Search

This work presents experimental tests of a vehicle localization system. Based on data collected by a Global Positioning System (GPS), an odometer and a gyrometer, to measure respectively vehicle position, vehicle velocity and yaw velocity, an estimation strategy of the vehicle cover distance is designed. A prototype is then realized in order to test the strategy on urban and extra urban circuits in Benevento (Italy). The experiments are conducted on a Lancia Kappa 2.0 vehicle and the prototype is obtained connecting a dSpace MicroAutoBox electronic control unit with a TomTom Navigator, a gyrometer and the vehicle odometer. The experimental results are here analyzed.

Parkinson's disease (PD) is treated by means of deep brain stimulation (DBS), a therapy based on the injection of current on a regular basis into the basal ganglia, a set of small subcortical nervous system nuclei. DBS is effective in relief of motor symptoms and leads to a notable reduction of drug dose. From an engineering viewpoint, it also raises several optimization-related issues, like energy consumption minimization and stimulation effectiveness. How DBS really works, however, is still unknown, even though several hypotheses and experiments have been reported in literature. To shed some light on the function of DBS, we focused in [1] on those brain nuclei involved in the genesis of PD motor symptoms and developed for them conductance-based models to mimic quantitative data from different in vitro experiments. Now, we use such models in a network scheme to reproduce the main existing anatomical connections between and within the basal ganglia and the resulting macroscopic behaviors reported in literature both for normal and Parkinsonian state. The overall model is proposed as a simulatioParkinson's disease (PD) is treated by means of deep brain stimulation (DBS), a therapy based on the injection of current on a regular basis into the basal ganglia, a set of small subcortical nervous system nuclei. DBS is effective in relief of motor symptoms and leads to a notable reduction of drug dose. From an engineering viewpoint, it also raises several optimization-related issues, like energy consumption minimization and stimulation effectiveness. How DBS really works, however, is still unknown, even though several hypotheses and experiments have been reported in literature. To shed some light on the function of DBS, we focused in (S. Santaniello et al., 20007) on those brain nuclei involved in the genesis of PD motor symptoms and developed for them conductance-based models to mimic quantitative data from different in vitro experiments. Now, we use such models in a network scheme to reproduce the main existing anatomical connections between and within the basal ganglia and the resulting macroscopic behaviors reported in literature both for normal and Parkinsonian state. The overall model is proposed as a simulation instrument to better understand the functional mechanisms currently explaining the basal ganglia physiology and the cellular effects of DBS.n instrument to better understand the functional mechanisms currently explaining the basal ganglia physiology and the cellular effects of DBS.

Parkinson's disease (PD) is a neuro-degenerative pathology affecting the basal ganglia, a set of small subcortical nervous system nuclei. It induces a progressive necrosis of dopaminergic (i.e., releasing dopamine, a neurotransmitter) cells and, as a consequence, produces altered information patterns along movement-related ganglia-mediated pathways in the brain, thus inducing motor disorders like tremor at rest and postural instability. While pharmacological and electrical therapies are currently available for PD treatment, the mechanisms according to which such disease operates are still partly unclear, due to the lack of knowledge about the basal ganglia role in motor tasks execution. For that reason, in order to shed some light on the inner dynamics of the basal ganglia and investigate how PD alters their electric patterns, we develop a two-stages modeling study: in the present paper we focus on those nuclei involved in the genesis of PD motor symptoms and, for them, develop a conductance-based electrical model able to mimic quantitative data from different in vitro physiological analyses. Such models show how several highly nonlinear electrical behaviors can stem from the interaction between specific ionic currents as particular parameters change. In (S. Santaniello et al., 2007), then, cellular models are inserted in a network scheme to reproduce the main actual anatomical connections and the resulting macroscopic behaviors reported in literature for normal and Parkinsonian conditions.

