Effects of self-generated facial expressions on mood.

Two experiments were conducted in which participants looked at photographs (Experiment 1, n?=?129) or slides (Experiment 2, n?=?90) of people engaging in positive or negative facial expressions. Participants attempted to communicate these facial expressions as accurately as they could to a video camera while viewing themselves in a mirror or without viewing themselves in a mirror. Participants in a control group maintained neutral facial expressions. Participants experienced increased positive moods when they engaged in positive facial expressions and decreased positive moods when they engaged in negative facial expressions. These effects were enhanced when participants viewed themselves in a mirror. The effects of facial expressions on positive affect were stronger for participants with high private self-consciousness. Results were integrated with research identifying individuals who are responsive to self-produced versus situational cues and with theory and research on self-awareness. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

无线通信技术在沙漠油田安全生产中的应用

介绍无线通信技术在沙漠油田安全生产中的应用。     

Tributary use and large-scale movements of grass carp in Lake Erie

Infrequent captures of invasive, non-native grass carp (Ctenopharyngodon idella) have occurred in Lake Erie over the last 30+ years, with recent evidence suggesting wild reproduction in the lake’s western basin (WB) is occurring. Information on grass carp movements in the Laurentian Great Lakes is lacking, but an improved understanding of large-scale movements and potential areas of aggregation will help inform control strategies and risk assessment if grass carp spread to other parts of Lake Erie and other Great Lakes. Twenty-three grass carp captured in Lake Erie’s WB were implanted with acoustic transmitters and released. Movements were monitored with acoustic receivers deployed throughout Lake Erie and elsewhere in the Great Lakes. Grass carp dispersed up to 236 km, with approximately 25% of fish dispersing greater than 100 km from their release location. Mean daily movements ranged from <0.01 to 2.49 km/day, with the highest daily averages occurring in the spring and summer. The Sandusky, Detroit, and Maumee Rivers, and Plum Creek were the most heavily used WB tributaries. Seventeen percent of grass carp moved into Lake Erie’s central or eastern basins, although all fish eventually returned to the WB. One fish emigrated from Lake Erie through the Huron-Erie Corridor and into Lake Huron. Based on our results, past assessments may have underestimated the potential for grass carp to spread in the Great Lakes. We recommend focusing grass carp control efforts on Sandusky River and Plum Creek given their high use by tagged fish, and secondarily on Maumee and Detroit Rivers.     

模糊模式识别在轨道电路分路不良预警中的应用

针对站内25 Hz相敏轨道电路分路不良问题,通过系统分析,建立轨道电路预警模型,采用模糊模式识别方法实现轨道电路调整电压、现场温湿度以及故障次数的预警,并详细论述了轨道电路模糊模式识别模型的建立,同时给出了预警系统的实现方案;模拟实验及仿真结果表明,模糊模式识别在轨道电路分路不良预警中具有较高的准确性和应用价值,对解决轨道电路分路不良问题提供了有效的技术支持,为轨道电路日常维护和故障的及时发现处理创造了条件.     

基于蚁群优化的WSN能耗均衡链状路由协议

为了从路由技术的角度解决无线传感器网络的能耗问题,综合蚁群优化算法和PEGASIS协议的思想提出了ACO-PEGASIS路由协议;该协议采用蚁群优化算法构建通信链,解决了PEGASIS协议中由于贪婪算法的局部性产生的相邻节点间的长链问题;并在成链过程中综合考虑节点间距离、节点剩余能量等因子,以均衡全网的能量消耗;同时根据距离和能量因素选取链头节点并采用一定措施降低链头重选次数;仿真结果表明,与PEGASIS协议相比,该协议更加有效地均衡了全网的能量消耗,延长了网络的生存周期。     

Enhancing collaborative filtering by user interest expansion via personalized ranking

Recommender systems suggest a few items from many possible choices to the users by understanding their past behaviors. In these systems, the user behaviors are influenced by the hidden interests of the users. Learning to leverage the information about user interests is often critical for making better recommendations. However, existing collaborative-filtering-based recommender systems are usually focused on exploiting the information about the user's interaction with the systems; the information about latent user interests is largely underexplored. To that end, inspired by the topic models, in this paper, we propose a novel collaborative-filtering-based recommender system by user interest expansion via personalized ranking, named iExpand. The goal is to build an item-oriented model-based collaborative-filtering framework. The iExpand method introduces a three-layer, user-interests-item, representation scheme, which leads to more accurate ranking recommendation results with less computation cost and helps the understanding of the interactions among users, items, and user interests. Moreover, iExpand strategically deals with many issues that exist in traditional collaborative-filtering approaches, such as the overspecialization problem and the cold-start problem. Finally, we evaluate iExpand on three benchmark data sets, and experimental results show that iExpand can lead to better ranking performance than state-of-the-art methods with a significant margin.     

A new model of job design: Initial evidence and implications for future research

Clegg and Spencer's (2007) model of job design synthesizes and extends recent conceptions of the job design process by incorporating variables such as knowledge, motivation, and trust into a cyclical and dynamic system. The objective of this study was to examine the sequential organization of variables that comprise the model, as a basis from which to justify further investigations of the model's dynamic properties. Data were collected via questionnaires from 432 participants in two work organizations. Results obtained from structural equation modeling are broadly supportive of the proposed relationships between the variables. Implications of this initial study for future research and practice are discussed. © 2011 Wiley Periodicals, Inc.     

A case of using the Semantic Interoperability Framework for custom orthopedic implants manufacturing

The efficiency and effectiveness of the daily practice in orthopedic surgery depend on the availability, interoperability and unique access to a wide set of information, related to the patient’s medical record and diagnosis, domain knowledge and available resources and staff. The most important of the tangible resources, needed for the therapeutic or preventive actions are orthopedic implants. In some cases, the implants may be highly complex and customized products, which need to be manufactured (assembled) on basis of the above information in a shortest possible timeframe. In this paper, the case of the custom orthopedic implants manufacturing is described from the perspective of the collaborative enterprising, with special consideration of the interoperability issues of the involved enterprise collaboration. It is shown how the previously developed Semantic Interoperability Framework can be used to improve the efficiency of the manufacturing and other relevant processes.     

Biomedical Visual Computing: Case Studies and Challenges

Advances in computational geometric modeling, imaging, and simulation let researchers build and test models of increasing complexity, generating unprecedented amounts of data. As recent research in biomedical applications illustrates, visualization will be critical in making this vast amount of data usable; it's also fundamental to understanding models of complex phenomena.