桥面不平度随机激励模型

桥面不平度是影响车辆-桥梁振动的主要因素,定量地研究桥面的凹凸不平对车辆-桥辆振动的影响程度,关键是要能够建立一个能正确模拟实际桥面状况的桥面不平度模型.指出了传统的用周期性函数表示不平度模型的缺点,引入随机不平度理念,建立了一种用路面功率谱函数表示桥面不平度的方法,并建立了桥面不平度随机激励时域模型.通过对比分析发现,建立的桥面不平度模型是可信的,从而提供了一种在缺少实测数据时如何通过计算机模拟获得桥面不平度仿真数据的方法.     

Specificity of Systemically Released Cotton Volatiles as Attractants for Specialist and Generalist Parasitic Wasps

Cotton plants under herbivore attack release volatile semiochemicals that attract natural enemies of the herbivores to the damaged plant. The volatiles released in response to herbivory are not only released from the damaged leaves but from the entire cotton plant. We found that cotton plants that released myrcene, (Z)-3-hexenyl acetate, (E)--ocimene, linalool, (E)-4,8-dimethyl-1,3,7-nonatriene, (E)--farnesene, and (E, E)-4,8,12-trimethyl-1,3,7,11-tridecatetraene systemically from undamaged leaves of caterpillar damaged plants were attractive to the generalist parasitoid Cotesia marginiventris and the specialist parasitoid Microplitis croceipes. Plants from which the caterpillar damaged leaves were removed and that released those compounds systemically were significantly preferred over undamaged control plants in two-choice experiments in a flight tunnel. Artificially damaged cotton plants that released green leafy volatiles and constitutive terpenoids were less attractive for M. croceipes and C. marginiventris. Only C. marginiventris preferred artificially damaged plants over undamaged control plants, whereas M. croceipes showed no preference. The apparent lack of specificity of systemically released compounds in response to different herbivores feeding on the lower leaves is discussed.     

基于图的人-物交互识别

提出了一种基于图的人与物体的交互（Human-Object Interactions,HOIs）识别方法。为了对静态图像中人与物体间丰富的交互关系进行有效的表示,采用具有强大关系建模能力的图结构为图像生成对应的人-物交互关系图。为了对图像中上下文（context）信息加以利用,提出了引入注意力机制的特征处理网络（Feature Processing Network,FPNet）。通过图注意力（Graph Attention Network,GAT）网络完成对真实的HOIs的检测和识别。该方法在V-COCO数据集与HICO-DET数据集上进行了验证,并与其他方法进行了比较,结果表明该方法具有较好的效果。     

蛋白质-RNA对接中打分函数设计及RNA结合位点识别研究进展

分子对接是目前研究蛋白质-RNA相互作用与识别的有效方法之一.其中,打分函数的合理设计与分子结合位点的准确识别对成功预测蛋白质-RNA复合物结构至关重要.结合小组的工作,对用分子对接方法预测蛋白质-RNA复合物结构中所涉及2个关键性问题(即分子对接打分函数的设计和RNA结合位点的预测)及研究进展进行了回顾,并对几种常用的方法进行了比较.最后分析了这两方面研究目前所存在的主要问题,并对未来的发展方向进行了展望.     

Self-excited vibration problems of maglev vehicle-bridge interaction system

The self-excited vibration problems of maglev vehicle-bridge interaction system were addressed, which greatly degrades the stability of the levitation control, decreases the ride comfort, and restricts the cost of the whole system. Firstly, the coupled model containing the quintessential parts was built, and the mechanism of self-excited vibration was explained in terms of energy transmission from levitation system to bridge. Then, the influences of the parameters of the widely used integral-type proportion and derivation（PD） controller and the delay of signals on the stability of the interaction system were analyzed. The result shows that the integral-type PD control is a nonoptimal approach to solve the self-excited vibration completely. Furthermore, the differential-type PD controller can guarantee the passivity of levitation system at full band. However, the differentiation of levitation gap should be filtered by a low-pass filter due to noise of gap differentiation. The analysis indicates that a well tuned low-pass filter can still keep the coupled system stable.     

