26 research outputs found
A robust estimation of the response of floating wind turbines through piecewise linearization
Irregular ventricular tachycardia underdetected by implantable cardioverter defibrillator device
A case of sustained monomorphic ventricular tachycardia underdetected by a single chamber
implantable cardioverter defibrillator because of RR interval irregularity is presented. The
programmed stability criterion is responsible for the underdetection. Special attention must be
paid when it comes to programming this detection parameter. (Cardiol J 2008; 15: 281-283
Monopile foundation stiffness estimation of an instrumented offshore wind turbine through model updating
Rapid development of offshore wind foundation models has resulted in a large number of built structures with generally underestimated foundation stiffness properties and a need to update and validate both the individual structural models and the underlying foundation design frameworks. This paper outlines a structural health monitoring approach, based on the combination of output only structural health monitoring methods and model updating, to estimate foundation stiffness parameters using field monitored data. Field monitoring data from an offshore wind turbine under idling conditions, over a large monitoring period, are presented and operational modal analysis is applied to estimate the modal parameters. Those are compared to modal properties predicted by finite element models, employing either old (API/DNVGL) or new (PISA) foundation design properties, which are calibrated using geotechnical site investigation data. A new approach to interpret seabed level statically equivalent foundation stiffness, in terms of effective lateral and rotational stiffness against load eccentricity, is presented. Seabed level statically equivalent foundation properties are updated by comparison against the observed modal behaviour and the optimised foundation parameters are presented, demonstrating a close match to the predictions of the PISA method
Addressing the clinical unmet needs in primary Sjögren's Syndrome through the sharing, harmonization and federated analysis of 21 European cohorts
For many decades, the clinical unmet needs of primary Sjögren's Syndrome (pSS) have been left unresolved due to the rareness of the disease and the complexity of the underlying pathogenic mechanisms, including the pSS-associated lymphomagenesis process. Here, we present the HarmonicSS cloud-computing exemplar which offers beyond the state-of-the-art data analytics services to address the pSS clinical unmet needs, including the development of lymphoma classification models and the identification of biomarkers for lymphomagenesis. The users of the platform have been able to successfully interlink, curate, and harmonize 21 regional, national, and international European cohorts of 7,551 pSS patients with respect to the ethical and legal issues for data sharing. Federated AI algorithms were trained across the harmonized databases, with reduced execution time complexity, yielding robust lymphoma classification models with 85% accuracy, 81.25% sensitivity, 85.4% specificity along with 5 biomarkers for lymphoma development. To our knowledge, this is the first GDPR compliant platform that provides federated AI services to address the pSS clinical unmet needs. © 2022 The Author(s
Online Bayesian Identification of Non-Smooth Systems
The robustness of online Bayesian Identification algorithms has been illustrated for a wide range of physical problems. The successful convergence of such algorithms for problems of highly nonlinear nature is tied to the precision of the approximation of the observed system via the employed state-space model. More sophisticated approximations, result in an increase of both the convergence rate and the associated computational cost. Nonetheless, the latter is a price worth paying for ensuring the former in the case of highly nonlinear problems. The assumption placed by most Bayesian filtering algorithms is that the parameters to be estimated are identifiable at each updating step. This however is a property that does not necessarily hold for systems involving non-smooth nonlinearities, i.e., systems whose state-space or measurement equations are not differentiable. Such systems are linked to the modelling of damage-related phenomena such as plasticity, impact and sliding amongst other. Hence, a separate approach is proposed herein, namely the modification of algorithms to account for the lack of identifiability encountered for parameters of a non-smooth system at a specific step. This modification is termed by the authors as, the Discontinuous, D- modification and relies on the idea that unidentifiable parameters should remain invariant in the corresponding updating steps. This work will illustrate the benefits of the D- modification on the convergence of the Unscented Kalman Filter for non-smooth problems. An example from the dynamics of rocking bodies will be used to demonstrate the advantages of the method
A Discontinuous Unscented Kalman Filter for Non-Smooth Dynamic Problems
For a number of applications, including real/time damage diagnostics as well as control, online methods, i.e., methods which may be implemented on-the-fly, are necessary. Within a system identification context, this implies adoption of filtering algorithms, typically of the Kalman or Bayesian class. For engineered structures, damage or deterioration may often manifest in relation to phenomena such as fracture, plasticity, impact, or friction. Despite the different nature of the previous phenomena, they are described by a common denominator: switching behavior upon occurrence of discrete events. Such events include for example, crack initiation, transitions between elastic and plastic response, or between stick and slide modes. Typically, the state-space equations of such models are non-differentiable at such events, rendering the corresponding systems non-smooth. Identification of non-smooth systems poses greater difficulties than smooth problems of similar computational complexity. Up to a certain extent, this may be attributed to the varying identifiability of such systems, which violates a basic requirement of online Bayesian Identification algorithms, thus affecting their convergence for non-smooth problems. Herein, a treatment to this problem is proposed by the authors, termed the Discontinuous D– modification, where unidentifiable parameters are acknowledged and temporarily excluded from the problem formulation. In this work, the D– modification is illustrated for the case of the Unscented Kalman Filter UKF, resulting in a method termed DUKF, proving superior performance to the conventional, and widely adopted, alternative
A preliminary investigation of methods for generating fragility curves for rocking bodies
