Miracle-dz/UniFAR-FTUs huggingface dataset:
Polynomial bases for subspaces of vector fields in the unit ball. Method of ridge functions

This paper deals with the construction of orthogonal polynomial bases for particular subspaces of vector fields defined in the unit ball of ℝ3. Our approach uses vector spherical harmonics to construct orthogonal sets of specific solenoidal and potential vector fields by means of ridge functions. It is shown that the approach leads to bases according to the subspaces induced by the Helmholtz–Hodge decomposition of square integrable vector fields.
Likelihood methods for missing covariate data in highly stratified studies

Summary. The paper considers canonical link generalized linear models with stratum‐specific nuisance intercepts and missing covariate data. This family includes the conditional logistic regression model. Existing methods for this problem, each of which uses a conditioning argu‐ ment to eliminate the nuisance intercept, model either the missing covariate data or the missingness process. The paper compares these methods under a common likelihood framework. The semiparametric efficient estimator is identified, and a new estimator, which reduces dependence on the model for the missing covariate, is proposed. A simulation study compares the methods with respect to efficiency and robustness to model misspecification.
Spectral properties and an inverse eigenvalue problem for non-symmetric systems of ordinary differential operators

Abstract - We consider a nonsymmetric first-order differential operator , where P is a 2×2 matrix whose components are in L2(0, 1). We study an eigenvalue problem for A with boundary conditions at x = 0, 1. We establish an asymptotic form of the eigenvalues and prove that the set of the root vectors forms a Riesz basis in {L2(0, 1)}2. Moreover we show some characterization of L2-coefficients in an inverse eigenvalue problem. The key is a transformation formula.
Facilitating Strongly Coupled Ocean-Atmosphere Data Assimilation with an Interface Solver

AbstractIn a strongly coupled data assimilation (DA), a cross-fluid covariance is specified that allows measurements from a coupled fluid (e.g., atmosphere) to directly impact analysis increments in a target fluid (e.g., ocean). The exhaustive solution to this coupled DA problem calls for a covariance where all available measurements can influence all grid points in all fluids. Solution of such a large algebraic problem is computationally expensive, often calls for a substantial rewrite of existing fluid-specific DA systems, and, as shown in this paper, can be avoided.The proposed interface solver assumes that covariances between coupled measurements and target fluid are often close to null (e.g., between stratospheric observations and the deep ocean within a 6-h forecast cycle). In the interface solver, two separate DA solvers are run in parallel: one that produces an analysis solution in the atmosphere, and one in the ocean. Each system uses a coupled observation vector where in addition to resident mea.
M-estimation for near unit roots in spatial autoregression with infinite variance

We investigate the limiting behaviour of M-estimators of parameters for a near unit root spatial autoregressive model Z ij (n)=α n Z i−1, j (n)+β n Z i, j−1(n)−α n β n Z i−1, j−1(n)+ε ij , 1≤i, j≤n. Innovations are assumed to be independent and identically distributed and in the domain of attraction of a stable law. We let α n =e c/n and β n =e d/n , where c and d are nonzero unknown constants. It is shown that the self-normalized M-estimators are asymptotically normal. A simulation study is also given.
The Smooth-Lasso and other ℓ1+ℓ2-penalized methods

