Is low health literacy associated with overweight and obesity in adolescents: An epidemiology study in a 12-16 years old population, Nanning, China, 2012

© 2014 Lam and Yang. Background: The problem of overweight and obesity in children and adolescents is considered an epidemic in both developed and developing world by the WHO. There has been little study on the relationship between health literacy and body weight among adolescents. This epidemiological study aims to investigate the association between low health literacy and overweight and obesity among a population of Chinese adolescents aged 12-16 years in the city of Nanning, China in 2012. Methods: This study was a population-based cross-sectional health survey utilising a two-stage random cluster sampling design. The sample consisted of high school students aged between 12-16 years with the total student population attending high schools in a large city as the sample frame. Health literacy was measured by the Chinese version of the short form of the Test of Functional Health Literacy translated for and validated among Taiwanese adolescents. Overweight and obesity were assessed in accordance to the recommendation of the World Health Organization (WHO) Global Database of Body Mass Index classification methods. Data were analysed using logistic regression modelling techniques with adjustment to the cluster sampling effect. Results: A total of 1035 students responded to the survey providing usable information with 628 (48.1%) respondents classified as high, 558 (42.8%) moderate, and 119 (9.1%) low levels of health literacy. After adjusting for potential confounding factors and the cluster sampling effect, low health literacy was significantly associated with overweight and obesity (OR = 1.84, 95% C.I. = 1.13-2.99). Conclusion: Results suggested that low health literacy level was associated with many aspects of adolescence health including their body weight. These results have public health implications on an important global problem of adolescence body weight. Enhancing the health literacy should be considered as part of the strategies in combating adolescence weight problem

A trajectory-based recruitment strategy of social sensors for participatory sensing

Participatory sensing, a promising sensing paradigm, enables people to collect and share sensor data on phenomena of interest using mobile devices across many applications, such as smart transportation and air quality monitoring. This article presents a framework of participatory sensing and then focuses on a key technical challenge: developing a trajectory-based recruitment strategy of social sensors in order to enable service providers to identify well suited participants for data sensing based on temporal availability, trust, and energy. To devise a basic recruitment strategy, the Dynamic Tensor Analysis algorithm is initially adopted to learn the time-series tensor of trajectory so that the users' trajectory can be predicted. To guarantee reliable sensing data collection and communication, the trust and energy factors are taken into account jointly in our multi-objective recruitment strategy. In particular, friend-like social sensors are also defined to deal with an emergency during participatory sensing. An illustrative example and experiment are conducted on a university campus to evaluate and demonstrate the feasibility and extensibility of the proposed recruitment strategy

Experimental investigation on the deformation characteristics of granular materials under drained rotational shear

Rotational shear is the type of loading path where samples are subjected to cyclic rotation of principal stress directions while the magnitudes of principal stresses are maintained constant. This paper presents results from an experimental investigation on the drained deformation behaviour of saturated sand in rotational shear conducted in a hollow cylinder apparatus. Two types of granular materials, Leighton Buzzard sand and glass beads are tested. A range of influential factors are investigated including the material density, the deviatoric stress level, and the intermediate principal stress. It is observed that the volumetric strain during rotational shear is mainly contractive and most of strains are generated during the first 20 cycles. The mechanical behaviour of sand under rotational shear is generally non-coaxial, i.e., there is no coincidence between the principal axes of stress and incremental strain, and the variation of the non-coaxiality shows a periodic trend during the tests. The stress ratio has a significant effect on soil response in rotational shear. The larger the stress ratio, the more contractive behaviour and the lower degree of non-coaxiality are induced. The test also demonstrates that the effect of the intermediate principal stress, material density and particle shape on the results is pronounced

Launching an efficient participatory sensing campaign: A smart mobile device-based approach

