Deducing 1D concentration profiles from EPR imaging: a new approach based on the concept of virtual components and optimization with the genetic algorithm

Application of the genetic algorithm (GA) in conjunction with the concept of virtual components (VC) to determine 1D concentration profiles from EPRI spectra (images) is described. In this approach the concentration profile is expressed as the superposition of virtual components described by analytical functions of the Gaussian and Boltzmann type. The method was implemented in the computer program ACon, which allows for fully automated profile extraction via the nonlinear least-squares fitting of experimental images. The parametric sensitivity of the GA internal parameters such as population size, probabilities of the crossover, mutation and elitist retention to the search space was investigated in detail in order to find their optimal settings. The customized genetic algorithm was evaluated using simulated and experimental test data sets and its performance was compared with the Monte Carlo approach.     

Inverting chaos: Extracting system parameters from experimental data

Given a set of experimental or numerical chaotic data and a set of model differential equations with several parameters, is it possible to determine the numerical values for these parameters using a least-squares approach, and thereby to test the model against the data? We explore this question (a) with simulated data from model equations for the Rossler, Lorenz, and pendulum attractors, and (b) with experimental data produced by a physical chaotic pendulum. For the systems considered in this paper, the least-squares approach provides values of model parameters that agree well with values obtained in other ways, even in the presence of modest amounts of added noise. For experimental data, the "fitted" and experimental attractors are found to have the same correlation dimension and the same positive Lyapunov exponent. (c) 1996 American Institute of Physics.     

A dynamic visco-hyperelastic model of dielectric elastomers and their energy dissipation characteristics

In this paper, we present a model describing the nonlinear dynamic visco-hyperelastic behaviors of dielectric elastomers (DE), with the purpose to explain the material’s dynamic energy dissipation mechanism, and provide convenience for actual design of DE devices. On the basic mechanical properties of the material, a visco-hyperelastic constitutive relationship, derived from Kelvin–Voigt rheological model and expressed as complex modulus, is created at first. Then, from the approximate relationship between harmonic motion frequency and the stretch rate (as well as the amplitude of stretch ratio) of the film, a new model-fitting approach is put forward to obtain the three intrinsic parameters, based on the uniaxial tensile tests for VHB 4910 DE film at different stretch rates (from 0.029 to 0.71 s^?1). Applying the proposed parameters, the hysteresis and energy dissipation behaviors of the DE film are subsequently predicted, showing good agreement with the experimental results. Finally, the influences of the kinematic variable pair on energy dissipation properties are quantitatively investigated.     

混沌系统控制与同步的细菌觅食和差分进化混合算法

将混沌系统的控制与同步问题转化为函数优化问题,提出CDEM算法.把差分进化算法与细菌觅食算法相融合,提高DE算法的收敛性,并利用遗传变异算子保持种群多样性;利用CDEM算法求解混沌系统的控制与同步问题.以典型的离散混沌系统Hénon Map为例进行数值试验,结果表明算法有效、稳定,并分析各个参数对该算法的影响.     

Analytic equation of state for solids with multi-exponential potential based on analytic mean field potential approach and applied to the epsilon phase of solid oxygen

The thermodynamic properties of the ε phase of solid oxygen are studied by using the analytic mean field approach （AMFP）. Analytic expressions for the Helmholtz free energy, internal energy and equation of state of solid oxygen have been derived based on the multi-exponential potential. The formulism for the case of double-exponential （DE） model is applied to the ε phase of solid oxygen. Its four potential parameters are determined through fitting the experimental compression data of the ε phase of solid oxygen. Numerical results of the pressure dependence of the volume calculated by using the AMFP are in good agreement with the original experimental data. This suggests that the AMFP is a useful approach to study the thermodynamic properties of the ε phase of solid oxygen. Furthermore, we predict the variation of the volume, lattice parameters and intermolecular distances with pressure, and some thermodynamic quantities versus volume, at several higher temperatures.     

