Choosing a diversification project in a regulated economy

Choosing a diversification project in a regulated economy involves consideration of a large number of micro and macro issues. In order to make an optimal choice of strategy, a formal approach to diversification planning is necessary. This article develops an approach which aims at breaking up the problem of identification and selection of projects into manageable components. The approach involves three steps: identification of broad industry groups: identification of specific projects within each broad industry group; and comprehensive feasibility study. The major benefit of this approach lies in providing a systematic mechanism for reducing the number of alternatives and in recognizing the link between the internal management processes of strategy formulation with the political and administrative processes in government and regulatory bodies. The article is based largely on the Indian experience.     

对《高海拔缺氧、文化和人类生育力或生殖能力》一文的评论

在戈尔斯坦、查隆和比尔最近发表的论文--<高海拔缺氧、文化和人类生育力或生殖能力的比较研究>(载<美国人类学家>85:28-49,1983)中,作者试图把文化当作解释喜马拉雅山区居民人口差异问题的惟一因素,完全排除了缺氧的影响,同时他们还对别人过去发表的用缺氧进行解释的相关材料(魏兹以及其他人1978;本格汉和塞奇勒1980;古朴塔1980)提出批评.     

Evaluation of the benchmark dose for point of departure determination for a variety of chemical classes in applied regulatory settings

Repeated-dose studies received by the New Substances Assessment and Control Bureau (NSACB) of Health Canada are used to provide hazard information toward risk calculation. These studies provide a point of departure (POD), traditionally the NOAEL or LOAEL, which is used to extrapolate the quantity of substance above which adverse effects can be expected in humans. This project explored the use of benchmark dose (BMD) modeling as an alternative to this approach for studies with few dose groups. Continuous data from oral repeated-dose studies for chemicals previously assessed by NSACB were reanalyzed using U.S. EPA benchmark dose software (BMDS) to determine the BMD and BMD 95% lower confidence limit (BMDL(05) ) for each endpoint critical to NOAEL or LOAEL determination for each chemical. Endpoint-specific benchmark dose-response levels , indicative of adversity, were consistently applied. An overall BMD and BMDL(05) were calculated for each chemical using the geometric mean. The POD obtained from benchmark analysis was then compared with the traditional toxicity thresholds originally used for risk assessment. The BMD and BMDL(05) generally were higher than the NOAEL, but lower than the LOAEL. BMDL(05) was generally constant at 57% of the BMD. Benchmark provided a clear advantage in health risk assessment when a LOAEL was the only POD identified, or when dose groups were widely distributed. Although the benchmark method cannot always be applied, in the selected studies with few dose groups it provided a more accurate estimate of the real no-adverse-effect level of a substance.     

Participatory action research and researcher’s responsibilities: an experience with an Indigenous community

This paper seeks to explore the relational participatory action research (PAR) frameworks that have been developed to allow non-Indigenous researchers, along with Indigenous co-researcher participants, to learn and honour Indigenous stories. Specifically, in the context of PAR research in the Chittagong Hill Tracts of Bangladesh, we outline: (a) potential challenges between Indigenous research paradigms and Western research paradigms, (b) the situation of the non-Indigenous researcher in relation to the Indigenous community, (c) challenges associated with the non-Indigenous researcher’s selection of a research site, (d) collaboration throughout the research process and (e) the processes of developing and maintaining responsibilities. The aim is not to offer simple answers to such challenges, but to highlight the manner in which such processes can be addressed. This research may provide practical insight for future non-Indigenous researchers working with Indigenous communities through a participatory sharing process with Indigenous co-researcher participants, Elders, leaders, knowledge-holders and youths.     

Improved estimation of common location of two exponential populations with order restricted scale parameters using censored samples

ABSTRACT

Estimation of common location parameter of two exponential populations is considered when the scale parameters are ordered using type-II censored samples. A general inadmissibility result is proved which helps in deriving improved estimators. Further, a class of estimators dominating the MLE has been derived by an application of integrated expression of risk difference (IERD) approach of Kubokawa. A discussion regarding extending the results to a general k( ? 2) populations has been done. Finally, all the proposed estimators are compared through simulation.     

