High-throughput single-cell analysis is a challenging task. Label-free tomographic phase microscopy is an excellent candidate to perform this task. However, in-line tomography is very difficult to implement in practice because it requires a complex set-up for rotating the sample and examining the cell along several directions. We demonstrate that by exploiting the random rolling of cells while they are flowing along a microfluidic channel, it is possible to obtain in-line phase-contrast tomography, if smart strategies for wavefront analysis are adopted. In fact, surprisingly, a priori knowledge of the three-dimensional position and orientation of rotating cells is no longer needed because this information can be completely retrieved through digital holography wavefront numerical analysis. This approach makes continuous-flow cytotomography suitable for practical operation in real-world, single-cell analysis and with a substantial simplification of the optical system; that is, no mechanical scanning or multi-direction probing is required. A demonstration is given for two completely different classes of biosamples: red blood cells and diatom algae. An accurate characterization of both types of cells is reported, despite their very different nature and material content, thus showing that the proposed method can be extended by adopting two alternate strategies of wavefront analysis to many classes of cells.

Cooperative spectrum sensing techniques are mainly based on two different decision approaches, according to the role of the decision maker: i) in the Combining Decision approach, the decision maker combines the sensing information collected from its cooperators, without participating in the sensing of the monitored band; ii) in the Sensing & Combining Decision approach, the decision maker combines both the sensing information of its cooperators and its own local sensing information. The choice of the decision approach deeply affects the performance of any cooperative spectrum sensing technique. However, the key issue of choosing the decision approach that guarantees the higher detection accuracy independently of the underlying cooperative sensing architecture is still an open problem. For this, in this paper, the criteria for an effective decision-approach selection are analytically derived with the object of maximizing the detection accuracy in presence of realistic channel propagation effects. Specifically, through a theoretical analysis, it is proven that the detection accuracy exhibits a threshold behavior as a function of the adopted decision approach. Closed-form expressions of such a threshold are analytically derived and practical insights for the decision approach choice are provided. Finally, the theoretical analysis is validated through simulations

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