Deep brain stimulation (DBS) is an effective electric therapy to treat movement disorders associated with chronical neural diseases like essential tremor, dystonia and Parkinson's disease. In spite of a long clinical experience, the cellular effects of the DBS are still partially unknown because of the lack of information about the target sites. Recent studies, however, have proposed the local field potentials (LFPs) in the targets as a useful tool to study the behavior before and after stimulation [Priori et al., 2006]. Our work investigates the relationship between DBS settings and LFPs in a detailed simulator of the electric activity in the Vim (one of the preferred surgical targets) under tremor conditions. A least-square approach is adopted to identify a functional, input-output ARX model structure for the Vim and evaluate the effects of the stimulation on its electric patterns. Based on it, an adaptive minimum variance control scheme is then proposed to restore the spectral features of the Vim's LFPs to reference values, i.e., as in subjects not affected by movement disorders. Results indicate good performances in tracking the reference spectral features through selective changes in the low (2-7 Hz), α (7-13 Hz) and β (13-35 Hz) ranges.

Human bones recovered from the archaeological site of Pontecagnano (Salerno, Italy) have been studied to reconstruct the diet of an Etrurian population. Two different areas were investigated, named Library and Sant’ Antonio, with a total of 44 tombs containing human skeletal remains, ranging in age from the 8th to the 3rd century B.C. This time span was confirmed by 14C dating obtained using Accelerator Mass Spectrometry (AMS) on one bone sample from each site. Atomic Absorption Spectrometry (AAS) was used to extract information about the concentration of Sr, Zn, Ca elements in the bone inorganic fraction, whilst stable isotope ratio measurements (IRMS) were carried out on bone collagen to obtain the δ13C and δ15N. A reliable technique has been used to extract and separate the inorganic and organic fractions of the bone remains. Both IRMS and AAS results suggest a mixed diet including C3 plant food and herbivore animals, consistent with archaeological indications. #Revised version of a paper presented at ...

The neural spiking activity of the Subthalamic Nucleus (STN) is devoted to modulate movement actuation and correct movement disorders (i.e. tremor at rest, rigidity, akynesia and postural instability) in Parkinson's Disease (PD) patients. Moreover, it has been recently revealed that an opportune electrical stimulation, called Deep Brain Stimulation (DBS), can annihilate, if associated with the most common L-dopa based pharmacological therapies, PD-related motor disorders. Currently, a great effort is made both in Medicine and Engineering for understanding and modeling in details how the STN works, how PD determines its pathological behavior and how DBS restores the correct motor function. The paper presents a nonlinear, stochastic, continuous-state model describing the global electrical behavior of the STN in PD patients: inspired by the fundamental physiologic features of subthalamic cells, a fictitious vector state is introduced to represent the main dynamics. Its numerical parameters and stochastic properties are chosen by fitting experimental data coming from two PD patients during the surgical implantation of stimulation electrodes in the brain.

In automotive powertrain control strategy, engine torque estimators are preferred to expensive sensors for obvious economic reasons. In the literature several works have been presented proposing both instantaneous engine torque and mean engine torque estimators. The first ones are based on complex models and tipically are suitable for diagnosis purposes, while the latter estimate the torque by means of static maps. In this work, a nonlinear torque estimator for a spark ignition engine has been developed. The total torque acting at the engine shaft has been obtained solving a tracking problem by means of an LQ control strategy. The novel idea is to reduce the nonlinear engine model to a second order Taylor approximation, named a nicely nonlinear model. It is then linearized via feedback and an LQ controller is designed. This approach has been tested on Mid-Size real time dSPACE simulator showing excellent results both for performance and for computational load.

The role and task of intellectual Gino Clerics, considered by historians restoration as one of the leaders of the institutional culture of the protection is in the experience of excavation and restoration of the Basilica of Cimitile opportunities for discussion disciplinary very significant. The emphasis, sometimes contradictory or radical attitudes has also led some opinions on clerics that does not really do justice to neither the intellectual nor the historical context in which the Italian Superintendent operated. The test facility, facing a period of about thirty years highlights the different perspectives under which visual Clerics is operating above and in the decade following the Second World War broke out. It appears, in this way the evolution of Italian thought of the restoration, the thought that you will find his explanation consistent with the promulgation of the Charter of Venice.

Guerini studio, Milano

In this paper a combustion model of direct injection diesel engine is proposed to calculate the in-cylinder pressure and a crank-slider mechanism model to calculate instantaneous indicated torque. The crankshaft is modelled as a rigid body. The parameters of both models are identified via non-linear least square optimization algorithm. The data, used for the identification procedure, are purposely obtained through experiments on a diesel turbocharged BMW MD47 1900cc with a dynamic test-bench.