Sequential Bayesian learning for stochastic volatility with variance‐gamma jumps in returns

In this work, we investigate sequential Bayesian estimation for inference of stochastic volatility with variance‐gamma (SVVG) jumps in returns. We develop an estimation algorithm that combines the sequential learning auxiliary particle filter with the particle learning filter. Simulation evidence and empirical estimation results indicate that this approach is able to filter latent variances, identify latent jumps in returns, and provide sequential learning about the static parameters of SVVG. We demonstrate comparative performance of the sequential algorithm and off‐line Markov Chain Monte Carlo in synthetic and real data applications.     

Conformational and orientational guidance of the analgesic dipeptide kyotorphin induced by lipidic membranes: putative correlation toward receptor docking

The analgesic dipeptide kyotorphin (L-Tyr-L-Arg) and an acylated kyotorphin derivative were studied by a combination of theoretical (molecular dynamics simulation and quantum mechanics methods) and experimental (fluorescence and infrared spectroscopies) approaches both in solution and in model systems of membranes. At biological pH the peptides have a neutral net charge. Nevertheless, their phenolic rings interact with phospholipid molecules (partition coefficient varies from 6 x 10(2) to 2 x 10(4), depending on the lipid and pH used) despite being exposed to the aqueous bulk medium. The lowest energy transition dipole moment is displaced from the normal to the lipid bilayer by 20 degrees on average. The observed extensive interaction, pK(a), precise location, and well-defined orientation in membranes combined with the ability to discriminate rigid raftlike membrane domains suggest that kyotorphin meets the structural constraints needed for receptor-ligand interaction. The acylated kyotorphin derivative mimics kyotorphin properties and represents a promising way for entrapment in a drug carrier and transport across the blood-brain barrier.     

Development of an empirical force field for silica. Application to the quartz-water interface

Interactions of pulverized crystalline silica with biological systems, including the lungs, cause cell damage, inflammation, and apoptosis. To allow computational atomistic modeling of these pathogenic processes, including interactions between silica surfaces and biological molecules, new parameters for quartz, compatible with the CHARMM empirical force field were developed. Parameters were optimized to reproduce the experimental geometry of alpha-quartz, ab initio vibrational spectra, and interactions between model compounds and water. The newly developed force field was used to study interactions of water with two singular surfaces of alpha-quartz, (011) and (100). Properties monitored and analyzed include the variation of the density of water molecules in the plane perpendicular to the surface, disruption of the water H-bond network upon adsorption, and space-time correlations of water oxygen atoms in terms of Van Hove self-correlation functions. The vibrational density of states spectra of water in confined compartments were also computed and compared with experimental neutron-scattering results. Both the attenuation and shifting to higher frequencies of the hindered translational peaks upon confinement are clearly reproduced by the model. However, an upshift of librational peaks under the conditions of model confinement still remains underrepresented at the current empirical level.     

On the sigma-model of deformed special geometry

We discuss the deformed sigma-model that arises when considering four-dimensional N=2$N=2$ abelian vector multiplets in the presence of an arbitrary chiral background field. In addition, we allow for a class of deformations of special geometry by non-holomorphic terms. We analyze the geometry of the sigma-model in terms of intrinsic torsion classes. We show that, generically, the deformed geometry is non-Kähler. We illustrate our findings with an example. We also express the deformed sigma-model in terms of the Hesse potential that underlies the real formulation of special geometry.     

Effect of high hydrostatic pressure on phenolic compounds,ascorbic acid and antioxidant activity in cashew apple juice

The cashew apple is native to Brazil, but there is insufficient information regarding the nutritional properties of this fruit. The objective of this study was to evaluate the impact of high pressure processing (HPP) at room temperature (25 °C) on phenolic compound and ascorbic acid contents and antioxidant capacity of cashew apple juice. This study showed that HPP at 250 or 400 MPa for 3, 5 and 7 min did not change pH, acidity, total soluble solids, ascorbic acid or hydrolysable polyphenol contents. However, juice pressurized for 3 and 5 min showed higher soluble polyphenol contents. Antioxidant capacity, measured by the ferric-reducing antioxidant power method, was not altered by HPP, but when treated at 250 MPa for 3 min, it resulted in an increased value when 2,2-diphenyl-1-picrylhydrazyl was used. These data demonstrate that HPP can be used in the food industry for the generation of products with higher nutritional quality.     

Deformation and rigidity results for the 2k‐Ricci tensor and the 2k‐Gauss‐Bonnet curvature

We present several deformation and rigidity results within the classes of closed Riemannian manifolds which either are 2k‐Einstein (in the sense that their 2k‐Ricci tensor is constant) or have constant 2k‐Gauss‐Bonnet curvature. The results hold for a family of manifolds containing all non‐flat space forms and the main ingredients in the proofs are explicit formulae for the linearizations of the above invariants obtained by means of the formalism of double forms.     

A spatial scan statistic for case event data based on connected components

We propose a new spatial scan statistic based on graph theory as a method for detecting irregularly-shaped clusters of events over space. A graph-based method is proposed for identifying potential clusters in spatial point processes. It relies on linking the events closest than a given distance and thus defining a graph associated to the point process. The set of possible clusters is then restricted to windows including the connected components of the graph. The concentration in each of these possible clusters is measured through classical concentration indices based on likelihood ratio and also through a new concentration index which does not depend on any alternative hypothesis. These graph-based spatial scan tests seem to be very powerful against any arbitrarily-shaped cluster alternative, whatever the dimension of the data. These results have applications in various fields, such as the epidemiological study of rare diseases or the analysis of astrophysical data.     

Computational scheme for solving nonlinear fractional stochastic differential equations with delay

Abstract

This paper studies the numerical solution of fractional stochastic delay differential equations driven by Brownian motion. The proposed algorithm is based on linear B-spline interpolation. The convergence and the numerical performance of the method are analyzed. The technique is adopted for determining the statistical indicators of stochastic responses of fractional Langevin and Mackey-Glass models with stochastic excitations.     

Selection of intensity modulated radiation therapy treatment beam directions using radial basis functions within a pattern search methods framework

The selection of appropriate radiation incidence directions in radiation therapy treatment planning is important for the quality of the treatment plan, both for appropriate tumor coverage and for better organ sparing. The objective of this paper is to discuss the benefits of using radial basis functions within a pattern search methods framework in the optimization of the highly non-convex beam angle optimization (BAO) problem. Pattern search methods are derivative-free optimization methods that require few function value evaluations to converge and have the ability to avoid local entrapment. These two characteristics gathered together make pattern search methods suited to address the BAO problem. The pattern search methods framework is composed by a search step and a poll step at each iteration. The poll step performs a local search in a mesh neighborhood and assures convergence to a local minimizer or stationary point. The search step provides the flexibility for a global search since it allows searches away from the neighborhood of the current iterate. Radial basis functions are used and tested in this step both to influence the quality of the local minimizer found by the method and to obtain a better coverage of the search space in amplitude. A set of retrospective treated cases of head-and-neck tumors at the Portuguese Institute of Oncology of Coimbra is used to discuss the benefits of using this approach in the optimization of the BAO problem.     

Study of the Cost Functional for Free Material Design Problems

We study properties of the cost functional arising in free material optimization problems, with special emphasis on semicontinuity and its relation to convexity.