23 resultados para dynamic responses

em Universidade do Minho


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"Series title: Computational methods in applied sciences, ISSN1871-3033, vol. 42"

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Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

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The Our Lady of Conception church is located in village of Monforte (Portugal) and is not in use nowadays. The church presents structural damage and, consequently, a study was carried out. The study involved the survey of the damage, dynamic identification tests under ambient vibration and the numerical analysis. The church is constituted by the central nave, the chancel, the sacristy and the corridor to access the pulpit. The masonry walls present different thickness, namely 0.65 m in the chancel, 0.70 m in the sacristy, 0.92 in the central nave and 0.65 m in the corridor. The masonry walls present 8 buttresses with different dimensions. The total longitudinal and transversal dimensions of the church are equal to 21.10 m and 14.26 m, respectively. The survey of the damage showed that, in general, the masonry walls are in good conditions, with exception of the transversal walls of the nave, which present severe cracks. The arches of the vault presents also severe cracks along the central nave. As consequence, the infiltrations have increased the degradation of the vault and paintings. Furthermore, the foundations present settlements in the Southwest direction. The dynamic identification test were carried out under the action of ambient excitation of the wind and using 12 piezoelectric accelerometers of high sensitivity. The dynamic identification tests allowed to estimate the dynamic properties of the church, namely frequencies, mode shapes and damping ratios. A FEM numerical model was prepared and calibrated, based on the first four experimental modes estimated in the dynamic identification tests. The average error between the experimental and numerical frequencies of the first four modes is equal to 5%. After calibration of the numerical model, pushover analyses with a load pattern proportional to the mass, in the transversal and longitudinal direction of the church, were performed. The results of the analysis numerical allow to conclude that the most vulnerable direction of the church is in the transversal one and the maximum load factor is equal to 0.35.

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Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

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In this study, a high-performance composite was prepared from jute fabrics and polypropylene (PP). In order to improve the compatibility of the polar fibers and the non-polar matrix, alkyl gallates with different hydrophobic groups were enzymatically grafted onto jute fabric by laccase to increase the surface hydrophobicity of the fiber. The grafting products were characterized by FTIR. The results of contact angle and wetting time showed that the hydrophobicity of the jute fabrics was improved after the surface modification. The effect of the enzymatic graft modification on the properties of the jute/PP composites was evaluated. Results showed that after the modification, tensile and dynamic mechanical properties of composites improved, and water absorption and thickness swelling clearly decreased. However, tensile properties drastically decreased after a long period of water immersion. The thermal behavior of the composites was evaluated by TGA/DTG. The fiber-matrix morphology in the modified jute/PP composites was confirmed by SEM analysis of the tensile fractured specimens.

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The manipulation of electric ordering with applied magnetic fields has been realized on magnetoelectric (ME) materials, however, their ME switching is often accompanied by significant hysteresis and coercivity that represents, for some applications, a severe weakness. To overcome this obstacle, this work focus on the development of a new type of ME polymer nanocomposites that exhibits tailored ME response at room temperature. The multiferroic nanocomposites are based on three different ferrite nanoparticles, Zn0.2Mn0.8Fe2O4 (ZMFO), CoFe2O4 (CFO) and Fe3O4 (FO), dispersed in a piezoelectric co-polymer poly(vinylindene fluoride-trifluoroethylene), P(VDF-TrFE), matrix. No substantial differences were detected on the time-stable piezoelectric response of the composites (≈ -28 pC.N−1) with distinct ferrite fillers and for the same ferrite content of 10wt.%. Magnetic hysteresis loops from pure ferrite nanopowders showed different magnetic responses. ME results of the nanocomposite films with 10wt.% ferrite content revealed that the ME induced voltage increases with increasing DC magnetic field until a maximum of 6.5 mV∙cm−1∙Oe−1, at an optimum magnetic field of 0.26 T, and 0.8 mV∙cm−1∙Oe−1, at an optimum magnetic field of 0.15T, for the CFO/P(VDF-TrFE) and FO/P(VDF-TrFE) composites, respectively. On the contrary, the ME response of the ZMFO/P(VDF-TrFE) exposed no hysteresis and high dependence on the ZMFO filler content. Possible innovative applications such as memories and information storage, signal processing, ME sensors and oscillators have been addressed for such ferrite/PVDF nanocomposites.

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This work reports on the influence of the substrate polarization of electroactive β-PVDF on human adipose stem cells (hASCs) differentiation under static and dynamic conditions. hASCs were cultured on different β-PVDF surfaces (non-poled and “poled -”) adsorbed with fibronectin and osteogenic differentiation was determined using a quantitative alkaline phosphatase assay. “Poled -” β-PVDF samples promote higher osteogenic differentiation, which is even higher under dynamic conditions. It is thus demonstrated that electroactive membranes can provide the necessary electromechanical stimuli for the differentiation of specific cells and therefore will support the design of suitable tissue engineering strategies, such as bone tissue engineering.

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Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.

