Performance of a fly ash geopolymeric mortar for coating of ordinary portland cement concrete exposed to harsh chemical environments

Premature degradation of ordinary Portland cement (OPC) concrete infrastructures is a current and serious problem with overwhelming costs amounting to several trillion dollars. The use of concrete surface treatments with waterproofing materials to prevent the access of aggressive substances is an important way of enhancing concrete durability. The most common surface treatments use polymeric resins based on epoxy, silicone (siloxane), acrylics, polyurethanes or polymethacrylate. However, epoxy resins have low resistance to ultraviolet radiation while polyurethanes are sensitive to high alkalinity environments. Geopolymers constitute a group of materials with high resistance to chemical attack that could also be used for coating of concrete infrastructures exposed to harsh chemical environments. This article presents results of an experimental investigation on the resistance to chemical attack (by sulfuric and nitric acid) of several materials: OPC concrete, high performance concrete (HPC), epoxy resin, acrylic painting and a fly ash based geopolymeric mortar. Three types of acids, each with high concentrations of 10%, 20% and 30%, were used to simulate long term degradation by chemical attack. The results show that the epoxy resin had the best resistance to chemical attack, irrespective of the acid type and acid concentration.

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

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.

Exploring chemical conversions in metabolic networks by tracing atoms transitions

Dissertação de mestrado em Bioinformática

A domain-specific language for ETL patterns specification in Data Warehousing Systems

During the last few years many research efforts have been done to improve the design of ETL (Extract-Transform-Load) systems. ETL systems are considered very time-consuming, error-prone and complex involving several participants from different knowledge domains. ETL processes are one of the most important components of a data warehousing system that are strongly influenced by the complexity of business requirements, their changing and evolution. These aspects influence not only the structure of a data warehouse but also the structures of the data sources involved with. To minimize the negative impact of such variables, we propose the use of ETL patterns to build specific ETL packages. In this paper, we formalize this approach using BPMN (Business Process Modelling Language) for modelling more conceptual ETL workflows, mapping them to real execution primitives through the use of a domain-specific language that allows for the generation of specific instances that can be executed in an ETL commercial tool.

Using a domain-specific language to enrich ETL schemas

Today it is easy to find a lot of tools to define data migration schemas among different types of information systems. Data migration processes use to be implemented on a very diverse range of applications, ranging from conventional operational systems to data warehousing platforms. The implementation of a data migration process often involves a serious planning, considering the development of conceptual migration schemas at early stages. Such schemas help architects and engineers to plan and discuss the most adequate way to migrate data between two different systems. In this paper we present and discuss a way for enriching data migration conceptual schemas in BPMN using a domain-specific language, demonstrating how to convert such enriched schemas to a first correspondent physical representation (a skeleton) in a conventional ETL implementation tool like Kettle.

Cross-language influences on new second language vocabulary acquisition: the effect of learning method

Dissertação de mestrado integrado em Psicologia

Effect of ionic liquid anion and cation on the physico-chemical properties of poly(vinylidene fluoride)/ionic liquid blends

Poly(vinylidene fluoride), PVDF, has been blended with different ionic liquids (IL) in order to evaluate the effect of the different IL anions and cations on the electroative -phase, thermal, mechanical and electrical properties of the polymer blend. [C2MIM][Cl], [C6MIM][Cl], [C10MIM][Cl], [C2MIM][NTf2], [C6MIM][NTf2], [C10MIM][NTf2] have been selected and were introduced in the polymer at a weight percentage of 40 wt%. It was found that the incorporation of ILs into the PVDF matrix leads to an increase of the -phase content due to the strong electrostatic interactions between the dipolar moments of PVDF and the ILs. Further, the incorporation of ILs into PVDF strongly decreases the elastic modulus and increases the electrical conductivity of the blend with respect to the pure polymer matrix, all these effects being accompanied by a modification of the crystallization kinetics, as indicated by the modified spherulitic microstructure. Thus, novel PVDF/IL blends films with high transparency, excellent antistatic properties, and highly polar crystal form fraction were successfully achieved.

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.

