1-Meixner Random Vectors

Journal of Theoretical Probability - A definition of d-dimensional n-Meixner random vectors is given first. This definition involves the commutators of their semi-quantum operators. After that we...     

Thermal analysis: an effective characterization method of polyvinyl acetate films applied in corrosion inhibition field

Journal of Thermal Analysis and Calorimetry - To prepare a commercial product with economic and technical relevance, polyvinyl acetate (PVAc) was synthesized, under our laboratory conditions,...     

Accurate,sensitive determination of omega-6 and omega-3 polyunsaturated fatty acids in human plasma,urine samples

Quantitative determination of omega-6 and omega-3 polyunsaturated fatty acids in human plasma and urine with high accuracy and precision provides significant information to monitor the underlying etiology of several diseases. In this regard, liquid chromatography-mass spectrometry is a good choice owing to its great selectivity and sensitivity. Additionally, the hybrid quadrupole–time of flight–mass spectrometer systems provides easy identification of target compounds with superior mass measurements. In this study, an analytical method has been developed for simple, accurate and simultaneous determination of linoleic acid, arachidonic acid, docosahexaenoic acid and eicosapentaenoic acid in a short chromatographic analysis period. The developed method is suitable for the quantitative detection of these four compounds with detection limits ranging between 1.1–3.0 ng ml⁻¹ and its applicability was assessed in human urine and plasma samples. As a result, acceptable accuracy (between 83 and 111%) and good precision (<6%) were obtained for target compounds using matrix matching calibration strategy.     

Thermal conductivity and interfacial energy of solid Bi in the Bi–Ag eutectic system

Journal of Thermal Analysis and Calorimetry - The equilibrated grain boundary groove shapes for solid Bi (Bi–2.87&nbsp;at.%Ag) in equilibrium with Bi–Ag eutectic liquid have been...     

The Landscape of the Spiked Tensor Model

We consider the problem of estimating a large rank-one tensor u ^⊗k ∈ (ℝⁿ)^⊗k , k ≥ 3 , in Gaussian noise. Earlier work characterized a critical signal-to-noise ratio λ  _Bayes = O(1) above which an ideal estimator achieves strictly positive correlation with the unknown vector of interest. Remarkably, no polynomial-time algorithm is known that achieved this goal unless λ ≥ Cn^{(k − 2)/4} , and even powerful semidefinite programming relaxations appear to fail for 1 ≪ λ ≪ n^{(k − 2)/4} . In order to elucidate this behavior, we consider the maximum likelihood estimator, which requires maximizing a degree-k homogeneous polynomial over the unit sphere in n dimensions. We compute the expected number of critical points and local maxima of this objective function and show that it is exponential in the dimensions n , and give exact formulas for the exponential growth rate. We show that (for λ larger than a constant) critical points are either very close to the unknown vector u or are confined in a band of width Θ(λ^{−1/(k − 1)}) around the maximum circle that is orthogonal to u . For local maxima, this band shrinks to be of size Θ(λ^{−1/(k − 2)}) . These “uninformative” local maxima are likely to cause the failure of optimization algorithms. © 2019 Wiley Periodicals, Inc.