Miracle-dz/UniFAR-FTUs huggingface dataset:
Stability and three-dimensional evolution of a transitional dynamic stall vortex

This paper describes a series of experiments using particle image velocimetry to investigate the dynamic stall resulting due to a rapid pitching motion of a flat plate. There exist in such unsteady separated flows multiple time-dependent coherent structures, whose interaction and evolution are complex and nonlinear. The experiments presented here are aimed at determining the behaviour of a dynamic stall vortex system in the Reynolds number range $10^{3}<Re<10^{4}$ . Evidence is presented for the development of the three-dimensional structure associated with the dynamic stall vortex and its interaction with the no-slip boundary condition at the surface of the pitching plate. The analysis presented suggests that a centrifugal instability exists, and that the form of the three-dimensional structure is consistent with that expected of a centrifugal instability. The structure and scale dependence of the flow are explored using wavelet and Fourier methods, with the dependence of the flow on Reynolds number examined, as well as the influence of spanwise end boundary conditions.
PTLp: Partial Transport Lp Distances

Optimal transport and its related problems, including optimal partial transport, have proven to be valuable tools in machine learning for computing meaningful distances between probability or positive measures. This success has led to a growing interest in defining transport-based distances that allow for comparing signed measures and, more generally, multi-channeled signals. Transport $\mathrm{L}^{p}$ distances are notable extensions of the optimal transport framework to signed and possibly multi-channeled signals. In this paper, we introduce partial transport $\mathrm{L}^{p}$ distances as a new family of metrics for comparing generic signals, benefiting from the robustness of partial transport distances. We provide theoretical background such as the existence of optimal plans and the behavior of the distance in various limits. Furthermore, we introduce the sliced variation of these distances, which allows for rapid comparison of generic signals. Finally, we demonstrate the application of the proposed distances in signal class separability and nearest neighbor classification.
The impact of COVID-19 on community-dwelling people post-stroke and informal caregivers: a qualitative study

Background/ aims: Little is known about the experience of people post-stroke and their informal caregivers during the COVID-19 pandemic. The aim of this study was to understand the challenges faced by people post-stroke and informal caregivers during the pandemic, as well as the impact on their healthcare support, lifestyle, and self-care behaviors. Methods: A multi-perspective qualitative study was undertaken, with semi-structured interviews being carried out to sixteen participants: eight stroke patients and eight informal caregivers, mostly performed online. Reflexive thematic analysis was used, with data being independently coded and categorized before consolidated into themes and subthemes. Findings: Three themes were derived from the data analysis: i) Perceived impact of COVID-19 pandemic, ii) What helped? - strategies to manage the distress provoked by COVID-19, and iii) The value of rehabilitation and physical activity, with findings highlighting the negative psychological impact of the pandemic. In response to the perceived lack of support and access to health and social services, participants highlighted the use of digital approaches and professional support. Conclusions: Findings suggest the importance of self-management support and/or digital content in order to mitigate the impact of COVID-19. The involvement of peers, family members, friends or others seems to be an important strategy to increase motivation in remote rehabilitation and physical activity.
Analysis of Oscillation Effects on HotStreak Migration Characteristics in Turbine Vane Passage

ABSTRACT The high pressure turbine is subjected to the inlet hot gas resulting from the combustor, which is generally non-uniform. The strong non-uniform temperature at the turbine inlet is known as “hotstreak. ” Although many studies have been performed to investigate the hotstreak migration in the turbine vane passage, the HS is generally modeled to be steady and there are relatively few studies on the unsteady oscillating hot streak (OHS). The present study performs numerical investigations on the oscillation effects on the HS migration characteristics. The OHS is modeled to be oscillating in the circumferential direction, with varying oscillation magnitude and frequency. The steady hot streak (SHS) is modeled to be positioned at the guide vanes. Comparisons between the SHS and the OHS are conducted in detail regarding the flow and heat transfer characteristics. Both of the two cases of HS are based on the NASA experiment report and the No. 4313 case in the experimental design is selected. It is found that the change of HS from steady to oscillating leads to significant differences of transient periodic fluctuating characteristics of heat load and pressure on the guide vane. The HS areas are increased significantly and the mean temperature is decreased correspondingly. The introduction of oscillation effects is found to merit a better prediction of the real HS migration features in the real turbine passage.
Numerical simulations of effective thermal conductivity in aluminum foam sandwich panel

In this work, the effective thermal conductivities of aluminum foam sandwich panels with the porosity range from 40% to 60% were studied by simulation method. The influence of porosity and pore size on the effective thermal conductivities was analyzed, and their influence mechanism was studied. In addition, simulation results were verified by theoretical formula. This further proves the feasibility of simulation method for research on the effective thermal conductivity of aluminum foam sandwich panels. The results confirmed that the porosity and pore size of aluminum foam sandwich panel had great impact upon its effective thermal conductivity.
Label-free super-resolution with coherent nonlinear structured-illumination microscopy

