Time-dependent behaviour of reinforced concrete slabs

In this thesis is studied the long-term behaviour of steel reinforced slabs paying particular attention to the effects due to shrinkage and creep. Despite the universal popularity of using this kind of slabs for simply construction floors, the major world codes focus their attention in a design based on the ultimate limit state, restraining the exercise limit state to a simply verification after the design. For Australia, on the contrary, this is not true. In fact, since this country is not subjected to seismic effects, the main concern is related to the long-term behaviour of the structure. Even if there are a lot of studies about long-term effects of shrinkage and creep, up to date, there are not so many studies concerning the behaviour of slabs with a cracked cross section and how shrinkage and creep influence it. For this reason, a series of ten full scale reinforced slabs was prepared and monitored under laboratory conditions to investigate this behaviour. A wide range of situations is studied in order to cover as many cases as possible, as for example the use of a fog room able to reproduce an environment of 100% humidity. The results show how there is a huge difference in terms of deflections between the case of slabs which are subjected to both shrinkage and creep effects soon after the partial cracking of the cross section, and the case of slabs which have already experienced shrinkage effects for several weeks, when the section has not still cracked, and creep effects only after the cracking.

A biophysical model for valence-based navigational learning: the role of D-Serine

Recent experiments have revealed the fundamental importance of neuromodulatory action on activity-dependent synaptic plasticity underlying behavioral learning and spatial memory formation. Neuromodulators affect synaptic plasticity through the modification of the dynamics of receptors on the synaptic membrane. However, chemical substances other than neuromodulators, such as receptors co-agonists, can influence the receptors' dynamics and thus participate in determining plasticity. Here we focus on D-serine, which has been observed to affect the activity thresholds of synaptic plasticity by co-activating NMDA receptors. We use a computational model for spatial value learning with plasticity between two place cell layers. The D-serine release is CB1R mediated and the model reproduces the impairment of spatial memory due to the astrocytic CB1R knockout for a mouse navigating in the Morris water maze. The addition of path-constraining obstacles shows how performance impairment depends on the environment's topology. The model can explain the experimental evidence and produce useful testable predictions to increase our understanding of the complex mechanisms underlying learning.