流程制造业与循环经济

阐述了发展循环经济的意义与循环经济的内涵,提出技术-经济及时空因素的集成与协调是推进循环经济的有效手段。在我国实现新型工业化的过程中,流程制造业既是支柱产业、基础产业,也是推进循环经济的重要切入点。     

Cycle Aware: Piloting a module for novice drivers

Introduction: In low-cycling countries, motor-vehicle traffic and driver behavior are well known barriers to the uptake of bicycles, particularly for utility cycling. Lack of separation between cyclists and faster-moving traffic is one key issue, while attitudes of drivers toward and/or harassment of cyclists is another. Cyclist-related driver education has been recommended as a means to improve driver-cyclist interactions. Methods: The driver licensing process provides an opportunity for such education. The Cycle Aware module was developed to test and enhance novice drivers’ knowledge of interacting safely with cyclists. It was piloted across three Australian jurisdictions targeting both novice and experienced drivers. Participants were asked to complete the Cycle Aware module and an accompanying survey. A total of 134 novice and 97 experienced drivers completed the survey with 42 novice and 50 experienced drivers going on to complete the module. Results: Both groups of drivers scored equally well in the module but the very youngest and very oldest participants were more likely to have some incorrect responses. We did not find any relationship between correct module scores and attitudes toward cyclists. Survey results showed both novice and experienced drivers had somewhat positive attitudes toward cyclists. The two cohorts differed on several attitude questions. Sixty percent (60%) of novices compared to 30% of experienced drivers reported feeling concerned when sharing the road with cyclists, and novices were less likely to agree that cyclists had a right to use the roads. Conclusions and practical applications: The analysis suggests novices need to be better equipped to share roads confidently with cyclists and to recognize cyclists as legitimate traffic participants.     

软岩隧道塌方事故致灾因素耦合分析*

为减少专家主观判断对软岩隧道塌方事故评估的影响,提出1种从事故出发逆推分析事故致灾因素耦合机制的方法。基于142个隧道施工塌方事故案例,系统总结隧道塌方事故致灾因素,对塌方事故的致灾因素出现频率进行排序;从致灾因素之间关联耦合关系出发,结合隧道施工塌方事故的多因素耦合致灾机理,研究隧道塌方事故产生过程的多因素耦合路径和耦合过程;采用N-K耦合模型开展隧道塌方事故多因素耦合路径下的耦合关联值评估,并对耦合关联值进行排序从而找到控制塌方事故发生的致灾因素组合。结果表明:除4个主要致灾因素的全耦合外,围岩岩性-降雨-地下水的耦合关联值是洞身段中最大值,为17.79%,围岩岩性-偏压-地下水的耦合关联值是洞口段中最大值,为24.02%;洞身段的围岩岩性-地下水因素和洞口段的围岩岩性-偏压因素分别对耦合关联值大小起决定影响;耦合关联值不具备叠加效应,2因素耦合关联值可能比3因素耦合关联值更大。研究结果可为提高隧道事故分析与安全防控提供科学依据。     

YOLOv4目标检测算法在煤矿工人口罩佩戴监测工作中的应用研究*

为防止煤矿工人吸入过量粉尘而导致职业性尘肺病,基于Keras框架利用YOLOv4 (you only look once)目标检测算法对井下人员佩戴防尘口罩情况进行高精度且快速的检测与识别,并与MTCNN(Multi-task convolutional neural network)和FaceNet构成的人脸识别算法相结合,进行煤矿工人口罩佩戴监测的研究。结果表明:模型对井下人员口罩佩戴有较高的检测精度,识别已佩戴口罩的矿井下作业人员的平均精度达到92.78%,识别未佩戴防尘口罩检测的平均精度为91.63%,与其他主流算法相比算法具有更好的鲁棒性和检测效果。研究结果为预防煤矿工人职业性尘肺病提供1种有效的技术手段。     

Occupational safety and health education under the lifelong learning framework in Serbia

Serbia is aligning with European Union requirements and the occupational safety and health (OSH) administration is one of the most representative sectors of this alignment. Many efforts were made in this field, by introducing new laws and regulations, but it turned out to be insufficient. OSH professionals need to renovate and strengthen their knowledge in accordance with continuous, updated and improved OSH standards and regulation. Lifelong learning (LLL) programmes can contribute to forming professionals who are always up to date. This paper presents an implemented LLL programme, over the duration of two academic years, dedicated to OSH professionals, and investigates whether this programme will be helpful and accepted by professionals. The results from the study show that the given LLL programme had indeed a positive influence on the professional careers of the participants and that the LLL presents the future trend in OSH education.     

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.     

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.     

Learning for social-ecological change: a qualitative review of outcomes across empirical literature in natural resource management

Learning is considered as a promising mechanism to cope with rapid environmental change. The implications of learning for natural resource management (NRM) have not been explored in-depth and the evidence on the topic is scattered across multiple sources. We provide a qualitative review of types of learning outcomes and consider their manifestations in NRM across selected empirical literature. We conducted a systematic search of the peer-reviewed literature (N = 1,223) and a qualitative meta-synthesis of included articles, with an explicit focus on learning outcomes and NRM changes (N = 53). Besides social learning, we found several learning concepts used, including policy and transformative learning, and multiple links between learning and NRM reported. We observe that the development of skills, together with a system approach involving multi-level capacities, is decisive for implications of learning for NRM. Future reviews could systematically compare how primary research applies different learning concepts and discusses links between learning and NRM changes.     

湖泊水质富营养化评价的模糊神经网络方法

为了探索人工神经网络用于湖泊营养化评价的可能性,提出了基于多准则学习的模糊神经网络湖泊水质营养化评价模型。该模型应用于我国五大主要湖泊水质营养化的评价结果表明,模糊神经网络用于湖泊水质营养化评价,具有简便、实用、客观性和广泛的通用性。      

RS-PSO-ELM下腐蚀管道失效压力预测

为提高腐蚀管道失效压力的预测精度并简化其计算过程,提出基于粗糙集(RS)和粒子群算法(PSO)融合极限学习机(ELM)的腐蚀管道失效压力预测模型。通过属性约简提取影响失效压力的关键因素,选用PSO优化ELM的输入权值和隐含层偏差,将归一化的核心指标数据代入计算。结果表明:该模型预测结果与实际值基本一致,与单一ELM模型相比,预测结果的均方差(MSE)降至0.255;与其他蚀管道失效压力评价模型相比,该模型预测结果的绝对误差平均值降至0.32。