I-V characteristics of polycrystalline Y1-xCaxBa2Cu3O7samples (x=0.025 and 0.20) have been measured at different temperatures and magnetic fields in the range 0.1 T-6.9 T. The scaling behavior has been established for both samples at all magnetic fields. The dynamic exponent z displays some morphology dependence with higher value for small grain size sample Y0.8Ca0.2Ba2Cu3O7. The static exponen...

This study aims to determine the effect of PhET simulation-assisted project-based learning model on students' ability master concept elasticity. The type research used in this was a quasi-experimental design with pre-test and post-test control group design. population were all students class XI IPA at SMAN 1 Wanasaba East Lombok, totaling 142 students. sample taken using purposive sampling, so ...

where the equivalency holds because p(Xi|Hi) is independent of Θt, i.e., Xi = PiHi based on Section 4 of our submission. Here p(Hi|Θt) is a zero-mean Gaussian, with block-wise diagonal covariance matrix Ωi = diag[Tμ, T , · · · , T ], where T is repeated once for each sample from subject i. Note that because the KL divergence term is independent of the hidden variables, we may ignore it for the ...

We report results of glass transition (T(g)) measurements for polymer thin films using atomic force microscopy (AFM). The AFM mode, shear modulation force microscopy (SMFM), involves measuring the temperature-dependent shear force on a tip modulated parallel to the sample surface. Using this method we have measured the surface T(g) of thin (17-500 nm) polymer films and found that T(g) is indepe...

Let X = {X(t), t ∈ [0, T ]} be a second order random process of which n independent realizations are observed on a fixed grid of p time points. Under mild regularity assumptions on the sample paths of X, we show the asymptotic normality of suitable nonparametric estimators of the trend function μ = EX in the space C([0, T ]) as n, p → ∞ and, using Gaussian process theory, we derive approximate ...

Abstract. Let X1, ..., Xn1 be a random sample from a population with mean μ1 and variance σ 2 1 , and Y1, ..., Yn2 be a random sample from another population with mean μ2 and variance σ 2 2 independent of {Xi, 1 ≤ i ≤ n1}. Consider the two sample t-statistic T = X̄−Ȳ −(μ1−μ2) √ s1/n1+s 2 2/n2 . This paper shows that lnP (T ≥ x) ∼ −x2/2 for any x := x(n1, n2) satisfying x → ∞, x = o(n1 + n2) as n...

What population does the sample represent? The answer to this question is of crucial importance when estimating a survivor function in duration studies. As is well-known, in a stationary population, survival data obtained from a cross-sectional sample taken from the population at time t(0) represents not the target density f (t) but its length-biased version proportional to t f (t), for t > 0. ...

We consider properties of determinants of some random symmetric matrices issued from multivariate statistics: Wishart/Laguerre ensemble (sample covariance matrices), Uniform Gram ensemble (sample correlation matrices) and Jacobi ensemble (MANOVA). If n is the size of the sample, r ≤ n the number of variates and Xn,r such a matrix, a generalization of the Bartlett-type theorems gives a decomposi...