蒙特卡罗模拟元素特征X射线注量的展宽技术

蒙特卡罗模拟技术可以有效提高核辐射探测分析效率、降低分析成本,在促进X荧光分析技术发展过程中也发挥了重要作用。在应用蒙特卡罗模拟能量色散X荧光分析中,为使蒙特卡罗模拟元素特征X射线注量谱与实验能谱之间的物理差异更小,提出了一种模拟注量展宽算法。首先依据离散统计物理理论,建立了Si-PIN半导体探测器对X射线的响应函数模型,并利用加权非线性最小二乘法拟合得到各系数,再对系数进行归一化处理,得到归一化后的响应函数R(E, E′)。然后利用R(E, E′)对模拟注量进行展宽转换,得到脉冲幅度谱(pulse height spectrum, PHS),使模拟谱更趋近于实验谱,这样就可以通过蒙特卡罗模拟得到与实测能谱一致性较高的模拟能谱。研究中最后利用建立的探测器响应函数模型对Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Sn元素K系全能峰拟合χ2_r值在1.04～1.18范围内,对铜合金样品中六种元素特征X射线模拟注量转换结果与实验值一致性较好,并实现了对多元素混合样品复杂重迭谱的有效模拟和展宽。     

IRIS-HSVD algorithm for automatic quantitation of in vivo 31P MRS

The rapid development of (31)P magnetic resonance spectroscopy (MRS) has enhanced non-invasive measurement of brain metabolites, which is important for biomedical research. The accuracy and efficiency of data post processing and quantification is paramount for MRS applications. One of the difficulties with in vivo(31)P MRS data quantification is the separation of broad line-width resonances from chemical compounds' resonances under a low signal-to-noise ratio condition. Furthermore, the chemical shift of some compounds caused by pH and Mg(2+) concentration can be troublesome. This work aims to develop an automatic algorithm using a state-space based quantification approach to solve the above mentioned problems. To achieve this aim, we utilized an HSVD based adaptive optimizing prior knowledge algorithm, which uses so called "interference" signals to optimize prior knowledge iteratively for parameter optimization. We termed this algorithm IRIS-HSVD, which stands for Iterative Reduction of Interference Signal HSVD. The Monte Carlo evaluations of the algorithm were conducted with simulated data using in vivo parameters commonly obtained from a 4T scanner. The performance of this algorithm using simulated data was compared to those of other automatic methods including HSVD and HTLS-PK. Examples of in vivo(31)P data obtained from brains of healthy subjects on a 4T MRI scanner were also presented, which demonstrated the superiority of the new method. The results were compared with those using AMARES.     

基于数据同化和差分进化算法的图像融合

针对现有融合方法不易根据后续处理目的对融合规则进行自适应调整,不同方法的优点不易综合的问题,提出一个基于数据同化和差分进化算法的图像融合框架.在该框架下,将基于非采样下的Contourlet变换作为模型算子,离散小波变换作为观测算子,可根据后续处理对图像各个属性指标值的依赖程度确定各个属性指标的权重,构造由图像各个属性评价指标的加权和所组成的目标函数,再利用差分进化算法来优化目标函数,从而获取更合适的图像.二组实验从视觉效果和量化指标（标准方差、平均梯度、熵、空间频率及均方根交叉熵）两方面验证了该框架的有效性.     

A simulation algorithm based on Bloch equations and product operator matrix: application to dipolar and scalar couplings

A product operator matrix is proposed to describe scalar couplings in liquid NMR. Combination of the product operator matrix and non-linear Bloch equations is employed to describe effects of chemical shift, translational diffusion, dipolar field, radiation damping, and relaxation in multiple spin systems with both scalar and dipolar couplings. A new simulation algorithm based on this approach is used to simulate NMR signals from dipolar field effects in the presence of scalar couplings. Several typical coupled spin systems with both intra-molecular scalar couplings and inter-molecular dipolar couplings are simulated. Monte Carlo methods are incorporated into simulations as well to analyze diffusion process in these complicated spin systems. The simulated results of diffusion and relaxation parameters and 2D NMR spectra are coincident with the experimental measurements, and agree with theoretical predictions as well. The simulation algorithm presented herein therefore provides a convenient means for designing pulse sequences and quantifying experimental results in complex coupled spin systems.     

