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Abstract: Sybil attacks have been regarded as a serious security threat to Ad hoc Networks and Sensor Networks. They may also impair the potential applications in Vehicular Ad hoc Networks (VANETs) by creating an illusion of traffic congestion. In this paper, we make various attempts to explore the feasibility of detecting Sybil attacks by analyzing signal strength distribution. First, we propose a cooperative method to verify the positions of potential Sybil nodes. We use a Random Sample Consensus (RANSAC)-based algorithm to make this cooperative method more robust against outlier data fabricated by Sybil nodes. However, several inherent drawbacks of this cooperative method prompt us to explore additional approaches. We introduce a statistical method and design a system which is able to verify where a vehicle comes from. The system is termed the Presence Evidence System (PES). With PES, we are able to enhance the detection accuracy using statistical analysis over an observation period. Finally, based on realistic US maps and traffic models, we conducted simulations to evaluate the feasibility and efficiency of our methods. Our scheme proves to be an economical approach to suppressing Sybil attacks without extra support from specific positioning hardware. [Copyright &y& Elsevier]

Abstract: Cloud computing is emerging as an increasingly important service-oriented computing paradigm. Management is a key to providing accurate service availability and performance data, as well as enabling real-time provisioning that automatically provides the capacity needed to meet service demands. In this paper, we present a unified reinforcement learning approach, namely URL, to automate the configuration processes of virtualized machines and appliances running in the virtual machines. The approach lends itself to the application of real-time autoconfiguration of clouds. It also makes it possible to adapt the VM resource budget and appliance parameter settings to the cloud dynamics and the changing workload to provide service quality assurance. In particular, the approach has the flexibility to make a good trade-off between system-wide utilization objectives and appliance-specific SLA optimization goals. Experimental results on Xen VMs with various workloads demonstrate the effectiveness of the approach. It can drive the system into an optimal or near-optimal configuration setting in a few trial-and-error iterations. [Copyright &y& Elsevier]

Abstract: Networked computing systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these environments. Moreover, failure events exhibit strong correlations in the time and space domains. In this paper, we develop a spherical covariance model with an adjustable timescale parameter to quantify the temporal correlation and a stochastic model to characterize spatial correlation. The models are further extended to take into account the information of application allocation to discover more correlations among failure instances. We cluster failure events based on their correlations and predict their future occurrences. Experimental results on a production coalition system, the Wayne State Computational Grid, show the offline and online predictions made by our predicting system can forecast 72.7–85.3% of the failure occurrences and capture failure correlations in a cluster coalition environment. [Copyright &y& Elsevier]

Abstract: Distributed hash table (DHT) networks based on consistent hashing functions have an inherent load uneven distribution problem. The objective of DHT load balancing is to balance the workload of the network nodes in proportion to their capacity so as to eliminate traffic bottleneck. It is challenging because of the dynamism, proximity and heterogeneity natures of DHT networks and time-varying load characteristics. In this paper, we present a hash-based proximity clustering approach for load balancing in heterogeneous DHTs. In the approach, DHT nodes are classified as regular nodes and supernodes according to their computing and networking capacities. Regular nodes are grouped and associated with supernodes via consistent hashing of their physical proximity information on the Internet. The supernodes form a self-organized and churn-resilient auxiliary network for load balancing. The hierarchical structure facilitates the design and implementation of a locality-aware randomized (LAR) load balancing algorithm. The algorithm introduces a factor of randomness in the load balancing processes in a range of neighborhood so as to deal with both the proximity and dynamism. Simulation results show the superiority of the clustering approach with LAR, in comparison with a number of other DHT load balancing algorithms. The approach performs no worse than existing proximity-aware algorithms and exhibits strong resilience to the effect of churn. It also greatly reduces the overhead of resilient randomized load balancing due to the use of proximity information. [Copyright &y& Elsevier]

