Quantum and classical properties of the fields generated by two interlinked second-order non-linear interactions

We consider two interlinked non-linear interactions occurring simultaneously in a single chi((2)) crystal. Classical and quantum working regimes are considered and their peculiar properties analysed. In particular, we describe an experiment, realized in the classical regime, that verifies the holographic nature of the process, and predict, for the quantum regime, the generation of a fully inseparable tripartite Gaussian state of light that can be used to support a general 1--> 2 continuous variable telecloning protocol.

Loss of Synaptic Connectivity, Particularly in Second Order Neurons Is a Key Feature of Diabetic Retinal Neuropathy in the Ins2Akita Mouse

Retinal neurodegeneration is a key component of diabetic retinopathy (DR), although the detailed neuronal damage remains ill-defined. Recent evidence suggests that in addition to amacrine and ganglion cell, diabetes may also impact on other retinal neurons. In this study, we examined retinal degenerative changes in Ins2^Akita diabetic mice. In scotopic electroretinograms (ERG), b-wave and oscillatory potentials were severely impaired in 9-month old Ins2^Akita mice. Despite no obvious pathology in fundoscopic examination, optical coherence tomography (OCT) revealed a progressive thinning of the retina from 3 months onwards. Cone but not rod photoreceptor loss was observed in 3-month-old diabetic mice. Severe impairment of synaptic connectivity at the outer plexiform layer (OPL) was detected in 9-month old Ins2Akita mice. Specifically, photoreceptor presynaptic ribbons were reduced by 25% and postsynaptic boutons by 70%, although the density of horizontal, rod- and cone-bipolar cells remained similar to non-diabetic controls. Significant reductions in GABAergic and glycinergic amacrine cells and Brn3a+ retinal ganglion cells were also observed in 9-month old Ins2^Akita mice. In conclusion, the Ins2^Akita mouse develops cone photoreceptor degeneration and the impairment of synaptic connectivity at the OPL, predominately resulting from the loss of postsynaptic terminal boutons. Our findings suggest that the Ins2^Akita mouse is a good model to study diabetic retinal neuropathy.

A Lagrangian approach for modeling road collisions using second-order models of traffic flow

In [M. Herty, A. Klein, S. Moutari, V. Schleper, and G. Steinaur, IMA J. Appl. Math., 78(5), 1087–1108, 2013] and [M. Herty and V. Schleper, ZAMM J. Appl. Math. Mech., 91, 763–776, 2011], a macroscopic approach, derived from fluid-dynamics models, has been introduced to infer traffic conditions prone to road traffic collisions along highways’ sections. In these studies, the governing equations are coupled within an Eulerian framework, which assumes fixed interfaces between the models. A coupling in Lagrangian coordinates would enable us to get rid of this (not very realistic) assumption. In this paper, we investigate the well-posedness and the suitability of the coupling of the governing equations within the Lagrangian framework. Further, we illustrate some features of the proposed approach through some numerical simulations.

Blind Characterisation of Sensors with Second-Order Dynamic Response

Compensation for the dynamic response of a temperature sensor usually involves the estimation of its input on the basis of the measured output and model parameters. In the case of temperature measurement, the sensor dynamic response is strongly dependent on the measurement environment and fluid velocity. Estimation of time-varying sensor model parameters therefore requires continuous textit{in situ} identification. This can be achieved by employing two sensors with different dynamic properties, and exploiting structural redundancy to deduce the sensor models from the resulting data streams. Most existing approaches to this problem assume first-order sensor dynamics. In practice, however second-order models are more reflective of the dynamics of real temperature sensors, particularly when they are encased in a protective sheath. As such, this paper presents a novel difference equation approach to solving the blind identification problem for sensors with second-order models. The approach is based on estimating an auxiliary ARX model whose parameters are related to the desired sensor model parameters through a set of coupled non-linear algebraic equations. The ARX model can be estimated using conventional system identification techniques and the non-linear equations can be solved analytically to yield estimates of the sensor models. Simulation results are presented to demonstrate the efficiency of the proposed approach under various input and parameter conditions.

