Gotowa bibliografia na temat „Modena (Italy). Torre Ghirlandina”

Clinical practice and research are frequently seen as two worlds apart, in psychiatry as in the vast majority of medical specialties. In order to bridge the gap between them, economic founds and grants are required, not always easy to obtain. In this contribution we report the birth of the Association for Research in Psychiatry (ARPSY) and its main activities. ARPSY was born in May 2016 thanks to a research prize assigned to dr. Giorgio Mattei by the eight Rotary Clubs of the Province of Modena, Italy (Rotary Club Modena, Mirandola, Carpi, Sassuolo, Vignola Castelfranco Bazzano, Frignano, Modena L.A. Muratori, Castelvetro di Modena Terra dei Rangoni, that altogether make up the so-called “Ghirlandina Group”). Aim of the association is to promote mental health among students and trainees, mental health professionals, patients and their families, and among the general population by means of fund raising, in order to finance research projects, clinical interventions and educational activities.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Measuring the response of a structure to the ambient and service loads is a source of information that can be used to estimate some important engineering parameters or, to a certain extent, to characterize the structural behavior as a whole. By repeating the data acquisition over a period of time, it is possible to check for variations in the structure’s response, which may be correlated to the appearance or growth of a damage (e.g. following some exceptional event as the earthquake, or as a consequence of materials and components aging). The complexity of some existing structures and their environment very often requires the execution of a monitoring plan in order to support analyses and decisions through the evidence of measured data. If the monitoring is implemented through a sensor network continuously acquiring over time, then the evolution of the structural behavior may be tracked continuously as well. Such approach has become a viable option for practical applications since the last decade, as a consequence of the progress in the data acquisition and storage systems. However, proper methods and algorithms are needed for managing the large amount of data and the extraction of valuable knowledge from it. This article presents a methodology aimed at making automatic the process of structural monitoring in case it is carried continuously over time. It relies on some existing methods from the machine learning and data mining fields, which are casted into a process targeted to delimit the need of the human being intervention to the training phase and the engineering judgment of the results. The methodology has been successfully applied to the real-world case of an ancient masonry bell tower, the Ghirlandina Tower (Modena, Italy), where a network made of 12 accelerometers and 3 thermocouples has been acquiring continuously since August 2012. The structural characterization is performed by identifying the first modes of vibration, whose evolution over time has been tracked.

The monumental complex consisting of the cathedral, tower and main square of Modena (Northern Italy) has been a UNESCO World Heritage Site since 1997. The visible tilting of the Ghirlandina tower has always generated concerns for its preservation, even more after the recent seismic events. This paper highlights the role of structural monitoring for the conservation of the site, with particular reference to the data acquired during the recent Emilia earthquakes. Unexpectedly, the inclination of this leaning tower decreased after the major seismic event. Some considerations are presented regarding the difficulty of modelling this kind of effects on buildings with complex historical stratifications and the application of the observational method, derived from geotechnical engineering, is proposed. The importance of structural monitoring is once again recalled, in order to preserve world heritage and comply with the principle of minimum intervention.