Selective voltammetric determination of electroactive neuromodulating species in biological samples using iron(II) phthalocyanine modified multi-wall carbon nanotubes paste electrode

Iron(II) phthalocyanine (FePc) modified multi-wall carbon nanotubes paste electrodes (MWCNTPEs) were used as voltammetric sensors to selectively detect dopamine (DA) in the presence of serotonin (5-HT). The electrochemical behavior of DA at the new modified electrode was investigated using CV. The enhanced current response of DA indicates that FePc modification of the MWCNTPE surface results in a high catalytic activity for the redox reaction of DA. Differential pulse voltammetry was applied in detection of DA and 5-HT at FePc-MWCNTPE. The method parameters were optimized. Detection limit of 2.05 × 10⁻⁷ M was obtained for DA by using the electrocatalytic oxidation signal corresponding to the Fe^II/Fe^III redox process. The separation between the peak potentials of DA and 5-HT is 170 mV which is large enough for the simultaneously, selective determination of the two chemical species in their mixtures. There was no electrochemical response for ascorbic acid (AA) added in the sample. The monoamine neurotransmitter measuring method has been tested in analyzing deproteinized serum samples.     

Polypyrrole functionalized with FePcTSA for NO2 sensor application

The nitrogen dioxide (NO₂) sensing capability of polypyrrole (PPy) was enhanced dramatically after functionalized with iron(III)phthalocyanine-4,4′,4″,4-tetrasulfonic acid monosodium salt (FePcTSA). The incorporated phthalocyanine was confirmed by different characterization techniques such as UV–vis spectroscopy, FTIR, GFAAS, EDAX, etc. The resistance of the functionalized PPy decreased spontaneously during exposure to NO₂ gas at room temperature. This material exhibited excellent stability, reversibility, and reproducibility. The lowest response time (t₅₀) thus obtained is 47 s with a highest response factor (ΔR/R₀ × 100) of 50.25.     

Interaction of Langmuir–Blodgett and spin-coated films of μ-carbido-bridged ironphthalocyanine with NO2: Optical and conductimetric behaviour

The present study investigates the interaction of NO₂ gas and μ-carbido-bridged iron phthalocyanine (PcFeCFePc) films obtained by Langmuir–Blodgett (LB) and spin-coating (SC) techniques. The phthalocyanine bridged dimer under study belongs to the polynuclear unsubstituted phthalocyanines class and presents poor solubility: in contrast the corresponding N-base bis-adducts are soluble enough in organic solvents to be deposited by Langmuir–Blodgett and spin-coating techniques. The reaction with NO₂ is monitored by visible spectra variation that shows identical behaviour for both kinds of films, indicating that the chemical reaction between the gas and the films is independent of the deposition method. The electrical conductivity change as a function of time with NO₂ is instead dissimilar: for spin-coated films it shows a behaviour already observed for sandwich-type phthalocyanine whereas for LB films it resembles that of monomeric phthalocyanine. Such a response implies that the charges (holes) generated in the oxidation/reduction process are carried differently through the material, and we attempt to explain this behaviour taking into account the two different structural and morphological features induced by the two techniques.     

基于逆Lipschitz条件的二阶导数迭代学习控制

为了提高收敛性和扩展学习律选项,避免高阶相对度的强约束条件,提出了在全局逆Lipschitz条件下的二阶导数迭代学习控制.利用范数理论证明了算法的收敛性.由于二阶导数对噪音敏感,采用多项式滤波避免了振荡,利于工程应用.仿真结果表明,该算法是有效的,应用于不同对象时提高了收敛速度,且精度满足工程应用.     

A Galerkin finite element scheme for time–space fractional diffusion equation

In this paper, a Galerkin finite element scheme to approximate the time–space fractional diffusion equation is studied. Firstly, the fractional diffusion equation is transformed into a fractional Volterra integro-differential equation. And a second-order fractional trapezoidal formula is used to approach the time fractional integral. Then a Galerkin finite element method is introduced in space direction, where the semi-discretization scheme and fully discrete scheme are given separately. The stability analysis of semi-discretization scheme is discussed in detail. Furthermore, convergence analysis of semi-discretization scheme and fully discrete scheme are given in details. Finally, two numerical examples are displayed to demonstrate the effectiveness of the proposed method.     

基于双曲正切函数的二阶时变参数扩张状态观测器

当传统扩张状态观测器(ESO)的状态初值与系统的状态初值相差较大时,普遍存在微分峰值现象.为了消除这种现象,本文给出了用双曲正切非线性函数构造ESO的一般形式,并且用Lyapunov函数证明了二阶ESO的误差系统为渐近稳定.然后又利用双曲正切函数自身的饱和特性,设计出一种时变ESO,可以实现微分峰值的有效抑制.最后,把这种ESO的仿真结果与经典ESO的仿真结果进行对比,表明这里提出的ESO能够有效抑制微分峰值现象,并可以获得系统状态变量和非线性扰动的精确估计.     

