改进蚁群PID-神经元解耦的CFB锅炉燃烧系统控制

床温和主汽压都是循环流化床锅炉生产运行中的重要参数,会直接影响机组的安全性和经济性。但由于这两者对象存在非线性、大时延、强耦合等特点,其现场控制效果一直不太理想。本文首先采用自适应神经元将床温和主汽压解耦,再利用具有分工特征的蚁群算法优化参数的PID控制器对两者进行独立控制。采用该算法优化常规PID控制参数,能够实现控制参数的快速寻优。该方案应用于循环流化床锅炉燃烧系统仿真,结果表明能有效实现系统解耦,且具有响应快、超调量小等优点,有效地提高了控制品质。     

An imaging pH optode for cell studies based on covalent attachment of 8-hydroxypyrene-1,3,6-trisulfonate to amino cellulose acetate films

The objective of this study was to create a thin film optode for fast pH measurements that meets the requirements for imaging pH-responses from cells as well as for a future hybrid design for detection of multiple analytes simultaneously. The sensor is based on the covalent attachment of 8-hydroxypyrene-1,3,6-trisulfonate (HPTS) to a film forming cellulose acetate material through a sulfonamide linkage. The synthesis routes of the cellulose material and regio-specific covalent attachment of the dye are described in detail. The sensor was sterilized in two different ways and showed excellent biocompatibility with Chinese hamster ovary cells. Imprints from cells and μm thin cell extensions were visualized when altering pH of the surrounding solution. The sensor was tested together with time-dependent sigmoidal calibrations giving pH determinations with an exceptional precision and accuracy during measurement within pH 6-8. The precision of the optode, calculated as pooled S.D. (n = 8) according to IUPAC recommendations between pH 6.641 and 7.742 was 0.0029. The accuracy was significantly better than the electrode used as reference during the measurements. The response time (0-95%) was 100 s between pH 6.641 and 7.742 and the reverse response (95-0%) was 80 s. The sensor shows great potential for extra-cellular pH determination over time during cell growth and pharmacological exposure.     

Imaging subcellular features of a sectioned rat brain using time-of-flight secondary ion mass spectrometry and scanning probe microscopy

Coronal sections of unfixed rat brain samples were prepared on a flat substrate in order to reveal hippocampal formation (CA1-4 pyramidal neurons) and adjacent neocortical white matter. We demonstrate the feasibility of using surface sensitive techniques such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) and scanning probe microscopy (SPM) to probe lipid distribution, as well as the subcellular features of neurons. In the same anatomical areas, the phase shift image in SPM is especially useful in revealing the cross-section of subcellular structures. We show that the phase shift images reveal distinctive subcellular features and ion images of CN⁻ and PO₂⁻ fragments from ToF-SIMS appear to define some of the subcellular features.     

The statistics of lines in natural images and implications for visual detection

As borders between different regions, lines are an important element of natural images. Already at the level of the mammalian primary visual cortex (V1), neurons respond best to oriented bars. We reduce a set of images to linear segments and analyze their statistical properties. In particular, appropriately defined Fourier spectra show more power in their transverse component than in the longitudinal one. We then characterize filters that are best suited for extracting information from such images, and find some qualitative consistency with neural connections in V1. We also demonstrate that such filters are efficient in reconstructing missing lines in an image.     

Quenching influence of cell culture medium on photoluminescence and morphological structure of porous silicon

In this work, the degradation of visible photoluminescence of porous silicon (PSi) under the influential actions of cell culture medium has been mainly studied in order to comprehend the quenching mechanisms necessitating the cell growth on spongy-like-silicon structures, which could form either micro- and/or nano-dimensional morphologies after stain-etching of the poly- or single-crystalline Si surfaces. Quenching effect of the neuron culture medium on visibly luminescent and non-luminescent porous silicon is found to be quite obvious so that this step of the culture process, especially, over nanostructured silicon is extremely essential for a variety of bionanotechnological applications.     

Channel block-optimized spiking activity of Hodgkin-Huxley neurons on random networks

In this paper, we numerically study the effect of channel block on the spiking temporal coherence and spatial synchronization on Hodgkin-Huxley (HH) neuron networks. It is found that under sodium CB the spike coherence is badly reduced, and the synchronization can, depending on the network randomness (the fraction of random shortcuts), be either enhanced or reduced, while, under potassium CB, the spike coherence can be enhanced but the synchronization is reduced. Interestingly, for certain networks of relatively large randomness, the neuron firings can achieve the best temporal coherence at an optimal potassium CB. These results show that under certain conditions channel blocking can increase and optimize the spike coherence and the synchronization on the complex HH neuron networks, whereby the neurons would exhibit a better and the best sub-threshold signal encoding.     

Engineered self-organization of neural networks using carbon nanotube clusters

A novel approach was developed to form engineered, electrically viable, neuronal networks, consisting of ganglion-like clusters of neurons. In the present method, the clusters are formed as the cells migrate on low affinity substrate towards high affinity, lithographically defined carbon nanotube templates on which they adhere and assemble. Subsequently, the gangliated neurons send neurites to form interconnected networks with pre-designed geometry and graph connectivity. This process is distinct from previously reported formation of clusterized neural networks in which a network of linked neurons collapses via neuronal migration along the inter-neuron links. The template preparation method is based on photo-lithography, micro-contact printing and carbon nanotube chemical vapor deposition techniques. The present work provides a new approach to form complex, engineered, interconnected neuronal network with pre-designed geometry via engineering the self-assembly process of neurons.     

自抑制神经元控制系统的参数设计方法及特性分析

在分析神经元控制模型的基础上,从控制理论角度,构建了自抑制神经元控制系统的方框图,推导了系统参数(T、τ、b、k)的设计条件,给出了参数设计曲线及取值表,推导了控制系统的单位响应函数、峰值时间tp、峰值和稳态值Mp。通过软件进行了仿真验证,并分析了各参数对系统性能的影响,结果发现,tp与τ呈现近似正相关的线性关系,与kb呈现出负相关的关系,Mp与T、kb呈现近似正相关的线性变化关系。完善了神经元模型设计理论和方法,对神经元控制系统设计具有指导意义。     

Order reduction of retarded nonlinear systems – the method of multiple scales versus center-manifold reduction

We compare two approaches for determining the normal forms of Hopf bifurcations in retarded nonlinear dynamical systems; namely, the method of multiple scales and a combination of the method of normal forms and the center-manifold theorem. To describe and compare the methods without getting involved in the algebra, we consider three examples: a scalar equation, a single-degree-of-freedom system, and a three-neuron model. The method of multiple scales is directly applied to the retarded differential equations. In contrast, in the second approach, one needs to represent the retarded equations as operator differential equations, decompose the solution space of their linearized form into stable and center subspaces, determine the adjoint of the operator equations, calculate the center manifold, carry out details of the projection using the adjoint of the center subspace, and finally calculate the normal form on the center manifold. We refer to the second approach as center-manifold reduction. Finally, we consider a problem in which the retarded term appears as an acceleration and treat it using the method of multiple scales only. Communicated by G. Rega     

自适应神经元输电线路反时限过流保护

本文论述了一种基于自适应神经元方法实现输电线路的单片机反时特性曲线的新技术。该技术在对故障电流量进行测量、分析和判断的基础上,采用三种典型的反时限特性方程,基于自适应神经元的方法,综合考虑线路故障状态的特征,使用三个自适应神经元,并根据单个神经元的智能控制算法,推导出自适应神经元的反时限保护特性算法,从而解决了单片机不能实现的反对限指数运算,减小或消除了采用查表法的相对误差和时延。该方案具有很强的实用性。