Evaluation of a MEMS--based sensing unit for structural health monitoring: results on a medieval tower

Structural health monitoring is a field that relies on different methodologies to develop procedures that characterize the dynamic properties of physical structures to identify possible deteriorations of their behaviors. SHM systems include usually a data acquisition subsystem suitable for recording the structure response to ambient or external excitations. The recorded data are then analyzed in order to characterize the dynamic properties of the considered structure. This paper describes some tests performed by means of a new advanced SHM system, the Teleco SHM602, on a truncated middle-age tower presently included in an ancient palace of the XVI century located in the central part of Bologna. These tests rely on models obtained by means of standard and advanced identification technique

AR+ noise versus AR and ARMA models in SHM-oriented identification

The most common approach in Structural Health Monitoring (SHM) consists in performing accelerometric measures of the response of the monitored structures to natural or artificial stimuli (e.g. wind, urban traffic, seismic events etc.) and in modeling the dynamic behavior of the structure on the basis of these measures. The models can be used, in particular, to extract and compare the main modes i.e. the main resonant frequencies and in comparing these frequencies with those concerning the initial state of integrity of the building. This paper compares the results given by traditional AR and ARMA models with those offered by AR+noise models where an additive observation error is considered and shows that these models can offer some advantages in SHM applications in that describe more accurately the stochastic context of the process. The comparisons have been performed on two different sets of data: the first one has been collected on an industrial building in occasion of an heavy seismic event whereas the second one has been collected on a medieval tower excited by urban traffic

Structural monitoring of a tower by means of MEMS\u2013based sensing and enhanced autoregressive models

Structural Health Monitoring (SHM) methodologies are taking advantage of the development of new families of MEMS sensors and of the available network technologies. Advanced systems rely on intelligent bus-connected sensing units performing locally data filtering, elaboration and model identification. This paper describes a family of enhanced multivariate autoregressive models that can be used in SHM-oriented identification procedures and the implementation of a new advanced SHM system in the tower of the Engineering School of Bologna University. It describes also the results given by the considered procedure and a comparison of the implemented MEMS-based system with a traditional solution based on piezoelectric seismic accelerometers

The Management of Phaeochromocytomas and Paragangliomas in the Era of Precision Medicine: Where Are We Now? Evidence-Based Systemic Treatment Options and Future Cluster Oriented Perspectives

Pheochromocytomas (PCCs) and Paragangliomas (PGLs), commonly known as PPGLs to include both entities, are rare neuroendocrine tumors that may arise in the context of hereditary syndromes or be sporadic. However, even among sporadic PPGLs, identifiable somatic alterations in at least one of the known susceptibility genes can be detected. Therefore, about 3/4 of all PPGL patients can be assigned to one of the three molecular clusters that have been identified in the last years with difference in the underlying pathogenetic mechanisms, biochemical phenotype, metastatic potential, and prognosis. While surgery represents the mainstay of treatment for localized PPGLs, several therapeutic options are available in advanced and/or metastatic setting. However, only few of them hinge upon prospective data and a cluster-oriented approach has not yet been established. In order to render management even more personalized and improve the prognosis of this molecularly complex disease, it is undoubtable that genetic testing for germline mutations as well as genome profiling for somatic mutations, where available, must be improved and become standard practice. This review summarizes the current evidence regarding diagnosis and treatment of PPGLs, supporting the need of a more cluster-specific approach in clinical practice