Clinical applications of squamous cell carcinoma antigen-immunoglobulins M to monitor chronic hepatitis C

Hepatitis C virus (HCV) is the main cause of chronic liver disease and cirrhosis in Western countries. Over time, the majority of cirrhotic patients develop hepatocellular carcinoma (HCC), one of the most common fatal cancers worldwide - fourth for incidence rate. A high public health priority need is the development of biomarkers to screen for liver disease progression and for early diagnosis of HCC development, particularly in the high risk population represented by HCV-positive patients with cirrhosis. Several studies have shown that serological determination of a novel biomarker, squamous cell carcinoma antigen-immunoglobulins M (SCCA-IgM), might be useful to identify patients with progressive liver disease. In the initial part of this review we summarize the main clinical studies that have investigated this new circulating biomarker on HCV-infected patients, providing evidence that in chronic hepatitis C SCCA-IgM may be used to monitor progression of liver disease, and also to assess the virological response to antiviral treatment. In the last part of this review we address other, not less important, clinical applications of this biomarker in hepatology

Towards A Theory Of Quantum Computability

We propose a definition of quantum computable functions as mappings between superpositions of natural numbers to probability distributions of natural numbers. Each function is obtained as a limit of an infinite computation of a quantum Turing machine. The class of quantum computable functions is recursively enumerable, thus opening the door to a quantum computability theory which may follow some of the classical developments

A Hybrid Approach for Modeling Stochastic Ray Propagation in Stratified Random Lattices

The present contribution deals with ray propagation in semi-innite percolation lattices consisting of a succession of uniform density layers. The problem of analytically evaluating the probability that a single ray penetrates up to a prescribed level before being reected back into the above empty half-plane is addressed. A hybrid approach, exploiting the complementarity of two mathematical models in dealing with uniform congurations, is presented and assessed through numerical ray-tracing-based experiments in order to show improvements upon previous predictions techniques. "The definitive version is available at www3.interscience.wiley.com

A Hybrid Approach Based on PSO and Hadamard Difference Sets for the Synthesis of Square Thinned Arrays

A hybrid approach for the synthesis of planar thinned antenna arrays is presented. The proposed solution exploits and combines the most attractive features of a particle swarm algorithm and those of a combinatorial method based on the noncyclic difference sets of Hadamard type. Numerical experiments validate the proposed solution, showing improvements with respect to previous results. (c) 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Quantum Turing Machines Computations and Measurements

Contrary to the classical case, the relation between quantum programming languages and quantum Turing Machines (QTM) has not being fully investigated. In particular, there are features of QTMs that have not been exploited, a notable example being the intrinsic infinite nature of any quantum computation. In this paper we propose a definition of QTM, which extends and unifies the notions of Deutsch and Bernstein and Vazirani. In particular, we allow both arbitrary quantum input, and meaningful superpositions of computations, where some of them are "terminated" with an "output", while others are not. For some infinite computations an "output" is obtained as a limit of finite portions of the computation. We propose a natural and robust observation protocol for our QTMs, that does not modify the probability of the possible outcomes of the machines. Finally, we use QTMs to define a class of quantum computable functions---any such function is a mapping from a general quantum state to a probability distribution of natural numbers. We expect that our class of functions, when restricted to classical input-output, will be not different from the set of the recursive functions.Comment: arXiv admin note: substantial text overlap with arXiv:1504.02817 To appear on MDPI Applied Sciences, 202

Percolation-Based Approaches For Ray-Optical Propagation in Inhomogeneous Random Distribution of Discrete Scatterers

We address the problem of optical ray propagation in an inhomogeneous half�]plane lattice, where each cell can be occupied according to a known one�]dimensional obstacles density distribution. A monochromatic plane wave impinges on the random grid with a known angle and undergoes specular reflections on the occupied cells. We present two different approaches for evaluating the propagation depth inside the lattice. The former is based on the theory of the Martingale random processes, while in the latter ray propagation is modelled in terms of a Markov chain. A numerical validation assesses the proposed solutions, while validation through experimental data shows that the percolation model, in spite of its simplicity, can be applied to model real propagation problems

Computationally-Effective Optimal Excitation Matching for the Synthesis of Large Monopulse Arrays

Antenna arrays able to generate two different patterns are widely used in tracking radar systems [1]. Optimal (in the Dolph�]Chebyshev sense) sum [2] and difference patterns [3] can be generated by using two independent feed networks. Unfortunately, such a situation generally turns out to be impracticable because of its costs, the occupied physical space, the circuit complexity, and electromagnetic interferences. Thus, starting from the optimal sum pattern a sub�]optimal solution for the difference pattern is usually synthesized by means of the sub�]array technique. The array elements are grouped in sub�]arrays properly weighted for matching the constrains of the difference beam. Finding the best elements grouping and the sub�]array weights is a complex and challenging research topic, especially when dealing with large arrays. As far as linear arrays are concerned, McNamara proposed in [4] an analytical method for determining the �gbest compromise�h difference pattern. Unfortunately, when the ratio between the elements of the array and sub�]arrays increases, such a technique exhibits several limitations mainly due to the ill�]conditioning of the problem and the computational costs due to exhaustive evaluations. A non�]negligible saving might be achieved by applying optimization algorithms (see for instance [5] and [6]) aimed at minimizing a suitable cost function. Notwithstanding, optimization�]based approaches still appear computationally expensive when dealing with large arrays because of wide dimension of solution space to be sampled. In order to properly deal with these computational issues, this contribution presents an innovative approach based on an optimal excitation matching procedure. By exploiting the relationship between independently�]optimal sum and difference patterns, the dimension of the solution space is considerably reduced and efficiently sampled by taking into account the presence of array elements more suitable to change sub�]array membership. In the following, the proposed technique is described pointing out, through a representative case, its potentialities and effectiveness in dealing with large arrays. This is the author's version of the final version available at IEEE

Stochastic Ray Propagation in Stratified Random Lattices – Comparative Assessment of Two Mathematical Approaches

In this report, ray propagation in stratified semi-infinite percolation lattices consisting of a succession of uniform density layers is considered. The final version of this article is available at the url of the journal PIER: http://www.jpier.org/PIER