Augmented Reality to Support On-Field Post-Impact Maintenance Operations on Thin Structures

This paper proposes an augmented reality (AR) strategy in which a Lamb waves based impact detection methodology dynamically interacts with a head portable visualization device allowing the inspector to see the estimated impact position (with its uncertainty) and impact energy directly on the plate-like structure. The impact detection methodology uses a network of piezosensors bonded on the structure to be monitored and a signal processing algorithm (the Warped Frequency Transform) able to compensate for dispersion the acquired waveforms. The compensated waveforms yield to a robust estimation of Lamb waves difference in distance of propagation (DDOP), used to feed hyperbolic algorithms for impact location determination, and allow an estimation of the uncertainty of the impact positioning as well as of the impact energy. The outputs of the impact methodology are passed to a visualization technology that yielding their representation in Augmented Reality (AR) is meant to support the inspector during the on-field inspection/diagnosis as well as the maintenance operations. The inspector, in fact, can see interactively in real time the impact data directly on the surface of the structure. To validate the proposed approach, tests on an aluminum plate are presented. Results confirm the feasibility of the method and its exploitability in maintenance practice

Does Consumer Time Preference Affect Label Use?

Diet-related chronic diseases, such as overweight and obesity, are worrisome not only from a medical point of view, but also in terms of monetary expenditures, these health problems are strictly linked to sizeable sanitary costs (Chou et al., 2004; Yaniv et al., 2009; Cawley and Meyerhoefer, 2012; Ruhm, 2012). These costs are mainly due to the purchase of medical care (direct costs), and to the loss of productivity caused by hill-health (indirect costs) (Rosin, 2008). To challenge these problems and improve public health it is of particular importance to study the determinants of food consumption, and understand the best way to effectively address consumers toward healthy eating.To this purpose, one of the most investigated topics in the last decades has been the role of food-related information. Economists have found evidences that food information can exert a positive effect in increasing consumer nutrition knowledge and in promoting healthier consumption. Hence, policy makers have proposed different policy interventions to provide consumers with more, and more detailed, information. These information measures have included the diffusion of dietary guidelines, the promotion of nutritional education programs in the schools, and also specific campaigns to increase public awareness concerning fruit and vegetables consumption or the negative effects of some unhealthy food and drinks.In this context, another and maybe more direct way to provide consumers with food-related information is represented by on-package food labels, which currently constitute the principal tool through which consumers can easily acquire information about food products. The key role of food labels in making individuals able to do more conscious diet choices has been well established by the main findings of the economic literature (Drichoutis et al., 2006; Drichoutis et al., 2008a; Drichoutis et al., 2009; Norgaard and Brunso 2009; Barreiro-Hurlè et al., 2010). Therefore, given the importance of on-packaging information, the EU has recently introduced the EU Regulation No. 1169/2011, published in October 2011, in order to make labels even more effective and boost their utility for consumers. This new low has established some rules concerning mandatory information, nutritional facts and also the graphical standards allowed on food labels in all the EU. Nonetheless, consumers are not always willing to make use of the information reported on labels, and this makes of crucial importance to investigate and understand which factors can be able to discourage consumers in using labels

A sparsity promoting algorithm for time of flight estimation in Guided waves - based SHM

none3siUltrasonic Guided Waves (GW) are employed by many Structural Health Monitoring (SHM) systems. In plate-like components, GW based defect detection and localization is typically achieved through multiple piezoelectric transducers arranged in different array configurations. In active methods, one or more actuators are used to generate GWs and the sensors work as wave detectors. Defects can be detected and localized from the wave scattering that they generate. To increase the precision of localization approaches, it is important to minimize the uncertainty in the estimation of the time of flight (ToF) of the waves scattered by the defect. Such task is complicated by the dispersive and multimodal nature of ultrasonic GW propagation. In this work, we analyse two algorithms to extract the ToF from waveforms acquired with a Scanning Laser Doppler Vibrometer (SLDV). The algorithms outputs are used to feed beamforming procedures to image cracks with various orientations.openL. De Marchi; J. Moll; A. MarzaniL. De Marchi; J. Moll; A. Marzan

Chapter Monitoring online perception of environmental issues on coasts of Sicily

The analysis of big data on human experience (reviews, comments, ratings, etc.) can provide valuable insights to companies and institutions. This pioneer study applied the artificial intelligence proprietary tools of The Data Appeal Company for a different aim: monitoring the online perception of environmental issues on 88 beaches of Sicily. Results proved that it is possible to monitor environmental situation even to sites where there are no other kind of monitoring, using as bases the free and available contents posted by humans online, processed and analyzed by artificial intelligenc

Different amount of training affects body composition and performance in High-Intensity Functional Training participants

