Optimum design for maximum wavelength resolution for an edge filter-based ratiometric system

This paper provides a straightforward design method for achieving a maximum wavelength resolution for an edge filter-based ratiometric system. An analysis of the influence of a range of factors on the resolution of the ratiometric wavelength measurement system was carried out. The investigation shows that, for a given input optical signal and when the working wavelength range is known, it is relatively straightforward to select an optimum slope for the edge filter that will yield a maximum resolution for the system. An experimental verification is carried out using a tunable laser and three macrobending fibre edge filters, with a good match between experimental and simulation results.     

Novel Galvanic Nanostructures of Ag and Pd for Efficient Laser Desorption/Ionization of Low Molecular Weight Compounds

A simple approach for synthesis of palladium and silver nanostructures with readily adjustable morphologies was developed using galvanic electrochemical deposition, for application to surface-assisted laser desorption/ionization (SALDI) of small biological molecules. A range of fatty acids, triglycerides, carbohydrates, and antibiotics were investigated to assess the performance of the new materials. Intense analyte cations were generated from the galvanic surfaces upon UV laser irradiation such as potassium adducts for a film thickness <100 nm (originating from impurities of the electrolyte solution) and Pd and Ag cluster ions for films with a thickness >120 nm. Possible laser desorption/ionization mechanisms of these galvanic structures are discussed. The films exhibited self-organizing abilities and adjustable morphologies by changing electrochemical parameters. They did not require any stabilizing agents and were inexpensive and very easy to produce. SALDI analysis showed that the materials were stable under ambient conditions and analytical results with excellent measurement reproducibility and detection sensitivity similar to MALDI were obtained. Finally, we applied the galvanic surfaces to fast screening of natural oils with minimum sample preparation.

Measurement of mercury species in human blood using triple spike isotope dilution with SPME-GC-ICP-DRC-MS

The measurement of different mercury compounds in human blood can provide valuable information about the type of mercury exposure. To this end, our laboratory developed a biomonitoring method for the quantification of inorganic (iHg), methyl (MeHg), and ethyl (EtHg) mercury in whole blood using a triple-spike isotope dilution (TSID) quantification method employing capillary gas chromatography (GC) and inductively coupled dynamic reaction cell mass spectrometry (ICP-DRC-MS). We used a robotic CombiPAL® sample handling station featuring twin fiber-based solid-phase microextraction (SPME) injector heads. The use of two SPME fibers significantly reduces sample analysis cycle times making this method very suitable for high sample throughput, which is a requirement for large public health biomonitoring studies. Our sample preparation procedure involved solubilization of blood samples with tetramethylammonium hydroxide (TMAH) followed by the derivatization with sodium tetra(n-propyl)borate (NaBPr₄) to promote volatility of mercury species. We thoroughly investigated mercury species stability in the blood matrix during the course of sample treatment and analysis. The method accuracy for quantifying iHg, MeHg, and EtHg was validated using NIST standard reference materials (SRM 955c level 3) and the Centre de Toxicologie du Québec (CTQ) proficiency testing (PT) samples. The limit of detection (LOD) for iHg, MeHg, and EtHg in human blood was determined to be 0.27, 0.12, and 0.16 μg/L, respectively.

Preconditioned iterative methods for diffusion problems with high‐contrast inclusions

This paper is concerned with robust numerical treatment of an elliptic PDE with high‐contrast coefficients, for which classical finite‐element discretizations yield ill‐conditioned linear systems. This paper introduces a procedure by which the discrete system obtained from a linear finite element discretization of the given continuum problem is converted into an equivalent linear system of the saddle‐point type. Three preconditioned iterative procedures—preconditioned Uzawa, preconditioned Lanczos, and preconditioned conjugate gradient for the square of the matrix—are discussed for a special type of the application, namely, highly conducting particles distributed in the domain. Robust preconditioners for solving the derived saddle‐point problem are proposed and investigated. Robustness with respect to the contrast parameter and the discretization scale is also justified. Numerical examples support theoretical results and demonstrate independence of the number of iterations of the proposed iterative schemes on the contrast in parameters of the problem and the mesh size.     

