Lower semicontinuity of the feasible set mapping of linear systems relative to their domains

This paper deals with stability properties of the feasible set of linear inequality systems having a finite number of variables and an arbitrary number of constraints. Several types of perturbations preserving consistency are considered, affecting respectively, all of the data, the left-hand side data, or the right-hand side coefficients.

Motzkin decomposition of closed convex sets via truncation

A nonempty set F is called Motzkin decomposable when it can be expressed as the Minkowski sum of a compact convex set C with a closed convex cone D. In that case, the sets C and D are called compact and conic components of F. This paper provides new characterizations of the Motzkin decomposable sets involving truncations of F (i.e., intersections of FF with closed halfspaces), when F contains no lines, and truncations of the intersection F̂ of F with the orthogonal complement of the lineality of F, otherwise. In particular, it is shown that a nonempty closed convex set F is Motzkin decomposable if and only if there exists a hyperplane H parallel to the lineality of F such that one of the truncations of F̂ induced by H is compact whereas the other one is a union of closed halflines emanating from H. Thus, any Motzkin decomposable set F can be expressed as F=C+D, where the compact component C is a truncation of F̂. These Motzkin decompositions are said to be of type T when F contains no lines, i.e., when C is a truncation of F. The minimality of this type of decompositions is also discussed.

Stationarity and regularity of infinite collections of sets. Applications to infinitely constrained optimization

This article continues the investigation of stationarity and regularity properties of infinite collections of sets in a Banach space started in Kruger and López (J. Optim. Theory Appl. 154(2), 2012), and is mainly focused on the application of the stationarity criteria to infinitely constrained optimization problems. We consider several settings of optimization problems which involve (explicitly or implicitly) infinite collections of sets and deduce for them necessary conditions characterizing stationarity in terms of dual space elements—normals and/or subdifferentials.

Calmness modulus of linear semi-infinite programs

Our main goal is to compute or estimate the calmness modulus of the argmin mapping of linear semi-infinite optimization problems under canonical perturbations, i.e., perturbations of the objective function together with continuous perturbations of the right-hand side of the constraint system (with respect to an index ranging in a compact Hausdorff space). Specifically, we provide a lower bound on the calmness modulus for semi-infinite programs with unique optimal solution which turns out to be the exact modulus when the problem is finitely constrained. The relationship between the calmness of the argmin mapping and the same property for the (sub)level set mapping (with respect to the objective function), for semi-infinite programs and without requiring the uniqueness of the nominal solution, is explored, too, providing an upper bound on the calmness modulus of the argmin mapping. When confined to finitely constrained problems, we also provide a computable upper bound as it only relies on the nominal data and parameters, not involving elements in a neighborhood. Illustrative examples are provided.

Constraint qualifications in linear vector semi-infinite optimization

Linear vector semi-infinite optimization deals with the simultaneous minimization of finitely many linear scalar functions subject to infinitely many linear constraints. This paper provides characterizations of the weakly efficient, efficient, properly efficient and strongly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The global constraint qualifications are illustrated on a collection of selected applications.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.

Sonochemical synthesis of graphene oxide supported Pt–Pd alloy nanocrystals as efficient electrocatalysts for methanol oxidation

Pt–Pd bimetallic nanoparticles supported on graphene oxide (GO) nanosheets were prepared by a sonochemical reduction method in the presence of polyethylene glycol as a stabilizing agent. The synthetic method allowed for a fine tuning of the particle composition without significant changes in their size and degree of aggregation. Detailed characterization of GO-supported Pt–Pd catalysts was carried out by transmission electron microscopy (TEM), AFM, XPS, and electrochemical techniques. Uniform deposition of Pt–Pd nanoparticles with an average diameter of 3 nm was achieved on graphene nanosheets using a novel dual-frequency sonication approach. GO-supported bimetallic catalyst showed significant electrocatalytic activity for methanol oxidation. The influence of different molar compositions of Pt and Pd (1:1, 2:1, and 3:1) on the methanol oxidation efficiency was also evaluated. Among the different Pt/Pd ratios, the 1:1 ratio material showed the lowest onset potential and generated the highest peak current density. The effect of catalyst loading on carbon paper (working electrode) was also studied. Increasing the catalyst loading beyond a certain amount lowered the catalytic activity due to the aggregation of metal particle-loaded GO nanosheets.

Calmness of the Feasible Set Mapping for Linear Inequality Systems

In this paper we deal with parameterized linear inequality systems in the n-dimensional Euclidean space, whose coefficients depend continuosly on an index ranging in a compact Hausdorff space. The paper is developed in two different parametric settings: the one of only right-hand-side perturbations of the linear system, and that in which both sides of the system can be perturbed. Appealing to the backgrounds on the calmness property, and exploiting the specifics of the current linear structure, we derive different characterizations of the calmness of the feasible set mapping, and provide an operative expresion for the calmness modulus when confined to finite systems. In the paper, the role played by the Abadie constraint qualification in relation to calmness is clarified, and illustrated by different examples. We point out that this approach has the virtue of tackling the calmness property exclusively in terms of the system’s data.

Robust solutions to multi-objective linear programs with uncertain data

In this paper we examine multi-objective linear programming problems in the face of data uncertainty both in the objective function and the constraints. First, we derive a formula for the radius of robust feasibility guaranteeing constraint feasibility for all possible scenarios within a specified uncertainty set under affine data parametrization. We then present numerically tractable optimality conditions for minmax robust weakly efficient solutions, i.e., the weakly efficient solutions of the robust counterpart. We also consider highly robust weakly efficient solutions, i.e., robust feasible solutions which are weakly efficient for any possible instance of the objective matrix within a specified uncertainty set, providing lower bounds for the radius of highly robust efficiency guaranteeing the existence of this type of solutions under affine and rank-1 objective data uncertainty. Finally, we provide numerically tractable optimality conditions for highly robust weakly efficient solutions.

