A new method based on physical patterns to impute aerobiological datasets.

Limited research has assessed the accuracy of imputation methods in aerobiological datasets. We conducted a simulation study to evaluate, for the first time, the effectiveness of Gappy Singular Value Decomposition (GSVD), a data-driven approach, comparing it with the moving mean interpolation, a statistical approach. Utilizing complete pollen data from two monitoring stations in northeastern Italy for 2022, we randomly generated missing data considering the combination of various proportions (5%, 10%, 25%) and gap lengths (3, 5, 7, 10 days).

A novel data-driven method for the analysis and reconstruction of cardiac cine MRI.

Cardiac cine magnetic resonance imaging (MRI) can be considered the optimal criterion for measuring cardiac function. This imaging technique can provide us with detailed information about cardiac structure, tissue composition and even blood flow, which makes it highly used in medical science. But due to the image time acquisition and several other factors the MRI sequences can easily get corrupted, causing radiologists to misdiagnose 40 million people worldwide each and every single year.

Application and Advances in Radiographic and Novel Technologies Used for Non-Intrusive Object Inspection.

Increase in trading and travelling flows has resulted in the need for non-intrusive object inspection and identification methods. Traditional techniques proved to be effective for decades; however, with the latest advances in technology, the intruder can implement more sophisticated methods to bypass inspection points control techniques. The present study provides an overview of the existing and developing techniques for non-intrusive inspection control, current research trends, and future challenges in the field.

Higher order dynamic mode decomposition: From fluid dynamics to heart disease analysis.

In this work, we study in detail the performance of Higher Order Dynamic Mode Decomposition (HODMD) technique when applied to echocardiography images. HODMD is a data-driven method generally used in fluid dynamics and in the analysis of complex non-linear dynamical systems modeling several complex industrial applications. In this paper we apply HODMD, for the first time to the authors knowledge, for patterns recognition in echocardiography, specifically, echocardiography data taken from several mice, either in healthy conditions or afflicted by different cardiac diseases.