Kinetics and Statistical Distributions of Single-Molecule Conformational Dynamics

We developed a coarse-grained yet microscopic detailed model to study the statistical fluctuations of single-molecule protein conformational dynamics of adenylate kinase. We explored the underlying conformational energy landscape and found that the system has two basins of attractions, open and closed conformations connected by two separate pathways. The kinetics is found to be nonexponential, consistent with single-molecule conformational dynamics experiments. Furthermore, we found that the statistical distribution of the kinetic times for the conformational transition has a long power law tail, reflecting the exponential density of state of the underlying landscape. We also studied the joint distribution of the two pathways and found memory effects.

具有AGV和AS/RS的装配线物流系统分析

阐述了具有自动导引车(AGV)和自动存取系统(AS/RS)的物流系统的工作流程,建立了该类物流系统的排队网络模型,分析了系统的性能与系统设计参数之间的关系,为设计具有AGV和AS/RS的复杂物流系统提供依据。

基于神经网络的一类非线性系统模型参考控制

针对一类非线性系统,提出了一种神经网络模型参考控制方案。在训练实现对象模型的网络和实现控制器的网络时,由状态方程产生训练样本。通过对倒立摆系统的仿真实验验证了控制方案和样本生成策略的有效性,在仿真实验中用不同初始状态验证了训练后的神经网络的泛化能力。

考虑机器故障和有限缓冲器的级联生产线系统的建模和分析

本文在建立机器故障和系统阻塞的近似模型的基础上给出了系统的排队网络模型.利用这一模型,可以对问题解析地求解,以分析系统的性能,而不需要复杂的计算.仿真结果表明,其解的精度令人满意.

基于人工神经网络的钛合金焊接接头机械性能预测

采用多层前向反馈神经网络模型,对钛合金钨极氩弧焊的焊接接头机械性能进行了模拟和预测。其中,输入参数包括钛合金成分、冷却速度和热处理参数;输出参数包括5个重要的机械性能,即极限抗拉强度、延伸率、断面收缩率、屈服强度和硬度。详细分析了铝和钒这2种元素对机械性能的影响。

小湾坝基卸荷岩体参数研究

The Xiao-wan Power Station is the second highest arch dam in the world under construction. The height of the dam is about 292m. Large-scale excavation in the dam foundation of Xiao-wan Power Station has brought intensive unloading phenomenon. We collected a large number of firsthand data on unloaded rock mass in dam foundation, which supplies a natural testing ground for researching unloaded rock mass after excavation. Detailed study was carried out on the parameters of unloaded rock mass in the dam foundation of Xiao-wan Power Station. The study is not only importance for the Xiao-wan Power Station, but also has important instruction significance to similar projects in the Southwest of China. In order to study the mechanical parameters of unloaded rock mass, large field and laboratory tests were carried out. The test results showed the size effect of the sample is obvious. The change of deformation modulus of rock is not obvious. However, the Poisson's ratio of rock is increased under unloaded condition, its value is even more than 0.5. The theoretical forecasted results is accordance to the field tests including sound wave data and deformation monitoring data, which shows the forecasted results were reasonable. The soften yield criterion was adopted in the thesis to study the characteristics of the brittle rock mass in order to simulate their brittle failures. Based on the study results above, the transform of the structural plane network model to the numerical one was carried out, which made it feasible to consider the influence of large amount joints on the mechanical characteristic of rock mass in the numerical analyses. Using a factor, the degree of the damage or strengthen of rock mass can be determined rapidly, which proposed a rapid and feasible method for the determination of the parameters of rock mass.

