Miracle-dz/UniFAR-FTUs huggingface dataset:
Gain-control hybrid Raman fiber amplifier/EDFA incorporating ring cavity with a single pump source

All-optical gain-control Raman fiber amplifier (RFA) based on ring cavity technique using a pair of circulators is investigated experimentally. A pair of 1465nm laser diodes is used as the pump source to the RFA which provides a gain peak at around 1565 nm. The analyses of gain and noise figure are carried out using lasing wavelengths of 1550 and 1565 nm. Gain and noise figure variations are 0.4 and 0.5 dB respectively. We observed strong influence of pump-signal relative intensity noise transfer that results in noise figure penalty. The analyses are also carried out on hybrid configuration of RFA and EDFA and the characteristics of the dynamic range of the configurations are being compared.
Using neural networks to solve nonlinear differential equations in atomic and molecular physics

To represent the solution of a differential equation by an artificial neural network (ANN) was an idea introduced by Lagaris. Sugawara applied this concept to solve Schrodinger's equation for select systems. We have submitted their method to a new kind of application. Here, for the first time, the approach is applied to the equations derived from density functional theory (DFT). At first, we have tested the procedure for two simple systems: the double harmonic oscillator and the hydrogen atom. The ANN solutions obtained for these simple systems reproduced the analytical results easily. Next, we have moved to the Tomas–Fermi theory and the Kohn–Sham formulation of DFT. In order to show the feasibility of the ANN representation of electronic density, we have solved the Hooke model-atom and two light atoms: helium and lithium. The ANN results match well with the analytical solution to the Hooke model-atom and with the numerical solutions for helium and lithium. © 2010 Wiley Periodicals, Inc. Int J Quantum Chem, 2011
General Characteristics of Dust Devils.

Abstract An extensive dust devil census taken near Tucson, Ariz. , has provided, from two independent areas, quantitative information on the relation of environmental conditions to the spatial distribution, frequency and duration of a particular type of dry atmospheric thermal. The observations indicate that for these two areas, each approximately 100 mi2 in area, dust devils are initially sighted most frequently in the vicinity of dry river beds which lie in the lee of small hills. Once initiated, the visible lifetime of the observed dust devils ranged from a few seconds to approximately 20 rain. These data show that dust devil duration increases with dust devil size. The results indicate that the energy for the dust devil is the warm boundary layer air which is continually being fed into the visible vortex as it moves along with essentially the same speed and direction as the environmental wind. The highest dust devil frequency occurs with the lowest atmospheric stability and not necessarily with the hig.
Modular forms constructed from moduli of
 elliptic curves, with applications to explicit
 models of modular curves

These are the lecture notes from my portion of a mini-course for the summer school "Building Bridges 3" that was held in Sarajevo during July 2016. My lectures covered the Katz definition of modular forms, a family of forms defined from this perspective and their relation to Eisenstein series, and methods of finding explicit models of modular curves. The treatment is purely expository, and the results are mostly standard, although a few points of view may not be as widely known as they deserve to be.
Davies type estimate and the heat kernel bound under the Ricci flow

We prove a Davies type double integral estimate for the heat kernel $H(y,t;x,l)$ under the Ricci flow. As a result, we give an affirmative answer to a question proposed by Chow etc. Moreover, we apply the Davies type estimate to provide a new proof of the Gaussian upper and lower bounds of $H(y,t;x,l)$ which were first shown by Chau-Tam-Yu.
Constrained percolation, Ising model, and XOR Ising model on planar lattices

We study site percolation models on planar lattices including the [m,4,n,4] lattice and the square tilings on the Euclidean plane ( R2 ) or the hyperbolic plane ( H2 ), satisfying certain local constraints on degree‐4 faces. These models are closely related to Ising models and XOR Ising models (product of two i.i.d Ising models) on regular tilings of R2 or H2 . In particular, we obtain a description of the numbers of infinite “+” and “−” clusters of the ferromagnetic Ising model on a vertex‐transitive triangular tiling of H2 for different boundary conditions and coupling constants. Our results show the possibility that such an Ising configuration has infinitely many infinite “+” and “−” clusters, while its random cluster representation has no infinite open clusters. Percolation properties of corresponding XOR Ising models are also discussed.
Weak-type interpolation for noncommutative maximal operators

