Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect ...

Deconvolution is a quantitative approach that uses the picture as an estimate of the real specimen intensity and conducts the mathematical inverse of the imaging process to generate an improved ...

Abstract: Metasurfaces can alter radar echo characteristics by dynamically modulating the phase of incident electromagnetic waves, thereby degrading radar signal processing performance. Recovering the ...

Electron tomography is used to reveal the structure of cells in three dimensions (3D). The combination with cryogenic fixation provides a snapshot in time of the living state. However, cryotomography ...

Introduction: Primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC) are characterized by ductular reaction, hepatic inflammation, and liver fibrosis. Hepatic cells are ...

It has been well established that the dysfunctional placenta plays an important role in the pathogenesis of preeclampsia (PE), a hypertensive disorder in pregnancy. However, it is not well understood ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein mass spectrometry imaging (MSI) with electrospray-based ambient ionization ...

Abstract: High-resolution and amplitude-preserved imaging is crucial for mapping impedance interfaces and identifying hydrocarbon reservoirs in the subsurface. Although elastic reverse-time migration ...

Deconvolution is the problem of predicting pure signals from signal mixtures. It has wide applications in many areas, from astrophysics, to image processing, to medicine, to transcriptomics. Because ...

Extreme-deconvolution (XD) is a general algorithm to infer a d-dimensional distribution function from a set of heterogeneous, noisy observations or samples. It is fast, flexible, and treats the data's ...