Distinguishing video quality through differential matrices

Multicast multi-layered communications must implement efficient control algorithms to address undesirable network behaviors. This paper proposes two multi-metric algorithms for computing the rates of the video layers and improve the global video quality of a multicast session. In fact, we show that a single-metric approach may degrade some network parameters without obtaining any substantial improvements. Our first algorithm combines three metrics and a set of weights in such a way that one metric can be prioritized. This leads to an improved quality of multicast sessions, as we show through a number of experiments. In networks where the available resources are highly variable, however, the stability of the video quality is compromised if absolute values of the metrics are adopted. We then propose a second algorithm that uses the relative values of the metrics on a per-entry basis. Computation of the global quality of the multicast session is based on a differential matrix that stores the metrics for each receiver. This scheme takes into account the dynamics of the available resources and the heterogeneity of receivers. The great benefit of this approach is that the global video quality is always improved for every loop of the algorithm.     

Reliable Distributed Network Management by Replication

This paper presents a new clustering architecture for SNMP agents that supports semi-active replication of managed objects. A cluster of agents provides fault-tolerant object functionality: replicated managed objects of a crashed agent of a given cluster may be accessed through a peer cluster. The proposed architecture is structured in three layers. The lower layer corresponds to the managed objects at the network elements. The middle layer contains management entities called clusters that monitor and replicate managed objects. The upper layer allows the definition of management clusters as well as the relationship between clusters. A practical tool was implemented and is presented. The impact of replication on network performance is evaluated as well as a probabilistic analysis of replicated object consistency.     

Dietary Apigenin Exerts Immune-Regulatory Activity in Vivo by Reducing NF-κB Activity,Halting Leukocyte Infiltration and Restoring Normal Metabolic Function

The increasing prevalence of inflammatory diseases and the adverse effects associated with the long-term use of current anti-inflammatory therapies prompt the identification of alternative approaches to reestablish immune balance. Apigenin, an abundant dietary flavonoid, is emerging as a potential regulator of inflammation. Here, we show that apigenin has immune-regulatory activity in vivo. Apigenin conferred survival to mice treated with a lethal dose of Lipopolysaccharide (LPS) restoring normal cardiac function and heart mitochondrial Complex I activity. Despite the adverse effects associated with high levels of splenocyte apoptosis in septic models, apigenin had no effect on reducing cell death. However, we found that apigenin decreased LPS-induced apoptosis in lungs, infiltration of inflammatory cells and chemotactic factors’ accumulation, re-establishing normal lung architecture. Using NF-κB luciferase transgenic mice, we found that apigenin effectively modulated NF-κB activity in the lungs, suggesting the ability of dietary compounds to exert immune-regulatory activity in an organ-specific manner. Collectively, these findings provide novel insights into the underlying immune-regulatory mechanisms of dietary nutraceuticals in vivo.     

Antioxidant and antimicrobial activity and potential of heather (Erica spp.) extracts in the control of Listeria monocytogenes

In this work, heather and its flowers were studied regarding their antioxidant and antimicrobial activities. Plants were subjected to ultrasound-assisted methanolic extraction followed by fractionation. A phytochemical characterisation of extracts content in total phenols and flavonoids, and their antioxidant activity was performed. The antimicrobial activity was evaluated through the determination of minimum inhibitory concentration and by bioautography. Following, studies on the antilisterial potential were carried out by: time-kill curves, inhibition of biofilm formation and tolerance of Listeria monocytogenes to adverse conditions. The results evidenced the antioxidant activity in both extracts, as well as, the antimicrobial activity against Gram-positive bacteria. Concerning the evaluation of the antilisterial potential, a bacteriostatic behaviour and inhibition of biofilms formation ability were observed. Listeria monocytogenes showed an increased susceptibility to adverse conditions when preincubated with extracts. Thus, heather and its flowers may be a source of new compounds with antilisterial activity potential.     

Scalable Data Processing for Community Sensing Applications

Participatory Sensing is a new computing paradigm that aims to turn personal mobile devices into advanced mobile sensing networks. For popular applications, we can expect a huge number of users to both contribute with sensor data and request information from the system. In such scenario, scalability of data processing becomes a major issue. In this paper, we present a system for supporting participatory sensing applications that leverages cluster or cloud infrastructures to provide a scalable data processing infrastructure. We propose and evaluate three strategies for data processing in this architecture.