Miracle-dz/UniFAR-FTUs huggingface dataset:
Gravity‐wave drag on two mountains

The generation of linear internal gravity waves by the flow over two idealized mountains, whose summits are aligned in the same direction as the mean wind, is studied. In particular, the sensitivity of the wave drag to the downwind distance between the mountains is examined by using a three-dimensional numerical model based on the linearized steady-state Boussinesq equations of motion. Both two- and three-dimensional orography is considered. When the upstream conditions are such that the wind and buoyancy-frequency do not vary with height, and the mountains are wide enough for non-hydrostatic effects to be unimportant, the model predicts the same drag dependence on two-dimensional ridge spacing as was derived analytically by Grisogono et al. The corresponding three-dimensional numerical result predicted by the model is qualitatively very similar to the two-dimensional result. When the mountains are narrow and the waves are non-hydrostatic the drag dependence on mountain spacing is more complicated; maxima and minima in the drag can occur when the distance between the two mountains is such that waves generated by the mountain furthest upstream are in phase (maxima in the drag), or out of phase (minima in the drag), with the waves generated by the downstream mountain. It is shown that this is an important effect when the waves are trapped by upstream profiles whose wind speed varies with height.
The effect of hydrodynamic interactions on the orientation distribution in a fiber suspension subject to simple shear flow

A single, non‐Brownian fiber suspended in a viscous, Newtonian fluid undergoing simple shear flow rotates in one of a set of closed orbits known as Jeffery orbits. In a fiber suspension, the hydrodynamic interactions among the fibers determine the distribution of fibers among these orbits. The hydrodynamic interactions in dilute and semidilute suspensions have been studied using slender‐body theory. Hydrodynamic, orientational diffusivities were obtained from an ensemble average of the fiber–fiber interactions. The steady‐state fiber orientation distribution is controlled by the anisotropy and orientation dependence of the diffusivities. The steady‐state and transient fiber orientation distributions are derived using a perturbation analysis for weak hydrodynamic orientational diffusion that is an extension of the work of Leal and Hinch [J. Fluid Mech. 46, 685 (1972)] for weak, isotropic, rotary Brownian motion. In the dilute regime, the steady‐state experimental distributions of Anczurowski and Mason [J. .
Effects of ambient turbulence on the decay of a trailing vortex wake

Experiments were conducted to investigate the effects of ambient turbulence on the evolution of a trailing vortex wake. The wake was generated by towing an NACA 0012 wing, with a span of 10.2 cm and a chord of 5.1 cm, at an incidence of —10 deg and a speed of 40 cm/s in a tow tank. The chord Reynolds number was 20,400. The ambient turbulence was generated by towing three grids, with square meshes of 1.45, 10.2, and 20.3 cm, upstream of the wing. Turbulence parameters were measured with crossed hot-film probes. The trailing vortex wake, tagged with a fluorescent dye, was visualized from different perspectives and its decay was derived from 16-mm movie records. For weak turbulence with large integral scales compared with the vortex separation, vortex linking is the dominant mode of instability. The dominant wavelength of the linking decreases with increasing turbulence intensity or dissipation rate. As the turbulence intensity increases, vortex bursting appears and eventually replaces linking as the dominant mode of instability. For turbulence with a small integral scale as compared with the vortex separation, vortex instability is predominantly of the bursting type.
Using numerical weather prediction to assess climate models

Estimates of climate change remain uncertain—hampering strategic decision making in many sectors. In large part this uncertainty arises from uncertainty in the computational representation of known physical processes. This model component of climate change uncertainty is increasingly being assessed using perturbed model experiments. Some such model perturbations have, for example, led to headline global warming estimates of as much as 12 °C. These experiments consider many differently perturbed versions of a given base model and assess the likelihood of each perturbed model's climate prediction based on how well it simulates present‐day climate. In these experiments, the computational cost of the model assessment is extremely high unless one assumes that the climate anomalies associated with different model perturbations can be combined linearly. Here we demonstrate a different method, which harnesses the power of the data assimilation system to assess directly the perturbed physics of a model. Data assimilation involves the incorporation of daily observations to produce initial conditions (analyses) for numerical weather prediction (NWP). The method used here quantifies systematic initial tendencies in the first few time steps of a model forecast. After suitable temporal averaging, these initial tendencies imply systematic imbalances in the physical processes associated with model error. We show how these tendencies can be used to produce probability weightings for each model that could be used in the construction of probability distribution functions of climate change. The approach typically costs 5% of the cost of a 100‐year coupled model simulation that might otherwise be used to assess the simulation of present‐day climate. Importantly, since the approach is amenable to linear analysis, it could further reduce the cost of model assessment by several orders of magnitude: making the exercise computationally feasible. The initial tendency approach can only assess ‘fast physics’ perturbations, i.e. perturbations that have an impact on weather forecasts as well as climate. However, recent publications suggest that most of the present model parameter uncertainty is associated with fast physics. If such a test were adopted, assessment of the ability to simulate present‐day climate would then only be required for models that ‘pass’ the fast physics test. The study highlights the advantages of a more seamless approach to forecasting that combines NWP, climate forecasting, and all scales in‐between. Copyright © 2007 Royal Meteorological Society
Elaboration of a wide range of TiO2 micro/nanostructures by high power impulse inverted cylindrical magnetron sputtering