Second-Order Statistics of κ−µ Shadowed Fading Channels

In this paper, novel closed-form expressions for the level crossing rate and average fade duration of κ − μ shadowed fading channels are derived. The new equations provide the capability of modeling the correlation between the time derivative of the shadowed dominant and multipath components of the κ − μ shadowed fading envelope. Verification of the new equations is performed by reduction to a number of known special cases. It is shown that as the shadowing of the resultant dominant component decreases, the signal crosses lower threshold levels at a reduced rate. Furthermore, the impact of increasing correlation between the slope of the shadowed dominant and multipath components similarly acts to reduce crossings at lower signal levels. The new expressions for the second-order statistics are also compared with field measurements obtained for cellular device-to-device and body-centric communication channels, which are known to be susceptible to shadowed fading.

Analysis of the Second Harmonic Effect on Power Amplifier Intermodulation Products

A theoretical analysis is reported in this paper to investigate the effect that a second harmonic signal which might be present at an amplifier’s input has on generating additional intermodulation products, particularly the third-order intermodulation (IM3) products. The analysis shows that the amplitude of an extra generated IM3 component is equal to the product of the fundamental amplitude, the second harmonic amplitude, and the second order Taylor series coefficient. The effect of the second order harmonic on the IM3 is examined through a simulated example of a 2.22-GHz 10-W Class-EF amplifier whereby the IM3 levels have been reduced by 2-3 dB after employing a second harmonic termination stub at the input.

Ion-acoustic waves in a plasma consisting of adiabatic warm ions, non-isothermal electrons and a weakly relativistic electron beam: linear and higher-order nonlinear effects

The nonlinear propagation of finite amplitude ion acoustic solitary waves in a plasma consisting of adiabatic warm ions, nonisothermal electrons, and a weakly relativistic electron beam is studied via a two-fluid model. A multiple scales technique is employed to investigate the nonlinear regime. The existence of the electron beam gives rise to four linear ion acoustic modes, which propagate at different phase speeds. The numerical analysis shows that the propagation speed of two of these modes may become complex-valued (i.e., waves cannot occur) under conditions which depend on values of the beam-to-background-electron density ratio , the ion-to-free-electron temperature ratio , and the electron beam velocity v0; the remaining two modes remain real in all cases. The basic set of fluid equations are reduced to a Schamel-type equation and a linear inhomogeneous equation for the first and second-order potential perturbations, respectively. Stationary solutions of the coupled equations are derived using a renormalization method. Higher-order nonlinearity is thus shown to modify the solitary wave amplitude and may also deform its shape, even possibly transforming a simple pulse into a W-type curve for one of the modes. The dependence of the excitation amplitude and of the higher-order nonlinearity potential correction on the parameters , , and v0 is numerically investigated.

Kinetic analysis of the reaction between electrogenerated superoxide and carbon dioxide in the room temperature ionic liquids 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide and hexyltriethylammonium bis(trifluoromethylsulfonyl)imide

The reduction of oxygen in the presence of carbon dioxide has been investigated by cyclic voltammetry at a gold microdisk electrode in the two room-temperature ionic liquids 1-ethyl-3-methylimidazolium bis-(trifluoromethylsulfonyl)imide ([EMIM][N(Tf)(2)]) and hexyltriethylammonium bis(trifluoromethylsulfonyl)imide ([N-6222] [N(Tf)(2)]). With increasing levels of CO2, cyclic voltammetry shows an increase in the reductive wave and diminishing of the oxidative wave, indicating that the generated superoxide readily reacts with carbon dioxide. The kinetics of this reaction are investigated in both ionic liquids. The reaction was found to proceed via a DISP1 type mechanism in [EMIM][N(Tf)(2)] with an overall second-order rate constant of 1.4 +/- 0.4 x 10(3) M-1 s(-1). An ECE or DISP1 mechanism was determined to be the most likely pathway for the reaction in [N-6222][N(Tf)(2)], with an overall second-order rate constant of 1.72 +/- 0.45 x 10(3) m(-1) s(-1).

The use of ensemble empirical mode decomposition with canonical correlation analysis as a novel artifact removal technique

Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second-order statistics. The new technique is tested against the currently available wavelet denoising and EEMD-ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. © 1964-2012 IEEE.