Structured-illumination microscopy enables up to a two-fold lateral resolution improvement by spatially modulating the intensity profile of the illumination beam. We propose a novel way to generalize the concept of structured illumination to nonlinear widefield modalities by spatially modulating, instead of field intensities, the phase of the incident field while interferometrically measuring the complex-valued scattered field. We numerically demonstrate that for second-order and third-order processes an almost four- and six-fold increase in lateral resolution is achievable, respectively. This procedure overcomes the conventional Abbe diffraction limit and provides new possibilities for label-free super-resolution microscopy.
Volterra type operators between weighted Banach spaces and Bloch type spaces

Smith et al. gave the sufficient and necessary conditions for the boundedness of Volterra type operators on Banach spaces of bounded analytic functions when the symbol functions are univalent. Lin recently extended their results to weighted Banach spaces with standard weights. In this paper, continuing this line of investigation, we give the complete characterizations of the conditions for the boundedness and compactness of Volterra type operators $T_g$ and their companion operators $S_g$ between weighted Banach spaces $H^{\infty}_\nu$ and Bloch type spaces $\mathcal{B}^\infty_\nu$ with more general weights, which generalize their works.
Glissement et élongation des fluides à seuil

Le ketchup, la moutarde, la mousse a raser, sont des fluides a seuil, ils s’ecoulent uniquement lorsqu’on leur applique une contrainte superieure a une valeur critique, appelee contrainte seuil. Sur des surfaces lisses, ces fluides peuvent s’ecouler sous de petites contraintes : on a alors un phenomene de glissement. En etudiant par rheometrie les ecoulements de ces materiaux des sequences originales et une technique d’imagerie directe (velocimetrie en IRM), on montre que le glissement ne se produit qu’au-dela d’une contrainte critique. Selon les cas, cette contrainte critique est due soit a un effet de bord, soit a un effet de surface. L’exces de contrainte par rapport a cette contrainte critique varie lineairement avec la vitesse de glissement. De ce fait le glissement peut etre represente comme le cisaillement d’une couche de liquide le long de la paroi, mais la realite est plus complexe compte tenu de la structure du materiau au contact avec la paroi. Curieusement l’epaisseur de cette couche de liquide « equivalente » ne semble pas varier avec la concentration, la taille des gouttes, la force normale, etc. Ceci suggere que cette epaisseur est gouvernee par des forces plus elevees que la lubrification et la pression osmotique. Nous etudions egalement le glissement pour des ecoulements plus complexes. Pour cela on impose une elongation au fluide a seuil par une experience de traction avec des surfaces lisses. La force normale mesuree pour differents materiaux avec des structures differentes montre que la condition de transition solide-liquide en elongation est differente que ce que predit la theorie standard, et l’epaisseur de la couche de glissement est de plusieurs ordres de grandeur superieure a celle trouvee en cisaillement simple
Locality constrained dictionary learning for human behaviour recognition

ABSTRACT Improvement of the accuracy and robustness of human behaviour recognition is still a challenging problem. In this paper, a human behaviour recognition method based on locality constrained dictionary learning (LCDL) is proposed, in which two global features, namely average motion energy image (AMEI) and enhanced motion energy image (EMEI), are employed for the description of human behaviours. A discriminative structured dictionary is learned by the LCDL algorithm, whose sub-dictionary corresponds to each type of human behaviour. Moreover, the sparse representation errors of the testing samples are used for the recognition. The results of simulations and performance comparisons on typical datasets show that the proposed methods can reduce the storage space and calculation quantity through the normalization treatment of AMEIs and EMEIs. Since the locality constrained conditions can enforce the intra-class distance and improve the discriminative ability of the structured dictionary, the recognition performance is improved.
Face recognition based on texture information and geodesic distance approximations between multivariate normal distributions

Geodesic distance is a natural dissimilarity measure between probability distributions of a specific type, and can be used to discriminate texture in image-based measurements. Furthermore, since there is no known closed-form solution for the geodesic distance between general multivariate normal distributions, we propose two efficient approximations to be used as texture dissimilarity metrics in the context of face recognition. A novel face recognition approach based on texture discrimination in high-resolution color face images is proposed, unlike the typical appearance-based approach that relies on low-resolution grayscale face images. In our face recognition approach, sparse facial features are extracted using predefined landmark topologies, that identify discriminative image locations on the face images. Given this landmark topology, the dissimilarity between distinct face images are scored in terms of the dissimilarities between their corresponding face landmarks, and the texture in each one of these landmarks is represented by multivariate normal distributions, expressing the color distribution in the vicinity of each landmark location. The classification of new face image samples occurs by determining the face image sample in the training set which minimizes the dissimilarity score, using the nearest neighbor rule. The proposed face recognition method was compared to methods representative of the state-of-the-art, using color or grayscale face images, and presented higher recognition rates. Moreover, the proposed texture dissimilarity metric also is efficient in general texture discrimination (e.g. texture recognition of material images), as our experiments suggest.
Advances in attractive ellipsoid method for robust control design