青岛海湾大桥地震作用下的车桥动力响应研究

针对桥梁因车辆振动引起的疲劳开裂导致刚度下降而下挠增加等问题,本文以青岛海湾大桥大沽河桥段为例,运用振型叠加法对桥梁有限元模型进行时程分析,计算在地震作用下车桥系统的动力响应。结果表明,考虑地震作用时,位移时程曲线波动性较明显,且位移相对较大。考虑地震波后的加速度时程曲线比未考虑地震波时的波动性大,且加速度明显增加,可见地震波对车桥系统的动力响应影响很大,考虑地震波时的时程曲线波动性较不考虑地震波时明显;考虑地震波的作用后,随着速度的增加,桥梁的动挠度明显减小,这是因为车辆速度较小时,车辆在桥梁上的作用时间变长,同时车辆与地震共同作用的时间变长,在地震波的持续影响下,桥梁的动挠度增加;随着车辆数目的增加,桥梁的动力响应随之增大。该研究对青岛海湾大桥的抗震设计有重要的理论意义。     

The role of regulation in medical student learning in small groups: Regulating oneself and others’ learning and emotions

This study examines the role of regulatory processes in medical students as they learn to deliver bad news to patients in the context of an international web-based problem based learning environment (PBL). In the PBL a medical facilitator and students work together to examine video cases on giving bad news and share their perspectives on what was done effectively and what could be done differently. We examine how regulation occurs within this collaboration. A synchronous computer-supported collaborative learning environment (CSCL) facilitated peer discussion at a distance using a combination of tools that included video-conferencing, chat boxes, and a shared whiteboard to support collaborative engagement. We examine regulation along a continuum, spanning from self- to co-regulation, in situations where medical students learn how to manage their own emotions and adapt their responses to patient reactions. We examine the nature of the discourse between medical students and facilitators to illustrate the conditions in which metacognitive, co-regulation and social emotional activities occur to enhance learning about how to communicate bad news to patients.     

Observer‐based decentralized adaptive control for large‐scale pure‐feedback systems with unknown time‐delayed nonlinear interactions

This paper presents an approximation design for a decentralized adaptive output‐feedback control of large‐scale pure‐feedback nonlinear systems with unknown time‐varying delayed interconnections. The interaction terms are bounded by unknown nonlinear bounding functions including unmeasurable state variables of subsystems. These bounding functions together with the algebraic loop problem of virtual and actual control inputs in the pure‐feedback form make the output‐feedback controller design difficult and challenging. To overcome the design difficulties, the observer‐based dynamic surface memoryless local controller for each subsystem is designed using appropriate Lyapunov‐Krasovskii functionals, the function approximation technique based on neural networks, and the additional first‐order low‐pass filter for the actual control input. It is shown that all signals in the total controlled closed‐loop system are semiglobally uniformly bounded and control errors converge to an adjustable neighborhood of the origin. Finally, simulation examples are provided to illustrate the effectiveness of the proposed decentralized control scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

Molecular interaction networks in the analyses of sequence variation and proteomics data

Protein–protein interaction networks are typically generated in standard cell lines or model organisms as it is prohibitively difficult to record large interaction datasets from specific tissues or disease models at a reasonable pace. Although the interaction data are of high confidence, they thus do not reflect in vivo relationships as such. A wealth of physiologically relevant protein information, obtained under different conditions and from different systems, is available including information on genetic variation, protein levels, and PTMs. However, these data are difficult to assess comprehensively because the relationships between the entities remain elusive from the measurements. Here, we exemplarily highlight recent studies that gained deeper insight from genetic variation, protein, and PTM measurements using interaction information pointing toward the importance and potential of interaction networks for the interpretation of sequencing and proteomics data.