An inverted cylindrical magnetron sputtering reactor mode was used for TiO2 thin films deposition. The high voltage was delivered to the target in dc mode and in pulsed mode at low frequency (250 Hz) to reach high power impulse magnetron sputtering (HiPIMS) regimes and obtain subsequent higher plasma ionization rates. Time-resolved electrical and optical characterizations of the discharge were performed and the layer's chemistry, morphology and microstructure were characterized using x-ray photoelectron spectroscopy, scanning electron microscopy, atomic force microscopy, x-ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) analysis. In accordance to the conclusions described in the literature for TiO2 HiPIMS deposition in planar configuration, it is shown that the increase of peak target current (induced by the decrease of the duty cycle at constant average power) leads to smoothening and densification of the layers. The microstructure of the coatings is also strongly influenced by the energy and the flux of the incoming species to the substrate. XRD experiments show that passing from dc to HiPIMS mode leads to a transition from anatase to rutile formation, but HRTEM analyses allows one to highlight that the proportion of amorphous domains is also increased when increasing the energy delivered to the growing film. It results in the obtaining of layers with globular structure composed of rutile nano-crystallites embedded in an amorphous matrix.
Non-stationary magnetoencephalography by Bayesian filtering of dipole models

In this paper, we consider the biomagnetic inverse problem of estimating a time-varying source current from magnetic field measurements. It is assumed that the data are severely corrupted by measurement noise. This setting is a model for magnetoencephalography (MEG) when the dynamic nature of the source prevents us from effecting noise reduction by averaging over consecutive measurements. Thus, the potential applications of this approach include the single trial estimation of the brain activity, in particular from the spontaneous MEG data. Our approach is based on non-stationary Bayesian estimation, and we propose the use of particle filters. The source model in this work is either a single dipole or multiple dipole model. Part of the problem consists of the model determination. Numerical simulations are presented.
Can galaxies oscillate? A self-consistent model of a non-stationary stellar system

Construction d'un modele simple decrivant un systeme stellaire verifiant le theoreme de Jeans et capable eventuellement de generer des oscillations spheriques non amorties. Les resultats obtenus indiquent qu'en principe, des solutions non lineaires dependantes du temps pour les equations de Poisson et de Boltzmann sans collisions sont possibles mais qu'il est difficile de mettre en place des oscillations spheriques dans le systeme simple etudie ici
SOLVABLE AFFINE TERM STRUCTURE MODELS

An Affine Term Structure Model (ATSM) is said to be solvable if the pricing problem has an explicit solution, i.e., the corresponding Riccati ordinary differential equations have a regular globally integrable flow. We identify the parametric restrictions which are necessary and sufficient for an ATSM with continuous paths, to be solvable in a state space , where , the domain of positive factors, has the geometry of a symmetric cone. This class of state spaces includes as special cases those introduced by Duffie and Kan (1996) , and Wishart term structure processes discussed by Gourieroux and Sufana (2003) . For all solvable models we provide the procedure to find the explicit solution of the Riccati ODE.
Direct simulation of particle dispersion in a decaying isotropic turbulence

Dispersion of solid particles in decaying isotropic turbulence is studied numerically. The three-dimensional, time-dependent velocity field of a homogeneous, non-stationary turbulence was computed using the method of direct numerical simulation (DNS). A numerical grid containing 963 points was sufficient to resolve the turbulent motion at the Kolmogorov lengthscale for a range of microscale Reynolds numbers starting from Rλ = 25 and decaying to Rλ = 16. The dispersion characteristics of three different solid particles (corn, copper and glass) injected in the flow, were obtained by integrating the complete equation of particle motion along the instantaneous trajectories of 223 particles for each particle type, and then performing ensemble averaging. The three different particles are those used by Snyder & Lumley (1971), referred to throughout the paper as SL, in their pioneering wind-tunnel experiment. Good agreement was achieved between our DNS results and the measured time development of the mean-square displacement of the particles. The simulation results also include the time development of the mean-square relative velocity of the particles, the Lagrangian velocity autocorrelation and the turbulent diffusivity of the particles and fluid points. The Lagrangian velocity frequency spectra of the particles and their surrounding fluid, as well as the time development of all the forces acting on one particle are also presented. In order to distinguish between the effects of inertia and gravity on the dispersion statistics we compare the results of simulations made with and without the buoyancy force included in the particle motion equation. A summary of the significant results is provided in §7 of the paper. The main objective of the paper is to enhance the understanding of the physics of particle dispersion in a simple turbulent flow by examining the simulation results described above and answering the questions of how and why the dispersion statistics of a solid particle differ from those of its corresponding fluid point and surrounding fluid and what influences inertia and gravity have on these statistics.
Contributions from gallium vacancies and carbon-related defects to the “yellow luminescence” in GaN

