On an analogue of the Euler-Cauchy polygon method for the numerical solution of ux y = f(x,y, u,ux, uy)

This paper develops, with an eye on the numerical applications, an analogue of the classical Euler-Cauchy polygon method (which is used in the solution of the ordinary differential equation dy/dx=f(x, y), y(x ₀)=y ₀) for the solution of the following characteristic boundary value problem for a hyperbolic partial differential equation u _xy =f(x, y, u, u _x , y _y ), u(x, y ₀)=(x), u(x ₀, y)=(y), where (x ₀)=(y ₀). The method presented here, which may be roughly described as a process of bilinear interpolation, has the advantage over previously proposed methods that only the tabulated values of the given functions (x) and (y) are required for its numerical application. Particular attention is devoted to the proof that a certain sequence of approximating functions, constructed in a specified way, actually converges to a solution of the boundary value problem under consideration. Known existence theorems are thus proved by a process which can actually be employed in numerical computation.

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Predictive modeling and analysis of HfO2 thin film process based on Bayesian information criterion using PCA‐based neural networks

Principal component analysis (PCA)‐based neural network (NNet) models of HfO₂ thin films are used to study the process of efficient model selection and develop an improved model by using multivariate functional data such as X‐ray diffraction data (XRD). The accumulation capacitance and the hysteresis index input parameters, both characteristic of HfO₂ dielectric films, were selected for the inclusion in the model by analyzing the process conditions. Standardized XRD were used to analyze the characteristic variations for different process conditions; the responses and the electrical properties were predicted by NNet modeling using crystallinity‐based measurement data. A Bayesian information criterion (BIC) was used to compare the model efficiency and to select an improved model for response prediction. Two conclusions summarize the results of the research documented in this paper: (i) physical or material properties can be predicted by the PCA‐based NNet model using large‐dimension data, and (ii) BIC can be used for the selection and evaluation of predictive models in semiconductor manufacturing processes. Copyright © 2013 John Wiley & Sons, Ltd.     

Neutron bound states in a supersymmetric double Dirac delta electrostatic potential

We study neutron bound states in a particular (1+1)‐supersymmetric configuration. A simple physical setup is chosen so that the effective interaction becomes a particular kind of double Dirac delta potential. In this configuration it is shown that the neutron distinguishes between positive and negative electric charge as a consequence of a purely quantum mechanical effect. The theoretical background is presented and a possible application to a real‐life physical system is discussed.     

Incompletely condensed fluoroalkyl silsesquioxanes and derivatives: precursors for low surface energy materials

A novel synthetic method was developed for the controlled functionalization of fluorinated polyhedral oligomeric silsesquioxanes (F-POSS), which are useful as low surface energy materials for superhydrophobic and superoleophobic materials. Utilizing triflic acid, open-cage compounds were created and then reacted with a variety of dichlorosilanes to produce functional F-POSS structures possessing alkyl-, aryl-, and acrylate-based moieties. The crystal structure for an endo,endo-disilanol F-POSS compound was determined by single-crystal X-ray diffraction. The chemical structures were confirmed using multinuclear NMR spectroscopy ((1)H, (13)C, (19)F, and (29)Si), FT-IR, and combustion analysis. Dynamic contact angle measurements of these compounds were taken with water and hexadecane. These novel structures were found to possess excellent wetting-resistant behavior, similar to that of the parent F-POSS compound. They are the first well-defined fluorinated nano-building blocks with a controlled level of reactive functionality for the development of new superhydrophobic and superoleophobic materials.     

Peptide Modifications Differentially Alter G Protein‐Coupled Receptor Internalization and Signaling Bias

Although G protein‐coupled receptors (GPCRs) are targeted by more clinically used drugs than any other type of protein, their ligand development is particularly challenging. Humans have four neuropeptide Y receptors: hY₁R and hY₅R are orexigenic, while hY₂R and hY₄R are anorexigenic, and represent important anti‐obesity drug targets. We show for the first time that PEGylation and lipidation, chemical modifications that prolong the plasma half‐lives of peptides, confer additional benefits. Both modifications enhance pancreatic polypeptide preference for hY₂R/hY₄R over hY₁R/hY₅R. Lipidation biases the ligand towards arrestin recruitment and internalization, whereas PEGylation confers the opposite bias. These effects were independent of the cell system and modified residue. We thus provide novel insights into the mode of action of peptide modifications and open innovative venues for generating peptide agonists with extended therapeutic potential.     

Characterization and biological properties of a copper(II) complex with pyruvic acid thiosemicarbazone

Summary A copper(II) complex with pyruvic acid thiosemicarbazone (PTSC) of composition Cu(PTSC) (PTSC-H)Cl was characterized by IR, UV/Vis, and EPR spectroscopy. The antifungo, herbicide, cytotoxic and antitumor activities of the complex andPTSC are reported.

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Charakterisierung und biologische Eigenschaften eines Kupfer(II)-Komplexes mit Brenztraubensäurethiosemicarbazon

Zusammenfassung Ein Kupfer(II)-Komplex mit Brenztraubensäurethiosemicarbazon (PTSC) der Zusammensetzung Cu(PTSC)(PTSC-H)Cl wurde mittels IR-, UV/Vis- und EPR-Spektroskopie charakterisiert. Es wird über die antifungalen, herbiziden, cytotoxischen und antitumoralen Aktivitäten des Komplexes und vonPTSC berichtet.

     

A tabu search approach for solving a difficult forest harvesting machine location problem

This paper deals with two main problems in forest harvesting. The first is that of selecting the locations for the machinery to haul logs from the points where they are felled to the roadside. The second consists in designing the access road network connecting the existing road network with the points where machinery is installed. Their combination induces a very important and difficult problem to solve in forest harvesting. It can be formulated as a combination of two difficult optimization problems: a plant location problem and a fixed charge network flow problem. In this paper, we propose a solution approach based on tabu search. The proposed heuristic includes several enhancements of the basic tabu search framework. The main difficulty lies in evaluating neighboring solutions, which involves decisions related to location of machinery and to road network arcs. Hence, the neighborhood is more complex than in typical applications of metaheuristics. Minimum spanning tree algorithms and Steiner tree heuristics are used to deal with this problem. Numerical results indicate that the heuristic approach is very attractive and leads to better solutions than those provided by state-of-the-art integer programming codes in limited computation times, with solution times significantly smaller. The numerical results do not vary too much when typical parameters such as the tabu tenure are modified, except for the dimension of neighborhood.