DC isolation and RF dissipation loss of coplanar waveguide on GaAs multi conductive Layers bombarded by H/sup +/ and Fe/sup +/ ions

This letter explores the dc isolation and radio frequency (RF) dissipation loss of coplanar waveguide (CPW) lines of H/sup +/ and Fe/sup +/ ion bombarded GaAs multi conductive epitaxial layers. It is demonstrated that although a sheet resistivity as high as 10/sup 8/ /spl Omega/sq has been achieved by ion bombardment, showing excellent dc isolation, the RF dissipation loss of gold metallized CPW lines on the bombarded multi conductive epitaxial layers are higher than that on a semi-insulating GaAs substrate, especially at higher frequencies (0.5 dB/cm higher at 50 GHz). This is probably caused by deep level trappings due to the ion bombardment.     

有机介质中合成二硫化钛

本文研究了硫化氢与四氯化钛在某些有机介质中的反应，并提出了一个合成二硫化钛的新方法。该法是将干燥的硫化氢通入沸腾的四氯化铁的α－氯代萘溶液中，使硫化氢和四氯化钛发生复分解反应而生成二硫化钛。方法简便易行。Ｘ－射线物相鉴定及化学分析结果表明，产物为单一物相的、符合化学计量的二硫化钛。     

IDEO：在中国寻找另一个起点

IDEO以前在亚洲是以日本事务所为中心．现在转到上海来主要原因是什么？能介绍一下目前上海事务所的情况吗？     

双氧水冷漂助剂液中润湿剂的分离和鉴测

双氧水冷漂助剂液中的润滑剂——烷基硫酸钠可以在四级氧化铝柱上用氯仿和乙醇—水的淋洗体系进行分离而获得纯品;用NMR和GC法进行结构分析;两相滴定法测定其含量。     

Categorizing images in Web documents

The Web provides an increasingly powerful and popular publication mechanism. Web documents often contain a large number of images that serve various purposes. Identifying the functional categories of these images is an important task in Web repurposing. This article describes a study on the functional categorization of Web images using data collected from news Web sites. As the popularity of the Web soars, the content on the Web is increasingly accessed from wireless devices that have small screens and different bandwidths. Because many Web documents contain a large number of images serving different purposes, how to identify the function of each image so that it can be handled accordingly is an important issue in Web content repurposing. Much work remains to be done in function-based image classification of all images. Icons that appear regularly on Web sites (for example, newspaper logos) could be classified by analyzing different editions of the pages for repetitions. For the host class, a combination of detecting repetitive images and face recognition should help significantly.     

Material removal and surface damage in EDM of Ti3SiC2 ceramic

Material removal and surface damage of Ti₃SiC₂ ceramic during electrical discharge machining (EDM) were investigated. Melting and decomposition were found to be the main material removal mechanisms during the machining process. Material removal rate was enhanced acceleratively with increasing discharge current, i_e, working voltage, u_i, but increased deceleratively with pulse duration, t_e. Microcracks in the surface and loose grains in the subsurface resulted from thermal shock were confirmed, and the surface damage in Ti₃SiC₂ ceramic led to a degradation of both strength and reliability.     

hiX 5300在洪江的应用

介绍了西门子hiX5300的结构和性能。分析了hiX5300在洪江电信局的应用及故障处理情况。     

Managing Clinical Use of High-Alert Drugs: A Supervised Learning Approach to Pharmacokinetic Data Analysis

Drug-related problems, particularly those that result from sub- or overtherapeutic doses of high-alert medications, have become a growing concern in clinical medicine. In this paper, we use a model-tree-based regression technique (namely, M5) and support vector machine (SVM) for regression to develop learning-based systems for predicting the adequacy of a vancomycin regimen. We empirically evaluate each system's accuracy in predicting patients' peak and trough concentrations in different clinical scenarios characterized by renal functions and regimen types. Our data consist of 1099 clinical cases that were collected from a major tertiary medical center in southern Taiwan. We also examine the use of bagging for enhancing the prediction power of the respective systems and include in our evaluation a salient one-compartment model for performance benchmark purposes. Overall, our evaluation results suggest that both M5 and SVM are significantly more accurate than the benchmark one-compartment model in predicting patients' peak and trough concentrations across all investigated clinical scenarios. M5 appears to benefit considerably from bagging, which has a positive but seemingly smaller effect on SVM. Taken together, our findings indicate supervised learning techniques that are capable of effectively supporting clinicians' use of vancomycin or similar high-alert drugs in their patient care and management.