Random sampling provides several benefits for multi-band signals compared to uniform sampling case. These benefits include greater sample frequency flexibility, fewer restrictions on signal filtering, and, in the case of stationary sampling sequences, a decrease or suppression of spectrum aliases. This makes random sampling a preferred option in Software Defined Radio (SDR) systems, which face the challenge of supporting different standards with different sampling frequencies. However, the task of reconstruction becomes more complex with random sampling. In the literature, various reconstruction techniques are provided. In this paper, we focus on employing the ADPW-CG iterative method to address the reconstruction issue with randomly sampled signals within an SDR system context. The effectiveness of the proposed algorithm is evaluated in terms of complexity, reconstructed signal quality, and robustness, and robustness and the findings is compared with the performance of the SVD direct algorithm and other iterative methods. Based on the obtained results, we observed that the proposed approach demonstrates promising performance in comparison to other algorithms.

Interest in self-cleaning coatings is rising due to their potential to enhance comfort and quality of life in polluted urban environments, driving the search for materials with optimal physical properties. Convergent with this goal, this study investigates the wetting properties and photo-catalytic efficiency of reticulated TiO2 layers. It shows that these properties are significantly influenced by the topographical characteristics of the TiO2 surface, which can be precisely controlled through variations in pulverization pressure and low-temperature post-annealing treatments. Post-deposition annealing of the TiO2 layers achieves 100 % self-cleaning efficiency for both thick and thin films, with optical transmission ranging from approximately 60 %-80 % in the visible spectrum. Additionally, the TiO2 layers exhibited promising capabilities for eliminating pathogenic microorganisms and disinfecting surfaces. The underlying causal factors of these remarkable and technologically promising surface features are explored and discussed.