Confirmação da ocorrência de Abolboda poarchon Seub. (Xyridaceae) no Estado de São Paulo, Brasil

A ocorrência de Abolboda poarchon Seub. é documentada para o Estado de São Paulo, com base em coletas realizadas no município de Itirapina. O trabalho apresenta a descrição detalhada de A. poarchon e A. pulchella, espécies simpátricas, com características diagnósticas e distintivas para o reconhecimento das mesmas no campo.

Key to the nests of Brazilian Epiponini wasps (Vespidae: Polistinae)

Brazil possesses the richest diversity of Epiponini wasps in the world. However, field identification of genera of these wasps, based on morphological features, is difficult without optical equipment. Therefore, this work presents a key to the Brazilian Epiponini genera based on the structural features of the nests.

Identidades secretas: representações do negro nas Histórias em quadrinhos norte-americanas

Pós-graduação em Comunicação - FAAC

Identification of new isolates of Bacillus thuringiensis using rep-PCR products and delta-endotoxin electron microscopy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Structural integrity identification based on smart materials and neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically>30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, two sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with an experimental example, an investigation on a massive quarter scale model of a steel bridge section, in order to verify the performance of this proposed methodology.

Disparity between Multilocus Enzyme Electrophoresis, Microsatellite Markers and Pulsed-Field Gel Electrophoresis in epidemiological tracking of Candida albicans

Various molecular systems are available for epidemiological, genetic, evolutionary, taxonomic and systematic studies of innumerable fungal infections, especially those caused by the opportunistic pathogen C. albicans. A total of 75 independent oral isolates were selected in order to compare Multilocus Enzyme Electrophoresis (MLEE), Electrophoretic Karyotyping (EK) and Microsatellite Markers (Simple Sequence Repeats - SSRs), in their abilities to differentiate and group C. albicans isolates (discriminatory power), and also, to evaluate the concordance and similarity of the groups of strains determined by cluster analysis for each fingerprinting method. Isoenzyme typing was performed using eleven enzyme systems: Adh, Sdh, M1p, Mdh, Idh, Gdh, G6pdh, Asd, Cat, Po, and Lap (data previously published). The EK method consisted of chromosomal DNA separation by pulsed-field gel electrophoresis using a CHEF system. The microsatellite markers were investigated by PCR using three polymorphic loci: EF3, CDC3, and HIS3. Dendrograms were generated by the SAHN method and UPGMA algorithm based on similarity matrices (S(SM)). The discriminatory power of the three methods was over 95%, however a paired analysis among them showed a parity of 19.7-22.4% in the identification of strains. Weak correlation was also observed among the genetic similarity matrices (S(SM)(MLEE) x S(SM)(EK) x S(SM)(SSRs)). Clustering analyses showed a mean of 9 +/- 12.4 isolates per cluster (3.8 +/- 8 isolates/taxon) for MLEE, 6.2 +/- 4.9 isolates per cluster (4 +/- 4.5 isolates/taxon) for SSRs, and 4.1 +/- 2.3 isolates per cluster (2.6 +/- 2.3 isolates/taxon) for EK. A total of 45 (13%), 39(11.2%), 5 (1.4%) and 3 (0.9%) clusters pairs from 347 showed similarity (Si) of 0.1-10%, 10.1-20%, 20.1-30% and 30.1-40%, respectively. Clinical and molecular epidemiological correlation involving the opportunistic pathogen C. albicans may be attributed dependently of each method of genotyping (i.e., MLEE, EK, and SSRs) supplemented with similarity and grouping analysis. Therefore, the use of genotyping systems that give results which offer minimum disparity, or the combination of the results of these systems, can provide greater security and consistency in the determination of strains and their genetic relationships. (C) 2010 Elsevier B.V. All rights reserved.

Field study on nematode resistance in Nelore-breed cattle

The present study evaluated Nelore cattle with different degrees of resistance to natural infections by gastrointestinal nematodes. One hundred weaned male cattle, 11-12 months of age, were kept on the same pasture and evaluated from October 2003 to February 2004. Faecal and blood samples were collected for parasitological, haematological and immunological tests. In February 2004, the 10 most resistant and the 10 most susceptible animals were selected based on individual means of nematode faecal egg counts (FEC). Such animals were slaughtered for worm burden determination and nematode species identification. The repeatability estimates for FEC (+/- S.D.), log-transformed FEC and packed-cell volume (PCV) in all animals were 0.3 (+/- 0.05), 0.26 (+/- 0.04) and 0.42 (+/- 0.05), respectively. The resistant group showed lower FEC and worm burdens than the susceptible group (P < 0.05). There were no significant differences between groups regarding mean body weight, weight gain, PCV and total serum protein values (P > 0.05). The resistant group showed higher total serum IgE levels (P < 0.05) and higher mean eosinophil blood counts. However, the latter was statistically significant only 42 days after the beginning of the study. Nematodes Cooperia punctata and Haemonchus placei were predominant and the correlation between Cooperia and Haemonchus burdens was 0.64 (P < 0.05), which indicated that animals presenting increased numbers of one of those genera probably had increased numbers of the other. The current study provides further evidence of IgE active role in nematode immunity and suggests that total serum IgE level might serve as an additional marker to select Nelore cattle that are responsive to H. placei and C. punctata infections. (C) 2007 Elsevier B.V. All rights reserved.

