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Spatiotemporal evolution and driving factors for GHG emissions of aluminum industry in China

《能源前沿（英文）》 2023年第17卷第2期页码 294-305 doi: 10.1007/s11708-022-0819-7

摘要： China’s aluminum (Al) production has released a huge amount of greenhouse gas (GHG) emissions. As one of the biggest country of primary Al production, China must mitigate its overall GHG emission from its Al industry so that the national carbon neutrality target can be achieved. Under such a background, the study described in this paper conducts a dynamic material flow analysis to reveal the spatiotemporal evolution features of Al flows in China from 2000 to 2020. Decomposition analysis is also performed to uncover the driving factors of GHG emission generated from the Al industry. The major findings include the fact that China’s primary Al production center has transferred to the western region; the primary Al smelting and carbon anode consumption are the most carbon-intensive processes in the Al life cycle; the accumulative GHG emission from electricity accounts for 78.14% of the total GHG emission generated from the Al industry; China’s current Al recycling ratio is low although the corresponding GHG emission can be reduced by 93.73% if all the primary Al can be replaced by secondary Al; and the total GHG emission can be reduced by 88.58% if major primary Al manufacturing firms are transferred from Inner Mongolia to Yunnan. Based upon these findings and considering regional disparity, several policy implications are proposed, including promotion of secondary Al production, support of clean electricity penetration, and relocation of the Al industry.

关键词： aluminum material flow analysis GHG (greenhouse gas) emissions LMDI (logarithmic mean divisa index)

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Identifying the driving factors of successful megaproject construction management: Findings from three

Qinghua HE, Junyan XU, Ting WANG, Albert P. C. CHAN

《工程管理前沿（英文）》 2021年第8卷第1期页码 5-16 doi: 10.1007/s42524-019-0058-8

摘要： The construction of megaprojects has always resulted in extensive and long-term impacts on the society. However, the performance of megaproject management is poor, and improving it remains an urgent and necessary issue. Although many studies on megaproject success have been conducted, existing studies on the driving factors of successful megaproject construction are rather limited. Therefore, this study aims to systematically explore the key factors that can lead to successful megaproject construction management based on three cases: The Beijing–Shanghai High-Speed Railway, the Three Gorges Dam, and the Hong Kong–Zhuhai–Macao Bridge. Mixed research methods, such as literature review, case studies, and expert interviews, were used in this study. Consequently, 11 driving factors, namely, government support, public support, accumulation and application of technology and experience, development and innovation of technology, innovation and application of management system, organizational mode and structure, top management support, project culture, megaproject citizenship behavior, corporate reputation, and fulfillment of social responsibilities, were identified and grouped into five categories, namely, project environment, construction capabilities, organization, positive culture and behavior, and requirements for sustainable development. The contributions of this study lie in two aspects. First, the driving factors of successful megaproject construction are identified to deepen the understanding of industrial practitioners, assist them in focusing on key factors, and aid them in effectively managing megaprojects. Second, researchers could use the identified driving factors in conducting further empirical studies and apply them in future projects to enhance their chances of success.

关键词： megaproject management driving factors project success case study China

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Driving Factors of Green Mining in Coal Mining Enterprises in China

Lin-xiu Wang,Mu-xi Yu,Si-jia Wang

《工程管理前沿（英文）》 2015年第2卷第3期页码 211-223 doi: 10.15302/J-FEM-2015043

摘要： This study constructs a Green Mining model based on identification and analysis of the four key driving factors of Green Mining in coal mining enterprises in China. Twelve research propositions are raised and empirically tested by using Structural Equation Model. The result shows that four key factors affect the intended implementation of Green Mining by improving a corporations efficiency and reputation. The diffusion of Green Mining technology has direct positive influence on the intended Green Mining implementation; Stakeholders’ green appeal has a positive influence on the decision makers’ attitude and values. The empirical study provides support for the government to establish a reasonable regulation and control mechanism to improve enterprises’ enthusiasm for Green Mining. Four Green Mining incentive policies are raised to regulate and motivate the coal mining enterprises to improve their environmental behaviors. The government can adopt piece(s) of them to change the enterprises’ roles from traditional passive to modern initiative.