Our contribution is devoted to a further theoretic development of the attractive ellipsoid method (AEM). We consider dynamic models given by nonlinear ordinary differential equations in the presence of bounded disturbances. The resulting robustness analysis of the closed‐loop system incorporates the celebrated Clarke invariancy concept (an analytic extension of the celebrated Lyapunov methodology). We finally obtain a new general geometric characterization of the AEM‐based approach to the robust systems design. Moreover, we also discuss the corresponding numerical aspects of the proposed theoretical extensions of the method. The theoretic results obtained in this contribution are finally illustrated by a practically oriented computational example.
Shape optimization using a NURBS‐based interface‐enriched generalized FEM

This study presents a gradient‐based shape optimization over a fixed mesh using a non‐uniform rational B‐splines‐based interface‐enriched generalized finite element method, applicable to multi‐material structures. In the proposed method, non‐uniform rational B‐splines are used to parameterize the design geometry precisely and compactly by a small number of design variables. An analytical shape sensitivity analysis is developed to compute derivatives of the objective and constraint functions with respect to the design variables. Subtle but important new terms involve the sensitivity of shape functions and their spatial derivatives. Verification and illustrative problems are solved to demonstrate the precision and capability of the method. Copyright © 2016 John Wiley & Sons, Ltd.
Topology of three-dimensional steady cellular flow in a two-sided anti-parallel lid-driven cavity

The structure of the incompressible steady three-dimensional flow in a two-sided anti-symmetrically lid-driven cavity is investigated for an aspect ratio $\unicode[STIX]{x1D6E4}=1.7$ and spanwise-periodic boundary conditions. Flow fields are computed by solving the Navier–Stokes equations with a fully spectral method on $128^{3}$ grid points utilizing second-order asymptotic solutions near the singular corners. The supercritical flow arises in the form of steady rectangular convection cells within which the flow is point symmetric with respect to the cell centre. Global streamline chaos occupying the whole domain is found immediately above the threshold to three-dimensional flow. Beyond a certain Reynolds number the chaotic sea recedes from the interior, giving way to regular islands. The regular Kolmogorov–Arnold–Moser tori grow with increasing Reynolds number before they shrink again to eventually vanish completely. The global chaos at onset is traced back to the existence of one hyperbolic and two elliptic periodic lines in the basic flow. The singular points of the three-dimensional flow which emerge from the periodic lines quickly change such that, for a wide range of supercritical Reynolds number, each periodic convection cell houses a double spiralling-in saddle focus in its centre, a spiralling-out saddle focus on each of the two cell boundaries and two types of saddle limit cycle on the walls. A representative analysis for $\mathit{Re}=500$ shows chaotic streamlines to be due to chaotic tangling of the two-dimensional stable manifold of the central spiralling-in saddle focus and the two-dimensional unstable manifold of the central wall limit cycle. Embedded Kolmogorov–Arnold–Moser tori and the associated closed streamlines are computed for several supercritical Reynolds numbers owing to their importance for particle transport.
Estimation and influence diagnostics for zero-inflated hyper-Poisson regression model: full Bayesian analysis

ABSTRACT The purpose of this paper is to develop a Bayesian analysis for the zero-inflated hyper-Poisson model. Markov chain Monte Carlo methods are used to develop a Bayesian procedure for the model and the Bayes estimators are compared by simulation with the maximum-likelihood estimators. Regression modeling and model selection are also discussed and case deletion influence diagnostics are developed for the joint posterior distribution based on the functional Bregman divergence, which includes ψ-divergence and several others, divergence measures, such as the Itakura–Saito, Kullback–Leibler, and χ2 divergence measures. Performance of our approach is illustrated in artificial, real apple cultivation experiment data, related to apple cultivation.
Extending resource-based theory : considering strategic, ordinary and junk resources

