A perturbed martingale approach to global optimization

A new global stochastic search, guided mainly through derivative-free directional information computable from the sample statistical moments of the design variables within a Monte Carlo setup, is proposed. The search is aided by imparting to the directional update term additional layers of random perturbations referred to as ‘coalescence’ and ‘scrambling’. A selection step, constituting yet another avenue for random perturbation, completes the global search. The direction-driven nature of the search is manifest in the local extremization and coalescence components, which are posed as martingale problems that yield gain-like update terms upon discretization. As anticipated and numerically demonstrated, to a limited extent, against the problem of parameter recovery given the chaotic response histories of a couple of nonlinear oscillators, the proposed method appears to offer a more rational, more accurate and faster alternative to most available evolutionary schemes, prominently the particle swarm optimization.     

Markov processes conditioned on their location at large exponential times

Suppose that ${\left(X_t\right)}_{t\ge 0}$ is a one-dimensional Brownian motion with negative drift $?\mu$. It is possible to make sense of conditioning this process to be in the state 0 at an independent exponential random time and if we kill the conditioned process at the exponential time the resulting process is Markov. If we let the rate parameter of the random time go to 0, then the limit of the killed Markov process evolves like $X$ conditioned to hit 0, after which time it behaves as $X$ killed at the last time $X$ visits 0. Equivalently, the limit process has the dynamics of the killed “bang–bang” Brownian motion that evolves like Brownian motion with positive drift $+\mu$ when it is negative, like Brownian motion with negative drift $?\mu$ when it is positive, and is killed according to the local time spent at 0.An extension of this result holds in great generality for a Borel right process conditioned to be in some state $a$ at an exponential random time, at which time it is killed. Our proofs involve understanding the Campbell measures associated with local times, the use of excursion theory, and the development of a suitable analogue of the “bang–bang” construction for a general Markov process.As examples, we consider the special case when the transient Borel right process is a one-dimensional diffusion. Characterizing the limiting conditioned and killed process via its infinitesimal generator leads to an investigation of the $h$-transforms of transient one-dimensional diffusion processes that goes beyond what is known and is of independent interest.     

Local boundedness of weak solutions to the Diffusive Wave Approximation of the Shallow Water equations

In this paper we prove that weak solutions to the Diffusive Wave Approximation of the Shallow Water equations

${?}_{t}u?\mathrm{?}?({(u?z)}^{\alpha }|\mathrm{?}u{|}^{\gamma ?1}\mathrm{?}u)=f$

are locally bounded. Here, u describes the height of the water, z is a given function that represents the land elevation and f is a source term accounting for evaporation, infiltration or rainfall.     

Classical Backfitting for Smooth-Backfitting Additive Models

Smooth backfitting has been shown to have better theoretical properties than classical backfitting for fitting additive models based on local linear regression. In this article, we show that the smooth backfitting procedure in the local linear case can be alternatively performed as a classical backfitting procedure with a different type of smoother matrices. These smoother matrices are symmetric and shrinking and some established results in the literature are readily applicable. The connections allow the smooth backfitting algorithm to be implemented in a much simplified way, give new insights on the differences between the two approaches in the literature, and provide an extension to local polynomial regression. The connections also give rise to a new estimator at data points. Asymptotic properties of general local polynomial smooth backfitting estimates are investigated, allowing for different orders of local polynomials and different bandwidths. Cases of oracle efficiency are discussed. Computer-generated simulations are conducted to demonstrate finite sample behaviors of the methodology and a real data example is given for illustration. Supplementary materials for this article are available online.     

Strategies for differentiation of isobaric flavonoids using liquid chromatography coupled to electrospray ionization mass spectrometry

Flavonoids are a class of secondary plant metabolites existing in great variety in nature. Due to this variety, identification can be difficult, especially as overlapping compounds in both chromatographic separations and mass spectrometric detection are common. Methods for distinguishing isobaric flavonoids using MS² and MS³ have been developed. Chromatographic separation of various plant extracts was done with RP‐HPLC and detected with positive ESI‐MS operated in information‐dependent acquisition (IDA) mode. Two methods for the determination of flavonoid identity and substitution pattern, both featuring IDA criteria, were used together with the HPLC equipment. A third method where the collision energy was ramped utilized direct infusion. With the developed strategies, it is possible to differentiate between many isobaric flavonoids. Various classes of flavonoids were found in all of the plant extracts, in the red onion extract 45 components were detected and for 29 of them the aglycone was characterized, while the substituents were tentatively identified for 31 of them. For the strawberry extract, those numbers were 66, 30 and 60, and for the cherry extract 99, 56 and 71. The great variety of flavonoids, several of them isobaric, found in each of the extracts highlights the need for reliable methods for flavonoid characterization. Methods capable of differentiating between most of the isobars analyzed have been developed. Copyright © 2014 John Wiley & Sons, Ltd.     

Plasmonic nanostructures for local field enhancement in the UV region

In this work we describe an ultraviolet subwavelength focusing in plasmonic nanostructures. A system which provides a 20–25 times local field enhancement at a wavelength of 350 nm is proposed. This system represents a metalized V-shaped groove in a surface of a dielectric medium. Subwavelength focusing is achieved by a plasmon wave propagation along the surface of metal film and by the transfer of electromagnetic field through the dielectric medium. The influence of system parameters on a local field enhancement is investigated. A simplified model that allows for determining the geometric parameters of an optimized resonator is proposed.     

Novel matrix invariants for characterization of changes of proteomics maps

Previous studies on mathematical characterization of proteomics maps by sets of map invariants were based on the construction of a set of distance-related matrices obtained by matrix multiplication of a single matrix by itself. Here we consider an alternative characterization of proteomics maps based on a set of matrices characterizing local features of an embedded zigzag curve over the map. It is shown that novel invariants can well characterize proteomics maps. Advantages of the novel approach are discussed.