Miracle-dz/UniFAR-FTUs huggingface dataset:
High-speed three-dimensional measurements with a fringe projection-based optical sensor

Abstract. An optical three-dimensional (3-D) sensor based on a fringe projection technique that realizes the acquisition of the surface geometry of small objects was developed for highly resolved and ultrafast measurements. It realizes a data acquisition rate up to 60 high-resolution 3-D datasets per second. The high measurement velocity was achieved by consequent fringe code reduction and parallel data processing. The reduction of the length of the fringe image sequence was obtained by omission of the Gray code sequence using the geometric restrictions of the measurement objects and the geometric constraints of the sensor arrangement. The sensor covers three different measurement fields between 20 mm×20 mm and 40 mm×40 mm with a spatial resolution between 10 and 20 μm, respectively. In order to obtain a robust and fast recalibration of the sensor after change of the measurement field, a calibration procedure based on single shot analysis of a special test object was applied which works with low effort and time. The sensor may be used, e.g., for quality inspection of conductor boards or plugs in real-time industrial applications.
Características dos CFO e gerenciamento de resultados em companhias brasileiras

Apesar de a Teoria do Alto Escalão sustentar que os gestores da alta administração se pautam em suas características pessoais para interpretar as situações, formar opiniões e tomar as suas decisões, as pesquisas no Brasil investigam, predominantemente, como os aspectos contratuais, econômicos e institucionais afetam as escolhas organizacionais. Assim, este estudo teve o objetivo de preencher esta lacuna e verificar se as características dos Chief Financial Officer (CFO) estão associadas com a adoção de práticas de gerenciamento de resultados nas entidades. Para tanto, realizou-se uma pesquisa quantitativa, efetuada por meio do levantamento das informações referentes às companhias abertas brasileiras. Identificou-se que a idade e o nível educacional dos CFO apresentam associação negativa com as práticas de gerenciamento de resultados. Os achados sugerem que, assim como as características contratuais, econômicas e institucionais afetam o gerenciamento de resultados das entidades, as características observáveis dos CFO também são determinantes nesse processo.
Grothendieck's reconstruction principle and 2-dimensional topology and geometry

This paper attempts to relate some ideas of Grothendieck in his Esquisse d'un programme and some of the recent results on 2-dimensional topology and geometry. Especially, we shall discuss the Teichm\"uller theory, the mapping class groups, $SL(2, \bold C)$ representation variety of surface groups, and Thurston's theory of measured laminations.
Maximising 
H ‐colourings of graphs

For graphs G and H , an H ‐colouring of G is a map ψ : V ( G ) → V ( H ) such that i j ∈ E ( G ) ⇒ ψ ( i ) ψ ( j ) ∈ E ( H ) . The number of H ‐colourings of G is denoted by hom ( G , H ) . We prove the following: for all graphs H and δ ≥ 3 , there is a constant κ ( δ , H ) such that, if n ≥ κ ( δ , H ) , the graph K δ , n − δ maximises the number of H ‐colourings among all connected graphs with n vertices and minimum degree δ . This answers a question of Engbers. We also disprove a conjecture of Engbers on the graph G that maximises the number of H ‐colourings when the assumption of the connectivity of G is dropped. Finally, let H be a graph with maximum degree k . We show that, if H does not contain the complete looped graph on k vertices or K k , k as a component and δ ≥ δ 0 ( H ) , then the following holds: for n sufficiently large, the graph K δ , n − δ maximises the number of H ‐colourings among all graphs on n vertices with minimum degree δ . This partially answers another question of Engbers.
Slip Flow Analysis in an Experimental Chamber Simulating Differential Pumping in an Environmental Scanning Electron Microscope