We consider a linear regression problem in a high dimensional setting where the number of covariates p can be much larger than the sample size n . In such a situation, one often assumes sparsity of the regression vector, i.e., the regression vector contains many zero components. We propose a Lasso-type estimator ˆ β Quad (where ‘ Quad ’ stands for quadratic) which is based on two penalty terms. The ﬁrst one is the ℓ 1 norm of the regression coeﬃcients used to exploit the sparsity of the regression as done by the Lasso estimator, whereas the second is a quadratic penalty term introduced to capture some additional information on the setting of the problem. We detail two special cases: the Elastic-Net ˆ β EN introduced in [42], which deals with sparse problems where correlations between variables may exist; and the Smooth-Lasso 1 ˆ β SL , which responds to sparse problems where successive regression coeﬃcients are known to vary slowly (in some situations, this can also be interpreted in terms of correlations between successive variables). From a theoretical point of view, we establish variable selection consistency results and show that ˆ β Quad achieves a Sparsity Inequality, i.e., a bound in terms of the number of non-zero components of the ‘true’ regression vector. These results are provided under a weaker assumption on the Gram matrix than the one used by the Lasso. In some situations this guarantees a signiﬁcant improvement over the Lasso. Furthermore, a simulation study is conducted and shows that the S-Lasso ˆ β SL performs better than known methods as the Lasso, the Elastic-Net ˆ β EN , and the Fused-Lasso (introduced in [30]) with respect to the estimation accuracy. This is especially the case when the regression vector is ‘smooth’, i.e., when the variations between successive coeﬃcients of the unknown parameter of the regression are small. The study also reveals that the theoretical calibration of the tuning parameters and the one based on 10 fold cross validation imply two S-Lasso solutions with close performance.
Orthogonal polynomial projection quantization: a new Hill determinant method

Accurate energy eigenvalues are obtained by simply projecting the unknown bound state wave function on, essentially, arbitrary sets of orthogonal polynomials, and setting a subset of these to zero. The projection integrals are represented in terms of the power moments of the wave function, obtained recursively by transforming Schrödinger’s equation into a moment equation. Because unbounded wave functions do not have power moments, all solutions are guaranteed to be L2, resulting in a more robust, rapidly converging and stable method when compared with configuration space Hill determinant methods. More importantly, our approach permits the use of arbitrary, nonanalytic, positive reference functions, including those that manifest the true asymptotic behavior of the discrete states. These advantages are not usually possible with the standard Hill approach. The formulation presented here can be applied to any problem for which Schrödinger’s equation can be transformed into a moment equation. In this regard it is related to the L2 quantization prescription developed by Tymczak et al (1998 Phys. Rev. Lett. 80 3674; 1998 Phys. Rev. A 58 2708) corresponding to the Hill determinant method in momentum space, and to the eigenvalue moment method (Handy and Bessis 1985 Phys. Rev. Lett. 55 931; Handy et al 1988 Phys. Rev. Lett. 60 253), the first use of semidefinite programming related analysis in quantum physics. The latter method can be used to generate the ground state, whose orthogonal polynomials can serve to generate even more rapidly converging estimates for the excited discrete state energies. We demonstrate the power of this new approach on the sextic and quartic anharmonic oscillators, as well as on recently studied one- and two-dimensional pseudo-Hermitian Hamiltonians.
Nonparametric $n\sp {-1/2}$-consistent estimation for the general transformation models

We propose simple estimators for the transformation function A and the distribution function F of the error for the model Λ(Y) = α + Xβ + e It is proved that these estimators are consistent and can achieve the unusual n -l/2 rate of convergence on any finite interval under some regularity conditions. We show that our estimators are more attractive than another class of estimators proposed by Horowitz. Interesting decompositions of the estimators are obtained. The estimator of F is independent of the unknown transformation function A, and the variance of the estimator for A depends on A only through the density function of X. Through simulations, we find that the procedure is not sensitive to the choice of bandwidth, and the computation load is very modest. In almost all cases simulated, our procedure works substantially better than median nonparametric regression.
Heat transfer behavior of a rectangular thermosyphon loop

The thermal performance of a rectangular thermosyphon loop was studied. The analysis, using a one-dimensional approximation, the convectional friction factor, and an empirical correlation for the overall heat transfer in the cooler, was shown to be able to predict accurately the loop performance at steady state or approaching steady state, if the effective length was used to replace the geometeric length in the calculation of loop friction. The steady-state natural circulation flow solution obtained was shown to be a function of a dimensionless group PY or (NuGr/Pr) Y and agrees very well with the experimental results.
Analytical method of a multilayered meander-line polarizer plate with normal and oblique plane-wave incidence

