We have measured the temperature-dependent thermal conductivity kappa(T) of individual multiwall boron nitride nanotubes using a microfabricated test fixture that allows direct transmission electron microscopy characterization of the tube being measured. kappa(T) is exceptionally sensitive to isotopic substitution, with a 50% enhancement in kappa(T) resulting for boron nitride nanotubes with 99.5% 11B. For isotopically pure boron nitride nanotubes, kappa rivals that of carbon nanotubes of similar diameter.

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In this work all vibration transitions up to the second overtone of pair SH-molecules in KCI were calculated. The interaction of the identical molecules, which are characterized by "exact" resonance (equal pairs "SH~--"SH~. n = 32,33,34,36) were researched. The unequal molecular ions ~ "inexact" interaction (unequal pairs, "sH·-~ tsH~. 11 # k, n, k = 32,33,34,36) were also considered. In both cases the problem was to find the eigenvalues of the matrix of dipole-dipole interaction that conforms to the solution of a secular equation. The elements of the dipole-{)ipole matrix were calculated in tem1s of the mechanical anharmonicity. It was supposed that the function of the dipole moment has linear dependence on the vibrational coordinate. The conditions of "exact" resonance and the conditions of "inexact" resonance diverged considerably. In the case of the "exact" resonance we used the orthogonal transformation of the dipole-dipole matrix and obtained a precise solution. In case of the "inexact" resonance we used the method of successive diagonalization. The intensities of the pair lines were calculated as well.

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Pavement defect detection and classification systems based on machine learning algorithms are already very advanced and are increasingly demonstrating their outstanding advantages. One of the most important steps in the processing is image segmentation. In this paper, some image segmentation algorithms used in practice are presented, compared and evaluated. The advantages and disadvantages of each algorithm are evaluated and compared based on the criteria PA, MPA, F1. We propose a method to optimize the process of image segmentation of pavement defects using a combination of Markov Random Fields and graph theory. Experiments were conducted on 3 datasets from Portugal, Russia and Vietnam. Empirical results show that the segmentation of pavement defects is more accurate and effective when the two methods are combined.