人类欲望与全球资本主义:挑战与机遇

东西方古代和现代对人性和人类欲望的哲学见解,为对国际全球资本主义狂潮以及其相关行业的必要性提供了思想资源。所有这些可以追溯到早期家庭幼儿教育,即亚里斯多德所说的人类先验以及张载所说的美好生活,对人类欲望从结构上进行正确引导。在这方面,对于模仿和欲望这两个范畴以及其各自关系的深刻哲学反思,无论是预设还是被预设,都有助于重建此结构,而此结构可以产生这样的引导。     

The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*

An auditor gives a going concern uncertainty opinion when the client company is at risk of failure or exhibits other signs of distress that threaten its ability to continue as a going concern. The decision to issue a going concern opinion is an unstructured task that requires the use of the auditor's judgment. In cases where judgment is required, the auditor may benefit from the use of statistical analysis or other forms of decision models to support the final decision. This study uses the generalized reduced gradient (GRG2) optimizer for neural network learning, a backpropagation neural network, and a logit model to predict which firms would receive audit reports reflecting a going concern uncertainty modification. The GRG2 optimizer has previously been used as a more efficient optimizer for solving business problems. The neural network model formulated using GRG2 has the highest prediction accuracy of 95 percent. It performs best when tested with a small number of variables on a group of data sets, each containing 70 observations. While the logit procedure fails to converge when using our eight variable model, the GRG2 based neural network analysis provides consistent results using either eight or four variable models. The GRG2 based neural network is proposed as a robust alternative model for auditors to support their assessment of going concern uncertainty affecting the client company.     

On selecting from k finite populations the population with the largest α -quantile

Several procedures for ranking populations according to the quantile of a given order have been discussed in the literature. These procedures deal with continuous distributions. This paper deals with the problem of selecting a population with the largest α-quantile from k ≥ 2 finite populatins, where the size of each population is known. A selection rule is given based on the sample quantiles, where he samples are drawn without replacement. A formula for the minimum probability of a correct selection for the given rule, for a certain configuration of the population α-quantiles, is given in terms of the sample numbers.     

An empirical bayes estimate of multinomial probabilities

This paper deals with the prblem of estimating simultaneously the parameters (Cell probabilities) of m ≤ 2 independent multinomial distributions, with respect to a quadratic loss functions. An empirical Bayes estimator is proposed which is shown to have smaller risk than the maximum likelihood estimator for sufficiently large values of mq, where q is a measure of the average diversity of the given multinomial populations. Some numerical results are given on the performance of the proposed estimator.     

Maximum likelihood estimation of the parameters of a multiple step-stress model from the Birnbaum-Saunders distribution under time-constraint: A comparative study

The cumulative exposure model (CEM) is a commonly used statistical model utilized to analyze data from a step-stress accelerated life testing which is a special class of accelerated life testing (ALT). In practice, researchers conduct ALT to: (1) determine the effects of extreme levels of stress factors (e.g., temperature) on the life distribution, and (2) to gain information on the parameters of the life distribution more rapidly than under normal operating (or environmental) conditions. In literature, researchers assume that the CEM is from well-known distributions, such as the Weibull family. This study, on the other hand, considers a p-step-stress model with q stress factors from the two-parameter Birnbaum-Saunders distribution when there is a time constraint on the duration of the experiment. In this comparison paper, we consider different frameworks to numerically compute the point estimation for the unknown parameters of the CEM using the maximum likelihood theory. Each framework implements at least one optimization method; therefore, numerical examples and extensive Monte Carlo simulations are considered to compare and numerically examine the performance of the considered estimation frameworks.     

Test for the equality of interclass correlation cofefficients under unequal family sizes for several populations

Large sample ANOVA test and likelihood ratio test have been Proposed to test for the equaiity of sevcrai iniraciass correlation coefiicients unier unequai family sizes based on several independent multinormal samples, it has been found on the basis of simulation study that the likelihood ratio test consistenily and reliably produced results superior to those of the large sample ANOVA test in terms of power for various combinations of intraclass correlatxon coefficient values.     

用于改良杂交水稻品种的抗虫性转基因保持系(IR68899B)

杂种优势的利用使得水稻产量较半矮杆常规稻增加了 1 5%以上 ,为了保持产量的稳定 ,杂交稻品种还应具备对病虫的可遗传抗性 ,比如对茎杆钻心虫的抗性。而来自于苏云金杆菌并经人工剪裁合成的CryIA(b)基因便是有效地抗茎杆钻心虫基因之一。实践证明 ,基因转化是一项导入细菌基因于水稻基因组的行之有效的技术。笔者已利用获得转基因保持系这一途径来选育抗虫的杂交稻。利用基因枪方法 ,将CryIA(b)基因以及驱动该基因的 3 5S启动子成功地转入了IRRI的骨干保持系IR68899B。该基因的整合和表达已由Southern和Western杂交所证明。目前已分析到转基因植株的第二世代 (T2 )。鉴定表明 ,Bt 转基因植株中黄色茎杆钻心虫的抗性明显提高。本文首次报导转基因保持系的获得 ,以用于杂交稻品种的选育     

Software reliability assessment using accelerated testing methods

The use of operational profiles and usage-based testing has received considerable attention recently in the software engineering literature. Testing under the actual operational profile can, however, be expensive, time consuming or even infeasible in situations where the performance of a system is dominated by infrequent but highly critical events. We consider a real application that deals with telecommunications network restoration after network failure caused by cuts in fibre optic cables. We use this application to demonstrate the usefulness of traditional accelerated testing methods to test and estimate software reliability. These methods, which have been extensively used in hardware reliability, have an important role to play in software reliability assessment as well.     

Between Darius and Khomeini: exploring Iran's national identity problematique

Iran, since the advent of its nation-state building process, has struggled to define its national identity in a relevant and resonant way. This article, while acknowledging the multi-dimensional nature of Iran's national identity, focuses on its two most profound components: Nationalism and Islamism. It explores how the tensions between these two are at the heart of not only the problem of Iranian identity but also of Persian identity. Examining how these two bases of identity also rely on similarity as well as difference the article argues, through the use of the tool of a problematique, that a coherent Iranian national identity, inclusive of all including ethnic minorities, is not possible until the tensions between Nationalism and Islamism at the heart of Persian identity are resolved.