基于轮廓似然函数的PM_(10)极值浓度分析

以R软件为分析工具,选择GEV(generalized extreme value distribution)模型拟合四川省泸州市2003～2007年期间PM10每月最高日平均浓度数据,采用极大似然法估计模型的3个参数即位置参数、尺度参数、形状参数,利用所得的参数估计值计算得出某一标准值(如GB3095—1996)的重现期;进一步利用参数估计值计算轮廓似然函数,估计某一段固定时间间隔的PM10浓度的重现值以及其置信区间。结果表明,GEV模型能很好地拟合泸州市PM10数据,利用轮廓似然函数估计的不同时间间隔的重现值准确度高,统计结果可以为环境主管部门发布污染状况预警信息提供参考。     

Seasonal variation of microbial populations and biomass in Tatachia grassland soils of Taiwan

To investigate the seasonal variations of microbial ecology in grassland of Tatachia forest, soil properties, microbial populations, microbial biomass, and 16S rDNA clone library analysis were determined. The soil had temperatures 6.6–18.4°C, pH 3.6–5.1, total organic carbon 1.11–10.68%, total nitrogen 0.18–0.78%, and C/N ratios 3.46–20.55. Each gram of dry soil contained bacteria, actinomycetes, fungi, cellulolytic, phosphate-solubilizing microbes, and nitrogen-fixing microbes 4.54 × 10⁴ to 3.79 × 10⁷, 3.43 × 10² to 2.17 × 10⁵, 5.74 × 10³ to 3.76 × 10⁶, 1.97 × 10³ to 1.34 × 10⁶, 8.49 × 10² to 5.59 × 10⁵, and 3.86 × 10² to 3.75 × 10⁵ CFU, respectively. Each gram of soil contained 117–2,482 μg of microbial biomass carbon, 23–216 μg of microbial biomass nitrogen and 9–29 μg of DNA. The microbial populations, microbial biomass, and DNA decreased stepwise with the depth of soil, and they had low values in winter seasons. The microbial populations, microbial biomass carbon, microbial biomass nitrogen, and DNA at the BW2 horizon were 8.42–17.84, 19.26–64.40, 16.84–61.11, and 31.03–46.26% of those at the O horizon, respectively. When analyzing 16S rDNA library, members of Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, candidate division TM1, candidate division TM7, Gammatimonadetes, and Verrucomicrobia were identified. Members of Proteobacteria (44.4%) and Acidobacteria (33.3%) dominated the clone libraries. Within the phylum Proteobacteria, α-, β-, and γ-Proteobacteria were most numerous, followed by δ-Proteobacteria.     

Confidence intervals for the mean of the delta-lognormal distribution

Data that are skewed and contain a relatively high proportion of zeros can often be modelled using a delta-lognormal distribution. We consider three methods of calculating a 95% confidence interval for the mean of this distribution, and use simulation to compare the methods, across a range of realistic scenarios. The best method, in terms of coverage, is that based on the profile-likelihood. This gives error rates that are within 1% (lower limit) or 3% (upper limit) of the nominal level, unless the sample size is small and the level of skewness is moderate to high. Our results will also apply to the delta-lognormal linear model, when we wish to calculate a confidence interval for the expected value of the response variable, given the value of one or more explanatory variables. We illustrate the three methods using data on red cod densities, taken from a fisheries trawl survey in New Zealand.

Do farmers need relief seed? A methodology for assessing seed systems

This article outlines a methodology to help agencies better determine whether or not relief seed is needed by farmers affected by disaster. A brief review of current seed needs assessment procedures in southern Somalia and Mozambique illustrates problems of knowing which crops and households are affected, the importance of seed access (not just availability) and the need to plan interventions earlier than at present. The development of a Seed Systems Profile (SSP) is proposed to understand better both the socio-economic and agro-ecological aspects of farmers' seed systems. A five-step framework for assessing seed systems in disaster situations is also presented. These tools are currently being tested and further refined in Mozambique. A better understanding of farmers' seed systems will allow for the development of relief and rehabilitation interventions that effectively enhance the resilience and reduce the vulnerability of these systems.     

Ion Composition Elucidation (ICE): an Investigative Tool for Characterization and Identification of Compounds of Regulatory Importance

Ion composition elucidation (ICE) often leads to identification of compounds and provides high-quality evidence for tracking compounds to their sources. Mass spectra for most organic compounds are not found in mass spectral libraries used to tentatively identify analytes. In addition, multiple matches are common. Ion Composition Elucidation provides the numbers of atoms of each element in the ions in the mass spectrum, greatly limiting the number of possible compounds that could produce the mass spectrum. Review of chemical and commercial literature then limits the number of possible compounds to one or a few that can be purchased to confirm tentative compound identifications by comparison of mass spectra and chromatographic retention times. Ion composition elucidation is conceptually simple relative to other analytical techniques and more easily explained to a judge or jury. It is based on sums of the exact masses of atoms and their isotopic abundances. Several applications of ICE are demonstrated for ultra-trace-level compounds in an extract of the e.uent from a tertiary sewage treatment plant including: (1) measurement of five values to determine an ion's composition and to generate evidence for the compound's identity, (2) rejection of incorrect library matches, (3) rapid screening for a target compound in an extract, and (4) a strategy for tracking unidentified compounds to their sources.     

Aggressive driving: a survey of attitudes, opinions and behaviors

INTRODUCTION: Aggressive driving encompasses a continuum of behaviors that range from extreme acts, such as shootings, to less severe manifestations, such as arguments and gestures. It is clear from the available data that aggressive driving is not uncommon and very risky. However, little is known about the opinions and practices of drivers. The purpose of this study was to help bridge these gaps. METHODS: The data were gathered by means of a public opinion poll among a representative sample of 1,201 Canadian drivers. Univariate frequency distributions and 95% confidence intervals were calculated and logistic regression and generalized linear latent models were used to summarize the data. RESULTS: It was found that the issue of aggressive driving is a significant one as a considerable percentage of drivers admits to it. The results coming from the logistic regression and the generalized linear latent model suggest that male and younger drivers are more likely to behave aggressively in traffic and that behaving more aggressively is associated with a history of traffic tickets. DISCUSSION: When gauging people's attitudes, opinions, and behaviors, it becomes clear that aggressive driving is a considerable problem. There also seems to be a need for a better understanding of which specific behaviors respondents associate with the generic term "aggressive driving." IMPACT ON INDUSTRY: Results from this study further emphasize the need of increasing the aggressive driving knowledge base.     

吉阳核电厂址近地面层温度梯度及风廓线规律适用性研究

观测安徽吉阳核电厂址近地面层的气象数据,对该厂址近地面层温度梯度及风廓线规律的适用性进行了分析,通过散点图的形式寻找风速比随稳定度参数的变化特征。结果表明,本区气温日变化符合一般观测规律,四季平均气温有较大差异、温差偏大,春夏两季多易出现逆温,春冬逆温强度较夏季偏大;非中性层结条件下风速比值随稳定度的增强而离散增大。     

铁路工程设计践行绿色发展的实践

设计是铁路工程绿色发展的关键环节之一,以某铁路工程为例,在阐述工程概况和主要问题的基础上,从线路纵断面、辅助坑道、隧道弃渣综合利用、弃土(渣)场数量及取土场数量等方面进行优化设计,并对优化效果进行分析。