Plastic-damage smeared crack model to simulate the behaviour of structures made by cement based materials

This work proposes a constitutive model to simulate nonlinear behaviour of cement based materials subjected to different loading paths. The model incorporates a multidirectional fixed smeared crack approach to simulate crack initiation and propagation, whereas the inelastic behaviour of material between cracks is treated by a numerical strategy that combines plasticity and damage theories. For capturing more realistically the shear stress transfer between the crack surfaces, a softening diagram is assumed for modelling the crack shear stress versus crack shear strain. The plastic damage model is based on the yield function, flow rule and evolution law for hardening variable, and includes an explicit isotropic damage law to simulate the stiffness degradation and the softening behaviour of cement based materials in compression. This model was implemented into the FEMIX computer program, and experimental tests at material scale were simulated to appraise the predictive performance of this constitutive model. The applicability of the model for simulating the behaviour of reinforced concrete shear wall panels submitted to biaxial loading conditions, and RC beams failing in shear is investigated.

Risk assessment in a research laboratory during sol–gel synthesis of nano-TiO2

The occupational risks in the nanotechnology research laboratories are an important topic since a great number of researchers are involved in this area. The risk assessment performed by both qualitative and quantitative methods is a necessary step for the management of the occupational risks. Risk assessment could be performed by qualitative methods that gather consensus in the scientific community. It is also possible to use quantitative methods, based in different technics and metrics, as indicative exposure limits are been settled by several institutions. While performing the risk assessment, the information on the materials used is very important and, if it is not updated, it could create a bias in the assessment results. The exposure to TiO2 nanoparticles risk was assessed in a research laboratory using a quantitative exposure method and qualitative risk assessment methods. It was found the results from direct-reading Condensation Particle Counter (CPC) equipment and the CB Nanotool seem to be related and aligned, while the results obtained from the use of the Stoffenmanager Nano seem to indicate a higher risk level.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

A construção de um currículo de project-based learning: o currículo ideal e o currículo formal

O objetivo deste trabalho é apresentar os resultados da análise das concepções de dois protagonistas de uma reforma curricular que está sendo implementada numa escola de engenharia. A principal característica do novo currículo é o uso de projetos e oficinas como atividades complementares a serem realizadas pelos estudantes. As atividades complementares acontecerão em paralelo ao trabalho realizado nas disciplinas sem que haja uma relação de interdisciplinaridade. O novo currículo está sendo implantado desde fevereiro de 2015. Segundo Pacheco (2005) há dois momentos, dentre outros, no processo de mudança curricular, o currículo “ideal”, determinado por dimensões epistemológica, política, econômica, ideológica, técnica, estética, e histórica e, que recebe influência direta daquele que idealiza e cria o novo currículo e, o currículo “formal” que se traduz na prática implementada na escola. São essas duas etapas estudadas nesta pesquisa. Para isso serão considerados como fontes de dados dois protagonistas, um mais ligado à concepção do currículo e outro da sua implementação, a partir dos quais se busca compreender as motivações, crenças e percepções que, por sua vez, determinam a reforma curricular. Entrevistas semiestruturadas foram utilizadas como técnica de pesquisa, com o propósito de se entender a gênese da proposta e as mudanças entre essas duas etapas. Os dados revelam que mudanças aconteceram desde a idealização até a formalização do currículo, motivadas por demandas do processo de implementação, revela ainda diferenças na visão de currículo e a motivação para romper com padrões na formação de engenheiros no Brasil.

Gamification e game-based learning: uma abordagem lúdica à aprendizagem

Relatório de estágio de mestrado em Ensino de Informática

Assessing the production of jet mix columns using alkali activated waste based on mechanical and financial performance and CO2 (eq) emissions

Recent research has proved the potential of alkaline activated fly-ash for soil stabilisation. However, such studies have not focused on the link between financial, mechanical and environmental aspects of this solution, but only on their absolute mechanical properties. The present paper characterises the mechanical behaviour of a large spectrum of activator-ash-soil combinations used to build jet mixing columns, analysing also the cost and CO2 (eq) emissions. The concern with these two vectors forced a decrease in the quantity of stabilising agent added to the soil, relatively to previous research, and the effects of such low quantities have not yet been published. However, the results clearly showed a significant improve in strength, still well above the average values expected when improving the stressstrain behaviour of a weak soil. Uniaxial compressive strength tests were used to assess the effects of the fly-ash percentage, the alkalieash ratio and the water content. The carbon calculator recently developed by the European Federation of Foundation Contractors and the Deep Foundations Institute was used to quantify the CO2 (eq) emissions associated with this technique. The financial cost was estimated based on the experience of a major Portuguese contractor. For comparison purposes, soil cement mixtures were also analysed, using similar conditions and tools used for the soil-ash analysis. Results showed that the cement and ash solutions are very similar in terms of overall performance, with some advantage of the former regarding financial cost, and a significant advantage of the latter regarding the CO2 (eq) emissions. This new grout, although it is in an embryonic stage, it has the potential for broader developments in the field.

