Alginate-Based Rapid Prototyping System

Alginate hydrogels are an import class of ionic biopolymers for medical and biotechnological applications, produced by the combination of alginate with a proper cross-linking agent. During the gel formation, cross-links can be formed between the alginate chains and cationic species, changing the elastic behaviour of the material that controls the volume change phenomena of the gels. This paper proposes a new rapid prototyping system to produce three-dimensional alginate structures by extruding, layer-by-layer, a previously prepared solution of sodium alginate in water mixed with a solution of calcium chloride, both of known concentration. The building process to obtain these gel structures is described, from a chemical point of view, and some obtained structures are shown. The alginate concentration over both the kinetics and accuracy effects of the process is investigated. The preliminary findings of this research work promise to open an exciting new area for medical applications.Mechanical Engineerin

Comparação do desempenho de sensores de fibra óptica e de dispositivos tradicionais na monitorização de deformações em estruturas de betão

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia CivilA observação do comportamento de estruturas, realizada durante a construção e em serviço, permite a avaliação do seu desempenho com base em valores directamente medidos in situ e possibilita a verificação das teorias de comportamento estrutural consideradas na modelação e na análise dessas estruturas. Com efeito, a observação do comportamento de uma estrutura e o tratamento dos dados resultantes dessa observação,para além de permitir o controlo da sua segurança, pode ainda ser utilizada para a melhoria da qualidade da própria obra e servir também para obter informação relevante tendo em vista o projecto de futuras construções similares. A evolução tecnológica que se tem desenvolvido nos últimos anos tem permitido avanços muito significativos no domínio da monitorização do comportamento estrutural, através de um contínuo melhoramento dos sensores existentes, do surgimento de novos sensores, bem como de sistemas de aquisição automática, responsáveis por um salto qualitativo muito importante em termos da qualidade e quantidade da informação disponível. Neste contexto surgiram os sensores de fibra óptica, tecnologia que, embora recente, tem tido uma franca expansão, disponibilizando sensores para a medição de diferentes grandezas. A introdução de novas tecnologias nos sistemas de monitorização deve ser feita de forma prudente, permitindo os benefícios associados mas sem perder a fiabilidade garantidas por tecnologias com provas dadas em diversos anos de experiência. Neste sentido, a inclusão de novos sensores deve ser precedida de ensaios laboratoriais que atestem tanto quanto possível a qualidade e a fiabilidade desses sensores, e, por outro lado, na utilização em obra deverá haver alguma redundância de sensores comprovados e sensores novos. É neste âmbito que se insere o presente trabalho, dedicado às primeiras utilizações de uma tecnologia emergente aplicável à monitorização do comportamento de estruturas, a fibra óptica, comparando-a com alguns dos sensores tradicionais, já com várias décadas de uso, procurando um melhor desempenho assim como uma optimização de custo. Neste contexto, propõe-se uma metodologia para a comparação do desempenho da tecnologia da fibra óptica com a dos dispositivos tradicionais para a monitorização de estruturas de betão, focando-se na medição de extensões no interior do betão. Ao longo do trabalho descrevem-se os ensaios realizados e apresentam-se os resultados obtidos que são comparados e analisados, permitindo extrair algumas conclusões

Topological Optimisation of Scaffolds for Tissue Engineering

AbstractAdvanced additive manufacturing technologies, namely Biomanufacturing, are being used to fabricate scaffolds with controlled architecture for tissue engineering applications. These technologies combined with computer-aided design (CAD) enable to produce three-dimensional structures layer-by-layer in a multitude of materials. Actual prediction of the effective mechanical properties of scaffolds produced by Biomanufacturing, is very important for tissue engineering applications. A novel computer based technique for scaffold design is topological optimisation. Topological optimisation is a form of “shape” optimisation, usually referred to as “layout” optimisation. The goal of topological optimisation is to find the best use of material for a body that is subjected to either a single load or a multiple load distribution. This paper proposes a topological optimisation scheme in order to obtain the ideal topological architectures of scaffolds, maximising its mechanical behaviour