砂砾岩储层流动单元四维模型研究

This article is an important part of "95" technological subject of SINOPEC. It has a large number of difficulties and workloads, and has significant theoretical meanings and practical value. The study area is composed of sandstone & conglomerate reservoir of alluvial fan & fan delta, which belong to Sha3 lower member and Sha4 upper member of lower tertiary of Yong'an Town Oilfield in Dongying Depression. The target stataum develops in the hanging wall of the synsedimentary fault in the scarp zone of Dongying Depression. The frequently intense movements result in the variation of sandstone and conglomerate reservoir and the evolution of the time and space of Sha3 lower member and Sha4 upper member in Yong'an Town Oilfield. As a result, it is difficult for the individual reservoir correlation at the root of fan, which bring about a tackle problem for the exploitation of oilfield. In this background, the research of fluid units will be more difficult. In this article, the new concepts, the new methods, and the new techniques of sedimentology, petroleum geology, reservoir geology, physics of crystal surface, dynamic & static state reservoir description and well logging geology are synthetically applied, and the computer technology are made full uses of, and the identifying, dividing and appraising of the two-formation-type sandstone & conglomerate reservoir fluid units of Sha3 lower member and Sha4 upper member systemically analyzed in Yong'an Town Oilfield, Dongying Depression. For the first time, the single-well model, the section model, the plane model, the nuclear magnetism log model, the microcosmic network model, the 4-D geology model and the simulation model of the two-formation-type reservoir fluid units of the of sandstone & conglomerate reservoir of Sha3 lower member and Sha4 upper member are established, and the formative mechanism and distributing & enrichment laws of oil-gas of the two type of sandstone and conglomerate reservoir fluid units are revealed. This article established the optimizing, identifying, classifying and appraising standard of the two-formation-type reservoir fluid units of the of sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member, which settles the substantial foundations for static state model of the fluid units, reveals the macroscopic & microcosmic various laws of geometrical static state of the fluid units, and instructs the oil exploitation. This article established static state model of the two-formation-type sandstone and conglomerate reservoir fluid units by using the multi-subject theories, information and techniques, and reveals the geometrical configuration, special distribution and the oil-gas enrichment laws of the sandstone and conglomerate reservoir fluid units. For the first time, we established the nuclear magnetism log model of the two-formation-type sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member, which reveals not only the character and distributing laws of the porosity and permeability, bat also the formation and distribution of the movable fluid. It established six type of microcosmic net model of the two-formation-type sandstone and conglomerate reservoir of Sha3 lower member and Sha4 upper member in the working area by using the advanced theories, such as rock thin section, SEM, image analysis, intrusive mercury, mold, rock C.T. measure & test image etc., which reveals the microcosmic characteristic of porosity & throat, filterate mode and microcosmic oil-gas enrichment laws of the sandstone and conglomerate reservoir. For the first time, it sets up the 4-D model and mathematic model of the sandstone and conglomerate reservoir, which reveals the distributing and evolving laws of macroscopic & microcosmic parameters of the two-formation-type sandstone and conglomerate reservoir and oil-gas in 4-D space. At the same time, it also forecasts the oil-gas distribution and instructs the oilfield exploitation. It established reservoir simulation model, which reveals the filterate character and distributing laws of oil-gas in different porosity & throat net models. This article established the assistant theories and techniques for researching, describing, indicating and forecasting the sandstone and conglomerate reservoir fluid units, and develops the theories and techniques of the land faces faulted basin exploitation geology. In instructing oilfield exploitation, it had won the notable economic & social benefits.

An artificial immune system for continuous analysis of time-varying data

M. Neal, An Artificial Immune System for Continuous Analysis of Time-Varying Data, in Proceedings of the 1st International Conference on Artificial Immune Systems (ICARIS), 2002, eds J Timmis and P J Bentley, volume 1, pages 76-85,

How Could We Explore the Terrorist Issue?

The problem of terrorism can be analyzed by means of a wide array of research theories and models. There is however a question which of these may be regarded as especially useful to analyze different aspects of terrorism such as its reasons, characteristics and effects. Among concepts or theories which more or less fulfill the above-mentioned requirements, one can mention: chaos theory, decision theory, spatial competition theory, exchange theory, black box theory, theory of disaster, system model, model of billiard balls, core model, asymmetrical model, network model or concept of hybridity.

Wizualizacja kartograficzna dostępności przestrzennej w modelu monocentrycznym

Wydział Nauk Geograficznych i Geologicznych

Learning and Production of Movement Sequences: Behavioral, Neurophysiological, and Modeling Perspectives

