Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation study of high-frequency energetic particle driven geodesic acoustic mode

High-frequency energetic particle driven geodesic acoustic modes (EGAM) observed in the large helical device plasmas are investigated using a hybrid simulation code for energetic particles and magnetohydrodynamics (MHD). Energetic particle inertia is incorporated in the MHD momentum equation for the simulation where the beam ion density is comparable to the bulk plasma density. Bump-on-tail type beam ion velocity distribution created by slowing down and charge exchange is considered. It is demonstrated that EGAMs have frequencies higher than the geodesic acoustic modes and the dependence on bulk plasma temperature is weak if (1) energetic particle density is comparable to the bulk plasma density and (2) charge exchange time (τcx ) is sufficiently shorter than the slowing down time (τs ) to create a bump-on-tail type distribution. The frequency of high-frequency EGAM rises as the energetic particle pressure increases under the condition of high energetic particle pressure. The frequency also increases as the energetic particle pitch angle distribution shifts to higher transit frequency. It is found that there are two kinds of particles resonant with EGAM: (1) trapped particles and (2) passing particles with transit frequency close to the mode frequency. The EGAMs investigated in this work are destabilized primarily by the passing particles whose transit frequencies are close to the EGAM frequency.
Least median of squares estimation in power systems

An algorithm for solving LMS (least median of squares) in nonlinear systems has been proposed. The solutions are found through resampling methods based on linear approximations. These methods are suitable for parallel processing. The robustness of the LMS estimator has been verified on several test systems and illustrated on the IEEE 14-bus system. The concept of leverage points shed new light on the meter placement issue as well as the concepts of local redundancy and local breakdown point. A preliminary conclusion is that shorter lines have to be provided with enough measurements in order to increase their local redundancy. Indeed, they tend to be isolated in the factor space and weakly coupled with the surrounding measurements. >
Constructing S-boxes with low multiplicative complexity

Multiplicative complexity is the minimum number of AND-gates required to implement a given Boolean function in (AND, XOR) algebra. It is a good measure of a hardware complexity of an S-box, but an S-box cannot have too low multiplicative complexity due to security constraints. In this article we focus on generic constructions that can be used to find good n×n S-boxes with low multiplicative complexity. We tested these constructions in the specific case when n = 8. We were able to find 8 × 8 S-boxes with multiplicative complexity at most 16 (which is half of the known bound on multiplicative complexity of the AES S-box), while providing a reasonable resistance against linear and differential cryptanalysis.
Dynamics of an ensemble of plane waves in nonlinear dispersive media

A statistical description of the dynamics of an ensemble of plane waves in nonlinear and strongly dispersive media is derived. A modulational instability, a second sound wave, and a localized group of waves are obtained from the description. The results apply to the dynamics of many optical waves in strongly dispersive dielectric media with the Kerr effect as well as plasma waves for which decays or the wave particle interactions are prohibited.
Effect of initial conditions on two-dimensional free shear layers

The influence of periodic perturbations on the development of two-dimensional free shear layers generated by a splitter plate was investigated in cases where the ratios of the two velocities u1 and u2 either side of the splitter plate were such that 0 < u1/u2 < 1. Investigations were carried out in both a suction and a blower wind tunnel. Results show that even very weak periodic perturbations caused by the wind tunnel may cause significant nonlinear spreading in the downstream development of the shear layer, a behaviour which is also observed when the shear layer is deliberately excited. Other things being equal, the effect of the disturbance is greater when flow separation at the splitter plate is turbulent than when it is laminar. No self-induced feedback frequencies were measured in the test section. All tonal components that were detected in the flow could be traced to external sources. The influence of trailing-edge thickness on the shear-layer development is found to become significant when it exceeds 50% of the sum of boundary-layer displacement thickness at the point of separation. As the trailing edge becomes thicker, the range over which the shear layer is self-similar is shifted farther downstream. This behaviour may be crucial for predicting the evolution of shear layers in high-speed flows having thin boundary layers at separation. The momentum thickness criterion for estimating the development length of the flow as suggested by Bradshaw is shown to be insufficient for two-stream layers, where additional parameters, e.g. the trailing-edge geometry, have to be taken into account. Discrepancies between previously published observations of shear layers, as well as the considerable scatter in reported measurements, may therefore, to a large extent, be attributable to contamination of the experimental facility.
Linear inverse problems for generalised random variables

