Antioxidant extraction process for Andean Oca by a photodiode array detector using response surface methodology

Application of Experimental Design techniques has proven to be essential in various research fields, due to its statistical capability of processing the effect of interactions among independent variables, known as factors, in a system’s response. Advantages of this methodology can be summarized in more resource and time efficient experimentations while providing more accurate results. This research emphasizes the quantification of 4 antioxidants extraction, at two different concentration, prepared according to an experimental procedure and measured by a Photodiode Array Detector. Experimental planning was made following a Central Composite Design, which is a type of DoE that allows to consider the quadratic component in Response Surfaces, a component that includes pure curvature studies on the model produced. This work was executed with the intention of analyzing responses, peak areas obtained from chromatograms plotted by the Detector’s system, and comprehending if the factors considered – acquired from an extensive literary review – produced the expected effect in response. Completion of this work will allow to take conclusions regarding what factors should be considered for the optimization studies of antioxidants extraction in a Oca (Oxalis tuberosa) matrix.

Single-tube nested PCR assay with in-house DNA extraction for Mycobacterium tuberculosis detection in blood and urine

Abstract: INTRODUCTION : Molecular analyses are auxiliary tools for detecting Koch's bacilli in clinical specimens from patients with suspected tuberculosis (TB). However, there are still no efficient diagnostic tests that combine high sensitivity and specificity and yield rapid results in the detection of TB. This study evaluated single-tube nested polymerase chain reaction (STNPCR) as a molecular diagnostic test with low risk of cross contamination for detecting Mycobacterium tuberculosis in clinical samples. METHODS: Mycobacterium tuberculosis deoxyribonucleic acid (DNA) was detected in blood and urine samples by STNPCR followed by agarose gel electrophoresis. In this system, reaction tubes were not opened between the two stages of PCR (simple and nested). RESULTS: STNPCR demonstrated good accuracy in clinical samples with no cross contamination between microtubes. Sensitivity in blood and urine, analyzed in parallel, was 35%-62% for pulmonary and 41%-72% for extrapulmonary TB. The specificity of STNPCR was 100% in most analyses, depending on the type of clinical sample (blood or urine) and clinical form of disease (pulmonary or extrapulmonary). CONCLUSIONS: STNPCR was effective in detecting TB, especially the extrapulmonary form for which sensitivity was higher, and had the advantage of less invasive sample collection from patients for whom a spontaneous sputum sample was unavailable. With low risk of cross contamination, the STNPCR can be used as an adjunct to conventional methods for diagnosing TB.

Valorization of grape pomace through hot compressed water extraction/hydrolysis

The world energy consumption is expected to increase strongly in coming years, because of the emerging economies. Biomass is the only renewable carbon resource that is abundant enough to be used as a source of energy Grape pomace is one of the most abundant agro-industrial residues in the world, being a good biomass resource. The aim of this work is the valorization of grape pomace from white grapes (WWGP) and from red grapes (RWGP), through the extraction of phenolic compounds with antioxidant activity, as well as through the extraction/hydrolysis of carbohydrates, using subcritical water, or hot compressed water (HCW). The main focus of this work is the optimization of the process for WWGP, while for RWGP only one set of parameters were tested. The temperatures used were 170, 190 and 210 °C for WWGP, and 180 °C for RWGP. The water flow rates were 5 and 10 mL/min, and the pressure was always kept at 100 bar. Before performing HCW assays, both residues were characterized, revealing that WWGP is very rich in free sugars (around 40%) essentially glucose and fructose, while RWGP has higher contents of structural sugars, lignin, lipids and protein. For WWGP the best results were achieved at 210 °C and 10 mL/min: higher yield in water soluble compounds (69 wt.%), phenolics extraction (26.2 mg/g) and carbohydrates recovery (49.3 wt.% relative to the existing 57.8%). For RWGP the conditions were not optimized (180 °C and 5 mL/min), and the values of the yield in water soluble compounds (25 wt.%), phenolics extraction (19.5 mg/g) and carbohydrates recovery (11.4 wt.% relative to the existing 33.5%) were much lower. The antioxidant activity of the HCW extracts from each assay was determined, the best result being obtained for WWGP, namely for extracts obtained at 210 °C (EC50=20.8 μg/mL; EC50 = half maximum effective concentration; EC50 = 22.1 μg/mL for RWGP, at 180 ºC).

