N连接糖基化过程的动态图建模

单克隆抗体药物是当前国际市场上最具价值的药品种类之一,而N连接糖基化反应是单克隆抗体制备过程中非常重要的一个环节.本文采用有向图来描述糖蛋白结构,图模型描述反应网络,因此可以方便地采用分支限界法来生成整个反应网络.而且在这种图模型表示的反应网络中,糖基化反应的分析计算会变得更为容易.综合考虑实际细胞动态变化中高尔基体内转运反应的影响,提出了N连接糖基化反应的动态平衡方程,相比较现有的稳态模型可以提供更多的反应过程信息,并且为反应质量的实时控制做出了理论依据.另外,本文以理论计算与实测值偏差为目标,采用遗传算法对反应过程的大量生化参数进行优化,从而提高计算模型的精度.为了提升仿真模型的计算能力和对实验设计的指导作用,本文基于C++开发了一款专用的糖基化仿真计算平台,提供网络结构的可视化、反应过程的动态曲线、反应参数优化等功能.通过对比本文模型的数据分析与实际机理分析一致验证了模型的有效性.     

Dynamic 3D modelling for architectural design

A graphics design system employing 2D input and display devices (such as the pen and tablet and the calligraphic CRT) to input, edit, and view 3D objects representing landscapes and architectural structures in realtime is discussed. Landscape is entered via a procedure that uses an inking algorithm to obtain 2D data defining the site's contours and additional available interactive devices to obtain the contour heights. Extrusion techniques and compound transformations are used to generate volumes from facial elements input via a suite of rubberband algorithms that take advantage of the graphics hardware. Dynamic menus, displayed transformation parameter values and extensive editing features facilitate user interaction. Architectural studies of complex structures built by combining basic architectural units input using extrusion techniques are presented.     

压电陶瓷执行器的动态迟滞非线性特性建模

针对精密定位系统中压电陶瓷执行器的迟滞非线性特性建模问题,提出了一种基于Hammerstein迟滞模型的建模方法。通过引入一个Backlash类的算子来描述迟滞非线性的轮廓。在利用"扩展输入空间法"将迟滞特性的多值映射转换为一一映射的基础上,采用引力搜索算法优化的支持向量回归机建立静态迟滞模型。为体现迟滞的动态特性,用ARX模型表征迟滞环的率相关性,从而建立了Hammerstein级联模型。并从精密定位系统中采集了实测数据,通过电容传感器获取压电陶瓷执行器给定电压下的位移值,对所提出的模型进行了实验。实验表明:该模型具有较好的性能,辨识过程简便且易于工程实现。     

Dynamic modelling using neural networks

A neural network structure is presented that uses feedback of unmeasured system states to represent dynamic systems more efficiently than conventional feedforward and recurrent networks, leading to better predictions, reduced training requirement and more reliable extrapolation. The structure identifies the actual system states based on imperfect knowledge of the initial state, which is available in many practical systems, and is therefore applicable only to such systems. It also enables a natural integration of any available partial state-space model directly into the prediction scheme, to achieve further performance improvement. Simulation examples of three varied dynamic systems illustrate the various options and advantages offered by the state-feedback neural structure. Although the advantages of the proposed structure, compared with the conventional feedforward and recurrent networks, should hold for most practical dynamic systems, artificial systems can readily be created and real systems can surely be found for which one or more of these advantages would vanish or even get reversed. Caution is therefore recommended against interpreting the suggested advantages as strict theorems valid in all situations.     

压电舵机动态迟滞建模与带有鲁棒干扰观测器的两自由度控制

压电宏纤维复合材料(MFC)驱动的舵机具有功耗低、质量小以及可靠性高等优点,在无人飞行器领域有很大的应用潜力.压电材料的动态迟滞非线性会降低舵机的控制精度和稳定性, MFC柔性结构使舵机易受外扰影响.本文首先建立MFC舵机Hammerstein动态迟滞非线性模型,并设计了迟滞逆补偿器.针对模型不确定性和外扰影响,设计了带有鲁棒干扰观测器的二自由度控制器,保证在外扰和模型不确定性下控制系统的鲁棒性. MFC舵机控制实验结果表明,所设计的控制器具有良好的抗干扰性能和鲁棒性,较传统干扰观测器显著提高了控制性能.     