Abstract: The mesencephalic trigeminal nucleus (Me5) innervates muscle spindles and is responsible for receiving and transmitting proprioception from the oro-facial region. Molecular mechanisms underlying the development of the Me5 are poorly understood. Evidence is provided here that transcription factor Drg11 is required for Me5 development. Drg11 was expressed in the Me5 cells of the embryonic and early postnatal mouse brains, and the Me5 cells were absent in Drg11 −/− mice at birth. The absence of the Me5 cells in Drg11 −/− mice appeared to be caused by increased cell death in the Me5 during embryonic development. In postnatal Drg11 −/− mice, Me5 cell innervation of masseter muscle spindles was undetectable, while robust trigeminal motoneuron innervation of masseter muscle fibers was detected. The postnatal body weight of Drg11 −/− mice was notably less than that of wild-type mice, and this might result, in part, from disruption of the oro-facial proprioceptive afferent pathway. Taken together, our results demonstrate an essential role for Drg11 in the development of the Me5. [Copyright &y& Elsevier]

Abstract: Virtualization provides a vehicle to manage the available resources and enhance their utilization in network computing. System dynamics requires virtual machines be distributed and reconfigurable. To construct reconfigurable distributed virtual machines, service migration moves the runtime services among physical servers when necessary. By incorporating the mobile agent technology, distributed virtual machines can improve their resource utilization and service availability significantly. This paper focuses on finding the optimal migration policies for service and agent migrations for high throughput in reconfigurable distributed virtual machines. We analyze three issues of this decision problem: migration candidate determination, migration timing and destination server selection. The service migration timing and destination server selection are formulated by two optimization models. We derive the optimal migration policy for distributed and heterogenous systems based on stochastic optimization theories. Renewal processes are applied to model the dynamics of migration. We solve the agent migration problem by dynamic programming and extend the optimal service migration decision by considering the interplay of the hybrid mobility. We verify the accuracy of our migration decision policy in simulations. [Copyright &y& Elsevier]

Dynamic remapping is critical to the performance of bulk synchronous computations that have non-deterministic behaviors because of the need of barrier synchronization between phases. There are two basic issues in remapping: when and how to remap. This paper presents a formal analysis of the issue of when to remap for dynamic computations with a priori known statistical behaviors, with an objective of finding optimal remapping frequencies for a given tolerance of load imbalance. The problem is formulated as two complement sequential stochastic optimization. Since general optimization techniques tend to reveal stationary properties of the workload process, they are not readily applicable to the analysis of the effect of periodic remapping. Instead, this paper develops new analytical approaches to precisely characterize the transient statistical behaviors of the workload process on both homogeneous and heterogeneous machines. Optimal remapping frequencies are derived for various random workload change processes with known or unknown probabilistic distributions. They are shown accurate via simulations. [Copyright &y& Elsevier]

Abstract: According to the pay-per-use model adopted in clouds, the more resources an application running in a cloud computing environment consumes, the greater the amount of money the owner of the corresponding application will be charged. Therefore, applying intelligent solutions to minimize the resource consumption is of great importance. In this paper, we study the problem of identifying an assignment scheme between the interacting components of an application, such as processes and virtual machines, and the computing nodes of a cloud system, such that the total amount of resources consumed by the respective application is minimized. Because centralized solutions are deemed unsuitable for large distributed systems or large-scale applications, we propose a fully distributed algorithm (called DRA) to overcome scalability issues. DRA takes decisions concerning the transition from one assignment scheme to another in a dynamic way, based solely on local information. We also propose and test two modifications of the basic DRA algorithm to deal better with the heterogeneity of cloud servers in terms of capacity constraints. We must note that we capture heterogeneity regarding the network model. Through theoretical analysis, we formally prove that DRA achieves convergence and always provides an optimal solution for tree-based networks in the uncapacitated case. Moreover, we prove through experimental evaluation that DRA achieves up to 55% network cost reduction when compared to the most recent algorithm in the literature. We also show that the proposed modifications of DRA improve the algorithm’s performance considerably in the case where servers have limited capacity. [Copyright &y& Elsevier]

Abstract: We test a two-stage compensation mechanism for promoting cooperation in Prisoner''s Dilemma games. Players first simultaneously choose binding non-negative amounts to pay their counterparts for cooperating, and then play the induced game knowing these amounts. In our games, all payment pairs consistent with mutual cooperation in subgame-perfect equilibrium transform these games into coordination games, with both mutual cooperation and mutual defection as Nash equilibria in the second stage. When endogenous transfer payments are not permitted, cooperation is much less likely. Mutual cooperation is most likely when the (sufficient) payments are identical, and it is also substantially more likely with payment pairs that bring the mutual-cooperation payoffs closer together. Both the Fehr–Schmidt and Charness–Rabin models predict that transfers that make final payoffs closer are preferred; however, they do not explain why equal transfers are particularly effective. Transfers are also effective in sustaining cooperation even when they are imposed and not chosen. [Copyright &y& Elsevier]