A two-step approach for the analysis of hybrids in comparative social policy analysis: a nuanced typology of childcare policies

Typologies have represented an important tool for the development of comparative social policy research and continue to be widely used in spite of growing criticism of their ability to capture the complexity of welfare states and their internal heterogeneity. In particular, debates have focused on the presence of hybrid cases and the existence of distinct cross-national pattern of variation across areas of social policy. There is growing awareness around these issues, but empirical research often still relies on methodologies aimed at classifying countries in a limited number of unambiguous types. This article proposes a two-step approach based on fuzzy-set-ideal-type analysis for the systematic analysis of hybrids at the level of both policies (step 1) and policy configurations or combinations of policies (step 2). This approach is demonstrated by using the case of childcare policies in European economies. In the first step, parental leave policies are analysed using three methods – direct, indirect, and combinatory – to identify and describe specific hybrid forms at the level of policy analysis. In the second step, the analysis focus on the relationship between parental leave and childcare services in order to develop an overall typology of childcare policies, which clearly shows that many countries display characteristics normally associated with different types (hybrids and. Therefore, this two-step approach enhances our ability to account and make sense of hybrid welfare forms produced from tensions and contradictions within and between policies.

Thickness-induced stabilization of ferroelectricity in SrRuO3/Ba0.5Sr0.5TiO3/Au thin film capacitors

Pulsed-laser deposition has been used to fabricate Au/Ba0.5Sr0.5TiO3/SrRuO3/MgO thin film capacitor structures. Crystallographic and microstructural investigations indicated that the Ba0.5Sr0.5TiO3 (BST) had grown epitaxially onto the SrRuO3 lower electrode, inducing in-plane compressive and out- of-plane tensile strain in the BST. The magnitude of strain developed increased systematically as film thickness decreased. At room temperature this composition of BST is paraelectric in bulk. However, polarization measurements suggested that strain had stabilized the ferroelectric state, and that the decrease in film thickness caused an increase in remanent polarization. An increase in the paraelectric-ferroelectric transition temperature upon a decrease in thickness was confirmed by dielectric measurements. Polarization loops were fitted to Landau-Ginzburg-Devonshire (LGD) polynomial expansion, from which a second order paraelectric-ferroelectric transition in the films was suggested at a thickness of similar to500 nm. Further, the LGD analysis showed that the observed changes in room temperature polarization were entirely consistent with strain coupling in the system. (C) 2002 American Institute of Physics.

Intrinsic dielectric response in ferroelectric nano-capacitors

Measurements on 'free-standing' single-crystal barium titanate capacitors with thickness down to 75 nm show a dielectric response typical of large single crystals, rather than conventional thin films. There is a notable absence of any broadening or temperature shift of the dielectric peak or loss tangent. Peak dielectric constants of similar to25 000 are observed, and Curie-Weiss analysis demonstrates first order transformation behaviour. This is in dramatic contrast to results on conventionally deposited thin film capacitor heterostructures, which show large dielectric peak broadening and temperature shifts (e.g. Parker et al 2002 Appl. Phys. Lett. 81 340), as well as an apparent change in the nature-of the paraelectric-ferroelectric transition from first to second order. Our data are compatible with a recent model by Bratkovsky and Levanyuk (2004 Preprint cond-mat/0402100), which attributes dielectric peak broadening to gradient terms that will exist in any thin film capacitor heterostructure. The observed recovery of first order transformation behaviour is consistent with the absence of significant substrate clamping in our experiment, as modelled by Pertsev et al (1998,Phys. Rev. Lett. 80 1988), and illustrates that the second order behaviour seen in conventionally deposited thin films cannot be attributed to the effects of reduced dimensionality in the system, nor to the influence of an intrinsic universal interfacial capacitance associated with the electrode- ferroelectric interface.

Multi-zone TAP-reactors theory and application - IV. Ideal and non-ideal boundary conditions

We study the influence of non-ideal boundary and initial conditions (BIC) of a temporal analysis of products (TAP) reactor model on the data (observed exit flux) analysis. The general theory of multi-response state-defining experiments for a multi-zone TAP reactor is extended and applied to model several alternative boundary and initial conditions proposed in the literature. The method used is based on the Laplace transform and the transfer matrix formalism for multi-response experiments. Two non-idealities are studied: (1) the inlet pulse not being narrow enough (gas pulse not entering the reactor in Dirac delta function shape) and (2) the outlet non-ideality due to imperfect vacuum. The effect of these non-idealities is analyzed to the first and second order of approximation. The corresponding corrections were obtained and discussed in detail. It was found that they are negligible. Therefore, the model with ideal boundary conditions is proven to be completely adequate to the description and interpretation of transport-reaction data obtained with TAP-2 reactors.

An FPGA Based Coprocessor for GLCM and Haralick Texture Features and Their Application in Prostate Cancer Classification

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

A new Jacobian matrix for optimal learning of single-layer neural networks

This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.