Simulation-based density estimation for time series using covariate data

This paper proposes a simulation-based density estimation technique for time series that exploits information found in covariate data. The method can be paired with a large range of parametric models used in time series estimation. We derive asymptotic properties of the estimator and illustrate attractive finite sample properties for a range of well-known econometric and financial applications.

Enhanced sensitivity in detection of Kerr rotation by double modulation and time averaging based on Allan variance

Experiments in spintronics necessarily involve the detection of spin polarization. The sensitivity of this detection becomes an important factor to consider when extending the low temperature studies on semiconductor spintronic devices to room temperature, where the spin signal is weaker. In pump-probe experiments, which optically inject and detect spins, the sensitivity is often improved by using a photoelastic modulator (PEM) for lock-in detection. However, spurious signals can arise if diode lasers are used as optical sources in such experiments, along with a PEM. In this work, we eliminated the spurious electromagnetic coupling of the PEM onto the probe diode laser, by the double modulation technique. We also developed a test for spurious modulated interference in the pump-probe signal, due to the PEM. Besides, an order of magnitude enhancement in the sensitivity of detection of spin polarization by Kerr rotation, to 3x10(-8) rad was obtained by using the concept of Allan variance to optimally average the time series data over a period of 416 s. With these improvements, we are able to experimentally demonstrate at room temperature, photoinduced steady-state spin polarization in bulk GaAs. Thus, the advances reported here facilitate the use of diode lasers with a PEM for sensitive pump-probe experiments. They also constitute a step toward detection of spin-injection in Si at room temperature.

Extending the Supramolecular Synthon Based Fragment Approach (SBFA) for Transferability of Multipole Charge Density Parameters to Monofluorobenzoic Acids and their Cocrystals with Isonicotinamide: Importance of C-H center dot center dot center dot O, C-H center dot center dot center dot F, and F center dot center dot center dot F Intermolecular Regions

An extension of the supramolecular synthon-based fragment approach (SBFA) method for transferability of multipole charge density parameters to include weak supramolecular synthons is proposed. In particular, the SBFA method is applied to C-H center dot center dot center dot O, C-H center dot center dot center dot F, and F center dot center dot center dot F containing synthons. A high resolution charge density study has been performed on 4-fluorobenzoic acid to build a synthon library for C-H center dot center dot center dot F infinite chain interactions. Libraries for C-H center dot center dot center dot O and F center dot center dot center dot F synthons were taken from earlier work. The SBFA methodology was applied successfully to 2- and 3-fluorobenzoic acids, data sets for which were collected in a routine manner at 100 K, and the modularity of the synthons was demonstrated. Cocrystals of isonicotinamide with all three fluorobenzoic acids were also studied with the SBFA method. The topological analysis of inter- and intramolecular interaction regions was performed using Bader's AIM approach. This study shows that the SBFA method is generally applicable to generate charge density maps using information from multiple intermolecular regions.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix.

Fourier spectrum based extraction of an equivalent trap state density in indium gallium zinc oxide transistors

Segregating the dynamics of gate bias induced threshold voltage shift, and in particular, charge trapping in thin film transistors (TFTs) based on time constants provides insight into the different mechanisms underlying TFTs instability. In this Letter we develop a representation of the time constants and model the magnitude of charge trapped in the form of an equivalent density of created trap states. This representation is extracted from the Fourier spectrum of the dynamics of charge trapping. Using amorphous In-Ga-Zn-O TFTs as an example, the charge trapping was modeled within an energy range of Delta E-t approximate to 0.3 eV and with a density of state distribution as D-t(Et-j) = D-t0 exp(-Delta E-t/kT) with D-t0 = 5.02 x 10(11) cm(-2) eV(-1). Such a model is useful for developing simulation tools for circuit design. (C) 2014 AIP Publishing LLC.