Extraction of Trypanosoma cruzi DNA from food: a contribution to the elucidation of acute Chagas disease outbreaks

Abstract: INTRODUCTION: Before 2004, the occurrence of acute Chagas disease (ACD) by oral transmission associated with food was scarcely known or investigated. Originally sporadic and circumstantial, ACD occurrences have now become frequent in the Amazon region, with recently related outbreaks spreading to several Brazilian states. These cases are associated with the consumption of açai juice by waste reservoir animals or insect vectors infected with Trypanosoma cruzi in endemic areas. Although guidelines for processing the fruit to minimize contamination through microorganisms and parasites exist, açai-based products must be assessed for quality, for which the demand for appropriate methodologies must be met. METHODS: Dilutions ranging from 5 to 1,000 T. cruzi CL Brener cells were mixed with 2mL of acai juice. Four Extraction of T. cruzi DNA methods were used on the fruit, and the cetyltrimethyl ammonium bromide (CTAB) method was selected according to JRC, 2005. RESULTS: DNA extraction by the CTAB method yielded satisfactory results with regard to purity and concentration for use in PCR. Overall, the methods employed proved that not only extraction efficiency but also high sensitivity in amplification was important. CONCLUSIONS: The method for T. cruzi detection in food is a powerful tool in the epidemiological investigation of outbreaks as it turns epidemiological evidence into supporting data that serve to confirm T. cruzi infection in the foods. It also facilitates food quality control and assessment of good manufacturing practices involving acai-based products.

Production and characterization of Chitin-Glucan Complex by Komagataella pastoris

This thesis was focused on the production, extraction and characterization of chitin:β-glucan complex (CGC). In this process, glycerol byproduct from the biodiesel industry was used as carbon source. The selected CGC producing yeast was Komagataella pastoris (formerly known as Pichia pastoris), due the fact that to achieved high cell densities using as carbon source glycerol from the biodiesel industry. Firstly, a screening of K. pastoris strains was performed in shake flask assays, in order to select the strain of K. pastoris with better performance, in terms of growth, using glycerol as a carbon source. K. pastoris strain DSM 70877 achieved higher final cell densities (92-97 g/l), using pure glycerol (99%, w/v) and in glycerol from the biodiesel industry (86%, w/v), respectively, compared to DSM 70382 strain (74-82 g/l). Based on these shake flask assays results, the wild type DSM 70877 strain was selected to proceed for cultivation in a 2 l bioreactor, using glycerol byproduct (40 g/l), as sole carbon source. Biomass production by K. pastoris was performed under controlled temperature and pH (30.0 ºC and 5.0, respectively). More than 100 g/l biomass was obtained in less than 48 h. The yield of biomass on a glycerol basis was 0.55 g/g during the batch phase and 0.63 g/g during the fed-batch phase. In order to optimize the downstream process, by increasing extraction and purification efficiency of CGC from K. pastoris biomass, several assays were performed. It was found that extraction with 5 M NaOH at 65 ºC, during 2 hours, associated to neutralization with HCl, followed by successive washing steps with deionised water until conductivity of ≤20μS/cm, increased CGC purity. The obtained copolymer, CGCpure, had a chitin:glucan molar ratio of 25:75 mol% close to commercial CGC samples extracted from A. niger mycelium, kiOsmetine from Kitozyme (30:70 mol%). CGCpure was characterized by solid-state Nuclear Magnetic Resonance (NMR) spectroscopy and Differential Scanning Calorimetry (DCS), revealing a CGC with higher purity than a CGC commercial (kiOsmetine). In order to optimize CGC production, a set of batch cultivation experiments was performed to evaluate the effect of pH (3.5–6.5) and temperature (20–40 ºC) on the specific cell growth rate, CGC production and polymer composition. Statistical tools (response surface methodology and central composite design) were used. The CGC content in the biomass and the volumetric productivity (rp) were not significantly affected within the tested pH and temperature ranges. In contrast, the effect of pH and temperature on the CGC molar ratio was more pronounced. The highest chitin: β-glucan molar ratio (> 14:86) was obtained for the mid-range pH (4.5-5.8) and temperatures (26–33 ºC). The ability of K. pastoris to synthesize CGC with different molar ratios as a function of pH and temperature is a feature that can be exploited to obtain tailored polymer compositions.(...)

Semantic relations extraction from unstructured information for domain ontologies enrichment

Based in internet growth, through semantic web, together with communication speed improvement and fast development of storage device sizes, data and information volume rises considerably every day. Because of this, in the last few years there has been a growing interest in structures for formal representation with suitable characteristics, such as the possibility to organize data and information, as well as the reuse of its contents aimed for the generation of new knowledge. Controlled Vocabulary, specifically Ontologies, present themselves in the lead as one of such structures of representation with high potential. Not only allow for data representation, as well as the reuse of such data for knowledge extraction, coupled with its subsequent storage through not so complex formalisms. However, for the purpose of assuring that ontology knowledge is always up to date, they need maintenance. Ontology Learning is an area which studies the details of update and maintenance of ontologies. It is worth noting that relevant literature already presents first results on automatic maintenance of ontologies, but still in a very early stage. Human-based processes are still the current way to update and maintain an ontology, which turns this into a cumbersome task. The generation of new knowledge aimed for ontology growth can be done based in Data Mining techniques, which is an area that studies techniques for data processing, pattern discovery and knowledge extraction in IT systems. This work aims at proposing a novel semi-automatic method for knowledge extraction from unstructured data sources, using Data Mining techniques, namely through pattern discovery, focused in improving the precision of concept and its semantic relations present in an ontology. In order to verify the applicability of the proposed method, a proof of concept was developed, presenting its results, which were applied in building and construction sector.