Multivariate Count Data Models for Time Series Forecasting

Count data appears in many research fields and exhibits certain features that make modeling difficult. Most popular approaches to modeling count data can be classified into observation and parameter-driven models. In this paper, we review two models from these classes: the log-linear multivariate conditional intensity model (also referred to as an integer-valued generalized autoregressive conditional heteroskedastic model) and the non-linear state-space model for count data. We compare these models in terms of forecasting performance on simulated data and two real datasets. In simulations, we consider the case of model misspecification. We find that both models have advantages in different situations, and we discuss the pros and cons of inference for both models in detail.     

Deactivation of excited states of kynurenine covalently linked to nitroxides

Due to ability of stable nitroxides to interact with free radicals, they are used as antioxidants for therapeutic and research goals in biology and medicine. A modern trend in medical chemistry is the design of multifunctional molecules such as UV absorbers covalently bound to nitroxides, which provides both UV protection and antioxidant properties combined in the same molecule. In the present work, we report the synthesis of conjugates of a natural UV filter kynurenine (KN) with nitroxides (KN‐RNO^• conjugates) and the study of their photochemical properties in aqueous and methanol solutions. Due to the spin‐exchange interaction between KN and nitroxide moieties, the triplet lifetimes in conjugates are much shorter than in KN molecule, but the triplet quantum yields are significantly higher. The reaction of intramolecular electron transfer between photoexcited KN and nitroxide moieties is the main factor determining the quantum yield of KN‐RNO^• conjugates photodecomposition. Consequently, KN‐RNO^• conjugates in aqueous solution are photochemically less stable than the parent KN molecule. Nevertheless, the photostability of KN‐RNO^• conjugates is much higher than that of cinnamates which are widely used as UV absorbers in modern sunscreen formulations. Thus, the combination of the endogenous chromophore KN with nitroxides is very promising for medical applications.     

Ultrafilter semigroups generated by direct sums

Let λ be an infinite cardinal and for every ordinal α<λ, let A _α be a set with a distinguished element 0 _α ∈A _α . The direct sum of sets A _α , α<λ, is the subset \(X=\bigoplus_{\alpha<\lambda}A_{\alpha}\) of the Cartesian product ∏_α<λ A _α consisting of all x with finite supp?(x)={α<λ:x(α)≠0 _α }. Endow X with a topology by taking as a neighborhood base at x∈X the subsets of the form {y∈X:y(α)=x(α) for all α<γ} where γ<λ. Let Ult?(X) denote the set of all nonprincipal ultrafilters on X converging to 0∈X. There is a natural partial semigroup operation on X which induces a semigroup operation on Ult?(X). We show that if direct sums X and Y are homeomorphic, then the semigroups Ult?(X) and Ult?(Y) are isomorphic.     

Functional central limit theorems for self-normalized least squares processes in regression with possibly infinite variance data

Based on an R²-valued random sample {(y_i,x_i),1≤i≤n} on the simple linear regression model y_i=x_iβ+α+ε_i with unknown error variables ε_i, least squares processes (LSPs) are introduced in D[0,1] for the unknown slope β and intercept α, as well as for the unknown β when α=0. These LSPs contain, in both cases, the classical least squares estimators (LSEs) for these parameters. It is assumed throughout that {(x,ε),(x_i,ε_i),i≥1} are i.i.d. random vectors with independent components x and ε that both belong to the domain of attraction of the normal law, possibly both with infinite variances. Functional central limit theorems (FCLTs) are established for self-normalized type versions of the vector of the introduced LSPs for (β,α), as well as for their various marginal counterparts for each of the LSPs alone, respectively via uniform Euclidean norm and sup–norm approximations in probability. As consequences of the obtained FCLTs, joint and marginal central limit theorems (CLTs) are also discussed for Studentized and self-normalized type LSEs for the slope and intercept. Our FCLTs and CLTs provide a source for completely data-based asymptotic confidence intervals for β and α.