Miracle-dz/UniFAR-FTUs huggingface dataset:
A depth-averaged mu(I)-rheology for shallow granular free-surface flows

The µ(I)-rheology is a nonlinear viscous law, with a strain-rate invariant and pressure-dependent viscosity, that has proved to be effective at model ling dry granular flows in the intermediate range o f the inertial number, I. This paper shows how to inc orporate the rheology into depth-averaged granular avalanche models. To leading order, the rh eology generates an effective basal friction, which is equivalent to a rough bed friction law. A depth-averaged viscous-like term can be derived by integrating the in-plane deviatoric stress throu gh the avalanche depth, using pressure and velocity profiles from a steady-uniform solution to the full µ(I)-rheology. The resulting viscosity is proportional to the thickness to the three halves p ower, with a coefficient of proportionality that is angle dependent. When substituted into the depth-av eraged momentum balance this term generates second-order derivatives of the depth-averaged velo city, which are multiplied by a small parameter. Its inclusion therefore represents a singular pertu rbation to the equations. It is shown that a granul ar front propagating down a rough inclined plane is co mpletely unaffected by the rheology, but, discontinuities, which naturally develop in invisci d roll-wave solutions, are smoothed out. By comparison with existing experimental data, it is s hown that the depth-averaged µ(I)-rheology accurately predicts the growth rate of spatial inst abilities to steady-uniform flow, as well as the dependence of the cut-off frequency on the Froude n umber and inclination angle. This provides strong evidence that, in the steady-uniform flow re gime, the predicted decrease in the viscosity with increasing slope is correct. Outside the range of a ngles where steady-uniform flows develop, the viscosity becomes negative, which implies that the equations are ill-posed. This is a signature of the ill-posedness of the full µ(I)-rheology at both hig h and low inertial numbers. The depth-averaged µ(I)-rheology therefore cannot be used outside the valid range of angles without additional regularization.
The Impact of Model Misspecification on Parameter Estimation and Item‐Fit Assessment in Log‐Linear Diagnostic Classification Models

Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3 vs. 5), and items (25 vs. 50) as well as different attribute correlations (.50 vs. .80) and marginal attribute difficulties (equal vs. different). We investigated misspecifications of interaction effect parameters under correct Q-matrix specification and two types of Q-matrix misspecification. While the misspecification of interaction effects had little impact on classification accuracy, invalid Q-matrix specifications led to notably decreased classification accuracy. Two proposed item-fit indexes were more strongly sensitive to overspecification of Q-matrix entries for items than to underspecification. Information-based fit indexes AIC and BIC were sensitive to both over- and underspecification.
Likelihood-free inference and approximate Bayesian computation for stochastic modelling

With increasing model complexity, sampling from the posterior distribution in a Bayesian context becomes challenging. The reason might be that the likelihood function is analytically unavailable or computationally costly to evaluate. In this thesis a fairly new scheme called approximate Bayesian computation is studied which, through simulations from the likelihood function, approximately simulates from the posterior. This is done mainly in a likelihood-free Markov chain Monte Carlo framework and several issues concerning the performance are addressed. Semi-automatic ABC, producing near-sucient summary statistics, is applied to a hidden Markov model and the same scheme is then used, together with a varying bandwidth, to make inference on a real data study under a stochastic Lotka-Volterra model.
Development of a superconducting joint between a GdBa2Cu3O7-δ-coated conductor and YBa2Cu3O7−δ bulk: towards a superconducting joint between RE (Rare Earth) Ba2Cu3O7−δ-coated conductors

