工具实在论学派述评

工具实在论学派认为,科学的技术体现是科学发现和知识产生的手段,仪器是科学技术体现的方式。当代科学不是偶然地,而是在本质上通过仪器被技术化体现的。在工具实在论学派的视野中,科学的技术即仪器成为揭示新事物的基础,人类知觉的放大和增强也只有通过仪器才会发生。正因如此,工具实在论学派具有对现有科学哲学的批判性、仪器和实验核心地位的实践性以及对身体和知觉关注的现象学性三个特点。     

理性的透视：从“中庸”的视角

古希腊先哲对实践理性的探讨、近代欧洲先哲对工具理性与新实践理性的探讨、西哲对理性的探讨,启示现代世界：工具理性存在着毁灭人类的可能性。而以“中道”为标准的实践理性。能在道德层面弥补工具理性的不足,防止工具理性的无度泛滥。     

我国产业结构调整的金融与政策支持

我国近期面对的主要挑战是如何使宏观经济与结构改革、产业进步相互促进 ,迎接新世纪的到来。国内外的经验表明 ,实行金融、政策与产业结构的有机结合 ,是提高科技水平 ,推动产业结构调整和升级的最有效方法之一。产业政策既是金融及其有关政策的实施对象 ,又是调整结构目标实现的重要表现形式 ,但产业政策必须兼容在金融及经济政策之中 ,二者的总体目标是一致的。中国的最大优势是能集中财力办大事 ,如果失去了国家财金政策的支持 ,也就失去了优势。应进行财金制度创新 ,挖掘政策潜力 ,建立财金及经济政策对产业调整和产业升级的激励机制 ,发挥财金政策的“四两拨千斤”效应     

Projection‐Based Statistical Inference in Linear Structural Models with Possibly Weak Instruments

It is well known that standard asymptotic theory is not applicable or is very unreliable in models with identification problems or weak instruments. One possible way out consists of using a variant of the Anderson–Rubin ((1949), AR) procedure. The latter allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, but not for individual coefficients. This problem may in principle be overcome by using projection methods (Dufour (1997), Dufour and Jasiak (2001)). At first sight, however, this technique requires the application of costly numerical algorithms. In this paper, we give a general necessary and sufficient condition that allows one to check whether an AR‐type confidence set is bounded. Furthermore, we provide an analytic solution to the problem of building projection‐based confidence sets from AR‐type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are needed to build the confidence intervals.     

Overall Successful Aging: Its Factorial Structure and Predictive Factors

As the concept of successful ageing (SA) tends to take different meanings among researchers, there is a lack of consensus on how to measure SA. In order to address this gap, the present study aims to explore the factor structure of SA involving SA indicators presented in the literature. Using Americans' Changing Lives study (ACL), a second-order confirmatory factor analysis on factors constituting an overall SA measure and a SEM regression model to examine the predictive factors of the overall SA measure were estimated. A second-order confirmatory factor model including three latent constructs of SA – Physical Domain (diseases, functional health, and physical activity), Mental Domain (depression, self-efficacy, and cognitive impairment), and Social Domain (formal social integration, informal social integration, and social support) – fits the data properly. The findings of a SEM regression model replicates the findings of previous SA research, suggesting the overall SA latent construct is a valid measure for SA.     

卫星导航接收机测速精度测量方法研究

以GPS为例,研究卫星导航接收机动态测量精度的测量方法。讨论了被动式导航接收机的测速原理,阐述了卫星导航信号模拟源产生信号的基本方法,说明通过调节模拟源中各延迟环节的时延量,即可模拟产生相对于载频的频偏,以此作为接收机动态的理论真值并与实际测量值相比较,可获得包括速度在内的动态测量精度。在理论分析的基础上介绍了基于模拟源的接收机测速精度测量的实现方法。     

Adjusted estimates for time-to-event endpoints

In the analysis of retrospective data or when interpreting results from a single-arm phase II clinical trial relative to historical data, it is often of interest to show plots summarizing time-to-event outcomes comparing treatment groups. If the groups being compared are imbalanced with respect to factors known to influence outcome, these plots can be misleading and seemingly incompatible with results obtained from a regression model that accounts for these imbalances. We consider ways in which covariate information can be used to obtain adjusted curves for time-to-event outcomes. We first review a common model-based method and then suggest another model-based approach that is not as reliant on model assumptions. Finally, an approach that is partially model free is suggested. Each method is applied to an example from hematopoietic cell transplantation.     

Cox regression analysis in presence of collinearity: an application to assessment of health risks associated with occupational radiation exposure

This paper considers the analysis of time to event data in the presence of collinearity between covariates. In linear and logistic regression models, the ridge regression estimator has been applied as an alternative to the maximum likelihood estimator in the presence of collinearity. The advantage of the ridge regression estimator over the usual maximum likelihood estimator is that the former often has a smaller total mean square error and is thus more precise. In this paper, we generalized this approach for addressing collinearity to the Cox proportional hazards model. Simulation studies were conducted to evaluate the performance of the ridge regression estimator. Our approach was motivated by an occupational radiation study conducted at Oak Ridge National Laboratory to evaluate health risks associated with occupational radiation exposure in which the exposure tends to be correlated with possible confounders such as years of exposure and attained age. We applied the proposed methods to this study to evaluate the association of radiation exposure with all-cause mortality.     

创新金融工具的风险与监管浅析

90年代以来 ,全球几乎每场风暴都与创新金融工具有关 ,在我们看到创新金融工具在避险、保值、促进全球金融业加速发展的同时 ,又不得不面对它们给金融业可能带来的巨大风险。本文对创新金融工具风险的形成、风险的类型和如何有效的监管作一定的探讨。     

Transformation using ( x + 0.5) to stabilize the variance of populations

Transformation is required to achieve homo-scedasticity when we perform ANOVA to test the effect of factors on population abundance. The effectiveness of transformations decreases when the data contain zeros. Especially, the logarithmic transformation or the Box–Cox transformation is not applicable in such a case. For the logarithmic transformation, 1 is traditionally added to avoid such problems. However, there is no concrete foundation as to why 1 is added rather than other constants, such as 0.5 or 2, although the result of ANOVA is much influenced by the added constant. In this paper, I suggest that 0.5 is preferable to 1 as an added constant, because a discrete distribution defined in {0, 1, 2, . . .} is approximately described by a corresponding continuous distribution defined in (0, ≧) if we add 0.5. Numerical investigation confirms this prediction. Received: October 16, 1998 / Accepted: June 10, 1999