This paper describes the combination of experimental measurements with mathematical–physical analysis during the investigation of flow in an aperture at low pressures in a prepared experimental chamber. In the first step, experimental measurements of the pressure in the specimen chamber and at its outlet were taken during the pumping of the chamber. This process converted the atmospheric pressure into the operating pressure typical for the current AQUASEM II environmental electron microscope at the ISI of the CAS in Brno. Based on these results, a mathematical–physical model was tuned in the Ansys Fluent system and subsequently used for mathematical–physical analysis in a slip flow regime on a nozzle wall at low pressure. These analyses will be used to fine-tune the experimental chamber. Once the chamber is operational, it will be possible to compare the results obtained from the experimental measurements of the nozzle wall pressure, static pressure, total pressure and temperature from the nozzle axis region in supersonic flow with the results obtained from the mathematical–physical analyses. Based on the above comparative analyses, we will be able to determine the realistic slip flow at the nozzle wall under different conditions at the continuum mechanics boundary.
Entropy‐based lamarckian quantum‐behaved particle swarm optimization for flexible ligand docking

AutoDock is a widely used software for flexible ligand docking problems since it is open source and easy to be implemented. In this paper, a novel hybrid algorithm is proposed and applied in the docking environment of AutoDock version 4.2. 6 in order to enhance the accuracy and the efficiency for dockings with flexible ligands. This search algorithm, called entropy‐based Lamarckian quantum‐behaved particle swarm optimization (ELQPSO), is a combination of the QPSO with an entropy‐based update strategy and the Solis and Wet local search (SWLS) method. By using the PDBbind core set v.2016, the ELQPSO is compared with the Lamarckian genetic algorithm (LGA), Lamarckian particle swarm optimization (LPSO) and Lamarckian QPSO (LQPSO). The experimental results reveal that the corresponding docking program of ELQPSO, named as EQDOCK in this paper, has a competitive performance in dealing with the protein‐ligand docking problems. Moreover, for the test cases with different number of torsions, the EQDOCK outperforms the other three docking programs in finding docking conformations with small root mean squared deviation (RMSD) values in most cases. In particular, it has an advantage of solving highly flexible ligand docking problems over the others.
A probabilistic weak formulation of mean field games and applications

Mean field games are studied by means of the weak formulation of stochastic optimal control. This approach allows the mean field interactions to enter through both state and control processes and take a form which is general enough to include rank and nearest-neighbor effects. Moreover, the data may depend discontinuously on the state variable, and more generally its entire history. Existence and uniqueness results are proven, along with a procedure for identifying and constructing distributed strategies which provide approximate Nash equlibria for finite-player games. Our results are applied to a new class of multi-agent price impact models and a class of flocking models for which we prove existence of equilibria.
A finite element formulation of the outlet gradient boundary condition for convective–diffusive transport problems

A simple finite element formulation of the outlet gradient boundary condition is presented in the general context of convective–diffusive transport processes. Basically, the method is based on an upstream evaluation of the dependent variable gradient along open boundaries. Boundary normal unit vectors and gradient operators are evaluated using covariant bases and metric tensors, which allow handling finite elements of mixed dimensions. Even though the presented method has implications for many fields where diffusion processes are involved, discussion and illustrative examples address more particularly the framework of contaminant transport in porous media, in which the outlet gradient concentration is classically, but wrongly assumed to be zero. Copyright © 2004 John Wiley & Sons, Ltd.
Nonlinear image operators, higher-order statistics, and the AND-like combinations of frequency components

The frequency domain plays a key role in the description of signals and systems. In the classical approaches, the individual frequency components are treated as independent. In linear systems, the superposition principle restricts the filtering to an OR-like processing of independent complex exponentials. Likewise, the classical second-order statistic (the power spectrum) measures only the occurrence of each individual frequency component, independent of whether it occurs in a systematic combination with other components or not. This basic limitation can be overcome by the extension of the classical approaches to nonlinear systems and higher-order statistics, which makes it possible to selectively address AND-like combinations of frequency components. We measure which AND combinations are statistically most relevant in natural images, and investigate how this statistical structure can be exploited by nonlinear Volterra filters.
Positive effect of COVID pandemic on the depression, stress and insomnia among first-year university students