In a statistical inverse theory both the unknown quantity and the measurement are random variables. The solution of the inverse problem is then the conditional distribution of the unknown variable with the measurement supposed to be known. Both variables often have their values in spaces of functions or generalised functions while the statistical theory of conditional distributions has only been fully developed for Polish spaces. Also, the mappings representing the solution of linear inverse problems with Gaussian priors and noises are usually only defined on a subset of the spaces used. This problem has previously been correctly handled only for Hilbert-space-valued variables. The existence of a regular version of the conditional distribution of random variables with values in spaces of generalised functions is shown and the inverse problem is solved in the linear Gaussian case.
Optical diffraction tomography within a variational Bayesian framework

Optical diffraction tomography techniques aim to find an image of an unknown object (e.g. a map of its refraction index) using measurements of the scattered field that results from its interaction with a known interrogating wave. We address this issue as a nonlinear inverse scattering problem. The forward model is based upon domain integral representations of the electric field whose discrete counterparts are obtained by means of a method of moments. The inverse problem is tackled in a Bayesian estimation framework involving a hierarchical prior model that accounts for the piece-wise homogeneity of the object. A joint unsupervised estimation approach is adopted to estimate the induced currents, the contrast and all the other parameters introduced in the prior model. As an analytic expression for the joint maximum a posteriori (MAP) and posterior mean (PM) estimators is hard to obtain, a tractable approximation of the latter is proposed. This approximation is based upon a variational Bayesian technique and consists in the best separable distribution that approximates the true posterior distribution in the Kullback–Leibler sense. This leads to an implicit parametric optimization scheme which is solved iteratively.
The effect of metallic contamination on enhanced oxygen diffusion in silicon at low temperatures

Measurements are reported for the recovery of stress-induced dichroism in the 9 mu m oxygen infrared absorption band for samples given various treatments prior to stressing. Enhanced hopping rates are observed in samples deliberately contaminated with copper or iron and the degree of enhancement up to a factor of 102 depends on the conditions of the stressing treatment. It is also shown that the enhancement is a transient effect. The results are tentatively explained in terms of an oxygen-vacancy interaction with the vacancies being generated by site switching of the metal atoms.
Collapsibility and response variables in contingency tables

SUMMARY Various definitions of the collapsibility of a hierarchical log linear model for a multidimensional contingency table are considered and shown to be equivalent. Necessary and sufficient conditions for collapsibility are found in terms of the generating class. It is shown that log linear models are appropriate for tables with response and explanatory variables if and only if they are collapsible onto the explanatory variables. Some key word8: Collapsibility; Contingency table; Graphical model; Interaction graph; Log linear model; Response variable; S-sufficiency. shown to be closely related. Some models have the property that relations between a set of the classifying factors may be studied by examination of the table of marginal totals formed by summing over the remaining factors. Such models are said to be collapsible onto the given set of factors. Collapsibility has important consequences for hypothesis testing and model selection, and can be useful in data reduction. We consider various definitions of collapsibility and show their equivalence. Furthermore, necessary and sufficient conditions for collapsi- bility are found in terms of the generating class. Many tables analysed in practice involve response variables. Simple examples, one of which is given in ? 3, suffice to show the importance of distinguishing between response and explanatory variables: first, that inappropriate models may be avoided, and second that natural and relevant models that are not log linear may be considered. This paper characterizes appropriate and inappropriate log linear models for tables with response variables and some alternative approaches for the analysis of such tables are briefly considered. We consider a multidimensional contingency table N based on a set of classifying factors F. For a given subset a of F we are interested in the table of marginal totals Na, that is to say the table of cell counts summed over the remaining factors aC, that is the complement of a in F. We identify a hierarchical log linear model L, that is the set of probabilities p E L, with its generating class, whose elements, generators, are given in square brackets: thus for example the model (AB) (BCD) for a 4-way table corresponds
Estimating constrained concentration–response functions between air pollution and health

The health risks associated with short‐term exposure to air pollution have been the focus of much recent research, most of which has considered linear concentration–response functions (CRFs) between ambient concentrations of pollution and a health response. A much smaller number of studies have relaxed this assumption of linearity and allowed the shape of the function to be estimated from the data. However, this increased flexibility has resulted in CRFs being estimated that appear unfeasible, often showing decreases in the risk to health with increasing concentrations. Therefore, this paper proposes a Bayesian hierarchical model for estimating constrained CRFs in this context, which is based on monotonic integrated splines. These splines produce non‐decreasing CRFs, owing to the associated regression parameters being constrained to be non‐negative, which we ensure by modelling the latter with a ‘slab and spike’ prior. The efficacy of our approach is assessed via simulation before being applied to a study of ozone concentrations and respiratory disease in Greater London between 2000 and 2005. Copyright © 2012 John Wiley & Sons, Ltd.
Wear mechanisms of UHMWPE for artificial knee joints in combined rolling and sliding cyclic motion

