Viscosities of the Gay-Berne nematic liquid crystal

We present molecular dynamics simulation measurements of the viscosities of the Gay-Berne phenomenological model of liquid crystals in the nematic and isotropic phases. The temperature dependence of the rotational and shear viscosities, including the nonmonotonic behavior of one shear viscosity are in good agreement with experimental data. The bulk viscosities are significantly larger than the shear viscosities, again in agreement with experiment.Comment: 11 pages, 4 Postscript figures, Revte

Gravimetric sensors operating at 1.1 GHz based on inclined c-axis ZnO grown on textured Al electrodes

Shear mode solidly mounted resonators (SMRs) are fabricated using an inclined c-axis ZnO grown on a rough Al electrode. The roughness of the Al surface is controlled by changing the substrate temperature during the deposition process to promote the growth of inclined ZnO microcrystals. The optimum substrate temperature to obtain homogeneously inclined c-axis grains in ZnO films is achieved by depositing Al at 100 °C with a surface roughness ~9.2 nm, which caused an inclination angle of ~25° of the ZnO c-axis with respect to the surface normal. Shear mode devices with quality-factors at resonance, Q r and effective electromechanical coupling factors, [Formula: see text], as high as 180 and 3.4% are respectively measured. Mass sensitivities, S m of (4.9 ± 0.1) kHz · cm(2)/ng and temperature coefficient of frequency (TCF) of ~-67 ppm/K are obtained using this shear mode. The performance of the devices as viscosity sensors and biosensors is demonstrated by determining the frequency shifts of water-ethanol mixtures and detection of Rabbit immunoglobin G (IgG) whole molecule (H&L) respectively.The research leading to these results has received funding from the European Community’s Horizon 2020 Programme under Grant Agreement No. SPIRE-01-2014-636820, the IC1208 Cost action, and from the Ministerio de Economía y Competitividad del Gobierno de España through the project MAT2013-45957-R. Financial support from these institutions is therefore gratefully acknowledged. G.R. also wishes to acknowledge funding from the Cambridge Commonwealth, European and International Trust

Carbon nanotube forests as top electrode in electroacoustic resonators

We grow carbon nanotube forests on piezoelectric AlN films and fabricate and characterize nanotube-based solidly mounted bulk acoustic wave resonators employing the forests as the top electrode material. The devices show values for quality factor at anti-resonance of ∼430, and at resonance of ∼100. The effective coupling coefficient is of ∼6%, and the resonant frequencies are up to ∼800 MHz above those observed with metallic top electrodes. AlN promotes a strong catalyst-support interaction, which reduces Fe catalyst mobility, and thus enforces the growth of forests by the base growth mechanism.This work was partially supported by the European Commission through the project GRAFOL and the COST action IC1208 and by the Ministerio de Economía y Competitividad del Gobierno de España through project MAT2013-45957.This is the accepted manuscript. The final version is available at http://scitation.aip.org/content/aip/journal/apl/107/13/10.1063/1.4932197

Regularizing Portfolio Optimization

The optimization of large portfolios displays an inherent instability to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification "pressure". This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade-off between the two, depending on the size of the available data set

The merit of high-frequency data in portfolio allocation

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a multi-scale spectral decomposition where volatilities, correlation eigenvalues and eigenvectors evolve on different frequencies. In an extensive out-of-sample forecasting study, we show that the proposed approach yields less risky and more diversified portfolio allocations as prevailing methods employing daily data. These performance gains hold over longer horizons than previous studies have shown

Strategies used as spectroscopy of financial markets reveal new stylized facts

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions and (iii) real investors to random strategies with respect to timing that share otherwise all other characteristics. We find that more trading results in smaller net return due to trading frictions. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by investors. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.Comment: 13 pages including 5 figures and 1 tabl

A micro-accelerometer MDO benchmark problem

Many optimization and coordination methods for multidisciplinary design optimization (MDO) have been proposed in the last three decades. Suitable MDO benchmark problems for testing and comparing these methods are few however. This article presents a new MDO benchmark problem based on the design optimization of an ADXL150 type lateral capacitive micro-accelerometer. The behavioral models describe structural and dynamic effects, as well as electrostatic and amplification circuit contributions. Models for important performance indicators such as sensitivity, range, noise, and footprint area are presented. Geometric and functional constraints are included in these models to enforce proper functioning of the device. The developed models are analytical, and therefore highly suitable for benchmark and educational purposes. Four different problem decompositions are suggested for four design cases, each of which can be used for testing MDO coordination algorithms. As a reference, results for an all-in-one implementation, and a number of augmented Lagrangian coordination algorithms are given. © 2009 The Author(s)