Monte Carlo simulation of electron swarms in nitrogen in uniformE×B fields

The motion of electrons in nitrogen in uniform E× B fields is simulated using the Monte Carlo technique for 240⩽E/N⩽600 Td (1 Td=1×10^-17 V cm²) and 0⩽B/N⩽0.45×10^-17 T cm³ . The electron-molecule collision cross sections adopted are the same cross sections as those used previously for the numerical solution of the Boltzmann equation. The swarm parameters obtained from the Monte Carlo simulation are compared with the Boltzmann solution and with the experimental data available in the literature. In relation to E×B fields, it is concluded that the Monte Carlo approach provides an independent method of substantiating the validity of the equivalent electric-field approach     

加权差分进化算法应用于换热网络综合

针对差分进化算法应用于换热网络受控制参数影响和后期种群多样性丧失进化乏力的不足,引入加权差分进化算法提升优化性能,算法的有效性已经在连续变量优化得到证明.本研究将其引入属于混合整型变量的换热网络综合,实现差分进化算法无控制参数调节.使用三个小到中等规模网络算例进行验证,其中两个算例取得目前公开文献最优年综合费用.通过建...     

对爱因斯坦模型的修正及考虑热效应的三个通用状态方程

 对固体考虑热效应的爱因斯坦模型进行了修正。指出考虑热效应的通用状态方程中不应该包含零点振动项，方程参数不应该直接取为参考温度下的实验值V_R，B_R，B′_R和γ^G_R，而应该取为零温下的数值V₀，B₀，B′₀和γ^G₀；提出了一种从V_R，B_R，B′_R和γ^G_R求解V₀，B₀，B′₀和γ^G₀的方法。将提出的方法应用于三个典型的通用状态方程，包括Baonza、mMNH和Vinet方程。数值结果表明，利用相同的实验参数对三个方程解出的参数，以及预测的零压和低压下的热物理性质差异很小，而且都与实验数据符合很好。这些结果表明，在零压和低压下预测热物理性质的精确度不足以用来判断各种通用状态方程的适用性。     

Universal octahedral-site distortion in orthorhombic perovskite oxides

Lattice parameters of the orthorhombic perovskites RMO3 (R=rare earth, M=Ti, V, ..., Ni, and Ga) have been simulated based on the ionic M-O bond length and rigid MO6/2 octahedra. Comparison with experimental data shows that the long-standing lattice-parameter anomaly generally found for the larger R3+ ions in these families is caused by a structural feature that is not revealed by the geometric tolerance factor widely used for the perovskites.     

Energy deposition model for I-125 photon radiation in water

In this study, an electron-tracking Monte Carlo algorithm developed by us is combined with established photon transport models in order to simulate all primary and secondary particle interactions in water for incident photon radiation. As input parameters for secondary electron interactions, electron scattering cross sections by water molecules and experimental energy loss spectra are used. With this simulation, the resulting energy deposition can be modelled at the molecular level, yielding detailed information about localization and type of single collision events. The experimental emission spectrum of I-125 seeds, as used for radiotherapy of different tumours, was used for studying the energy deposition in water when irradiating with this radionuclide.     

用改进的两步模拟退火法进行二元光学元件的设计

为了减少二元光学元件设计的计算量并提高设计精度,在对现有算法机理进行深入分析的基础上,提出了适用于二元光学元件设计的两步模拟退火法.该算法在整个退火过程中采用先量化后优化的策略,并将优化过程分为两个阶段：搜索并锁定最优解区间;快速收敛到最优解.模拟实验显示,与传统设计方法相比,该算法不仅保持了全局寻优的特点,而且提高了稳健性和效率.算法剔除了对设计结果影响较大的量化误差,提高了设计精度.用此法实例设计了单焦面辐射聚焦元件,得到了与目标图像一致的光学实验结果.     