Carbon-doped GaN layers grown by molecular-beam epitaxy are studied with photoluminescence and positron annihilation spectroscopy. Semi-insulating layers doped with >1018 cm−3 carbon show a strong luminescence band centered at ∼2.2 eV (yellow luminescence). The absolute intensity of the 2.2 eV band is compared with the gallium vacancy concentration determined by positron annihilation spectroscopy. The results indicate that a high concentration of gallium vacancies is not necessary for yellow luminescence and that there is in fact a causal relationship between carbon and the 2.2 eV band. Markedly different deep-level ionization energies are found for the high-temperature quenching of the 2.2 eV photoluminescence in carbon-doped and reference samples. We propose that while the model of Neugebauer and Van de Walle [Appl. Phys. Lett. 69, 503 (1996)] applies for GaN of low carbon concentration, a different yellow luminescence mechanism is involved when the interstitial carbon concentration is comparable to or .
Multi scale detail-preserving denoising method of infrared image via relative total variation

How to remove the noise in infrared image effectively with detail preserving is a significant but difficult problem in infrared image processing. Various methods have been proposed to obtain good results. However, these algorithms usually cannot distinguish noise and detail efficiently, which leads to smoothing some details in infrared images. Recently a novel local measure called relative total variation (RTV) is proposed to accomplish effective texture removal. RTV measure is combined with a general windowed total variation measure and a novel inherent variation measure to smooth the image texture effectively while preserving the main structure. In this paper, using detail preserving smoothing method via RTV, a multi scale denoising algorithm for infrared image is proposed. Firstly, the infrared image is decomposed into several scales by non-subsampled Contourlet transform (NSCT). NSCT decomposition does not do any down sampling or up sampling, thus the results are not band limited. Secondly，the algorithm applies RTV based detail preserving denoising method for each decomposed layers. Different smoothing parameters are respectively used to adjust the denoising levels in different scales. Finally, various synthetic weights are utilized to different layers to reconstruct the final infrared denosing results. Compared with other infrared denoising approaches, the quantitative comparisons demonstrate that the proposed method could well suppress the noise of infrared image while preserving the edge details effectively. Both visual quality and objective measure results show that this method is efficient and has a good application in infrared image denoising.
Conditional Inapproximability and Limited Independence

Understanding the theoretical limitations of efficient computation is one of the most fundamental open problems of modern mathematics. This thesis studies the approximability of intractable optimization problems. In particular, we study so-called Max CSP problems. These are problems in which we are given a set of constraints, each constraint acting on some k variables, and are asked to find an assignment to the variables satisfyingas many of the constraints as possible. A predicate P : [q]ᵏ → {0, 1} is said to be approximation resistant if it is intractable to approximate the corresponding CSP problem to within a factor which is better than what is expected from a completely random assignment to the variables. We prove that if the Unique Games Conjecture is true, then a sufficient condition for a predicate P :[q]ᵏ → {0, 1} to be approximation resistant is that there exists a pairwise independent distribution over [q]ᵏ which is supported on the set of satisfying assignments Pˉ¹(1) of P. We also study predicates P : {0, 1}² → {0, 1} on two boolean variables. The corresponding CSP problems include fundamental computational problems such as Max Cut and Max 2-Sat. For any P, we give an algorithm and a Unique Games-based hardness result. Under a certain geometric conjecture, the ratios of these two results are shown to match exactly. In addition, this result explains why additional constraints beyond the standard “triangle inequalities” do not appear to help when solving these problems. Furthermore,we are able to use the generic hardness result to obtain improved hardness for the special cases of Max 2-Sat and Max 2-And. For Max 2-Sat, we obtain a hardness of αLLZ + e ≈ 0.94016, where αLLZ is the approximation ratio of the algorithm due to Lewin, Livnat and Zwick. For Max 2-And, we obtain a hardness of 0.87435. For both of these problems, our results surprisingly demonstrate that the special case of balanced instances (instances where every variable occurs positively and negatively equally often) is not the hardest. Furthermore, the result for Max 2-And also shows that Max Cut is not the hardest 2-CSP. Motivated by the result for k-CSP problems, and their fundamental importance in computer science in general, we then study t-wise independent distributions with random support. We prove that, with high probability, poly(q) ・ n² random points in [q]ⁿ can support a pairwise independent distribution. Then, again with high probability, we show that (poly(q) ・n)ᵗ log(nᵗ) random points in [q]ⁿ can support a t-wise independent distribution. For constant t and q, we show that Ω(nᵗ) random points are necessary in order to be able to support a t-wise independent balanced distribution with non-negligible probability. Also, we show that every subset of [q]ⁿ with size at least qⁿ(1−poly(q)ˉᵗ) can support a t-wise independent distribution. Finally, we prove a certain noise correlation bound for low-degree functions with small Fourier coefficients. This type of result is generally useful in hardness of approximation, derandomization, and additive combinatorics.
Relative Importance of Performance Factors in Winning NBA Games in Regular Season versus Playoffs

