4 resultados para State Crack-Growth

em Universidade do Minho


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Tissue engineering often rely on scaffolds for supporting cell differentiation and growth. Novel paradigms for tissue engineering include the need of active or smart scaffolds in order to properly regenerate specific tissues. In particular, as electrical and electromechanical clues are among the most relevant ones in determining tissue functionality in tissues such as muscle and bone, among others, electroactive materials and, in particular, piezoelectric ones, show strong potential for novel tissue engineering strategies, in particular taking also into account the existence of these phenomena within some specific tissues, indicating their requirement also during tissue regeneration. This referee reports on piezoelectric materials used for tissue engineering applications. The most used materials for tissue engineering strategies are reported together with the main achievements, challenges and future needs for research and actual therapies. This review provides thus a compilation of the most relevant results and strategies and a start point for novel research pathways in the most relevant and challenging open questions.

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Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

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To examine effects of mother's anxiety and depression and associated risk factors during early pregnancy on fetal growth and activity. Repeated measures of mother's anxiety (State-Anxiety Inventory (STAI-S)) and depression (Edinburgh Postnatal Depression Scale (EPDS)) and related socio demographics and substance consumption were obtained at the 1st and 2nd pregnancy trimesters, and fetus' (N = 147) biometric data and behavior was recorded during ultrasound examination at 20-22 weeks of gestation. Higher anxiety symptoms were associated to both lower fetal growth and higher fetal activity. While lower education, primiparity, adolescent motherhood, and tobacco consumption predicted lower fetal growth, coffee intake predicted lower fetal activity. Vulnerability of fetal development to mother's psychological symptoms as well as to other sociodemographic and substance consumption risk factors during early and mid pregnancy is suggested.

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Dissertação de mestrado em Bioengenharia