How do children learn to cross the street? The process of pedestrian safety training

Objective: Pedestrian injuries are a leading cause of child death and may be reduced by training children to cross streets more safely. Such training is most effective when children receive repeated practice at the complex cognitive–perceptual task of judging moving traffic and selecting safe crossing gaps, but there is limited data on how much practice is required for children to reach adult levels of functioning. Using existing data, we examined how children's pedestrian skills changed over the course of 6 pedestrian safety training sessions, each composed of 45 crossings within a virtual pedestrian environment.

Methods: As part of a randomized controlled trial on pedestrian safety training, 59 children ages 7–8 crossed the street within a semi-immersive virtual pedestrian environment 270 times over a 3-week period (6 sessions of 45 crossings each). Feedback was provided after each crossing, and traffic speed and density were advanced as children's skill improved. Postintervention pedestrian behavior was assessed a week later in the virtual environment and compared to adult behavior with identical traffic patterns.

Results: Over the course of training, children entered traffic gaps more quickly and chose tighter gaps to cross within; their crossing efficiency appeared to increase. By the end of training, some aspects of children's pedestrian behavior was comparable to adult behavior but other aspects were not, indicating that the training was worthwhile but insufficient for most children to achieve adult levels of functioning.

Conclusions: Repeated practice in a simulated pedestrian environment helps children learn aspects of safe and efficient pedestrian behavior. Six twice-weekly training sessions of 45 crossings each were insufficient for children to reach adult pedestrian functioning, however, and future research should continue to study the trajectory and quantity of child pedestrian safety training needed for children to become competent pedestrians.     

Pipeline leakage detection and isolation: An integrated approach of statistical and wavelet feature extraction with multi-layer perceptron neural network (MLPNN)

Leakage diagnosis of hydrocarbon pipelines can prevent environmental and financial losses. This work proposes a novel method that not only detects the occurrence of a leakage fault, but also suggests its location and severity. The OLGA software is employed to provide the pipeline inlet pressure and outlet flow rates as the training data for the Fault Detection and Isolation (FDI) system. The FDI system is comprised of a Multi-Layer Perceptron Neural Network (MLPNN) classifier with various feature extraction methods including the statistical techniques, wavelet transform, and a fusion of both methods. Once different leakage scenarios are considered and the preprocessing methods are done, the proposed FDI system is applied to a 20-km pipeline in southern Iran (Goldkari-Binak pipeline) and a promising severity and location detectability (a correct classification rate of 92%) and a low False Alarm Rate (FAR) were achieved.     

An empirical examination of personal learning within the context of teams

Using a sample of 588 employees in 59 work teams, we tested a model that situates personal learning within the context of teams, viewing it as a joint function of teams' leadership climate (i.e., transformational leadership) and task characteristics (i.e., task routineness and task interdependence). Consistent with our hypotheses, we found that the positive relationships between transformational leadership climate and the two dimensions of personal learning (relational job learning and personal skill development) were moderated by the nature of the teams' tasks. Specifically, transformational leadership climate was more strongly associated with personal learning for members of teams working on tasks that were less routine, rather than more routine. However, no significant moderation was found for leadership climate and task interdependence. Our findings underscore the importance of taking into account the contextual conditions within which leadership influence occurs while also demonstrating the potential role that leaders can play in promoting employees' personal learning. Overall, our study bolsters theories that conceptualize adult learning as a transaction between people and their social environments and points to a practical need to match leadership styles with team task characteristics to unleash transformational leadership effects. Copyright © 2015 John Wiley & Sons, Ltd.     

湖南慈利马尾松树轮宽度对气候的响应及1854年以来冬季极端低温重建

利用采自湖南慈利的马尾松树轮样本,建立研究区的标准树轮宽度年表。树轮气候响应分析发现:马尾松径向生长与月最大日降水量在生长季之前部分月份显著负相关(p0.05),在生长季之内部分月份显著正相关(p0.05),与月平均温度、月平均最低温度、月极端最低温度在生长季之前和之内大多月份均显著正相关(p0.05),其中与上一年11月到当年2月(冬季)的平均极端最低温度相关最好(r=0.62,p0.01)。重建了湖南慈利地区1854年以来冬季极端最低温度,重建气温在十年尺度上表现出明显的反"S"型,1854—1916年和1981—2015年处于暖冬时期,1917—1980年处于寒冬时期。此外,共发现29个寒冬年,其中包括3个寒冬时段,分别为1922—1925年、1927—1930年和1953—1960年,其中1953—1960年是自1854年以来最冷的时段。空间相关性分析表明重建序列可以指示我国中东部的冬季低温变化,而冬季低温可能与热带印度洋、西太平洋海温变化异常有关。     