改进的DLA方法模拟薄膜二维生长

对经典的DLA模型进行改进，研究了薄膜的二维生长过程.通过改变表征吸附原子在基底扩散 能力的参量D_T，D_C以及表征沉积速率的参量D_V，得到 了与实验一致的薄 膜分形生长模式和团状生长模式.分析了薄膜的形核阶段原子团的大小分布，以及不同条件 下原子团的数目和大小随覆盖度的变化. 关键词： DLA 薄膜生长 分形生长 团状生长     

多传感器目标识别系统的特征优化方法

来自多传感器的目标特征往往是高维数的,并且包含了更多的冗余信息和噪声。为了减小数据获取的代价,提高目标识别器的性能和效率,提出了基于遗传算法(GA)的多传感器目标识别系统特征优化方法。将遗传算法与神经网络目标分类器结合,通过识别结果的反馈信息,控制GA的遗传进化方向,从而实现特征优化。为了克服遗传算法的未成熟收敛问题,提出了相关选择与自适应遗传算子相结合的改进遗传算法。仿真实验结果验证了方法的有效性。     

光滑粒子流体动力学有限元法接触算法研究

 耦合光滑粒子流体动力学（SPH）方法和有限元法（FEM）,是研究冲击动力学问题的一种有效途径。为解决SPH粒子和有限单元间的接触问题,提出了SPH-FEM接触算法。该算法是在有限元节点处设置背景粒子,采用SPH接触算法的思想,计算施加在SPH粒子和有限元节点上的接触力,并且以外力的形式分别加入到SPH动量方程和有限元动力学方程中。利用SPH-FEM接触算法,对两杆撞击以及圆柱形钢弹正冲击钢板发生的冲塞破坏过程进行了三维数值模拟,靶板采用含损伤的Johnson-Cook模型和Grüneisen状态方程,模拟结果与实验结果吻合较好。     

A simulation based method to assess inversion algorithms for transverse relaxation data

NMR relaxometry is a very useful tool for understanding various chemical and physical phenomena in complex multiphase systems. A Carr-Purcell-Meiboom-Gill (CPMG) [P.T. Callaghan, Principles of Nuclear Magnetic Resonance Microscopy, Clarendon Press, Oxford, 1991] experiment is an easy and quick way to obtain transverse relaxation constant (T₂) in low field. Most of the samples usually have a distribution of T₂ values. Extraction of this distribution of T₂s from the noisy decay data is essentially an ill-posed inverse problem. Various inversion approaches have been used to solve this problem, to date. A major issue in using an inversion algorithm is determining how accurate the computed distribution is. A systematic analysis of an inversion algorithm, UPEN [G.C. Borgia, R.J.S. Brown, P. Fantazzini, Uniform-penalty inversion of multiexponential decay data, Journal of Magnetic Resonance 132 (1998) 65–77; G.C. Borgia, R.J.S. Brown, P. Fantazzini, Uniform-penalty inversion of multiexponential decay data II. Data spacing, T₂ data, systematic data errors, and diagnostics, Journal of Magnetic Resonance 147 (2000) 273–285] was performed by means of simulated CPMG data generation. Through our simulation technique and statistical analyses, the effects of various experimental parameters on the computed distribution were evaluated. We converged to the true distribution by matching up the inversion results from a series of true decay data and a noisy simulated data. In addition to simulation studies, the same approach was also applied on real experimental data to support the simulation results.     

A structural health monitoring strategy using cepstral features

A statistical pattern recognition based damage detection algorithm is proposed. The algorithm is developed according to the training and testing scheme, typical of pattern recognition applications. The original contribution of the work is given by the use of an adaptation of Mel-Frequency Cepstral Coefficients as damage sensitive features, as their compactness and de-correlation characteristics make them particularly suited for statistical pattern recognition applications. At the same time, the ease of extraction, which requires minimal user expertise, represents an important advantage over other more popular features, and makes the cepstral features particularly convenient for implementation into automatic structural health monitoring routines. The damage detection algorithm employs the squared Mahalanobis distance to solve the Structural Health Monitoring assignment. The method is validated by using both simulated and experimental data, and the performance of said features is compared to that of Auto-Regressive (AR) coefficients, which have been largely used to solve the task of structural damage detection. The experimental data were measured on a steel frame, which behave nonlinearly in its damaged configuration, at the Los Alamos National Laboratory. Results demonstrate that the proposed approach may be conveniently used in real-life applications, since cepstral features outperform AR coefficients when dealing with experimental data modeled to mimic the operational and environmental variability.