The CXCL12/CXCR4 axis is strongly implicated as key determinant of tumor invasion and metastasis in ovarian cancer. However, little is known about the potential downstream signals of the CXCL12/CXCR4 axis that contribute to ovarian cancer cell invasion and metastasis. ARHGAP10, a member of Rho GTPase activating proteins is a potential tumor suppressor gene in ovarian cancer. In this study, a negative correlation between the protein levels of CXCL12, CXCR4, vascular endothelial growth factor (VEGF), vascular endothelial growth factor receptor-2 (VEGFR2) and ARHGAP10 was uncovered in ovarian cancer tissues and paired adjacent noncancerous tissues. CXCL12 stimulation reduced the expression of ARHGAP10. Furthermore, the pretreatment of CXCR4 inhibitor (AMD3100) or the vascular endothelial growth factor receptor-2 (VEGFR2) inhibitor (SU1498) abrogated the CXCL12-deduced expression of ARHGAP10. Finally, an in vitro functional assay revealed that CXCL12 did not stimulate ovarian cancer cell invasion when ARHGAP10 was overexpressed or when ovarian cancer cells were pre-treated with AMD3100 or SU1498. Knockdown of ARHGAP10 significantly suppressed the inhibitory effects of SU1498 on ovarian cancer cell invasion and lung metastasis. In summary, these findings suggest that CXCL12/CXCR4 promotes ovarian cancer cell invasion by suppressing ARHGAP10 expression, which is mediated by VEGF/VEGFR2 signaling. • ARHGAP10 was negativley correlated with CXCL12, CXCR4, VEGF and VEGFR2 in ovarian tissues. • ARHGAP10 overexpression, CXCR4 inhibitor or VEGFR2 inhibitor inhibited CXCL12-induced ovarian cell invasion. • Knockdown of ARHGAP10 suppressed the inhibitory effects of VEGFR2 inhibitor on cell invasion. [ABSTRACT FROM AUTHOR]

Abstract Interleukin-12 receptor β2 (IL-12Rβ2) is a signaling subunit of heterodimeric receptors for IL-12 and IL-35. It plays important regulatory functions in the development of Th1 cells and in the expression of inflammatory cytokines in mammals and other higher vertebrates. However, little is known about IL-12Rβ2 in teleost fish. In this work, we have cloned and characterized IL-12Rβ2 from grass carp (Ctenopharyngodon idella). The full-length cDNA of grass carp IL-12Rβ2 is 2875 bp, which encodes a mature protein with 741 amino acids. This mature protein contains three fibronectin type III domains, a transmembrane helix, and CXW and WSXWS-like motifs that are characteristic of the type I cytokine receptor family. Phylogenetic analysis revealed that cyprinid fish IL-12Rβ2 formed a single branch, clearly separated from those of other vertebrates. We expressed and purified a recombinant grass carp IL-12Rβ2 protein containing major antigenic regions, which was used to raise a polyclonal antibody. The specificity of the antibody was assessed by Western blotting analysis of whole cell lysates from Escherichia coli cells expressing the recombinant IL-12Rβ2, grass carp intestinal intraepithelial lymphocytes, and cultured C. idella kidney cells. To explore the potential regulatory role of IL-12Rβ2 in inflammation, we generated an intestinal inflammation model by anal intubation of fish with Aeromonas hydrophila. Immunohistochemical staining of the inflamed intestines revealed that IL-12Rβ2 expression is consistent with inflammatory cell recruitment during intestinal inflammation. Real-time quantitative PCR revealed that IL-12Rβ2 is widely expressed in normal tissues and is up-regulated in most tissues after infecting with A. hydrophila. We found that IL-12Rβ2, IL-12p35, and interferon-γ were expressed in similar patterns in the intestines during inflammation. Taken together, our results suggest that IL-12Rβ2 is involved in the regulation of intestinal inflammation. Highlights • The full-length cDNA encoding fish IL-12Rβ2 was cloned by RACE techniques. • IL-12Rβ2 is involved in Aeromonas hydrophila -induced intestinal inflammation. • IL-12Rβ2 is up-regulated in most tissues one day after A. hydrophila infection. • IL-12Rβ2, IL-12p35, and IFN-γ are expressed in similar patterns during inflammation. [ABSTRACT FROM AUTHOR]

