编辑活动的系统分析

本文概述了作者多年编辑实践中的一些经验与本会，多方面多角度立体式地透视了编辑活动在编辑实践中的种种作用，并给出了一些自己的看法。     

高频准谐振零电流开关电源

本文研究了串联谐振、并联负载的准谐振零电流开关电源。文中首先讨论了电源的工作原理，电路结构，参数设计；并用ＰＳＰＩＣＥ软件包对电源进行了计算机仿真分析；最后给出了电源的电气实验波形。     

基于ARM的PCMCIA接口设计

嵌入式系统在网络控制和通信领域有着越来越广泛的应用。本文通过分析PC卡时序,利用ARM处理器S3C4510B和外部电路设计PCMCIA接口,实现与无线网卡的软、硬件接口,从而可以使用基于ARM的嵌入式系统来开发无线网络产品。     

Design of Sliding Surface with Global Robustness

ＤｅｓｉｇｎｏｆＳｌｉｄｉｎｇＳｕｒｆａｃｅｗｉｔｈＧｌｏｂａｌＲｏｂｕｓｔｎｅｓｓＦＥＮＧＹｏｎｇ；ＲＡＮＳｈｕｃｈｅｎｇ；ＣＨＩＹｕｄｏｎｇ；ＲＥＮＱｉａｎ（冯勇，冉树成，池毓东，任倩）（Ｄｅｐｔ．ｏｆＥｌｅｃｔｒｉｃａｌＥｎｇｉｎｅｅｒｉｎｇ，...     

炭/酚醛预浸布树脂含量的β-射线连续监测

利用自行建立的β-射线监测系统对炭/酚醛预浸布的树脂含量进行了连续监测研究。根据实验数据拟合出了树脂含量与β-射线监测系统输出信号间的定量关系式,同时分析了β-射线源的稳定性、炭纤维布的波动性对监测精度的影响。连续监测结果表明,该β-射线监测系统具有较高的测量精度,可以用于预浸布树脂含量的连续、在线监测。     

Effects of atmospheric ozone on microarray data quality

A data anomaly was observed that affected the uniformity and reproducibility of fluorescent signal across DNA microarrays. Results from experimental sets designed to identify potential causes (from microarray production to array scanning) indicated that the anomaly was linked to a batch process; further work allowed us to localize the effect to the posthybridization array stringency washes. Ozone levels were monitored and highly correlated with the batch effect. Controlled exposures of microarrays to ozone confirmed this factor as the root cause, and we present data that show susceptibility of a class of cyanine dyes (e.g., Cy5, Alexa 647) to ozone levels as low as 5-10 ppb for periods as short as 10-30 s. Other cyanine dyes (e.g., Cy3, Alexa 555) were not significantly affected until higher ozone levels (> 100 ppb). To address this environmental effect, laboratory ozone levels should be kept below 2 ppb (e.g., with filters in HVAC) to achieve high quality microarray data.     

DSC法测量低温相变蓄冷纳米流体的比热容

介绍差示扫描量热仪（DSC）测量液体比热容的原理和方法，并测量4种不同体积分数的TiO2-Ba-Cl2-H2O纳米流体比热容。结果表明，加入纳米粒子后其比热容都有所降低，并随TiO2体积分数的增大而逐渐减小。     

Pathological brain detection in MRI scanning via Hu moment invariants and machine learning

Abstract

Background: We proposed a new automatic and rapid computer-aided diagnosis system to detect pathological brain images obtained in the scans of magnetic resonance imaging (MRI). Methods: For simplification, we transformed the problem to a binary classification task (pathological or normal). It consisted of two steps: first, Hu moment invariants (HMI) were extracted from a specific MR brain image; then, seven HMI features were fed into two classifiers: twin support vector machine (TSVM) and generalised eigenvalue proximal SVM (GEPSVM). Results: Then, a 5 × 5-fold cross validation on a data set containing 90 MR brain images, demonstrated that the proposed methods “HMI + GEPSVM” and “HMI + TSVM” achieved classification accuracy of 98.89%, higher than eight state-of-the-art methods: “DWT + PCA + BP-NN”, “DWT + PCA + RBF-NN”, “DWT + PCA + PSO-KSVM”, “WE + BP-NN”, “WE + KSVM”, “DWT + PCA + GA-KSVM”, “WE + PSO-KSVM” and “WE + BBO-KSVM”. Conclusion: The proposed methods are superior to other methods on pathological brain detection (p < 0.05).     

A new approach to satellite-based estimation of precipitation over snow cover

Current satellite-based remote-sensing approaches are largely incapable of estimating precipitation over snow cover. This note reports a proof-of-concept study of a new satellite-based approach to the estimation of precipitation over snow-covered surfaces. The method is based on the principle that precipitation can be inferred from the changes in the snow water equivalent of the snowpack. Using satellite-based snow water equivalent measurements, we derived daily precipitation amounts for the northern hemisphere for three snow-accumulation seasons, and evaluated these against independent reference datasets. The new precipitation estimates captured realistic-looking storm events over largely un-instrumented regions. However, the data are noisy and, on a seasonal scale, the amount of precipitation is believed to be underestimated. Nevertheless, current uncertainty in snow measurements, albeit large (50–100%), is still lower than direct precipitation measurements over snow (100–140%) and therefore this approach is still useful. The method will become more feasible as the quality of remotely sensed snow measurements improves.