Compressive and shear behaviour of masonry panels: experimentation and numerical analysis

The compressive and shear behavior of masonry is here studied both experimental- ly and numerically. An experimental campaign has been carried out on 9 square-shaped one leaf masonry panels, reproducing historical masonry. Tests have been done for evaluating the elastic and shear moduli in both plane directions, with 6 panels rotated by 90 degrees, lead- ing to vertically aligned bed joints, and 3 panels maintained with horizontal bed joints. Com- pressive tests were executed on 6 masonry panels, 3 of them rotated by 90 degrees. Initial shear strength and shear modulus parallel to bed joints are evaluated through shear tests on 9 masonry triplets. Shear tests are performed on 3 rotated panels, applying an horizontal dis- tributed load, without vertical compression. Attention is paid to the service load state: only the initial phase of the tests is studied. Numerical models are proposed for representing actu- al masonry behavior, both discrete [1] and continuous [2,3], standard and micropolar, ob- tained by homogenization procedures [4]. Several numerical analyses are performed for simulating the experimental tests on masonry triplets and panels. The mechanical elastic pa- rameters of both discrete and continuous models are calibrated starting from laboratory data of masonry constituents and then by fitting the results of the initial phases of the experimental tests on masonry specimens

Computational Models of Adult Neurogenesis

Experimental results in recent years have shown that adult neurogenesis is a significant phenomenon in the mammalian brain. Little is known, however, about the functional role played by the generation and destruction of neurons in the context of and adult brain. Here we propose two models where new projection neurons are incorporated. We show that in both models, using incorporation and removal of neurons as a computational tool, it is possible to achieve a higher computational efficiency that in purely static, synapse-learning driven networks. We also discuss the implication for understanding the role of adult neurogenesis in specific brain areas.Comment: To appear Physica A, 7 page

Dynamical and Statistical Criticality in a Model of Neural Tissue

For the nervous system to work at all, a delicate balance of excitation and inhibition must be achieved. However, when such a balance is sought by global strategies, only few modes remain balanced close to instability, and all other modes are strongly stable. Here we present a simple model of neural tissue in which this balance is sought locally by neurons following `anti-Hebbian' behavior: {\sl all} degrees of freedom achieve a close balance of excitation and inhibition and become "critical" in the dynamical sense. At long timescales, the modes of our model oscillate around the instability line, so an extremely complex "breakout" dynamics ensues in which different modes of the system oscillate between prominence and extinction. We show the system develops various anomalous statistical behaviours and hence becomes self-organized critical in the statistical sense