样方形状对空间点格局的性能影响分析——以天目山阔叶林为例

利用浙西天目山常绿阔叶林样地调查数据,在随机样方点格局分析基础上,提出样方形状对点格局分析性能影响差异性问题。结果表明:(1)在最优样方面积相同条件下,通过配对t检验得出圆形与正方形、圆形与正六边形和正方形与正六边形样方性能对比的配对t检验概率P分别为0.249、0.043和0.023,表明样方形状对点格局分析性能影响具有差异性,圆形样方和正方形样方之间没有显著差异,正六边形样方与圆形样方、正方形样方之间差异显著;(2)圆形～正六边形和正方形～正六边形样方间VMR差值的95%置信区间分别为[-0.429,-0.010]和[-0.196,-0.021],其区间值上界均小于0,表明正六边形样方分析性能为最优,其性能高于圆形样方和正方形样方;(3)随机样方法在样本量较小时,点格局分析结果不稳定,但随着采样数目逐步增大到90以上时,其VMR值和P值趋于稳定。

Prevalence and risk factors of gastroesophageal reflux disease in Qashqai migrating nomads, southern Iran

AIM： To investigate the prevalence and risk factors of gastroesophageal reflux disease （GERD） symptoms in Qashqai migrating nomads with a different life style in Fars province, southern Iran. METHODS： In summer 2006, 748 Qashqai migrating nomads aged 25 years or more were enrolled using a multiple-stage stratified cluster random sampling method. A questionnaire consisting of demographic characteristics, lifestyle and GERD symptoms （heartburn, regurgitation, chest pain, dysphagia, hoarseness and cough） as completed for each subject. RESULTS： The questionnaire was completed in 717 subjects. The prevalence rate of GERD, defined as reflux occurring at least one time per week in the preceding year, was 33% （237 subjects）. The prevalence was higher in older individuals （36.0% vs 28.9%, P 〈 0.05） and in those with other gastrointestinal complaints （51.0% vs 27.8%, P 〈 0.001）, but not different in obese and non-obese subjects. It was also higher in those consuming fruits and vegetables more than once a week （36.2% vs 17.3%, P 〈 0.001）. GERD had a positive correlation with smoking （42.1% vs 27.8%, P 〈 0.001）, but a negative relation with non-alcoholic beverages. The association between GERD and non-steroidal antiinflammatory drugs （NSAIDs） consumption was also significant （40.2% vs 25.4%, P 〈 0.001）. CONCLUSION： The prevalence of GERD （33%） is very high in Qashqai migrating nomads which may be due to a lower socioeconomic and educational level of these people and difference in the life style. Older age, frequent consumption of fruits and vegetables, smoking and NSAIDs are risk factors for GERD in this population.

General Classes of Variance Estimators in Simple Random Sampling Using Multi-auxiliary Variables

Srivastava and Jhajj [ 1 6] proposed a class of estimators for estimating population variance using multi auxiliary variables in simple random sampling and they utilized the means and variances of auxiliary variables. In this paper, we adapted this class and motivated by Searle [13], and we suggested more generalized class of estimators for estimating the population variance in simple random sampling. The expressions for the mean square error of proposed class have been derived in general form. Besides obtaining the minimized MSE of the proposed and adapted class, it is shown that the adapted classis the special case of the proposed class. Moreover, these theoretical findings are supported by an empirical study of original data.

Exploring the relationship of physical exercise situations, attitude and intensity with middle school students＇ shame

In order to explore the relationship between physical exercises and the feeling of shame, 1258 Shanghai middle school students are surveyed with the help of the middle school students＇ shame measurement scale with the combination of delaminating and random sampling. The results of questionnaire show that the feeling of shame is closely related with the scene of physical exercises, the extent students like physical exercises and the intensity they take exercises, which provide methodological support for the remission of the shame of middle school students with physical exercise.

吉林蛟河42hm^2针阔混交林样地植物种-面积关系

种-面积关系是生态学中的基本问题,其构建方式对种-面积关系的影响以及最优种-面积模型的选择仍然存在争议。该文利用吉林蛟河42hm2针阔混交林样地数据,分别采用巢式样方法和随机样方法建立对数模型、幂函数模型和逻辑斯蒂克模型,并通过赤池信息量准则(AIC)检验种-面积模型优度。结果表明,种-面积关系受到取样方法的影响,随机样方法的拟合效果优于巢式样方法。采用随机样方法构建的幂指数模型(AIC=89.11)和逻辑斯蒂克模型(AIC=71.21)优于对数模型(AIC=113.81)。根据AIC值可知,随机样方法构建的逻辑斯蒂克模型是拟合42hm2针阔混交林样地种-面积关系的最优模型。该研究表明:在分析种-面积关系时不仅应考虑尺度效应,还需注意生境变化及群落演替的影响。

A Pseudo Random Number Generator under Windows Using Refined Descriptive Sampling

In this paper, we propose a software component under Windows that generates pseudo random numbers using RDS （Refined Descriptive Sampling） as required by the simulation. RDS is regarded as the best sampling method as shown in the literature. In order to validate the proposed component, its implementation is proposed on approximating integrals. The simulation results from RDS using ＂RDSRnd＂ generator were compared to those obtained using the generator ＂Rnd＂ included in the Pascal programming language under Windows. The best results are given by the proposed software component.

A random adaptive method to adjust MAC parameters in IEEE802.11e WLAN

The IEEE 802.11e standard is proposed to provide QoS support in WLAN by providing prioritized differentiation of traffic. Since all the stations in the same priority access category (AC) have the same set of parameters, when the number of stations increases, the probability of different stations in the same AC choosing the same values will increase, which will result in collisions. Random adaptive MAC (medium access control) parameters scheme (RAMPS) is proposed, which uses random adaptive MAC differentiation parameters instead of the static ones used in the 802.11e standard. The performance of RAMPS is compared with that of enhanced distributed coordination access (EDCA) using NS2. The results show that RAMPS can reduce collision rate of the AC and improve the throughput by using adaptive random contention window size and inter-frame spacing values. RAMPS ensures that at any given time, several flows of the same priority have different MAC parameter values. By using the random offset for the inter-frame spacing value and the backoff time, RAMPS can provide intra-AC differentiation. The simulation results show that RAMPS outperforms EDCA in terms of both throughput and end-to-end delay irrespective of the traffic load.

Applications of the representative points in statistical simulations

The paper gives a new approach to statistical simulation and resampling by the use of numbertheoretic methods and representative points. Resempling techniques take samples from an approximate population. The bootstrap suggests to use a random sample to form an approximate population. We propose to construct some approximate population distribution by the use of two kinds of representative points, and samples are taken from these approximate distributions. The statistical inference is based on those samples. The statistical inference in this paper involves estimation of mean, variance, skewness, kurtosis, quantile and density of the population distribution. Our results show that the new method can significantly improve the results by the use of Monte Carlo methods.