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Road pavements undergo various environmental factors such as temperature changes, precipitation, and traffic exposure, which can lead to cracks in asphalt pavements compromising road user safety and necessitating costly repairs. To gain a deeper understanding of the mechanisms behind asphalt pavement cracking, this study proposes the utilization of the electrical resistivity tomography method to measure the electrical resistivity of soil-supporting road pavements. Electrical resistivity measurements were conducted on soil-supporting road pavements at various times, both before and during the winter season, in four different road sections. Two of these sections were located on Regional Road N707 in the Ifrane region, while the other two were located on National Road N13 in the Azrou and Timahdite regions. The results of the geophysical campaign provided valuable insights into the impact of the winter season on soil resistance and the formation of cracks in asphalt pavements. To achieve this, electrical tomography was employed to generate 2D images of the electrical resistivity of the soil, which were subsequently compared to asphalt cracking data collected in the field through visual surveys and/or asphalt cores. The 2D analysis of the electrical resistivity images of the road pavements under study revealed a decrease in electrical resistivity values during the winter season. This decrease can be attributed to a combination of factors including asphalt pavement cracking, water infiltration during winter, and soil characteristics supporting the asphalt pavement. These findings offer valuable insights intro targeted maintenance and repair efforts.

Severe combined immunodeficiency (SCID) is the most severe form of primary immunodeficiency (PID), characterized by fatal opportunistic infections. The ADA gene encodes adenosine deaminase, an enzyme that catalyzes the irreversible deamination of adenosine and deoxyadenosine in the catabolic pathway of purine. Mutations of the ADA gene have been identified in patients with severe combined immunodeficiency. In this study, we performed a bioinformatics analysis of the human ADA gene to identify potentially harmful nonsynonymous SNPs and their effect on protein structure and stability. Using eleven prediction tools, we identified 15 nsSNPs (H15D, H15P, H17Q, H17Y, D19N, T26I, G140E, C153F, A183D, G216R, H258Y, C262Y, S291L, S291W, and K34OE) as harmful. The results of ConSurf’s analysis revealed that all these nsSNPs are localised in the highly conserved positions and affect the structure of the native proteins. In addition, our computational analysis showed that the H15D, G140E, G216R, and S291L mutations identified as being associated with severe combined immunodeficiency affect protein structure. Similarly, the results of the analyses of Rmsd, Rmsf, and Rg showed that all these factors influence protein stability, flexibility, and compaction with different levels of impact. This study is the first comprehensive computational analysis of nsSNPs of the ADA gene. However, functional analyses are needed to elucidate the biological mechanisms of these polymorphisms in severe combined immunodeficiency.