Notizie preliminari sull'azione fitodinamica dell'acido difenililacetico sulla pianta del tabacco

Summary The application of diphenylilacetic acid has shown favorable effects on the growth of tobacco plants. Solutions containing 10 p.p.m. and 20 p.p.m. produce, in weight, an almost double growth in treated plants in comparison with the controls. Diphenylilacetic acid can be considered as a growth-promoting substance. The data are not definite.     

Heterostructure in ZnO Nano-Tetrapods

1 Introduction 　　Nanoscale science and technology have attracted greatattention since the novel properties become dominant for well-known materials as their sizes reduced to some critical dimension. These properties frequently originate in lattice distortions, structure transformations etc[1]. The variations of size and structure ofnanocrystals lead to the change of their electronic structures. Very recently, nanoscale materials with different electronic structures were utilized in fabricating nanoscale junctions[2]. 　　……     

高师英语职业技能教育改革

高师院校肩负着培养基础教育师资的重任。衡量师资素质的重要标准之一，是教师职业素质与技能掌握、运用的程度。因而职业技能教育是高师教育中一个重要组成部分。本文通过对高师院校英语职业技能教育的反思，以及对基础教育发展需求分析，提出从可持续发展、教育的内在价值与创新教育的三个层面探讨高师英语职业技能教育改革。     

Forecast accuracy after pretesting with an application to the stock market

In econometrics, as a rule, the same data set is used to select the model and, conditional on the selected model, to forecast. However, one typically reports the properties of the (conditional) forecast, ignoring the fact that its properties are affected by the model selection (pretesting). This is wrong, and in this paper we show that the error can be substantial. We obtain explicit expressions for this error. To illustrate the theory we consider a regression approach to stock market forecasting, and show that the standard predictions ignoring pretesting are much less robust than naive econometrics might suggest. We also propose a forecast procedure based on the ‘neutral Laplace estimator’, which leads to an improvement over standard model selection procedures. Copyright © 2004 John Wiley & Sons, Ltd.     

DETERMINATION OF KRAFT LIGNIN CONCENTRATIONS BY FTIR

A fast and accurate method based on FTIR is developed for determining the lignin content and its characteristic bands in alkali solutions. The work consisted of two main parts: 1) establishing a predictive model and 2) determination of the accuracy of the model. The model was derived by applying the partial least squares algorithm for multivariate analyses to a set of spectrum data obtained from selected IR absorption regions in the range of 1600 - 900 cm-1. The model was tested with spent liquors obtained from commercial pulp mills.The accuracy of the predictive model is extremely high suitable for commercial applications,particularly for monitoring the dynamic response of modern kraft pulping processes.     

Which survey indicators are useful for monitoring consumption? Evidence from European countries

This paper assesses the information content of two survey indicators for consumption developments in the near future for eight European countries in the period 1985–1998. Empirical work on this topic typically focuses on consumer confidence, the perceptions of buyers of consumption goods. This paper examines whether perceptions of sellers of consumption goods, measured by retail trade surveys, may also improve short‐term monitoring of consumption. We find that both consumer confidence and retailer confidence embody valuable information, when analysed in isolation. For France, Italy and Spain we conclude that adding retail confidence does not improve the indicator model once consumer confidence has been included. For the UK the reverse case is obtained. For the remaining four countries we show that combining consumer sentiment and retail trade confidence into a composite indicator leads to optimal results. Our results suggest that incorporating information from retail trade surveys may offer significant benefits for the analysis of short‐term prospects of consumption. Copyright © 2004 John Wiley & Sons, Ltd.     

基于神经网络的企业信用等级评估

企业信用等级评估是金融领域重要的问题，论文采用人工神经网络模型研究企业信用等级的评估问题，按照企业样本在信用等级的分布状况来抽样，然后，根据企业样本性质的不同，将其分为制造业和非制造业两大类，利用偏相关分析方法建立了企业信用评级的指标体系，此外，还介绍了几种企业信用评级常用的评估模型，并将神经网络评估模型的性能和其他的信用评估模型作了比较，实验结果表明神经网络模型具有更好的预测准确性。     

管理系统的最经济控制问题

依据最经济控制问题的概念及其对无确定性数学模型系统分析存在的局限性，对现代管理系统最经济控制问题，提出了在满足系统基本要求前提下。实现控制功能及品质与控制成本比最佳或最划算的模型定义，并对管理系统的可靠性、ABC管理法、WSR方法论等方面的可靠性成本、运行成本和最佳收益等最经济控制问题进行了研究．