Enzymatic processing of protein-based fibers

Wool and silk are major protein fiber materials used by the textile industry. Fiber protein structure-function relationships are briefly described here, and the major enzymatic processing routes for textiles and other novel applications are deeply reviewed. Fiber biomodification is described here with various classes of enzymes such as protease, transglutaminase, tyrosinase, and laccase. It is expected that the reader will get a perspective on the research done as a basis for new applications in other areas such as cosmetics and pharma.

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

State of the art and open questions on cathode preparation based on carbon coated lithium iron phosphate

One important component with particular relevance in battery performance is the cathode, being one of the main responsible elements for cell capacity and cycle life. Carbon coated lithium iron phosphate, C-LiFePO4, active material is one of the most promising cathode materials for the next generation of large scale lithium ion battery applications and strong research efforts are being devoted to it, due to its excellent characteristics, including high capacity, ~170 mAh/g, and safety. This review summarizes the main developments on C-LiFePO4 based cathode film preparation and performance. The effect of the binder, conductive additive, relationship between active material-binder-conductive additive and drying step, in the electrode film fabrication and performance is presented and discussed. Finally, after the presentation of the cell types fabricated with C-LiFePO4 active material and their performance, some conclusions and guidelines for further investigations are outlined.

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.

Analysis and selection of indicators for a sustainability assessment method for school buildings based on SBTool ‐ PT

Nowadays, the sustainability of buildings has an extreme importance. This concept goes towards the European aims of the Program Horizon 2020, which concerns about the reduction of the environmental impacts through such aspects as the energy efficiency and renewable technologies, among others. Sustainability is an extremely broad concept but, in this work, it is intended to include the concept of sustainability in buildings. Within the concept that aims the integration of environmental, social and economic levels towards the preservation of the planet and the integrity of the users, there are, currently, several types of tools of environmental certification that are applicable to the construction industry (LEED, BREEAM, DGNB, SBTool, among others). Within this context, it is highlighted the tool SBTool (Sustainable Building Tool) that is employed in several countries and can be subject to review in institutions of basic education, which are the base for the formation of the critical masses and for the development of a country. The main aim of this research is to select indicators that can be used in a methodology for sustainability assessment (SBTool) of school buildings in Portugal and in Brazil. In order to achieve it, it will also be analyzed other methodologies that already incorporate parameters directly related with the schools environment, such as BREEAM or LEED.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Polymer electrolyte based on DNA and N,N,N-trimethyl-N-(2-hydroxyethyl)ammonium bis(trifluoromethylsulfonyl)imide

Combining ionic liquids (ILs) with polymers offers the prospect of new applications, where they surpass the performance of conventional media, such as organic solvents, giving advantages in terms of improved safety and a higher operating temperature range. In this work we have investigated the morphology, thermal and electrochemical properties of polymer electrolytes prepared through the addition of con- trolled quantities of the cholinium based IL N,N,N-trimethyl-N-(2-hydroxyethyl)ammonium bis(trifluo- romethylsulfonyl)imide ([N1 1 1 2(OH)] [NTf2]) to a deoxyribonucleic acid (DNA) host network. These novel IL-based electrolytes have been analyzed aiming at applications in electrochemical devices. An optimized sample showed good thermal stability up to 155 °C and a wide electrochemical window of ~3.5 V. The highest conductivity was registered for the DNA[N1 1 1 2(OH)][NTf2] (1:1) (2.82 × 10-5 and 1.09 × 10-3 S cm-1 at 30 and 100 °C, respectively).

PEGylated DOTA-AHA-based Gd(III) chelates – A relaxometric study

Three PEGylated derivatives of 1,4,7,10-tetraazacyclododecane-1-((6-amino)hexanoic)-4,7,10-triacetic acid) (DOTA-AHA) with different molecular weights were prepared and characterized. Their Gd(III) chelates were studied in aqueous solution using variable-temperature 1H nuclear magnetic relaxation dispersion (NMRD) and 17ONMR spectroscopy in view of the determination of their relaxivity and the parameters that govern it. The relaxivity varied from 5.1 to 6.5 mM-1.s-1 (37 ºC and 60 MHz) with the increasing molecular weight of the PEG chain, being slightly higher than that of the parent chelate Gd(DOTA-AHA), due to a small contribution of a slow global rotation of the complexes. A variable temperature 1H NMR study of several Ln(III) chelates of DOTA-A(PEG750)HA allowed the determination of the isomeric M/m ratio (M = square antiprismatic isomer and m = twisted square antiprismatic isomer, the latter presenting a much faster water exchange) which for the Gd(III) chelate was estimated in circa 1:0.2, very close to that of [Gd(DOTA)]-. This explains why the PEGylated Gd(III) chelate has a water rate exchange similar to that of [Gd(DOTA)]-. The predominance of the M isomer is a consequence of the bulky PEG moiety which does not favor the stabilization of the m isomer in sterically crowded systems at the substituent site, contrary to what happens with less packed asymmetrical DOTA-type chelates with substitution in one of the four acetate C(α) atoms.