117,914 research outputs found
Endodontic Ni–Ti rotary instruments for Glide-path, Are they still necessary and how to think about the ideal instrument?
No full text: How to cite this article: Reda R, Maccari E, Bhandi S. Endodontic Ni-Ti Rotary Instruments for Glide-path, Are They Still Necessary and How to Think about the Ideal Instrument? J Contemp Dent Pract 2024;25(6):505-506. Keywords: Alloy, Endodontics, Glide Path, NiTi Rotary Instruments, Patency
Il sodalizio tra Bilenchi e Maccari (con un'appendice di testi dispersi di R. Bilenchi)
No full textIl contributo prende in considerazione aspetti significativi dell'amicizia tra Romano Bilenchi e Mino Maccari, mettendo in luce le implicazioni con le scelte letterarie e artistiche dei due intellettuali
The BKT Universality Class in the Presence of Correlated Disorder
No full textThe correct detection of the Berezinskii-Kosterlitz-Thouless (BKT) transition in quasi-two-dimensional superconductors still remains a controversial issue. Its main signatures, indeed, are often at odds with the theoretical expectations. In a recent work (Maccari, I.; Benfatto, L.; Castellani, C. Phys. Rev. B 2017, 96, 060508), we have shown that the presence of spatially correlated disorder plays a key role in this sense because it is the reason underlying the experimentally-observed smearing of the universal superfluid-density jump. In the present paper we closely investigate the effects of correlated disorder on the BKT transition, specifically addressing the issue of whether or not it changes the BKT universality class
On the Performance and Effectiveness of Digital Contact Tracing in the Second Wave of COVID-19 in Italy
No full textContact-tracing smartphone applications have been developed and used as a complement to manual contact tracing in the COVID-19 pandemic. The goal of these apps is to trace contacts between people and notify the mobile phone owners when one of their contacts tested positive. People who receive a notification should behave as exposed people, take a test, and possibly isolate themselves until they receive the result. Unfortunately, identifying contacts based on distance is technically a daunting task: apps can be configured conservatively (a very small number of people are notified, limiting the effectiveness of the app) or they may be more tolerant and produce a high number of notifications but also of false positives. We review the data available from Immuni, the Italian app, which provides detailed figures on the notifications sent and the positive users, and we show that Immuni was configured to generate a very large amount of notifications. We estimate the testing resources that the health system would have needed if the app was downloaded by 100% of the adult population, and every notified person would require a test. In such conditions, Immuni would have generated a number of tests orders of magnitude higher than what was available. We compare the performance of Immuni with the currently available literature on other apps and observe that contact-tracing apps had a limited impact on the second wave of the COVID-19 pandemic. As contact tracing exposes citizens to privacy risks, we discuss some ways to reshape the goal of the apps to achieve a better tradeoff between social benefit and risk
A collaborative firewall for wireless ad-hoc social networks
No full textA collaborative firewall can be realized in a multi-hop distributed wireless network when all or some of the nodes in the network agree on a filtering policy and enforce it when routing a packet. Cooperative firewalling introduces many challenges, how to distribute the rules, how to enforce them, how to reduce the global rule-set in order to limit the impact on the network performance. This paper studies the performance of a collaborative firewall when only a subset of the nodes of the ad-hoc network filter the packets. In order to achieve higher performances the integration with OLSR protocol is proposed. Simulations on realistic scenarios are performed and the source code of the simulator is released
Pharmacophore-based optimization of affinity and selectivity toward a1-adrenergic receptors
No full textNPART+: Improving Wireless Network Topology Generators with Data from the Real World
No full textTopology generators are a key asset for researchers in computer science and telecommunications that often need to test network protocols or distributed systems in simulated environments that resemble real scenarios. Despite that, in the research area of distributed wireless networks still many works use very simplistic models that do not have the characteristics of the currently existing large-scale wireless mesh networks. The only topology generator that tries to produce synthetic graphs that look like real networks is NPART [1].In this work we test the characteristics of NPART against another, completely different approach: TrueNets [2]. TrueNets uses accurate data representing land surface of a real world location to create topologies of networks that could actually exist. The downside of TrueNets is twofold: it can be used only when data-sets are available and generating topologies is computationally intensive. We show that using aggregate data from TrueNets we are able to improve NPART. We call the new generator NPART+ and we show that compared to topologies generated with TrueNets, NPART+ (or its variants) improves NPART in several metrics, but still it can not match the accuracy of TrueNets
On the Properties of Infective Flooding in Low-Duty-Cycle Networks
No full textBroadcasting information in a network is an important function in networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient information broadcasting in mesh networks with low duty-cycling without the need to build a distribution tree. The model provides lower and upper stochastic bounds with high probability. We show that the lower bound is very close to the theoretical optimum and that a preliminary implementation provides results that are very close to the lower bound on classical graph models
Infective flooding in low-duty-cycle networks, properties and bounds
No full textFlooding information is an important function in many networking applications. In some networks, as wireless sensor networks or some ad-hoc networks it is so essential as to dominate the performance of the entire system. Exploiting some recent results based on the distributed computation of the eigenvector centrality of nodes in the network graph and classical dynamic diffusion models on graphs, this paper derives a novel theoretical framework for efficient resource allocation to flood information in mesh networks with low duty-cycling without the need to build a distribution tree or any other distribution overlay. Furthermore, the method requires only local computations based on each node neighborhood. The model provides lower and upper stochastic bounds on the flooding delay averages on all possible sources with high probability. We show that the lower bound is very close to the theoretical optimum. A simulation-based implementation allows the study of specific topologies and graph models as well as scheduling heuristics and packet losses. Simulation experiments show that simple protocols based on our resource allocation strategy can easily achieve results that are very close to the theoretical minimum obtained building optimized overlays on the network
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