压电作动器的动态迟滞建模与H∞鲁棒控制

压电作动器具有率相关动态迟滞非线性特性,给传统建模和控制技术提出了挑战.本文针对压电作动器,提出了一种基于Bouc-Wen的Hammerstein率相关迟滞非线性模型,其中Bouc-Wen模型和线性动态模块分别用于描述系统的静态迟滞非线性特性和率相关特性.同时,构造了一个基于Bouc-Wen模型的迟滞补偿器,将迟滞补偿器与被控对象串联使系统线性化;并建立了不确定性系统模型,提出了一种H∞鲁棒跟踪控制方案,可以实现给定频率范围内单频率和复合频率参考信号的良好跟踪.实验结果表明,所建动态模型具有良好的泛化能力,跟踪控制相对误差小于8%,证明了所提出方法的有效性.     

Dynamic image modelling by neural networks

Sometimes an image can be characterized with the help of a dynamic system in terms of a first-order differential equation, e.g. when a scanner output contains additive noise and/or is degraded due to interaction between the sensing elements (the cameras) or by other phenomena. In this paper, an algorithm for image estimation from the noisy output of a scanner is hypothesized. Determination of the parameters A, B, and the C matrices of a dynamic system leads to the design of an estimator whose input is the output of a scanner with uniform speed. A portion of the overall algorithm using neural networks trained by a gradient descent learning algorithm is discussed in detail. In particular, the determination of A. B, C from states, time derivatives of states and inputs are highlighted. The details of implementation are included. The salient points regarding the development of the complete algorithm are discussed. It is hoped that the results achieved so far will give rise to new techniques for the application of neural networks to image enhancement in particular and to image processing in general.     

Dynamic modelling of a four-legged robot

A unified dynamic modelling approach of closed and/or open kinematic chain mechanisms is established. It is based on the use of the Newton-Euler formalism and the explicit formulation of kinematic holonomic constraints for the closed loop mechanisms. The approach is then applied to derive the dynamic modelling of a four-legged robot adopting a walking gait. The different movement sequences of the gait are analysed in order to calculate the all necessary terms in the dynamic equations of the quadruped robot.Nomenclature g acceleration vector due to the gravity - m _i mass of bodyS _i - G _i mass centre of bodyS _i - I _i inertia tensor of the bodyS _i about its mass centre - f coefficient of viscous friction - V _Gi 3-dim absolute velocity vector - _i 3-dim absolute angular velocity vector - t _i 6-dim twist vector of the bodyS _i defined as - n, l number of bodies, joints - d _i number of degree of freedom of the jointi - I _d 3×3 identity matrix - T _infi ^supr 6-dim wrench vector acting on the bodyS _i in whichr stands for:l (constraint wrench),g (gravity wrench),f (friction wrench),e (external wrench),m (driving wrench) - _i joint angle of the bodyS _i - O₍₃₎ 3-dim zero vector     

Dynamic aspects of visual modelling languages

A large class of diagrammatic languages falls under the broad definition of “executable graphics”, meaning that some transformational semantics can be devised for them. On the other hand, the definition of static aspects of visual languages often relies on some form of parsing or constructive process. We propose here an approach to the definition of visual languages syntax and semantics based on a notion of transition as production/consumption of resources. Transitions can be represented in forms which are intrinsic to the diagrams or external to them. A collection of abstract metamodels is presented to discuss the approach.     

Dynamic delamination modelling using interface elements

Existing techniques in explicit dynamic Finite Element (FE) codes for the analysis of delamination in composite structures and components can be simplistic, using simple stress-based failure function to initiate and propagate delaminations.This paper presents an interface modelling technique for explicit FE codes. The formulation is based on damage mechanics and uses only two constants for each delamination mode; firstly, a stress threshold for damage to commence, and secondly, the critical energy release rate for the particular delamination mode. The model has been implemented into the LLNL DYNA3D Finite Element (FE) code and the LS-DYNA3D commercial FE code.The interface element modelling technique is applied to a series of common fracture toughness based delamination problems, namely the DCB, ENF and MMB tests. The tests are modelled using a simple dynamic relaxation technique, and serves to validate the methodology before application to more complex problems.Explicit Finite Elements codes, such as DYNA3D, are commonly used to solve impact type problems. A modified BOEING impact test at two energy levels is used to illustrate the application of the interface element technique, and it’s coupling to existing in-plane failure models. Simulations are also performed without interface elements to demonstrate the need to include the interface when modelling impact on composite components.     