ABSTRACT Literature data show that acute, severe, and also chronic stress play an important role in the development of somatic and mental disorders. It is well documented in the literature that starting university studies results in anxiety in many ways for individuals. In this present work, we examined how perceived stress affects the appearance of depression and sleep disorders among a special group: the first-year undergraduates. In February 2020, 134 students completed a 14-question Perceived Stress Scale questionarre. In addition, the 13-question Beck Depression Scale and the 8-question Athens Insomnia Scale were used as measures to assess their current mental health status. Following the outbreak of the COVID-19 pandemic, the extent to which anxiety and depressive symptoms changed had become a major issue worldwide. In June 2020, we repeated our previous measures in the given population with the same methods. Our research clearly proved higher perceived stress values among undergraduate students, which were associated with high depressive symptom parameters and insomnia. However, unexpectedly, questionnaires completed during the quarantine period of the COVID pandemic showed lower perceived stress, which was accompanied by a decrease in depressive symptoms and insomnia.
R matrices of three-state Hamiltonians solvable by coordinate Bethe ansatz

We review some of the strategies that can be implemented to infer an R-matrix from the knowledge of its Hamiltonian. We apply them to the classification achieved in Crampe, Frappat, and Ragoucy, J. Phys. A 46, 405001 (2013), on three state U(1)-invariant Hamiltonians solvable by coordinate Bethe ansatz, focusing on models for which the S-matrix is not trivial. For the 19-vertex solutions, we recover the R-matrices of the well-known Zamolodchikov–Fateev and Izergin–Korepin models. We point out that the generalized Bariev Hamiltonian is related to both main and special branches studied by Martins in Nucl. Phys. B 874, 243 (2013), that we prove to generate the same Hamiltonian. The 19-vertex SpR model still resists to the analysis, although we are able to state some no-go theorems on its R-matrix. For 17-vertex Hamiltonians, we produce a new R-matrix.
Thioredoxin h2 inhibits the MPKK5-MPK3 cascade to regulate the CBF–COR signaling pathway in Citrullus lanatus suffering chilling stress

Abstract Thioredoxins (TRXs) are ubiquitous oxidoreductases and present as a multigenic family. TRXs determine the thiol redox balance, which is crucial for plants in the response to cold stress. However, limited knowledge is available about the role of TRXs in watermelon (Citrullus lanatus), which is highly sensitive to chilling stress in agricultural practice. Here, we identified 18 genes encoding 14 typical and 4 atypical TRXs from the watermelon genome, and found that ClTRX h2 localized at the plasma membrane was largely induced by chilling. Virus-induced gene silencing of ClTRX h2 resulted in watermelon plants that were more sensitive to chilling stress. We further found that ClTRX h2 physically interacted with mitogen-activated protein kinase kinase 5 (ClMPKK5), which was confirmed to phosphorylate and activate ClMPK3 in vitro, and the activation of ClMPK3 by ClMPKK5 was blocked by a point mutation of the Cys-229 residue to Ser in ClMPKK5. Additionally, ClTRX h2 inhibited the chilling-induced activation of ClMPK3, suggesting that the ClMPKK5–ClMPK3 cascade is regulated in a redox-dependent manner. We showed that ClMPK3-silenced plants had increased tolerance to chilling, as well as enhanced transcript abundances of the C-repeat/DREB binding factor (ClCBF) and cold-responsive (ClCOR) genes. Taken together, our results indicate that redox status mediated by ClTRX h2 inhibits ClMPK3 phosphorylation through the interaction between ClTRX h2 and ClMPKK5, which subsequently regulates the CBF–COR signaling pathway when submitted to chilling stress. Hence, our results provide a link between thiol redox balance and MAPK cascade signaling, revealing a conceptual framework to understand how TRX regulates chilling stress tolerance in watermelon.
On a three level two-grid finite element method for the 2D-transient Navier-Stokes equations

