Adsorption of pentacene on filled d-band metal surfaces: long-range ordering and adsorption energy

The growth of pentacene on suitable metallic templates is studied by means of low-energy electron diffraction and ultraviolet photoelectron spectroscopy. Highly ordered pentacene single layers can be prepared by deposition on filled d-band metal templates kept at 370 K. The presence of the steps for the Cu(119) vicinal surface and of the Au troughs for the Au(110)-(1 x 2) surface allows the formation of commensurate long-range ordered structures with (3 x 7) and (3 x 6) periodicities, respectively. A detailed analysis of the molecular induced electronic states evolution is performed for different growth morphologies. The adsorption energy of the ordered molecular single layers on the Au(110) surface is lower (1.90 eV) than on the Cu vicinal surface (2.36 eV), where the steps enhance the molecule adsorption energy.     

Structure and growth of thin films of aniline on silver: nucleation and premelting of nanocrystallites, porosity, and crystallization

The structure and growth of thin films of aniline vapor deposited on Ag(111) and Ag(110) surfaces have been examined using optical second harmonic generation (SHG) and linear optical differential reflectivity (DR). Aniline thin films deposited at 90 K give a detectable SH signal that arises from small polycrystallites with orientation anisotropy in the film. Upon annealing, the SH signal decreases, first due to premelting (at approximately 145 K) of the polycrystallites and then sublimation (at approximately 180 K) of the film. Quantitative analysis of the SH intensity change by a premelting model [J. Phys. Chem. 1988, 92, 7241] allows the determination of the average size of the crystallites as 1.1 nm in diameter and containing approximately 45 aniline molecules. The existence of the nanocrystalline structure and its premelting are confirmed by DR experiments. The DR signal around 145 K exhibits change corresponding to an order-disorder transition. Quantitative analysis of the DR data results in the same nanocrystallite size. Experimental observations indicate that films deposited at 90 K contain not only nanocrystallites but also approximately 30% porosity, which can be reduced by annealing. At temperatures above 195 K, micron-size crystallites start to form within the amorphous film, causing a large amount of light scattering while the film sublimates. It appears that, for molecules such as aniline with stronger intermolecular interactions, more enthalpy is released, upon adsorption to the local surrounding molecules, causing them to reorient into crystalline form. The low deposition temperature, on the other hand, prevents diffusion for further crystallization beyond nanocrystallites. The refractive index of the amorphous aniline solid can be determined as 1.68 +/- 0.03.     

On some invariants in numerical semigroups and estimations of the order bound

Let S={s _i } _i∈??? be a numerical semigroup. For s _i ∈S, let ν(s _i ) denote the number of pairs (s _i ?s _j ,s _j )∈S ². When S is the Weierstrass semigroup of a family $\{\mathcal{C}_{i}\}_{i\in\mathbb{N}}Let S={s _i } _i∈ℕ⊆ℕ be a numerical semigroup. For s _i ∈S, let ν(s _i ) denote the number of pairs (s _i −s _j ,s _j )∈S ². When S is the Weierstrass semigroup of a family {C_i}_{i ? \mathbbN}\{\mathcal{C}_{i}\}_{i\in\mathbb{N}} of one-point algebraic-geometric codes, a good bound for the minimum distance of the code C_i\mathcal{C}_{i} is the Feng and Rao order bound d _ORD (C _i ). It is well-known that there exists an integer m such that d _ORD (C _i )=ν(s _i+1) for each i≥m. By way of some suitable parameters related to the semigroup S, we find upper bounds for m and we evaluate m exactly in many cases. Further we conjecture a lower bound for m and we prove it in several classes of semigroups.     

Reoptimizing the 0-1 knapsack problem

In this paper we study the problem where an optimal solution of a knapsack problem on n items is known and a very small number k of new items arrive. The objective is to find an optimal solution of the knapsack problem with n+k items, given an optimal solution on the n items (reoptimization of the knapsack problem). We show that this problem, even in the case k=1, is NP-hard and that, in order to have effective heuristics, it is necessary to consider not only the items included in the previously optimal solution and the new items, but also the discarded items. Then, we design a general algorithm that makes use, for the solution of a subproblem, of an α-approximation algorithm known for the knapsack problem. We prove that this algorithm has a worst-case performance bound of , which is always greater than α, and therefore that this algorithm always outperforms the corresponding α-approximation algorithm applied from scratch on the n+k items. We show that this bound is tight when the classical Ext-Greedy algorithm and the algorithm are used to solve the subproblem. We also show that there exist classes of instances on which the running time of the reoptimization algorithm is smaller than the running time of an equivalent PTAS and FPTAS.     

Robust portfolio asset allocation and risk measures

Many financial optimization problems involve future values of security prices, interest rates and exchange rates which are not known in advance, but can only be forecast or estimated. Several methodologies have therefore, been proposed to handle the uncertainty in financial optimization problems. One such methodology is Robust Statistics, which addresses the problem of making estimates of the uncertain parameters that are insensitive to small variations. A different way to achieve robustness is provided by Robust Optimization which, given optimization problems with uncertain parameters, looks for solutions that will achieve good objective function values for the realization of these parameters in given uncertainty sets. Robust Optimization thus offers a vehicle to incorporate an estimation of uncertain parameters into the decision making process. This is true, for example, in portfolio asset allocation. Starting with the robust counterparts of the classical mean-variance and minimum-variance portfolio optimization problems, in this paper we review several mathematical models, and related algorithmic approaches, that have recently been proposed to address uncertainty in portfolio asset allocation, focusing on Robust Optimization methodology. We also give an overview of some of the computational results that have been obtained with the described approaches. In addition we analyse the relationship between the concepts of robustness and convex risk measures.     

Bioactive clerodane diterpenes from roots of Carex distachya

Two new clerodane diterpenes were isolated from roots of Carex distachya Desf., a perennial plant widely distributed in the coastal area of the Mediterranean basin. Chemical characterization of the metabolites was carried out mainly by 1D and 2D NMR spectroscopy. The isolated compounds influenced either positively or negatively the plant growth (root and shoot elongation) of three coexisting herbaceous species.