Chromosomes of Crossopriza lyoni (Blackwall 1867), intraindividual numerical chromosome variation in Physocyclus globosus (Taczanowski 1874), and the distribution pattern of NORs (Araneomorphae, Haplogynae, Pholcidae)

Pholcidae (Haplogynae) encompasses 967 described species, of which only 14 have been cytogenetic analyzed. Several chromosomal features have already been described including presence of meta- and sub-metacentric chromosomes and sex determination chromosome system (SDCS) of the X, X1X2Y, and X1X2 types, which contrast with the telo- and acrocentric chromosomes and SDCS of the X1X2 type typical of entelegyne spiders. To obtain further cytogenetic information for the family, we examined two pholcid species, Crossopriza lyoni (Blackwall 1867) and Physocyclus globosus (Taczanowski 1874) using both conventional staining and silver staining techniques. Crossopriza lyoni exhibited 2n = 23 = 22 + X in males and 2n = 24 = 22 + XX in females, while P. globosus showed 2n = 15 = 14 + X and 4n = 30 = 28 + 2X, both in male adults, 2n = 16 = 14 + XX in female adults and embryos, and 2n = 15 = 14 + X in male embryos. Both species revealed predominately metacentric and submetacentric chromosomes and a SDCS of the X/XX type. The cytogenetic data obtained in this work and those already recorded for C. lyoni indicate interpopulational and intraspecific numerical chromosome variation, suggesting the presence of chromosomal races or cytotypes in this species. The intraindividual numerical chromosome variation observed in male adult specimens of P. globosus may be explained by the presence of cytoplasmatic bridges between germ cells. The use of the silver staining technique to reveal the nucleolar organizer region (NOR) showed that chromosome pairs 4 and 6 and the X chromosome in C. lyoni are telomeric NOR-bearers, and that the chromosome pair 2 in P. globosus possesses a proximal NOR in the long arm.

Pattern of macrophage activation in yersinia-resistant and yersinia-susceptible strains of mice

Th1 cells, in cooperation with activated macrophages, are required to overcome Yersinia enterocolitica infection in mice. The pathway macrophages utilize to metabolize arginine can alter the outcome of inflammation in different ways. The objective of this study was to verify the pattern of macrophages activation in Y. enterocolitica infection of BALB/c (Yersinia-susceptible) and C57BL/6 (Yersinia-resistant) mice. Both strains of mice were infected with Y. enterocolitica O:8 WA 2707. Peritoneal macrophages and spleen cells were obtained on the 1st, 3rd and 5th day post-infection. The iNOS and the arginase activities were assayed in supernatants of macrophage cultures, by measuring their NO/citrulline and ornithine products, respectively. TGFβ-1 production was also assayed. The Th1 and Th2 responses were evaluated in supernatants of lymphocyte cultures, by IFN-γ and IL-4 production. Our results showed that in the early phase of Y. enterocolitica infection (1st and 3rd day), the macrophages from C57BL/6 mice produced higher levels of NO/citrulline and lower levels of ornithine than macrophages from BALB/c mice. The infection with Y. enterocolitica leads to an increase in the TGF-β1 and IL-4 production by BALB/c mice and to an increase in the IFN-γ levels produced by C57BL/6 mice. These results suggest that Y. enterocolitica infection leads to the modulation of M1 macrophages in C57Bl/6 mice, and M2 macrophages in BALB/c mice. The predominant macrophage population (M1 or M2) at the 1st and 3rd day of infection thus seems to be important in determining Y. enterocolitica susceptibility or resistance.

Pattern of silver nitrate-staining during meiosis and spermiogenesis in testicular lobes of Antiteuchus tripterus (Heteroptera: Pentatomidae)

The pattern of silver nitrate (Ag)-staining differed among testicular lobes of Antiteuchus tripterus. In general, these differences are in regard to the number, size, shape, coloring intensity, and location of the stained bodies or masses, observed during meiosis and spermiogenesis. These characteristics were similar in lobes 1-3. Lobes 4-6, however, differed from each other and from lobes 1-3 as well. Because the Ag-staining method is specific for nucleolar organizing regions and nucleolar material, the observations in meiosis of lobes 1-3 suggested the presence of a single pair of nucleolar organizing region-bearing chromosomes in A. tripterus, as previously found in other Pentatomidae species. In general, the amount of Ag-stained material seen in meiosis of the testicular lobes 1-3 of A. tripterus is smaller than in the other lobes. The differences among lobes observed during spermiogenesis included a striking variation in morphology of the Ag-stained material found in the head and tail of the spermatids. Given that the key role of the nucleolar material is to participate in protein synthesis, interlobular variations seem to be related to the different functions attributed to each lobe (reproduction to lobes 1-3 and basically nutrition to lobes 4-6). To our knowledge, this is the first time that the nucleolar material was studied in each testicular lobe during spermatogenesis. The present observations encourage further studies since, in addition to being of basic biological interest, several Pentatomidae species are agricultural pests and added knowledge of their biology, mainly in reproduction, may be important for the development of control strategies. ©FUNPEC-RP.

