NodeSig{\rm N{\small ode}S{\small ig}}: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings

Learning node representations is a crucial task with a plethora of interdisciplinary applications. Nevertheless, as the size of the networks increases, most widely used models face computational challenges to scale to large networks. While there is a recent effort towards designing algorithms that solely deal with scalability issues, most of them behave poorly in terms of accuracy on downstream tasks. In this paper, we aim at studying models that balance the trade-off between efficiency and accuracy. In particular, we propose ${\rm N{\small ode}S{\small ig}}$, a scalable embedding model that computes binary node representations. ${\rm N{\small ode}S{\small ig}}$ exploits random walk diffusion probabilities via stable random projection hashing, towards efficiently computing embeddings in the Hamming space. Our extensive experimental evaluation on various graphs has demonstrated that the proposed model achieves a good balance between accuracy and efficiency compared to well-known baseline models on two downstream tasks

RELINE: Point-of-Interest Recommendations using Multiple Network Embeddings

The rapid growth of users' involvement in Location-Based Social Networks (LBSNs) has led to the expeditious growth of the data on a global scale. The need of accessing and retrieving relevant information close to users' preferences is an open problem which continuously raises new challenges for recommendation systems. The exploitation of Points-of-Interest (POIs) recommendation by existing models is inadequate due to the sparsity and the cold start problems. To overcome these problems many models were proposed in the literature, but most of them ignore important factors such as: geographical proximity, social influence, or temporal and preference dynamics, which tackle their accuracy while personalize their recommendations. In this work, we investigate these problems and present a unified model that jointly learns users and POI dynamics. Our proposal is termed RELINE (REcommendations with muLtIple Network Embeddings). More specifically, RELINE captures: i) the social, ii) the geographical, iii) the temporal influence, and iv) the users' preference dynamics, by embedding eight relational graphs into one shared latent space. We have evaluated our approach against state-of-the-art methods with three large real-world datasets in terms of accuracy. Additionally, we have examined the effectiveness of our approach against the cold-start problem. Performance evaluation results demonstrate that significant performance improvement is achieved in comparison to existing state-of-the-art methods

Prevention of orthodontic enamel demineralization: a systematic review with meta‐analyses

Aim of this systematic review was to assess the efficacy of preventive interventions against the development of white spot lesions (WSLs) during fixed appliance orthodontic treatment. Nine databases were searched without limitations in September 2018 for randomized trials. Study selection, data extraction and risk of bias assessment were done independently in duplicate. Random-effects meta-analyses of mean differences (MDs) or relative risks (RRs) with their 95% confidence intervals (CIs) were conducted, followed by sensitivity analyses, and the GRADE analysis of the evidence quality. A total of 24 papers (23 trials) were included, assessing preventive measures applied either around orthodontic brackets (21 trials; 1427 patients; mean age 14.4 years) or molar bands (2 trials; 46 patients; age/sex not reported). Active patient reminders were associated with reduced WSL incidence on patient level compared to no reminder (3 trials; 190 patients; RR: 0.4; 95% CI: 0.31-0.64; Number Needed to Treat [NNT]: 3 patients), flat surface sealants were associated with reduced WSL incidence on tooth level than no sealant (5 trials; 2784 teeth; RR: 0.8; 95% CI: 0.63-0.95; NNT: 33 teeth), and fluoride varnish was associated with reduced WSL severity on tooth level (2 trials; 1160 teeth; MD: -0.32 points; 95% CI: -0.44 to -0.21 points). However, the quality of evidence was low according to GRADE, due to risk of bias. Some evidence indicates that active patient reminders and flat surface sealants or fluoride varnish around orthodontic brackets might be associated with reduced WSL burden, but further research is needed. Keywords: adverse effects; clinical trials; dental caries; evidence-based medicine; fixed appliances; systematic review

Minimally Invasive Surgery for Hepatocellular Carcinoma; Latest Advances

Surgical resection is the gold standard for hepatocellular carcinoma management for early stages of the disease. With advances in technology and techniques, minimally invasive surgery provides a great number of advantages for these patients during their surgery and for their post-operative care. The selection of patients following a multi-disciplinary approach is of paramount importance. Adding to this, the developments in laparoscopic instruments and training, as well as the promising advantages of robotic surgery along with other forms of technology, increase the pool of patients that can undergo operation safely and with good results worldwide. We review results from great centres worldwide and delineate the accurate multi-disciplinary approach for this

EXA2PRO programming environment:Architecture and applications

The EXA2PRO programming environment will integrate a set of tools and methodologies that will allow to systematically address many exascale computing challenges, including performance, performance portability, programmability, abstraction and reusability, fault tolerance and technical debt. The EXA2PRO tool-chain will enable the efficient deployment of applications in exascale computing systems, by integrating high-level software abstractions that offer performance portability and efficient exploitation of exascale systems' heterogeneity, tools for efficient memory management, optimizations based on trade-offs between various metrics and fault-tolerance support. Hence, by addressing various aspects of productivity challenges, EXA2PRO is expected to have significant impact in the transition to exascale computing, as well as impact from the perspective of applications. The evaluation will be based on 4 applications from 4 different domains that will be deployed in JUELICH supercomputing center. The EXA2PRO will generate exploitable results in the form of a tool-chain that support diverse exascale heterogeneous supercomputing centers and concrete improvements in various exascale computing challenges

Tumuli exploration using surface 3D Electrical Resistivity Tomography

Introduction The direct current resistivity method is nowadays a well established geophysical technique, used routinely and successfully in the detection and mapping of concealed subsurface structures, like walls, ditches and anthropogenic or natural cavities (Dahlin and Zhou, 2004). In archaeological geophysics, tombs constitute the most common subterranean manmade cavities of the greatest archaeological and historical importance. Several successful case studies in the detection of tombs hav..

Dynamo effects in magnetized ideal-plasma cosmologies

The excitation of cosmological perturbations in an anisotropic cosmological model and in the presence of a homogeneous magnetic field has been studied, using the ideal magnetohydrodynamic (MHD) equations. In this case, the system of partial differential equations which governs the evolution of the magnetized cosmological perturbations can be solved analytically. Our results verify that fast-magnetosonic modes propagating normal to the magnetic field, are excited. But, what's most important, is that, at late times, the magnetic-induction contrast grows, resulting in the enhancement of the ambient magnetic field. This process can be particularly favored by condensations, formed within the plasma fluid due to gravitational instabilities.Comment: 7 pages, RevTex, accepted for publication to IJMP