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Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

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Gold nanoparticles were dispersed in two different dielectric matrices, TiO2 and Al2O3, using magnetron sputtering and a post-deposition annealing treatment. The main goal of the present work was to study how the two different host dielectric matrices, and the resulting microstructure evolution (including both the nanoparticles and the host matrix itself) promoted by thermal annealing, influenced the physical properties of the films. In particular, the structure and morphology of the nanocomposites were correlated with the optical response of the thin films, namely their localized surface plasmon resonance (LSPR) characteristics. Furthermore, and in order to scan the future application of the two thin film system in different types of sensors (namely biological ones), their functional behaviour (hardness and Young's modulus change) was also evaluated. Despite the similar Au concentrations in both matrices (~ 11 at.%), very different microstructural features were observed, which were found to depend strongly on the annealing temperature. The main structural differences included: (i) the early crystallization of the TiO2 host matrix, while the Al2O3 one remained amorphous up to 800 °C; (ii) different grain size evolution behaviours with the annealing temperature, namely an almost linear increase for the Au:TiO2 system (from 3 to 11 nm), and the approximately constant values observed in the Au:Al2O3 system (4–5 nm). The results from the nanoparticle size distributions were also found to be quite sensitive to the surrounding matrix, suggesting different mechanisms for the nanoparticle growth (particle migration and coalescence dominating in TiO2 and Ostwald ripening in Al2O3). These different clustering behaviours induced different transmittance-LSPR responses and a good mechanical stability, which opens the possibility for future use of these nanocomposite thin film systems in some envisaged applications (e.g. LSPR-biosensors).

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Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a marked decline in cognition and memory function. Increasing evidence highlights the essential role of neuroinflammatory and immune-related molecules, including those produced at the brain barriers, on brain immune surveillance, cellular dysfunction and amyloid beta (Aß) pathology in AD. Therefore, understanding the response at the brain barriers may unravel novel pathways of relevance for the pathophysiology of AD. Herein, we focused on the study of the choroid plexus (CP), which constitutes the blood-cerebrospinal fluid barrier, in aging and in AD. Specifically, we used the PDGFB-APPSwInd (J20) transgenic mouse model of AD, which presents early memory decline and progressive Aß accumulation, and littermate age-matched wild-type (WT) mice, to characterize the CP transcriptome at 3, 5-6 and 11-12months of age. The most striking observation was that the CP of J20 mice displayed an overall overexpression of type I interferon (IFN) response genes at all ages. Moreover, J20 mice presented a high expression of type II IFN genes in the CP at 3months, which became lower than WT at 5-6 and 11-12months. Importantly, along with a marked memory impairment and increased glial activation, J20 mice also presented a similar overexpression of type I IFN genes in the dorsal hippocampus at 3months. Altogether, these findings provide new insights on a possible interplay between type I and II IFN responses in AD and point to IFNs as targets for modulation in cognitive decline.

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Exposure to chronic stress can have broad effects on health ranging from increased predisposition for neuropsychiatric disorders to deregulation of immune responses. The chronic unpredictable stress (CUS) protocol has been widely used to study the impact of stress exposure in several animal models and consists in the random, intermittent, and unpredictable exposure to a variety of stressors during several weeks. CUS has consistently been shown to induce behavioral and immunological alterations typical of the chronic stress-response. Unfortunately C57BL/6 mice, one of the most widely used mouse strains, due to the great variety of genetically modified lines, seem to be resistant to the commonly used 4-week-long CUS protocol. The definition of an alternative CUS protocol allowing the use of C57BL/6 mice in chronic stress experiments is a need. Here, we show that by extending the CUS protocol to 8?weeks is possible to induce a chronic stress-response in C57BL/6 mice, as revealed by abrogated body weight gain, increased adrenals weight, and an overactive hypothalamic-pituitary-adrenal axis with increased levels of serum corticosterone. Moreover, we also observed stress-associated behavioral alterations, including the potentiation of anxious-like and depressive-like behaviors and a reduction of exploratory behavior, as well as subtle stress-related changes in the cell population of the thymus and of the spleen. The present protocol for C57BL/6 mice consistently triggers the spectrum of CUS-induced changes observed in rats and, thus, will be highly useful to researchers that need to use this particular mouse strain as an animal model of neuropsychiatric disorders and/or immune deregulation related to CUS.

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[Excerpt] We read with interest the case report by Ismael et al1 describing a patient with Sjo¨gren’s syndrome and cystic lung disease who could not be weaned from a ventilator due to severe central excessive dynamic airway collapse (EDAC) of the lower part of the trachea and proximal bronchi. EDAC corresponds to the expiratory bulging of the tracheobronchial wall without known airway structural abnormalities, leading to a decrease of at least 50% in internal diameter.2 It is a rare and underdiagnosed entity, commonly confused with other respiratory diseases such as asthma and COPD. Although noninvasive procedures such as cervicothoracic computed tomography scan on inspiration and expiration may suggest the disorder, the accepted standard method for diagnosis is bronchoscopy.3-7 (...).

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Dissertação de mestrado integrado em Engenharia Biomédica

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Dissertação de mestrado integrado em Biomedical Engineering Biomaterials, Biomechanics and Rehabilitation