Simulation techniques for generalized Gaussian densities

This contribution deals with the Monte Carlo simulation of generalized Gaussian random variables. Such a parametric family of distributions has been proposed in many applications in science to describe physical phenomena and in engineering, and it seems to be also useful in modelling economic and financial data. For values of the shape parameter α within a certain range, the distribution presents heavy tails. In particular, the cases α=1/3 and α=1/2 are considered. For such values of the shape parameter, different simulation methods are assessed.     

试论环境约束下的江苏省重工业发展之路

本文对江苏省主要重工业污染排放情况进行了因素分解,考察了江苏省的地方政策在重工业行业污染控制方面的有效性,并分析了污染控制目标下的经济效益,以期为产业政策的调整提供依据。     

Robust Bayesian nonlinear mixed‐effects modeling of time to positivity in tuberculosis trials

Early phase 2 tuberculosis (TB) trials are conducted to characterize the early bactericidal activity (EBA) of anti‐TB drugs. The EBA of anti‐TB drugs has conventionally been calculated as the rate of decline in colony forming unit (CFU) count during the first 14 days of treatment. The measurement of CFU count, however, is expensive and prone to contamination. Alternatively to CFU count, time to positivity (TTP), which is a potential biomarker for long‐term efficacy of anti‐TB drugs, can be used to characterize EBA. The current Bayesian nonlinear mixed‐effects (NLME) regression model for TTP data, however, lacks robustness to gross outliers that often are present in the data. The conventional way of handling such outliers involves their identification by visual inspection and subsequent exclusion from the analysis. However, this process can be questioned because of its subjective nature. For this reason, we fitted robust versions of the Bayesian nonlinear mixed‐effects regression model to a wide range of TTP datasets. The performance of the explored models was assessed through model comparison statistics and a simulation study. We conclude that fitting a robust model to TTP data obviates the need for explicit identification and subsequent “deletion” of outliers but ensures that gross outliers exert no undue influence on model fits. We recommend that the current practice of fitting conventional normal theory models be abandoned in favor of fitting robust models to TTP data.     

Campylobacter QMRA: A Bayesian Estimation of Prevalence and Concentration in Retail Foods Under Clustering and Heavy Censoring

A Bayesian statistical temporal‐prevalence‐concentration model (TPCM) was built to assess the prevalence and concentration of pathogenic campylobacter species in batches of fresh chicken and turkey meat at retail. The data set was collected from Finnish grocery stores in all the seasons of the year. Observations at low concentration levels are often censored due to the limit of determination of the microbiological methods. This model utilized the potential of Bayesian methods to borrow strength from related samples in order to perform under heavy censoring. In this extreme case the majority of the observed batch‐specific concentrations was below the limit of determination. The hierarchical structure was included in the model in order to take into account the within‐batch and between‐batch variability, which may have a significant impact on the sample outcome depending on the sampling plan. Temporal changes in the prevalence of campylobacter were modeled using a Markovian time series. The proposed model is adaptable for other pathogens if the same type of data set is available. The computation of the model was performed using OpenBUGS software.     

A new heavy-tailed distribution defined on the bounded interval: the logit slash distribution and its application

This paper proposes a new heavy-tailed and alternative slash type distribution on a bounded interval via a relation of a slash random variable with respect to the standard logistic function to model the real data set with skewed and high kurtosis which includes the outlier observation. Some basic statistical properties of the newly defined distribution are studied. We derive the maximum likelihood, least-square, and weighted least-square estimations of its parameters. We assess the performance of the estimators of these estimation methods by the simulation study. Moreover, an application to real data demonstrates that the proposed distribution can provide a better fit than well-known bounded distributions in the literature when the skewed data set with high kurtosis contains the outlier observations.     