Alginate/Aloe Vera Hydrogel Films for Biomedical Applications

AbstractThis paper describes a methodology to produce hydrogel films, composed of alginate and Aloe vera, for wound healing and drug delivery applications. The films were prepared through the solvent-casting method and subsequently submitted to an additional cross-linking step to improve their properties. Alginate films with different Aloe vera contents (5, 15 and 25%) were prepared and its properties evaluated in terms of thickness, transparency, swelling behavior and in vitro degradation. Results show a positive influence of Aloe vera on the transparency of the films, in both dry and wet state. Films were immersed in acetate buffer at pH 5.5 simulating the value of the skin, to evaluate its water absorption capacity. It was found that water absorption increases as the Aloe vera content increases, suggesting that Aloe vera enhances the hydrophilic properties of the films. The in vitro degradation tests were performed through the incubation of the films, for 10 weeks, in a simulated body fluid at 37°C. After this period, films kept its structure integrity exhibiting a weight loss in the range of 14.1-18.6%

Modeling and simulation of photofabrication processes using unsaturated polyester resins

Several kinetic models have been proposed to simulate thermosetting cure reactions. The most complex models, based on a mechanistic approach of cure reactions, are developed based on the concepts of free radical polymerization and the mechanism of reactions with diffusion. However, mechanistic models are usually quite impractical for engineering purposes because of the difficulty in obtaining the model parameters. An alternative to these mechanistic models are the phenomenological models, formulated in terms of the degree of cure and much easier to apply. Phenomenological models have been largely used to study thermal-initiated cure reactions, although only few works used them to model the kinetics of ultraviolet-initiated cure reaction. This work proposes a photo-thermal-kinetic model to study the behavior of unsaturated polyester resins during ultraviolet-initiated cure reactions. The model considers samples with different amounts of initiator concentration and cure reactions performed under different ultraviolet light intensities. The model has been numerically solved using the finite element techniquePortuguese Foundation for Science and Technology; contract grant number: POCTI/EME/58405/2004

Tracking recurrent concepts using context

The problem of recurring concepts in data stream classification is a special case of concept drift where concepts may reappear. Although several existing methods are able to learn in the presence of concept drift, few consider contextual information when tracking recurring concepts. Nevertheless, in many real-world scenarios context information is available and can be exploited to improve existing approaches in the detection or even anticipation of recurring concepts. In this work, we propose the extension of existing approaches to deal with the problem of recurring concepts by reusing previously learned decision models in situations where concepts reappear. The different underlying concepts are identified using an existing drift detection method, based on the error-rate of the learning process. A method to associate context information and learned decision models is proposed to improve the adaptation to recurring concepts. The method also addresses the challenge of retrieving the most appropriate concept for a particular context. Finally, to deal with situations of memory scarcity, an intelligent strategy to discard models is proposed. The experiments conducted so far, using synthetic and real datasets, show promising results and make it possible to analyze the trade-off between the accuracy gains and the learned models storage cost

Cell-instructive pectin hydrogels crosslinked via thiol-norbornene photo-click chemistry for skin tissue engineering

Cell-instructive hydrogels are attractive for skin repair and regeneration, serving as interactive matrices to promote cell adhesion, cell-driven remodeling and de novo deposition of extracellular matrix compo nents. This paper describes the synthesis and photocrosslinking of cell-instructive pectin hydrogels using cell-degradable peptide crosslinkers and integrin-specific adhesive ligands. Protease-degradable hydro gels obtained by photoinitiated thiol-norbornene click chemistry are rapidly formed in the presence of dermal fibroblasts, exhibit tunable properties and are capable of modulating the behavior of embedded cells, including the cell spreading, hydrogel contraction and secretion of matrix metalloproteases. Keratinocytes seeded on top of fibroblast-loaded hydrogels are able to adhere and form a compact and dense layer of epidermis, mimicking the architecture of the native skin. Thiol-ene photocrosslinkable pec tin hydrogels support the in vitro formation of full-thickness skin and are thus a highly promising plat form for skin tissue engineering applications, including wound healing and in vitro testing modinfo:eu-repo/semantics/publishedVersio