Simple empirical formulas for perpendicular and parallel polarization susceptances for a meander-line grating plate are given. The numerical results compared favorably with experimental data and published data. Simple transmission-line model in terms of E -type mode and H -type mode for multilayered meander-line polarizer plate is presented for plane wave incidence at normal and oblique angles. Numerical results for design examples are given for practical application.
Classical and Computational Solid Mechanics

Tensor analysis stress tensor analysis of strain conservation laws elastic and plastic behaviour of materials linearized theory of elasticity solutions of problems in linearized theory of elasticity by potentials two-dimensional problems in linearized theory of elasticity variational calculus, energy theorems, Saint-Venant's principle Hamilton's principle, wave propagation, applications of generalized co-ordinates elasticity and thermodynamics irreversible thermodynamics and viscoelasticity thermoelasticity viscoelasticity large deformation incremental approach to solving some nonlinear problems finite element methods mixed and hybrid formulations finite element methods for plates and shells finite element modelling of nonlinear elasticity, viscoelasticity, plasticity, viscoplasticity and creep.
Quantitative in situ nanoindentation in an electron microscope

We report the development of a method for quantitative, in situ nanoindentation in an electron microscope and its application to study the onset of deformation during the nanoindentation of aluminum films. The load-displacement curve developed during in situ nanoindentation shows the characteristic ''staircase'' instability at the onset of plastic deformation. The instability corresponds to the first appearance of dislocations in previously defect-free grains, and occurs at a force near that measured in conventional nanoindentation experiments on similarly oriented Al grains. Plastic deformation proceeds through the formation and propagation of prismatic loops punched into the material, and half-loops that emanate from the sample surface. This new experimental technique permits the direct observation of the microstructural mechanisms that operate at the onset of deformation.
Electron capture by Lii+ (i=2,3), Ni+ and Nei+ (i=2,3,4,5) ions from atomic hydrogen

Cross section measurements are reported for electron capture by multiply charged lithium, nitrogen and neon ions from atomic hydrogen. The ion energies depend on the ion charge state i and typically range from 3i keV to 12i keV. Experimental technique and resulting uncertainties are discussed in detail. Good agreement is obtained with published experimental results where comparison is possible. Discrepancies are observed, however, in comparison with available theoretical calculations.
Determination of W Values and Backscatter Coefficients for Slow Electrons in Air

Measurements are reported to determine the average energy W expended to form an ion pair in air for incident electrons in the energy range from 30 eV to 5 keV. For energies T greater than or equal to 60 eV the standard deviations are lower than 1%. In addition, backscatter coefficients R/sub i/ with respect to the spatial ionization distribution have been determined. R/sub i/ is an important quantity describing the electron transport in matter and is needed to correct W values. The experimental data are compared with the results of other authors.
Treatment of Observation Error due to Unresolved Scales in Atmospheric Data Assimilation

Abstract Observations of the atmospheric state include scales of motion that are not resolved by numerical models into which the observed data are assimilated. The resulting observation error due to unresolved scales, part of the “representativeness error,” is state dependent and correlated in time. A mathematical formalism and algorithmic approach has been developed for treating this error in the data assimilation process, under an assumption that there is no model error. The approach is based on approximating the continuum Kalman filter in such a way as to maintain terms that account for the observation error due to unresolved scales. The two resulting approximate filters resemble the Schmidt–Kalman filter and the traditional discrete Kalman filter. The approach is tested for the model problem of a passive tracer undergoing advection in a shear flow on the sphere. The state contains infinitely many spherical harmonics, with a nonstationary spectrum, and the problem is to estimate the projection of this .
Multi-Mode Driving Control of a Parallel Hybrid Electric Vehicle Using Driving Pattern Recognition