Abstract A knee joint simulator was designed and constructed for studying the wear of ultra high molecular weight polyethylene (UHMWPE) tibial analogs. The kinematic conditions and physiological forces occurring on the analogous femoral‐tibial bearing surfaces were almost the same as those in a normal human knee joint. Especially, combined rolling and sliding motion was imposed on the femoral‐tibial contact surfaces. The wear prints of the tibial trays produced by the simulator could be divided into five zones of different wear appearances. Abrasive wear occurred in Zones 1 and 5, the two ends of the wear track. In Zone 2, it was worn by spalling small irregular blocks of mass as well as delaminating plastic layer from the surface due to the squeezing and stretching actions. In Zone 3, delamination wear occurred due to combined effect of rolling and sliding. Ripples were formed on the surface of Zone 4, which the femoral component rolled on. An about 50 μm thick surface layer was obviously deformed plastically and was spalled after many loading cycles. However, the wear patterns on Zones 2, 3 and 4 were similar to that occurring on some retrieved knee replacements subjected to short time failure. The wear patterns and the wear mechanisms occurring on the PE tibias meet the requirements suggested by ASTM (ASTM F732 and F1715) and ISO (F14243–1), the present simulator is considered to be suitable for the study of wear in artificial knee joints.
A design procedure for slot arrays fed by single-ridge waveguide

R.S. Elliott's (1983) design procedure for arrays of longitudinal slots in one broad wall of each rectangular waveguide is extended to the case in which the waveguides have ridges in the opposite broad walls. External mutual coupling has been taken into account. A two-be-eight array was constructed and tested, and the results validate the theory. Ridging is significant because it permits E-plane scanning from broadside to endfire. >
Intercomparison of EMCCD- and sCMOS-based imaging spectrometers for biomedical applications in low-light conditions

Hyperspectral imaging provides means for characterizing large biological samples with microscopic spatial resolution and a narrow spectral sampling interval. However, this approach requires having a measurable light signal in each spectral band. Overcoming the limitations imposed by working with biological samples requires the use of a highly sensitive sensor to detect weak signals. For this study we have built and compared the performance of two imaging spectrometers using optimized for low light environments: an electron-multiplying CCD (EMCCD) and a scientific CMOS (sCMOS). Both systems have been designed to lower the risk of damaging photosensitive samples, delay the bleaching of fluorophores and detect weak fluorescence signals. The cameras work within the VNIR spectral region (400 nm - 900 nm) with a spectral sampling lower than 4 nm. The produced images have scene pixel sizes smaller than 25 μm and a field of view larger than 25 mm. The systems have been tested side to side measuring the diffusion front of a fluorescent tag in samples of porcine skin in challenging light conditions. The study aimed to show the advantages and limitations of each approach. Preliminary results show good performance of the EMCCD for fluorescence applications, whereas more experimental results are needed to be able to conclude on the performance of the sCMOS sensor. However, the sCMOS appears promising for imaging scenes with high dynamics in low light settings.
PULSE COMPRESSION, FIBER COMMUNICATIONS, AND DIFFRACTION : A UNIFIED APPROACH

A unified approach is developed to three important areas of signal and image processing: pulse compression and real-time spectrum analysis, fiber-cable communications and dispersion, and Fresnel diffraction and optical filtering. The results are based on the properties of quadratic phase filters and Fresnel transforms, and they lead to a variety of analogies among the time responses of fiber cables, the spatial variations of diffracted fields, and the role of frequency modulation in narrow-band systems. The analysis includes deterministic and stochastic excitations.
Multichannel blind separation and deconvolution of sources with arbitrary distributions

Blind deconvolution and separation of linearly mixed and convolved sources is an important and challenging task for numerous applications. While several algorithms have shown promise in these tasks, these techniques may fail to separate signal mixtures containing both sub- and super-Gaussian distributed sources. In this paper, we present a simple and efficient extension of a family of algorithms that enables the separation and deconvolution of mixtures of arbitrary non-Gaussian sources. Our technique monitors the statistics of each of the outputs of the separator using a rigorously-derived sufficient criterion for stability and then selects the appropriate nonlinearity for each channel such that local convergence conditions of the algorithm are satisfied. Extensive simulations show the validity and efficiency of our method to blindly extract mixtures of arbitrary-distributed source signals.
An efficient meshfree point collocation moving least squares method to solve the interface problems with nonhomogeneous jump conditions

