Miracle-dz/UniFAR-FTUs huggingface dataset:
ON CHANGE POINT DETECTION AND ESTIMATION

In this paper, a survey of the change point detection and estimation will be given. Change point problem primarily arose from the process of quality control in which one is concerned about the output of a production line and wants to find any departure from an acceptable standard of the products. The problem of abrupt changes is often encountered in various experimental and mathematical sciences. From the statistical point of view, we want to infer (detect) whether there is a statistically significant change point in a sequence of chronologically ordered data. In the case there is a COMMUN. STATIST. —SIMULA. , 30(3), 665–697 (2001)
A Note on Osserman Lorentzian Manifolds

Let p be a point of a Lorentzian manifold M. We show that if M is spacelike Osserman at p, then M has constant sectional curvature at p; similarly, if M is timelike Osserman at p, then M has constant sectional curvature at p. The reverse implications are immediate. The timelike case and 4‐dimensional spacelike case were first studied in [3]; we use a different approach to this case. 1991 Mathematics Subject Classification 53B30, 53C50.
Metal Foams: A Design Guide

Introduction Making Metal Foams Characterization Methods Properties of Metal Foams Design Analysis for Material Selection Design Formulae for Simple Structures A Constitutive Model for Metal Foams Design for Creep with Metal Foams Sandwich Structures Energy Management: Packaging and Blast Protection Sound Absorption and Vibration Suppression Thermal Management and Heat Transfer Electrical Properties of Metal Foams Cutting, Finishing and Joining Cost Estimation and Viability Case Studies Suppliers of Metal Foams Web Sites Index .
Investigating Experimental Effects Within the Framework of Structural Equation Modeling: An Example With Effects on Both Error Scores and Reaction Times

Structural equation modeling provides the framework for investigating experimental effects on the basis of variances and covariances in repeated measurements. A special type of confirmatory factor analysis as part of this framework enables the appropriate representation of the experimental effect and the separation of experimental and nonexperimental parts of variance. The constraint of the matrix of loadings is essential for the representation of the effect. Appropriate constraints of loadings are achievable with the aid of the polynomial function. The representation can even bear on several response modes. The usefulness of this method is demonstrated in data obtained by an experimental task with 3 treatment levels with respect to reaction times and error scores. A model with latent variables representing constancy and increase in reaction times and one latent variable representing increase in error scores serves best in these data. Both reaction times and error scores show experimental effects.
Comparative Study of Soil Nutrient Status in Three Forest Types of Dharmapuri Forest Circle, Tamil Nadu, South India

Indian forests are very diverse based on the rainfall, soil, topography and climatic factors. The interaction between forest vegetation and site factors decides the type, pattern and distribution across ecozones. Variable temperature and moisture differences generated from elevation and aspect gradients may have some effect on organic matter decomposition (Griffiths et al., 2009). The soil and vegetation have a complex interrelation since they develop together over a long period of time. The presence of essential soil nutrients will provides the best information towards nutrient cycling and biochemical cycle in the soil plant ecosystem (Gairola et al., 2012). An adequate knowledge of various forest soils and the complex relationship between the life of various trees and other plants of the forest is highly essential to understand the soil plant relationship. International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 8 Number 02 (2019) Journal homepage: http://www.ijcmas. com
Hygro‐thermo‐chemo‐mechanical modelling of concrete at early ages and beyond. Part I: hydration and hygro‐thermal phenomena

Part 1 of the paper presents a new numerical model of hygro‐thermal and hydration phenomena in concrete at early ages and beyond. This is a solidification‐type model where all changes of material properties are expressed as functions of hydration degree, and neither as maturity nor as equivalent hydration period as in maturity‐type models. A mechanistic approach has been used to obtain the governing equations, by means of an averaging theory of Hassanizadeh and Gray, also called hybrid mixture theory. The developments start at the micro‐scale and balance equations for phases and interfaces are introduced at this level and then averaged for obtaining macroscopic balance equations. Constitutive laws are directly introduced at macroscopic level. The final equations, mass (water species and dry air), energy and momentum balance equations, have been written in terms of the chosen primary variables: gas pressure, capillary pressure, temperature and displacements. An evolution equation for the internal variable, hydration degree, describes hydration rate as a function of chemical affinity, considering in addition to the existing models, an effect of the relative humidity on the process. The model takes into account full coupling between hygral, thermal and chemical phenomena, as well as changes of concrete properties caused by hydration process, i.e. porosity, density, permeability, and strength properties. Phase changes and chemical phenomena, as well as the related heat and mass sources are considered. Two examples showing possibilities of the model for analysis of autogenous self‐heating and self‐desiccation phenomena, as well as influence of the ambient relative humidity and the concrete element dimensions upon hygro‐thermal performance and shrinkage of the elements, are presented and discussed. Copyright © 2006 John Wiley & Sons, Ltd.
Low-frequency dynamics of shock-induced separation in a compression ramp interaction

