On the Lebesgue test for convergence of Fourier series on unbounded Vilenkin groups

We extend the Dezern–Waterman version of the Lebesgue test for convergence of Vilenkin–Fourier series to the case of unbounded Vilenkin groups.     

Ergodic Uniformly Differentiable Functions Modulo p on ℤ p

We establish necessary and sufficient conditions for ergodicity of uniformly differentiable functions modulo p on ℤp. This result is applied to study ergodic rational functions on ℤ3.     

Strong convergence of two‐dimensional Vilenkin‐Fourier series

We prove that certain means of the quadratical partial sums of the two‐dimensional Vilenkin‐Fourier series are uniformly bounded operators from the Hardy space to the space for We also prove that the sequence in the denominator cannot be improved.     

Sets of Minimality of (1 − 1)-Rational Functions

We describe dynamical systems associated to (1 ? 1)-rational functions on the field of p-adic numbers.We focus on sets of minimality of such systems.     

Maximal functions,Hardy spaces and Fourier multiplier theorems on unbounded Vilenkin groups

We consider relations between various existing concepts of Hardy spaces on Vilenkin groups. The problem of an appropriate Fourier multiplier theorem for unbounded Vilenkin groups is revisited and the conditions made more precise under which such a theorem is established. Theorem 3.1 from Avdispahi? and Memi? (2010) [1] is rectified.     

GC-MS-based urine metabolic profiling of autism spectrum disorders

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders resulting from multiple factors. Diagnosis is based on behavioural and developmental signs detected before 3 years of age, and there is no reliable biological marker. The purpose of this study was to evaluate the value of gas chromatography combined with mass spectroscopy (GC-MS) associated with multivariate statistical modeling to capture the global biochemical signature of autistic individuals. GC-MS urinary metabolic profiles of 26 autistic and 24 healthy children were obtained by liq/liq extraction, and were or were not subjected to an oximation step, and then were subjected to a persilylation step. These metabolic profiles were then processed by multivariate analysis, in particular orthogonal partial least-squares discriminant analysis (OPLS-DA, R ²Y(cum) = 0.97, Q ²(cum) = 0.88). Discriminating metabolites were identified. The relative concentrations of the succinate and glycolate were higher for autistic than healthy children, whereas those of hippurate, 3-hydroxyphenylacetate, vanillylhydracrylate, 3-hydroxyhippurate, 4-hydroxyphenyl-2-hydroxyacetate, 1H-indole-3-acetate, phosphate, palmitate, stearate, and 3-methyladipate were lower. Eight other metabolites, which were not identified but characterized by a retention time plus a quantifier and its qualifier ion masses, were found to differ between the two groups. Comparison of statistical models leads to the conclusion that the combination of data obtained from both derivatization techniques leads to the model best discriminating between autistic and healthy groups of children.     

Numerical analysis of progressive damage in nonwoven fibrous networks under tension

Understanding a mechanical behaviour of polymer-based nonwoven materials that include large-strain deformation and damage can help to evaluate a response of nonwoven fibrous networks to various loading conditions. Here, a nonwoven felt made by thermal bonding of polypropylene fibres was used as a model system. Its deformation and damage behaviour was analysed by means of experimental assessment of damage evolution based on single-fibre failure and finite-element simulations. Tensile tests of nonwoven fabrics were carried out to characterise their damage behaviour under in-plane mechanical loading. It was found that progressive failure of fibres led to localization of damage initiation and propagation, ultimately resulting in failure of the nonwoven felt. To obtain the criteria that control the onset and propagation of damage in these materials, tensile tests on single fibres, extracted from the felt with bond points attached to their ends, were performed. A finite-element model was developed to study damage initiation and propagation in nonwovens. In the model, structural randomness of a nonwoven fibrous network was implemented by means of direct introduction of fibres according to the orientation distribution function. The evolution of damage in the network was controlled by a single-fibre failure criterion obtained experimentally. The proposed numerical model not only captured the macroscopic response of the felt successfully but also reproduced the underlying mechanisms involved in deformation and damage of nonwovens.     

The Team Orienteering Problem with Time Windows: An LP-based Granular Variable Neighborhood Search

The Team Orienteering Problem (TOP) is a known NP-hard problem that typically arises in vehicle routing and production scheduling contexts. In this paper we introduce a new solution method to solve the TOP with hard Time Window constraints (TOPTW). We propose a Variable Neighborhood Search (VNS) procedure based on the idea of exploring, most of the time, granular instead of complete neighborhoods in order to improve the algorithm’s efficiency without loosing effectiveness. The method provides a general way to deal with granularity for those routing problems based on profits and complicated by time constraints. Extensive computational results are reported on standard benchmark instances. Performance of the proposed algorithm is compared to optimal solution values, when available, or to best known solution values obtained by state-of-the-art algorithms. The method comes out to be, on average, quite effective allowing to improve the best know values for 25 test instances.     

Hybridized evolutionary local search algorithm for the team orienteering problem with time windows

The orienteering problem (OP) consists in finding an elementary path over a subset of vertices. Each vertex is associated with a profit that is collected on the visitor’s first visit. The objective is to maximize the collected profit with respect to a limit on the path’s length. The team orienteering problem (TOP) is an extension of the OP where a fixed number m of paths must be determined. This paper presents an effective hybrid metaheuristic to solve both the OP and the TOP with time windows. The method combines the greedy randomized adaptive search procedure (GRASP) with the evolutionary local search (ELS). ELS generates multiple distinct child solutions using a mutation mechanism. Each child solution is further improved by a local search procedure. GRASP provides multiple starting solutions to the ELS. The method is able to improve several best known results on available benchmark instances.