Remoção de matéria orgânica, de nutrientes e de coliformes no processo anaeróbio em dois estágios (reator compartimentado seguido de reator UASB) para o tratamento de águas residuárias de suinocultura

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of Aspergillus spp. exogenous fibrolytic enzymes on in vitro fermentation of tropical forages

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Understanding the Crystallization Mechanism of a Wollastonite Base Glass Using Isoconversional, IKP Methods and Master Plots

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Modeling a system of phosphated cross-linked high amylose for controlled drug release. Part 1: Synthesis and polymer characterization

High amylose was cross-linked with sodium trimetaphosphate (STMP) using 2% and 4% solutions of NaOH at room temperature with reaction contact times of 0.5, 1, 2 and 4 h. The different polymers obtained were analyzed by FT IR, C-13 and P-31 solid state NMR, SEM and C, H and P elemental analysis. The results were used to propose a two-stage mechanism for phosphate incorporation, the first being kinetically controlled. (C) 2008 Elsevier Ltd. All rights reserved.

SUGARCANE BAGASSE PULPING and BLEACHING: THERMAL and CHEMICAL CHARACTERIZATION

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Uma análise experimental de algoritmos exatos aplicados ao problema da árvore geradora multiobjetivo

The Multiobjective Spanning Tree Problem is NP-hard and models applications in several areas. This research presents an experimental analysis of different strategies used in the literature to develop exact algorithms to solve the problem. Initially, the algorithms are classified according to the approaches used to solve the problem. Features of two or more approaches can be found in some of those algorithms. The approaches investigated here are: the two-stage method, branch-and-bound, k-best and the preference-based approach. The main contribution of this research lies in the fact that no research was presented to date reporting a systematic experimental analysis of exact algorithms for the Multiobjective Spanning Tree Problem. Therefore, this work can be a basis for other research that deal with the same problem. The computational experiments compare the performance of algorithms regarding processing time, efficiency based on the number of objectives and number of solutions found in a controlled time interval. The analysis of the algorithms was performed for known instances of the problem, as well as instances obtained from a generator commonly used in the literature

Detecção e diagnóstico de falhas não-supervisionados baseados em estimativa de densidade recursiva e classificador fuzzy auto-evolutivo

In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison

Absence of chemopreventive influence of propolis on the rat liver altered foci development

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial Distribution of Seropositive Dogs to Leptospira spp. and Evaluation of Leptospirosis Risk Factors Using a Decision Tree

Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.

Clinical Viability of Immediate Loading of Dental Implants: Part I-Factors for Success

Two-stage procedure for dental implants presents corroborated clinical success over 40 years. The evolution of surgical techniques, development of diagnostic methods, knowledge about tissue biology, and quality of implants regarding design and surface supported studies with I surgical stage followed by immediate prosthesis placement. However, several factors influence the treatment success with immediate loading. SO, this Study aimed to evaluate some factors regarding the success and characteristics of implants and patients.

Calculating the Best Dual Bound for Problems with Multiple Lagrangian Relaxations

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Application of crude xylanase from Bacillus licheniformis 77-2 to the bleaching of eucalyptus Kraft pulp

Alkalophilic Bacillus licheniformis 77-2 produced an extracellular alkali-tolerant xylanase with negligible cellulase activity in medium containing corn straw. The effectiveness of crude xylanase on treatment of eucalyptus Kraft pulp was evaluated. A biobleaching experiment was carried out to compare the chlorine saving with pulp treated and untreated by the enzyme. Two-stage bleaching was employed, using a ClO2 chlorination and NaOH extraction (DE sequence). With the enzymatic treatment, in order to obtain the same value of Kappa number and brightness, respectively 28.5 and 30% less ClO2 was required in comparison to the enzymatically untreated samples.

Desempenho de reatores anaeróbios de fluxo ascendente com manta de lodo em dois estágios tratando águas residuárias de suinocultura

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Desempenho de processo anaeróbio em dois estágios (reator compartimentado seguido de reator UASB) para tratamento de águas residuárias de suinocultura

Avaliou-se o efeito das águas residuárias de suinocultura com concentrações de sólidos suspensos totais em torno de 6.000 mg L-1 (DQOtotal variando de 7.557 a 11.640 mg L-1) no desempenho de processo anaeróbio em dois estágios compostos por reator compartimentado (ABR) e reator de fluxo ascendente com manta de lodo (UASB), instalados em série, em escala-piloto (volumes de 530 e 120 L, respectivamente), submetidos a tempos de detenção hidráulica (TDH) de 56 a 18 h no primeiro reator e de 13 a 4 h no segundo reator. As eficiências médias de remoção de DQOtotal variaram de 71,1 a 87,5% no reator ABR e de 41,5 a 50,1% no reator UASB, resultando em valores médios de 86,8 a 94,9% para o sistema de tratamento anaeróbio em dois estágios com carga orgânica volumétrica (COV), na faixa de 5,05 a 10,12 kg DQOtotal (m³ d)-1, no reator ABR, e de 2,83 a 9,63 kg DQOtotal (m³ d)-1, no reator UASB. As eficiências de remoção de SST e SSV foram da ordem de 95,6%. O teor de metano no biogás manteve-se acima de 70% para os dois reatores. A produção volumétrica de metano máxima de 0,755 m³ CH4 (m³ d)-1 ocorreu no reator 1, com COV de 10,12 kg DQOtotal (m³ d)-1 e TDH de 18 h. Os valores médios de pH variaram na faixa de 7,2 a 8,0 para os efluentes dos reatores 1 e 2. Os ácidos voláteis totais mantiveram-se estáveis com concentrações abaixo de 200 mg L-1. Com variações abruptas e acentuadas de concentrações de SST e DQOtotal do afluente, os reatores mantiveram as eficiências de remoção de DQO e sólidos suspensos, em torno de 70%, e a qualidade do biogás, com 80% de CH4.

Tratamento anaeróbio de águas residuárias do beneficiamento de café por via úmida em reatores UASB em dois estágios

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)