Vehicle performance such as fuel consumption and catalyst-out emissions is affected by a driving pattern, which is defined as a driving cycle with grades in this study. To optimize the vehicle performances on a temporary driving pattern, we developed a multi-mode driving control algorithm using driving pattern recognition and applied it to a parallel hybrid electric vehicle (parallel HEV). The multi-mode driving control is defined as the control strategy which switches a current driving control algorithm to the algorithm optimized in a recognized driving pattern. For this purpose, first, we selected six representative driving patterns, which are composed of three urban driving patterns, one expressway driving pattern, and two suburban driving patterns. A total of 24 parameters such as average cycle velocity, positive acceleration kinetic energy, stop time/total time, average acceleration, and average grade are chosen to characterize the driving patterns. Second, in each representatives driving pattern, control parameters of a parallel HEV are optimized by Taguchi method though the fuel-consumption and emissions simulations. And these results are compared with those by parametric study. There are seven control parameters, six of them are weighting factors of performance measures for deciding the ratio of engine power to required power from driving load. And the other is the charging/ discharging method of battery. Finally, in driving, a neural network (the Hamming network) decides periodically which representative driving pattern is closest to a current driving pattern by comparing the correlation related to 24 characteristic parameters. And then the current driving control algorithm is switched to the optimal one, assuming the driving pattern does not change in the next period.
Coronal Mass Ejections and Galactic Cosmic-Ray Modulation

We present a study of the long-term evolution of coronal mass ejections (CMEs) observed by the Large Angle and Spectrometric Coronograph (LASCO) on board SOHO during the ascending, maximum, and part of the descending phases of solar cycle 23 and their relation with the modulation of galactic cosmic-ray (GCR) intensity observed at 1 AU by the Climax neutron monitor and IMP-8 spacecraft. We compare the long-term GCR modulation with the CME occurrence rate at all, low, and high latitudes, as well as the observed CME parameters (width and speed). Twenty-seven day averages of CME occurrence rates and CME properties from 1996 January to 2003 December are presented in the Appendix. The general anticorrelation between GCR intensity and the CME rate is relatively high (~-0.88). However, when we divide the CME rate into low- and high-latitude rates and compare them with the GCR intensity during the ascending phase of solar cycle 23, we find a lower anticorrelation between the low-latitude the CME rate and GCR intensity (~-0.71) and a very high anticorrelation between the high-latitude CME rate and GCR intensity (~-0.94). This suggests that, in general, CMEs could cause the decrease in the GCR flux in the inner heliosphere, as stated by the global merged interaction region (GMIR) theory. In particular, during the ascending phase of cycle 23 (qA > 0), this flux comes mainly from heliospheric polar regions. Thus, high-latitude CMEs may play a central role in the long-term cosmic-ray modulation during this phase of the cycle by blocking the polar entrance of GCRs to the inner heliosphere. This study supports the scenario in which CMEs, among other structures, are the building blocks of GMIRs, although we propose that the spherical shells (GMIRs) are closed separately at polar and equatorial regions by CMEs of different latitudes. Our results suggest that all CME properties show some correlation with the GCR intensity, although there is no specific property (width, speed, or a proxy of energy) that definitely has a higher correlation with GCR intensity.
How do shape anisotropy and spatial orientation of the constituents affect the permittivity of dielectric heterostructures

The study of dielectric heterostructures has been advancing at a rapid pace. Much of the interest in these materials stems from the fact that their physical properties can be systematically tuned by variation of the size and shape of the constituents. Here we report on extensive computer simulations of the effective permittivity of dielectric periodic (deterministic) heterostructures, having monosized hard core inclusions of anisotropic shape (rod, ellipsoid) embedded in an otherwise homogeneous and isotropic matrix. The real and imaginary parts of the permittivity, in the quasistatic limit, are rigorously evaluated with the use of the PHI3D field calculation package and the resolution of boundary integral equations. In this article, we show that the effective permittivity has critical properties near a conduction threshold. The conduction threshold concentration can be significantly modified by the size, shape, and spatial arrangement of the constituents. More specifically, it obeys a square law dependen.
Study on the magnetization reversal process in a magnetic nanowire and a magnetic dot observed by magnetic field sweeping magnetic force microscopy measurements (invited)

