Minimally changed run sequences in factorial experiments

Randomization of run sequences in factorial experiments may result in large number of changes in factor levels which will make the experimentation expensive, time-consuming and difficult. Experiments in which it is difficult to change the levels of factor(s) use of minimally changed run sequences may often be preferable to a random run sequence. In the present paper, we have developed method for obtaining minimally changed run sequences for factorial experiments. The general expression of factor-wise number of level changes for the developed minimally changed run sequences has also been obtained. A relationship has been established between the time count effect of a lower order factorial with minimally changed run sequences and that of a higher order factorial with minimally changed run sequences obtained through the lower order minimally changed run sequences. For providing a readymade solution to the end users, a SAS macro has also been developed for generating these minimally changed run sequences along with its parameters.     

The Cucconi Test for Location-scale Alternatives in Application to Asymmetric Hydrological Variables

To identify location-scale trends, which environmental data often exhibit, location-scale tests have to be addressed. The aim of this article was to estimate size and power of the Cucconi rank-based test when applied to various skewed distributions, typical in hydrology. Results of the Monte Carlo simulation revealed great power for series with low coefficient of variation, time of change close to the middle, not very heavy tail, and with length of at least 60. Comparison to the Lepage test discovered larger usefulness of the Cucconi test for short series and change close to the middle. Several practical applications were presented.     

Risk‐Based Approach for Microbiological Food Safety Management in the Dairy Industry: The Case of Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

According to Codex Alimentarius Commission recommendations, management options applied at the process production level should be based on good hygiene practices, HACCP system, and new risk management metrics such as the food safety objective. To follow this last recommendation, the use of quantitative microbiological risk assessment is an appealing approach to link new risk‐based metrics to management options that may be applied by food operators. Through a specific case study, Listeria monocytogenes in soft cheese made from pasteurized milk, the objective of the present article is to practically show how quantitative risk assessment could be used to direct potential intervention strategies at different food processing steps. Based on many assumptions, the model developed estimates the risk of listeriosis at the moment of consumption taking into account the entire manufacturing process and potential sources of contamination. From pasteurization to consumption, the amplification of a primo‐contamination event of the milk, the fresh cheese or the process environment is simulated, over time, space, and between products, accounting for the impact of management options, such as hygienic operations and sampling plans. A sensitivity analysis of the model will help orientating data to be collected prioritarily for the improvement and the validation of the model. What‐if scenarios were simulated and allowed for the identification of major parameters contributing to the risk of listeriosis and the optimization of preventive and corrective measures.     

论苯教的宇宙观

本文运用大量文献资料,从空间观、时间观、自然观和生命观等方面对苯教的宇宙观做了介绍和分析。     

生命意识的悲歌——陶渊明诗文浅论

:陶渊明的“田园诗”隽永厚朴。但田园美景、隐逸风度只是他生活、创作的一部分。他蔑视官场 ,赞美田园的宁静之美 ,同时功名难就的悲哀始终萦绕心头而难以排解 ,现实与理想、时空与生命的矛盾冲突谱写了他苍凉悲愤的生命之歌     

Confidence intervals and bands for the binormal ROC curve revisited

Two types of confidence intervals (CIs) and confidence bands (CBs) for the receiver operating characteristic (ROC) curve are studied: pointwise CIs and simultaneous CBs. An optimized version of the pointwise CI with the shortest width is developed. A new ellipse-envelope simultaneous CB for the ROC curve is suggested as an adaptation of the Working-Hotelling-type CB implemented in a paper by Ma and Hall (1993). Statistical simulations show that our ellipse-envelope CB covers the true ROC curve with a probability close to nominal while the coverage probability of the Ma and Hall CB is significantly smaller. Simulations also show that our CI for the area under the ROC curve is close to nominal while the coverage probability of the CI suggested by Hanley and McNail (1982) uniformly overestimates the nominal value. Two examples illustrate our simultaneous ROC bands: radiation dose estimation from time to vomiting and discrimination of breast cancer from benign abnormalities using electrical impedance measurements.     

光照时间、CaO浓度和底质对大瓶螺（Ampullaria gigas）生长繁殖的影响

通过水族缸设置不同因子水平养殖大瓶螺，研究结果表明：光照时间对大瓶螺产卵量有极显著影响；CaO浓度、底质对雄螺的生长速度有显著影响。光照时间对雌螺产卵量起主导因子作用。每天光照时间为12h、CaO浓度为0.12g/L、底质为泥土时大瓶螺产卵量最大、生长速度最快。     

Wavelet fuzzy hybrid model for physico-financial signals

In the present paper, a fuzzy logic-based method is combined with wavelet decomposition to develop a step-by-step dynamic hybrid model to analyze and approximate one-dimensional physico-financial signals characterized by fuzzy values. Computational tests based on a well-known signal and conducted with the pure fuzzy model, the wavelet one and the new hybrid model, are developed and result in an efficient hybrid one.     

Testing for markov process vs semi-markov process

Here we have obtained a non-parametric test for testing the null hypothesis H₀ that the given realization is from a Markov process against the alternative hypothesis H₁ that it is from a semi-Markov process with the transition rate monotone increasing (or decreasing). We have shown that the test criterion has normal distribution asymptotically, and the test is consistent and unbiased.     

Semiparametric Bayesian accelerated failure time model with interval-censored data

Many existing approaches to analysing interval-censored data lack flexibility or efficiency. In this paper, we propose an efficient, easy to implement approach on accelerated failure time model with a logarithm transformation of the failure time and flexible specifications on the error distribution. We use exact inference for the Dirichlet process without approximation in imputation. Our algorithm can be implemented with simple Gibbs sampling which produces exact posterior distributions on the features of interest. Simulation and real data analysis demonstrate the advantage of our method compared to some other methods.