174 research outputs found
Conditional Reliability in Uncertain Graphs
Network reliability is a well-studied problem that requires to measure the
probability that a target node is reachable from a source node in a
probabilistic (or uncertain) graph, i.e., a graph where every edge is assigned
a probability of existence. Many approaches and problem variants have been
considered in the literature, all assuming that edge-existence probabilities
are fixed. Nevertheless, in real-world graphs, edge probabilities typically
depend on external conditions. In metabolic networks a protein can be converted
into another protein with some probability depending on the presence of certain
enzymes. In social influence networks the probability that a tweet of some user
will be re-tweeted by her followers depends on whether the tweet contains
specific hashtags. In transportation networks the probability that a network
segment will work properly or not might depend on external conditions such as
weather or time of the day. In this paper we overcome this limitation and focus
on conditional reliability, that is assessing reliability when edge-existence
probabilities depend on a set of conditions. In particular, we study the
problem of determining the k conditions that maximize the reliability between
two nodes. We deeply characterize our problem and show that, even employing
polynomial-time reliability-estimation methods, it is NP-hard, does not admit
any PTAS, and the underlying objective function is non-submodular. We then
devise a practical method that targets both accuracy and efficiency. We also
study natural generalizations of the problem with multiple source and target
nodes. An extensive empirical evaluation on several large, real-life graphs
demonstrates effectiveness and scalability of the proposed methods.Comment: 14 pages, 13 figure
Core Decomposition in Multilayer Networks: Theory, Algorithms, and Applications
Multilayer networks are a powerful paradigm to model complex systems, where
multiple relations occur between the same entities. Despite the keen interest
in a variety of tasks, algorithms, and analyses in this type of network, the
problem of extracting dense subgraphs has remained largely unexplored so far.
In this work we study the problem of core decomposition of a multilayer
network. The multilayer context is much challenging as no total order exists
among multilayer cores; rather, they form a lattice whose size is exponential
in the number of layers. In this setting we devise three algorithms which
differ in the way they visit the core lattice and in their pruning techniques.
We then move a step forward and study the problem of extracting the
inner-most (also known as maximal) cores, i.e., the cores that are not
dominated by any other core in terms of their core index in all the layers.
Inner-most cores are typically orders of magnitude less than all the cores.
Motivated by this, we devise an algorithm that effectively exploits the
maximality property and extracts inner-most cores directly, without first
computing a complete decomposition.
Finally, we showcase the multilayer core-decomposition tool in a variety of
scenarios and problems. We start by considering the problem of densest-subgraph
extraction in multilayer networks. We introduce a definition of multilayer
densest subgraph that trades-off between high density and number of layers in
which the high density holds, and exploit multilayer core decomposition to
approximate this problem with quality guarantees. As further applications, we
show how to utilize multilayer core decomposition to speed-up the extraction of
frequent cross-graph quasi-cliques and to generalize the community-search
problem to the multilayer setting
Protecting entanglement via the quantum Zeno effect
We study the exact entanglement dynamics of two atoms in a lossy resonator.
Besides discussing the steady-state entanglement, we show that in the strong
coupling regime the system-reservoir correlations induce entanglement revivals
and oscillations and propose a strategy to fight against the deterioration of
the entanglement using the quantum Zeno effect.Comment: 4 pages, 3 figure
Surgical Management of Retraction Pockets: Does Mastoidectomy have a Role?
Abstract
Introduction Retraction pocket is a condition in which the eardrum lies deeper within the middle ear. Its management has no consensus in literature.
Objective To assess the role of mastoidectomy in the management of retraction pockets added to a tympanoplasty.
Methods Prospective study of patients with retraction pocket and referred to surgery. The patients were randomly assigned to two groups: one managed with tympanoplasty and mastoidectomy and the other group with tympanoplasty only. The minimum follow-up considered was 12 months. The outcomes were: integrity of eardrum, recurrence, and hearing status.
Results This study included 43 patients. In 24 cases retraction occurred in the posterior half of the eardrum, and in 19 patients there was clinical evidence of ossicular interruption. The two groups of treatment were composed by: 21 patients that underwent tympanoplasty with mastoidectomy and 22 patients had only tympanoplasty. One case of the first group had a recurrence. In 32 cases patients follow up was longer than 48 months. The average air-bone gap changed from 22.1 dB to 5 dB. The percentage of air-bone gap improvement was assessed at 60% in those patients treated with mastoidectomy, and 64.3% in those without it (p > 0.5).
