Global and regional sea level variations in the recent past and future: insight from observations and modeling

This work is focused on the analysis of sea–level change (last century), based mainly on instrumental observations. During this period, individual components of sea–level change are investigated, both at global and regional scales. Some of the geophysical processes responsible for current sea-level change such as glacial isostatic adjustments and current melting terrestrial ice sources, have been modeled and compared with observations. A new value of global mean sea level change based of tide gauges observations has been independently assessed in 1.5 mm/year, using corrections for glacial isostatic adjustment obtained with different models as a criterion for the tide gauge selection. The long wavelength spatial variability of the main components of sea–level change has been investigated by means of traditional and new spectral methods. Complex non–linear trends and abrupt sea–level variations shown by tide gauges records have been addressed applying different approaches to regional case studies. The Ensemble Empirical Mode Decomposition technique has been used to analyse tide gauges records from the Adriatic Sea to ascertain the existence of cyclic sea-level variations. An Early Warning approach have been adopted to detect tipping points in sea–level records of North East Pacific and their relationship with oceanic modes. Global sea–level projections to year 2100 have been obtained by a semi-empirical approach based on the artificial neural network method. In addition, a model-based approach has been applied to the case of the Mediterranean Sea, obtaining sea-level projection to year 2050.

Motor control system in Parkinson’s disease: a modeling approach

Parkinson’s disease is a neurodegenerative disorder due to the death of the dopaminergic neurons of the substantia nigra of the basal ganglia. The process that leads to these neural alterations is still unknown. Parkinson’s disease affects most of all the motor sphere, with a wide array of impairment such as bradykinesia, akinesia, tremor, postural instability and singular phenomena such as freezing of gait. Moreover, in the last few years the fact that the degeneration in the basal ganglia circuitry induces not only motor but also cognitive alterations, not necessarily implicating dementia, and that dopamine loss induces also further implications due to dopamine-driven synaptic plasticity got more attention. At the present moment, no neuroprotective treatment is available, and even if dopamine-replacement therapies as well as electrical deep brain stimulation are able to improve the life conditions of the patients, they often present side effects on the long term, and cannot recover the neural loss, which instead continues to advance. In the present thesis both motor and cognitive aspects of Parkinson’s disease and basal ganglia circuitry were investigated, at first focusing on Parkinson’s disease sensory and balance issues by means of a new instrumented method based on inertial sensor to provide further information about postural control and postural strategies used to attain balance, then applying this newly developed approach to assess balance control in mild and severe patients, both ON and OFF levodopa replacement. Given the inability of levodopa to recover balance issues and the new physiological findings than underline the importance in Parkinson’s disease of non-dopaminergic neurotransmitters, it was therefore developed an original computational model focusing on acetylcholine, the most promising neurotransmitter according to physiology, and its role in synaptic plasticity. The rationale of this thesis is that a multidisciplinary approach could gain insight into Parkinson’s disease features still unresolved.