Characterization of physical, mechanical and chemical properties of quiscal fibres : the influence of atmospheric DBD plasma treatment

This paper reports the first attempt of characterizing various physical, mechanical and chemical properties of Quiscal fibres, used by the native communities in Chile and investigating the influence of atmospheric dielectric barrier discharge plasma treatment on various properties such as diameter and linear density, fat, wax and impurity%, moisture regain, chemical elements and groups, thermal degradation, surface morphology, etc. According to the experimental observations, Quiscal fibre has lower tenacity than most of the technical grade natural fibres such as sisal, hemp, flax, etc., and plasma treatment at optimum dose improved its tenacity to the level of sisal fibres. Plasma treatment also reduced the amount of fat, wax and other foreign impurities present in Quiscal fibres as well as removed lignin and hemicellulose partially from the fibre structure. Plasma treatment led to functionalization of Quiscal fibre surface with chemical groups, as revealed from attenuated total reflection spectroscopy and also confirmed from the elemental analysis using energy dispersive Xray technique and pH and conductivity measurements of fibre aqueous extract. The wetting behavior of Quiscal fibre also improved considerably through plasma treatment. However, untreated and plasma treated Quiscal fibres showed similar thermal degradation behavior, except the final degradation stage, in which plasma treated fibres showed higher stability and incomplete degradation unlike the untreated fibres. The experimental results suggested that the plasma treated Quiscal fibres, like other technical grade natural fibres, can find potential application as reinforcement of composite materials for various industrial applications.

Effect of chemical and plasma DBD treatments on pseudostem plantain fiber properties

Las fibras del seudotallo de plátano (FSP) fueron modificadas mediante epiclorhidrina (EP), anhídrido acético (AA), y su combinación (AA_EP), y con plasma a tres descargas de barrera dieléctrica (DBD) 1, 3 y 6 kW min m-2. Las FSP tratadas y sin tratar fueron caracterizadas mediante espectroscopia infrarroja por la transformada de Fourier (FT-IR), termogravimetría (TGA), microscopía electrónica de barrido (SEM) y pruebas mecánicas de tensión y de humectabilidad. Los espectros FT-IR, las micrografías SEM, y el análisis TGA indicaron pérdidas de lignina, hemicelulosa, impurezas y ceras. Estos efectos en conjunto con las reacciones de grupos OH y -C-C-, con los tratamientos químicos y de plasma respectivamente, incrementaron la hidrofobicidad de las FSP tratadas. Los tratamientos químicos produjeron reacciones de esterificación, eterificación y entrecruzamiento de los grupos OH libres en las FSP, lo que hizo que mostraran mayor rigidez que las expuestas al plasma. Las micrografías SEM mostraron que las FSP expuestas al plasma quedaron con superficie más irregular y rugosa que la de las FSP tratadas químicamente. La humectabilidad de las fibras, medida mediante pruebas de ángulo de contacto, se redujo como consecuencia de ambos tratamientos, característica importante para un relleno en los materiales compuestos.

Digital manipulatives as scaffolds for preschoolers’ language development

The study reported here aims at contributing to a deeper understanding of the educational possibilities offered by digital manipulatives in preschool contexts. It presents a study carried with a digital manipulative to enhance the development of lexical knowledge and language awareness, which are relevant language abilities for formal literacy learning. The study took place in a Portuguese preschool, with a class of 20 five-year-olds in collaboration with the teacher. The digital manipulative supported the construction of multiple fictional worlds, motivating children's verbal interactions, and the playing of words and sound games, thus contextualizing the learning of an extensive collection of vocabulary and language awareness abilities. The degree of engagement and involvement that the manipulative provided in supporting children’s imaginative play as well as the imitation, in their own play, of the playful pedagogical interventions that the teacher had designed, shows the importance of well- designed materials that support a child-centered learning model. As such, it sustains a discussion on the potential of digital manipulatives to enhance fundamental language development in the preschool years. Further, the study highlights the importance of multidisciplinary teams in the creation of innovative pedagogical materials.

The music of language: an ERP investigation of the effects of musical training on emotional prosody processing

Recent studies have demonstrated the positive effects of musical training on the perception of vocally expressed emotion. This study investigated the effects of musical training on event-related potential (ERP) correlates of emotional prosody processing. Fourteen musicians and fourteen control subjects listened to 228 sentences with neutral semantic content, differing in prosody (one third with neutral, one third with happy and one third with angry intonation), with intelligible semantic content (semantic content condition--SCC) and unintelligible semantic content (pure prosody condition--PPC). Reduced P50 amplitude was found in musicians. A difference between SCC and PPC conditions was found in P50 and N100 amplitude in non-musicians only, and in P200 amplitude in musicians only. Furthermore, musicians were more accurate in recognizing angry prosody in PPC sentences. These findings suggest that auditory expertise characterizing extensive musical training may impact different stages of vocal emotional processing.

Influence of river ecological condition on changes in physico-chemical water parameters along rivers

Dissertação de mestrado em Ecology

Characterization of physical, mechanical and chemical properties of quiscal fibres: the influence of atmospheric dbd plasma treatment

This paper reports the first attempt of characterizing several physical, mechanical and chemical properties of Quiscal fibres, usually used by the native communities in Chile and on investigations concerning the influence of atmospheric dielectric barrier discharge (DBD) plasma treatment on various properties such as diameter and linear density, percent of impurity, moisture regain, chemical elements and groups, thermal degradation, surface morphology, among others.