Branch and bound algorithms for maximizing expected improvement functions

Deterministic computer simulations are often used as replacement for complex physical experiments. Although less expensive than physical experimentation, computer codes can still be time-consuming to run. An effective strategy for exploring the response surface of the deterministic simulator is the use of an approximation to the computer code, such as a Gaussian process (GP) model, coupled with a sequential sampling strategy for choosing design points that can be used to build the GP model. The ultimate goal of such studies is often the estimation of specific features of interest of the simulator output, such as the maximum, minimum, or a level set (contour). Before approximating such features with the GP model, sufficient runs of the computer simulator must be completed.Sequential designs with an expected improvement (EI) design criterion can yield good estimates of the features with minimal number of runs. The challenge is that the expected improvement function itself is often multimodal and difficult to maximize. We develop branch and bound algorithms for efficiently maximizing the EI function in specific problems, including the simultaneous estimation of a global maximum and minimum, and in the estimation of a contour. These branch and bound algorithms outperform other optimization strategies such as genetic algorithms, and can lead to significantly more accurate estimation of the features of interest.     

The Impact of Estimation: A New Method for Clustering and Trajectory Estimation in Patient Flow Modeling

The ability to accurately forecast and control inpatient census, and thereby workloads, is a critical and long‐standing problem in hospital management. The majority of current literature focuses on optimal scheduling of inpatients, but largely ignores the process of accurate estimation of the trajectory of patients throughout the treatment and recovery process. The result is that current scheduling models are optimizing based on inaccurate input data. We developed a Clustering and Scheduling Integrated (CSI) approach to capture patient flows through a network of hospital services. CSI functions by clustering patients into groups based on similarity of trajectory using a novel semi‐Markov model (SMM)‐based clustering scheme, as opposed to clustering by patient attributes as in previous literature. Our methodology is validated by simulation and then applied to real patient data from a partner hospital where we demonstrate that it outperforms a suite of well‐established clustering methods. Furthermore, we demonstrate that extant optimization methods achieve significantly better results on key hospital performance measures under CSI, compared with traditional estimation approaches, increasing elective admissions by 97% and utilization by 22% compared to 30% and 8% using traditional estimation techniques. From a theoretical standpoint, the SMM‐clustering is a novel approach applicable to any temporal‐spatial stochastic data that is prevalent in many industries and application areas.     

Multi-Dimensional Deprivation in India During and After the Reforms: Do the Household Expenditure and the Family Health Surveys Present Consistent Evidence?

This paper uses the recent approach of multidimensional deprivation measures to provide a comprehensive and wide ranging assessment of changes to living standards in India during the period, 1992/93–2004/5. This covers the reforms and the immediate post reforms time periods. The study is the first to be based on the simultaneous use of two parallel data sets, namely the National Sample Survey (NSS) and National Family Health Survey (NFHS) data sets, covering proximate rounds and near identical time periods. The results allow a check of consistency on the picture of deprivation in India between these two data sets. The study is conducted both at regionally disaggregated levels and by socio economic groups. The deprivation dimensions range widely from the conventional expenditure dimensions to non-expenditure dimensions such as access to drinking water and clean fuel, to health dimensions such as child stunting and the mother’s BMI. The use of decomposable deprivation measures allows the identification of regions, socio economic groups and deprivation dimensions that are contributing more than others to total deprivation.     

Fertility Behaviour under Income Uncertainty

This paper develops a two-period stochastic model of fertility behaviour to provide a possible explanation for the recent sharp decline in birth rates in the former Soviet Republics and Eastern European countries. Due to the existence of irreversibilities associated with the childbearing decision and the option of postponing childbearing for a later time, it may be optimal for individuals to postpone childbearing during times of increased income uncertainty.