In vitro osteogenic cell proliferation, mineralization, and in vivo osseointegration of injection molded high-density polyethylene-based hybrid composites in rabbit animal model

The present work reports the biocompatibility property of injection molded HDPE-HA-Al2O3 hybrid composites. In vitro cytocompatibility results reveal that osteogenic cell viability and bone mineralization are favorably supported in a statistically significant manner on HDPE-20% HA-20% Al2O3 composite, in comparison to HDPE-40 wt.% HA or HDPE-40 wt.% Al2O3. The difference in cytocompatibility property is explained in terms of difference in substrate wettability/surface energy and importantly, both the cell proliferation at 7 days or bone mineralization at 21 days on HDPE-20% HA-20% Al2O3 composite are either comparable or better than sintered HA. The progressive healing of cylindrical femoral bone defects in rabbit animal model was assessed by implantation experiments over 1, 4 and 12 weeks. Based on the histological analysis as well as histomorphometrical evaluation, a better efficacy of HDPE-20% HA-20% Al2O3 over high-density polyethylene (HDPE) for bone regeneration and neobone formation at host bone-implant interface was established. Taken together, the present study unequivocally establishes that despite the presence of 20% Al2O3, HDPE-based hybrid composites are as biocompatible as HA in vitro or better than HDPE in vivo.

Density functional theory based study of chlorine doped WS2-metal interface

Investigation of a transition metal dichalcogenide (TMD)-metal interface is essential for the effective functioning of monolayer TMD based field effect transistors. In this work, we employ the Density Functional Theory calculations to analyze the modulation of the electronic structure of monolayer WS2 with chlorine doping and the relative changes in the contact properties when interfaced with gold and palladium. We initially examine the atomic and electronic structures of pure and doped monolayer WS2 supercell and explore the formation of midgap states with band splitting near the conduction band edge. Further, we analyze the contact nature of the pure supercell with Au and Pd. We find that while Au is physiosorbed and forms n-type contact, Pd is chemisorped and forms p-type contact with a higher valence electron density. Next, we study the interface formed between the Cl-doped supercell and metals and observe a reduction in the Schottky barrier height (SBH) in comparison to the pure supercell. This reduction found is higher for Pd in comparison to Au, which is further validated by examining the charge transfer occurring at the interface. Our study confirms that Cl doping is an efficient mechanism to reduce the n-SBH for both Au and Pd, which form different types of contact with WS2. (C) 2016 AIP Publishing LLC.

An analysis of collective damage for short fatigue cracks based on equilibrium of crack numerical density

Collective damage of short fatigue cracks was analyzed in the light of equilibrium of crack numerical density. With the estimation of crack growth rate and crack nucleation rate, the solution of the equilibrium equation was studied to reveal the distinct feature of saturation distribution for crack numerical density. The critical time that characterized the transition of short and long-crack regimes was estimated, in which the influences of grain size and grain-boundary obstacle effect were investigated. Furthermore, the total number of cracks and the first order of damage moment were discussed.

A New Ignition Criterion Based Upon a Critical Thermal Energy Density

It has long been known that various ignition criteria of energetic materials have been limited in applicability to small regions. In order to explore the physical nature of ignition, we calculated how much thermal energy per unit mass of energetic materials was absorbed under different external stimuli. Hence, data of several typical sensitivity tests were analyzed by order of magnitude estimation. Then a new concept on critical thermal energy density was formulated. Meanwhile, the chemical nature of ignition was probed into by chemical kinetics.

Enhanced cycling performance and high energy density of LiFePO4 based lithium ion batteries

LiFePO4 attracts a lot of attention as cathode materials for the next generation of lithium ion batteries. However, LiFePO4 has a poor rate capability attributed to low electronic conductivity and low density. There is seldom data reported on lithium ion batteries with LiFePO4 as cathode and graphite as anode. According to our experimental results, the capacity fading on cycling is surprisingly negligible at 1664 cycles for the cell type 042040. It delivers a capacity of 1170 mAh for 18650 cell type at 4.5C discharge rate. It is confirmed that lithium ion batteries with LiFePO4 as cathode are suitable for electric vehicle application. (c) 2007 Elsevier B.V. All rights reserved.