One-point statistics and intermittency of induced electric field in the solar wind

The interplanetary induced electric field e=vxb is studied, using solar wind time series. The probability distribution functions (PDFs) of the electric field components are measured from the data and their non-gaussianity is discussed. Moreover, for the first time we show that the electric field turbulence is characterized by intermittency. This point is addressed by studying, as usual, the scaling of the PDFs of field increments, which allows a quantitative characterization of intermittency.Comment: Accepted for publication on Europhysics Letters, April 22th, 200

Clinical management of a peri-implant giant cell granuloma

Purpose. Implant therapy plays an important role in contemporary dentistry with high rates of long-term success. However, in recent years, the incidence of peri-implantitis and implant failures has significantly increased. The peripheral giant cell granuloma (PGCG) rarely occurs in peri-implant tissues and it is clinically comparable to the lesions associated with natural teeth. Therefore, the study of possible diseases associated with dental implants plays an important role in order to be able to diagnose and treat these conditions. Materials and Methods. This report described a 60-year-old Caucasian male who presented a reddish-purple pedunculated mass, of about 2 cm in diameter, associated with a dental implant and the adjacent natural tooth. Results. An excisional biopsy was performed and the dental implant was not removed. Histological examination provided the diagnosis of PGCG. After 19-month follow-up, there were no signs of recurrence of peri-implantitis around the implant. Conclusion. The correct diagnosis and appropriate surgical treatment of peri-implant giant cell granuloma are very important for a proper management of the lesion in order to preserve the implant prosthetic rehabilitation and prevent recurrences

SecCo: Automated Services to Secure Containers in the DevOps Paradigm

Containers are core building blocks for creating applications based on the microservice paradigm. However, assessing their security is complex, especially when deployed in distributed and heterogeneous scenarios. Moreover, developers and IT operators should only focus on integration and delivery processes without dealing with tasks to guarantee securing requirements. To overcome such issues, in this paper, we introduce the ideas at the basis of Project SecCo (Securing Containers), i.e., an architecture for extending and improving current security assessment methodologies into the continuous integration and continuous delivery DevOps pipeline. To this end, SecCo proposes a framework able to orchestrate new automatic security services to prevent and reduce security vulnerabilities in the design, implementation, and deployment phases, and to identify and mitigate, at runtime, attempts to exploit them. The paper also showcases the main research challenges to be addressed for pursuing the vision of SecCo

Impact of heart rate on myocardial salvage in timely reperfused patients with STSegment elevation myocardial infarction. new insights from cardiovascular magnetic resonance

BACKGROUND: Previous studies evaluating the progression of the necrotic wave in relation to heart rate were carried out only in animal models of ST-elevated myocardial infarction (STEMI). Aim of the study was to investigate changes of myocardial salvage in relation to different heart rates at hospital admission in timely reperfused patients with STEMI by using cardiovascular magnetic resonance (CMR). METHODS: One hundred-eighty-seven patients with STEMI successfully and timely treated with primary coronary angioplasty underwent CMR five days after hospital admission. According to the heart rate at presentation, patients were subcategorized into 5 quintiles: <55 bpm (group I, n = 44), 55-64 bpm (group II, n = 35), 65-74 bpm (group III, n = 35), 75-84 bpm (group IV, n = 37), ≥85 bpm (group V, n = 36). Area at risk, infarct size, microvascular obstruction (MVO) and myocardium salvaged index (MSI) were assessed by CMR using standard sequences. RESULTS: Lower heart rates at presentation were associated with a bigger amount of myocardial salvage after reperfusion. MSI progressively decreased as the heart rates increased (0.54 group I, 0.46 group II, 0.38 group III, 0.34 group IV, 0.32 group V, p<0.001). Stepwise multivariable analysis showed heart rate, peak troponin and the presence of MVO were independent predictor of myocardial salvage. No changes related to heart rate were observed in relation to area at risk and infarct size. CONCLUSIONS: High heart rates registered before performing coronary angioplasty in timely reperfused patients with STEMI are associated with a reduction in salvaged myocardium. In particular, salvaged myocardium significantly reduced when heart rate at presentation is ≥85 bpm

Arbitrary-order Hilbert spectral analysis and intermittency in solar wind density fluctuations

The properties of inertial and kinetic range solar wind turbulence have been investigated with the arbitrary-order Hilbert spectral analysis method, applied to high-resolution density measurements. Due to the small sample size, and to the presence of strong non-stationary behavior and large-scale structures, the classical structure function analysis fails to detect power law behavior in the inertial range, and may underestimate the scaling exponents. However, the Hilbert spectral method provides an optimal estimation of the scaling exponents, which have been found to be close to those for velocity fluctuations in fully developed hydrodynamic turbulence. At smaller scales, below the proton gyroscale, the system loses its intermittent multiscaling properties, and converges to a monofractal process. The resulting scaling exponents, obtained at small scales, are in good agreement with those of classical fractional Brownian motion, indicating a long-term memory in the process, and the absence of correlations around the spectral break scale. These results provide important constraints on models of kinetic range turbulence in the solar wind

On the Robustness of Bayesian Neural Networks to Adversarial Attacks

Vulnerability to adversarial attacks is one of the principal hurdles to the adoption of deep learning in safety-critical applications. Despite significant efforts, both practical and theoretical, training deep learning models robust to adversarial attacks is still an open problem. In this paper, we analyse the geometry of adversarial attacks in the large-data, overparameterized limit for Bayesian Neural Networks (BNNs). We show that, in the limit, vulnerability to gradient-based attacks arises as a result of degeneracy in the data distribution, i.e., when the data lies on a lower-dimensional submanifold of the ambient space. As a direct consequence, we demonstrate that in this limit BNN posteriors are robust to gradient-based adversarial attacks. Crucially, we prove that the expected gradient of the loss with respect to the BNN posterior distribution is vanishing, even when each neural network sampled from the posterior is vulnerable to gradient-based attacks. Experimental results on the MNIST, Fashion MNIST, and half moons datasets, representing the finite data regime, with BNNs trained with Hamiltonian Monte Carlo and Variational Inference, support this line of arguments, showing that BNNs can display both high accuracy on clean data and robustness to both gradient-based and gradient-free based adversarial attacks.Comment: arXiv admin note: text overlap with arXiv:2002.0435