Nanostructured polymer blends: Synthesis and structure

Nanostructured polymer blends prepared via anionic ring opening polymerizations of cyclic monomers in the presence of a pre-made polymer melt exhibit a number of special properties over traditional polymer blends and homopolymers. Here, we report on a simple and versatile method of in situ polymerization of macrocyclic carbonates in the presence of a maleic anhydride polypropylene (mPP) matrix and a surface-active compatibilizer (i.e. PC grafted onto a mPP backbone generated in situ) to yield a micro- and nanostructured polymer blends consisting of a polycarbonate (PC) minor phase, and a polypropylene (PP) major phase. By varying the processing conditions and concentration of the macrocyclic carbonate it was possible to reduce the size of the PC dispersions to an average minor diameter of 150 nm. NMR and TEM characterizations indicate that the PC dispersions do not influence crystal content in the PP phase. Overall, the results point to a simple strategy and versatile route to new polymeric materials with enhanced benefits.     

On the learning control of a robot manipulator

This paper derives a learning control law to achieve trajectory following for a robot manipulator. The controller consists of two parts, a computed torque servo for the rigid body terms that can be modelled and a learning law for the unmodelled dynamics. An advantage of this method is that bounds can be assigned to the position and velocity tracking errors.     

Learning to Predict Non-Deterministically Generated Strings

In this article we present an algorithm that learns to predict non-deterministically generated strings. The problem of learning to predict non-deterministically generated strings was raised by Dietterich and Michalski (1986). While their objective was to give heuristic techniques that could be used to rapidly and effectively learn to predict a somewhat limited class of strings, our objective is to give an algorithm which, though impractical, is capable of learning to predict a very general class. Our algorithm is meant to provide a general framework within which heuristic techniques can be effectively employed.     

一部特具匠心的精品教材——评张仲谋《宋词欣赏教程》

张仲谋教授的新著《宋词欣赏教程》，是南京大学出版社出版的“江苏省高等学校精品教材系列”中的一种。该书共8章，既构成一个严谨的教学体系，又多有创新出彩之处；对于词的艺术个性有深刻的把握和精当的阐发；又善于引导学生，循循善诱。该书既是教材，亦具有学术专著的品格。     

Co- and Ni-exchanged ferrierite: The contribution of synchrotron X-ray diffraction data to siting of TMIs

High-silica zeolites exchanged with transition metal ions (TMIs) are the subject of great interest for their unusual catalytic activity and selectivity. Structural information like coordination and accessibility of TMIs in zeolites are important factors for understanding their catalytic activity. Siting of TMIs in zeolites is typically obtained by spectroscopic (EXAFS, EPR, UV–vis and IR) and computational methods, as in the case of Co-ferrierite. However, some controversy exists in the literature concerning the model for incorporation of bare Co ions in ferrierite. We show here that the results of our synchrotron X-ray powder diffraction studies on Co- and Ni-exchanged ferrierite (Si/Al = 8.5) are in a good agreement with the model of Co siting based on an indirect spectroscopic approach and help to validate this model. By direct structural evidences, a possible explanation for the larger catalytic activity of Co sites in the main channels of ferrierite can be inferred. A combination of data from in situ XRD continuous monitoring of the Co ion migration during calcination and crystal-chemical considerations allows to device a strategy for the design of optimised co-cations containing Co-ferrierite catalysts.     

青藏铁路西格二线混凝土冻融试验研究

由于工期的要求,青藏铁路西格增建二线必须进行冬期施工。根据工程状况,分析了混凝土受冻的破坏机理,针对施工环境及对混凝土设计强度和要求,进行了大量冻融试验分析,对引气剂、水胶比、砂率、粉煤灰掺量等原材料与混凝土含气量的关系及其混凝土搅拌温度与静停时间等对混凝土性能的影响进行了分析与技术论证,确保了该线冬期混凝土施工顺利进行。     

The impact of roasting on the ochratoxin A content of coffee

Roasting coffee led to a drop in the ochratoxin A (OTA) concentration, as measured by the reference method, especially for dark type roasts. The way the beverage was prepared also affected the OTA content, which could paradoxically be higher than that of the initial roasted coffee. Assays on the thermal stability of pure OTA showed that it ought to be found in larger quantities in roasted coffee. This suggested that OTA was masked by reactions with the substrate during roasting. The absence of OTA in green coffee is therefore the best guarantee of safety.     

靶向抗癌药格列卫与其治疗白血病疗效监测

Gleevec是抑制致癌的融合蛋白BCR-ABL的一种分子靶向治疗药物,BCR-ABL是一种与慢性髓细胞性白血病(CML)有关的酪氨酸激酶抑制剂。用Gleevec选择性地抑制BCR-ABL活性在治疗CML中显示出很好的效果,特别是在CML慢性期,因此,监测疗效非常重要。现就Gleevec的研究进展及如何监测其在CML中的疗效作一简单综述。     

An adaptive tracking problem for a family of retarded time-delay plants

Most of the existing switching control techniques are developed specifically for finite-dimensional linear time-invariant (LTI) systems. In many practical applications, however, it is essential to take time delay into consideration in the modelling as the control system can be highly sensitive to delay. In this paper, a multi-model switching control algorithm is proposed for retarded time-delay systems. It is assumed that the plant is represented by a family of known multi-input multi-output, observable, LTI models with multiple delays in the states, and that corresponding to each model in the known family, there exists a high-performance finite-dimensional LTI controller. In addition, it is supposed that a bound on the magnitude of the external inputs and disturbances is available. It is then shown that the proposed switching controller can stabilize the uncertain system, and that under some mild conditions, output tracking can be achieved in the given problem setting. Copyright © 2007 John Wiley & Sons, Ltd.     

A novel distributed approach to robust fault detection and identification

In this paper, we propose a novel distributed robust fault detection and identification (RFDI) scheme for a class of nonlinear systems. Firstly, a detection and identification estimator—robust fault tracking approximator (RFTA) is designed for online health monitoring. A novel feature of the RFTA is that it can simultaneously detect and accurately identify the shape and magnitude of the fault and disturbance. Moreover, it takes less online training time compared with the traditional neural network based fault diagnosis schemes. For some distributed systems, a network of distributed estimators is constructed where the RFTA is embedded into each estimator. Then we use consensus filter to filter the outputs of each estimator. One of the most important merits of the consensus filter is that its outputs can dramatically improve the accuracy of fault detection and identification. Next, the stability of the distributed RFDI scheme is rigorously investigated. Finally, two numerical examples are given to illustrate the feasibility and effectiveness of the proposed approach.