Lightweight concrete masonry units based on processed granulate of corn cob as aggregate

A research work was performed in order to assess the potential application of processed granulate of corn cob (PCC) as an alternative lightweight aggregate for the manufacturing process of lightweight concrete masonry units (CMU). Therefore, CMU-PCC were prepared in a factory using a typical lightweight concrete mixture for non-structural purposes. Additionally, lightweight concrete masonry units based on a currently applied lightweight aggregate such as expanded clay (CMU-EC) were also manufactured. An experimental work allowed achieving a set of results that suggest that the proposed building product presents interesting material properties within the masonry wall context. Therefore, this unit is promising for both interior and exterior applications. This conclusion is even more relevant considering that corn cob is an agricultural waste product.

Fused deposition modeling with polypropylene

This paper addresses the potential of polypropylene (PP) as a candidate for fused deposition modeling (FDM)-based 3D printing technique. The entire filament production chain is evaluated, starting with the PP pellets, filament production by extrusion and test samples printing. This strategy enables a true comparison between parts printed with parts manufactured by compression molding, using the same grade of raw material. Printed samples were mechanically characterized and the influence of filament orientation, layer thickness, infill degree and material was assessed. Regarding the latter, two grades of PP were evaluated: a glass-fiber reinforced and a neat, non-reinforced, one. The results showed the potential of the FDM to compete with conventional techniques, especially for the production of small series of parts/components; also, it was showed that this technique allows the production of parts with adequate mechanical performance and, therefore, does not need to be restricted to the production of mockups and prototypes.

Desenvolvimento de estruturas fibrosas com comportamento auxético

Tese de Doutoramento Engenharia Têxtil

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

“ Da Moda ao Resíduo e do Resíduo à Moda”: um contributo sustentável no uso da pele residual na Indústria do calçado

Dissertação de mestrado em Design e Marketing

Melhoria de processos numa indústria têxtil através da aplicação do paradigma Lean

Dissertação de mestrado em Engenharia Industrial

Gestão de inventários numa empresa de produção de linhas de costura

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Development of high specific strength components, with internal cellular structure, for several applications

Dissertação de mestrado em Engenharia Mecânica

Controlo e gestão da produção no setor de corte térmico

Dissertação de mestrado integrado em Engenharia Mecânica

Desenvolvimento de um protótipo didático de uma máquina de corte de pedra por fio diamantado

Dissertação de mestrado integrado em Engenharia Mecânica

Corte térmico: orçamentação de produtos e racionalização do processo

Dissertação de mestrado integrado em Engenharia Mecânica

Avaliação do desempenho ambiental do aglomerado negro de cortiça

Dissertação de mestrado integrado em Engenharia Civil

Marine origin polysaccharides in drug delivery systems

Oceans are a vast source of natural substances. In them, we find various compounds with wide biotechnological and biomedical applicabilities. The exploitation of the sea as a renewable source of biocompounds can have a positive impact on the development of new systems and devices for biomedical applications. Marine polysaccharides are among the most abundant materials in the seas, which contributes to a decrease of the extraction costs, besides their solubility behavior in aqueous solvents and extraction media, and their interaction with other biocompounds. Polysaccharides such as alginate, carrageenan and fucoidan can be extracted from algae, whereas chitosan and hyaluronan can be obtained from animal sources. Most marine polysaccharides have important biological properties such as biocompatibility, biodegradability, and anti-inflammatory activity, as well as adhesive and antimicrobial actions. Moreover, they can be modified in order to allow processing them into various shapes and sizes and may exhibit response dependence to external stimuli, such as pH and temperature. Due to these properties, these biomaterials have been studied as raw material for the construction of carrier devices for drugs, including particles, capsules and hydrogels. The devices are designed to achieve a controlled release of therapeutic agents in an attempt to fight against serious diseases, and to be used in advanced therapies, such as gene delivery or regenerative medicine.