131 research outputs found
Electrophysiological Correlates of Stimulus-driven Reorienting Deficits after Interference with Right Parietal Cortex during a Spatial Attention Task: A TMS-EEG Study
No full textTMS interference over right intraparietal sulcus (IPS) causally disrupts behaviorally and EEG rhythmic correlates of endogenous spatial orienting before visual target presentation [Capotosto, P., Babiloni, C., Romani, G. L., & Corbetta, M. Differential contribution of right and left parietal cortex to the control of spatial attention: A simultaneous EEG-rTMS study. Cerebral Cortex, 22, 446-454, 2012; Capotosto, P., Babiloni, C., Romani, G. L., & Corbetta, M. Fronto-parietal cortex controls spatial attention through modulation of anticipatory alpha rhythms. Journal of Neuroscience, 29, 5863-5872, 2009]. Here we combine data from our previous studies to examine whether right parietal TMS during spatial orienting also impairs stimulus-driven reorienting or the ability to efficiently process unattended stimuli, that is, stimuli outside the current focus of attention. Healthy volunteers (n = 24) performed a Posner spatial cueing task while their EEG activity was being monitored. Repetitive TMS (rTMS) was applied for 150 msec simultaneously to the presentation of a central arrow directing spatial attention to the location of an upcoming visual target. Right IPS-rTMS impaired target detection, especially for stimuli presented at unattended locations; it also caused a modulation of the amplitude of parieto-occipital positive ERPs peaking at about 480 msec (P3) post-target. The P3 significantly decreased for unattended targets and significantly increased for attended targets after right IPS-rTMS as compared with sham stimulation. Similar effects were obtained for left IPS stimulation albeit in a smaller group of volunteers. We conclude that disruption of anticipatory processes in right IPS has prolonged effects that persist during target processing. The P3 decrement may reflect interference with postdecision processes that are part of stimulus-driven reorienting. Right IPS is a node of functional interaction between endogenous spatial orienting and stimulus-driven reorienting processes in human vision
Ricordo di un fondatore: Claudio Dematté a dieci anni dalla scomparsa
No full textA dieci anni dalla scomparsa di Claudio Dematté - fondatore di questa rivista da lui diretta per 16 anni - i suoi collaboratori ricordano la sua figura e il segno che ha lasciato nelle istituzioni, nelle imprese e nelle realtà con cui è entrato in contatto nei suoi diversi ruoli di docente, di intellettuale e di manager
I processi di transizione delle imprese familiari.
No full textMediocredito Lombardo, Studi e Ricerch
A particle filter-based model selection algorithm for fatigue damage identification on aeronautical structures
No full textThe early diagnosis of cracks in aeronautical structures is a fundamental task for the safe system operation and the optimization of maintenance policies, in view of the increasing interest in life extension programs of several high-investment industries. In principle, these tasks could be fulfilled within a condition-based framework, where direct or indirect observations of the degradation evolution are processed, possibly in real time, by proper diagnostic computational tools. In the past, several attempts have been made to build real-time monitoring systems collecting strain signals acquired from sensor networks. However, in real applications, some issues remain unresolved, for example, the large number of observations available to be handled within a unique diagnostic framework, their relationship with the underlying crack size, and their typical large uncertainties. In this paper, we provide a practical solution by innovatively combining a particle filtering-based model identification algorithm with a measurement system exploiting real-time observations of the crack length reconstructed by a committee of artificial neural networks. The artificial neural networks are trained by simulated strain fields generated by a finite element model. The resulting tool allows to perform an automatic, simultaneous, and real-time (a) selection of the model more properly describing the system state evolution, so as to detect the crack propagation onset time, (b) estimation of the model parameters, and (c) estimation of the crack length, within a unique probabilistic framework based on particle filtering. The methodology is demonstrated with reference to a real helicopter panel subject to fatigue and equipped with a fiber Bragg grating sensor network
Real-time prognosis of random loaded structures via Bayesian filtering: A preliminary discussion
No full textParticle filters are effective tools for the monitoring of damage propagation phenomena. However, a common hypothesis of particle filters for damage prognosis is the constant-amplitude fatigue loading affecting the damage growth. This work constitutes a preliminary analysis of the performance of particle filtering in case of random load, relaxing the hypothesis of constant-amplitude fatigue. Two case studies referring to stationary random loads are introduced: the first concerning a narrow-band stress history, while the second focusing on a wide-band stress spectrum. A solution for each case study is provided and validated using numerical simulations of fatigue cracks in a metallic plate
Real- Time sequential monte carlo sampling based on a committee of artificial neural networks for residual lifetime prediction of a component subjected to fatigue crack growth
No full textAbstractMost of the studies available in the literature about sequential Monte-Carlo sampling algorithm assume that a sufficient number of process observations is available, to guarantee the convergence of the algorithm on the target process evolution. This requirement is remotely met if the process of fatigue crack growth is concerned, due to the costs of maintenance procedures, especially within the aeronautical field. A real-time diagnostic system is the enabler of the prognostic health monitoring methodology.This work is about the application of sequential Monte-Carlo sampling to estimate the probabilistic residual lifetime of a monitored structural component, subjected to fatigue crack propagation. A real-time diagnostic unit for crack detection and damage assessment, trained with Finite Element simulations of damage evolution, generates the information as input to the prognostic unit. A crack propagation model provides the knowledge of the residual lifetime prior to the application of fatigue loads. The prognostic unit updates in real-time the probability density functions of the component residual lifetime at each discrete time during fatigue crack evolution. The methodology is preliminarily applied in simulated environment to an aeronautical metallic panel and the overall performance of a fully autonomous prognostic health monitoring system based upon simulated strain measures is evaluated.
Continuous crack growth monitoring and residual life prediction under variable- Amplitude loading conditions
No full textAbstractThe paper deals with the problem of fatigue crack growth under variable-amplitude loading from a lifetime prediction viewpoint. A sequential Monte Carlo technique is employed to monitor crack propagation in presence of several uncertainties related to the material properties, measurement systems and environmental variability. The algorithm is able to estimate the most probable parameters describing crack growth data focusing on the most probable crack growth trajectories and enhancing the prediction of the residual life of the structure. Monte Carlo sampling allows accounting for the variable amplitude loading condition, simulating several crack growth evolutions using different loads and selecting the more appropriate for the actual crack evolution. The outcome of the algorithm that is the residual life prediction is used to appreciate the performances of the method. The end of the paper discusses the application of the method within structural health monitoring systems and lifetime predictor frameworks
Resting-state Modulation of Alpha Rhythms by Interference with Angular Gyrus Activity
No full textThe default mode network is active during restful wakefulness and suppressed during goal-driven behavior. We hypothesize that inhibitory interference with spontaneous ongoing, that is, not task-driven, activity in the angular gyrus (AG), one of the core regions of the default mode network, will enhance the dominant idling EEG alpha rhythms observed in the resting state. Fifteen right-handed healthy adult volunteers underwent to this study. Compared with sham stimulation, magnetic stimulation (1 Hz for 1 min) over both left and right AG, but not over FEF or intraparietal sulcus, core regions of the dorsal attention network, enhanced the dominant alpha power density (8-10 Hz) in occipitoparietal cortex. Furthermore, right AG-rTMS enhanced intrahemispheric alpha coherence (8-10 Hz). These results suggest that AG plays a causal role in the modulation of dominant low-frequency alpha rhythms in the resting-state condition
- …
