中央苏区图书出版物研究

从图书出版年度分布、出版部门分布、类别分布等方面,对土地革命战争时期中央苏区出版的446种图书进行统计分析。     

Chinese families in transition: Cultural conflicts and adjustment problems

Challenged to cope with two different cultures, Chinese American immigrant families face many stressors and conflicts. Such difficulties faced by these individuals usually stem from language, religious, and value differences. Furthermore, family members are faced with role and status changes due to differing rates and levels of acculturation. As a result, there is a great need for mental health services. However, due to cultural barriers, mental health services are not accessible nor acceptable to many Chinese Americans. Effective intervention strategies which integrate the Chinese cultural values and norms with psychotherapy are recommended.     

On the nearly nonstationary seasonal time series

A time series is said to be nearly nonstationary if some of its characteristic roots are close to the unit circle. For a seasonal time series, such a notion of near-nonstationarity is studied in a double-array setting. This approach not only furnishes a natural transition between stationarity and nonstationarity, but also unifies the corresponding asymptotic theories in a seasonal-time-series context. The general theory is expressed in terms of functionals of independent diffusion processes. The asymptotic results have applications to estimation and testing in a nearly nonstationary situation and serve as a useful alternative to the common practice of seasonal adjustment.     

Estimation of conditional quantiles by a new smoothing approximation of asymmetric loss functions

In this paper, nonparametric estimation of conditional quantiles of a nonlinear time series model is formulated as a nonsmooth optimization problem involving an asymmetric loss function. This asymmetric loss function is nonsmooth and is of the same structure as the so-called lopsided absolute value function. Using an effective smoothing approximation method introduced for this lopsided absolute value function, we obtain a sequence of approximate smooth optimization problems. Some important convergence properties of the approximation are established. Each of these smooth approximate optimization problems is solved by an optimization algorithm based on a sequential quadratic programming approximation with active set strategy. Within the framework of locally linear conditional quantiles, the proposed approach is compared with three other approaches, namely, an approach proposed by Yao and Tong (1996), the Iteratively Reweighted Least Squares method and the Interior-Point method, through some empirical numerical studies using simulated data and the classic lynx pelt series. In particular, the empirical performance of the proposed approach is almost identical with that of the Interior-Point method, both methods being slightly better than the Iteratively Reweighted Least Squares method. The Yao-Tong approach is comparable with the other methods in the ideal cases for the Yao-Tong method, but otherwise it is outperformed by other approaches. An important merit of the proposed approach is that it is conceptually simple and can be readily applied to parametrically nonlinear conditional quantile estimation.     

Beliefs, death, anxiety, denial, and treatment preferences in end-of-life care: a comparison of social work students, community residents, and medical students

This study examined cultural and religious beliefs, death anxiety, denial, and medical treatment preferences in end-of-life care in a sample of social work students, community residents, and medical students in a mid-western city of 49,000. Results indicated that most social work students, community residents, and medical students preferred palliative as opposed to life-prolonging care during terminal illness. The three groups differed in cultural and religious beliefs and all three reported a moderate amount of death anxiety. Students reported less denial of terminality than community residents. Implications for personal and professional preparation to provide end-of-life care are discussed.     

Presenting Results from Model Based Studies to Decision-Makers: Can Sensitivity Analysis be a Defogging Agent?

The motivation of the present work is to provide an auxiliary tool for the decision-maker (DM) faced with predictive model uncertainty. The tool is especially suited for the allocation of R&Dresources. When taking decisions under uncertainties, making use of the output from mathematical or computational models, the DM might be helped if the uncertainty in model predictions be decomposed in a quantitative-rather than qualitativefashion, apportioning uncertainty according to source. This would allow optimal use of resources to reduce the imprecision in the prediction. For complex models, such a decomposition of the uncertainty into constituent elements could be impractical as such, due to the large number of parameters involved. If instead parameters could be grouped into logical subsets, then the analysis could be more useful, also because the decision maker might likely have different perceptions (and degrees of acceptance) for different kinds of uncertainty. For instance, the decomposition in groups could involve one subset of factors for each constituent module of the model; or one set for the weights, and one for the factors in a multicriteria analysis; or phenomenological parameters of the model vs. factors driving the model configuratiodstructure aggregation level, etc.); finally, one might imagine that a partition of the uncertainty could be sought between stochastic (or aleatory) and subjective (or epistemic) uncertainty. The present note shows how to compute rigorous decomposition of the output's variance with grouped parameters, and how this approach may be beneficial for the efficiency and transparency of the analysis.