上海基础房价相关指标及走势的分析与研究

基础房价的相关指标及其走势一直是大众关心的热门话题．本文通过对上海基础房价相关指标的分析，建立了市场房价走势的两个数学模型．模型一：在相关性分析的基础上利用主成分分析消除指标间的共线性，再用回归拟合房价模型并进行预测；模型二：在相关性分析的基础上利用核估计方法预测出房价．继呵对2005年下半年的房价走势进行了预测，得出的结果与实际情况相吻合．     

Ion implantation induced by Cu ablation at high laser fluence

High energy laser plasma-produced Cu ions have been implanted in silicon substrates placed at different distances and angles with respect to the normal to the surface of the ablated target. The implanted samples have been produced using the iodine high power Prague Asterix Laser System (PALS) using 438 nm wavelength irradiating in vacuum a Cu target. The high laser pulse energy (up to 230 J) and the short pulse duration (400 ps) produced a non-equilibrium plasma expanding mainly along the normal to the Cu target surface. Time-of-flight (TOF) technique was employed, through an electrostatic ion energy analyzer (IEA) placed along the target normal, in order to measure the ion energy, the ion charge state, the energy distribution and the charge state distribution. Ions had a Boltzmann energy distributions with an energy increasing with the charge state. At a laser fluence of the order of 6 × 10⁶ J/cm², the maximum ion energy was about 600 keV and the maximum charge state was about 27+.In order to investigate the implantation processes, Cu depth profiles have been performed with Rutherford backscattering spectrometry (RBS) of 1.5 MeV helium ions, Auger electron spectroscopy (AES) with 3 keV electron beam and 1 keV Ar sputtering ions in combination with scanning electron microscopy (SEM). Surface analysis results indicate that Cu ions are implanted within the first surface layers and that the ion penetration ranges are in agreement with the ion energy measured with IEA analysis.     

Experimental identification of physical parameters of fluid-filled pipes using acoustical signal processing

A method is formulated for the identification of an unknown physical parameter of a fluid-filled pipe using the measurement of sound speed in the pipe. The method uses a simple formula which provides the relationship between the sound speed and a few physical parameters of the pipe: thickness, diameter, wall material constants and fluid constants. Once the sound speed in the pipe is measured, the simple formula can be used to extract one of the unknown parameters providing the remaining ones are known.The sound speed in the pipe is measured using a 3-transducer array. In order to demonstrate the potential of the technique the results of several measurements obtained in a water-filled steel pipe are presented.The required accuracy of the measurement of sound speed and of the specification of known parameters is analysed. The accuracy depends on the unknown parameter which is to be identified. For example, if the pipe thickness is the unknown parameter, the other parameters have to be known within a very narrow margin of error. On the contrary, if the fluid properties have to be identified the needed accuracy of known parameters gets much lower.     

Application of x-ray fluorescence analysis to investigation of the composition of gunshot residues

We have used x-ray fluorescence analysis to study the elemental composition of gunshot residues from smooth-bore and rifled-bore guns. We have established that it is possible to differentiate between types of projectiles (jacketed/lead), types of primers (corrosive/noncorrosive), and types of propellant powders (black/smokeless) by analysis of the elemental composition of the gunshot residues. We have shown that the mercury content in gunshot residues on the surface of the object carrying the residues steadily decreases as storage time increases. Despite this fact, mercury can be preserved as a component of gunshot residues on the object (cotton cloth) under room conditions for more than 45 days. __________ Translated from Zhurnal Prikladnoi Spektroskopii, Vol. 73, No. 3, pp. 320–325, May–June, 2006.     

Bayesian Prediction Analysis for Growth Curve Model Using Noninformative Priors

We apply a Bayesian approach to the problem of prediction in an unbalanced growth curve model using noninformative priors. Due to the complexity of the model, no analytic forms of the predictive densities are available. We propose both approximations and a prediction-oriented Metropolis-Hastings sampling algorithm for two types of prediction, namely the prediction of future observations for a new subject and the prediction of future values for a partially observed subject. They are illustrated and compared through real data and simulation studies. Two of the approximations compare favorably with the approximation in Fearn (1975, Biometrika, 62, 89–100) and are very comparable to the more accurate Rao-Blackwellization from Metropolis-Hastings sampling algorithm.     

Synthesis and structures of nitroxyalkyl methylphosphonates

The reactions of ethylene glycol mononitrate and glycerol 1,3-dinitrate with methylphosphonic dichloride afforded new nitroxyalkyl methylphosphonates.     

我国医疗费用增长与医疗设备投入的相关性研究

近年来我国卫生总费用占GDP的比例增长很快,而在卫生费用结构上则发生政府投入下降和个人支出的上升。本文采集了大量的统计数据,采用统计相关性研究的方法,论证了医疗设备规模的不断扩大是导致医疗费用上升的主要因素之一;医疗设备的快速增长与医院维修费用投入的增长直接相关,而引起医疗设备维修大量投入的主要原因则是故障期内医疗设备的非正常闲置。本文通过对个人卫生费用的上升、医疗设备规模的扩大及其医疗设备维修投入费用增加相关性的分析,说明了在这种关系下,十分有必要研究医院医疗设备维修体系,以在卫生投入和患者权益上达到平衡。     

中学生男性性别角色期望的因子模型与应用

运用中学生男性性别角色期望调查表和因子分析方法对贵阳市中学生进行男性性别角色期望调查和定性与定量分析,为中学生树立适宜的性别角色观,促进其心理健康发展提供量化依据.分析显示:传统的男性角色并不被现代中学生完全接受,无论是男中学生还是女中学生都在力图探求一种新的男性性别角色模式,且两性中学生对这一新的男性性别角色模式的期望和把握是有一定差异的.     

Numerical analysis of the Toda lattice equations

Numerical solutions to three systems of integrable evolutionary equations from the Toda lattice hierarchy are analyzed. These are the classical Toda lattice, the second local dispersive flow, and the second extended dispersive flow. Special attention is given to the properties of soliton solutions. For the equations of the second local flow, two types of solitons interacting in a special manner are found. Solutions corresponding to various initial data are qualitatively outlined.     

Temperature effect on deposition rate of silicon nitride films

Temperature effects on deposition rate of silicon nitride films were characterized by building a neural network prediction model. The silicon nitride films were deposited by using a plasma enhanced chemical vapor deposition system and process parameter effects were systematically characterized by 2⁶⁻¹ fractional factorial experiment. The process parameters involved include a radio frequency power, pressure, temperature, SiH₄, N₂, and NH₃ flow rates. The prediction performance of generalized regression neural network was drastically improved by optimizing multi-valued training factors using a genetic algorithm. Several 3D plots were generated to investigate parameter effects at various temperatures. Predicted variations were experimentally validated. The temperature effect on the deposition rate was a complex function of parameters but N₂ flow rate. Larger decreases in the deposition rate with the temperature were only noticed at lower SiH₄ (or higher NH₃) flow rates. Typical effects of SiH₄ or NH₃ flow rate were only observed at higher or lower temperatures. A comparison with the refractive index model facilitated a selective choice of either SiH₄ or NH₃ for process optimization.