利用反预报方法从截面预言近滴线丰质子核的结合能

在Origin等数据处理软件中,当实验数据较少时,自由参数的不同初始化设置会导致较大的结果差异,这为物理结果的确定带来较大不确定性.通过最小二乘法分析了345MeV/u ~(78) Kr+~9Be反应中产生的丰质子同位素的截面和结合能,并得到线性回归方程.通过回归方程,利用结合能预报部分丰质子核素的截面,以及通过实验截面对近质子滴线核素的结合能进行反预报测量.这对于近质子滴线的丰质子核素实验测量具有较好的借鉴意义.     

线性回归分析与能源需求预测

结合实例介绍了回归模型方法在能源预测中的应用，具体地讨论了最简单、最基本的直线回归模型结构及参数估计方法，对于其他一些曲线回归模型则可通过变量代换转化为直线回归模型。     

Robustness of alternative non‐linearity tests for SETAR models

In recent years there has been a growing interest in exploiting potential forecast gains from the non‐linear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type non‐linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non‐linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non‐linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR‐type non‐linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

蝗虫体内无机物的百分含量

动物体的鲜重(FM)、干重(DM)、灰分重(AM)及其比值在不同分类群和不同生态型的动物类群中变化很大,其中 DM/FM 和 AM/DM 比值反映了动物体水、无机矿物质和有机物三者之间的比例,是了解动物体化学组成的两个重要参数.我们在进行直翅目蝗总科昆虫整体痕量元素含量分析的同时,测定和计算了35种蝗总科昆虫的AM/DM 比值,现将结果以及其它主要动植物类群的有关资料一并介绍如下.     

动态校正的PI型广义预测控制器及其在反应釜系统中的仿真研究

提出了一种新型的广义预测控制器。由于在控制器的设计中,进行了预测误差的动态校正,并且控制器采用了比例积分型(PI)目标函数,因此该控制器对未建模动态具有很强的鲁棒性。应用低阶的模型对一个强放热的化学反应釜模型进行的仿真研究检验了该方法的有效性。     

发样矿物元素分析在干扰及校正

研究了影响发样矿物元素分析结果准确性的各种干扰因素 ,对取样、洗涤、烘干、消化及元素仪器测定等环节进行了探讨 ;同时对相关技术指标进行了测定 ,结果表明 :方法变异系数 <3%,标准回收率为 (10 0± 5 ) %.     

靖西县新圩铝土矿地质特征及控矿因素

根据多年的实际工柞经验，论述了靖西新圩铝土矿床的地质特征及控矿因素。     

抗战时期国民政府开发西北地区矿产资源活动述论

抗战时期，随着国际国内形势的日益严峻，国民政府开始把西北地区作为战略重点大力发展，西北地区的矿产资源也随之得到了前所未有的开发。一系列开发西北地区矿产资源的活动，不但促进了西北地区工矿业的发展与进步，使西北地区的重工业初具雏形，而且为抗战的胜利和西北地区经济的发展做出了巨大贡献，同时大大提高了西北地区在国家的战略地位。     

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.     

优化矿井巷道 提高经济效益

通过讨论矿井回风大巷断面与矿井生产营运成本之间的内在联系,提出一种优化设计矿井回风大巷巷道断面的途径。