门控核素心血池显像测定左心功能的临床意义

目的　应用门控核素心血池显像检测手段对临床心功能状态的判断提供一客观、准确的量化指标。方法　选取我院 393例因各种心脏疾病行门控核素心血池检查住院患者 ,用SPOPHYDS7型SPECT ,FRANKFURT门处理程序 ,获得左室各功能参数 ,依据WHO心功能分级标准 ,将心功能分为 1～ 4级。结果　临床心功能不同级别间心血池显像所获各指标值明显不同 ,心功能 1～ 4级 ,GEF、PER、PFR呈依次减低趋势 ,EDV及PS依次增大 ;GEF值小于 36%时心功能处于失代偿期者占 71 3% ,当GEF值小于 2 6%时多数心功能处于 3～ 4级 ,当GEF值为 2 6%～ 35%时 ,心功能多处于 2～ 3级 ,当GEF值大于 36%时心功能多处于 1～ 2级。同时表明 :心血池显像所获各项参数之间相关非常显著 ,且与临床心功能分级的相关性良好 ,依次为EDV、GEF、PER、PFR、PS。结论　核素心血池显像所获各项参数能够直接、客观、准确反映出临床心功能状态 ,同时提供室壁运动、相位分析等其他指标     

信息化环境下中职汽车实训课堂传承工匠精神的实践

随着科学技术的不断发展,中职汽车教学内容正发挥着越来越重要的作用。在信息化环境的背景下,传统的中职实训课堂已经无法满足学生和教师学习的需要,因此将工匠精神融入在内显得越来越重要。本文重点分析在信息化环境下中职汽车实训课堂传承工匠精神的实践策略。     

Impact of government incentives on the market penetration of electric vehicles in Australia

Incentives to buy and use electric vehicles (EVs) may influence individuals’ decisions to do so. To examine these impacts, a latent class discrete choice model is developed to analyse consumer preferences related to EV attributes and related government incentives. Data was collected from a stated preference survey of 1,076 residents of New South Wales (NSW), Australia. According to the results, the proposed latent constructs classify respondents into five segments. The segments are then used to distinguish respondent behaviours regarding EV attributes and related government incentives. The results show that rebate on the upfront cost of an EV is the most preferred one-off financial incentive, because EVs are expected to be expensive, especially in Australia which has a very small EV market at present. Furthermore, rebates on energy bills and parking fees are also well-received, as these things are expensive in Sydney, Australia. Thus, operational incentives for discounts on energy bills and parking fees may facilitate the success of EVs in NSW.     

Spatio-temporal analysis of car distance,greenhouse gases and the effect of built environment: A latent class regression analysis

This work examines the temporal–spatial variations of daily automobile distance traveled and greenhouse gas emissions (GHGs) and their association with built environment attributes and household socio-demographics. A GHGs household inventory is determined using link-level average speeds for a large and representative sample of households in three origin–destination surveys (1998, 2003 and 2008) in Montreal, Canada. For the emission inventories, different sources of data are combined including link-level average speeds in the network, vehicle occupancy levels and fuel consumption characteristics of the vehicle fleet. Urban form indicators over time such as population density, land use mix and transit accessibility are generated for each household in each of the three waves. A latent class (LC) regression modeling framework is then implemented to investigate the association of built environment and socio-demographics with GHGs and automobile distance traveled. Among other results, it is found that population density, transit accessibility and land-use mix have small but statistically significant negative impact on GHGs and car usage. Despite that this is in accordance with past studies, the estimated elasticities are greater than those reported in the literature for North American cities. Moreover, different household subpopulations are identified in which the effect of built environment varies significantly. Also, a reduction of the average GHGs at the household level is observed over time. According to our estimates, households produced 15% and 10% more GHGs in 1998 and 2003 respectively, compared to 2008. This reduction can be associated to the improvement of the fuel economy of vehicle fleet and the decrease of motor-vehicle usage – e.g., a decrease of 4% is observed for fuel efficiency rates and 12% for distance according to the raw average estimates from 1998 with respect to 2008. A strong link is also observed between socio-demographics and the two travel outcomes. While number of workers is positively associated with car distance and GHGs, low and medium income households pollute less than high-income households.     

