In this research, we have proposed the central-symmetrical property of image reconstructions from Zernike moments and pseudo-Zernike moments. We conducted the image reconstructions from the odd, even, and complete sets of Zernike moments and pseudo-Zernike moments, and verified the proposed central-symmetrical property. We have concluded that if the original image is centrally symmetrical, the ...

Systematic ab initio structure prediction was applied for the first time to predict low energy surface reconstructions by employing the minima hopping method on the α-boron (111) surface. Novel reconstruction geometries were identified and carefully characterized in terms of structural and electronic properties. Our calculations predict the formation of a planar, monolayer sheet at the surface,...

We may not be able to make you love reading, but advances in plastic and reconstructive surgery will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you the kindness. In this case, more...

The quality of super resolution images obtained by stochastic single-molecule microscopy critically depends on image analysis algorithms. We find that the choice of background estimator is often the most important determinant of reconstruction quality. A variety of techniques have found use, but many have a very narrow range of applicability depending upon the characteristics of the raw data. I...

We introduce open-loop quantum control protocols for characterizing the spectral properties of non-Gaussian noise, applicable to both classical and quantum dephasing environments. By engineering a multidimensional frequency comb via repetition of suitably designed pulse sequences, the desired high-order spectra may be related to observable properties of the qubit probe. We prove that access to ...

The Bayesian approach allows one to combine measurement data with prior knowledge about models of reality to draw inferences about the validity of those models. The posterior probability quantifies the degree of certainty one has about those models. We propose a method to explore the reliability, or uncertainty, of specific features of a Bayesian solution. If one draws an analogy between the ne...

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