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    Lactobacillus Cell Surface Proteins Involved in Interaction with Mucus and Extracellular Matrix Components

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    The gut microbiota is a complex microbial ecosystem where bacteria, through mutual interactions, cooperate in maintaining of wellbeing and health. Lactobacilli are among the most important constituents of human and animal intestinal microbiota and include many probiotic strains. Their presence ensures protection from invasion of pathogens, as well as stimulation of the immune system and protection of the intestinal flora, often exerted through the ability to interact with mucus and extracellular matrix components. The main factors responsible for mediating adhesion of pathogens and commensals to the gut are cell surface proteins that recognize host targets, as mucus layer and extracellular matrix proteins. In the last years, several adhesins have been reported to be involved in lactobacilli–host interaction often miming the same mechanism used by pathogens

    On the Properties of TCP Flow Arrival Process

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    We study the TCP flow arrival process, starting from the aggregated measurement at the TCP flow level taken from our campus network. In particular, we analyze the statistical properties of the TCP flow arrival process. We define the different traffic aggregates by splitting the original trace, such that i) each of them is constituted by all the TCP flows belonging to the same traffic relation, i.e., with the same source/destination IP addresses and ii) each traffic aggregate has, bytewise, the same amount of traffic. To induce a divisions of TCP-elephants and TCP-mice into different traffic aggregates, the used algorithm packs the largest traffic relations in the first traffic aggregates, so that subsequently generated aggregates are constituted by an increasing number of smaller traffic relations. The long range dependency (LRD) characteristics are presented, showing the possible causes of the LRD of TCP flow arrival process in i) the heavy tailed distribution of the number of flows in a traffic aggregate, and ii) the presence of TCP-elephants within them

    TCP anomalies: identification and analysis

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    Passive measurements have recently received large attention from the scientific community as a mean, not only for traffic characterization, but also to infer critical protocol behaviors and network working conditions. In this paper we focus on passive measurements of TCP traffic, main component of nowadays traffic. In particular, we propose a heuristic technique for the classification of the anomalies that may occur during the lifetime of a connection. Since TCP is a closed-loop protocol that infers network conditions and reacts accordingly by means of losses, the possibility of carefully distinguishing the causes of anomalies in TCP traffic is very appealing and may be instrumental to the deep understanding of TCP behavior in real environments and the protocol engineering
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