The low-frequency dynamics of the shock-induced separation region in a Mach 2 compression ramp interaction is investigated by performing high-speed particle image velocimetry (HSPIV) measurements, at a rate of 6kHz, in a streamwise–spanwise plane. The HSPIV measurements made in the upstream turbulent boundary layer indicate the presence of spanwise strips of elongated regions of uniform streamwise velocity that extend to lengths greater than 30δ, validating previous results based on planar laser scattering measurements obtained by Ganapathisubramani, Clemens & Dolling (J. Fluid Mech., vol. 585, 2007, p. 369). At a wall normal-location of y/δ=0.2, a surrogate for separation based on a velocity threshold is found to fluctuate over a streamwise range of ±1. 2δ, consistent with previous studies. The amplitude of unsteadiness has contributions from at least two sources that are related to the incoming boundary layer. First, the velocity threshold based surrogate separation line exhibits large-scale undulations along the spanwise direction that conform to the passage of elongated low- and high-speed regions in the upstream boundary layer. This motion is classified as the local influence of the upstream boundary layer. Second, the spanwise-averaged surrogate separation is found to respond to the overall change in streamwise velocity in the incoming boundary layer and is classified as the global influence of the upstream boundary layer. However, this global influence includes the contributions from the elongated low- and high-speed regions. Preliminary findings based on statistical analysis suggest that the local influence contributes nearly 50% more than the global influence. Regardless, the low-frequency unsteadiness of the separation-region can be attributed to the local and global influences of the incoming boundary layer.
Bayesian Hierarchical Model Uncertainty Quantification for Future Hydroclimate Projections in Southern Hills-Gulf Region, USA

The study investigates the hierarchical uncertainty of multi-ensemble hydroclimate projections for the Southern Hills-Gulf region, USA, considering emission pathways and a global climate model (GCM) as two main sources of uncertainty. Forty projections of downscaled daily air temperature and precipitation from 2010 to 2099 under four emission pathways and ten CMIP5 GCMs are adopted for hydroclimate modeling via the HELP3 hydrologic model. This study focuses on evapotranspiration (ET), surface runoff, and groundwater recharge projections in this century. Climate projection uncertainty is characterized by the hierarchical Bayesian model averaging (HBMA) method, which segregates emission pathway uncertainty and climate model uncertainty. HBMA is able to derive ensemble means and standard deviations, arising from individual uncertainty sources, for ET, runoff, and recharge. The model results show that future recharge in the Southern Hills-Gulf region is more sensitive to different climate projections and exhibits higher variability than ET and runoff. Overall, ET is likely to increase and runoff is likely to decrease in this century given the current emission path scenarios. Runoff are predicted to have an 18% to 20% decrease and ET is predicted to have around a 3% increase throughout the century. Groundwater recharge is likely to increase in this century with a decreasing trend. Recharge would increase about 13% in the early century and will have only a 3% increase in the late century. All hydrological projections have increasing uncertainty towards the end of the century. The HBMA result suggests that the GCM uncertainty dominates the overall hydrological projection uncertainty in the early century and the mid-century. The emission pathway uncertainty becomes important in the late century.
Measurement Noise and Stratospheric Gravity Wave Characteristics Obtained from GPS Occultation Data

Tsuda and Hocke (2002) reduce the amount of filtering applied to raw radio occultation data in order to increase the vertical resolution of GPS based temperature retrievals in the stratosphere. The authors discuss gravitywave characteristics obtained from these optimised retrievals, including characteristics of vertical wave number spectra for vertical wavelengths below 2 km, and the meridional distribution of potential energies for such short wavelengths. The filtering of raw data is required because real measurements contain noise. In this note, we discuss the role of measurement noise for gravity wave characteristics obtained from dry temperature retrievals of GPS based radio occultation soundings. We show that for realistic noise levels, temperature fluctuations can be safely interpreted as originating from small scale atmospheric waves in the altitude region below 30 km and for wavelengths greater than 2 km, with the detailed limits depending on noise and retrieval characteristics. An optimising procedure as the one applied by Tsuda and Hocke, however, may raise noise related effects to the level of atmospheric waves for short vertical wavelengths. We further show that conclusions for vertical wavelengths less than 2 km, if at all, can only be drawn after taking the actual noise characteristics of the observations and the details of the filter procedures applied in the retrieval into account.
Enhanced backscattering of polarized light from discrete random media : calculations in exactly the backscattering direction

