单标多点校正组合英蓝超滤测定地表水中多种阴离子

建立了利用组合单标多点校正和英蓝超滤单元的离子色谱法测定地表水中F-、C1-、NO3-、S0424—4-种离子的方法,方法操作简便,灵敏度高,线性范围广,抗干扰能力强,可同时快速测定不同数量级浓度的离子,降低了配置标准品和样品前处理的复杂性,减少了因前处理带来的干扰。     

过山车立环轨道设计方法

基于加速度研究过山车立环轨道曲线的设计方法.分别研究向心加速度恒定的立环曲线,加速度恒定的立环曲线和以欧拉螺线为基础的立环曲线.建立三种立环曲线的方程,通过数值方法进行求解,借助Matlab计算在给定初始条件和边界条件下的轨道曲线.以加速度为评判标准来分析三种曲线的优点和缺点,最终得到以加速度为基础的立环轨道曲线设计方...     

'All hazards approach' to disaster management: the role of information and knowledge management, Boyd's OODA Loop, and network-centricity

The ever-increasing complexity of disasters demands utilisation of knowledge that exists outside domains traditionally drawn upon in disaster management. To be operationally useful, such knowledge must he extracted, combined with information generated by the disaster itself, and transformed into actionable knowledge. The process, though, is hampered by existing, business-oriented approaches to knowledge management, by technical issues related to access to relevant, multi-domain information/knowledge, and by executive decision-making processes based predominantly on historical knowledge. Consequently, as shown by many recent incidents, the management of large-scale (mega) disasters is often inefficient and exceedingly costly. This paper demonstrates that the integration of modified information and knowledge management into the concepts of network-centric operations and network-enabled capabilities, and the employment of Boyd's OODA (Observe, Orient, Decide, and Act) Loop-based decision-making in unpredictable and dynamically changing environments, may address some of these problems.     

应急监测中便携式顶空/GC-MS法测定水中VOCs的初步研究

通过对实验室加标水样和实际水样的测定,研究了便携式顶空/气相色谱-质谱法(GC-MS)与吹扫捕集/GC-MS法测定水中VOCs的性能比较,探讨了利用Loop环测定水中高浓度VOCs的准确度. 结果表明:便携式顶空/GC-MS测定水中54种低浓度VOCs的检出限略高于吹扫捕集/GC-MS系统,准确度和精密度分别为67.4%～136%和9.08%～19.80%,均满足环境应急监测分析的要求;利用Loop环,便携式顶空/GC-MS可对水中高浓度级(mg/L)VOCs进行较为准确地测定,回收率为100%～149%;复杂的实际样品基本不干扰便携式顶空/GC-MS的测定,与吹扫捕集/GC-MS法相比,二者对实际水样的测定结果相对偏差小于20%;便携式顶空/GC-MS在水污染事故现场可得到基本准确的结果,可为事故后续处理提供有效的数据支持.      

Identifying crash propensity using specific traffic speed conditions

INTRODUCTION: In spite of recent advances in traffic surveillance technology and ever-growing concern over traffic safety, there have been very few research efforts establishing links between real-time traffic flow parameters and crash occurrence. This study aims at identifying patterns in the freeway loop detector data that potentially precede traffic crashes. METHOD: The proposed solution essentially involves classification of traffic speed patterns emerging from the loop detector data. Historical crash and loop detector data from the Interstate-4 corridor in the Orlando metropolitan area were used for this study. Traffic speed data from sensors embedded in the pavement (i.e., loop detector stations) to measure characteristics of the traffic flow were collected for both crash and non-crash conditions. Bayesian classifier based methodology, probabilistic neural network (PNN), was then used to classify these data as belonging to either crashes or non-crashes. PNN is a neural network implementation of well-known Bayesian-Parzen classifier. With its superb mathematical credentials, the PNN trains much faster than multilayer feed forward networks. The inputs to final classification model, selected from various candidate models, were logarithms of the coefficient of variation in speed obtained from three stations, namely, station of the crash (i.e., station nearest to the crash location) and two stations immediately preceding it in the upstream direction (measured in 5 minute time slices of 10-15 minutes prior to the crash time). RESULTS: The results showed that at least 70% of the crashes on the evaluation dataset could be identified using the classifiers developed in this paper.     

A theoretical and methodological framework for studying and modelling drivers’ mental representations

This article provides a synthetic overview of the research programme carried out at INRETS-LESCOT over the last 10 years, in view to studying and modelling the mental representations of car drivers. Theoretically, this research is in line with two complementary scientific traditions: Human Information Processing theories on the one hand, and theories of Operative Activity on the other. As discussed in Section 1 of the article, attention is given to the functional representations of drivers, constructed “by” and “for” the action, such as they are implemented in a driving situation, and taking into account both implicit and explicit dimensions. This aim directly impacts on the methodological approach implemented, in so far as it entails defining an “experimental continuum” ranging from naturalistic observations of the driving activity (on the open road), to setting up more controlled experimental protocols in order to permit in-depth, systematic and reproducible scientific investigations of drivers’ cognition. Section 2 of the article presents a synthetic view of these methods, while Section 3 presents several significant results obtained with them. Lastly, the final part of the article focuses on the computational formalism defined at INRETS-LESCOT (i.e. the driving schemas) designed to model driver knowledge and mental representations, and developed in a COgnitive Simulation MOdel of the DRIVEr called COSMODRIVE.     

Using qualitative models to define sustainable management for the commons in data poor conditions

Nearly 50 years after Hardin’s “tragedy of the commons” we have not yet found predictive tools to guide us towards sustainable management of common-pool resources (CPR). We often have a good understanding of the qualitative relationships between the principal actors in socioecological systems (SESs), but classical quantitative approaches require a tremendous amount of data to understand the drivers of SESs sustainability. Here we show that qualitative modelling approaches can provide important governance insights for SESs that are understood but not quantified.We used Loop Analysis to test the outcomes of different management regimes on a simple nature-based tourism SES described by economic, social and environmental variables. We tested the sustainability of different management scenarios on this system and we identified the necessary conditions to achieve it.We found that management regimes where property rights and responsibilities are shared between different stakeholders are more likely to be successful. However, the system is generally highly unstable and it is important to tune each strategy to each particular situation.The conditions for sustainability found across the different systems tested were: a low reinvestment rate of tourist revenues into new infrastructures and a low growth rate of the environment. Management strategies based on maximum sustainable yield, which keep the environment far from its carrying capacity, have less chance to be sustainable.Qualitative models of SESs are powerful diagnostic tools; they can help identifying variables that play an important role in determining socioecological sustainability in data-poor circumstances and guide the design of efficient data collection programmes. Our results highlight the importance of careful planning when designing management strategies for nature-based tourism. The application of one-size-fits-all solutions to every situation is likely to lead to the failure of the commons; however tourism-based SESs can be sustainable if management strategies are tuned to each particular case.     

基于环路热管的冷却系统实验研究

为了提高铁路车辆牵引变流器冷却系统技术水平,满足铁路车辆装备发展需求,针对热控领域先进技术环路热管进行了冷却系统实验研究.在阐述环路热管基本原理、实验系统搭建及参数设置的基础上,从气动特性和运行特性2个方面对实验结果进行数据分析,以期为今后牵引变流器及其他铁路大功率电子设备冷却技术的发展提供新思路及备选方案.