基于地质灾害的唐山市土地开发利用管理信息系统

灾害的破坏程度不仅取决于地震能量（受控于现代构造应力场的特征），同时也受岩溶塌陷，采空区塌陷等其他灾害的影响，故采用人工神经网络模型评价灾害危险性。借助地理信息系统软件，计算了唐山市各居住小区的建筑密度和建筑容积率，结合灾害危险性评价结果。确定了从防灾角度考虑的土地开发强度评价指标。应用Maplnfo自带二次开发语言MapBasic及Visual Basic进行二次开发，炳述了二次开发的步骤和过程。依据系统评价结果，对唐山市的城市规划布局和土地利用方向提出了几点建议。     

浅谈家用吊扇的调速方法

家用吊扇的核心部分是单相异步电动机,此绕组如图1,有一主绕组(工作绕组)与一串联电容器C的副绕组(启动绕组)相并联.这样做可使二绕组的电流在相位上相差90°,从而形成旋转磁场.转子的转动过程与三相异步电动机相似.     

Synthesis and characterization of new bis(1-aryliminomethylenylnaphthalen-2-oxy)nickel complexes and their catalytic behavior for vinyl polymerization of norbornene

The synthesized 1-aryliminomethylenylnaphthalen-2-ol derivatives reacted with nickel chloride to form bis(1-aryliminomethylenylnaphthalen-2-oxy)nickel complexes. All resultant compounds were structurally characterized by elemental analyses, IR and H NMR, and the structures of the formed complexes were elucidated by X-ray crystal structure analysis. The complexes show high catalytic activities for the vinyl polymerization of norbornene in the presence of methylaluminoxane. The catalytic activity variations have been followed by gas chromatography through monitoring the conversion of norbornene.     

具体和抽象统一的原则

学生学习知识,一般来说,是从生动的具体的直观开始的,生动的直观能使学生获得关于事物生动而具体的感性认识。但是,感性认识并没有揭露事物的本质,人们对事物本质的认识要通过一系列的抽象来完成。     

"单摆"课程小结

课程小结是教学的重要环节，画龙点晴的课程小结可起到梳理要点，迁移知识，归纳总结的作用．课程小结重在概括精炼，条理清晰，有利学生理性认识的形成．现以单摆为例，浅谈一下教学的课程小结，小结可在学生归纳总结的基础上，由教师再做系统的总结．     

The Difference of the Pulmonary-Artery Pressure of the Migrants from Difference Elevation at the 4636 - 4907 m Altitude

Study Objective： To compare and analyze the changes of the pulmonary-artery pressure of the migrants coming from different elevation in the hypoxic environment of 4636 - 4907 m extreme altitude. To explore the susceptibility to hypoxic pulmonary-artery hypertension （PH） in the subjects from different altitude and profession. Methods： By using Color Doppler Ultmsonography （CDU）, measuring the pulmonary-artery pressure of 207 healthy men, who had continuously being lived and worked at the extreme altitude for more than six months, and then were divided into three groups according to their profession and the altitude of original living place. Results： There was a significant difference in the outcomes of pulmonary-artery pressure from the 3 groups. Conclusions： Altitude of original living place, labor intensity are some of factors that impact the pulmonary-artery pressure of the people who exposure to a hypoxic environment. The pulmonary- artery pressure of person without strenuously physical work experience was more sensitive to hypoxic surroundings than that of labor workers. It was not always the fact at an extreme altitude that the moderate altitude mountaineers were superior to other migrants from a lower altitude or plain. The higher PH was found in the groups of the moderate altitude mountaineers and labor workers. It is unlikely certain that one with PH would surfer from HAPE.     

反渗透系统的设计思路探讨

反渗透作为一种重要的水处理技术,越来越广泛地应用到各种领域,其处理水源也变得复杂多样化,因此要求在反渗透系统和反渗透预处理设计时予以高度关注。本文主要讨论针对不同水源时反渗透系统的设计思路。     

识别混凝土板内部缺陷的人工神经网络算法

以一维有缺陷混凝土板为研究对象，分别采用Leverberg-Marcluardt和径向基神经网络算法，对缺陷的深度与厚度进行识别，从而实现对混凝土板内部缺陷的三维重构，称为红外CT模拟．两类神经网络算法的识别结果表明：Leverberg-Marcluardt神经网络较径向基神经网络具有更好的收敛精度与计算效率．     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.