We prove a Boyd-type interpolation result for noncommutative maximal operators of restricted weak type. Our result positively answers an open question posed recently by Bekjan, Chen and Osekowski. As a special case, we find a restricted weak type version of the noncommutative Marcinkiewicz interpolation theorem, due to Junge and Xu, with interpolation constant of optimal order.
On Kim-independence

We study NSOP$_{1}$ theories. We define Kim-independence, which generalizes non-forking independence in simple theories and corresponds to non-forking at a generic scale. We show that Kim-independence satisfies a version of Kim's lemma, local character, symmetry, and an independence theorem and that, moreover, these properties individually characterize NSOP$_{1}$ theories. We describe Kim-independence in several concrete theories and observe that it corresponds to previously studied notions of independence in Frobenius fields and vector spaces with a generic bilinear form.
Using Large Language Models to Generate Engaging Captions for Data Visualizations

Creating compelling captions for data visualizations has been a long- standing challenge. Visualization researchers are typically untrained in journalistic reporting and hence the captions that are placed be- low data visualizations tend to be not overly engaging and rather just stick to basic observations about the data. In this work we explore the opportunities offered by the newly emerging crop of large language models (LLM) which use sophisticated deep learning technology to produce human-like prose. We ask, can these power-ful software devices be purposed to produce engaging captions for generic data visualizations like a scatterplot. It turns out that the key challenge lies in designing the most effective prompt for the LLM, a task called prompt engineering . We report on first experiments using the popular LLM GPT-3 and deliver some promising results.
Joint Deep Reinforcement Learning and Unsupervised Learning for Channel Selection and Power Control in D2D Networks

Device-to-device (D2D) technology enables direct communication between devices, which can effectively solve the problem of insufficient spectrum resources in 5G communication technology. Since the channels are shared among multiple D2D user pairs, it may lead to serious interference between D2D user pairs. In order to reduce interference, effectively increase network capacity, and improve wireless spectrum utilization, this paper proposed a distributed resource allocation algorithm with the joint of a deep Q network (DQN) and an unsupervised learning network. Firstly, a DQN algorithm was constructed to solve the channel allocation in the dynamic and unknown environment in a distributed manner. Then, a deep power control neural network with the unsupervised learning strategy was constructed to output an optimized channel power control scheme to maximize the spectrum transmit sum-rate through the corresponding constraint processing. As opposed to traditional centralized approaches that require the collection of instantaneous global network information, the algorithm proposed in this paper used each transmitter as a learning agent to make channel selection and power control through a small amount of state information collected locally. The simulation results showed that the proposed algorithm was more effective in increasing the convergence speed and maximizing the transmit sum-rate than other traditional centralized and distributed algorithms.
Ab initio band bending, metal-induced gap states, and Schottky barriers of a carbon and a boron nitride nanotube device

We have characterized the fully self-consistent electronic properties of a prototypical metal/nanotube interface using a combined nonequilibrium Green's function and density-functional-theory-based formalism, under different conditions of gate and bias voltages. Both carbon and boron nitride nanotubes between Al electrodes were considered. The electronic properties of the interface are dominated both by a dipole and by metal-induced gap states formed through the transfer of charge between the metal and the nanotube. In addition, first-principles estimates\char22{}within the local density approximation\char22{}of the Schottky barrier heights are given.
Simultaneous differential photometry with the St. Andrews twin photometric telescope – I. The eclipsing binary TT Aurigae