Mining recurring concepts in a dynamic feature space

Most data stream classification techniques assume that the underlying feature space is static. However, in real-world applications the set of features and their relevance to the target concept may change over time. In addition, when the underlying concepts reappear, reusing previously learnt models can enhance the learning process in terms of accuracy and processing time at the expense of manageable memory consumption. In this paper, we propose mining recurring concepts in a dynamic feature space (MReC-DFS), a data stream classification system to address the challenges of learning recurring concepts in a dynamic feature space while simultaneously reducing the memory cost associated with storing past models. MReC-DFS is able to detect and adapt to concept changes using the performance of the learning process and contextual information. To handle recurring concepts, stored models are combined in a dynamically weighted ensemble. Incremental feature selection is performed to reduce the combined feature space. This contribution allows MReC-DFS to store only the features most relevant to the learnt concepts, which in turn increases the memory efficiency of the technique. In addition, an incremental feature selection method is proposed that dynamically determines the threshold between relevant and irrelevant features. Experimental results demonstrating the high accuracy of MReC-DFS compared with state-of-the-art techniques on a variety of real datasets are presented. The results also show the superior memory efficiency of MReC-DFS

Collaborative data stream mining in ubiquitous environments using dynamic classifier selection

In ubiquitous data stream mining applications, different devices often aim to learn concepts that are similar to some extent. In these applications, such as spam filtering or news recommendation, the data stream underlying concept (e.g., interesting mail/news) is likely to change over time. Therefore, the resultant model must be continuously adapted to such changes. This paper presents a novel Collaborative Data Stream Mining (Coll-Stream) approach that explores the similarities in the knowledge available from other devices to improve local classification accuracy. Coll-Stream integrates the community knowledge using an ensemble method where the classifiers are selected and weighted based on their local accuracy for different partitions of the feature space. We evaluate Coll-Stream classification accuracy in situations with concept drift, noise, partition granularity and concept similarity in relation to the local underlying concept. The experimental results show that Coll-Stream resultant model achieves stability and accuracy in a variety of situations using both synthetic and real world datasets

Electrospun polycaprolactone (PCL) degradation: An in vitro and in vivo study

This work was supported by the Fundação para a Ciência e a Tecnologia (FCT) through the following projects: CDRSP: UIDB/04044/2020, UIDP/04044/2020 and MARE: UIDB/04292/2020 and UIDP/04292/2020. This study was also supported by PAMI-ROTEIRO/0328/2013 (No. 022158), MATIS (CENTRO-01-0145-FEDER-000014-3362), SpinningTNT (POCI-01-02B7-FEDER-069285), and the project LA/P/0069/2020 granted to the Associate Laboratory ARNET.Polycaprolactone (PCL) is widely used in tissue engineering due to its interesting properties, namely biocompatibility, biodegradability, elastic nature, availability, cost efficacy, and the approval of health authorities such as the American Food and Drug Administration (FDA). The PCL degradation rate is not the most adequate for specific applications such as skin regeneration due to the hydrophobic nature of bulk PCL. However, PCL electrospun fiber meshes, due to their low diameters resulting in high surface area, are expected to exhibit a fast degradation rate. In this work, in vitro and in vivo degradation studies were performed over 90 days to evaluate the potential of electrospun PCL as a wound dressing. Enzymatic and hydrolytic degradation studies in vitro, performed in a static medium, demonstrated the influence of lipase, which promoted a rate of degradation of 97% for PCL meshes. In an in vivo scenario, the degradation was slower, although the samples were not rejected, and were well-integrated in the surrounding tissues inside the subcutaneous pockets specifically created.info:eu-repo/semantics/publishedVersio