Publications by authors named "Ali Faqeeh"

Contact tracing via digital tracking applications installed on mobile phones is an important tool for controlling epidemic spreading. Its effectivity can be quantified by modifying the standard methodology for analyzing percolation and connectivity of contact networks. We apply this framework to networks with varying degree distributions, numbers of application users, and probabilities of quarantine failures.

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Experimental and computational studies provide compelling evidence that neuronal systems are characterized by power-law distributions of neuronal avalanche sizes. This fact is interpreted as an indication that these systems are operating near criticality, and, in turn, typical properties of critical dynamical processes, such as optimal information transmission and stability, are attributed to neuronal systems. The purpose of this Rapid Communication is to show that the presence of power-law distributions for the size of neuronal avalanches is not a sufficient condition for the system to operate near criticality.

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Background: Facet radiofrequency denervation is a prevalent procedure used to try and relieve back pain. Despite the increasing use of this treatment, its effectiveness has been questioned. In consideration of the conflicting reports in the literature, we sought to conduct a trial to study the short-term effect of facet denervation in patients undergoing lumbar laminectomy(s) to determine the short-term effect of adding facet denervation to patients undergoing lumbar laminectomy(s) where the anatomy was exposed, allowing an open technique to be used for the denervation.

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We show that the community structure of a network can be used as a coarse version of its embedding in a hidden space with hyperbolic geometry. The finding emerges from a systematic analysis of several real-world and synthetic networks. We take advantage of the analogy for reinterpreting results originally obtained through network hyperbolic embedding in terms of community structure only.

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Study Design: A case report.

Background: Patients with ankylosing spondylitis have altered spinal biomechanics putting them at increased risk of spinal fractures that are unstable. As a result there is an increasing trend to treat these fractures with surgical stabilization.

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Optimal percolation is the problem of finding the minimal set of nodes whose removal from a network fragments the system into non-extensive disconnected clusters. The solution to this problem is important for strategies of immunization in disease spreading, and influence maximization in opinion dynamics. Optimal percolation has received considerable attention in the context of isolated networks.

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It is commonly assumed in percolation theories that at most one percolating cluster can exist in a network. We show that several coexisting percolating clusters (CPCs) can emerge in networks due to limited mixing, i.e.

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We introduce network L-cloning, a technique for creating ensembles of random networks from any given real-world or artificial network. Each member of the ensemble is an L-cloned network constructed from L copies of the original network. The degree distribution of an L-cloned network and, more importantly, the degree-degree correlation between and beyond nearest neighbors are identical to those of the original network.

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