降水量变化对大气污染物浓度影响分析

系统分析了2001～2010年南通市城区中大气自动监测站和降水监测点位数据,得出:10年间逐年降水量与二氧化硫年均浓度呈现高度线性负相关,其它时空降水量与大气污染物浓度分布中呈现非线性显著性负相关。降水量大污染物浓度就小,反之就大。2006～2010年5年平均降水量1083.49mm,比2001～2005年5年平均降水量多出244.97mm,大气污染指标5年平均浓度下降幅度为:可吸入颗粒物0.013mg/m3、二氧化硫0.009mg/m3、二氧化氮无变化。10年的平均季度降水量夏季最大为467.97mm,对应的夏季大气污染物最小均值为:可吸入颗粒物0.073mg/m3、二氧化硫0.026mg/m3;10年平均季度降水量冬季最小为137.84mm,对应的冬季大气污染物季最大均值为:可吸入颗粒物为0.104mg/m3、二氧化硫0.034mg/m3和二氧化氮0.036mg/m3。     

负压隔离病房排风系统杀毒灭菌探讨

为了解决医护人员和传染病人交叉感染的问题;通过设计负压隔离病房空间布局及负压系统组成及参数,规划被呼吸道传染病人污染后空气的气流路线、处理设施及杀毒灭菌处理方法.该设计有效降低医护人员在呼吸道传染病人流动、治疗过程中的感染风险,为医护人员在流动和治疗过程中提供了很好的保护,降低了感染率.     

氟化物和总硬度分析项目相关性的检验

目前,通过中国实验室国家认可委员会的实验室,按照ISO/IEC17025:2005《校准和检测实验室能力通用要求》,都要制定并实施质量控制程序以监控检测和校准的有效性,所得数据的记录方式应便于可发现其发展趋势,如可行,应采用统计技术对结果进行审查。文章利用认可准则规定的五种方法中的一种方法,就分析一个物品不同特性结果的相关性,即利用某地下水水质的监测数据对氟化物、总硬度进行一元线性回归,检验其相关性是负相关,并建立了回归方程,绘制回归直线,充分验证了监测数据的有效性和可靠性,从而证明实验室利用的质量监控方法有效。     

Application of a hurdle negative binomial count data model to demand for bass fishing in the southeastern United States

This paper identifies factors that influence the demand for a bass fishing trip taken in the southeastern United States using a hurdle negative binomial count data model. The probability of fishing for a bass is estimated in the first stage and the fishing trip frequency is estimated in the second stage for individuals reporting bass fishing trips in the Southeast. The applied approach allows the decomposition of the effects of factors responsible for the decision to take a trip and the trip number. Calculated partial and total elasticities indicate a highly inelastic demand for the number of fishing trips as trip costs increase. However, the demand can be expected to increase if anglers experience a success measured by the number of caught fish or their size. Benefit estimates based on alternative estimation methods differ substantially, suggesting the need for testing each modeling approach applied in empirical studies.     

Investigation on the role of traffic volume in accidents on urban highways

Introduction

Roadway safety is a major concern for the general public and public agencies, as roadway crashes claim many lives and cause substantial economic loss each year. In Iran, a large number of vehicles are involved in road accidents each year, which cause many deaths and extensive property damage; such accidents are among the major causes of death and disability in the country. Method: To reduce roadway accidents, the factors that affect the occurrence and severity of accidents should be scrutinized to prevent or reduce their effect. The method that many researchers have adopted to determine the effective parameters surrounding road accidents in recent years is through statistical modeling of accidents. In this article, the role of different kinds of vehicles in traffic flow are investigated separately in terms of the likelihood of crashes on urban highways, and the vehicles are divided into three groups: passenger cars, heavy vehicles, and light non-passenger car vehicles. Poisson and negative binomial (NB) regression models were applied to model the accidents in this research, which were categorized into two groups: no injury (property damage only) accidents and more severe (injury and fatal) accidents. Results: Ultimately, we conclude that light non-passenger car vehicles (i.e., taxis and motorcycles) play the largest role in the occurrence of crashes on urban highways for both types of accidents.     

