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

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

A tensor-based approach for big data representation and dimensionality reduction

PublishedJournal Article© 2013 IEEE. Variety and veracity are two distinct characteristics of large-scale and heterogeneous data. It has been a great challenge to efficiently represent and process big data with a unified scheme. In this paper, a unified tensor model is proposed to represent the unstructured, semistructured, and structured data. With tensor extension operator, various types of data are represented as subtensors and then are merged to a unified tensor. In order to extract the core tensor which is small but contains valuable information, an incremental high order singular value decomposition (IHOSVD) method is presented. By recursively applying the incremental matrix decomposition algorithm, IHOSVD is able to update the orthogonal bases and compute the new core tensor. Analyzes in terms of time complexity, memory usage, and approximation accuracy of the proposed method are provided in this paper. A case study illustrates that approximate data reconstructed from the core set containing 18% elements can guarantee 93% accuracy in general. Theoretical analyzes and experimental results demonstrate that the proposed unified tensor model and IHOSVD method are efficient for big data representation and dimensionality reduction

Crosstalk between astrocytic CXCL12 and microglial CXCR4 contributes to the development of neuropathic pain

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An optimized computational model for multi-community-cloud social collaboration

PublishedCommunity Cloud Computing is an emerging and promising computing model for a specific community with common concerns, such as security, compliance and jurisdiction. It utilizes the spare resources of networked computers to provide the facilities so that the community gains services from the cloud. The effective collaboration among the community clouds offers a powerful computing capacity for complex tasks containing the subtasks that need data exchange. Selecting the best group of community clouds that are the most economy-efficient, communication-efficient, secured, and trusted to accomplish a complex task is very challenging. To address this problem, we first formulate a computational model for multi-community-cloud collaboration, namely MG3. The proposed model is then optimized from four aspects: minimizing the sum of access cost and monetary cost, maximizing the security-level agreement and trust among the community clouds. Furthermore, an efficient and comprehensive selection algorithm is devised to extract the best group of community clouds in MG3. Finally, the extensive simulation experiments and performance analysis of the proposed algorithm are conducted. The results demonstrate that the proposed algorithm outperforms the minimal set coverings based algorithm and the random algorithm. Moreover, the proposed comprehensive community clouds selection algorithm can guarantee good global performance in terms of access cost, monetary cost, security level and trust between user and community clouds

Central administration of C-x-C chemokine receptor type 4 antagonist alleviates the development and maintenance of peripheral neuropathic pain in mice

Aim To explore the roles of C-X-C chemokine receptor type 4 (CXCR4) in spinal processing of neuropathic pain at the central nervous system (CNS). Methods Peripheral neuropathic pain (PNP) induced by partial sciatic nerve ligation (pSNL) model was assessed in mice. Effects of a single intrathecal (central) administration of AMD3100 (intrathecal AMD3100), a CXCR4 antagonist, on pain behavior and pain-related spinal pathways and molecules in the L3-L5 spinal cord segment was studied compare to saline treatment. Results Rotarod test showed that intrathecal AMD3100 did not impair mice motor function. In pSNL-induced mice, intrathecal AMD3100 delayed the development of mechanical allodynia and reversed the established mechanical allodynia in a dose-dependent way. Moreover, intrathecal AMD3100 downregulated the activation of JNK1 and p38 pathways and the protein expression of p65 as assessed by western blotting. Real-time PCR test also demonstrated that substance P mRNA was decreased, while adrenomedullin and intercellular adhesion molecule mRNA was increased following AMD3100 treatment. Conclusion Our results suggest that central (spinal) CXCR4 is involved in the development and maintenance of PNP and the regulation of multiple spinal molecular events under pain condition, implicating that CXCR4 would potentially be a therapeutic target for chronic neuropathic pain.published_or_final_versio

The actin-myosin regulatory MRCK kinases: regulation, biological functions and associations with human cancer

The contractile actin-myosin cytoskeleton provides much of the force required for numerous cellular activities such as motility, adhesion, cytokinesis and changes in morphology. Key elements that respond to various signal pathways are the myosin II regulatory light chains (MLC), which participate in actin-myosin contraction by modulating the ATPase activity and consequent contractile force generation mediated by myosin heavy chain heads. Considerable effort has focussed on the role of MLC kinases, and yet the contributions of the myotonic dystrophy-related Cdc42-binding kinases (MRCK) proteins in MLC phosphorylation and cytoskeleton regulation have not been well characterized. In contrast to the closely related ROCK1 and ROCK2 kinases that are regulated by the RhoA and RhoC GTPases, there is relatively little information about the CDC42-regulated MRCKα, MRCKβ and MRCKγ members of the AGC (PKA, PKG and PKC) kinase family. As well as differences in upstream activation pathways, MRCK and ROCK kinases apparently differ in the way that they spatially regulate MLC phosphorylation, which ultimately affects their influence on the organization and dynamics of the actin-myosin cytoskeleton. In this review, we will summarize the MRCK protein structures, expression patterns, small molecule inhibitors, biological functions and associations with human diseases such as cancer

A novel asynchronous access method with binary interfaces

© 2008 Silva et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Infant feeding counselling in Uganda in a changing environment with focus on the general population and HIV-positive mothers - a mixed method approach

<p>Abstract</p> <p>Background</p> <p>Health workers' counselling practices are essential to improve infant feeding practices. This paper will assess how infant feeding counselling was done and experienced by counsellors and mothers in Eastern Uganda in the context of previous guidelines. This has implications for implementation of the new infant feeding guidelines from 2009.</p> <p>Methods</p> <p>This paper combines qualitative and quantitative data from Mbale District in Eastern Uganda. Data was collected from 2003 to 2005 in a mixed methods approach. This includes: key-informant interviews among eighteen health workers in the public hospital, health clinics and non-governmental organisations working with people living with HIV, fifteen focus group discussions in the general population and among clients from an HIV clinic, two cross-sectional surveys including 727 mothers from the general population and 235 HIV-positive mothers.</p> <p>Results</p> <p>The counselling sessions were often improvised. Health workers frequently had pragmatic approaches to infant feeding as many clients struggled with poverty, stigma and non-disclosure of HIV. The feasibility of the infant feeding recommendations was perceived as challenging among health workers, both for HIV-positive mothers and in the general population. Group counselling with large groups was common in the public health service. Some extra infant feeding teaching capacities were mobilised for care-takers of undernourished children. A tendency to simplify messages giving one-sided information was seen. Different health workers presented contradicting simplified perspectives in some cases. Outdated training was a common concern with many health workers not being given courses or seminars on infant feeding since professional graduation. Other problems were minimal staffing, lack of resources, and programs being started and subsequently stopped abruptly. Many of the HIV-counsellors in the non-governmental organisations got extended training in counselling which seemed to be beneficial.</p> <p>Conclusions</p> <p>Health workers were faced with challenges related to workload, resources, scientific updating, and also a need to adjust to frequent changes in programs, recommendations and guidelines. The clients were faced with difficult choices, poverty, lack of education and stigma. Feasibility of the recommendations was a major concern. Systematic approaches to update health workers should be a priority.</p