Network robustness improvement via long-range links

Abstract Many systems are today modelled as complex networks, since this representation has been proven being an effective approach for understanding and controlling many real-world phenomena. A significant area of interest and research is that of networks robustness, which aims to explore to what extent a network keeps working when failures occur in its structure and how disruptions can be avoided. In this paper, we introduce the idea of exploiting long-range links to improve the robustness of Scale-Free (SF) networks. Several experiments are carried out by attacking the networks before and after the addition of links between the farthest nodes, and the results show that this approach effectively improves the SF network correct functionalities better than other commonly used strategies

Learning fine-grained search space pruning and heuristics for combinatorial optimization

Combinatorial optimization problems arise naturally in a wide range of applications from diverse domains. Many of these problems are NP-hard and designing efficient heuristics for them requires considerable time, effort and experimentation. On the other hand, the number of optimization problems in the industry continues to grow. In recent years, machine learning techniques have been explored to address this gap. In this paper, we propose a novel framework for leveraging machine learning techniques to scale-up exact combinatorial optimization algorithms. In contrast to the existing approaches based on deep-learning, reinforcement learning and restricted Boltzmann machines that attempt to directly learn the output of the optimization problem from its input (with limited success), our framework learns the relatively simpler task of pruning the elements in order to reduce the size of the problem instances. In addition, our framework uses only interpretable learning models based on intuitive local features and thus the learning process provides deeper insights into the optimization problem and the instance class, that can be used for designing better heuristics. For the classical maximum clique enumeration problem, we show that our framework can prune a large fraction of the input graph (around 99% of nodes in case of sparse graphs) and still detect almost all of the maximum cliques. Overall, this results in several fold speedups of state-of-the-art algorithms. Furthermore, the classification model used in our framework highlights that the chi-squared value of neighborhood degree has a statistically significant correlation with the presence of a node in a maximum clique, particularly in dense graphs which constitute a significant challenge for modern solvers. We leverage this insight to design a novel heuristic we call ALTHEA for the maximum clique detection problem, outperforming the state-of-the-art for dense graphs.Access provided by IREL Consortium c/o Maynooth University The Library Maynooth Universit

Clinical Behavior of the Gingival Margin following Conservative "Coronally Dynamic" Restorations in the Presence of Non-Carious Cervical Lesions Associated with Gingival Recession: A Pilot Study

Gingival recessions (GR) are often associated with the presence of non-carious cervical lesions (NCCL). The latter result in the disappearance of the cement-enamel junction (CEJ), with consequent difficulties both in measuring the recession itself and in performing root coverage techniques. The restoration of cervical lesions is consequently an important aspect in the treatment of GR, with the re-establishment of a "new" CEJ. This pilot study aimed to verify whether restorative therapy alone, with the execution of a restoration that mimics the convexity of the natural CEJ and thanks to a slight horizontal over-contour, can stabilize a clot in the intrasulcular site and consequently is able to change the position of the gingival margin in a coronal direction. In periodontally healthy patients, with a non-thin gingival phenotype, 10 GR-associated NCCL restorations were performed using a protocol inspired by concepts of prosthetic conditioning, with a progressively reduced convexity ("coronally dynamic restoration") and de-epithelialization of the gingival sulcus. We observed that 70% of the treated teeth showed a reduction in crown length after 15 days (-0.267 mm), without an increase in probing depth. While considering the limitations of the sample and the need to evaluate the different parameters that can affect the result, the coronally dynamic restoration of NCCL with GR was able to influence the position of the gingival margin in a coronal direction

Piavca: a framework for heterogeneous interactions with virtual characters

This paper presents a virtual character animation system for real time multimodal interaction in an immersive virtual reality setting. Human to human interaction is highly multimodal, involving features such as verbal language, tone of voice, facial expression, gestures and gaze. This multimodality means that, in order to simulate social interaction, our characters must be able to handle many different types of interaction, and many different types of animation, simultaneously. Our system is based on a model of animation that represents different types of animations as instantiations of an abstract function representation. This makes it easy to combine different types of animation. It also encourages the creation of behavior out of basic building blocks. making it easy to create and configure new beahviors for novel situations. The model has been implemented in Piavca, an open source character animation system

Intraperitoneal drain placement and outcomes after elective colorectal surgery: international matched, prospective, cohort study

Despite current guidelines, intraperitoneal drain placement after elective colorectal surgery remains widespread. Drains were not associated with earlier detection of intraperitoneal collections, but were associated with prolonged hospital stay and increased risk of surgical-site infections.Background Many surgeons routinely place intraperitoneal drains after elective colorectal surgery. However, enhanced recovery after surgery guidelines recommend against their routine use owing to a lack of clear clinical benefit. This study aimed to describe international variation in intraperitoneal drain placement and the safety of this practice. Methods COMPASS (COMPlicAted intra-abdominal collectionS after colorectal Surgery) was a prospective, international, cohort study which enrolled consecutive adults undergoing elective colorectal surgery (February to March 2020). The primary outcome was the rate of intraperitoneal drain placement. Secondary outcomes included: rate and time to diagnosis of postoperative intraperitoneal collections; rate of surgical site infections (SSIs); time to discharge; and 30-day major postoperative complications (Clavien-Dindo grade at least III). After propensity score matching, multivariable logistic regression and Cox proportional hazards regression were used to estimate the independent association of the secondary outcomes with drain placement. Results Overall, 1805 patients from 22 countries were included (798 women, 44.2 per cent; median age 67.0 years). The drain insertion rate was 51.9 per cent (937 patients). After matching, drains were not associated with reduced rates (odds ratio (OR) 1.33, 95 per cent c.i. 0.79 to 2.23; P = 0.287) or earlier detection (hazard ratio (HR) 0.87, 0.33 to 2.31; P = 0.780) of collections. Although not associated with worse major postoperative complications (OR 1.09, 0.68 to 1.75; P = 0.709), drains were associated with delayed hospital discharge (HR 0.58, 0.52 to 0.66; P < 0.001) and an increased risk of SSIs (OR 2.47, 1.50 to 4.05; P < 0.001). Conclusion Intraperitoneal drain placement after elective colorectal surgery is not associated with earlier detection of postoperative collections, but prolongs hospital stay and increases SSI risk

Search for Eccentric Black Hole Coalescences during the Third Observing Run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass $M>70$ $M_\odot$) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities $0 < e \leq 0.3$ at $0.33$ Gpc$^{-3}$ yr$^{-1}$ at 90\% confidence level.Comment: 24 pages, 5 figure