In the National Basketball Association (NBA), there are high expectations for the post-season among the teams having the league's best regular season records. However, not every team who plays great basketball in the regular season will succeed in the playoffs. The Phoenix Suns, for example, had the third best regular season record from the 200405 through 200607 seasons; however, not once did they reach the NBA Finals during those years. We hypothesized that how teams win games in the NBA differs between the regular season and the playoffs. This paper discusses the relative importance of performance factors in winning basketball games in the past 10 years of the NBA (between the 19992000 and 20082009 seasons). Specifically, we examined the contributions of overall efficiency (offensive and defensive ratings), along with the Four Factors (effective field goal percentage, turnover percentage, rebound percentage, and free throw rate) to winning games in the regular season and the playoffs, using a multiple linear regression and a logistic regression analysis. The results of these analyses indicate that efficient offense and defense are both essential to be successful in the regular season and the playoffs, but the importance of defense in winning games may be greater in the playoffs than in the regular season. Shooting efficiency on both ends of the floor (offensive and defensive effective field goal percentages) seems to be the most critical aspect of the game in the regular season as well as the playoffs. In addition, committing fewer turnovers could be another key to winning games, especially in the regular season. It appears that defense becomes more important for winning playoff series as a team advances further in the post-season. Lastly, rebounding may play a significant role in deciding the outcome of the Conference Finals where two teams most likely have similar shooting efficiency and turnover rates.
The structure and stability of vortex rings

A series of observations on experimentally produced vortex rings is described. The flow field, ring velocity and growth rate were observed using dye and hydrogen-bubble techniques. It was found that stable rings are formed and grow in such a way that most of their vorticity is distributed throughout a fluid volume which is larger than and moving with the visible dye core. As the vorticity diffuses out of this moving body of fluid into the outer irrotational fluid, it has two effects. It causes some of the fluid, with newly acquired vorticity, to be entrained into the interior of the bubble, while the rest is left behind and accounts for the appearance of ring vorticity in a wake. It was found that the velocity of translation U of these stable rings varies as t−1, at high Reynolds number, where t is the time measured from the start of the motion at a virtual origin at downstream infinity. A simple theoretical model is presented which explains all of these features of the observed stable flow. Rings of even higher Reynolds number become unstable and shed significantly more vorticity into the wake. Under some circumstances a new more stable vortex emerges from this shedding process and continues with less vorticity than before. Eventually, the ring motion ceases as all of its vorticity is deposited into the wake and is spread by viscous diffusion. Observations of the interaction between two nearly identical rings travelling a common path showed that, contrary to popular belief, rings do not pass back and forth through one another, but that the rearward one becomes entrained into the forward one. Only when the rearward ring has a much higher velocity than its partner can it emerge from the joining process and leave a slower-moving ring behind.
A fast reduced-rank interpolation method for prestack seismic volumes that depend on four spatial dimensions

Rank reduction strategies can be employed to attenuate noise and for prestack seismic data regularization. We present a fast version of Cadzow reduced-rank reconstruction method. Cadzow reconstruction is implemented by embedding 4D spatial data into a level-four block Toeplitz matrix. Rank reduction of this matrix via the Lanczos bidiagonalization algorithm is used to recover missing observations and to attenuate random noise. The computational cost of the Lanczos bidiagonalization is dominated by the cost of multiplying a level-four block Toeplitz matrix by a vector. This is efficiently implemented via the 4D fast Fourier transform. The proposed algorithm significantly decreases the computational cost of rank-reduction methods for multidimensional seismic data denoising and reconstruction. Synthetic and field prestack data examples are used to examine the effectiveness of the proposed method.
Assimilation of SEVIRI infrared radiances with HIRLAM 4D‐Var

Four‐dimensional variational data assimilation (4D‐Var) systems are ideally suited to obtain the best possible initial model state by utilizing information about the dynamical evolution of the atmospheric state from observations, such as satellite measurements, distributed over a certain period of time. In recent years, 4D‐Var systems have been developed for several global and limited‐area models. At the same time, spatially and temporally highly resolved satellite observations, as for example performed by the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board the Meteosat Second Generation satellites, have become available.