We have started to develop a superconducting bridge joint between two GdBa2Cu3O7−δ (Gd123)-coated conductors, where both conductors are placed in an end-to-end arrangement on the surface of a melt-textured YBCO (including Y2BaCuO5 and YBa2Cu3O7−δ) bulk, which acts as a superconducting medium between the coated conductors. As a first step in the development, one half of the bridge joint assembly was modeled and investigated. Experimental results achieved are as follows: (a) the higher-melting-temperature textured Gd123-coated conductor acts as a seed for the melt texture of the YBa2Cu3O7−δ (Y123) bulk, and (b) the superconducting phase continues across the Y123/Gd123 boundary. The critical current of the joint model is 10 A, which is about 10% of the original Gd123-coated conductor, at 77 K in a self-magnetic field. These results are considered to be extensible to the superconducting bridge joint between the Gd123-coated conductors.
Experimental study of the effect of nitrogen on titanium-arc cathode erosion

Experimental data on the dependence of titanium erosion rate on cathode temperature, Ar, and N/sub 2/ pressure from vacuum to 1 torr and arc motion are presented. Erosion rate is found to decrease with conditions that promote cathode poisoning/contamination. Higher cathode temperatures result in enhanced nitriding (poisoning), leading to a reduced erosion rate. A critical nitrogen pressure (0.001 torr) exists where a sharp drop in erosion is measured. Steered arcs show lower erosion rate values of 38 and 15 /spl mu/g/C for argon and nitrogen, when compared to random arc values of 45 and 35 /spl mu/g/C. Erosion rate studies on TiN-coated cathodes show a low value of around 22 /spl mu/g/C.
First observations of H2O and CO2 vapor in comet 67P/Churyumov-Gerasimenko made by VIRTIS onboard Rosetta

Context. Outgassing from cometary nuclei involves complex surface and subsurface processes that need to be understood to investigate the composition of cometary ices from coma observations. Aims. We investigate the production of water, carbon dioxide, and carbon monoxide from the nucleus of comet 67P/Churyumov-Gerasimenko (67P). These species have different volatility and are key species of cometary ices. Methods. Using the high spectral-resolution channel of the Visible InfraRed Thermal Imaging Spectrometer (VIRTIS-H), we observed the ν3 vibrational bands of H2O and CO2 at 2.67 and 4.27 μm, respectively, from 24 November 2014 to 24 January 2015, when comet 67P was between 2.91 and 2.47 AU from the Sun. Observations were undertaken in limb-viewing geometry at distances from the surface of 0 to 1.5 km and with various line-of-sight (LOS) orientations in the body-fixed frame. A geometry tool was used to characterize the position of the LOS with respect to geomorphologic regions and the illumination properties of these regions. Results. The water production of 67P did not increase much from 2.9 to 2.5 AU. High water column densities are observed for LOS above the neck regions, suggesting they are the most productive in water vapor. While water production is weak in regions with low solar illumination, CO2 is outgassing from both illuminated and non-illuminated regions, which indicates that CO2 sublimates at a depth that is below the diurnal skin depth. The CO2/H2O column density ratio varies from 2 to 60%. For regions that are in sunlight, mean values between 2 and 7% are measured. The lower bound value is likely representative of the CO2/H2O production rate ratio from the neck regions. For carbon monoxide, we derive column density ratios CO/H2O < 1.9% and CO/CO2< 80%. An illumination-driven model, with a uniformly active surface releasing water at a mean rate of 8 × 1025 s-1, provides an overall agreement to VIRTIS-H data, although some mismatches show local surface inhomogeneities in water production. Rotational temperatures of 90–100 K are derived from H2O and CO2 averaged spectra.
PSYCHIATRIC DISTURBANCES ASSOCIATED WITH OPEN-HEART SURGERY

