Miracle-dz/UniFAR-FTUs huggingface dataset:
Searching for Structure in Curve Samples

Abstract The shape of a regression curve can to a large extent be characterized by the succession of structural features like extrema, inflection points, and so on. When analyzing a sample of regression curves, it is often important to know at an early stage of data analysis which structural features are occurring consistently in each curve of the sample. Such a definition is usually not easy due to substantial interindividual variation both in the x and the y axis and due to the influence of noise. A method is proposed for identifying typical features without relying on an a priori specified functional model for the curves. The approach is based on the frequencies of occurrence of structural features, as, for example, maxima in the curve sample along the x axis. Important tools are nonparametric regression and differentiation and kernel density estimation. Apart from a theoretical foundation, the usefulness of the method is documented by application to two interesting biomedical areas: growth and develop.
Testing for the Constancy of Parameters over Time

Abstract Tests are proposed for detecting possible changes in parameters when the observations are obtained sequentially in time. While deriving the tests the alternative one has in mind specifies the parameter process as a martingale. The distribution theory of these tests relies on the large-sample results; that is, only the limiting null distributions are known (except in very special cases). The main tool in establishing these limiting distributions is weak convergence of stochastic processes. Suppose that we have vector-valued observations x 1, …, x n obtained sequentially in time (or ordered in some other linear fashion). Their joint distribution is described by determining the initial distribution for x 1 and the conditional distribution for each x k given the past up to x k–1. Suppose further that these distributions depend on a p-dimensional parameter vector θ. At least locally (i.e., in a short time period) this may be more or less legitimate. In the long run, however, the possibility of some ch.
Artificially soft and hard surfaces in electromagnetics

A transversely corrugated surface as used in corrugated horn antennas represents a soft boundary. A hard boundary is made by using longitudinal corrugations filled with dielectric material. The concept of soft and hard surfaces is treated in detail, considering different geometries. It is shown that both the hard and soft boundaries have the advantage of a polarization-independent reflection coefficient for geometrical optics ray fields, so that a circularly polarized wave is circularly polarized in the same sense after reflection. The hard boundary can be used to obtain strong radiation fields along a surface for any polarization, whereas the soft boundary makes the fields radiated along the surface zero. >
Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection

: Understanding the uncertainty of predictions is a desirable feature for perceptual modules in critical robotic applications. 3D object detectors are neural networks with high-dimensional output space. It suffers from poor calibration in classiﬁcation and lacks reliable uncertainty estimation in regression. To provide a reliable epistemic uncertainty estimation, we tailor Laplace approximation for 3D object detectors, and propose an Uncertainty Separation and Aggregation pipeline for Bayesian inference. The proposed Laplace-approximation approach can easily convert a deterministic 3D object detector into a Bayesian neural network capable of estimating epistemic uncertainty. The experiment results on the KITTI dataset empirically validate the effectiveness of our proposed methods, and demonstrate that Laplace approximation performs better uncertainty quality than Monte-Carlo Dropout, DeepEnsembles, and deterministic models.
Adaptive Power Method: Eigenvector Estimation from Sampled Data

Computing the dominant eigenvectors of a matrix A has many applications, such as principal component analysis, spectral embedding, and PageRank. However, in general, this task relies on the complete knowledge of the matrix A , which can be too large to store or even infeasible to observe in many applications, e.g., large-scale social networks. Thus, a natural question is how to accurately estimate the eigenvectors of A when only partial observations can be made by sampling entries from A . To this end, we propose the Adaptive Power Method (APM), a variant of the well-known power method. At each power iteration, APM adaptively selects a subset of the entries of A to observe based on the current estimate of the top eigenvector. We show that APM can estimate the dominant eigenvector(s) of A with squared error at most ϵ by observing roughly O ( nϵ − 2 log 2 ( n/ϵ )) entries of an n × n matrix. We present empirical results for the problem of eigenvector centrality computation on two real-world graphs and show that APM significantly outperforms a non-adaptive estimation algorithm using the same number of observations. Furthermore, in the context of eigenvector centrality, APM can also adaptively allocate the observation budget to selectively refine the estimate of nodes with high centrality scores in the graph.
One-step synthesis and enhanced blue emission of carbon-encapsulated single-crystalline ZnSe nanoparticles

Carbon-encapsulated ZnSe nanoparticles with diameters about 50nm were synthesized by noncatalytic one-step thermal evaporation method. The ZnSe cores have a wurtzite crystal structure. The as-synthesized products are uniform and composed of single-crystalline ZnSe nanoparticles enwrapped with polycrystalline graphite layers. The photoluminescence measurement of the carbon-encapsulated nanoparticles shows that the blue emission enhances dramatically compared with the naked ZnSe nanoparticles. This synthetic strategy might exploit a favorable route to synthesize carbon-encapsulated semiconductor nanostructures, which are potentially important for optoelectronic nanodevices.
Continuous Manufacturing of Oil in Water (O/W) Emulgel by Extrusion Process