Dynamic modelling of a simple existence constraint

A method is described for systematically deriving from a static formulation of a simple existence constraint the corresponding dynamic formulation. The latter formulation is embedded, under the form of applicability conditions, in a set of axiomatized update operations. A many-sorted first-order predicate calculus is used as the specification language. Update behaviour issues are identified and discussed.     

Dynamic metabolic modelling under the balanced growth condition

The issue of bioprocess dynamical modelling is addressed in the situation where measurements of extracellular species are the only available data besides measurements of the biomass itself. This question is investigated under the assumption that a metabolic network connecting the extracellular species is available. A metabolic flux analysis is first performed in order to test the consistency of the metabolic network. The elementary flux modes are computed and translated into a set of macro-reactions connecting the extracellular substrates and products. Then a dynamical model, compatible with the underlying metabolic network, is build on the basis of these macro-reactions. The approach is illustrated with the example of CHO cells cultivated in stirred flasks on a serum-free medium.     

Dynamic modelling of customer preferences for product design using DENFIS and opinion mining

Previous studies mainly employed customer surveys to collect survey data for understanding customer preferences on products and developing customer preference models. In reality, customer preferences on products could change over time. Thus, the time series data of customer preferences under different time periods should be collected for the modelling of customer preferences. However, it is difficult to obtain the time series data based on customer surveys because of long survey time and substantial resources involved. In recent years, a large number of online customer reviews of products can be found on various websites, from which the time series data of customer preferences can be extracted easily. Some previous studies have attempted to analyse customer preferences on products based on online customer reviews. However, two issues were not addressed in previous studies which are the fuzziness of the sentiment expressed by customers existing in online reviews and the modelling of customer preferences based on the time series data obtained from online reviews. In this paper, a new methodology for dynamic modelling of customer preferences based on online customer reviews is proposed to address the two issues which mainly involves opinion mining and dynamic evolving neural-fuzzy inference system (DENFIS). Opinion mining is adopted to analyze online reviews and perform sentiment analysis on the reviews under different time periods. With the mined time series data and the product attribute settings of reviewed products, a DENFIS approach is introduced to perform the dynamic modelling of customer preferences. A case study is used to illustrate the proposed methodology. The results of validation tests indicate that the proposed DENFIS approach outperforms various adaptive neuro-fuzzy inference system (ANFIS) approaches in the dynamic modelling of customer preferences in terms of the mean relative error and variance of errors. In addition, the proposed DENFIS approach can provide both crisp and fuzzy outputs that cannot be realized by using existing ANFIS and conventional DENFIS approaches.     

Dynamic probabilistic networks for modelling and identifying dynamic systems: a MCMC approach

In this article we deal with the problem of interpreting data coming from a dynamic system by using causal probabilistic (CPN), a probabilistic graphical model particularly appealing in Intelligent Data Analysis. We discuss the different approaches presented in the literature, outlining their pros and cons through a simple training example. Then, we present a new method for reconstructing the state of the dynamic system, based on Markov Chain Monte Carlo algorithms, called dynamic probabilistic network smoothing (DPN-smoothing). Finally, we present an example of the application of DPN-smoothing in the field of signal deconvolution.     

Dynamic physical and economic modelling of riparian restoration options

A dynamic simulation framework is used to compare benefit-cost ratios of riparian restoration investment strategies to pursue ecosystem service benefits. The model is meant to be adaptable to generic restoration planning applications, with the Middle Rio Grande riparian corridor in Albuquerque, New Mexico, U.S.A. presented here as the illustrating case. Model inputs include ecosystem service values from an original choice experiment, values from regional benefit transfer studies, and information from land managers.The model includes three control variable modules: forest management, river restoration, and recreation infrastructure. Investment influences these modules, which in turn affect ecosystem service flows for the region. The model is exercised to compare a “No-Action” alternative with “Optimal Benefit-Cost Ratio” restoration funding. An extended sensitivity analysis explores a range of both physical and economic assumptions. The analysis has two major outcomes. The first is that directed restoration funding yields significant gains as compared with No-Action for all scenarios tested. The second major finding is that although optimized benefit-cost ratios are above unity for all “states of the world” tested, the ratio itself and funding patterns varied widely. These sensitivities underscore the need for a transparent adaptive management decision process supported by tools aimed not at deterministic prediction, but rather at structuring dialogue and inquiry into issues that defy simple intuition.     