: This study assessed QOL, cognitive profile, and psychiatric symptoms before and after open heart surgery. The prospective study was conducted at the Faisalabad Institute of Cardiology from January 2022 to January 2023. A total of 95 patients were included in the study. All patients underwent neurological and physical evaluations. Every measure was assessed preoperatively and postoperatively. The effects of treatment-related factors and patient-related ones were analyzed. 27 (28%) patients had preoperative anxiety, which decreased to 10 (10.5%) after 1 week of surgery and to 6 (6.3%) after 6 months. 18 (18.9%) patients had preoperative depressive symptoms, which decreased to 7 (7.3%) patients after 1 week of surgery and 6 (6.3%) after 6 months. There was a significant improvement in the mean value of anxiety over the study period (P<.001). Regarding depressive symptoms, there was no significant improvement after 1 week (P<.208). Diabetes mellitus and age were inversely correlated with anxiety and depression; this correlation was statistically significant. Delirium, ischemic time, total bypass time, age, and hypertension were significant predictive factors of cognitive performance. Based on the results, it can be concluded that anxiety and depression adversely impacted the quality of life and were improved gradually over time. Cognitive function declined early after surgery and improved after 6 months.
Influence of added observations on analysis and forecast errors: Results from idealized systems

Recent tests of adding observations to improve individual forecasts have shown a mix of positive, negative, and neutral results. In this study, the influence of added observations on analysis and forecast errors is explored in idealized systems. The primary system studied is a three‐dimensional simulated observing and forecasting system that includes a quasi‐geostrophic forecast model and a three‐dimensional variational data‐assimilation system. In this simulated system, adding observations generally improves analyses and often improves 12‐hour forecasts. Even with perfect observational data and a perfect forecast model, however, there is a non‐negligible risk that adding observations will degrade analyses, and a significant risk that assimilated added observations will degrade forecasts on a time‐scale of one or several days. To illustrate several general principles that help interpret the results, several experiments are performed with low‐dimensional data‐assimilation systems; the results demonstrate that the risk of analysis degradation is inherent in statistical data assimilation. Experiments are also performed with a low‐dimensional forecast model, demonstrating that the risk of forecast degradation is inherent in prediction systems with sensitivity to small errors in initial conditions. Although degradations cannot be avoided, several circumstances are identified in which adding observations is less likely to degrade analyses and forecasts and on average improves analyses and forecasts by a larger amount. Copyright © 2002 Royal Meteorological Society.
Splitting a 4-manifold with infinite cyclic fundamental group, revised in a definite case

A sufficient condition that a closed connected definite 4-manifold with infinite cyclic fundamental group is TOP-split is given. By this condition, it is shown that every closed connected definite smooth 4-manifold with infinite cyclic fundamental group is TOP-split. By combining with an earlier result, it is confirmed that every closed connected oriented smooth 4-manifold with infinite cyclic fundamental group is TOP-split. This also implies that every smooth sphere-knot in a closed simply connected smooth 4-manifold is topologically unknotted if the fundamental group of the complement is infinite cyclic.
A numerical scheme to obtain the RCS of three-dimensional bodies of resonant size using the conjugate gradient method and the fast Fourier transform

A numerical scheme to obtain radar cross section (RCS) of three-dimensional bodies of resonant size (BRS) with arbitrary geometry and material composition is described. The RCS is obtained by solving the electric-field integral equation (EFIE) using the conjugate gradient-fast Fourier transform method (CG-FFT). The choice of a suitable set of basis and testing functions to discretize the EFIE leads to a very accurate and computationaly efficient CG-FFT procedure. This accuracy is checked by comparison with RCS measurements or predictions by other methods. As compared to the moment method, this CG-FFT scheme avoids the storage of large matrices and reduces the computer time by orders of magnitude. >
Adaptive PORT–MVRB estimation: an empirical comparison of two heuristic algorithms

In this article, we deal with an empirical comparison of two data-driven heuristic procedures of estimation of a positive extreme value index (EVI), working thus with heavy right tails. The semi-parametric EVI-estimators under consideration, the so-called peaks over random threshold (PORT)–minimum-variance reduced-bias (MVRB) EVI-estimators, are location and scale-invariant estimators, based on the PORT methodology applied to second-order MVRB EVI-estimators. Trivial adaptations of these algorithms make them work for a similar estimation of other parameters of extreme events, such as the Value-at-Risk at a level p, the expected shortfall and the probability of exceedance of a high level x, among others. Applications to simulated data sets and to real data sets in the field of finance are provided.
Exploiting graph cutsets for sampling-based approximations in bayesian networks

