建设项目竣工环境保护验收监测报告编写的几点体会

根据多年工作经验,提出了验收报告中常见的监测数据缺乏逻辑性,数据的合理性经不起推敲等问题。认为验收报告编写应注重基础资料的真实性和污染治理效果的真实性。     

陕北竞技体育人力资源现状与开发对策研究

采用文献资料法,问卷调查法,统计法,从"省运会"、"全运会"、"国际大赛"3个层面,对陕北竞技体育的实力现状进行分析;从数量和质量两个角度探讨陕北竞技体育人力资源的乐观面与存在的问题,提出开发人力资源的对策.     

浅析求解最大子段和问题的算法

用计算机解决复杂的问题,往往把一个大的、复杂的问题根据其功能划分为不同的模块,每一个模块完成一独立的功能.如果每一个模块用计算机语言来实现,那么当所有模块都实现时,即为对复杂问题的解决.最大子段和问题就是一具有独立功能的小模块,在很多大的问题中都涉及到此问题,用不同的算法解决此问题,并分析其优劣.     

珠江流域下游地区降水空间分布规律研究

剧烈人类活动和全球气候持续变化双重影响下流域水文气象要素特征研究是目前水文水资源领域热点问题之一。论文以珠江流域下游地区为研究区域,根据该地区125个雨量观测站1956—2005年50 a逐月降水资料,利用信息论中有向信息传输指数定量分析各观测站点之间降水的信息传递,并结合聚类分析方法判断各观测站的所属关系,研究珠江流域下游地区降雨的空间分布规律。研究表明:受地形条件和沿海季风气候的共同作用,珠江流域下游地区降水具有自相似性特点,在空间分布上存在7个相似区域。     

Determination of N-nitrosodimethylamine in drinking water by UPLC-MS/MS

The method for detecting N-nitrosodimethylamine (NDMA) in drinking water using ultra performance liquid chromatography (UPLC) coupled with tandem mass spectrometry (MS/MS) was improved by optimizing the clean-up procedure to remove the matrix interference in pretreatment process, and was then applied to a survey of NDMA in both raw and finished water samples from five water treatment plants in South China. The NDMA concentrations ranged from 4.7 to 15.1 ng/L in raw water samples, and from 4.68 to 46.9 ng/L in finished water. The NDMA concentration in raw water was found to be related with nitrite concentration, and during the treatment, the NDMA concentration increased following ozonation but decreased after subsequent activated carbon treatment.     

粪大肠菌群测定中的实验室质量控制研究

对在粪大肠菌群实验过程中涉及到的实验室质控设备、培养基、精密度检验等内容进行了分析,并对实验过程中的关键问题进行了阐述。     

UV-B辐射增强对壶状臂尾轮虫种群增殖的影响

运用群体累计培养的方法研究了UV-B辐射增强对壶状臂尾轮虫(Brachionus urceus)种群增殖的影响.结果表明:UV-B辐射增强对壶状臂尾轮虫的种群数量、雌体抱卵率和种群增殖率都有显著影响(P<0.05).实验表明,在本实验辐射强度(20μW/cm2)和剂量范围内(0.24、0.48、0.72、0.96和1.20kJ/m2),壶状臂尾轮虫的种群数量和种群增殖率均以对照组最高,各UV-B辐射处理组则随UV-B辐射剂量的增大而呈一致性减小,说明该种群的种群数量和种群增殖率随UV-B辐射的增强显示一致性的影响,两者都可以作为大气UV-B辐射强弱的生物指标.     

层次分析法在消防部队灭火救援战斗力评估中的应用

在研究消防专家测评和问卷抽样调查的基础上,建立了消防部队灭火救援战斗力评估指标体系,运用层次分析法确定了各指标的权重以及相应的评估模型,并通过实例计算,证明了该方法的可行性,为科学、有效地建设和管理消防部队、合理规范部队编制、不断发展和提高其作战力提供了依据.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data

Introduction: Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e., with a blood alcohol concentration (BAC) of 80 mg/dL or higher) committed by motorcyclists and car drivers. Methods: A total of 10,457 motorcycle DUIs and 8,402 car DUIs were compared using a series of logistic regression models, using data extracted from the documents of adjudication decisions by the courts of Jiangsu, China. Results: The results revealed that offenders from the high-BAC group (i.e., 200 mg/dL or higher) accounted for more than 20% of the total DUI offenses, and were more likely to be involved in a crash and punished with a longer detention. Motorcyclists had a higher likelihood of crash involvement, and were also more likely to be responsible for single-vehicle crashes associated with higher odds of injury sustained, compared to alcohol-impaired car drivers. In the verdict, motorcycle offenders were more likely to receive a less severe penalty. Conclusions: Interventions are clearly required to focus on reducing in the high-BAC group of offenders. For alcohol-impaired motorcyclists, their risks of crash and injury against BAC climb more steeply than the risks for car drivers. The factors including frequent occurrences, uncertainty of detection, and short-term sentences may weaken the deterrence effect of the criminalization of motorcycle DUI. Practical Applications: The traffic-related adjudication data support traffic safety analysis. Strategies such as combating motorcycle violations (e.g., unlicensed operators or driving unsafe vehicles), undertaking education and awareness campaigns, are expected for DUI prevention.