天津市滨海新区湿地景观格局变化及驱动力分析

湿地是生态系统的重要组成部分,是人类最重要的生存环境之一。天津滨海新区拥有丰富的湿地资源,但近年来随着经济的发展,人类活动的增强及相关政策的执行,湿地资源受到严重威胁。为全面掌握滨海新区近年来的湿地景观格局动态变化历程,本文以1986年、1996年、2006年和2016年TM遥感影像为主要数据源,运用遥感等技术手段,对滨海新区近30年来湿地景观格局时空演化进行动态分析、质心分析及指数分析,并简要讨论了湿地景观变化的主要驱动因子。结果表明：近30年间滨海新区湿地退化情况严重,累计退化面积达524.762 km²,其中2006?—?2016年湿地面积减幅最大,高达407.947 km²,减少区域集中分布在环渤海地带的淤泥质沙滩和浅海水域,转化后类型以建设用地为主。景观动态分析及质心分析结果表明：景观整体变化特征为破碎度逐渐增强、景观形状日趋复杂、景观生态功能日益减弱、景观分布向均衡化发展,整体湿地质心不断向内陆推移。驱动力分析结果显示：经济发展、人口增长和政策调控等人为因素是该时期景观格局变化的主要驱动因素。     

基于灰色-马尔可夫藕合模型的区域建设用地需求预测

建设用地需求的中长期准确预测是当前土地资源规划和利用的重点和难点。本文将灰色和马尔可夫两种预测模型相结合,建立灰色-马尔可夫藕合模型,以广东省揭阳市为例,对1997到2010年间主要建设用地规模进行了需求预测,同时与其它几种常规的预测方法进行了比较。结果表明,人文驱动力相关预测法误差相对较大,其中国内生产总值(GDP)相关法准确度要优于人口相关法。趋势线法计算简单,预测准确度也相对较高,但只适于短期预测。灰色预测法精确度较高,计算需要模型的支持、专业性强。灰色-马尔可夫预测法由于是对灰色预测的偏离值进行了纠正,因而准确度最高。尽管该方法需要大量数据的支持,计算量大,但仍是值得推荐的高准确度的区域建设用地的专业预测方法。     

实施简易工况法排气检测若干问题探讨

国标GB18285-2005和GB3847-2005规定在用机动车的排气检测方法选择与简易工况法标准限值的制定均由地方根据实际情况确定,虽增强了地方排气监管工作灵活性,但困难也增加了.各地在推动实施简易工况法时,检测方法的选择应重点从地方管理、地方经济、技术条件和机动车排气监督管理发展方向进行综合考虑,条件许可的地方选用简易瞬态工况法.简易工况法的初始标准限值可以先选用HJ/T 240-2005和HJ/T241-2005两个行业标准中的最松限值,然后在推进简易工况法的过程中逐步收集检测数据,并重新确定地方的排放限值.     

基于OEM技术的机动车行驶周期的研究

介绍了一种利用车载尾气检测设备得到重复度高的实验数据的可行方法，并且对实际测试的结果进行了分析，对各种驾驶工况产生的排放影响进行了比较和区分。研究表明，利用车载尾气检测设备完全可以测试在过去只有在实验室内才可以测试的机动车行驶周期。     

鲁南经济带城乡绿色发展效率时空分异及驱动因素识别

城乡绿色发展效率对高效低耗绿色发展模式构建、社会经济可持续发展以及实现城乡互动融合具有重要意义。基于鲁南经济带35个县（市、区）13 a面板数据,综合采用DEA-Malmquist指数法、城乡绿色发展效率脱钩状态模型、地理探测器等多种计量模型,对2005—2017年鲁南经济带城乡绿色发展效率时空分异特征与驱动因素进行综合研究,结果表明：（1）技术进步是鲁南经济带绿色TFP增长的主要来源,但其贡献度不断下降,而纯技术效率与规模效率对于绿色TFP增长的促进作用逐年增强;（2）研究期内鲁南经济带绿色TFP增长具有空间分异性,绿色TFP的高效率区和次高效率区有向东北和西南地区集中的趋势;（3）鲁南经济带城乡绿色发展效率的脱钩关系出现反复,由负脱钩（耦合）到脱钩再到负脱钩,整体上城乡绿色发展处于动态变化与非协调（或低级耦合）阶段;（4）普通中学在校学生数、粮食产量、城乡居民储蓄存款余额是城乡绿色发展效率的高作用力影响指标,因子交互作用后对城乡绿色发展效率解释力远超单因子,反映出鲁南经济带城乡绿色发展效率的驱动因素具有复杂性特征。     

