Observation of atomic steps on CaCO3 crystal surface

By using scanning polarization force microscopy,the deliquescence process and the atomic steps on the cleavage surface of CaCO3 in air were studied in situ.Under an exposure to medium umidity(-57%),the sloiw step movement has been observed.     

Expert system application for the loading capability assessment oftransmission lines

This paper describes the application of an expert system for the evaluation of the short-term thermal rating and temperature rise of overhead conductors. The expert system has been developed using a database and Leonardo expert system shell which is gaining popularity among commercial tools for developing expert system applications. The expert system has been found to compare well when evaluated against site tests. A practical application is given to demonstrate the usefulness of the expert system developed     

The prospects of non-volatile phase-change RAM

Phase-change read-and-write memory (PRAM) is a promising memory that can solve the problems of conventional memory—scalability, read/write speed, and reliability. We will review the opportunities and technical challenges of PRAM. The most important challenge of PRAM is the reduction of the writing current. Various approaches to reduce the writing current will be reviewed and the prospects of PRAM are discussed.     

Assessment of underground cable ratings based on distributed temperature sensing

Numerous power utilities have installed advanced distributed temperature sensing (DTS) systems to measure the temperature of underground cables. This paper presents a general procedure for real-time assessment of underground cable ratings based on DTS. After the identification and location of hot spots on a cable, the cable installation data, load, and DTS-recorded temperature over a period of time are used to estimate soil thermal parameters and assess cable ratings under normal and overloading conditions. In order to accurately estimate soil thermal parameters, a combined technique of the finite-element method and gradient-based optimization is used. The technique was validated in the laboratory and applied to a rating assessment of a 230-kV/500-MVA cable circuit. The assessed continuous and emergency ratings are helpful in improving the operation of this circuit.     

Exploratory analysis of brain connectivity with ICA.

Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task.     

~（60）Co辐照对聚四氟乙烯表面润湿性的影响

研究了具有低表面能的氟聚合物聚四氟乙烯（ＰＴＦＥ），经６０Ｃｏγ射线辐照后表面状态的变化，以及其对液体介质蒸馏水的润湿性。较详细地论述了辐照后表面粗糙度、结晶度以及表面化学基因等不同因素对ＰＴＦＥ表面润湿性的影响。通过对ＰＴＦＥ及其表面的红外、Ｘ光衍射，表面粗糙度的分析，弄清了辐照后ＰＴＦＥ表面化学基团的改变对有机氟聚合物表加的润湿性影响很大，而粗糙度和结晶度的变化对润湿性影响较小。     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load