On utilise le telescope pour obtenir une courbe de lumiere B complete de cette binaire a interaction de type B. On analyse la courbe de lumiere par le code de synthese LIGHT. Ce systeme est semi-detache mais il a un rapport de masse trop important pour pouvoir etre considere comme un systeme Algol classique
Invariant noncommutative connections

In this paper we classify invariant noncommutative connections in the framework of the algebra of endomorphisms of a complex vector bundle. It has been proven previously that this noncommutative algebra generalizes in a natural way the ordinary geometry of connections. We use explicitly some geometric constructions usually introduced to classify ordinary invariant connections, and we expand them using algebraic objects coming from the noncommutative setting. The main result is that the classification can be performed using a “reduced” algebra, an associated differential calculus and a module over this algebra.
Chiral super-Tremblay–Turbiner–Winternitz Hamiltonians and their dynamical superalgebra

The family of Tremblay–Turbiner–Winternitz (TTW) Hamiltonians Hk on a plane, corresponding to any positive real value of k, is shown to admit another supersymmetric extension than that previously introduced by the present author. This new extension is of the same kind as that considered by D’Hoker and Vinet in the study of magnetic monopoles and is characterized by the fact that all the irreducible representations of the corresponding dynamical superalgebra are atypical lowest-weight state ones. The new supersymmetric Hamiltonians may be referred to as chiral super-TTW Hamiltonians, the role of chirality being played here by the fermion number parity operator.
A generalization of the divide and conquer algorithm for the symmetric tridiagonal eigenproblem

In this paper, we present a generalized Cuppen's divide-and-conquer algorithm for the symmetric tridiagonal eigenproblem. We extend the Cuppen's work to the rank two modifications of the form $A =T +\beta_1\bw_1\bw_1^T + \beta_2\bw_2\bw_2^T$, where $T$ is a block tridiagonal matrix having three blocks. We introduce a new deflation technique and obtain a secular equation, for which the distribution of eigenvalues is nontrivial. We present a way to count the number of eigenvalues in each subinterval. It turns out that each subinterval contains either none, one or two eigenvalues. Furthermore, computing eigenvectors preserving the orthogonality are also suggested. Some numerical results, showing our algorithm can calculate the eigenvalue twice as fast as the Cuppen's divide-and-conquer algorithm, are included.
Geometrically exact time‐integration mesh‐free schemes for advection‐diffusion problems derived from optimal transportation theory and their connection with particle methods

We develop an optimal transportation mesh‐free particle method for advection‐diffusion in which the concentration or density of the diffusive species is approximated by Dirac measures. We resort to an incremental variational principle for purposes of time discretization of the diffusive step. This principle characterizes the evolution of the density as a competition between the Wasserstein distance between two consecutive densities and entropy. Exploiting the structure of the Euler–Lagrange equations, we approximate the density as a collection of Diracs. The interpolation of the incremental transport map is effected through mesh‐free max‐ent interpolation. Remarkably, the resulting update is geometrically exact with respect to advection and volume. We present three‐dimensional examples of application that illustrate the scope and robustness of the method. Copyright © 2017 John Wiley & Sons, Ltd.
Rheological behavior of powder injection molding model slurries

Slurries used in powder injection molding are typically made from high density fillers suspended in a molten wax or other carriers. Particle size and density and base fluid viscosity are the main experimental variables in this work. Slip corrections were made on all of the data for slurries of greater than 20 vol % solids content. Tests are reported on particles that cover a fivefold particle radius range. The data reflect a 1/r dependence on the particle radius. Particle densities range from 2.7 to 19.3 g/cm3. The data show a strong dependence on density. Base fluid viscosities range from 20 to 250 P, and it is shown that higher base‐fluid viscosities result in lower particle concentration effects on the relative fluid viscosity of the slurry. Rheological data are shown to be a function of the mean interparticle spacing, and plots of the relative viscosity versus the mean interparticle spacing exhibit an interesting convergence at about 150 μ.
An inertial primal‐dual fixed point algorithm for composite optimization problems

