Latin-American Society Of Forensic Genetics (SLAGF) results of the Interlaboratory Quality Control Exercise 2010-2011

Latin-American Society of Forensic Genetics (SLAGF) Interlaboratory Quality Control Exercise (2010-2011) included the analysis of three bloodstain samples in FTA Classic Card (three persons, biologically unrelated) and one theoretical exercise. There were 56 participating laboratories from 13 Latin-American countries that belong to society, were reported 70 STRs, including autosomal and sex chromosome markers with consensus in 53 STRs with a rate in reporting errors of 2.3%. Fifty-six laboratories reported results in theoretical exercise with mistakes in calculation of IP for each marker. It is necessary to hold meetings to discuss the results of this exercise to reach conclusions and recommendations on all aspects of DNA forensics analysis and paternity test, to improve results and quality in the results of each laboratory. © 2011 Elsevier B.V.

Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.

Biologic and genetics aspects of chagas disease at endemic areas

The etiologic agent of Chagas Disease is the Trypanosoma cruzi, transmitted through blood-sucking insect vectors of the Triatominae subfamily, representing one of the most serious public health concerns in Latin America. There are geographic variations in the prevalence of clinical forms and morbidity of Chagas disease, likely due to genetic variation of the T. cruzi and the host genetic and environmental features. Increasing evidence has supported that inflammatory cytokines and chemokines are responsible for the generation of the inflammatory infiltrate and tissue damage. Moreover, genetic polymorphisms, protein expression levels, and genomic imbalances are associated with disease progression. This paper discusses these key aspects. Large surveys were carried out in Brazil and served as baseline for definition of the control measures adopted. However, Chagas disease is still active, and aspects such as host-parasite interactions, genetic mechanisms of cellular interaction, genetic variability, and tropism need further investigations in the attempt to eradicate the disease. Copyright 2012 Marilanda Ferreira Bellini et al.

Vectorized algorithms for quadtree construction and descent

This paper presents vectorized methods of construction and descent of quadtrees that can be easily adapted to message passing parallel computing. A time complexity analysis for the present approach is also discussed. The proposed method of tree construction requires a hash table to index nodes of a linear quadtree in the breadth-first order. The hash is performed in two steps: an internal hash to index child nodes and an external hash to index nodes in the same level (depth). The quadtree descent is performed by considering each level as a vector segment of a linear quadtree, so that nodes of the same level can be processed concurrently. © 2012 Springer-Verlag.

The assessment of the quality of sugar using electronic tongue and machine learning algorithms

The correct classification of sugar according to its physico-chemical characteristics directly influences the value of the product and its acceptance by the market. This study shows that using an electronic tongue system along with established techniques of supervised learning leads to the correct classification of sugar samples according to their qualities. In this paper, we offer two new real, public and non-encoded sugar datasets whose attributes were automatically collected using an electronic tongue, with and without pH controlling. Moreover, we compare the performance achieved by several established machine learning methods. Our experiments were diligently designed to ensure statistically sound results and they indicate that k-nearest neighbors method outperforms other evaluated classifiers and, hence, it can be used as a good baseline for further comparison. © 2012 IEEE.

A precautionary tale when describing species in a world of invaders: Morphology, coloration and genetics demonstrate that Lysmata rauli is not a new species endemic to Brazil but a junior synonym of the Indo-Pacific L. vittata