Detection of small leakage from long transportation pipeline with complex noise

In the long distance pipeline remote monitoring system, small leak detection becomes an important issue. Weak singularities in small leak signals are usually difficult to detect precisely under complicated noise background, which may cause false alarm or miss alarm. The advantage of applying the harmonic wavelet method is explored in this paper. Pipeline small leak sensitive characteristics are recognized and the negative pressure wave inflexions are extracted by harmonic wavelet analysis, expressed in terms of harmonic wavelet time-frequency mesh map, time-frequency contour map, and time-frequency profile plot. This paper also presents a comparative study of both Daubechies wavelet and harmonic wavelet analysis when applied to pipeline small leak detection under complicated background noises. Results of simulating test and field experiment show that it is possible to distinguish weak non-stationarities from complicated noises by harmonic wavelet analysis in pipeline small leak detection system. The comparison clearly illustrates that harmonic wavelet based pipeline small leakage detection method is significantly more accurate than other wavelets analysis such as Daubechies wavelet. This work provides a reliable and safe guarantee for oil and gas long distance transportation, reducing petroleum product losses and protecting surrounding environment.     

How much e-waste is there in US basements and attics? Results from a national survey

The fate of used electronic products (e-waste) is of increasing concern because of their toxicity and the growing volume of e-waste. Addressing these concerns requires developing the recycling infrastructure, but good estimates of the volume of e-waste stored by US households are still unavailable. In this context, we make two contributions based on a national random survey of 2136 US households. First, we explain how much e-waste is stored by US households using count models. Significant explanatory variables include age, marital and employment status, ethnicity, household size, previous e-waste recycling behavior, and to some extent education, home ownership, and understanding the consequences of recycling, but neither income nor knowledge of e-waste recycling laws. Second, we estimate that on average, each US household has 4.1 small (≤10 pounds) and 2.4 large e-waste items in storage. Although these numbers are likely lower bounds, they are higher than recent US Environmental Protection Agency (EPA) estimates (based on narrower product categories). This suggests that the backlog of e-waste in the US is likely larger than generally believed; it calls for developing the recycling infrastructure but also for targeted recycling campaigns.     

Data mining of tree-based models to analyze freeway accident frequency

INTRODUCTION: Statistical models, such as Poisson or negative binomial regression models, have been employed to analyze vehicle accident frequency for many years. However, these models have their own model assumptions and pre-defined underlying relationship between dependent and independent variables. If these assumptions are violated, the model could lead to erroneous estimation of accident likelihood. Classification and Regression Tree (CART), one of the most widely applied data mining techniques, has been commonly employed in business administration, industry, and engineering. CART does not require any pre-defined underlying relationship between target (dependent) variable and predictors (independent variables) and has been shown to be a powerful tool, particularly for dealing with prediction and classification problems. METHOD: This study collected the 2001-2002 accident data of National Freeway 1 in Taiwan. A CART model and a negative binomial regression model were developed to establish the empirical relationship between traffic accidents and highway geometric variables, traffic characteristics, and environmental factors. RESULTS: The CART findings indicated that the average daily traffic volume and precipitation variables were the key determinants for freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies. IMPACT ON INDUSTRY: By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies.     

负压在焦化生产过程中对煤气设备及容器损坏的探讨

在焦化生产过程中,煤气设备及容器内容易出现负压而造成设备损坏。本文对此类典型事故进行了分析。     

Simulating correlated count data

In this study we compare two techniques for simulating count-valued random n-vectors Y with specified mean and correlation structure. The first technique is to use a lognormal-Poisson hierarchy (L-P method). A vector of correlated normals Z is generated and transformed to a vector of lognormals X. Then, Y is generated as conditionally independent Poissons with means X _i . The L-P method is simple, fast, and familiar to many researchers. However, the method requires each Y _i to be overdispersed (i.e., σ² > μ), and only low correlations are possible with this method when the variables have small means. We develop a second technique to generate the elements of Y as overlapping sums (OS) of independent X _j ’s (OS method). For example, suppose X, X ₁, and X ₂ are independent. If Y ₁ = X + X ₁ and Y ₂ = X + X ₂, then Y ₁ and Y ₂ are correlated because they share the common component X. A generalized version of the OS method for simulating n-vectors of two-parameter count-valued distributions is presented. The OS method is shown to address some of the shortcomings of the L-P method. In particular, underdispersed random variables can be simulated, and high correlations are feasible even when the means are small. However, negative correlations cannot be simulated with the OS method, and when n > 3, the OS method is more complicated to implement than the L-P method.