PublishedJournal Article© 2015 ACM. Participatory sensing is a promising sensing paradigm that enables collection, processing, dissemination and analysis of the phenomena of interest by ordinary citizens through their handheld sensing devices. Participatory sensing has huge potential in many applications, such as smart transportation and air quality monitoring. However, participants may submit low-quality, misleading, inaccurate, or even malicious data if a participatory sensing campaign is not launched effectively. Therefore, it has become a significant issue to establish an efficient participatory sensing campaign for improving the data quality. This article proposes a novel five-tier framework of participatory sensing and addresses several technical challenges in this proposed framework including: (1) optimized deployment of data collection points (DC-points); and (2) efficient recruitment strategy of participants. Toward this end, the deployment of DC-points is formulated as an optimization problem with maximum utilization of sensor and then a Wise-Dynamic DC-points Deployment (WD3) algorithm is designed for high-quality sensing. Furthermore, to guarantee the reliable sensing data collection and communication, a trajectory-based strategy for participant recruitment is proposed to enable campaign organizers to identify well-suited participants for data sensing based on a joint consideration of temporal availability, trust, and energy. Extensive experiments and performance analysis of the proposed framework and associated algorithms are conducted. The results demonstrate that the proposed algorithm can achieve a good sensing coverage with a smaller number of DC-points, and the participants that are termed as social sensors are easily selected, to evaluate the feasibility and extensibility of the proposed recruitment strategies

MobiFuzzyTrust: An efficient fuzzy trust inference mechanism in mobile social networks

PublishedJournal Article© 2014 IEEE. Mobile social networks (MSNs) facilitate connections between mobile users and allow them to find other potential users who have similar interests through mobile devices, communicate with them, and benefit from their information. As MSNs are distributed public virtual social spaces, the available information may not be trustworthy to all. Therefore, mobile users are often at risk since they may not have any prior knowledge about others who are socially connected. To address this problem, trust inference plays a critical role for establishing social links between mobile users in MSNs. Taking into account the nonsemantical representation of trust between users of the existing trust models in social networks, this paper proposes a new fuzzy inference mechanism, namely MobiFuzzyTrust, for inferring trust semantically from one mobile user to another that may not be directly connected in the trust graph of MSNs. First, a mobile context including an intersection of prestige of users, location, time, and social context is constructed. Second, a mobile context aware trust model is devised to evaluate the trust value between two mobile users efficiently. Finally, the fuzzy linguistic technique is used to express the trust between two mobile users and enhance the human's understanding of trust. Real-world mobile dataset is adopted to evaluate the performance of the MobiFuzzyTrust inference mechanism. The experimental results demonstrate that MobiFuzzyTrust can efficiently infer trust with a high precision.This work was partly supported by the National Nature Science Foundation of China under grant 61201219 and the EU FP7 CLIMBER project under Grant Agreement No. PIRSES-GA-2012-318939

Th gme 10: A numerical model to capture the geotechnical response to coal combustion at an underground coal gasification site

A detailed numerical modelling study was carried out to represent geotechnical aspects of the Wieczorek underground coal gasification (UCG) site in Poland. A coupled thermos-mechanical numerical model was created to represent a single coal burning panel. The coal burning proceb was simulated by modifying the energy balance equation with an additional term related to the calorific value of coal as a source. Temperature dependent material properties were abigned to the coupled thermal-mechanical model according to published data. In the model, the burning zone spread about 7.5m laterally after 20 days of burning. Results from the coupled model were used to gauge a worst-case scenario in terms of the potential size of a formed cavity. This data was used within a leb computationally expensive mechanicalonly numerical model in order to evaluate the ground subsidence caused by the worst-case scenario for single and multiple UCG burning panels. The single panel burning resulted in 23mm of ground subsidence at the top of the model after long term coal burning. The ground subsidence measured at the top of the model, at the center point of the gasification arrangement, was approximately 72mm when five panels were burnt with an edge to edge panel distance of 5m; this was increased to 85mm for seven panels. The numerical modelling results have implications to the industrial application of UCG