关键词： Green Mining driving factor Structural Equation Model empirical study

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“21世纪海上丝绸之路”蓝色经济国际合作：驱动因素、领域识别与机制构建

陈明宝,韩立民

《中国工程科学》 2016年第18卷第2期页码 98-104 doi: 10.15302/J-SSCAE-2016.02.012

摘要：

当今世界，蓝色经济已经成为全球海洋领域发展的重点，它强调的是海洋经济的可持续发展，突出国家间通过通力合作共同促进海洋资源开发与海洋生态环境保护。“21世纪海上丝绸之路”建设恰为中国与沿线国家的蓝色经济合作提供重要平台。从这一关系为切入点，研究沿线国家蓝色经济合作的驱动因素，构建包括国家战略发展、区域比较优势、政府政策导向、区域环境安全在内的蓝色经济合作领域选择依据，在考虑蓝色经济合作的一般领域的基础上，选择了资源能源、海洋产业、海洋科技、海洋生态环境作为中国与沿线国家合作的重点领域，并针对合作领域构建了以市场主导、陆海统筹、协作治理与利益协调为框架的合作机制。

关键词： 21世纪海上丝绸之路蓝色经济驱动因素领域识别合作机制

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基于驾驶脑的智能驾驶车辆硬件平台架构 Article

李德毅,高洪波

《工程（英文）》 2018年第4卷第4期页码 464-470 doi: 10.1016/j.eng.2018.07.015

摘要：

不同智能驾驶试验平台的传感器型号、数量、安装位置各不相同，导致传感器信息处理模块也各不相同；不同驾驶地图，其提供信息的粒度也没有固定标准，由此构成的智能驾驶系统软件模块的数量、接口各不相同。基于以驾驶脑为核心的智能驾驶车辆软件与硬件架构，决策模块将不直接与传感器信息处理模块发生关联，通过驾驶认知的形式化语言，将驾驶认知形式化，由驾驶脑认知形成决策。驾驶认知的形式化降低了传感器数量、类型、安装位置的变化对整个软件架构的影响，使得软件架构可以在不同传感器配置车辆平台上方便地移植。

关键词：驾驶脑智能驾驶硬件平台架构

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Mechanism of self-excited torsional vibration of locomotive driving system

Jianxin LIU, Huaiyun ZHAO, Wanming ZHAI

《机械工程前沿（英文）》 2010年第5卷第4期页码 465-469 doi: 10.1007/s11465-010-0115-9

摘要： A single wheelset drive model and 2-DOFs torsional vibration model were established to investigate the self-excited torsional vibration of a locomotive driving system. The simulation results indicate that the self-excited torsional vibration occurs when the steady slip velocity is located at the descending slope of the adhesion coefficient curve. The principle of energy conservation was used to analyze the mechanism of the self-excited vibration. The factors affecting on the amplitude of the self-excited vibration are studied.

关键词： locomotive driving system self-excited torsional vibration mechanism influence factor

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自动驾驶地图有关政策的思考和建议

刘经南,董杨,詹骄,高柯夫

《中国工程科学》 2019年第21卷第3期页码 92-97 doi: 10.15302/J-SSCAE-2019.03.004

摘要：

自动驾驶地图作为实现汽车自动驾驶的关键基础设施，对于推动我国自动驾驶领域的商业化开发至关重要。现阶段，我国受地图测绘、应用和监管等相关法律法规的制度掣肘，在自动驾驶地图的产业化进程方面相对滞后。为此，本文着重分析了我国在自动驾驶地图开发、应用和管理中面临的主要政策法规问题：自动驾驶地图是否需加密的问题、自动驾驶地图部分地理信息表达受限的问题、自动驾驶地图地理信息采集资质和审图流程的问题、自动驾驶地图事故责任和保险问题、自动驾驶地图相关测试规范和测试场景问题。同时结合国内外自动驾驶领域的发展趋势，给出加快我国自动驾驶汽车开发和商业化进程的四点建议：制定自动驾驶地图管理模式、允许自动驾驶地图应用试点及有序开放、适当放开企业权限及优化审核流程、建立国家级自动驾驶地图平台。

关键词：自动驾驶地图自动驾驶法规自动驾驶政策

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一种用于自动驾驶的车辆概率性长期轨迹预测框架 Article

刘金鑫, 罗禹贡, 钟志华, 李克强, 黄荷叶, 熊辉

《工程（英文）》 2022年第19卷第12期页码 228-239 doi: 10.1016/j.eng.2021.12.020

摘要：

在混合动态交通环境中，准确地预测周围车辆长期范围内的运动轨迹是自动驾驶车辆（AV）实现合理行为决策和保障行车安全不可或缺的前提条件之一。本文提出了一种车辆长期轨迹预测的概率框架，由驾驶意图推理模型（DIM）和轨迹预测模型（TPM）组成。DIM基于动态贝叶斯网络进行设计和应用，用于准确推断车辆潜在的驾驶意图。文中所提出的DIM结合了基本的交通规则和车辆多维运动信息。为了进一步提高轨迹预测精度并实现预测不确定性识别，本文开发了基于高斯过程（GP）的TPM，综合考虑了车辆模型的短期预测结果和运动特性。最后，在高速换道场景下进行仿真验证，说明了新方法的有效性。通过与其他先进方法进行对比，展示并验证了该框架在车辆长期轨迹预测任务中的优异性能。

