Robust estimation in single-index models when the errors have a unimodal density with unknown nuisance parameter

This paper develops a robust profile estimation method for the parametric and nonparametric components of a single-index model when the errors have a strongly unimodal density with unknown nuisance parameter. We derive consistency results for the link function estimators as well as consistency and asymptotic distribution results for the single-index parameter estimators. Under a log-Gamma model, the sensitivity to anomalous observations is studied using the empirical influence curve. We also discuss a robust K-fold cross-validation procedure to select the smoothing parameters. A numerical study carried on with errors following a log-Gamma model and for contaminated schemes shows the good robustness properties of the proposed estimators and the advantages of considering a robust approach instead of the classical one. A real data set illustrates the use of our proposal.

     

A segmentation procedure of the pervious area of the aorta artery from CT images without contrast medium

In this paper, we develop an algorithm for the segmentation of the pervious lumen of the aorta artery in computed tomography (CT) images without contrast medium, a challenging task due to the closeness gray levels of the different zones to segment. The novel approach of the proposed procedure mainly resides in enhancing the resolution of the image by the application of the algorithm deduced from the mathematical theory of sampling Kantorovich operators. After the application of suitable digital image processing techniques, the pervious zone of the artery can be distinguished from the occluded one. Numerical tests have been performed using 233 CT images, and suitable numerical errors have been computed and introduced ex novo to evaluate the performance of the proposed method. The above procedure is completely automatic in all its parts after the initial region of interest (ROI) selection. The main advantages of this approach relies in the potential possibility of performing diagnosis concerning vascular pathologies even for patients with severe kidney diseases or allergic problems, for which CT images with contrast medium cannot be achieved.     

A general framework for ADMM acceleration

Numerical Algorithms - The Alternating Direction Multipliers Method (ADMM) is a very popular algorithm for computing the solution of convex constrained minimization problems. Such problems are...     

Comparisons of the Expectations of System and Component Lifetimes in the Failure Dependent Proportional Hazard Model

Methodology and Computing in Applied Probability - In the failure dependent proportional hazard model, it is assumed that identical components work jointly in a system. At the moments of...     

Multi layer structure for encapsulation of organic transistors

A novel encapsulation structure to protect organic thin film transistors against oxygen and moisture contaminations is presented. The sealing architecture is comprised of three-layers: aluminum oxide deposited by means of Atomic Layer Deposition is the actual capping layer, while cross-linked poly-vinylphenol and poly-vinylphenol prevent the contamination/damage of the underlying organic semiconductor during the oxide growth. The process has negligible impact on device mobility but it enables poly-3-hexylthiophene based transistors to operate with an on/off ratio in excess of 10³ even after 100 days of continuous ambient air exposure.     

Fast and air stable near-infrared organic detector based on squaraine dyes

In search for an organic material suitable for the detection of near-infrared electromagnetic radiation and at the same time capable of air stable operation of related devices, so to address the many applications envisaged with this technology (remote control, chemical/biological sensing, optical communication, spectroscopic and medical instruments), we explore the performance of a blend of hydrazone end-capped symmetric squaraines and phenyl C₆₁ butyric acid methyl ester. We succeed in developing air stable solution-processed devices with external quantum efficiency in the NIR as high as 3.5% and response times of few hundreds of nanoseconds. Essential to these achievements has been a detailed characterization of the devices performed by correlating the optoelectronic performances to the morphology of the layers (extracted from AFM measurements) and to the charge carrier mobility (extracted from transistor structures), enabling their optimization at the chemical level, by tailoring the squaraine substitution pattern, and at the device level, by tuning the blend composition. We show that a good balance between holes and electrons mobility is essential for high EQE and fast response speed, and that a smooth morphology is mandatory to achieve long term air stability and operability with no need for encapsulation.     

Convex envelopes of bivariate functions through the solution of KKT systems

In this paper we exploit a slight variant of a result previously proved in Locatelli and Schoen (Math Program 144:65–91, 2014) to define a procedure which delivers the convex envelope of some bivariate functions over polytopes. The procedure is based on the solution of a KKT system and simplifies the derivation of the convex envelope with respect to previously proposed techniques. The procedure is applied to derive the convex envelope of the bilinear function xy over any polytope, and the convex envelope of functions \(x^n y^m\) over boxes.     

Linear-quadratic optimal control under non-Markovian switching

We study a finite-dimensional continuous-time optimal control problem on finite horizon for a controlled diffusion driven by Brownian motion, in the linear-quadratic case. We admit stochastic coefficients, possibly depending on an underlying independent marked point process, so that our model is general enough to include controlled switching systems where the switching mechanism is not required to be Markovian. The problem is solved by means of a Riccati equation, which turned out to be a backward stochastic differential equation driven by the Brownian motion and by the random measure associated with the marked point process.     

Fatou closedness under model uncertainty

We provide a characterization in terms of Fatou closedness for weakly closed monotone convex sets in the space of \({\mathcal P}\)-quasisure bounded random variables, where \({\mathcal P}\) is a (possibly non-dominated) class of probability measures. Applications of our results lie within robust versions the Fundamental Theorem of Asset Pricing or dual representation of convex risk measures.     

Integer programming models and linearizations for the traveling car renter problem

The traveling car renter problem (CaRS) is an extension of the classical traveling salesman problem (TSP) where different cars are available for use during the salesman’s tour. In this study we present three integer programming formulations for CaRS, of which two have quadratic objective functions and the other has quadratic constraints. The first model with a quadratic objective function is grounded on the TSP interpreted as a special case of the quadratic assignment problem in which the assignment variables refer to visitation orders. The second model with a quadratic objective function is based on the Gavish and Grave’s formulation for the TSP. The model with quadratic constraints is based on the Dantzig–Fulkerson–Johnson’s formulation for the TSP. The formulations are linearized and implemented in two solvers. An experiment with 50 instances is reported.