A growing wave of behavioral studies, using a wide variety of paradigms that were introduced or greatly refined in recent years, has generated a new wealth of parametric observations about serial order behavior. What was a mere trickle of neurophysiological studies has grown to a more steady stream of probes of neural sites and mechanisms underlying sequential behavior. Moreover, simulation models of serial behavior generation have begun to open a channel to link cellular dynamics with cognitive and behavioral dynamics. Here we summarize the major results from prominent sequence learning and performance tasks, namely immediate serial recall, typing, 2XN, discrete sequence production, and serial reaction time. These populate a continuum from higher to lower degrees of internal control of sequential organization. The main movement classes covered are speech and keypressing, both involving small amplitude movements that are very amenable to parametric study. A brief synopsis of classes of serial order models, vis-à-vis the detailing of major effects found in the behavioral data, leads to a focus on competitive queuing (CQ) models. Recently, the many behavioral predictive successes of CQ models have been joined by successful prediction of distinctively patterend electrophysiological recordings in prefrontal cortex, wherein parallel activation dynamics of multiple neural ensembles strikingly matches the parallel dynamics predicted by CQ theory. An extended CQ simulation model-the N-STREAMS neural network model-is then examined to highlight issues in ongoing attemptes to accomodate a broader range of behavioral and neurophysiological data within a CQ-consistent theory. Important contemporary issues such as the nature of working memory representations for sequential behavior, and the development and role of chunks in hierarchial control are prominent throughout.

Cerebellar Learning in an Opponent Motor Controller for Adaptive Load Compensation and Synergy Formation

This paper shows how a minimal neural network model of the cerebellum may be embedded within a sensory-neuro-muscular control system that mimics known anatomy and physiology. With this embedding, cerebellar learning promotes load compensation while also allowing both coactivation and reciprocal inhibition of sets of antagonist muscles. In particular, we show how synaptic long term depression guided by feedback from muscle stretch receptors can lead to trans-cerebellar gain changes that are load-compensating. It is argued that the same processes help to adaptively discover multi-joint synergies. Simulations of rapid single joint rotations under load illustrates design feasibility and stability.

Brightness Perception, Illusory Contours and Corticogeniculate Feedback

A neural network model of early visual processing offers an explanation of brightness effects often associated with illusory contours. Top-down feedback from the model's analog of visual cortical complex cells to model lateral geniculate nucleus (LGN) cells are used to enhance contrast at line ends and other areas of boundary discontinuity. The result is an increase in perceived brightness outside a dark line end, akin to what Kennedy (1979) termed "brightness buttons" in his analysis of visual illusions. When several lines form a suitable configuration, as in an Ehrenstein pattern, the perceptual effect of enhanced brightness can be quite strong. Model simulations show the generation of brightness buttons. With the LGN model circuitry embedded in a larger model of preattentive vision, simulations using complex inputs show the interaction of the brightness buttons with real and illusory contours.

Processing of Synthetic Aperture Radar Images by a Multiscale Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. The segmentation is performed by three "copies" of the BCS and FCS, of small, medium, and large scales, wherein the "short-range" and "long-range" interactions within each scale occur over smaller or larger distances, corresponding to the size of the early filters of each scale. A diffusive filling-in operation within the segmented regions at each scale produces coherent surface representations. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

The Hippocampus and Cerebellum in Adaptively Timed Learning, Recognition, and Movement

The concepts of declarative memory and procedural memory have been used to distinguish two basic types of learning. A neural network model suggests how such memory processes work together as recognition learning, reinforcement learning, and sensory-motor learning take place during adaptive behaviors. To coordinate these processes, the hippocampal formation and cerebellum each contain circuits that learn to adaptively time their outputs. Within the model, hippocampal timing helps to maintain attention on motivationally salient goal objects during variable task-related delays, and cerebellar timing controls the release of conditioned responses. This property is part of the model's description of how cognitive-emotional interactions focus attention on motivationally valued cues, and how this process breaks down due to hippocampal ablation. The model suggests that the hippocampal mechanisms that help to rapidly draw attention to salient cues could prematurely release motor commands were not the release of these commands adaptively timed by the cerebellum. The model hippocampal system modulates cortical recognition learning without actually encoding the representational information that the cortex encodes. These properties avoid the difficulties faced by several models that propose a direct hippocampal role in recognition learning. Learning within the model hippocampal system controls adaptive timing and spatial orientation. Model properties hereby clarify how hippocampal ablations cause amnesic symptoms and difficulties with tasks which combine task delays, novelty detection, and attention towards goal objects amid distractions. When these model recognition, reinforcement, sensory-motor, and timing processes work together, they suggest how the brain can accomplish conditioning of multiple sensory events to delayed rewards, as during serial compound conditioning.