Pharmaceutical industries and drug regulatory agencies are inclining towards continuous manufacturing due to better control over the processing conditions and in view to improve product quality. In the present work, continuous manufacturing of O/W emulgel by melt extrusion process was explored using lidocaine as an active pharmaceutical ingredient. Emulgel was characterized for pH, water activity, globule size distribution, and in vitro release rate. Additionally, effect of temperature (25°C and 60°C) and screw speed (100, 300, and 600 rpm) on the globule size and in vitro release rate was studied. Results indicated that at a given temperature, emulgel prepared under screw speed of 300 rpm resulted in products with smaller globules and faster drug release. Graphical Abstract
3D Monte Carlo simulation including full Coulomb interaction under high electron concentration regimes

We construct 3D Monte Carlo (MC) simulations including the full Coulomb interaction as accurately as possible. In order to achieve this goal, the usual strategy for the MC approach is employed; the Coulomb potential is split into the long-range and the short-range parts. The long-range part of the Coulomb potential is taken into account by solving the Poisson equation, in which the simulation parameters such as mesh size, charged-particle size, time step etc are carefully optimized by performing the particle simulations with turning off artificially all short-ranged scatterings. The short-range part of the Coulomb potential is incorporated into the MC simulations as scattering processes by developing a new scattering model, in which the impurities are localized in real space. It is shown that the present 3D MC simulations successfully explain the entire regime of the electron mobility as a function of impurity concentrations. In addition, it is found for the first time that the plasma frequency is modulated due to localization of the background impurities. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Experimental evidence of waves in the sublayer

Two-dimensional frequency-wave-number spectra [Fcy ](kx, ω) and [Fcy ](kz, ω) of the longitudinal velocity component are presented for the sublayer in fully developed turbulent pipe flow, at Reynolds numbers between 10600 and 46400. All of these sublayer spectra apparently scale by introducing dimensionless quantities based on a chara cteristic length scale ν/UT and a characteristic time scale ν/UT2. Representative convection velocities have been obtained from the [Fcy ](kx ω) spectra. The characteristic convection velocity in the sublayer is independent of wave-number and is the same at all positions in the layer cx ≃ 8·0UT. This result has led to the conclusion that sublayer turbulence is wave-like. Existing visualization data seem to indicate that the sublayer waves are also relatively periodic at least at low values of Reynolds number. Characteristic dimensions of the sublayer waves are λ+x ≃ 630, and λz+ = 135. Results of the visualization studies of Fage & Townend (1932) and of Runstadler, Kline & Reynolds (1963) and Kline et al. (1967) do not appear to conflict with a wave model for the sublayer. All of the existing measurements of the sublayer have been for relatively low Reynolds numbers. Some of the present results for positions just outside the sublayer suggest that at Reynolds numbers greater than 30000, the structure and properties will change substantially from those observed to date. In particular the streaky structure which is commonly regarded as being characteristic of the sublayer will probably not be detected at sufficiently high Reynolds numbers.
A Criterion for Determining the Number of Groups in a Data Set Using Sum-of-Squares Clustering

Marriott (1971, Biometrics 27, 501-514) used a heuristic argument to derive the criterion g2 l W I for determining the number of groups in a data set when the clustering objective function is the withingroup determinant I W 1. An analogous argument is employed to derive a criterion for use with the within-group sum-of-squares objective function trace (W). The behaviour of both Marriott's criterion and the new criterion is investigated by Monte Carlo methods. For homogeneous data based on uniform and independent variables, the performance of the new criterion is close to expectation while Marriott's criterion shows much more extreme behaviour. For grouped data, the new criterion correctly identifies the number of groups in 85% of data sets under a wide range of conditions, while Marriott's criterion shows a success rate of less than 40%. The new criterion is illustrated on the wellknown Iris data, and some cautionary comments are made about its use.
Weak Convergence Theorem for Nonexpansive and Monotone, Lipschitz Continuous Mappings

In this paper, we shall prove a weak convergence theorem for finding a common element of the set of fixed points of a nonexpansive mapping and the set of solutions of a variational inequality problem for a monotone, Lipschitz continuous mapping. With the help of a numerical example, we shall show the existence of a fixed point and find a solution of a variational inequality problem using C++. Further, we consider the problem of finding a common element of the set of fixed points of a nonexpansive mapping and the set of zeros of a monotone, Lipschitz continuous mapping.
Ultimate gate oxide thinness set by recombination-tunneling of electrons via Si–SiO2 interface traps

