Hyperspectral image (HSI) unmixing is an increasingly studied problem in various areas, including remote sensing. It has been tackled using both physical model-based approaches and more recently machine learning-based ones. In this article, we propose a new HSI algorithm combining model- techniques, based on unrolling approaches, delivering improved performance. Our approach unrolls the alterna...

This paper is a biased review of the primordial black hole (PBH) formation and abundance estimation. We first three-zone model for PBH to help an intuitive understanding process. Then, more accurate analyses, we introduce necessary tools such as cosmological long-wavelength solutions, definition mass compaction function in spherically symmetric spacetime peak theory. Combining all these tools, ...

SUMMARY emPAI Calc is an open-source web application for the estimation of protein abundance. It uses the correlation between the number of identified peptides and protein abundance in mass spectrometry-based proteomic experiments. The program is the first implementation of our previously reported emPAI algorithm; it calculates the emPAI from the protein identification results obtained by datab...

A recent short communication [1] showed that an orthogonal subspace projection (OSP) classifier developed for hyperspectral image classification in [2] was equivalent to a maximum likelihood estimator (MLE) resulting from a standard method of linear unmixing. It further concluded that the MLE subsumed the OSP classifier in spite of a constant difference in their magnitudes. Coincidentally, the ...