For reasons related to functionality, mobility, or as recently has been suggested to improve dynamic performance, several structural and non-structural elements are let to experience large rotations and displacements when subjected to ground excitations. This overall behavior can be characterized as rocking. Recently, the interest in the behavior of rocking elements subjected to ground motions has increased. This is partly due to the importance of the rocking bodies themselves, for example museum artifacts and monuments are irreplaceable, while hospital equipment is of paramount importance to post-seismic response, partly due to the fact that advances in technology have allowed for key elements of infrastructure to become more mobile, such as large super-computer units, and finally also due to the realization that a large part of the cost during earthquakes is attributed to non-structural elements. Characterizing the risk of these elements subjected to ground motions is therefore of increasing importance. However, the dynamic response of rocking elements during ground motions is strongly non-linear and the mode of failure of these objects is, unlike typical civil engineering applications, not related to exceeding a stress- but a displacement -or rotations - limit. Consequently, several of the existing methodologies to study the risk associated of structures are not applicable, as they usually are focused on systems that are geometrically linear and whose failure is associated with fracture or yield. A remedy for this is to study the risk associated to rocking bodies using the more general approach of creating probability of failure curves. The latter approach requires the use of time histories compatible with some measure of intensity as an input to the deterministic models. For this purpose there are several alternatives: stochastic methods able to generate synthetic time histories, such as the Spectral Representation method, methods based on selecting or scaling existing recorded ground motions based on their compatibility to an intensity measure, and numerical data driven approaches able to generate new time histories based on a set of selected time histories. Each of the previous methods has properties which may be more or less advantageous when applied to the problem of rocking. This work will focus on generating ground records compatible with a seismological intensity measure, the magnitude of the earthquake, for the purpose of generating probability of failure curves for rocking bodies. The effects of biaxial versus uniaxial input will be examined highlighting the importance of making use of the notion of principal axes. Based on this conclusions a methodology for creating probability of failure curves for rocking bodies will be proposed
Editorial: Robust Monitoring, Diagnostic Methods and Tools for Engineered Systems
ISSN:2297-336
Efficacy of Antimicrobial Treatment in Dogs with Atopic Dermatitis: An Observational Study
There is a shortage of studies reporting the efficacy of antimicrobial treatment of dogs with atopic dermatitis (AD) and skin infections (SIs). The aim of this study was to evaluate the change in the severity of skin lesions and pruritus, and the overall efficacy of antimicrobial treatment, in dogs with AD and bacterial overgrowth/infection and/or Malassezia dermatitis. A total of 20 dogs with AD and SIs were prospectively enrolled (group A) and they were examined before and after the administration of systemic antimicrobials that resulted in the resolution of SIs. In addition, 19 dogs fulfilling the same inclusion criteria and treated with systemic, with or without topical antimicrobials, were included retrospectively (group B). Since there were no major differences between the groups, their results were combined. The severity of skin lesions decreased significantly, by 30% based on Canine Atopic Dermatitis Extent and Severity Index-4 (CADESI-4), by 28.1% based on the erythema domain of CADESI-4 and based on owner’s global assessment of the severity of skin lesions. Pruritus decreased significantly, by 34.7% based on the Pruritus Visual Analogue Scale (PVAS). The efficacy of antimicrobial treatment was assessed as good to excellent by the investigator and the owner in 55% and 60% of the dogs, respectively. Despite the significant improvement, there was high variability in the response to treatment among dogs. Further studies are needed to find factors that determine the response to antimicrobial treatment in dogs with AD and SIs
A field trial of a fixed combination of permethrin and fipronil (Effitix®) for the treatment and prevention of flea infestation in dogs living with sheep
Abstract Background A large number of fleas parasitize dogs living with sheep in Greece. The primary aim of this randomized, blinded, placebo-controlled trial was to examine the efficacy of a permethrin-fipronil combination (Effitix®) for the treatment and prevention of flea infestation in dogs living with sheep and the secondary aim was to examine the efficacy of this intervention on flea infestation, pruritus and skin lesions of the people in contact with these dogs. Methods Thirty dogs living with sheep and infested by at least 10 fleas and all 80 sheep living on the same premises were randomly allocated into equal groups. Group A dogs were treated three times, every 4 weeks, with a spot-on containing 54.5% permethrin and 6.1% fipronil, group A sheep were treated, on the same days, with a pour-on containing 1% deltamethrin, whereas group B dogs were sham-treated and group B sheep were placebo-treated. Flea counting was performed at the beginning of the trial (day 0) and after 14, 28, 56 and 84 days and the first five fleas from each animal were used for species identification. At the same time points, flea infestation, pruritus and skin lesions of the people in contact with the dogs were assessed. Results The percentage of dogs with zero flea counts was significantly higher in group A than in group B on days 14, 28, 56 and 84 and flea counts were significantly lower in group A dogs than in group B dogs at the same time points. The percent efficacy of the permethrin-fipronil combination was higher than 78% (arithmetic means) or than 96% (geometric means) throughout the study. No adverse reactions were recorded. Between the two flea species found on dogs, Ctenocephalides canis was predominant over C. felis. Flea-infected sheep were not found at the beginning or during the study and no significant changes in flea infestation, pruritus and skin lesions of the people in contact with the dogs were witnessed throughout the study. Conclusions A spot-on solution containing 54.5% permethrin and 6.1% fipronil is safe and effective for the treatment and prevention of C. canis and C. felis infestations in dogs living with sheep