In this paper, we consider an inertial primal‐dual fixed point algorithm (IPDFP) to compute the minimizations of the sum of a non‐smooth convex function and a finite family of composite non‐smooth convex functions, each one of which is composed of a non‐smooth convex function and a bounded linear operator. This is a full splitting approach, in the sense that non‐smooth functions are processed individually via their proximity operators. The convergence of the IPDFP is obtained by reformulating the problem to the sum of three non‐smooth convex functions. Furthermore, we propose a preconditioning technique for the IPDFP. The key idea of the preconditioning technique is that the constant iterative parameters are updated self‐adaptively in the iteration process. What's more, we also give a simple and easy way to choose the diagonal preconditioners while the convergence of the iterative algorithms is maintained. This work brings together and notably extends several classical splitting schemes, like the primal‐dual method proposed by Chambolle and Pock, and the recent proximity algorithms of Charles et al. designed for the L1$$ {L}_1 $$ /TV image denoising model. The iterative algorithm is used for solving non‐differentiable convex optimization problems arising in image processing.
Monte Carlo renormalisation group study of bootstrap percolation

The authors develop a Monte Carlo position space renormalisation group method to study the scaling properties of bootstrap percolation. In this model sites on a lattice are randomly occupied with probability p and sites with less than m occupied neighbours are culled until a stable configuration remains. Using progressively larger length rescaling factors b, they obtain numerical results on the triangular lattice for the percolation threshold pc(b), the connectedness length exponent nu (b) and the fractal dimension df(b). The large b limit yields numerical values of df for m=2 and 3 which are consistent with df for ordinary percolation (m=0). Although the small b dependence of nu for m=2 and 3 is qualitatively different from that of ordinary percolation, the large b behaviour of nu suggests that m=2 and m=3 bootstrap percolation on the triangular lattice are in the same universality class as ordinary percolation.
Bio-empirical mode decomposition: visible and infrared fusion using biologically inspired empirical mode decomposition

Abstract. Bio-EMD, a biologically inspired fusion of visible and infrared (IR) images based on empirical mode decomposition (EMD) and color opponent processing, is introduced. First, registered visible and IR captures of the same scene are decomposed into intrinsic mode functions (IMFs) through EMD. The fused image is then generated by an intuitive opponent processing the source IMFs. The resulting image is evaluated based on the amount of information transferred from the two input images, the clarity of details, the vividness of depictions, and range of meaningful differences in lightness and chromaticity. We show that this opponent processing-based technique outperformed other algorithms based on pixel intensity and multiscale techniques. Additionally, Bio-EMD transferred twice the information to the fused image compared to other methods, providing a higher level of sharpness, more natural-looking colors, and similar contrast levels. These results were obtained prior to optimization of color opponent processing filters. The Bio-EMD algorithm has potential applicability in multisensor fusion covering visible bands, forensics, medical imaging, remote sensing, natural resources management, etc.
Maximum likelihood estimation of a GARCH‐stable model

Maximum likelihood is used to estimate a generalized autoregressive conditional heteroskedastic (GARCH) process where the residuals have a conditional stable distribution (GARCH-stable). The scale parameter is modeled such that a GARCH process with normally distributed residuals is a special case. The usual methods of estimating the parameters of the stable distribution assume constant scale and will underestimate the characteristic exponent when the scale parameter follows a GARCH process. The parameters of the GARCH-stable model are estimated with daily foreign currency returns. Estimates of characteristic exponents are higher with the GARCH-stable than when independence is assumed. Monte Carlo hypothesis testing procedures, however, reject our GARCH-stable model at the 1 percent significance level in four out of five cases. Copyright 1995 by John Wiley & Sons, Ltd.
A STUDY OF TEMPORAL FEATURES AND FREQUENCY CHARACTERISTICS IN AMERICAN ENGLISH FOREIGN ACCENT