Automated reasoning with graphical models has found many practical applications in domains such as planning, vision, speech recognition, genetic linkage analysis, diagnostics, and many others. Graphical models, combining graph theory and probability theory, facilitate a compact and structured representation for problems with uncertainty and provide a mechanism for answering queries such as computing the probability of an event given observations. Several exact algorithms for reasoning with graphical models exist. However, exact computation is not always possible due to prohibitive time and memory demands. In general, computing exact posterior marginals and even approximating posterior marginals within a desired degree of precision is NP-hard. In practice, we often choose methods that can quickly compute approximate answers to Bayesian queries, trading accuracy for speed. Approximation methods include algorithms for approximate inference, stochastic sampling, network simplifications (simplifying the structure of the underlying graph), and variational approximations. We often obtain a more flexible computation scheme, balancing complexity and accuracy, by combining exact and approximate computation. This dissertation focuses on combining search with existing sampling and bounding methods yielding two new schemes for approximating and bounding posterior marginals in Bayesian networks. Those two new schemes, cutset sampling and any-time bounds, exploit the network structure to bound the complexity of exact computation. Cutset sampling for computing approximate posterior marginals samples only a subset of variables, a cutset of the underlying graph. Since reducing the size of the sampling set results in lower sampling variance, cutset-based sampling converges faster than sampling on a full set of variables. Two variants of cutset sampling algorithm were developed. One, based on Gibbs sampling, is a general approach to collapsed Gibbs sampling in Bayesian networks. The second algorithm implements the likelihood weighting on a cutset. The proposed any-time bounds framework is an any-time scheme for computing bounds on posterior marginals. It enumerates a subset of cutset tuples and performs exact inference over these tuples and then bounds the remaining probability mass. Both methods exploit the problem's underlying network structure to control the time and space complexity of the computations. They focus on finding a cutset of the graph such that the complexity of exact reasoning is bounded when the cutset variables are assigned. The dissertation proposes a new algorithm for finding a minimum cost cutset that yields the specified complexity bound on exact inference.
The aR b relation in the calculation of rain attenuation

Because of its simplicity, the empirical relation A = aR^{b} between the specific attenuation A and the rainrate R is often used in the calculation of rain attenuation statistics. Values for the frequency-dependent parameters a and b are available, however, for only a limited number of frequencies. Some of these values, furthermore, were obtained experimentally, and may contain errors due to limitations in the experimental techniques employed. The aR^{b} relation is shown to be an approximation to a more general relation, except in the low-frequency and optical limits. Because the approximation is a good one, however, a comprehensive and self-consistent set of values for a and b is presented in both tabular and graphical form for the frequency range f = 1-1000 GHz. These values were computed by applying logarithmic regression to Mie scattering calculations. The dropsize distributions of Laws and Parsons, Marshall and Palmer, and Joss et al., were employed to provide calculations applicable to "widespread" and "convective" rain. Empirical equations for some of the curves of a(f) and b(f) are presented for use in systems studies requiring calculations at many frequencies. Some comparison is also made with experimental results, and suggestions are given regarding application of the various calculations.
The concentration of calcium ions and of free electrons in a meteor coma

Prism spectra are studied of eight bright meteors, belonging to different showers and photographed by small cameras in the Gissar observatory of the Institute of Astrophysics, Tajik Academy of Sciences. Monochromatic light curves for the H and K spectral lines of the ionized calcium doublet are constructed and from the ratio of their intensities at selected points along the meteor trajectories the column NCaII and the volume nCaII concentrations of calcium ions are determined. The obtained values NCaII = 10 16 −10 18 cm −2 and nCaII = 10 13 −10 15 cm −3 are in good agreement with the estimates of calcium abundance obtained by other methods and confirm that there is almost full ionization of calcium atoms in meteor comae. The volume concentration of free electrons ne = 4 × 10 13 cm −3 is defined, and the excitation temperature is calculated along the meteor paths.
Second-order in-plane dynamic perturbation of a crack propagating under shear loading

