263 research outputs found
Consensus Computation in Unreliable Networks: A System Theoretic Approach
This work addresses the problem of ensuring trustworthy computation in a
linear consensus network. A solution to this problem is relevant for several
tasks in multi-agent systems including motion coordination, clock
synchronization, and cooperative estimation. In a linear consensus network, we
allow for the presence of misbehaving agents, whose behavior deviate from the
nominal consensus evolution. We model misbehaviors as unknown and unmeasurable
inputs affecting the network, and we cast the misbehavior detection and
identification problem into an unknown-input system theoretic framework. We
consider two extreme cases of misbehaving agents, namely faulty (non-colluding)
and malicious (Byzantine) agents. First, we characterize the set of inputs that
allow misbehaving agents to affect the consensus network while remaining
undetected and/or unidentified from certain observing agents. Second, we
provide worst-case bounds for the number of concurrent faulty or malicious
agents that can be detected and identified. Precisely, the consensus network
needs to be 2k+1 (resp. k+1) connected for k malicious (resp. faulty) agents to
be generically detectable and identifiable by every well behaving agent. Third,
we quantify the effect of undetectable inputs on the final consensus value.
Fourth, we design three algorithms to detect and identify misbehaving agents.
The first and the second algorithm apply fault detection techniques, and
affords complete detection and identification if global knowledge of the
network is available to each agent, at a high computational cost. The third
algorithm is designed to exploit the presence in the network of weakly
interconnected subparts, and provides local detection and identification of
misbehaving agents whose behavior deviates more than a threshold, which is
quantified in terms of the interconnection structure
Controllability Metrics, Limitations and Algorithms for Complex Networks
This paper studies the problem of controlling complex networks, that is, the
joint problem of selecting a set of control nodes and of designing a control
input to steer a network to a target state. For this problem (i) we propose a
metric to quantify the difficulty of the control problem as a function of the
required control energy, (ii) we derive bounds based on the system dynamics
(network topology and weights) to characterize the tradeoff between the control
energy and the number of control nodes, and (iii) we propose an open-loop
control strategy with performance guarantees. In our strategy we select control
nodes by relying on network partitioning, and we design the control input by
leveraging optimal and distributed control techniques. Our findings show
several control limitations and properties. For instance, for Schur stable and
symmetric networks: (i) if the number of control nodes is constant, then the
control energy increases exponentially with the number of network nodes, (ii)
if the number of control nodes is a fixed fraction of the network nodes, then
certain networks can be controlled with constant energy independently of the
network dimension, and (iii) clustered networks may be easier to control
because, for sufficiently many control nodes, the control energy depends only
on the controllability properties of the clusters and on their coupling
strength. We validate our results with examples from power networks, social
networks, and epidemics spreading
Studio di farmacogenetica di cisplatino e radioterapia nei pazienti affetti da carcinoma della regione testa-collo
Lo scopo di questa tesi di dottorato è stato quello di correlare i polimrfosmi di alcuni geni coinvolti nella riparazione del danno indotto alla molecola di DNA da cisplatino e dalle radiazioni ionizzanti con la storia clinica di pazienti affetti da tumori della regione testa collo trattati con radio o radiochemioterapi
Molecular and taxonomic characterization of a endophytic fungus isolated from Helleborus bocconei subsp. intermedius (Ranunculaceae)
A non-sporulating fungus was isolated from different organs of Helleborus bocconei subsp. intermedius (Ranunculaceae) endemic to southern Italy and Sicily, known for the traditional use of dried roots in the treatment of lung diseases of cattle and horses.
Molecular characterization of endophytic fungus based on the internal transcribed spacer (ITS) region of the rRNA gene sequences was done. The DNA sequence of full length ITS region of the studied fungus was a 100% match to that of Chaetomium strumarium strain dH 21642 (GenBank accession number JX280851.1). The morphological characters of colony and mycelium of this microfungus are reported here
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