TransCom: a virtual disk-based cloud computing platform for heterogeneous services

PublishedJournal ArticleThis paper presents the design, implementation, and evaluation of TransCom, a virtual disk (Vdisk) based cloud computing platform that supports heterogeneous services of operating systems (OSes) and their applications in enterprise environments. In TransCom, clients store all data and software, including OS and application software, on Vdisks that correspond to disk images located on centralized servers, while computing tasks are carried out by the clients. Users can choose to boot any client for using the desired OS, including Windows, and access software and data services from Vdisks as usual without consideration of any other tasks, such as installation, maintenance, and management. By centralizing storage yet distributing computing tasks, TransCom can greatly reduce the potential system maintenance and management costs. We have implemented a multi-platform TransCom prototype that supports both Windows and Linux services. The extensive evaluation based on both test-bed experiments and real-usage experiments has demonstrated that TransCom is a feasible, scalable, and efficient solution for successful real-world use. © 2004-2012 IEEE

Entanglement and measurement-induced nonlocality of mixed maximally entangled states in multipartite dynamics

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Joint relay scheduling, channel access, and power allocation for green cognitive radio communications

PublishedJournal Article© 1983-2012 IEEE. The capacity of cognitive radio (CR) systems can be enhanced significantly by deploying relay nodes to exploit the spatial diversity. However, the inevitable imperfect sensing in CR has vital effects on the policy of relay selection, channel access, and power allocation that play pivotal roles in the system capacity. The increase in transmission power can improve the system capacity, but results in high energy consumption, which incurs the increase of carbon emission and network operational cost. Most of the existing schemes for CR systems have not jointly considered the imperfect sensing scenario and the tradeoff between the system capacity and energy consumption. To fill in this gap, this paper proposes an energy-aware centralized relay selection scheme that takes into account the relay selection, channel access, and power allocation jointly in CR with imperfect sensing. Specifically, the CR system is formulated as a partially observable Markov decision process (POMDP) to achieve the goal of balancing the system capacity and energy consumption as well as maximizing the system reward. The optimal policy for relay selection, channel access, and power allocation is then derived by virtue of a dynamic programming approach. A dimension reduction strategy is further applied to reduce its high computation complexity. Extensive simulation experiments and results are presented and analysed to demonstrate the significant performance improvement compared to the existing schemes. The performance results show that the received reward increases more than 50% and the network lifetime increases more than 35%, but the system capacity is reduced less than 6% only.This work was supported by the National Natural Science Foundation of China under Grants 61201219, 61171111, 61472150, and 61173045 and in part by the Fundamental Research Funds for the Central Universities under Grant 2013QN122

Green communication in energy renewable wireless mesh networks: routing, rate control, and power allocation

PublishedJournal Article© 2014 IEEE. The increasing demand for wireless services has led to a severe energy consumption problem with the rising of greenhouse gas emission. While the renewable energy can somehow alleviate this problem, the routing, flow rate, and power still have to be well investigated with the objective of minimizing energy consumption in multi-hop energy renewable wireless mesh networks (ER-WMNs). This paper formulates the problem of network-wide energy consumption minimization under the network throughput constraint as a mixed-integer nonlinear programming problem by jointly optimizing routing, rate control, and power allocation. Moreover, the min-max fairness model is applied to address the fairness issue because the uneven routing problem may incur the sharp reduction of network performance in multi-hop ER-WMNs. Due to the high computational complexity of the formulated mathematical programming problem, an energy-aware multi-path routing algorithm (EARA) is also proposed to deal with the joint control of routing, flow rate, and power allocation in practical multi-hop WMNs. To search the optimal routing, it applies a weighted Dijkstra's shortest path algorithm, where the weight is defined as a function of the power consumption and residual energy of a node. Extensive simulation results are presented to show the performance of the proposed schemes and the effects of energy replenishment rate and network throughput on the network lifetime