Electrohydrodynamically Enhanced Capillary Evaporator

A two-phase capillary evaporator has been enhanced using electrohydrodynamic (EHD) forces. The evaporator was experimentally investigated under DC applied electric field operating modes as well as without an applied electric field. The results without the applied EHD forces show that the induced flow increases with increasing applied heat loads until a dry out condition is reached. The applied DC voltage electric field provides flow enhancements as high as 200%. A slight polarity effect was observed.     

Nanoscale strain characterisation for ultimate CMOS and beyond

Strain engineering is used to maintain Moore's Law in scaled CMOS devices and as a technology booster for More-than-Moore devices in the nanoelectronics era. Strain is crucial because of its ability to increase electron and hole mobilities in Si. However, accurate correlations between electrical performance and strain measurements are needed to enable the necessary feedback between materials, processing and devices to achieve best possible solutions. In this work, we outline new methods for sensitive 3D profiling of strain on a nanoscale. High-resolution vertical and lateral strain profiles applicable to both global (biaxial) and process-induced (uniaxial) strained Si devices are demonstrated. Raman spectroscopy is pushed to its present limit for precise analysis of strain in small geometry devices, including the use of tip-enhanced Raman spectroscopy (TERS) to improve the spatial resolution further. TERS maps are compared with atomic force microscopy data collected simultaneously and show that variations in surface morphology correlate directly with strain in the epitaxial layers. Sub-nm strain profiling is applied to strained Si and SiGe MOSFET channels. Strain is profiled across patterned uniaxial strained-Si-on-insulator structures and analysed in bended nanowire transistors. Finally strain is investigated across the channel regions of electrically measured SiGe p-MOSFETs. Good agreement between nanoscale strain measurements and finite element modelling is demonstrated. Sample preparation is included in the analysis and genuine effects of processing are investigated.     

Discussion of aqueous urethane acrylate oligomers with sulfoisophthalate on the antistatic hydrophilic finishing of different fabrics

In this study, PEG(SE) containing sulfonic acid group was produced by transesterification of dimethyl 5‐sulfoisophthalate sodium salt (SIP) with PEG. The reactive urethane acrylate oligomers were synthesized by using SE as soft segment, isophorone diisocyanate (IPDI) as hard segment, and hydroxyethyl methacrylate (HEMA) as blocking agent. Their solution properties and thermal properties were investigated. Dipping process was carried out on polyethylene terephthalate (PET) fabric, polyamide (nylon) fabric, and cotton fabric for hydrophilic finishing and the effects of processing condition on the fixation behavior and hydrophilic property of treated fabric have been discussed. The conclusions are as follows: the particle size of oligomer solutions are about 45–90 μm, surface tension of solutions are below 43 dyn/cm, and they have smaller contact angle than water. The particle size, particle variance, and streaming current reading decreased, but the surface tension and contact angle enhanced upon increasing PEG molecular weight. The melting point of oligomer is 38°C–52°C and the glass transition point is −18°C to −25°C. In comparison with the fabric finishing, the add‐on of PET fabric is the highest, followed by nylon, then cotton. The durability of treated cotton fabric is the highest, followed by PET, then nylon. The hydrophilicity is most stable for nylon fabric with PEG molecular weight of 2,000, and cotton and PET fabric with molecular weight of 1,000. POLYM. COMPOS., 29:45–57, 2008. © 2007 Society of Plastics Engineers     

Optimal control policy for probabilistic Boolean networks with hard constraints

It is well known that the control/intervention of some genes in a genetic regulatory network is useful for avoiding undesirable states associated with some diseases like cancer. For this purpose, both optimal finitehorizon control and infinite-horizon control policies have been proposed. Boolean networks (BNs) and its extension probabilistic Boolean networks (PBNs) as useful and effective tools for modelling gene regulatory systems have received much attention in the biophysics community. The control problem for these models has been studied widely. The optimal control problem in a PBN can be formulated as a probabilistic dynamic programming problem. In the previous studies, the optimal control problems did not take into account the hard constraints, i.e. to include an upper bound for the number of controls that can be applied to the captured PBN. This is important as more treatments may bring more side effects and the patients may not bear too many treatments. A formulation for the optimal finite-horizon control problem with hard constraints introduced by the authors. This model is state independent and the objective function is only dependent on the distance between the desirable states and the terminal states. An approximation method is also given to reduce the computational cost in solving the problem. Experimental results are given to demonstrate the efficiency of our proposed formulations and methods.     

