从认识论"自我"到生存论"自我"

近代哲学建构的自我有着巨大的理论困难.黑格尔之后的非理性主义对自我的理解超越了近代认识论的视野,但仍有传统形而上学的残余.胡塞尔现象学既坚执纯粹自我是所有真理的源泉,又潜在地包含着对以往自我观的解构.海德格尔认为,此在以实存的情绪融入事情是自我拥有的基本方式.进而,梅洛-庞蒂克服了此在形式层面的生存状态,肯定了以身体主体方式在世的"沉默的我思".可见,现代西方哲学对近代哲学的超越意味着生存论自我对认识论自我的超越.     

关于对可转换债券融资发行范围的确定研究

可转换债券的双重属性以及企业生产经营状况使可转换债券融资具有很大的不确定性,最终导致不同的结果,结果的不同将影响企业进行融资决策中资本结构的制定,因而需要对可转换债券发行范围进行确定。完全转股和回售是企业经营状况良好和极差两种极端情况下可转债融资所产生的结果,此两种结果决定了可转换债券发行范围的上下限,将完全转股结果下所求得的最优融资资本结构作为可转债发行范围的上限,回售情况下得到的最优融资资本结构作为发行下限,从而得到可转换债券发行范围。最后利用基于随机模拟的遗传算法对融资决策模型进行求解,并通过算例解释了算法的有效性。     

基因技术的社会风险

基因技术给人类的生存与发展提供了许多希望。但是,基因技术对人类健康和生态环境具有潜在危害,对社会稳定和社会安全产生威胁,对人类价值观产生冲击,从而在社会各个层面产生意想不到的后果。因此,探讨基因技术将给人类带来的社会风险,提前采取预防措施,做到“未雨绸缪,防患于未然”,有助于促进基因技术的良性发展。     

波兰尼的"默会认识"思想研究

英国哲学家波兰尼首次在认识论领域提出"默会认识"这一概念.波兰尼的"默会认识",实质上就是认识主体对认识对象身心合一的整体理解.波兰尼认为,默会认识是人类获得和持有知识的终极能力,在认识的过程中起着决定性的作用.在对认识主体的地位和作用的重视上,其思想表现出与马克思主义认识论的某种契合关系.这种契合关系是我们吸收和借鉴波兰尼默会认识思想的基础,并为当代中国马克思主义认识论的发展提供了有益启示.     

整体思维在现代管理理论中的凸显及其知识论定位

现代管理学的思维方式,经历了一个从有限的整体思维走向比较彻底的整体思维的历史过程。泰勒在思维方式上是生产效率向度的局域整体思维。而梅奥开始从社会历史变化的角度审视工人生产行为,形成了“社会历史认识论”意义上的动态整体思维方式。巴纳德则自觉地关注组织本身的整体及组织与环境的统一,表现出彻底的整体思维方式。这一历史过程既是现代管理学自身的知识运动,也是社会学、心理学、生物学、哲学等主要知识对管理学影响的必然结果。     

Genetic programming as a means for programming computers by natural selection

Many seemingly different problems in machine learning, artificial intelligence, and symbolic processing can be viewed as requiring the discovery of a computer program that produces some desired output for particular inputs. When viewed in this way, the process of solving these problems becomes equivalent to searching a space of possible computer programs for a highly fit individual computer program. The recently developed genetic programming paradigm described herein provides a way to search the space of possible computer programs for a highly fit individual computer program to solve (or approximately solve) a surprising variety of different problems from different fields. In genetic programming, populations of computer programs are genetically bred using the Darwinian principle of survival of the fittest and using a genetic crossover (sexual recombination) operator appropriate for genetically mating computer programs. Genetic programming is illustrated via an example of machine learning of the Boolean 11-multiplexer function and symbolic regression of the econometric exchange equation from noisy empirical data.Hierarchical automatic function definition enables genetic programming to define potentially useful functions automatically and dynamically during a run, much as a human programmer writing a complex computer program creates subroutines (procedures, functions) to perform groups of steps which must be performed with different instantiations of the dummy variables (formal parameters) in more than one place in the main program. Hierarchical automatic function definition is illustrated via the machine learning of the Boolean 11-parity function.     

科学态度是科学素质的核心

提高科学素质是全世界的共识.科学素质包括四个因素:科学精神、科学态度、科学知识、科学方法.四者中科学精神与科学态度容易混淆.科学精神是本体论承诺.科学态度是认识论承诺,即科学知识可靠性的物质保证.科学素质是一个大系统,其中科学态度是这个系统的序参量.因此,这个系统符合协同学的自组织原则.同时,这个系统的输出又必然是科学态度,科学态度又反过来进一步整合大系统.于是,这又是一个超循环论模型.提高科学素质的关键是端正科学态度.     

A likelihood ratio test for goodness‐of‐fit of recessive and dominant models for case–control studies

Testing goodness‐of‐fit of commonly used genetic models is of critical importance in many applications including association studies and testing for departure from Hardy–Weinberg equilibrium. Case–control design has become widely used in population genetics and genetic epidemiology, thus it is of interest to develop powerful goodness‐of‐fit tests for genetic models using case–control data. This paper develops a likelihood ratio test (LRT) for testing recessive and dominant models for case–control studies. The LRT statistic has a closed‐form formula with a simple $\chi^{2}(1)$ null asymptotic distribution, thus its implementation is easy even for genome‐wide association studies. Moreover, it has the same power and optimality as when the disease prevalence is known in the population. The Canadian Journal of Statistics 41: 341–352; 2013 © 2013 Statistical Society of Canada     

Fitting of self-exciting threshold autoregressive moving average nonlinear time-series model through genetic algorithm and development of out-of-sample forecasts

Self-exciting threshold autoregressive moving average (SETARMA) nonlinear time-series model is considered here. Sufficient conditions for invertibility and stationarity are derived. Parameter estimation algorithm is developed by employing real-coded genetic algorithm stochastic optimization procedure. A significant feature of the work done is that optimal out-of-sample forecasts up to three-step ahead and their forecast error variances are derived analytically. Relevant computer programs are written in statistical analysis system (SAS) and C. As an illustration, annual mackerel catch time-series data are considered. Forecast performance of the fitted model for hold-out data is evaluated by using Naive and Monte Carlo approaches. It is found that optimal out-of-sample forecast values are quite close to actual values and estimated variances are quite close to theoretical values. Superiority of the SETARMA model over the SETAR model for equal predictive ability through Diebold–Mariano test is also established.     

“百年未有之大变局”之哲学分析

当今世界正处于“百年未有之大变局”中。这是中国共产党对于世界新的时代特征的全新、科学和准确的研判。“百年未有之大变局”这一重大论断，具有深厚的马克思主义哲学的本体论基础、认识论基础、矛盾论基础和历史观基础。作为科学世界观与方法论，马克思主义哲学的辩证唯物主义和历史唯物主义为我们深刻认识和精准把握“百年未有之大变局”的深层本质和哲学依据提供了重要的认知性引导、方法论基础和实践智慧支撑。