– The purpose of this paper is to answer the question: how to extend resource-based theory to take into account the contribution of all kinds of resources (including the less regarded ones) to performance? While recognising the importance of strategic resources in building and sustaining a competitive advantage, the authors contend that a symmetric analysis of more available resources can shed new light on the sources and mechanisms of superior performance. Thus, they aim to contribute to an extended theory of resources. , – Based on literature review and theorization process, the authors introduce alongside strategic resources, the concepts of “ordinary resources” and “junk resources”, showing how they may contribute to performance with an appropriate business model. Several illustrative cases are discussed to demonstrate that such resources need to be studied by resource-based theory (RBT). , – The authors propose shifting the focus of RBT from the study of strategic resources alone in order to consider other types as well: ordinary and junk resources. Such an approach involves significant implications for strategic management theory and management practices. , – The paper describes the conditions under which ordinary and junk resources (more available to most firms than strategic resources) may generate a competitive advantage. The extended resource-based theory can have implications for society as it may influence managers ' and public attitudes towards underestimated resources and lead to new business models. , – The approach developed in this article also goes beyond traditional critiques of RBT. Specifically, the authors ' analysis avoids tautological reasoning, distinguishing between: resources; perceptions of their attributes by firms; the services these resources render; the business model implemented to deploy these resources; and the effects in terms of performance. The authors build an extended resource-based theory, allowing the contribution of various kinds of resources to firm performance to be explained.
Interpolating clothoid splines with curvature continuity

An efficient algorithm for the computation of a C2 interpolating clothoid spline is herein presented. The spline is obtained following an optimisation process, subject to continuity constraints. Among the 9 various targets/problems considered, there are boundary conditions, minimum length path, minimum jerk, and minimum curvature (energy). Some of these problems are solved with just a couple of Newton iterations, whereas the more complex minimisations are solved with few iterations of a nonlinear solver. The solvers are warmly started with a suitable initial guess, which is extensively discussed, making the algorithm fast. Applications of the algorithm are shown relating to fonts, path planning for human walkers, and as a tool for the time‐optimal lap on a Formula 1 circuit track.
Visualising volumetric fractals

Fractal images have for many years been a rich source of exploration by those in computer science who also have an interest in graphics. They often served as a way of testing the performance of new computing hardware and to explore the capabilities of emerging display technologies. While there have been forays by some into 3D geometric fractals, the 3D equivalents of the Mandelbrot set have been largely ignored. This is largely due to the lack of suitable tools for rendering these sets except perhaps as isosurfaces, a rather unsatisfactory and limited representation. The following will illustrate the application of GPU based raycasting, a now relatively standard approach to volume rendering, to the representation of volumetric fractals. Leveraging existing software that has been designed for general volume visualisation allows the interested 3D fractal explorer to focus on the mathematical generation of the volume data rather than reinventing the entire volume rendering pipeline.
A Numerical Simulation of Nocturnal Drainage Flow

A three-dimensional mesoscale atmospheric model , previously used to simulate airflow over cooling ponds and hypothetical, simplified mountains , has been modified to simulate development of nocturnal drainage flow in realistic terrain, part of the California Geysers area. Turbulent fluxes appearing in the governing equations for mean variables are computed from simplified second-moment turbulence-closure equations where only a turbulence energy equation and a master-length scale equation are solved prognostically. Qualitative simulation of drainage flow, horizontal covergence in the valley, and resulting vertical motions are satisfactory. Simulated wind speeds near the surface are greater than observed values , possibly due to inadequate resolution of observations or to a lack of consideration of the drag associated with canopy flow.
Non-local total variation regularization approach for image restoration under a Poisson degradation

ABSTRACT Poisson noise (also known as shot or photon noise) arises due to the lack of information during the image acquisition phase, it is quite common in the field of microscopic or astronomical imaging applications. In this paper, we propose a non-local total variation regularization framework with a p-norm driven data-fidelity for denoising the Poissonian images. In precise, the energy functional is derived using a Maximum A Posteriori estimator of the Poisson probability density function. The diffusion amounts to a non-local total variation minimization process, which eventually preserves fine structures while denoising the data. The numerical solution is sought under a fast converging split-Bregman iterative scheme. The proposed model is compared visually and statistically with the state-of-the-art Poisson denoising models.
An ALE formulation for compressible flows based on multi-moment finite volume method

ABSTRACT A direct Arbitrary Lagrangian Eulerian (ALE) formulation using multi-moment finite volume method for viscous compressible flows on unstructured moving grids has been developed and presented in this paper. High-order polynomials are reconstructed over a compact mesh stencil by making use of both volume integrated average value (VIA) and point values (PV) at the vertices of mesh cells which change in time. By formulating the governing equation in ALE integral form and differential form, the computational variables, VIA and PV, are updated, respectively, by a finite volume scheme and a point-wise discretization using multi-moments (VIA and PV). A simple and efficient formulation is derived for moving mesh which satisfies the geometrical conservation law. In the computations involving moving-body, the PVs of velocity at the vertices of cells adjacent to the body surface are coincided with the motion of the body, which eliminates the numerical approximation to find the cell boundary values on the body surface in conventional finite volume method. Numerical tests are presented to verify the present method as a high-order ALE formulation for compressible flows on both stationary and moving grids.