The effects of High-Intensity Functional Training (HIFT) on body composition and the relationship of the latter with performance are not well defined. In this work we investigated, by means of Dual-energy X-ray Absorptiometry, the relative proportions of fat-, lean soft tissue-, and mineral mass in CrossFit\uae (CF, a popular mode of HIFT) participants (n = 24; age, 28.2 \ub1 3.39 y; BMI, 25.3 \ub1 2.04 kg/m2) with at least 1 year of CF training experience and weekly amount of training > 10 h/w (n = 13; Higher Training, HT) or < 10 h/w (n = 11; Lower Training, LT) as well as age- matched and BMI-matched physically active controls (CHT, CLT). Performance was assessed in the "Fran" workout. Data were analyzed by one-way or repeated measures ANOVA where needed. Association between variables was assessed with the Pearson's correlation coefficient r. Partial correlation was used where needed. Results showed that HT performed better than LT in the "Fran" (P < 0.001) and they had higher whole-body bone mineral density (P = 0.026) and higher lean soft mass (P = 0.002), and borderline lower percent fat mass (P = 0.050). The main difference between CF participants (HT, LT) and their respective controls (CHT, CLT) was a lower adiposity in the former. In CF participants, performance positively correlated with appendicular lean soft tissue mass (P = 0.030). It can be concluded that, in CF participants, a higher amount of weekly training improves most notably lean body mass and increases performance in association with increased skeletal muscle mass. CF participation is especially effective in reducing fat mass vs. age- and BMI-matched physically active controls

The effects of MgO, Na2O and SO3 on industrial clinkering process: phase composition, polymorphism, microstructure and hydration, using a multidisciplinary approach

Preprint publicado en: Materials Characterization Volume 155, September 2019, 109809The present investigation deals with how minor elements (their oxides: MgO, Na2O and SO3) in industrial kiln feeds affect (i) chemical reactions upon clinkering, (ii) resulting phase composition and microstructure of clinker, (iii) hydration process during cement production. Our results show that all these points are remarkably sensitive to the combination and interference effects between the minor chemical species mentioned above. Upon clinkering, all the industrial raw meals here used exhibit the same formation temperature and amount of liquid phase. Minor elements are preferentially hosted by secondary phases, such as periclase. Conversely, the growth rate of the main clinker phases (alite and belite) is significantly affected by the nature and combination of minor oxides. MgO and Na2O give a very fast C3S formation rate at T > 1450 K, whereas Na2O and SO3 boost C2S After heating, if SO3 occurs in combination with MgO and/or Na2O, it does not inihibit the C3S crystallisation as expected. Rather, it promotes the stabilisation of M1-C3S, thus indirectly influencing the aluminate content, too. MgO increseases the C3S amount and promotes the stabilisation of M3-C3S, when it is in combination with Na2O. Na2O seems to be mainly hosted by calcium aluminate structure, but it does not induce the stabilisation of the orhtorhombic polymorph, as supposed to occur. Such features play a key role in predicting the physicalmechanical performance of a final cement (i.e. rate of hydration and hardening) when used as a bulding material.The present study has been partly funded by the project PRIN 2017 (2017L83S77), of the Italian Ministry for Education, University and Research (MIUR)

Cluster-based Vibration Analysis of Structures with GSP

This article describes a divide-and-conquer strategy suited for vibration monitoring applications. Based on a low-cost embedded network of microelectromechanical accelerometers, the proposed architecture strives to reduce both power consumption and computational resources. Moreover, it eases the sensor deployment on large structures by exploiting a novel clustering scheme, which consists of unconventional and nonoverlapped sensing configurations. Signal processing techniques for inter- and intracluster data assembly are introduced to allow for a fullscale assessment of the structural integrity. More specifically, the capability of graph signal processing is adopted for the first time in vibration-based monitoring scenarios to capture the spatial relationship between acceleration data. The experimental validation, conducted on a steel beam perturbed with additive mass, reveals high accuracy in damage detection tasks. Deviations in spectral content and mode shape envelopes are correctly revealed regardless of environmental factors and operational uncertainties. Furthermore, an additional key advantage of the implemented architecture relies on its compliance with blind modal investigations, an approach that favors the implementation of autonomous smart monitoring systems

Warped Wigner-Hough Transform for Defect Reflection Enhancement in Ultrasonic Guided Wave Monitoring

To improve the defect detectability of Lamb wave inspection systems, the application of nonlinear signal processing was investigated. The approach is based on a Warped Frequency Transform (WFT) to compensate the dispersive behavior of ultrasonic guided waves, followed by a Wigner-Ville time-frequency analysis and the Hough Transform to further improve localization accuracy. As a result, an automatic detection procedure to locate defect-induced reflections was demonstrated and successfully tested by analyzing numerically simulated Lamb waves propagating in an aluminum plate. The proposed method is suitable for defect detection and can be easily implemented for real-world structural health monitoring applications

Mitochondrial Ca2+-dependent NLRP3 activation exacerbates the Pseudomonas aeruginosa-driven inflammatory response in cystic fibrosis

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