Sleepy driving and risk of obstructive sleep apnea among truck drivers in Saudi Arabia

Objective: Truck drivers represent a group at a particularly higher risk of motor vehicle accidents (MVAs). Sleepy driving and obstructive sleep apnea (OSA) among truck drivers are major risk factors for MVAs. No study has assessed the prevalence of sleepy driving and risk of OSA among truck drivers in Saudi Arabia. Therefore, this study aimed to assess sleepy driving and risk of OSA among these truck drivers.

Methods: This study included 338 male truck drivers working in Saudi Arabia. A validated questionnaire regarding sleepy driving and OSA was used. The questionnaire included sociodemographic assessment, the Epworth Sleepiness Scale (ESS), the Berlin Questionnaire (BQ), and driving-related items.

Results: The drivers had a mean age of 42.9?±?9.7 years. The majority (94.7%) drove more than 5?h a day. A history of MVAs during the last 6 months was reported by 6.5%. Approximately 95% of the participants reported that they had accidentally fallen asleep at least once while driving over the past 6 months, and 49.7% stated that this had happened more than 5 times during the last 6 months. Based on the BQ score, a high risk of OSA was detected in 29% of the drivers. “Not getting good-quality sleep” (odds ratio [OR]?=?2.89; 95% confidence interval [CI], 1.08–7.75; P = .014) and driving experience from 6 to 10 years (OR = 3.37; 95% CI, 1.28–8.91; P = .034) were the only independent predictors of MVAs in the past 6 months.

Conclusions: Sleepy driving and a high risk of OSA was prevalent among the study population of male truck drivers in Saudi Arabia. Not getting good-quality sleep and driving experience from 6 to 10 years contributes to the accident risk among these truck drivers.     

丹江口水库水体氮的时空分布及入库通量

为解析丹江口水库水体氮的时空分布特征及主要污染来源,以丹江口库区及主要入库河流为研究对象,分析了水体氮的空间分布、季节及年际变化;利用回归分析,解析了氮污染驱动因素;并估算了入库河流氮通量及对库区氮污染负荷的贡献率. 结果表明:研究区水体ρ(TN)、ρ(NH₄+-N)分别在0.07~16.73和0.01~10.65 mg/L之间,年均值分别为2.34和0.71 mg/L,空间分布呈入库河流高于库区的趋势;季节特征表现为春季、冬季>秋季>夏季. 2005—2014年库区水体ρ(TN)整体呈先升后降的趋势,其中取水口陶岔断面ρ(TN)上升较快,2012年较2007年增加了1.5倍,2013年开始ρ(TN)有所下降,但仍然维持在较高水平. 近10年来库区水体ρ(NH₄+-N)始终维持在较低水平. 神定河、犟河、泗河、剑河等环库支流河口氮污染最严重,城镇化是造成流域水体氮污染的主要驱动力. 汉江TN入库量贡献最大,占63.0%,其中境外来水TN入库量占总量的59.2%,为达到丹江口水库生态环境保护要求的Ⅲ类水质(GB 3838—2002《地表水环境质量标准》)目标,汉江TN需削减量为16 715.0 t/a. 境内河流中,环库河流的TN入库量最大,其中泗河、老灌河、神定河、金钱河、犟河和天河等TN入库量较大,TN需削减量分别为 2 286.7、2 197.7、1 493.6、1 106.9、979.1和728.9 t/a.      

The use and safety of medications known to affect driving in Jordan: A cross-sectional study

Objectives: The aim of this study was to estimate the main driving-impairing medications used by drivers in Jordan, the reported frequency of medication side effects, the frequency of motor vehicle crashes (MVCs) while using driving-impairing medicines, as well as factors associated with MVCs.

Methods: A cross-sectional study involving 1,049 individuals (age 18–75 years) who are actively driving vehicles and taking at least one medication known to affect driving (anxiolytics, antidepressants, hypnotics, antiepileptics, opioids, sedating antihistamines, hypoglycemic agents, antihypertensives, central nervous system [CNS] stimulants, and herbals with CNS-related effects) was conducted in Amman, Jordan, over a period of 8 months (September 2013–May 2014) using a structured validated questionnaire.

