made to offer a shared-memory programming model on such distributed memory computers. Most systems provide a shared-memory that is coherent in that all processes that use it agree on the order of all memory events. This dissertation explores the possibility of a significant improvement in the performance of some applications when they use non-coherent memory. First, a new formal model to describe existing non-coherent memories is developed. I use this model to prove that certain problems can be solved using asynchronous iterative algorithms on shared-memory in which the coherence constraints are substantially relaxed. In the course of the development of the model I discovered a new type of non-coherent behavior called Local Consistency. Second, a programming model, Mermera, is proposed. It provides programmers with a choice of hierarchically related non-coherent behaviors along with one coherent behavior. Thus, one can trade-off the ease of programming with coherent memory for improved performance with non-coherent memory. As an example, I present a program to solve a linear system of equations using an asynchronous iterative algorithm. This program uses all the behaviors offered by Mermera. Third, I describe the implementation of Mermera on a BBN Butterfly TC2000 and on a network of workstations. The performance of a version of the equation solving program that uses all the behaviors of Mermera is compared with that of a version that uses coherent behavior only. For a system of 1000 equations the former exhibits at least a 5-fold improvement in convergence time over the latter. The version using coherent behavior only does not benefit from employing more than one workstation to solve the problem while the program using non-coherent behavior continues to achieve improved performance as the number of workstations is increased from 1 to 6. This measurement corroborates our belief that non-coherent shared memory can be a performance boon for some applications.

Communicable Memory and Lazy Barriers for Bulk Synchronous Parallelism in BSPk

Communication and synchronization stand as the dual bottlenecks in the performance of parallel systems, and especially those that attempt to alleviate the programming burden by incurring overhead in these two domains. We formulate the notions of communicable memory and lazy barriers to help achieve efficient communication and synchronization. These concepts are developed in the context of BSPk, a toolkit library for programming networks of workstations|and other distributed memory architectures in general|based on the Bulk Synchronous Parallel (BSP) model. BSPk emphasizes efficiency in communication by minimizing local memory-to-memory copying, and in barrier synchronization by not forcing a process to wait unless it needs remote data. Both the message passing (MP) and distributed shared memory (DSM) programming styles are supported in BSPk. MP helps processes efficiently exchange short-lived unnamed data values, when the identity of either the sender or receiver is known to the other party. By contrast, DSM supports communication between processes that may be mutually anonymous, so long as they can agree on variable names in which to store shared temporary or long-lived data.

An Efficient User-Level Shared Memory Mechanism for Application-Specific Extensions

This paper focuses on an efficient user-level method for the deployment of application-specific extensions, using commodity operating systems and hardware. A sandboxing technique is described that supports multiple extensions within a shared virtual address space. Applications can register sandboxed code with the system, so that it may be executed in the context of any process. Such code may be used to implement generic routines and handlers for a class of applications, or system service extensions that complement the functionality of the core kernel. Using our approach, application-specific extensions can be written like conventional user-level code, utilizing libraries and system calls, with the advantage that they may be executed without the traditional costs of scheduling and context-switching between process-level protection domains. No special hardware support such as segmentation or tagged translation look-aside buffers (TLBs) is required. Instead, our ``user-level sandboxing'' mechanism requires only paged-based virtual memory support, given that sandboxed extensions are either written by a trusted source or are guaranteed to be memory-safe (e.g., using type-safe languages). Using a fast method of upcalls, we show how our mechanism provides significant performance improvements over traditional methods of invoking user-level services. As an application of our approach, we have implemented a user-level network subsystem that avoids data copying via the kernel and, in many cases, yields far greater network throughput than kernel-level approaches.

Cuckoo: a Language for Implementing Memory- and Thread-safe System Services

This paper is centered around the design of a thread- and memory-safe language, primarily for the compilation of application-specific services for extensible operating systems. We describe various issues that have influenced the design of our language, called Cuckoo, that guarantees safety of programs with potentially asynchronous flows of control. Comparisons are drawn between Cuckoo and related software safety techniques, including Cyclone and software-based fault isolation (SFI), and performance results suggest our prototype compiler is capable of generating safe code that executes with low runtime overheads, even without potential code optimizations. Compared to Cyclone, Cuckoo is able to safely guard accesses to memory when programs are multithreaded. Similarly, Cuckoo is capable of enforcing memory safety in situations that are potentially troublesome for techniques such as SFI.

A Customizable Camera-based Human Computer Interaction System Allowing People With Disabilities Autonomous Hands Free Navigation of Multiple Computing Task

Many people suffer from conditions that lead to deterioration of motor control and makes access to the computer using traditional input devices difficult. In particular, they may loose control of hand movement to the extent that the standard mouse cannot be used as a pointing device. Most current alternatives use markers or specialized hardware to track and translate a user's movement to pointer movement. These approaches may be perceived as intrusive, for example, wearable devices. Camera-based assistive systems that use visual tracking of features on the user's body often require cumbersome manual adjustment. This paper introduces an enhanced computer vision based strategy where features, for example on a user's face, viewed through an inexpensive USB camera, are tracked and translated to pointer movement. The main contributions of this paper are (1) enhancing a video based interface with a mechanism for mapping feature movement to pointer movement, which allows users to navigate to all areas of the screen even with very limited physical movement, and (2) providing a customizable, hierarchical navigation framework for human computer interaction (HCI). This framework provides effective use of the vision-based interface system for accessing multiple applications in an autonomous setting. Experiments with several users show the effectiveness of the mapping strategy and its usage within the application framework as a practical tool for desktop users with disabilities.

From Working Memory to Long-term Memory and Back: Linked but Distinct

Neural models have proposed how short-term memory (STM) storage in working memory and long-term memory (LTM) storage and recall are linked and interact, but are realized by different mechanisms that obey different laws. The authors' data can be understood in the light of these models, which suggest that the authors may have gone too far in obscuring the differences between these processes.

A Memory Model for Concept Hierarchy Representation and Commonsense Reasoning

Most associative memory models perform one level mapping between predefined sets of input and output patterns1 and are unable to represent hierarchical knowledge. Complex AI systems allow hierarchical representation of concepts, but generally do not have learning capabilities. In this paper, a memory model is proposed which forms concept hierarchy by learning sample relations between concepts. All concepts are represented in a concept layer. Relations between a concept and its defining lower level concepts, are chunked as cognitive codes represented in a coding layer. By updating memory contents in the concept layer through code firing in the coding layer, the system is able to perform an important class of commonsense reasoning, namely recognition and inheritance.