The title problem is solved, for a crack propagating in a slab which is composed of material which can be viscoelastic, “vertically stratified” and transversely isotropic with the axis in the “vertical” direction. The result is illustrated by specialising to the case of a stationary crack in the plane x3 = 0 of an infinite isotropic elastic medium, whose leading edge is at x1 = a cos(kx2), with |k|a ≪ 1.
Low-threshold high quantum efficiency 670 nm GaInP/AlGaInP ridge-waveguide lasers

Low-threshold, low-noise GaInP-AlGaInP visible compressively strained QW laser diodes are of great interest for applications like optical storage systems and low-cost, short-range data transmission via plastic optical fiber. In addition to a stable lateral single mode operation even at high injection currents, these applications require a low temperature dependence of the output parameters. The latter is a major problem in the GaInP-AlGaInP material system, since barrier heights for carriers are restricted. We developed a simple self-aligning ridge-waveguide laser process based on ECR-RIE dry etching with an Ar/CCl/sub 2/F/sub 2/ plasma and an additional wet etching step.
Coffee (Coffea arabica L,var. Castillo) seedling growth in Nariño, Colombia

Coffee is one of the most socioeconomically important crops worldwide. Currently, environmental variations due to climate change are affecting coffee development and growth. Therefore, it is important to evaluate areas that offer a different environment during seedling stage since it is fundamental for successful cultivation. Four municipalities located at different altitudes in the Department of Nariño were selected: La Florida (1879 m a.s.l.), Sandoná (1924 m a.s.l.), Consacá (2001 m a.s.l.), and La Unión (1417 m a.s.l.). The experiment was conducted as a randomized complete block design. Growth variables were measured for five months, including total height-TH, number of leaves-NL, total leaf area-LA, fresh weight-FW, and dry weight-W. The following indices were calculated from the variables recorded: relative growth rate-RGR, leaf area index-LAI, net assimilation rate-NAR, crop growth rate-CGR, leaf area duration-LAD, and leaf area ratio-LAR. The data related to TH, NL, W, and LA recorded during the last evaluation (120 days after being transplanted) showed differences between locations; the maximum values in TH, W and LA were recorded in La Union, while higher averages in NL were obtained in Sandoná. The index values for CGR, LAI, LAR, RGR, and LAD were higher in La Unión, while NAR was higher in La Florida. The results lead to conclude that there are differences in coffee seedling growth depending on the climatic conditions. Accordingly, the highest growth was observed in areas at lower altitudes; therefore, these are recommended for seedling establishment given the higher growth rate, especially that of leaves.
Ambisonic Decoder Test Methodologies based on Loudspeaker Reproduction

The comparative evaluation of the quality of different Ambisonic decoding strategies presents a number of challenges, most notably the lack of a suitable reference signal other than the original, real-world audio scene. In a previous paper, a new test methodology for such evaluations was presented via a listening test conducted using binaural reproduction. In this paper, this methodology is further reﬁned and the results of a new listening test using loudspeaker reproduction over a 7.0. 4 array is presented. The results again indicate some signiﬁcant differences between the decoders for certain attributes.
Skewness Sentiment and Market Anomalies

This study demonstrates that skewness preference of investors is an important driver of various market anomalies. Using a combined measure of mispricing based on 11 prominent anomaly strategies, we show that return predictability associated with the mispricing component of market anomalies is stronger among firms with higher idiosyncratic skewness. The predictability differences are driven by the higher underperformance of high-skewness firms in short anomaly portfolios. Skewness does not affect the performance of long anomaly portfolios. Portfolio holdings data from a retail brokerage firm show that investors with stronger skewness preferences assign relatively larger weights to stocks in short anomaly portfolios. This paper was accepted by Karl Diether, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023. 4898 .