Abstract Minimizing energy consumption and network load is a major challenge for network-on-chip (NoC) based multi-processor systems-on-chip (MPSoCs). Efficient task and core mapping can greatly reduce the overall energy consumption and communication overhead among the interdependent tasks. In this paper, we propose a novel Knapsack based bin packing algorithm for workload consolidation that places tasks in such a manner that utilization of available processing elements is maximized, while network overhead, regarding the communication among the tasks, is minimized. We also propose a task swapping algorithm that attempts to further optimize the task placement produced by the bin packing algorithms. Moreover, several core mapping techniques are implemented and the performance of each technique is evaluated under varying configurations. In addition, we also apply a Pareto-efficient algorithm, on top of the bin packing algorithms, attempting to explore the solution in two dimensions, i.e., energy consumption and network load. The experimental results show that the proposed Knapsack based bin packing algorithm coupled with the Pareto-efficient algorithm achieves significant energy savings and reduction in network load as compared to state-of-the-art algorithms, as well as the greedy algorithm. Particularly, the Pareto-efficient algorithm when applied on top of the Knapsack algorithm shows on average 50% and 55% reduction in energy consumption and network load as compared to the greedy algorithm, respectively. While the proposed Pareto-efficient algorithm applied with Knapsack algorithm also demonstrate superior performance compared to three other state-of-the-art heuristics. Highlights • Introduce a new class of bin packing problem, i.e., variable benefit bin packing. • A Knapsack based bin packing algorithm is proposed for workload consolidation. • Proposed Knapsack algorithm reduces both energy consumption and network load. • Various mapping heuristics are proposed to map the bins onto cores of MPSoC. • Pareto-efficient algorithm to explore solutions in two dimensions simultaneously. [ABSTRACT FROM AUTHOR]

A novel 1(2), 2(18)-di seco indole diterpenoid , drechmerin H ( 1 ), was isolated from the fermentation broth of Drechmeria sp. together with a new indole diterpenoid, 2′- epi terpendole A ( 3 ), and a known analogue, terpendole A ( 2 ). Their structures were determined by HRESIMS, 1D and 2D NMR, ECD, and X-ray single crystal diffraction analyses as well as quantum chemical calculation. The abosulte configuration of terpendole A ( 2 ) was determined for the first time. Compound 1 displayed the significant agonistic effect on pregnane X receptor (PXR) with EC 50 value of 134.91 ± 2.01 nM, and its interaction with PXR was investigated by molecular docking. Meantime, a plausible biosynthetic pathway for compounds 1–3 is also discussed in the present work. [ABSTRACT FROM AUTHOR]

Abstract: The Middle East respiratory syndrome coronavirus (MERS-CoV) closely resembled severe acute respiratory syndrome coronavirus (SARS-CoV) in disease manifestation as rapidly progressive acute pneumonia with multi-organ dysfunction. Using monocyte-derived-dendritic cells (Mo-DCs), we discovered fundamental discrepancies in the outcome of MERS‐CoV‐ and SARS-CoV-infection. First, MERS-CoV productively infected Mo-DCs while SARS-CoV-infection was abortive. Second, MERS-CoV induced significantly higher levels of IFN-γ, IP-10, IL-12, and RANTES expression than SARS-CoV. Third, MERS-CoV-infection induced higher surface expression of MHC class II (HLA-DR) and the co-stimulatory molecule CD86 than SARS-CoV-infection. Overall, our data suggests that the dendritic cell can serve as an important target of viral replication and a vehicle for dissemination. MERS-CoV-infection in DCs results in the production of a rich combination of cytokines and chemokines, and modulates innate immune response differently from that of SARS-CoV-infection. Our findings may help to explain the apparent discrepancy in the pathogenicity between MERS-CoV and SARS-CoV. [Copyright &y& Elsevier]