Self-consistent gradient flow for shape optimization

We present a model for image segmentation and describe a gradient-descent method for level-set based shape optimization. It is commonly known that gradient-descent methods converge slowly due to zig–zag movement. This can also be observed for our problem, especially when sharp edges are present in the image. We interpret this in our specific context to gain a better understanding of the involved difficulties. One way to overcome slow convergence is the use of second-order methods. For our situation, they require derivatives of the potentially noisy image data and are thus undesirable. Hence, we propose a new method that can be interpreted as a self-consistent gradient flow and does not need any derivatives of the image data. It works very well in practice and leads to a far more efficient optimization algorithm. A related idea can also be used to describe the mean-curvature flow of a mean-convex surface. For this, we formulate a mean-curvature Eikonal equation, which allows a numerical propagation of the mean-curvature flow of a surface without explicit time stepping.     

基于弹簧粒子模型的大规模WSN定位算法的衍生算法

为了提高基于弹簧粒子模型的大规模无线传感器网络定位算法(LASPM定位算法)的鲁棒性,将对LASPM基本定位算法进行优化及改进,并提出一系列的改进衍生算法.针对弱节点将设计简单的迭代定位方法,提出了3个补丁算法,分别用于处理局部极值、剔除坏节点和处理节点动态变化等问题.仿真实验结果表明,新算法的节点计算复杂度、通信复杂度在网络规模增大时仍然保持常量,节点计算步数不随网络规模变化而变化,时间复杂度也保持常量.实验研究结果表明,本文的定位算法具有良好的鲁棒性.     

自适应残差图像的分数阶全变分去噪算法

目的 全变分（TV）去噪模型具有较好的去噪效果,但对于图像的弱边缘和纹理细节的保持不够理想。自适应分数阶全变分（AFTV）模型根据图像局部信息,区分图像的纹理区域和非纹理区域,自适应计算投影算法中的软阈值,可较好地保持图像的弱边缘和纹理细节,但该方法当噪声增大时“阶梯”效应比较明显,弱边缘和纹理细节保持效果不够理想。针对该问题,提出一种改进的分数阶全变分去噪算法。方法 该算法在计算残差图像时,用分数阶全变分模型替代整数一阶全变分模型,并根据较精确的残差图像的局部方差区分图像纹理区域和平坦区域,使保真项参数的自适应选取更加合理,提高了算法的去噪性能。结果 针对3种不同类型的噪声图像,将本文模型与TV模型和AFTV模型进行对比实验,并采用峰值信噪比（PSNR）和结构相似性（SSIM）评定去噪效果和纹理保持能力。对于高斯噪声图像,本文算法在PSNR方面比TV模型和AFTV模型分别可平均提高2.72 dB和1.38 dB,SSIM分别可平均提高0.047和0.020。对于椒盐噪声图像,本文算法结合中值滤波算法在PSNR和SSIM方面比传统中值滤波算法分别可平均提高1.308 dB和0.011。对于泊松噪声图像,本文算法在PSNR、SSIM方面与AFTV较接近,比TV分别可提高1.59 dB和0.005。结论 通过对添加不同类型的噪声图像进行实验,结果表明提出的算法在去噪性能上与TV和AFTV相比均有较大提高,尤其对于噪声较大的图像效果更为显著,在去噪效率上与AFTV的时间复杂度相当,时耗接近略有降低。且本文算法普适性较好,能有效去除多种典型类型的噪声。     

An analytic algorithm for the space–time fractional advection–dispersion equation

Fractional advection–dispersion equation (FADE) is a generalization of the classical ADE in which the first order time derivative and first and second order space derivatives are replaced by Caputo derivatives of orders 0<α?1, 0<β?1 and 1<γ?2, respectively. We use Caputo definition to avoid (i) mass balance error, (ii) hyper-singular improper integral, (iii) non-zero derivative of constant, and (iv) fractional derivative involved in the initial condition which is often ill-defined. We present an analytic algorithm to solve FADE based on homotopy analysis method (HAM) which has the advantage of controlling the region and rate of convergence of the solution series via the auxiliary parameter ? over the variational iteration method (VIM) and homotopy perturbation method (HPM). We find that the proposed method converges to the numerical/exact solution of the ADE as the fractional orders α, β, γ tend to their integral values. Numerical examples are given to illustrate the proposed algorithm. Example 5 describes the intermediate process between advection and dispersion via Caputo fractional derivative.