A Facile Measurement of Heterogeneous Electron Transfer Kinetics

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

Discovering promising regions to help global numerical optimization algorithms

We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.

Algorithms for automatic segmentation of bovine embryos produced

In vitro production has been employed in bovine embryos and quantification of lipids is fundamental to understand the metabolism of these embryos. This paper presents a unsupervised segmentation method for histological images of bovine embryos. In this method, the anisotropic filter was used in the differents RGB components. After pre-processing step, the thresholding technique based on maximum entropy was applied to separate lipid droplets in the histological slides in different stages: early cleavage, morula and blastocyst. In the postprocessing step, false positives are removed using the connected components technique that identify regions with excess of dye near pellucid zone. The proposed segmentation method was applied in 30 histological images of bovine embryos. Experiments were performed with the images and statistical measures of sensitivity, specificity and accuracy were calculated based on reference images (gold standard). The value of accuracy of the proposed method was 96% with standard deviation of 3%.

Using Threads to Overcome Synchronization Delays in Parallel Multiple Progressive Alignment Algorithms

Sao Paulo State Research Foundation-FAPESP

Assessing land use by cattle in heterogeneous environments

The aim of this note is to describe preliminary results on assessment of land use by cattle, obtained in a pilot study using Geographic Information System (GIS). The research was carried out on a semi-natural pasture in Sweden, where the geographic positions of one cow were recorded during 25 consecutive days during summer. The cow, wearing a GPS collar, was integrated in a herd of 53 Hereford cattle. Each location point registered for the animal was considered as a sampling unit (N=3,097). The spatial distribution of ground declivity, water sources, cattle tracks, and classes of woody vegetation cover (forest, grassland with trees and open grassland) were recorded. The storage, processing and data analysis were carried out using the Idrisi and GS+ softwares. Three occupation zones were identified in function of the variation in the space used by the animal, which were occupied in a cyclical pattern; with the animal moving from one zone to another in cycles of five days. It was also clear that the cattle distribution in the area was neither random nor uniform, and it was affected by environmental characteristics that act as conditioners on its distribution. These preliminary results suggest that definition of zones of occupation and the environmental conditioners are promising tools to understand the land use by cattle

Organização genômima e análise da expressão do gene hnRNP Q-like (Heterogeneous nuclear ribonucleoprotein A-like) retroinserido no cromossomo B de Astatotilapia latifasciata

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Convenient synthesis of ketal derivatives from cubebin using amberlite as heterogeneous catalyst

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

Cooperative effects of H+ and H- hydrido carbonyl ruthenium derivatives; role of homogeneous and heterogeneous protonic and lewis acids in catalytic hydrocarbonylation reactions

The role played by H+ hydrido iodocarbonyl and H- hydrido carbonyl ruthenium catalysts in the different catalytic steps of hydroformylation and hydroesterification of olefins, and in the homologation of alcohols has been investigated. The H- hydrido carbonyl species are mainly involved in the activation of olefins and in the hydrogenation of the acyl intermediates to aldehydes and alcohols, whereas the H+ hydrido iodocarbonyl derivatives are involved in the activation of alcohols and other oxygenated substrates, and in their carbonylation to esters. The cooperation between the two species, possible under particular reaction conditions, results in an improvement of the selectivity towards homologation (carbonylation plus hydrogenation) products. Heterogeneous Lewis acid promoters, easily recyclable from the reaction mixture, have also been successfully used in the hydrocarbonylation of alcohols, resulting in an increase of the carbonylation and homologation products. A reaction pathway in agreement with the experimental results is discussed. © 1989.

Coagulation-flocculation of TiO2 in suspension used in heterogeneous photocatalysis

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

A comparison about evolutionary algorithms for optimum-path forest clustering optimization

In this paper we deal with the problem of boosting the Optimum-Path Forest (OPF) clustering approach using evolutionary-based optimization techniques. As the OPF classifier performs an exhaustive search to find out the size of sample's neighborhood that allows it to reach the minimum graph cut as a quality measure, we compared several optimization techniques that can obtain close graph cut values to the ones obtained by brute force. Experiments in two public datasets in the context of unsupervised network intrusion detection have showed the evolutionary optimization techniques can find suitable values for the neighborhood faster than the exhaustive search. Additionally, we have showed that it is not necessary to employ many agents for such task, since the neighborhood size is defined by discrete values, with constrain the set of possible solution to a few ones.

OntoSDM: an approach to improve quality on spatial data mining algorithms

The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.