As the ever-decreasing gate oxide thickness approaches the threshold for direct tunneling of electrons across the gate oxide, i.e., about 3 nm, a defect-generation mechanism, which is not present in thicker gate oxides, becomes inevitable. The source of this mechanism is the recombination of channel electrons into the interface traps and their subsequent tunneling through the gate oxide to the gate metal. This carrier transport process generates additional interface traps, and the resultant regenerative feedback cycle culminates in a soft breakdown of the gate oxide, fatally compromising its reliability, and setting the ultimate gate oxide thinness to a value in the neighborhood of 3 nm.
A divide and conquer approach to least-squares estimation

The problem of estimating parameters theta which determine the mean mu ( theta ) of a Gaussian-distributed observation X is considered. It is noted that the maximum-likelihood (ML) estimate, in this case the least-squares estimate, has desirable statistical properties but can be difficult to compute when mu ( theta ) is a nonlinear function of theta . An estimate formed by combining ML estimates based on subsections of the data vector X is proposed as a computationally inexpensive alternative. The main result is that this alternative estimate, termed here the divide-and-conquer (DAC) estimate, has ML performance in the small-error region when X is appropriately subdivided. As an example application, an inexpensive range-difference-based position estimator is derived and shown by means of Monte-Carlo simulation to have small-error-region mean-square error equal to the Cramer-Rao lower bound. >
Analysis of a threshold dividend strategy for a MAP risk model

We consider a class of Markovian risk models in which the insurer collects premiums at rate c1(c2) whenever the surplus level is below (above) a constant threshold level b. We derive the Laplace-Stieltjes transform (LST) of the distribution of the time to ruin as well as the LST (with respect to time) of the joint distribution of the time to ruin, the surplus prior to ruin, and the deficit at ruin. By interpreting that the insurer pays dividends continuously at rate c1−c2 whenever the surplus level is above b, we also derive the expected discounted value of total dividend payments made prior to ruin. Our results are obtained by making use of an existing connection which links an insurer's surplus process to an embedded fluid flow process.
A Mixed Methods Study of 15 Years of Aboriginal Health Research in the Kimberley: ‘We’ve Been Researched, We Think, from Head to Toe, Inside and Outside, Upside Down’

Indigenous peoples have long been the subjects of research, with the burden generally outweighing the benefit. This mixed methods study investigates the characteristics and outcomes of Aboriginal health research in the Kimberley region of Western Australia from 2006–2020 to inform future research practices. Quantitative data from projects submitted to the Kimberley Aboriginal Health Planning Forum Research Subcommittee were reviewed, and key characteristics were recorded and descriptively analysed. Fifteen individuals from a range of local organisations who were involved with research during this time participated in qualitative semi-structured interviews, including 11 Aboriginal people. The project team, including Aboriginal investigators, integrated quantitative and qualitative findings. Three major interview themes were questionable ‘research world’ behaviours; translation of findings and impact of research; and local involvement and control. The experiences of interviewees were congruent with quantitative data for the larger body of projects (N = 230). Most projects (60%) were not initiated within the Kimberley, with positive impact for local communities often not clear. There were, however, examples of Kimberley Aboriginal-led research excellence. A way forward includes research that is developed, driven, and led by the community; alignment with research priorities; local Aboriginal involvement that is resourced and acknowledged; and comprehensive knowledge translation plans embedded in projects.
Synthesis of Carboxymethyl Chitosan and Its Derivatives Using KI and/or Ultrasonication

: Chitosan is a natural polysaccharide that is mainly obtained from the shell of marine crustaceans including crabs, lobsters, shrimps, etc. Chitosan has been widely used in biomedicine due to its special characteristics of low toxicity, biocompatibility, biodegradation, and low immunogenicity. However, owing to the limited solubility of CS in water, its water-soluble derivatives are preferred for the mentioned applications. Carboxymethyl chitosan (CMC) is one of the water-soluble derivatives of chitosan, which has antibacterial, anticancer, antitumor, antifungal, antioxidant properties, and is used in both drug delivery and enzyme delivery. This material is also utilized in tissue engineering, wound healing, and bioimaging. For these reasons, in this article, a different and novel method by using KI and/or ultrasonication is proposed.
Wavelet analyses of velocities in laboratory isotropic turbulence

Orthonormal wavelet transformations are used to decompose velocity signals of grid turbulence into both space and scale. The transforms exhibit small-scale enhancements of (i) the spatial fluctuation, (ii) the correlation in space between the adjacent scales, and (iii) the correlation in space between the longitudinal and transverse components. The spatial fluctuation and the scale–scale correlation at small scales are more significant in the transverse component than in the longitudinal component. These features are the same for different families of wavelets. Turbulence contains tube-like structures of vorticity. We demonstrate that wavelet transforms of velocities are enhanced at the positions of the tubes, by using a direct numerical simulation. Thus our wavelet analyses have captured the effects of those coherent structures on velocities measured in the experiment, which would be difficult for traditional analysis techniques such as those with velocity increments.
Advances in three-dimensional geoelectric forward solver techniques