Enhanced backscattering of polarized light by disordered media composed of independently scattering particles of arbitrary size and shape is studied theoretically. Rigorous relations between the cyclical and the ladder parts of the backscattering matrix in exactly the backscattering direction are derived for three commonly used representations of polarization, and the corresponding polarization backscattering enhancement factors are introduced. The ladder part of the Stokes-backscattering matrix is calculated by solving Chandrasekhar’s vector radiative transfer equation [ Radiative Transfer ( Clarendon, London, 1950)]. The general properties of the enhancement factors are studied, and the results of numerical computations are reported for finite and semi-infinite homogeneous slabs composed of spherical and randomly oriented nonspherical particles. It is shown that the enhancement factors depend strongly on the direction of light incidence, the optical thickness of the medium, the true absorption, and the particle size and shape.
Bi-Directional Self-Attention for Vision Transformers

Self-Attention (SA) maps a set of key-value pairs to an output by aggregating information from each pair according to its compatibility with a query. This allows SA to aggregate surrounding context (represented by key-value pairs) around a specific source (e.g. a query). Critically however, this process cannot also refine a source (e.g. a query) based on the surrounding context (e.g. key-value pairs). We address this limitation by inverting the way key-value pairs and queries are processed. We propose Inverse Self-Attention (ISA), which instead maps a query (source) to an output based on its compatibility with a set of key-value pairs (scene). Leveraging the inherent complementary nature of ISA and SA, we further propose Bi-directional Self-Attention (BiSA), an attention layer that couples SA and ISA by convexly combining their outputs. BiSA can be easily adapted into any existing transformer architecture to improve the expressibility of attention layers. We showcase this flexibility by extensively studying the effects of BiSA on CIFAR100 [1], ImageNet1K [2], and ADE20K [3], and extend the Swin Transformer [4] and LeViT [5] with BiSA, and observe substantial improvements.
Practical and Intrinsic Predictability of Severe and Convective Weather at the Mesoscales

AbstractThis study explores both the practical and intrinsic predictability of severe convective weather at the mesoscales using convection-permitting ensemble simulations of a squall line and bow echo event during the Bow Echo and Mesoscale Convective Vortex (MCV) Experiment (BAMEX) on 9–10 June 2003. Although most ensemble members—initialized with realistic initial condition uncertainties smaller than the NCEP Global Forecast System Final Analysis (GFS FNL) using an ensemble Kalman filter—forecast broad areas of severe convection, there is a large variability of forecast performance among different members, highlighting the limit of practical predictability. In general, the best-performing members tend to have a stronger upper-level trough and associated surface low, producing a more conducive environment for strong long-lived squall lines and bow echoes, once triggered. The divergence in development is a combination of a dislocation of the upper-level trough, surface low with corresponding marginal env.
Reducing component estimation for varying coefficient models

The estimation problem for varying coefficient models has been studied by many authors. We consider the problem in the case that the unknown functions admit different degrees of smoothness. In this paper we propose a reducing component local polynomial method to estimate the unknown functions. It is shown that all of our estimators achieve the optimal convergence rates. The asymptotic distributions of our estimators are also derived. The established asymptotic results and the simulation results show that our estimators outperform the the existing two-step estimators when the coefficient functions admit different degrees of smoothness. We also develop methods to speed up the estimation of the model and the selection of the bandwidths.
Factors Influencing Students’ Understanding of Basic Statistical Concepts

This study focused on modelling the influence of teaching practices, students’ attitudes towards statistics, learning practices and perceived ability on students’ understanding in basic statistical concepts using Structural Equation Modelling. A total of 416 students from four Malaysian public tertiary institutions made up the sample for this study. The results showed that students’ perceived ability in statistics has a strong influence on students’ understanding of basic statistical concepts (measured by performance) and students’ attitudes toward statistics. Teaching practices also significantly affect students’ learning practices. This study found that learning practices and teaching practices do not affect students’ attitudes toward statistics and do not lead to an increase in students’ understanding of basic statistical concepts as measured through their test performance.
AI‐based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data‐driven techniques are used extensively for hydrologic time‐series prediction. We created various data‐driven models (DDMs) based on machine learning: long short‐term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow‐coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow‐coverage (S‐C), precipitation (P), maximum temperature (Tmax), and minimum temperature (Tmin), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine‐recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow‐coverage dataset improves the models' prediction accuracies in the snowmelt‐dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high‐volume data processing.
Long-wave equations and direct simulations for the breakup of a viscous fluid thread surrounded by an immiscible viscous fluid

