高扬的旗帜——博山电机厂集团股份有限公司精神文明建设纪实

建厂已近60年的博山电机厂,在企业发展的历史上曾经有过辉煌:40年代,作为军工厂,在抗日战争的烽火和解放战争的硝烟中为新中国的解放事业做出了很大的贡献;50年代,作为全国八大电机厂之一,又为新中国的建设事业提供了许多优良的产品,而且作为汽车电机、直流微电机、交流     

Nd3+ Doped Silicate Glass Photonic Crystal Fiber with Random Hole Distributions

The fabrication of one kind of large core area Nd3 doped silicate glass photonic crystal fiber, and demonstration of the fiber's waveguidence properties were reported. This fiber owns a random air hole distribution in the cladding. The measured minimum loss of this kind of fiber is 10 dB·m-1 at 660 nm. These fibers can sustain only a single mode at least over wavelength ranging from 660 nm to 980 nm.     

Evaluation of accuracy of measuring intraocular pressure by handheld non-contact applanation tonometer

PURPOSE: To evaluate the accuracy of measuring intraocular pressure by handheld non-contact applanation tonometer. METHOD: 58 patients' (113 eyes) intraocular pressure were measured by Keeler, non-contact tonometer and R 900 Goldmann applanation tonometer and the results of measurement of intraocular pressure by the two kinds of tonometers were compared. RESULT: The mean intraocular pressure measured by non-contact is 16.31 +/- 5.59 mmHg and 17.49 +/- 6.13 mmHg (1 mmHg = 0.1333 kPa) by Goldmann applanation tonometer, respectively. There was no statistical significance to be found (P > 0.05) between the two methods. By linear correlation and regression analysis, a positive correlation was found between the two methods (r = 0.8942, b = 0.8154). CONCLUSION: The handheld non-contact tonometer has the same accuracy and reliability of measurement of intraocular pressure comparing with Goldmann applanation tonometer, and it can be used in glaucoma clinic and screening.     

锆(Ⅳ)-3,5-diBr-PADAP-安替比林三元配合物的分光光度研究与应用

本文提出在安替比林存在下,以3,5-diBr-PADAP为显色剂,分光光度测定微量锆的新方法。在pH1～2的HCl介质中,锆(W)与试剂和安替比林形成配合比为1:1:1的红色三元配合物,最大吸收值在615nm波长处,摩尔吸光系数ε=1.35×10~5。锆(Ⅳ)量在0～25μg/25ml范围内,遵守比尔定律。方法简单、快速、准确。若采用钽试剂—苯萃取法分离共存离子,可适用于钽铌矿和合金中痕量锆的测定。     

Evolving Fault-Tolerant Neural Networks

In this paper, genetic algorithm is used to help improve the tolerance of feedforward neural networks against an open fault. The proposed method does not explicitly add any redundancy to the network, nor does it modify the training algorithm. Experiments show that it may profit the fault tolerance as well as the generalisation ability of neural networks.