In vitro mechanical fatigue behavior of poly-ε-caprolactone macroporous scaffolds for cartilage tissue engineering: Influence of pore filling by a poly(vinyl alcohol) gel

Polymeric scaffolds used in regenerative therapies are implanted in the damaged tissue and subjected to repeated loading cycles. In the case of articular cartilage engineering, an implanted scaffold is typically subjected to long term dynamic compression. The evolution of the mechanical properties of the scaffold during bioresorption has been deeply studied in the past, but the possibility of failure due to mechanical fatigue has not been properly addressed. Nevertheless, the macroporous scaffold is susceptible to failure after repeated loading-unloading cycles. In this work fatigue studies of polycaprolactone scaffolds were carried by subjecting the scaffold to repeated compression cycles in conditions simulating the scaffold implanted in the articular cartilage. The behaviour of the polycaprolactone sponge with the pores filled with a poly(vinyl alcohol) gel simulating the new formed tissue within the pores was compared with that of the material immersed in water. Results were analyzed with Morrow’s criteria for failure and accurate fittings are obtained just up to 200 loading cycles. It is also shown that the presence of poly(vinyl alcohol) increases the elastic modulus of the scaffolds, the effect being more pronounced with increasing the number of freeze/thawing cycles.

Extracting kinetic information from literature with KineticRE

To better understand the dynamic behavior of metabolic networks in a wide variety of conditions, the field of Systems Biology has increased its interest in the use of kinetic models. The different databases, available these days, do not contain enough data regarding this topic. Given that a significant part of the relevant information for the development of such models is still wide spread in the literature, it becomes essential to develop specific and powerful text mining tools to collect these data. In this context, this work has as main objective the development of a text mining tool to extract, from scientific literature, kinetic parameters, their respective values and their relations with enzymes and metabolites. The approach proposed integrates the development of a novel plug-in over the text mining framework @Note2. In the end, the pipeline developed was validated with a case study on Kluyveromyces lactis, spanning the analysis and results of 20 full text documents.

Coagulation/flocculation/flotation/nanofiltration processes using Moringa Oleifera as coagulant of Eutrophized river

This study investigated the efficiency of Moringa oleifera (MO) seeds as natural coagulant in coagulation/flocculation/dissolved air flotation (C/F/DAF), followed by nanofiltration (NF) for Microcystis protocystis and microcystin-LR removal. The methodology adopted in this work was performed in two steps: 1) coagulation/flocculation/dissolved air flotation (C/F/DAF) process using the MO extracted in saline solution of potassium chloride (KCl-1M) and sodium chloride (NaCl-1M) in optimum dosage 50 mg·L-1; 2) nanofiltration process using NF90 and NF270 membrane provided Dow Chemical Company®. A working pressure of 8 bar was applied. In all samples were analyzed color, turbidity, pH, cyanobacterial cells count and microcystin concentration. The use of MO seeds as natural coagulant, obtained satisfactory results in the M. protocystis, color and turbidity removal. NF was able to completely remove cyanobacterial cells and microcystins (100 %) from M. protocystis (always under the quantification limit). Therefore, C/F/DAF+NF sequence is a safe barrier against M. protocystis and microcystins in drinking water.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

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.

A firefly dynamic penalty approach for solving engineering design problems

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.

Narrative change in Gloria Films: Comparing various processes of therapeutic innovation

Aims: The present study focuses on the analysis of novelty emergence in classic Gloria Films with Rogers, Perls, and Ellis to understand how the same client formulated her own problem and if and how change occurred in those three sessions. Method: The Innovative Moments Coding System was applied to track innovative moments (IMs) and their themes. Results: The session with Rogers showed more diversity in disclosed problems and themes of IMs, as well as a higher proportion of reflection IMs. The session with Perls demonstrated a high proportion of protest IMs. The session with Ellis showed less innovation than other sessions. The changes found were based mostly on reflection and protest IMs in three sessions. Conclusion: Narrative innovations occurred in the three single sessions. The type of dominant innovation is consistent with the therapeutic model and the IMs model. The exploration of the IMs’ themes allowed a more precise identification of Gloria's new narrative positions and their development throughout those sessions.

A narrativa da liderança escolar: os alunos como agentes de revelação

Publicado em "Educação, territórios e desenvolvimento humano: atas do I Seminário Internacional, Vol. I – conferências e intervenções". ISBN 978-989-96186-9-5

Mechanical ventilation for the treatment of severe excessive dynamic airway collapse

[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 (...).

Evaluating balance, stability and gait symmetry of stroke patients using kinematic and dynamic gait lab data

Dissertação de mestrado integrado em Engenharia Biomédica

Avaliação da camada intermetálica em placas de circuito impresso com acabamento superficial HASL com diferentes processos de soldagem

Dissertação de mestrado integrado em Engenharia de Materiais

Otimização das características de um chassis tubular de automóvel de competição com tração a duas rodas motrizes

Dissertação de mestrado integrado em Engenharia Mecânica

Processos de melhoria social: a requalificação do Bairro Social de Santa Tecla

Dissertação de mestrado integrado em Arquitectura

Expressão e caracterização de uma lectina recombinante de interesse biomédico

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Engenharia Clínica)

Dynamic modelling and analysis of hydraulic forces in radial blood pumps

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

Dynamic interface model for masonry walls subjected to high strain rate out-of-plane loads

The present study proposes a dynamic constitutive material interface model that includes non-associated flow rule and high strain rate effects, implemented in the finite element code ABAQUS as a user subroutine. First, the model capability is validated with numerical simulations of unreinforced block work masonry walls subjected to low velocity impact. The results obtained are compared with field test data and good agreement is found. Subsequently, a comprehensive parametric analysis is accomplished with different joint tensile strengths and cohesion, and wall thickness to evaluate the effect of the parameter variations on the impact response of masonry walls.