We consider capillary driven breakup of a viscous liquid thread in a second immiscible viscous liquid of infinite extent and arbitrary viscosity. Postulating the existence of long-wave dynamics, we use the slenderness parameter 1 (proportional to the interfacial slope, for example) to construct consistent asymptotic theories using matched asymptotic expansions at arbitrary viscosity ratios. Three canonical models are found, two of which hold for asymptotically small values of the inner to outer viscosity ratio λ∼ 2 and λ∼ 1/ ln(1/ ), respectively, and the third valid for large λ∼ 1/( 2 ln(1/ )). The smallest and largest λ produce appropriate limits of models described in the literature when the inner or outer fluid is air, respectively. The intermediate λ model is found to be ill-posed and a technique is described to regularize it by considering terms arising from the asymptotic forms of the λ∼ 2 model as its scaled viscosity ratio becomes large, and from the asymptotic forms of the λ∼ 1/( 2 ln(1/ )) as its scaled viscosity becomes small. Time-dependent direct numerical simulations based on boundary integral methods are also used to predict the dynamics for a large range of viscosity ratios (0.001 λ 20). Intermediate values of λ indicate that the dynamics is not long-wave, consistent with the asymptotic analysis, but are self-similar in a pinch-off region with order one aspect ratio. Simulations at large and small values of λ produce intricate dynamics near pinching and in particular the formation of necks, threads and bulges. The direct simulations and the asymptotic models valid at λ∼ 2 and λ∼ 1/( 2 ln(1/ )) complement each other and the former confirm the validity of the long-wave assumptions.
Derivations with nilpotent values on Lie ideals

Let R be a ring containing no nonzero nil right ideal and let LU be a Lie ideal of R. If d is a derivation of R so that d(u) is a nilpotent element for each it E U, then d = 0 when R is a prime ring and Uis not commutative. The main result shows that in general, d(I) = 0 for I the ideal R generated by [U-, U] and that R is the subdirect sum of two images so that d induces the zero derivation on one, and the image of U in the other is commutative. This paper continues a line of investigation in the literature concerning derivations having nilpotent values. The first such result, which inspired all those which followed, is due to I. N. Herstein [6] who proved that if R is a prime ring and d is an inner derivation of R satisfying d(x)" = 0 for all x E R and n a fixed integer, then d = 0. This result was extended to arbitrary derivations in semiprime rings in [3]. In [2], the authors considered derivations satisfying d(x) n= 0 for all x E I, an ideal of R, and proved that d(I) = 0 when R has no nil right ideal. Using the general approach in [2], Carini and Giambruno [1] study the situation when d(x)f(X) = 0 for all x E U, a Lie ideal of R. They prove first that d(U) = 0 when R is a prime ring, charR 7& 2, and R contains no nil right ideal, and then obtain the same conclusion when n(x) = n is fixed and R is a 2-torsion free semiprime ring. Our purpose here is to remove both the bound on the indices of nilpotence and the characteristic assumptions on R. We rely on the ideas in [1] to handle the semisimple case, and the methods in [2] to complete the proof in general. Throughout this paper let R denote a ring containing no nonzero nil right ideal, U a Lie ideal of R, Z the center of R, and d a derivation of R. For any nonempty subset A of R, call d nil on A if d(a)n(a) = 0 for each a E A. It is clear that to conclude that d = 0, or that d(U) = 0, when d is nil on U, one must assume that R does not contain a nil ideal I, since otherwise for any y E I, [r,y] = d,(r) E I is nilpotent and so d,, is nil on R. The reason why we must assume that R contains no nil right ideal is given in [2]: If d is nil Received by the editors September 23, 1988 and, in revised form, February 23, 1989. 1980 Alathematics Subject Classification (1985 Revtision). Primary 16A72; Secondary 16A68, 1 6A 1 2 ? 1990 American Mathematical Society 0002-9939/90 $1.00 + $ 25 per page
Convergence estimates of the dynamics of a hyperbolic system with variable coefficients

A damped hyperbolic equation with a dissipative nonlinearity posed in the energy space H01(Ω)×L2(Ω) is considered. The differential operator involved is not the Laplace operator but rather the operator − div(aϵ(x) ∇ ( · )) that has its coefficient depending on a parameter ϵ. We analyze the behavior of the global attractors as the parameter ϵ tends to 0. It is assumed that the coefficient aϵ(x) has a well determined behavior with the parameter, and the idea is to relate the distance of the global attractors with the magnitude aϵ − a0, measured in an appropriate norm. Copyright © 2013 John Wiley & Sons, Ltd.