Dynamic modelling of metals – Time scales and target loads

Over the past decade steady-state methods have been developed to assess critical loads of metals avoiding long-term risks in view of food quality and eco-toxicological effects on organisms in soils and surface waters. However, dynamic models are needed to estimate the times involved in attaining a certain chemical state in response to input (deposition, fertilizers or manure) scenarios. Starting from a mass balance, a universal dynamic model was developed by defining appropriate dimensionless quantities, which depend only on the metal under consideration. For any given metal, the model (differential equation) is characterised by the interplay of four (dimensionless) variables: the initial condition, i.e. the concentration at the start of the simulation, the input (driving force), time, and the concentration of the metal at any given point in time. Depending on the question asked, one of these quantities is fixed and the functional relationship between the other three provides the answer.The model allows to investigate the time development of the soil chemical status under a constant future input of the metal to predict (i) the future metal concentration as a function of time (scenario analysis), (ii) the time when a prescribed chemical state (e.g., a critical concentration or steady state) is reached (delay times), and (iii) which future input (reduction) is needed to reach a prescribed chemical state within a prescribed time period (target loads). The general solutions are illustrated with concrete examples, using (average) data from the Netherlands for four metals: cadmium, lead, copper and zinc. The modelling approach set out in this paper illustrates the potential use of dynamic models in the support of policies aimed at reducing emissions of metals by providing an understanding of the structural properties of the model, independent of site-specific parameters. It thus allows assessing temporal behaviour and time scales before embarking on detailed modelling for individual sites.     

Dynamic modelling and stabilization of a new configuration of two-wheeled machines

This paper presents a novel design of two-wheeled vehicles and an associated stabilization approach. The proposed design provides the vehicle with more flexibility in terms of increased degrees of freedom which enable the vehicle to enlarge its working space. The additional translational degree of freedom (DOF), offered by the linear actuator, assists an attached payload to reach different levels of height as and when required. The model of the system mimics the scenario of the double inverted pendulum on a moving base, with the added DOF. Lagrangian dynamic formulation is used to derive the system dynamics. Joints frictions based on the Coulomb friction model are considered so as to retain nonlinear characteristics of the system. A PD-PID robust control approach is derived for the stabilization of the system. An investigation of the impact of damping associated with joints on the stability of the system is carried out. Simulation results validating the model and the control approach are presented and discussed.     

Dynamic influent pollutant disturbance scenario generation using a phenomenological modelling approach

Activated Sludge Models are widely used for simulation-based evaluation of wastewater treatment plant (WWTP) performance. However, due to the high workload and cost of a measuring campaign on a full-scale WWTP, many simulation studies suffer from lack of sufficiently long influent flow rate and concentration time series representing realistic wastewater influent dynamics. In this paper, a simple phenomenological modelling approach is proposed as an alternative to generate dynamic influent pollutant disturbance scenarios. The presented set of models is constructed following the principles of parsimony (limiting the number of parameters as much as possible), transparency (using parameters with physical meaning where possible) and flexibility (easily extendable to other applications where long dynamic influent time series are needed). The proposed approach is sub-divided in four main model blocks: 1) model block for flow rate generation, 2) model block for pollutants generation (carbon, nitrogen and phosphorus), 3) model block for temperature generation and 4) model block for transport of water and pollutants. The paper is illustrated with the results obtained during the development of the dynamic influent of the Benchmark Simulation Model no. 2 (BSM2). The series of simulations show that it is possible to generate a dry weather influent describing diurnal flow rate dynamics (low rate at night, high rate during day time), weekend effects (with different flow rate during weekends, compared to weekdays), holiday effects (where the wastewater production is assumed to be different for a number of weeks) and seasonal effects (with variations in the infiltration and thus also the flow rate to the WWTP). In addition, the dry weather model can be extended with a rain and storm weather generator, where the proposed phenomenological model can also mimic the “first flush” effect from the sewer network and the influent dilution phenomena that are typically observed at full-scale WWTPs following a rain event. Finally, the extension of the sewer system can be incorporated in the influent dynamics as well: the larger the simulated sewer network, the smoother the simulated diurnal flow rate and concentration variations. In the discussion, it is pointed out how the proposed phenomenological models can be expanded to other applications, for example to represent heavy metal or organic micro-pollutant loads entering the treatment plant.