Nondestructive evaluation of concrete compression strength by means of Artificial Neural Network (ANN)

The evaluation of structural performance of existing concrete buildings, built according to standards and materials quite different to those available today, requires procedures and methods able to cover lack of data about mechanical material properties and reinforcement detailing. To this end detailed inspections and test on materials are required. As a consequence tests on drilled cores are required; on the other end, it is stated that non-destructive testing (NDT) cannot be used as the only mean to get structural information, but can be used in conjunction with destructive testing (DT) by a representative correlation between DT and NDT. The aim of this study is to verify the accuracy of some formulas of correlation available in literature between measured parameters, i.e. rebound index, ultrasonic pulse velocity and compressive strength (SonReb Method). To this end a relevant number of DT and NDT tests has been performed on many school buildings located in Cesena (Italy). The above relationships have been assessed on site correlating NDT results to strength of core drilled in adjacent locations. Nevertheless, concrete compressive strength assessed by means of NDT methods and evaluated with correlation formulas has the advantage of being able to be implemented and used for future applications in a much more simple way than other methods, even if its accuracy is strictly limited to the analysis of concretes having the same characteristics as those used for their calibration. This limitation warranted a search for a different evaluation method for the non-destructive parameters obtained on site. To this aim, the methodology of neural identification of compressive strength is presented. Artificial Neural Network (ANN) suitable for the specific analysis were chosen taking into account the development presented in the literature in this field. The networks were trained and tested in order to detect a more reliable strength identification methodology.

The role of CD8+CCR4+ T-cells in axial spondyloarthritis

Axial spondyloarthritis (AxSpA) is an inflammatory disease affecting the axial skeleton. The infiltrate of T-cells in the structural lesions has been found to contribute to bone remodeling, but consensus relating the functional contribution of different T-cell subsets to pathogenesis has not been reached yet. Aim of the project was to characterize circulating T-cells and their homing markers from axSpA patients in order to identify cellular populations that could migrate to inflamed tissues and be implicated in axSpA. We found an altered proportion of circulating naïve and memory T-cells in axSpA patients, and a skew in favor of CD8+ T-cells expressing the chemokine receptor CCR4. Since CCL17 and CCL22, the two ligands for CCR4, are found to be elevated in the sera of axSpA patients, we investigated in details the role of CD8+CCR4+ T cells in axSpA. Our data showed that circulating CD8+CCR4+ T-cells display an effector memory phenotype and express homing markers for tissues that are target of the disease. Noteworthy, CD8+CCR4+ T cells from axSpA patients were activated, expressed markers of proliferation and acquired a cytotoxic phenotype, as demonstrated by the increased production of granzyme and perforin. CD8+CCR4+ T cells from axSpA patients upregulate the transcription of genes involved in bone mineralization and downregulate genes involved in osteoclast differentiation, indicating their possible involvement in bone remodeling. Furthermore, CD8+CCR4+ T cells stimulated with PMA and ionomycin were able to produce and release TNF and IL-8, two cytokines involved in osteoclastogenesis, indicating that CD8+CCR4+ T-cells after stimulation would be able to promote osteoclasts differentiation and neutrophils recruitment. Taken together our data suggest that CD8+CCR4+ T cells might exert a pathogenic role in axSpA, by releasing mediators of tissue damage, bone remodeling and recruitment of other pro inflammatory cells.