N=4 Extended MSSM

We investigate a perturbative N=4 sector coupled to the MSSM and show that it allows for a stable vacuum correctly breaking the electroweak symmetry. The particle spectrum of the MSSM is enrichened by several new particles stemming out from the new N=4 sector of the theory, and a new lepton doublet required to cancel global and gauge anomalies of the theory. Even if the conformal invariance of the N=4 sector is explicitly broken, a nontrivial UV behavior of the coupling constants is possible: by studying the renormalization group equations at two loops we find that the Yukawa couplings of the heavy fermionic states flow to a common fixed point at a scale of a few TeVs. The parameter space of the new theory is reduced imposing naturalness of the couplings and soft supersymmetry breaking masses, perturbativity of the model at the EW scale as well as phenomenological constraints. Our preliminary results on the spectrum of the theory suggest that the LHC can rule out a significant portion of the parameter space of this model.Comment: 22 pages, 2 figure

Machine Learning For In-Region Location Verification In Wireless Networks

In-region location verification (IRLV) aims at verifying whether a user is inside a region of interest (ROI). In wireless networks, IRLV can exploit the features of the channel between the user and a set of trusted access points. In practice, the channel feature statistics is not available and we resort to machine learning (ML) solutions for IRLV. We first show that solutions based on either neural networks (NNs) or support vector machines (SVMs) and typical loss functions are Neyman-Pearson (N-P)-optimal at learning convergence for sufficiently complex learning machines and large training datasets . Indeed, for finite training, ML solutions are more accurate than the N-P test based on estimated channel statistics. Then, as estimating channel features outside the ROI may be difficult, we consider one-class classifiers, namely auto-encoders NNs and one-class SVMs, which however are not equivalent to the generalized likelihood ratio test (GLRT), typically replacing the N-P test in the one-class problem. Numerical results support the results in realistic wireless networks, with channel models including path-loss, shadowing, and fading

Location-Verification and Network Planning via Machine Learning Approaches

In-region location verification (IRLV) in wireless networks is the problem of deciding if user equipment (UE) is transmitting from inside or outside a specific physical region (e.g., a safe room). The decision process exploits the features of the channel between the UE and a set of network access points (APs). We propose a solution based on machine learning (ML) implemented by a neural network (NN) trained with the channel features (in particular, noisy attenuation values) collected by the APs for various positions both inside and outside the specific region. The output is a decision on the UE position (inside or outside the region). By seeing IRLV as an hypothesis testing problem, we address the optimal positioning of the APs for minimizing either the area under the curve (AUC) of the receiver operating characteristic (ROC) or the cross entropy (CE) between the NN output and ground truth (available during the training). In order to solve the minimization problem we propose a twostage particle swarm optimization (PSO) algorithm. We show that for a long training and a NN with enough neurons the proposed solution achieves the performance of the Neyman-Pearson (N-P) lemma.Comment: Accepted for Workshop on Machine Learning for Communications, June 07 2019, Avignon, Franc

A Power Cap Oriented Time Warp Architecture

Controlling power usage has become a core objective in modern computing platforms. In this article we present an innovative Time Warp architecture oriented to efficiently run parallel simulations under a power cap. Our architectural organization considers power usage as a foundational design principle, as opposed to classical power-unaware Time Warp design. We provide early experimental results showing the potential of our proposal

Euler-Richardson method preconditioned by weakly stochastic matrix algebras : a potential contribution to Pagerank computation

Let S be a column stochastic matrix with at least one full row. Then S describes a Pagerank-like random walk since the computation of the Perron vector x of S can be tackled by solving a suitable M-matrix linear system Mx = y, where M = I − τ A, A is a column stochastic matrix and τ is a positive coefficient smaller than one. The Pagerank centrality index on graphs is a relevant example where these two formulations appear. Previous investigations have shown that the Euler- Richardson (ER) method can be considered in order to approach the Pagerank computation problem by means of preconditioning strategies. In this work, it is observed indeed that the classical power method can be embedded into the ER scheme, through a suitable simple preconditioner. Therefore, a new preconditioner is proposed based on fast Householder transformations and the concept of low complexity weakly stochastic algebras, which gives rise to an effective alternative to the power method for large-scale sparse problems. Detailed mathematical reasonings for this choice are given and the convergence properties discussed. Numerical tests performed on real-world datasets are presented, showing the advantages given by the use of the proposed Householder-Richardson method

Fatigue microstructural evolution in pseudo elastic NiTi alloy

Abstract Shape memory property characterizes the behavior of many Ti based alloys (SMAs). This property is due to a metallurgical phenomenon, which allows to change the lattice structure without boundaries changing as a reversible transition. Equiatomic NiTi alloys are among the most industrially used SMAs: they are characterized by two different mechanical behaviors in terms of shape recovering: • a shape memory effect (SME). This is obtained when the recovery of the initial shape takes place only after heating over a critical temperature, with a consequent crystallographic structure transition; • a pseudoelastic effect (PE). This is obtained when the critical temperature is lower than environmental temperature. In this case, the recovery of the initial shape takes place only after unloading. In recent years, research relating to materials of shape memory has gone in the direction of application in many fields of engineering such as aerospace or mechanical systems. In this work the evolution of microstructural lattice has been studied taking in to account the effect of low cycles fatigue loads

Erratum: Minimally modified theories of gravity: a playground for testing the uniqueness of general relativity

In a recent paper [1], it was introduced a new class of gravitational theories with two local degrees of freedom. The existence of these theories apparently challenges the distinctive role of general relativity as the unique non-linear theory of massless spin-2 particles. Here we perform a comprehensive analysis of these theories with the aim of (i) understanding whether or not these are actually equivalent to general relativity, and (ii) finding the root of the variance in case these are not. We have found that a broad set of seemingly different theories actually pass all the possible tests of equivalence to general relativity (in vacuum) that we were able to devise, including the analysis of scattering amplitudes using on-shell techniques. These results are complemented with the observation that the only examples which are manifestly not equivalent to general relativity either do not contain gravitons in their spectrum, or are not guaranteed to include only two local degrees of freedom once radiative corrections are taken into account. Coupling to matter is also considered: we show that coupling these theories to matter in a consistent way is not as straightforward as one could expect. Minimal coupling, as well as the most straightforward non-minimal couplings, cannot be used. Therefore, before being able to address any issues in the presence of matter, it would be necessary to find a consistent (and in any case rather peculiar) coupling scheme

Fatigue in lung cancer patients: symptom burden and management of challenges.

Lung cancer (LC) remains the most common cause of cancer death in several countries across the world. Fatigue is the most frequently reported symptom in LC patients throughout the entire course of disease, and all international guidelines recommend early screening for cancer-related fatigue (CRF) and symptoms that can affect patients’ quality of life. In patients with LC, fatigue belongs to the symptom cluster of pain, depression, and insomnia, which are commonly observed simultaneously, but are typically treated as separate although they may have common biological mechanisms. The treatment of CRF remains one of the difficult areas in the oncology field: scarce evidence supports pharmacological therapies, while some interesting data arising indicates alternative remedies and physical exercise seem to be one of the most effective approaches for CRF at any stage of LC