Magnetars: Properties, Origin and Evolution

Magnetars are neutron stars in which a strong magnetic field is the main energy source. About two dozens of magnetars, plus several candidates, are currently known in our Galaxy and in the Magellanic Clouds. They appear as highly variable X-ray sources and, in some cases, also as radio and/or optical pulsars. Their spin periods (2–12 s) and spin-down rates (∼10−13–10−10 s s−1) indicate external dipole fields of ∼1013−15 G, and there is evidence that even stronger magnetic fields are present inside the star and in non-dipolar magnetospheric components. Here we review the observed properties of the persistent emission from magnetars, discuss the main models proposed to explain the origin of their magnetic field and present recent developments in the study of their evolution and connection with other classes of neutron stars.

Stability in Linear Optimization Under Perturbations of the Left-Hand Side Coefficients

This paper studies stability properties of linear optimization problems with finitely many variables and an arbitrary number of constraints, when only left hand side coefficients can be perturbed. The coefficients of the constraints are assumed to be continuous functions with respect to an index which ranges on certain compact Hausdorff topological space, and these properties are preserved by the admissible perturbations. More in detail, the paper analyzes the continuity properties of the feasible set, the optimal set and the optimal value, as well as the preservation of desirable properties (boundedness, uniqueness) of the feasible and of the optimal sets, under sufficiently small perturbations.

Global behavior of the Douglas–Rachford method for a nonconvex feasibility problem

In recent times the Douglas–Rachford algorithm has been observed empirically to solve a variety of nonconvex feasibility problems including those of a combinatorial nature. For many of these problems current theory is not sufficient to explain this observed success and is mainly concerned with questions of local convergence. In this paper we analyze global behavior of the method for finding a point in the intersection of a half-space and a potentially non-convex set which is assumed to satisfy a well-quasi-ordering property or a property weaker than compactness. In particular, the special case in which the second set is finite is covered by our framework and provides a prototypical setting for combinatorial optimization problems.

Energy Loss Function of Solids Assessed by Ion Beam Energy-Loss Measurements: Practical Application to Ta2O5

We present a study where the energy loss function of Ta2O5, initially derived in the optical limit for a limited region of excitation energies from reflection electron energy loss spectroscopy (REELS) measurements, was improved and extended to the whole momentum and energy excitation region through a suitable theoretical analysis using the Mermin dielectric function and requiring the fulfillment of physically motivated restrictions, such as the f- and KK-sum rules. The material stopping cross section (SCS) and energy-loss straggling measured for 300–2000 keV proton and 200–6000 keV helium ion beams by means of Rutherford backscattering spectrometry (RBS) were compared to the same quantities calculated in the dielectric framework, showing an excellent agreement, which is used to judge the reliability of the Ta2O5 energy loss function. Based on this assessment, we have also predicted the inelastic mean free path and the SCS of energetic electrons in Ta2O5.

A multi-method study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the activation pathway

The change in the carbonaceous skeleton of nanoporous carbons during their activation has received limited attention, unlike its counterpart process in the presence of an inert atmosphere. Here we adopt a multi-method approach to elucidate this change in a poly(furfuryl alcohol)-derived carbon activated using cyclic application of oxygen saturation at 250 °C before its removal (with carbon) at 800 °C in argon. The methods used include helium pycnometry, synchrotron-based X-ray diffraction (XRD) and associated radial distribution function (RDF) analysis, transmission electron microscopy (TEM) and, uniquely, electron energy-loss spectroscopy spectrum-imaging (EELS-SI), electron nanodiffraction and fluctuation electron microscopy (FEM). Helium pycnometry indicates the solid skeleton of the carbon densifies during activation from 78% to 93% of graphite. RDF analysis, EELS-SI, and FEM all suggest this densification comes through an in-plane growth of sp2 carbon out to the medium range without commensurate increase in order normal to the plane. This process could be termed ‘graphenization’. The exact way in which this process occurs is not clear, but TEM images of the carbon before and after activation suggest it may come through removal of the more reactive carbon, breaking constraining cross-links and creating space that allows the remaining carbon material to migrate in an annealing-like process.

Raman spectroscopy study of the transformation of the carbonaceous skeleton of a polymer-based nanoporous carbon along the thermal annealing pathway

We report a multi-wavelength Raman spectroscopy study of the structural changes along the thermal annealing pathway of a poly(furfuryl alcohol) (PFA) derived nanoporous carbon (NPC). The Raman spectra were deconvoluted utilizing G, D, D′, A and TPA bands. The appropriateness of these deconvolutions was confirmed via recovery of the correct dispersive behaviours of these bands. It is proposed that the ID/IG ratio is composed of two parts: one associated with the extent of graphitic crystallites (the Tuinstra–Koenig relationship), and a second related to the inter-defect distance. This model was used to successfully determine the variation of the in-plane size and intra-plane defect density along the annealing pathway. It is proposed that the NPC skeleton evolves along the annealing pathway in two stages: below 1600 °C it was dominated by a reduction of in-plane defects with a minor crystallite growth, and above this temperature growth of the crystallites accelerates as the in-plane defect density approaches zero. A significant amount of transpolyacetylene (TPA)-like structures was found to be remaining even at 2400 °C. These may be responsible for resistance to further graphitization of the PFA-based carbon at higher temperatures.