The objective of this study was to investigate morphological variation in traits of systematic relevance and the phylogenetic position, ecology, and reproductive biology of the shrimp Lysmata rauli Laubenheimer and Rhyne, 2010 (Caridea: Hippolytidae), described based only on a single specimen collected in Salvador, Bahia, Brazil. We analyzed a total of 89 specimens from Camamu Bay, Bahia (n = 88) and from S3o Vicente estuary, São Paulo (n = 1). Considerable morphological variation was detected in the rostral spine series, number of segments on the carpus and merus of pereiopod 2, number of spiniform setae on the ventrolateral margin of merus and on the ventral margin of propodus of pereiopods 3-5. Importantly, L rauli can be distinguished neither using morphology, nor coloration from the Indo-Pacific L. vittata (Stimpson, 1860). Furthermore, molecular phylogenetic analyses (using the 16S mt DNA fragment) did not reveal any considerable genetic dissimilarities between L rauli and L vittata. Thus, our results clearly indicate that L rauli is not a new species but a junior synonym of L vittata. The high density observed within the structures of oyster farming indicates that the invasive L vittata lives in crowds in Brazil. The studied population was composed of males, hermaphrodites, and transitional individuals (having characteristics of males and hermaphrodites). The above information suggests that L rauli is a protandric simultaneous hermaphrodite, as it has been observed in all species of Lysmata that have been investigated. Lysmata vittata has invaded the southwestern Atlantic and is present in Bahia, Rio de Janeiro and S3o Paulo, Brazil. © The Crustacean Society, 2013. Published by Brill NV, Leiden.

Use of algorithms for semi-automatic quantification of pulmonary fibrosis and emphysema

Obtaining a semi-automatic quantification of pathologies found in the lung, through images of high resolution computed tomography (HRCT), is of great importance to aid in medical diagnosis. Paraccocidioidomycosis (PCM) is a systemic disease that affects the lung and even after effective treatment leaves sequels such as pulmonary fibrosis and emphysema. It is very important to the area of tropical diseases that the lung injury be quantified more accurately. In this stud, we propose the development of algorithms in computational environment Matlab® able to objectively quantify lung diseases such as fibrosis and emphysema. The program consists in selecting the region of interest (ROI), and through the use of density masks and filters, obtaining the lesion area quantification in relation to the healthy area of the lung. The proposed method was tested on 15 exams of HRCT of patients with confirmed PCM. To prove the validity and effectiveness of the method, we used a virtual phantom, also developed in this research. © 2013 Springer-Verlag.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Uma ferramenta alternativa para síntese de circuitos lógicos usando a técnica de circuito evolutivo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritmos de alinhamento múltiplo e técnicas de otimização para esses algoritmos utilizando Ant Colony

Pós-graduação em Ciência da Computação - IBILCE

Simultaneous spectrometric determination of Cu2+, Mn2+ and Zn2+ in polivitaminic/polimineral drug using SPA and GA algorithms for variable selection

Este artigo apresenta uma aplicação do método para determinação espectrofotométrica simultânea dos íons divalentes de cobre, manganês e zinco à análise de medicamento polivitamínico/polimineral. O método usa 4-(2-piridilazo) resorcinol (PAR), calibração multivariada e técnicas de seleção de variáveis e foi otimizado o empregando-se o algoritmo das projeções sucessivas (APS) e o algoritmo genético (AG), para escolha dos comprimentos de onda mais informativos para a análise. Com essas técnicas, foi possível construir modelos de calibração por regressão linear múltipla (RLM-APS e RLM-AG). Os resultados obtidos foram comparados com modelos de regressão em componentes principais (PCR) e nos mínimos quadrados parciais (PLS). Demonstra-se a partir do erro médio quadrático de previsão (RMSEP) que os modelos apresentam desempenhos semelhantes ao prever as concentrações dos três analitos no medicamento. Todavia os modelos RLM são mais simples pois requerem um número muito menor de comprimentos de onda e são mais fáceis de interpretar que os baseados em variáveis latentes.

The genetics of New World monkey visual pigments

To have color vision, having at least two cone photopigment types with different spectral sensitivities present in distinct photoreceptors is necessary together with the neural circuitry necessary to extract color information. Visual pigments are highly conserved molecules, but differences can be found among vertebrate groups. Primates have a variety of cone photopigments (i.e., opsins) that are expressed by polymorphic genes. This article examines the diversity of cone photopigments in New World monkeys and their behavioral relevance.

Distributional potential of the Triatoma brasiliensis species complex at present and under scenarios of future climate conditions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Simulating Population Genetics of Pathogen Vectors in Changing Landscapes: Guidelines and Application with Triatoma brasiliensis

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