SUMMARY Modern geoelectrical data acquisition systems allow large amounts of data to be collected in a short time. Inversions of such data sets require powerful forward solvers for predicting the electrical potentials. State-of-the-art solvers are typically based on finite elements. Recent developments in numerical mathematics led to direct matrix solvers that allow the equation systems arising from such finite element problems to be solved very efficiently. They are particularly useful for 3-D geoelectrical problems, where many electrodes are involved. Although modern direct matrix solvers include optimized memory saving strategies, their application to realistic, large-scale 3-D problems is still somewhat limited. Therefore, we present two novel techniques that allow the number of gridpoints to be reduced considerably, while maintaining a high solution accuracy. In the areas surrounding an electrode array we attach infinite elements that continue the electrical potentials to infinity. This does not only reduce the number of gridpoints, but also avoids the artificial Dirichlet or mixed boundary conditions that are well known to be the cause of numerical inaccuracies. Our second development concerns the singularity removal in the presence of significant surface topography. We employ a fast multipole boundary element method for computing the singular potentials. This renders unnecessary mesh refinements near the electrodes, which results in substantial savings of gridpoints of up to more than 50 per cent. By means of extensive numerical tests we demonstrate that combined application of infinite elements and singularity removal allows the number of gridpoints to be reduced by a factor of ≈6–10 compared with traditional finite element methods. This will be key for applying finite elements and direct matrix solver techniques to realistic 3-D inversion problems.
Mixing Line Analysis of Clouds and Cloudy Boundary Layers

Abstract The diagnostic study of the thermodynamic structure of nonprecipitating clouds and cloudy boundary layers is formulated using a mixing line and saturation point approach. A parametric model for the mean structure is developed as a tool for diagnostic and prognostic modeling. Cloud-scale mixing process are analyzed in the same framework, together with the energetics of the evaporative instability in cumulus clouds. A velocity scale emerges for this evaporative instability. The statistical study of saturation level distribution in partially cloudy boundary layers is proposed to related cloud fraction to the mean thermodynamic mixing processes.
One-shot measurement of surface profile using an astigmatic microscope system

We propose a microscopic system which could be applied to three-dimensional surface profile measurement. In the system, a two-dimensional pinhole array is imaged onto the surface under measurement by an objective lens. These spots act as discrete object points which are then imaged to the CCD chip by the microscope which contains two orthogonal cylindrical lenses. Due to the astigmatism of the two cylindrical lenses, the shape of the image of object points on the CCD camera becomes oval unless the object point is located at a position which satisfies the best imaging condition. By calculating the focus error signal using the intensities measured at a group of CCD cells, the information on the distance of the corresponding object point could be found out. The basic concept of the system was checked by computer simulation on the point spread function of various object points. A preliminary measurement system which consists of the same optical components used in the computer simulation has been set up for verification of the idea. Since this system requires only one image to analyze the surface profile, it is a one-shot measurement system, and is insensitive to environmental noises such as mechanical vibration.
Metric Invariance of the French Version of the Contingencies of Self-Worth Scale

Abstract The Contingencies of Self-Worth Scale is a self-report questionnaire assessing seven types of ‘reward’ for self-worth. To test its construct validity, the French version was administered to 787 undergraduate students of both sexes and the data submitted to confirmatory factor analyses (CFA) with the robust MLM or WLSMV estimators. The reliability of the 7-factor structure as well as its sex invariance were checked with the multiple-group factor model for ordered-categorical measures. The correlated 7-factor structure fitted the data in both sex groups separately first, and then in a simultaneous analysis, confirming the adequacy of the measurement model. Metric invariance was also supported. CFA statistical tests, fit statistics, and parameter estimates as well as indices of local ill-fit were analyzed keeping as basic goal to preserve the questionnaire in its original form. Scalar equivalence across gender was not supported. The exploration of method biases, interacting with gender, as well as w.
Relativistic algorithm for time transfer in Mars missions under IAU Resolutions: an analytic approach

With tremendous advances in modern techniques, Einstein's general relativity has become an inevitable part of deep space missions. We investigate the relativistic algorithm for time transfer between the proper time τ of the onboard clock and the Geocentric Coordinate Time, which extends some previous works by including the effects of propagation of electromagnetic signals. In order to evaluate the implicit algebraic equations and integrals in the model, we take an analytic approach to work out their approximate values. This analytic model might be used in an onboard computer because of its limited capability to perform calculations. Taking an orbiter like Yinghuo-1 as an example, we find that the contributions of the Sun, the ground station and the spacecraft dominate the outcomes of the relativistic corrections to the model.