In this paper, an error analysis of a three steps two level Galekin finite element method for the two dimensional transient Navier-Stokes equations is discussed. First of all, the problem is discretized in spatial direction by employing finite element method on a coarse mesh $\mathcal{T} _H$ with mesh size $H$. Then, in step two, the nonlinear system is linearized around the coarse grid solution, say, $u_H$, which is similar to Newton's type iteration and the resulting linear system is solved on a finer mesh $\mathcal{T}_h$ with mesh size $h$. In step three, a correction is obtained through solving a linear problem on the finer mesh and an updated final solution is derived. Optimal error estimates in $L^{\infty}({\bf L}^2)$-norm, when $h=\mathcal{O} (H^{2-\delta})$ and in $L^{\infty}(\bH^1)$-norm, when $h=\mathcal{O}(H^{4-\delta})$ for the velocity and in $L^{\infty}(L^2)$-norm, when $h=\mathcal{O}(H^{4-\delta})$ for the pressure are established for arbitrarily small $\delta>0$. Further, under uniqueness assumption, these estimates are proved to be valid uniformly in time. Then based on backward Euler method, a completely discrete scheme is analyzed and {\it a priori} error estimates are derived. Finally, the paper is concluded with some numerical experiments.
Study of the effect of Ethanolic extract of pomegranate peels on some blood serum biochemical parameters in alloxan induced diabetes male rats

This study was conducted in at the Biotechnology Research Center / Nahrain University / Baghdad Governorate, for the period 2/8/2020 to 15/9/2020, the follow of the effects of dosing with ethanolic extract of pomegranate peels on 30 male rats of (2-3) months of age and weights (170-220 g) were included, it was divided into two parts, one of which is intact and the other in which diabetes was introduced by using alloxan at a concentration (90 mg / kg) of body weight, The results showed of the biological study that the development of experimental diabetes showed significant increase (P <0.05) in the concentrations of Glucose, Total cholesterol (TC), Trigleserid (TG), low-density lipoproteins cholesterol (LDL-C), Very-low-density lipoprotein cholesterol (VLDL-C), and the enzymes of aspartate transaminase and alanine transaminase (AST و ALT), and malonedialdehyde concentration (MDA), Compared with a intact control group, while it led to a significant decrease (P <0.05) in body weight, insulin concentration, high-density lipoprotein cholesterol (HDL), in the affected control group. Dosing in intact rats with ethanolic extract of pomegranate peel at a concentration of 75 and 150 mg / kg of body weight led to a significant decrease in the concentrations of glucose, TC, TG, LDL-C and VLDL-C, as well as AST, ALT, and MDA enzymes, compared with a healthy control group, Significant increase in body weight, insulin and HDL-C concentrations for all treatments compared with the healthy control group. Dosing of diabetic rats with ethanolic extract of pomegranate peels at a concentration of 75 and 150 mg / kg of body weight led to a significant decrease in the concentrations of glucose, TC, TG, LDL-C and VLDL-C, as well as AST, ALT, and MDA enzymes, compared with the infected and untreated control group, a significant increase in body weight, insulin and HDL-C concentrations, for all treatments, compared with the affected control group.
Optimization methods for Dirichlet control problems

Abstract We discuss several optimization procedures to solve finite element approximations of linear-quadratic Dirichlet optimal control problems governed by an elliptic partial differential equation posed on a 2D or 3D Lipschitz domain. The control is discretized explicitly using continuous piecewise linear approximations. Unconstrained, control-constrained, state-constrained and control-and-state constrained problems are analysed. A preconditioned conjugate method for a reduced problem in the control variable is proposed to solve the unconstrained problem, whereas semismooth Newton methods are discussed for the solution of constrained problems. State constraints are treated via a Moreau–Yosida penalization. Convergence is studied for both the continuous problems and the finite dimensional approximations. In the finite dimensional case, we are able to show convergence of the optimization procedures even in the absence of Tikhonov regularization parameter. Computational aspects are also treated and several numerical examples are included to illustrate the theoretical results.
Single shock solution for non convex scalar conservation laws

In this paper we study the finite time emergence of one shock for the solution of scalar conservation laws in one space dimension with general flux f . We give a necessary and sufficient condition to the initial data connecting to flux. The proof relies on the structure theorem for the linear degenerate flux and the finer analysis of characteristic curves.
K-theory for the Leaf Spaces of the Orbit Foliations of the co-adjoint Action of some 5-dimensional Solvable Lie groups

In this paper, combining Kirillov's method of orbits with Connes' method in Differential Geometry, we study the so-called MD(5,3C)-foliations, i.e. the orbit foliations of the co-adjoint action of MD(5,3C)-groups. First, we classify topologically MD(5,3C)-foliations based on the classification of all MD(5,3C)-algebras in [22] and the picture of co-adjoint orbits (K-orbits) of all MD(5,3C)-groups in [23]. Finally, we study K-theory for leaf space of MD(5,3C)-foliations and describe analytically or characterize Connes' C*-algebras of the considered foliations by KK-functors.
On the discretisation in time of the stochastic Allen–Cahn equation