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

La Cène ou la figure du banquet comme image de crise morale chez Zeng Fanzhi

Les yeux et les masques sont prévalents dans les oeuvres du peintre chinois contemporain Zeng Fanzhi (né en 1964), comme métaphore du jeu de pouvoir qui oppose les individus à l’appareil social et politique. Son oeuvre La Cène, d’après Leonard de Vinci, est un exemple frappant de cette préoccupation. Cet essai examine l’utilisation par l’artiste de cette représentation occidentale d’une crise morale (une trahison qui mène à la mort du Christ) pour exprimer la dystopie qui marque la Chine contemporaine. L’interprétation par Zeng de l’oeuvre de Vinci témoigne d’une compréhension profonde de sa signification à la Renaissance comme conflit entre le pouvoir terrestre et spirituel, auquel il surimpose la fonction du banquet dans la culture chinoise comme lieu de lutte politique. Un nihilisme détaché imprègne ce travail, à l’instar de l’interprétation métaphorique du banquet de Platon par Søren Kierkegaard, In Vino Veritas.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Quantitative image analysis as a tool for Yarrowia lipolytica dimorphic growth evaluation in different culture media

Yarrowia lipolytica, a yeast strain with a huge biotechnological potential, capable to produce metabolites such as γ-decalactone, citric acid, intracellular lipids and enzymes, possesses the ability to change its morphology in response to environmental conditions. In the present study, a quantitative image analysis (QIA) procedure was developed for the identification and quantification of Y. lipolytica W29 and MTLY40-2P strains dimorphic growth, cultivated in batch cultures on hydrophilic (glucose and N-acetylglucosamine (GlcNAc) and hydrophobic (olive oil and castor oil) media. The morphological characterization of yeast cells by QIA techniques revealed that hydrophobic carbon sources, namely castor oil, should be preferred for both strains growth in the yeast single cell morphotype. On the other hand, hydrophilic sugars, namely glucose and GlcNAc caused a dimorphic transition growth towards the hyphae morphotype. Experiments for γ-decalactone production with MTLY40-2P strain in two distinct morphotypes (yeast single cells and hyphae cells) were also performed. The obtained results showed the adequacy of the proposed morphology monitoring tool in relation to each morphotype on the aroma production ability. The present work allowed establishing that QIA techniques can be a valuable tool for the identification of the best culture conditions for industrial processes implementation.

Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

O ambiente como argumento final na imprensa brasileira

O presente artigo analisa, no quadro da ecolinguística, uma notícia publicada num jornal brasileiro, acerca de um funcionário público proeminente detido pela polícia. Reconhece a centralidade da enunciação para a análise linguística e procura identificar a ideologia subjacente à modalização operada. Defende que o artigo analisado simplifica a realidade, cria dicotomias simplistas e, num certo sentido, manipula os factos para criar espetacularização e atrair o público. Em particular, evoca o interdiscurso ambiental que percorre a esfera pública para, por associação, valorizar a imagem do indivíduo-alvo e, em seguida, inverter a valorização e criar dele uma imagem fortemente disfórica. O interdiscurso ambiental é, então, dado como pacífico, aceite inquestionavelmente por todos os cidadãos, e a militância ambiental é apresentada como traço mais elevado do caráter do indivíduo em causa.. Apesar de se apresentar como uma notícia, com caraterística de texto objetivizado, o artigo em análise é claramente avaliativo e substitui os tribunais pela praça pública para a condenação do indivíduo-alvo, mesmo sem o ter ouvido e considerado a sua defesa.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Eating behavior and body image among psychology students

OBJECTIVE: To characterize eating habits and possible risk factors associated with eating disorders among psychology students, a segment at risk for eating disorders. METHOD: This is a cross-sectional study. The questionnaires Bulimic Investigatory Test Edinburgh (BITE), Eating Attitudes Test (EAT-26), Body Shape Questionnaire (BSQ) and a variety that considers related issues were applied. Statistical Package for the Social Sciences (SPSS) 11.0 was utilized in analysis. The study population was composed of 175 female students, with a mean age of 21.2 (DP ± 3.6 years). RESULTS: A positive result was detected on the EAT-26 for 6.9% of the cases (CI95%: 3.6-11.7%). The prevalence of increased symptoms and intense gravity, according to the BITE questionnaire was 5% (CI95%: 2.4-9.5%) and 2.5% (CI95%: 0.7-6.3%), respectively. According to the findings, 26.29% of the students presented abnormal eating behavior. The population with moderate/severe BSQ scores presented dissatisfaction with corporal weight. CONCLUSION: The results indicate that attention must be given to eating behavior risks within this group. A differentiated gaze is justified with respect to these future professionals, whose practice is jeopardized in cases in which they are themselves the bearers of installed symptoms or precursory behavior.