Conclusion Tympanoplasty and ossiculoplasty should be considered to treat atelectatic middle ear and ossicular chain interruption. Mastoidectomy as a way to increase air volume in the ear seems to be a paradox; it does not add favorable prognostic factor to management of retraction pockets
Span-core Decomposition for Temporal Networks: Algorithms and Applications
When analyzing temporal networks, a fundamental task is the identification of
dense structures (i.e., groups of vertices that exhibit a large number of
links), together with their temporal span (i.e., the period of time for which
the high density holds). In this paper we tackle this task by introducing a
notion of temporal core decomposition where each core is associated with two
quantities, its coreness, which quantifies how densely it is connected, and its
span, which is a temporal interval: we call such cores \emph{span-cores}.
For a temporal network defined on a discrete temporal domain , the total
number of time intervals included in is quadratic in , so that the
total number of span-cores is potentially quadratic in as well. Our first
main contribution is an algorithm that, by exploiting containment properties
among span-cores, computes all the span-cores efficiently. Then, we focus on
the problem of finding only the \emph{maximal span-cores}, i.e., span-cores
that are not dominated by any other span-core by both their coreness property
and their span. We devise a very efficient algorithm that exploits theoretical
findings on the maximality condition to directly extract the maximal ones
without computing all span-cores.
Finally, as a third contribution, we introduce the problem of \emph{temporal
community search}, where a set of query vertices is given as input, and the
goal is to find a set of densely-connected subgraphs containing the query
vertices and covering the whole underlying temporal domain . We derive a
connection between this problem and the problem of finding (maximal)
span-cores. Based on this connection, we show how temporal community search can
be solved in polynomial-time via dynamic programming, and how the maximal
span-cores can be profitably exploited to significantly speed-up the basic
algorithm.Comment: ACM Transactions on Knowledge Discovery from Data (TKDD), 2020. arXiv
admin note: substantial text overlap with arXiv:1808.0937
An association of boswellia, betaine and myo-inositol (Eumastós) in the treatment of mammographic breast density. A randomized, double-blind study
Mammographic breast density is a recognized risk factor for breast cancer. The causes that lead to the proliferation of the glandular breast tissue and, therefore, to an increase of breast density are still unclear. However, a treatment strategy to reduce the mammary density may bring about very relevant clinical outcomes in breast cancer prevention. Myo-inositol is a six-fold alcohol of cyclohexane, has already been proved to modulate different pathways: inflammatory, metabolic, oxidative and endocrine processes, in a wide array of human diseases, including cancer and the genesis of mammary gland and breast diseases, like fibrosis, as well as metabolic and endocrine cues. Similarly, boswellic acid and betaine (three-methyl glycine) both inhibit inflammation and exert protective effects on breast physiology. Based on this scientific background, we hypothesized that a combination including, boswellic acid, betaine and myo-inositol would be able to reduce breast density working on different pathways.OBJECTIVE: Mammographic
breast density is a recognized risk factor for
breast cancer. The causes that lead to the proliferation
of the glandular breast tissue and,
therefore, to an increase of breast density are
still unclear. However, a treatment strategy to
reduce the mammary density may bring about
very relevant clinical outcomes in breast cancer
prevention.
Myo-inositol is a six-fold alcohol of cyclohexane,
has already been proved to modulate different
pathways: inflammatory, metabolic, oxidative
and endocrine processes, in a wide array of human
diseases, including cancer and the genesis
of mammary gland and breast diseases, like fibrosis,
as well as metabolic and endocrine cues.
Similarly, boswellic acid and betaine (threemethyl
glycine) both inhibit inflammation and exert
protective effects on breast physiology.
Based on this scientific background, we hypothesized
that a combinat ion including,
boswellic acid, betaine and myo-inositol would
be able to reduce breast density working on
different pathways.
PATIENTS AND METHODS: In this study,
seventy-six premenopausal women were randomly
assigned to the placebo and the experimental
drug arms (Eumastós®) for six months.
RESULTS: After 6 months of treatment, statistically
significant difference between the two
groups was recorded on the breast density reduction
(60% vs. 9%), using mammographic as
well as ultrasound examination.
CONCLUSIONS: Preliminary data collected
here with support the starting assumptions,that the association comprising boswellic acid,
betaine and myo-inositol significantly reduces
mammary density, providing the first evidence
for a new and safe approach for the management
of mammographic density treatment
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