We consider the stochastic Allen–Cahn equation perturbed by smooth additive Gaussian noise in a bounded spatial domain with smooth boundary in dimension d≤3 , and study the semidiscretisation in time of the equation by an Euler type split‐step method with step size k>0 . We show that the method converges strongly with a rate O(k12) . By means of a perturbation argument, we also establish the strong convergence of the standard backward Euler scheme with the same rate.
The triangle-free process and the Ramsey number $R(3,k)$

The areas of Ramsey theory and random graphs have been closely linked ever since Erd\H{o}s' famous proof in 1947 that the 'diagonal' Ramsey numbers $R(k)$ grow exponentially in $k$. In the early 1990s, the triangle-free process was introduced as a model which might potentially provide good lower bounds for the 'off-diagonal' Ramsey numbers $R(3,k)$. In this model, edges of $K_n$ are introduced one-by-one at random and added to the graph if they do not create a triangle; the resulting final (random) graph is denoted $G_{n,\triangle}$. In 2009, Bohman succeeded in following this process for a positive fraction of its duration, and thus obtained a second proof of Kim's celebrated result that $R(3,k) = \Theta \big( k^2 / \log k \big)$. In this paper we improve the results of both Bohman and Kim, and follow the triangle-free process all the way to its asymptotic end. In particular, we shall prove that $$e\big( G_{n,\triangle} \big) \,=\, \left( \frac{1}{2\sqrt{2}} + o(1) \right) n^{3/2} \sqrt{\log n },$$ with high probability as $n \to \infty$. We also obtain several pseudorandom properties of $G_{n,\triangle}$, and use them to bound its independence number, which gives as an immediate corollary $$R(3,k) \, \ge \, \left( \frac{1}{4} - o(1) \right) \frac{k^2}{\log k}. $$ This significantly improves Kim's lower bound, and is within a factor of $4 + o(1)$ of the best known upper bound, proved by Shearer over 25 years ago.
Seismic Waveform Inversion Capability on Resource-Constrained Edge Devices

Seismic full wave inversion (FWI) is a widely used non-linear seismic imaging method used to reconstruct subsurface velocity images, however it is time consuming, has high computational cost and depend heavily on human interaction. Recently, deep learning has accelerated it’s use in several data-driven techniques, however most deep learning techniques suffer from overfitting and stability issues. In this work, we propose an edge computing-based data-driven inversion technique based on supervised deep convolutional neural network to accurately reconstruct the subsurface velocities. Deep learning based data-driven technique depends mostly on bulk data training. In this work, we train our deep convolutional neural network (DCN) (UNet and InversionNet) on the raw seismic data and their corresponding velocity models during the training phase to learn the non-linear mapping between the seismic data and velocity models. The trained network is then used to estimate the velocity models from new input seismic data during the prediction phase. The prediction phase is performed on a resource-constrained edge device such as Raspberry Pi. Raspberry Pi provides real-time and on-device computational power to execute the inference process. In addition, we demonstrate robustness of our models to perform inversion in the presence on noise by performing both noise-aware and no-noise training and feeding the resulting trained models with noise at different signal-to-noise (SNR) ratio values. We make great efforts to achieve very feasible inference times on the Raspberry Pi for both models. Specifically, the inference times per prediction for UNet and InversionNet models on Raspberry Pi were 22 and 4 s respectively whilst inference times for both models on the GPU were 2 and 18 s which are very comparable. Finally, we have designed a user-friendly interactive graphical user interface (GUI) to automate the model execution and inversion process on the Raspberry Pi.
Contact structures on Lie algebroids

In this paper we generalize the main notions from the geometry of (almost) contact manifolds in the category of Lie algebroids. Also, using the framework of generalized geometry, we obtain an (almost) contact Riemannian Lie algebroid structure on a vertical Liouville distribution over the big-tangent manifold of a Riemannain manifold.