We are going to study a simple and effective method for the numerical solution of the closed interface boundary value problem with both discontinuities in the solution and its derivatives. It uses a strong‐form meshfree method based on the moving least squares (MLS) approximation. In this method, for the solution of elliptic equation, the second‐order derivatives of the shape functions are needed in constructing the global stiffness matrix. It is well‐known that the calculation of full derivatives of the MLS approximation, especially in high dimensions, is quite costly. In the current work, we apply the diffuse derivatives using an efficient technique. In this technique, we calculate the higher‐order derivatives using the approximation of lower‐order derivatives, instead of calculating directly derivatives. This technique can improve the accuracy of meshfree point collocation method for interface problems with nonhomogeneous jump conditions and can efficiently estimate diffuse derivatives of second‐ and higher‐orders using only linear basis functions. To introduce the appropriate discontinuous shape functions in the vicinity of interface, we choose the visibility criterion method that modifies the support of weight function in MLS approximation and leads to an efficient computational procedure for the solution of closed interface problems. The proposed method is applied for elliptic and biharmonic interface problems. For the biharmonic equation, we use a mixed scheme, which replaces this equation by a coupled elliptic system. Also the application of the present method to elasticity equation with discontinuities in the coefficients across a closed interface has been provided. Representative numerical examples demonstrate the accuracy and robustness of the proposed methodology for the closed interface problems. © 2014 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 31: 1031–1053, 2015
Wave propagation in isotropic linear viscoelastic media

Assuming isothermal conditions, a suitable form of the free energy is formulated for general, isotropic linear viscoelastic media. On applying a proper form of the principle of dissipation, a strong condition of dissipation is derived, which imposes restrictions on constitutive parameters of particular materials. The field equations of boundary value problems in the time domain and the frequency domain are formulated and, in particular, the problem of scattering of an acoustic pulse with plane or spherical wave front by a viscoelastic scatterer is discussed. The relation to the corresponding elastic scattering problem for steady, harmonic waves is established, and a general scheme of solution for viscoelastic scatterers is laid down.
Quadratic analysis of information measures for object recognition

We have been studying information theoretic measures, entropy and mutual information, as performance metrics for object recognition given a standard suite of sensors. Our work has focused on performance analysis for the pose estimation of ground-based objects viewed remotely via a standard sensor suite. Target pose is described by a single angle of rotation using a Lie group parameterization: O (epsilon) SO(2), the group of 2 X 2 rotation matrices. Variability in the data due to the sensor by which the scene is observed is statistically characterized via the data likelihood function. Taking a Bayesian approach, the inference is based on the posterior density, constructed as the product of the data likelihood and the prior density for object pose. Given multiple observations of the scene, sensor fusion is automatic in the joint likelihood component of the posterior density. The Bayesian approach is consistent with the source-channel formulation of the object recognition problem, in which parameters describing the sources (objects) in the scene must be inferred from the output (observation) of the remote sensing channel. In this formulation, mutual information is a natural performance measure. In this paper we consider the asymptotic behavior of these information measures as the signal to noise ratio (SNR) tends to infinity. We focus on the posterior entropy of the object rotation angle conditioning on image data. We consider single and multiple sensor scenarios and present quadratic approximations to the posterior entropy. Our results indicate that for broad ranges of SNR, low dimensional posterior densities in object recognition estimation scenarios are accurately modeled asymptotically.
Optimizing electron beam lithography in the nanometer range

The constant increase in component density in silicon chips has been a steady trend in microelectronics over the last 50 years. Gordon Moore predicted in 1965 that the number of components per chip would double every year. Though the formulation of the Moore’s law has since been corrected, the tendency for exponential increase of component density in the chip remains. The driving force behind this trend has been the improvement in the basic technical characteristics and economics of microelectronic devices through the reduction of their feature sizes. Vast intellectual and material resources are focussed on increasing the resolution of lithography as the cornerstone technology of modern electronics, optoelectronics, and micromechanics. New technological developments in the transition to nanoscale devices have advanced these efforts even further. Both electron-beam lithography with Gaussian sharp-focused beams and projection electron-lithography systems with a resolution of a few nanometers are suitable for creating nanoscale devices. The first may be used for direct writing and fabrication of master masks, however the scan speed decreases dramatically with beam diameter. Since increasing the resolution and the throughput are important problems in electron-beam nanolithography, we have developed a mathematical model of the electron-beam-lithography processing of nanostructures to solve them. The model takes into account electron diffraction, the aberration of the lenses, and electron-resist interaction. It also allows the prediction of the exposure time of nanostructure arrays, and the optimization of the minimum feature size versus the speed of exposure process. The theoretical limit of the resolution of an electro-optical system is defined by the diffraction of the electron, having waveFigure 1. Diameter of the electron-beam lithographic tools as a function of beam-convergence half angle. 1: Wide source. 2: Point source. E0 = 50keV,ΔE = 1.5eV, Cc = 40mm, Cs = 60mm.