Closed string thermal torus from thermo field dynamics

In this Letter a topological interpretation for the string thermal vacuum in the thermo field dynamics (TFD) approach is given. As a consequence, the relationship between the imaginary time and TFD formalisms is achieved when both are used to study closed strings at finite temperature. The TFD approach starts by duplicating the system's degrees of freedom, defining an auxiliary (tilde) string. In order to lead the system to finite temperature a Bogoliubov transformation is implemented. We show that the effect of this transformation is to glue together the string and the tilde string to obtain a torus. The thermal vacuum appears as the boundary state for this identification. Also, from the thermal state condition, a Kubo-Martin-Schwinger condition for the torus topology is derived. © 2005 Elsevier B.V. All rights reserved.

Measurement of the t(t)over-bar production cross section in pp collisions at 7 TeV in lepton plus jets events using b-quark jet identification

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Performance of tau-lepton reconstruction and identification in CMS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of Landslide Scars in the Region of the Serra do Mar, São Paulo State, Brazil, Using Digital Image Processing and Spatial Analysis Tools

The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.

Identification of Eimeria mitis and Eimeria praecox in broiler feces using polymerase chain reaction

There are few reports concerning the epidemiology of Eimeria praecox and Eimeria mitis in Brazil. In the present experiment, the polymerase chain reaction (PCR) was used to identify these species in 156 samples of broiler chicken feces from several Brazilian states and the Federal District. Oocysts present in feces samples were purified by sodium chloride flotation followed by addition of DNAzol reagent (Invitrogen®) for extraction of genomic DNA. DNA was precipitated and stored following DNAzol reagent manufacture's instructions. The primers and PCR conditions were as described by Schnitzler et al. (1999). In the 156 field samples analyzed by PCR, 70 and 45 were positive for E. praecox and E. mitis, respectively. In this study we have shown that DNA extraction using DNAzol followed by PCR can be a useful tool in epidemiological studies, since it provides fast and reliable detection of Eimeria sp. in field samples.

Measurements of gunshot residues by sector field inductively coupled plasma mass spectrometry - Further studies with pistols

The most popular handgun in Brazil is the single round-barrel caliber 0.38 revolver. In recent years, however, owing to the modernization of police arms and their availability on the legal and illicit markets, pistols have become increasingly popular and currently represent about 20% of police seizures. In a previous paper we presented a novel collection method for gunshot residues (GSR) using a sampling procedure based on ethylenediamine-tetraacetic acid (EDTA) solution as a complexing agent on moistened swabs with subsequent detection using sector field-high resolution-inductively coupled plasma-mass spectrometry (SF-HR-ICP-MS). In the present paper, we discuss the capability of this methodology to identify antimony (Sb), barium (Ba) and lead (Pb) on the hands of volunteers after shot tests with 9 mm and 0.40 in. caliber pistols. Two types of munitions were tested: 9 mm Taurus and clean range. The use of a technique with high sensitivity, such as SF-HR-ICP-MS, permits the identification of low concentrations (less than 1 mu g/L) of metals in firearm residue and constitutes a powerful tool in forensic science. We also discuss the importance of the sampling procedure, including collection from a different body part than the gun hand of the suspect. Comparison of the analytical data obtained allows clear discrimination between samples from the hands of shooters and non-shooters. (C) 2007 Elsevier B.V.. All rights reserved.

Evaluation and identification of lightning models by artificial neural networks

This paper describes a novel approach for mapping lightning models using artificial neural networks. The networks acts as identifier of structural features of the lightning models so that output parameters can be estimated and generalized from an input parameter set. Simulation examples are presented to validate the proposed approach. More specifically, the neural networks are used to compute electrical field intensity and critical disruptive voltage taking into account several atmospheric and structural factors, such as pressure, temperature, humidity, distance between phases, height of bus bars, and wave forms. A comparative analysis with other approaches is also provided to illustrate this new methodology.

Modeling and identification of fertility maps using artificial neural networks

The application of agricultural fertilizers using variable rates along the field can be made through fertility maps previously elaborated or through real-time sensors. In most of the cases applies maps previously elaborated. These maps are identified from analyzes done in soil samples collected regularly (a sample for each field cell) or irregularly along the field. At the moment, mathematical interpolation methods such as nearest neighbor, local average, weighted inverse distance, contouring and kriging are used for predicting the variables involved with elaboration of fertility maps. However, some of these methods present deficiencies that can generate different fertility maps for a same data set. Moreover, such methods can generate inprecise maps to be used in precision farming. In this paper, artificial neural networks have been applied for elaboration and identification of precise fertility maps which can reduce the production costs and environmental impacts.