关键词：自动驾驶动态贝叶斯网络驾驶意图识别高斯过程车辆轨迹预测

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Development and application prospects of piezoelectric precision driving technology

ZHAO Chunsheng, ZHANG Jiantao, ZHANG Jianhui, JIN Jiamei

《机械工程前沿（英文）》 2008年第3卷第2期页码 119-132 doi: 10.1007/s11465-008-0034-1

摘要： With the rapid development of science and technology, microelectronics manufacturing, photonics technology, space technology, ultra-precision machining, micro-robotics, biomedical engineering and other fields urgently need the support of modern precision driving theory and technology. Modern precision driving technology can be generally divided into two parts: electromagnetic and non-electromagnetic driving technology. Electromagnetic driving technology is based on traditional technology, has a low thrust-weight ratio, and needs deceleration devices with a cumbrous system or a complex structure. Moreover, it is difficult to improve positioning accuracy with this technology type. Thus, electromagnetic driving technology is still unable to meet the requirements for the above applications. Non-electromagnetic driving technology is a new choice. As a category of non-electromagnetic driving technology, piezoelectric driving technology becomes an important branch of modern precision driving technology. High holding torque and acute response make it suitable as an accurate positioning actuator. This paper presents the development of piezoelectric precision driving technology at home and abroad and gives an in-depth analysis. Future perspectives on the technology’s applications in the following fields are described: 1) integrated circuit manufacturing technology; 2) fiber optic component manufacturing technology; 3) micro parts manipulation and assembly technology; 4) biomedical engineering; 5) aerospace technology; and 6) ultra-precision processing technology.

关键词： Electromagnetic ultra-precision processing technology piezoelectric cumbrous

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A driving pulse edge modulation technique and its complex programming logic devices implementation

Xiao CHEN,Dong-chang QU,Yong GUO,Guo-zhu CHEN

《信息与电子工程前沿（英文）》 2015年第16卷第12期页码 1088-1098 doi: 10.1631/FITEE.1500111

摘要： With the continual increase in switching speed and rating of power semiconductors, the switching voltage spike becomes a serious problem. This paper describes a new technique of driving pulse edge modulation for insulated gate bipolar transistors (IGBTs). By modulating the density and width of the pulse trains, without regulating the hardware circuit, the slope of the gate driving voltage is controlled to change the switching speed. This technique is used in the driving circuit based on complex programmable logic devices (CPLDs), and the switching voltage spike of IGBTs can be restrained through software, which is easier and more flexible to adjust. Experimental results demonstrate the effectiveness and practicability of the proposed method.

关键词： Driving pulse edge modulation Switching voltage spike Complex programmable logic device (CPLD) Active gate drive

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Reverse driving character of 2-DOF closed chain haptic device

GUO Wei-dong, GUO Xin, ZHANG Yu-ru

《机械工程前沿（英文）》 2006年第1卷第3期页码 356-359 doi: 10.1007/s11465-006-0029-8

摘要： Reverse driving character plays an important role in evaluating the performance of a haptic device, and it is the primary rule in the mechanical design. This article mainly investigates the problem of 2-DOF haptic device design f

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Driving mechanism and boundary control of urban sprawl

Dongmei JIANG,Xiaoshun LI,Futian QU,Mingyan LI,Shaoliang ZHANG,Yunlong GONG,Xiaoping SHI,Xin CHEN

《环境科学与工程前沿（英文）》 2015年第9卷第2期页码 298-309 doi: 10.1007/s11783-014-0639-z

摘要： Since the reform and opening-up, China’s economy has achieved remarkable development and so does the urbanization. However, there is an unavoidable contradiction between urban sprawl and the protection of arable land and the environment. By redefining the urban sprawl boundary, this paper is to provide a solution for the conflict above on the China’s urbanization context. The ideal boundary, moderate boundary and limit boundary are defined for urban sprawl in space. Taking Nanjing city as a case, the three urban sprawl boundaries are estimated in this paper based on the calculation of agricultural land resources value in Nanjing. The results show that 1) the integrated value of agricultural (cultivated) land resources in Nanjing is 1.55 × 10 CNY·hm , the economic value accounts for only 8.74% of the integrated value, while 91.26% of the integrated value has not revealed itself due to the existing institutional arrangements, policy distortions, and imperfect land market; 2) it is difficult to define the ideal and moderate boundaries due to the relatively low price of North Nanjing. In South Nanjing the land price is expensive and the ideal, moderate and limit boundaries are expanded to Jiangning, Qixia, and Yuhuatai; 3) the city scale of South Nanjing should be limited within 5.82 × 10 hm , which is roughly the same as the designated size of 5.81 × 10 hm in the urban planning. It is suggested that the rational scope of urban expansion should be controlled within the moderate boundary.