In this paper, a detailed acoustic study of foreign accent is proposed using temporal features, intonation patterns, and frequency characteristics in American English. Using a database which consists of words uttered in isolation, temporal features such as voice onset time, word-final stop closure duration, and characteristics of duration are investigated. Accent differences for native-produced versus Mandarin, German, and Turkish accented English utterances are analyzed. Of the dimensions considered, the most important accent relayer is found to be word-final stop closure duration. Mandarin accented English utterances show significant differences in terms of this feature when compared to native speaker utterances. In addition, the intonation characteristics across a set of foreign accents in American English is investigated. It is shown that Mandarin speaker utterances possess a larger negative continuative intonation slope than native speaker utterances, and German speaker utterances had a more positive intonation slope when compared to native speaker utterances. Finally, a detailed frequency analysis of foreign accented speech is conducted. It is shown that the midfrequency range (1500–2500 Hz) is the most sensitive frequency band to non-native speaker pronunciation variations. Based on this knowledge a new frequency scale for the calculation of cepstrum coefficients is formulated which is shown to outperform the Mel-scale in terms of its ability to classify accent automatically among four accent classes.In this paper, a detailed acoustic study of foreign accent is proposed using temporal features, intonation patterns, and frequency characteristics in American English. Using a database which consists of words uttered in isolation, temporal features such as voice onset time, word-final stop closure duration, and characteristics of duration are investigated. Accent differences for native-produced versus Mandarin, German, and Turkish accented English utterances are analyzed. Of the dimensions considered, the most important accent relayer is found to be word-final stop closure duration. Mandarin accented English utterances show significant differences in terms of this feature when compared to native speaker utterances. In addition, the intonation characteristics across a set of foreign accents in American English is investigated. It is shown that Mandarin speaker utterances possess a larger negative continuative intonation slope than native speaker utterances, and German speaker utterances had a more positive.
Improved VCA in hyperspectral image processing

In recent decades, hyperspectral Images (HSI) have been widely exploited in many fields for rich information containing in them. Many algorithms have been brought out for endmember extracting, among which, VCA algorithm performs a better precision and lower complexity. However, endmembers of the same HIS extracted with traditional VCA algorithm are not always the same in different runs. After deeply analyzing, the authors have proposed an improved VCA algorithm to resolve that shortcoming. For verification, experiment and comparative study have been performed. On conclusion, the improved VCA algorithm has manifested higher efficiency and accuracy than the traditional one.
DYNAMIC ANTI-WINDUP SYNTHESIS FOR DISCRETE-TIME LINEAR SYSTEMS SUBJECT TO INPUT SATURATION AND L2 DISTURBANCES

Abstract This paper deals with the synthesis of dynamic anti-windup compensators for discrete-time linear systems with saturating controls. Considering that the system is subject to the action of L2 bounded disturbances, two approaches for computing the antiwindup compensator in order to guarantee both that the systems trajectories are bounded and a certain L2 performance level is achieved by the regulated outputs are proposed. The first approach considers the synthesis of full order compensators and the second one addresses the synthesis of reduced order compensators.
Silicon-based surface plasmon resonance combined with surface-enhanced Raman scattering for chemical sensing

A Si-based surface plasmon resonance (SPR) technique has been successfully applied to NO2 sensing at ppm level, with estimated detectability at less than 100 ppb. Surface-enhanced Raman scattering (SERS) has been used in this scheme as an inherent additional data acquisition channel capable of providing spectroscopic selectivity and amplified sensitivity. The behavior of both the SERS spectrum and the SPR-induced photosignal produced by Au-on-Si grating structures coated with thin 18-crown-6 metal-free phthalocyanine films was simultaneously recorded for exposure of the films to 10 ppm of NO2 in air and its reversal in clean air. Both responses have been found to be reversible. The combination of Si-based SPR and SERS looks promising for thin-film and surface explorations, both in fundamental and sensor applications.