Finite-time optimal tracking control for a class of nonlinear systems with prescribed performance

In this paper, a finite-time optimal tracking control scheme based on integral reinforcement learning is developed for partially unknown nonlinear systems. In order to realize the prescribed performance, the original system is transformed into an equivalent unconstrained system so as to a composite system is constructed. Subsequently, a modified nonlinear quadratic performance function containing the auxiliary tracking error is designed. Furthermore, the technique of experience replay is used to update the critic neural network, which eliminates the persistent of excitation condition in traditional optimal methods. By combining the prescribed performance control with the finite-time optimization control technique, the tracking error is driven to a desired performance in finite time. Consequently, it has been shown that all signals in the partially unknown nonlinear system are semiglobally practical finite-time stable by stability analysis. Finally, the provided comparative simulation results verify the effectiveness of the developed control scheme.     

Methylene blue photocatalytic degradation under visible irradiation of Al doped ZnO powders by hydrothermal synthesis sensitized with octa-iso-pentyloxyphthalocyanine lead

AZO powders were sensitized through chemisorption method by octa-iso-pentyloxy phthalocyanine lead and characterized by Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. The results showed that after sensitization process AZO photo physical properties improved greatly in visible regions. Photocatalytic degradation of methylene blue was studied under visible irradiation in aqueous solution and the pseudo first order model was used to obtain kinetic information of the photocatalytic degradation. The results indicated that photocatalytic activities of PbPc(iso-PeO)₈-AZO were better than of AZO powders.     

Selective toxicity of hydroxyl-rich carbon nanodots for cancer research

Nano Research - The toxicity of nanoparticles in a biological system is an integration of effects arising from surface functionality, particle size, ionic dissolution, etc. This complexity suggests...     

二溴对甲基偶氮甲磺光度法测定钢中微量锶

研究了二溴对甲基偶氮甲磺与锶生成2:1兰色络合物进行钢中微量锶的测定.该法λ_(max)=638nm,摩尔吸光系数E_(638)=5.01×10~4,锶量在0.02～0.34μg/L范围内服从比尔定律.方法已用于钢中微量锶的测定,结果满意.     

Super connectivity of Kronecker products of graphs

Let G₁ and G₂ be two connected graphs. The Kronecker product G₁×G₂ has vertex set V(G₁×G₂)=V(G₁)×V(G₂) and the edge set . In this paper, we show that if G is a bipartite graph with κ(G)=δ(G), then G×Kn(n?3) is super-κ.     

A system-level model for a silicon thermal flow sensor

A system-level model with lumped parameters for a thermal flow sensor is presented. The model is built with 13 circuit cells consisting of thermal resistors and thermal capacitors in SPICE. The circuit cell originates from the heat conduction equation using the Finite Differential Method, including the 2-D thermal conduction cell, the convection cell, and the thermal capacity in the chip. Based on the thermal model of the flow sensor, the 2-D temperature distribution of the chip can be calculated with SPICE in both the constant power mode (CP) and constant temperature difference mode (CTD). As an example, the system level model of the thermal anemometer in the CTD mode was established in PSPICE. Wind tunnel test was carried out to verify the system model, and show a reasonable agreement with the simulation results, with an error less than 8%.     

基于图像混合图结构的区域匹配和图像约化算法

讨论使用混合图对图像进行识别的连通性、相似性和可比性原则,并提出一种混合图结构的约化算法。通过可比性原则,对图像的混合图结构中复合节点用参考图像进行比较,计算出混合图复合节点在参考图像中的可能匹配和相似度,以此对混合图结构进行约化。为方便计算和阐述约化过程,使用单个属性,对混合图进行属性标记,把相似性比较简化为线性复杂度的排序和查询运算。结果显示,该方法切实可行。     

A new neural network algorithm for planarization problems

To deal with the planarization problem widely used in many applications including routing very-large-scale integration （VLSI） circuits, this paper points out that only when its vertices are arranged in some specific order in a line can a planar graph be embedded on a line without any cross connections or cross edges. Energy function is proposed to meet the need of embedding a graph on a single line and route it correctly. A Hopfield network is designed according to the proposed energy function for such embedding and routing. The advantage of the proposed method is that it not only can detect if a graph is a planar one or not, but also can embed a planar graph or the maximal planar subgraph of a non-planar graph on a single line. In addition, simulated annealing is employed for helping the network to escape from local minima during the running of the Hopfield network. Experiments of the proposed method and its comparison with some existent conventional methods were performed and the results indicate that the proposed method is of great feasibility and effectiveness especially for the planarization problem of large graphs.     

3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor beta (TRbeta), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q(2) (cross-validated) values 0.600 and 0.616 and non-cross-validated r(2) values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (r(pred)(2)) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRbeta. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor beta but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.