Monitoring and adaptive management: resolving social and organisational issues to improve information sharing in natural resource management

Adaptive, or 'learning by doing', approaches are often advocated as a means of providing increased understanding within natural resource management. However, a number of organisational and social issues need to be resolved if these approaches are to be used successfully. A case study in the South Island high country of New Zealand is used to review what is needed to support an ongoing community-based monitoring and adaptive management programme. First, the case study is described, paying attention to the social context of the resource management problem. The results of a workshop that explored this problem are then outlined, along with a proposed information flow suggested by participants. Requirements for future steps to resolve these problems (such as information protocols and a multi-stakeholder information system) are discussed. Finally, some broad lessons are drawn from this exercise that could help others developing similar approaches.     

巷道放顶煤人-机-环境系统可靠性研究

应用系统可靠性和人 -机工程学理论 ,建立了急倾斜煤层巷道放顶煤人 -机 -环境系统可靠性模型 ,给出了系统可用度和生产能力的计算公式。结合开滦马家沟矿 972 3工作面人 -机-环境系统分析 ,探讨了提高系统可靠性和生产能力的有效途径。理论分析及实例计算结果表明 ,所建立的模型能简便地找出系统的薄弱环节 ,准确预测系统可用度和生产能力 ,从而为指导矿井设计和生产提供科学依据     

Development of machine learning based prediction models for hazardous properties of chemical mixtures

Lower flammability limit (LFL), upper flammability limit (UFL), auto-ignition temperature (AIT) and flash point (FP) are crucial hazardous properties for fire and explosion hazards assessment and consequence analysis. In this study, a comprehensive prediction model set was constructed by using expanded chemical mixture databases of chemical mixture hazardous properties. Machine learning based gradient boosting quantitative structure-property relationship (GB-QSPR) method is implemented for the first time to improve the model performance and prediction accuracy. The result shows that all developed models have significantly higher accuracy than other regular QSPR models, with the 5-fold cross-validation RMSE of LFL, UFL, AIT, and FP models being 1.06, 1.14, 1.08, and 1.17, respectively. All developed QSPR models can be used to estimate reliable chemical mixture hazardous properties and provide useful guidance in chemical mixture hazard assessment and consequence analysis.     

提高GPS定位精度的群调度滤波算法*

为解决现行安全生产科技领域中全球定位系统（GPS）/惯性导航系统（INS）融合系统容易产生较大时变误差的关键问题,满足GPS定位信号的精度和信号数据处理时间的要求,提出1种群调度滤波算法,通过实验仿真,分别与模糊算法、机器学习算法及卡尔曼滤波网络算法进行比较研究。结果表明:群调度滤波算法兼顾了定位精度与数据处理时间,具有较大优势,可在航空安全、船舶安全、应急监测、灾后抢险等安全科技领域广泛应用。     

CASS处理技术的原理和应用

介绍了CASS工艺的原理、特点、核心构筑物和设计、运行中应注意的主要问题以及常见故障的排除方法。     

Signs that encourage internalized recycling: Clinical validation, weak messages and “creative elaboration”

Two experiments examined clinical validation's ability to increase examination of a persuasive message and increase long-term recycling. In Experiment 1, validating (acknowledging) recycling's inconvenience decreased criticism of the persuasive message, supporting validation's ability to reduce reactance and open the reader to new ideas. Validation did not improve attitudes towards the sign's author, removing liking for the communicator as an alternate explanation for attitude change. In Experiment 2, different recycling signs were created from a 2(no validation/validation) by 2(weak/strong arguments) factorial design, and placed in university buildings. The validation weak sign increased recycling more than the validation strong sign, especially after the signs were removed. We suggest that validation induced people to scrutinize the weak message and use their existing pro-recycling attitudes to “creatively elaborate” it. Discussion emphasizes clinical validation and the Elaboration Likelihood Model as theoretical tools, as well as the potential for thought provoking signs to have long-term effects.