铜、镉、汞对水稻幼苗抗氧化酶活性的影响

目的:研究必需元素Cu2+和非必需元素Cd2+、Hg2+对水稻幼苗生长的影响,探讨水稻抵抗重金属毒害的机理.方法:用质量浓度为0.25 mmol/L、0.5 mmol/L、1.0 mmol/L重金属离子溶液滴灌水稻幼苗,测定处理后幼苗根和叶的长度,蛋白质和叶绿素含量,过氧化氢酶、超氧化物歧化酶和过氧化物酶活性及过氧化物酶和超氧化物歧化酶同工酶的表达变化.结果:重金属离子抑制水稻幼苗生长,降低幼苗根和叶可溶性蛋白含量,增强了根、叶POD活性和根系SOD活性;Cu2+增强幼苗叶SOD活性,而Cd2+和Hg2+抑制幼苗叶SOD活性.不同浓度Cd2+降低水稻幼苗叶绿素含量;不同浓度Hg2+降低幼苗根和叶CAT活性;Cd2+增强根CAT活性,但抑制叶CAT活性;随着Cu2+浓度增大而逐渐减弱根和叶CAT活性.POD与SOD同工酶电泳结果与其活性检测相一致.结论:Cu2+、Cd2+、Hg2+处理对水稻幼苗POD、SOD和CAT活性的影响与重金属种类和浓度有关并存在器官特异性.水稻幼苗表现出抗氧化活性增加和减少两种情况,说明抗氧化系统不仅具有解毒功能,同时还是Cd2+、Cu2+和Hg2+对植物产生毒性的作用位点.     

我国工业重工化对经济增长影响的实证分析

近些年来,我国出现了重新重工业化的趋势,重工业在我国经济中发挥着特殊重要的作用.采用1981-2006年的数据,在单位根检验、协整检验和格兰杰因果关系检验的基础上建立了误差修正模型,以此说明我国重工业与经济增长的长期均衡的正向关系和短期动态关系,指出我国应大力发展重工业,走一条新型工业化的道路.     

先秦的“法治”思想和实践考量

先秦法家在与儒家“礼治”的争论中提出“法治”思想,并与战国时期富国强兵的国家策略结合,变法图存的“法治”实践此起彼伏。其中最为成功的是秦国的商鞅变法,秦国由此迅速崛起并最终吞并六国,建立起统一的封建国家。秦帝国的建立是“法治”思想和实践的里程碑,大秦将集权专制和“法治”相互糅合,将法家重刑思想发展到极端,走向了崇尚暴力和滥刑滥杀的野蛮恐怖境地,导致天下怨叛,秦王朝二世而亡,君权至上最终将法治引向了集权专制的死胡同。     

审美现代性视野中的米兰·昆德拉

与卡林内斯库的审美现代性理论不同,米兰·昆德拉提出的“欧洲小说”观念,是以审美现代性对抗“资产阶级的现代性”的源头所在。米兰·昆德拉在小说理论和创作实践中展现出了对资产阶级的启蒙现代性的批判,和对审美现代性立场的坚执中产生的反省,阐述了他独特的“欧洲小说观”与审美现代性起源新说。他站在小说家的立场上,以审美现代性的态度,审视和评判现代生活,深入地考察了现代人生存中的一系列现象：媚俗,舞者,轻与重,快与慢,记忆与遗忘,革命、鸟托邦与抒情姿态,等等,犀利地揭示出其中的现代性悖谬。     

稠油油藏注蒸汽储层热伤害规律实验研究

针对稠油油藏注蒸汽过程中储层的热伤害问题，研究了稠油油藏热采过程注入的高温、高pH 热流体对储层 渗透率的影响，研究中利用正反向流动实验方法，研究了高温冷凝液注入疏松砂岩后引起的微粒运移作用及储层渗透 率的变化特征；并利用储层矿物的水热反应实验，分析了疏松砂岩油藏注蒸汽开发过程中的微粒运移机理。实验结果 表明，注蒸汽过程中，稠油油藏储层渗透率随温度及pH 值的升高而降低。高速流动的蒸汽及冷凝液造成储层内固相 微粒的运移及滞留，使储层非均质性进一步加剧；同时，高温、高pH 的蒸汽冷凝液既促使黏土矿物发生膨胀又造成储 层矿物发生溶解与转化，从而进一步加剧了稠油油藏疏松砂岩储层的储层热伤害。