关键词： urban sprawl rational expansion driving forces boundary control Nanjing

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Meta-analysis of the risk factors of breast cancer concerning reproductive factors and oral contraceptive

Qiong DAI MD, Bei LIU MD, Yukai DU MM,

《医学前沿（英文）》 2009年第3卷第4期页码 452-458 doi: 10.1007/s11684-009-0080-z

摘要： The authors performed a meta-analysis of case-control studies that addressed whether reproductive factors and oral contraceptive use were associated with breast cancer by searching the MEDLINE, PubMed, Proquest, Embase, ScienceDirect, African Healthline, BMJ Health Intelligence and Chinese Periodical net databases for all English-language and Chinese-language papers published from January 1, 1997 to December 31, 2007. A total of 15 studies calculating pool ORs indicated that menopausal age >50yr [odds ratio (OR), 1.39; 95% confidence interval (CI), 1.22―1.57] and oral contraceptive use (OR, 2.12*, “*”: summary OR was adjusted; 95% CI, 1.24―3.62) were correlated with the increase in breast cancer risk while the summary OR based on number of full-term pregnancies ≥1 (OR, 0.63*; 95% CI, 0.60―0.68) and breast-feeding (OR, 0.76; 95% CI, 0.64―0.90) indicated no association with breast cancer risk. The correlation was statistically significant. Menopausal age >50yr and oral contraceptive use are positively correlated with an increase in breast cancer risk while breast-feeding and number of full-term pregnancies ≥1 are protective factors.

关键词： meta-analysis breast cancer risk factors reproductive factors oral contraceptive use

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Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration

Kang Yuan,Yanjun Huang,Shuo Yang,Zewei Zhou,Yulei Wang,Dongpu Cao,Hong Chen,

《工程（英文）》 doi: 10.1016/j.eng.2023.03.018

摘要： Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment. This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data- and model-driven method. First, a data-driven decision-making module based on deep reinforcement learning (DRL) is developed to pursue a rational driving performance as much as possible. Then, model predictive control (MPC) is employed to execute both longitudinal and lateral motion planning tasks. Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements. Finally, two principles of safety and rationality for the self-evolution of autonomous driving are proposed. A motion envelope is established and embedded into a rational exploration and exploitation scheme, which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent. Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted, and the results show that the proposed online-evolution framework is able to generate safer, more rational, and more efficient driving action in a real-world environment.

关键词： Autonomous driving Decision-making Motion planning Deep reinforcement learning Model predictive control

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Research on Anthropomorphic Obstacle Avoidance Trajectory Planning for Adaptive Driving Scenarios Based

Jian Wu,Yang Yan,Yulong Liu,Yahui Liu,

《工程（英文）》 doi: 10.1016/j.eng.2023.07.018

摘要： The forward design of trajectory planning strategies requires preset trajectory optimization functions, resulting in poor adaptability of the strategy and an inability to accurately generate obstacle avoidance trajectories that conform to real driver behavior habits. In addition, owing to the strong time-varying dynamic characteristics of obstacle avoidance scenarios, it is necessary to design numerous trajectory optimization functions and adjust the corresponding parameters. Therefore, an anthropomorphic obstacle-avoidance trajectory planning strategy for adaptive driving scenarios is proposed. First, numerous expert-demonstrated trajectories are extracted from the HighD natural driving dataset. Subsequently, a trajectory expectation feature-matching algorithm is proposed that uses maximum entropy inverse reinforcement learning theory to learn the extracted expert-demonstrated trajectories and achieve automatic acquisition of the optimization function of the expert-demonstrated trajectory. Furthermore, a mapping model is constructed by combining the key driving scenario information that affects vehicle obstacle avoidance with the weight of the optimization function, and an anthropomorphic obstacle avoidance trajectory planning strategy for adaptive driving scenarios is proposed. Finally, the proposed strategy is verified based on real driving scenarios. The results show that the strategy can adjust the weight distribution of the trajectory optimization function in real time according to the “emergency degree” of obstacle avoidance and the state of the vehicle. Moreover, this strategy can generate anthropomorphic trajectories that are similar to expert-demonstrated trajectories, effectively improving the adaptability and acceptability of trajectories in driving scenarios.

关键词： Obstacle avoidance trajectory planning Inverse reinforcement theory Anthropomorphic Adaptive driving scenarios