Estimation of mean and covariance of stochastic multi-class OD demands from classified traffic counts

This paper proposes a new model to estimate the mean and covariance of stochastic multi-class (multiple vehicle classes) origin–destination (OD) demands from hourly classified traffic counts throughout the whole year. It is usually assumed in the conventional OD demand estimation models that the OD demand by vehicle class is deterministic. Little attention is given on the estimation of the statistical properties of stochastic OD demands as well as their covariance between different vehicle classes. Also, the interactions between different vehicle classes in OD demand are ignored such as the change of modes between private car and taxi during a particular hourly period over the year. To fill these two gaps, the mean and covariance matrix of stochastic multi-class OD demands for the same hourly period over the year are simultaneously estimated by a modified lasso (least absolute shrinkage and selection operator) method. The estimated covariance matrix of stochastic multi-class OD demands can be used to capture the statistical dependency of traffic demands between different vehicle classes. In this paper, the proposed model is formulated as a non-linear constrained optimization problem. An exterior penalty algorithm is adapted to solve the proposed model. Numerical examples are presented to illustrate the applications of the proposed model together with some insightful findings on the importance of covariance of OD demand between difference vehicle classes.     

浅谈高职院校大学新生班级管理

大学校园，是大学生正确树立世界观、人生观和价值观的主要场所，是高校培养人才的主要阵地。随着高职院校的扩招，每年新生的到来，都为学校注入了新鲜血液。但不可避免的，新生入校后对新环境多方面的不适应，再加上学生素质参差不齐，给学校及班级管理带来了很大的难度。文中通过新生的特点及班级管理存在的问题，探讨班级管理的一些措施及建解...     

The influence of attitude towards individuals’ choice for a remotely piloted commercial flight: A latent class logit approach

The Remotely Piloted Commercial Passenger Aircraft Attitude Scale (RPCPAAS) was created to measure positive and negative attitudes towards a new and plausible form of air travel. This information was then used, in combination with a latent class logit model built on data generated from a stated choice experiment to gain insight into the choice behaviour between conventionally piloted aircraft (CPA) with a pilot on-board and remotely piloted aircraft (RPA) with a pilot on the ground. The results revealed that individuals, on-average, if presented a choice between a CPA and a RPA of equivalent attributes, would elect for the CPA option. However, there is variability in the passengers’ sensitivity to various flight attributes, and these sensitivities were influenced by individuals’ attitude towards the new technology (i.e., RPA). From an operational perspective, and assuming that one day passengers of commercial airlines are offered the choice between CPA and RPA, the strategies employed by airlines to encourage the use of the new technology need to be different, based on individuals’ attitude towards RPA.     

基于“现代学徒制”理念的建筑工程技术人才培养模式探究

高等职业教育培养的学生应是"高技能"人才,而目前就业学生却难以满足企业的技能需求,"现代学徒制"人才培养模式加强了企业的介入和学生职业技能的培养。文中从培养高职建筑工程技术人才角度出发,在扩大招生对象、扩充授课教师队伍、改进授课模式等方面,进行了有效的探讨。     

Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany

In the light of European energy efficiency and clean air regulations, as well as an ambitious electric mobility goal of the German government, we examine consumer preferences for alternative fuel vehicles (AFVs) based on a Germany-wide discrete choice experiment among 711 potential car buyers. We estimate consumers’ willingness-to-pay and compensating variation (CV) for improvements in vehicle attributes, also taking taste differences in the population into account by applying a latent class model with 6 distinct consumer segments. Our results indicate that about 1/3 of the consumers are oriented towards at least one AFV option, with almost half of them being AFV-affine, showing a high probability of choosing AFVs despite their current shortcomings. Our results suggest that German car buyers’ willingness-to-pay for improvements of the various vehicle attributes varies considerably across consumer groups and that the vehicle features have to meet some minimum requirements for considering AFVs. The CV values show that decision-makers in the administration and industry should focus on the most promising consumer group of ‘AFV aficionados’ and their needs. It also shows that some vehicle attribute improvements could increase the demand for AFVs cost-effectively, and that consumers would accept surcharges for some vehicle attributes at a level which could enable their private provision and economic operation (e.g. fast-charging infrastructure). Improvement of other attributes will need governmental subsidies to compensate for insufficient consumer valuation (e.g. battery capacity).     

Over-reporting vs. overreacting: Commuters’ perceptions of travel times

In a large-scale, real-life peak avoidance experiment, we asked participants to provide estimates of their average in-vehicle travel time during their morning commute. After comparing the reported travel times with the actual corresponding travel times, we found that the average travel times were overstated by a factor of 1.5. We showed that driver- and link-specific characteristics partially explained these exaggerations. Using the stated and revealed preference data, we investigated whether the driver-specific reporting errors were consistent with the drivers’ scheduling behaviors in reality and in hypothetical choice experiments. In both cases, we found no robust evidence that drivers behave as if they misperceive travel times to a similar extent as those they misreported, thereby implying that the reported travel times did not represent the actual or perceived travel times in a truthful manner. The results of this study suggest that caution should be recommended when reported travel time data are used in an uncritical manner during transport research and when determining policy.