We have studied the details of the magnetization reversal process in Ni–Fe nanowires and dots using magnetic field sweeping (MFS)-magnetic force microscopy (MFM). All the points within the nanowire and the dot show important changes in phase (changes in stray field) including a hysteresis loop, a decrease and an increase in phase, as the magnetic field is varied. From these results, it is demonstrated that domain wall motion dominates the magnetization reversal process of a 10-nm-thick Ni–Fe nanowire with widths between 100 and 1000nm. It is also demonstrated that the nucleation, the movement, and the annihilation of the vortex core can be directly observed in the magnetization reversal process of a 40-nm-thick Ni–Fe circular dot with diameters between 200 and 800nm. Furthermore, it is found that, in the magnetization reversal process of a 10-nm-thick Ni–Fe elliptical dot with several major axial distances between adjacent dots, the magnetization between the adjacent dots magnetostatically couples as the .
On subspace identification of the extended observability matrix

A lower left Q-orthogonal (LQ) decomposition is often used in order to compute certain projections of the known data matrices and to estimate the extended observability matrix from the column space (range) of a projected matrix. An alternative method based on the partial least squares (PLS) method is presented in this paper. A Monte Carlo simulation experiment of a MIMO system is presented in order to compare the method with two other subspace methods presented in the literature. In addition some new results in subspace identification are proved. Consistency of the estimate of the extended observability matrix is also addressed.
Resonant and voltage-tunable terahertz detection in InGaAs /InP nanometer transistors

The authors report on detection of terahertz radiation by high electron mobility nanometer InGaAs∕AlInAs transistors. The photovoltaic type of response was observed at the 1.8–3.1THz frequency range, which is far above the cutoff frequency of the transistors. The experiments were performed in the temperature range from 10to80K. The resonant response was observed and was found to be tunable by the gate voltage. The resonances were interpreted as plasma wave excitations in the gated two-dimensional electron gas. The minimum noise equivalent power was estimated, showing possible application of these transistors in sensing of terahertz radiation.
Increasing permittivity in HfZrO thin films by surface manipulation

We report on the electrical and physical characterization of nanoscale crystalline HfxZr1−xO2 films by x-ray diffraction (XRD) and attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. Increasing the ZrO2 content generally led to an increase in tetragonal phase fraction and dielectric constant. This was reflected in both XRD and ATR-FTIR measurements. We demonstrate that not only the composition, but also the distribution of ZrO2 throughout the film determines phase formation. Concentrating ZrO2 at the top surface of the film allowed the dielectric constant to be optimized for a given composition. These observations are explained by a surface energy thermodynamic model.
Very Fast and Correctly Sized Estimation of the Bds Statistic

This paper is concerned with the study of some fundamental aspects of the BDS test. Brock, Dechert, Scheinkman & LeBaron (Econometric Reviews, 1996) propose this non-parametric tool as a test of the null hypothesis of an independently and identically distributed (i.i.d.) time series, with power against virtually all linear and non-linear, stochastic and deterministic ("chaotic") alternatives. Unfortunately, it is extremely processing-intensive and requires an efficient computer algorithm to be viably run even on relatively small data sets. An algorithm is presented which is very fast, rather simple and easily implemented in common programming environments; a version for MATLAB is part of the paper. The algorithm overcomes a number of deficiencies of the two most widely used BDS packages by Dechert and LeBaron. Extensive Monte-Carlo simulations are conducted which show that the properties of the BDS statistic are sensitive to the choice of embedding dimension and dimensional distance, and to sample size. Unless the choice parameters are set in accordance with the recommendations emerging from the simulations, a statistical test for "iidness" is bound to be badly sized on small samples and thus yield misleading conclusions. Tables of the small-sample distribution are offered for correctly sized testing. The recommendations, tabulated quantile values and computer algorithms put forward will hopefully help render the BDS test part of the standard econometric toolbox.