Generating probabilistic boolean networks from a prescribed transition probability matrix

Probabilistic Boolean networks (PBNs) have received much attention in modeling genetic regulatory networks. A PBN can be regarded as a Markov chain process and is characterised by a transition probability matrix. In this study, the authors propose efficient algorithms for constructing a PBN when its transition probability matrix is given. The complexities of the algorithms are also analysed. This is an interesting inverse problem in network inference using steady-state data. The problem is important as most microarray data sets are assumed to be obtained from sampling the steady-state.     

Digital circuit macromodeling with PSPICE

Ordinary algebra is used to represent Boolean algebra on logic variables with states 0 and 1, so to achieve a unify approach to simulated both digital and analog circuit in PSPICE. Result on mixed A/D simulation shows a save in memory but generally longer run time.     

Linear logic for deductive databases

This paper deals with deductive databases in linear logic. The semantics of queries, views, constraints, and (view) updates are defineddeclaratively in linear logic. In constrast to classical logic, we can formalise non-shared view, transition constraints, and (view) updates easily. Various proof search strategies are presented along with an algorithm for query evaluation from a bottom-up direction. An additional advantage is that the associated meaning of a given relation can be defined in terms of the validity of a legal update in a given relation. We also defined formally the update principles and showed the correctness of the update translation algorithms. In this approach, we provide virtual view updates along with real view updates, and view DELETIONs are special cases of view REPLACEMENTs. This permits three transactional view update operations (INSERTION, DELETION, REPLACEMENT) in comparison to only (INSERTION, DELETION) in most existing systems. Dong-Tsan Lee, Ph.D.: He is a computer scientist in the Department of Computer Science at University of Western Australia, Perth, Western Australia, Australia. He received the B.S. and M.S. degrees from the Department of Computer Science at National Chiao-Tung University, Taiwan, in 1983 and 1985, respectively, and earned the Ph.D. degree from the Department of Computer Science at University of Western Australia. His research interests include database and artificial intelligence, linear logic, and real-time software engineering. Chin-Ping Tsang, Ph.D.: He is currently an associate professor in the Department of Computer Science at University of Western Australia, Perth, Western Australia, Australia. He received the Ph.D. degree from the University of Western Australia. He was the head of the Department of Computer Science at the University of Western Australia from 1994 to 1997. His research interests include artificial intelligence, non-classicial logic and neural nets.     

Recognition of handwritten numerals by Quantum Neural Network with fuzzy features

This paper describes a new kind of neural network – Quantum Neural Network (QNN) – and its application to the recognition of handwritten numerals. QNN combines the advantages of neural modelling and fuzzy theoretic principles. Novel experiments have been designed for in-depth studies of applying the QNN to both real data and confusing images synthesized by morphing. Tests on synthesized data examine QNN's fuzzy decision boundary with the intention to illustrate its mechanism and characteristics, while studies on real data prove its great potential as a handwritten numeral classifier and the special role it plays in multi-expert systems. An effective decision-fusion system is proposed and a high reliability of 99.10% has been achieved. Received October 26, 1998 / Revised January 9, 1999     

平板以外高原之上——回溯Z型板建造系统开发及其校舍应用

介绍2015年香港中文大学建筑学院研究团队对一种轻量预制Z型板系统的开发过程,并揭示其对于可持续建造的涵义.建造便利性、舒适性与空间特色均来源于Z型板单元,随后它在一项室内展览装置搭建以及一项震后重建项目中应用,成功建设了青海玉树高原的拉吾尕小学.