Results: Sixty-three percent of participants noticed a link between a medicine taken and feeling sleepy and 57% stated that they experience at least one adverse effect other than sleepiness from their medication. About 22% of the participants reported having a MVC while on medication. Multiple logistic regression analysis showed that among the participants who reported having a crash while taking a driving-impairing medication, the odds ratios were significantly higher for the use of inhalant substance (odds ratio [OR] = 2.787, P = .014), having chronic conditions (OR = 1.869, P = .001), and use of antiepileptic medications (OR = 2.348, P = .008) and significantly lower for the use of antihypertensives (OR = 0.533, P = .008).

Conclusion: The study results show high prevalence of adverse effects of medications with potential for driving impairment, including involvement in MVCs. Our findings highlight the types of patient-related and medication-related factors associated with MVCs in Jordan, such as inhalant use, presence of chronic conditions, and use of antiepileptics.     

Simulator study of young driver's instinctive response of lower extremity to a collision

Objective: A driver's instinctive response of the lower extremity in braking movement consists of two parts, including reaction time and braking reaction behavior. It is critical to consider these two components when conducting studies concerning driver's brake movement intention and injury analysis. The purposes of this study were to investigate the driver reaction time to an oncoming collision and muscle activation of lower extremity muscles at the collision moment. The ultimate goal is to provide data that aid in both the optimization of intervention time of an active safety system and the improvement of precise protection performance of a passive safety system.

Method: A simulated collision scene was constructed in a driving simulator, and 40 young volunteers (20 male and 20 female) were recruited for tests. Vehicle control parameters and electromyography characteristics of eight muscles of the lower extremity were recorded. The driver reaction time was divided into pre-motor time (PMT) and muscle activation time (MAT). Muscle activation level (A_COL) at the collision moment was calculated and analysed.

Results: PMT was shortest for the tibialis anterior (TA) muscle (243～317 ms for male and 278～438 ms for female). Average MAT of the TA ranged from 28-55 ms. A_COL was large (5～31% for male and 5～23% for female) at 50 km/h, but small (<12%) at 100 km/h. A_COL of the gluteus maximus was smallest (<3%) in the 25 and 100 km/h tests. A_COL of RF of men was significantly smaller than that of women at different speeds.

Conclusions: Ankle dorsiflexion is firstly activated at the beginning of the emergency brake motion. Males showed stronger reaction ability than females, as suggested by male's shorter PMT. The detection of driver's brake intention is upwards of 55ms sooner after introducing the electromyography. Muscle activation of the lower extremity is an important factor for 50 km/h collision injury analysis. For higher speed collisions, this might not be a major factor. The activations of certain muscles may be ignored for crash injury analysis at certain speeds, such as gluteus maximus at 25 or 100 km/h. Furthermore, the activation of certain muscles should be differentiated between males and females during injury analysis.     

The useful field of view assessment predicts simulated commercial motor vehicle driving safety

Objective: The Useful Field of View (UFOV) assessment, a measure of visual speed of processing, has been shown to be a predictive measure of motor vehicle collision (MVC) involvement in an older adult population, but it remains unknown whether UFOV predicts commercial motor vehicle (CMV) driving safety during secondary task engagement. The purpose of this study is to determine whether the UFOV assessment predicts simulated MVCs in long-haul CMV drivers.

Method: Fifty licensed CMV drivers (M_age = 39.80, SD = 8.38, 98% male, 56% Caucasian) were administered the 3-subtest version of the UFOV assessment, where lower scores measured in milliseconds indicated better performance. CMV drivers completed 4 simulated drives, each spanning approximately a 22.50-mile distance. Four secondary tasks were presented to participants in a counterbalanced order during the drives: (a) no secondary task, (b) cell phone conversation, (c) text messaging interaction, and (d) e-mailing interaction with an on-board dispatch device.

Results: The selective attention subtest significantly predicted simulated MVCs regardless of secondary task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC in the simulated drive. The e-mail interaction secondary task significantly predicted simulated MVCs with a 4.14 times greater risk of an MVC compared to the no secondary task condition. Subtest 3, a measure of visual speed of processing, significantly predicted MVCs in the email interaction task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC during the email interaction task.

Conclusions: The UFOV subtest 3 may be a promising measure to identify CMV drivers who may be at risk for MVCs or in need of cognitive training aimed at improving speed of processing. Subtest 3 may also identify CMV drivers who are particularly at risk when engaged in secondary tasks while driving.