Comparative analysis of electromyographic pattern in the forearm muscles of hemiplegic patients

It was purposed the use of electromyography (EMG) to evaluate the activation of the agonists and antagonists muscles of spastic patients, to test the viability in the development of an instrument that given quantitative data of the patient spasticity. 30 hemiplegic and 15 normal volunteers had been submitted to the EMG of flexor and extensor carpi ulnaris muscles during the flexion and extension movements of the wrist. The individuals with less severe spasticity (mAS (modified Ashworth Scale) ringing 0 to 3 degree), had presented deficit in the activation of the flexor muscles in plegic side in relation to the non plegic side and that the individuals seriously compromised by the spasticity (mAS = 4 degree) present deficit of reciprocal inhibition. One evidenced is that the non plegic member does not present a similar neuro-motor comportment when compared to the normal member. The surface electromyography is a practical clinical instrument to evaluate the patient with spasticity and the hemiplegic patient needs to be evaluated on both sides (deficient and no deficient) because the no compromised side do not show a normality standard.

Routine libraries for pattern recognition in quasispecies.

The results obtained through biological research usually need to be analyzed using computational tools, since manual analysis becomes unfeasible due to the complexity and size of these results. For instance, the study of quasispecies frequently demands the analysis of several, very lengthy sequences of nucleotides and amino acids. Therefore, bioinformatics tools for the study of quasispecies are constantly being developed due to different problems found by biologists. In the present study, we address the development of a software tool for the evaluation of population diversity in quasispecies. Special attention is paid to the localization of genome regions prone to changes, as well as of possible hot spots.

Leg muscles recruitment pattern in soccer players and active individuals during isometric contractions

This study aimed to compare the torque, torque ratio (Hamstrings:Quadriceps - H:Q), electromyographic (EMG) activity and EMG ratio (knee flexors:knee extensors EMG) in soccer players (SG, N=10) and active subjects (AG, N=10). Subjects performed three maximal voluntary isometric knee extensions and flexions at 45° and 90° to determine the peak torque and EMG activity. Torque and EMG activity of the knee flexor (biceps femoris [BF] and semitendinosus [ST]) were divided by the torque and EMG activity of the knee extensor (vastuls lateralis [VL] and rectus femoris [RF]) to calculate torque ratios (H:Q) and EMG ratios (BF:VL, BF:RF, ST:VL, ST:RF). The flexion torque was significantly higher for SG (p<0.05) in 45° and 90°. EMG activity for SG was significantly higher in agonist contractions for VL, RF and ST, and significantly lower in antagonist contractions for RF and ST when compared to AG Torque and EMG ratios were similar between groups and there were good correlations between torque ratio and BF:VL ratio (r=0.71, p=0.02) and BF:RF ratio (r=0.81, p=0.004) at 45. The EMG results could overestimate the joint balance calculated using torque ratios. Differences in recruitment pattern between soccer players and non-athletes can be related to the training routines and the EMG ratios presents applicable in trained populations.

Fast non-technical losses identification through Optimum-Path Forest

Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as Artificial Neural Networks and Support Vector Machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the Optimum-Path Forest classifier for a fast non-technical losses recognition, which has been demonstrated to be superior than neural networks and similar to Support Vector Machines, but much faster. Comparisons among these classifiers are also presented. © 2009 IEEE.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Optimizing optimum-path forest classification for huge datasets

Traditional pattern recognition techniques can not handle the classification of large datasets with both efficiency and effectiveness. In this context, the Optimum-Path Forest (OPF) classifier was recently introduced, trying to achieve high recognition rates and low computational cost. Although OPF was much faster than Support Vector Machines for training, it was slightly slower for classification. In this paper, we present the Efficient OPF (EOPF), which is an enhanced and faster version of the traditional OPF, and validate it for the automatic recognition of white matter and gray matter in magnetic resonance images of the human brain. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.

Differences in dietary pattern between obese and eutrophic children

Background: Excessive consumption of energy is a decisive factor of obesity, but a simple quantitative assessment of consumption between obese and eutrophic individuals not always explains the problem, raising questions about the importance of the qualitative aspects of food. Therefore, the purpose of this study was to evaluate the differences in nutrient composition and meal patterns between eutrophic and obese schoolchildren. Methods. The diet of 83 children (42 obese and 41 eutrophic), aged between 7 and 11 years of age, was assessed by two non-consecutive dietary recalls. After the software analysis of macro and micronutrients composition, the different types and amount of legumes, fruits and vegetables were analyzed to verify the dietary patterns. Results: No differences were verified in energy consumption between the groups (eutrophic = 1934.2 672.7 kcal, obese = 1835.8 621.2 kcal). In general, children showed consumption within the recommended ranges of carbohydrates, lipids and proteins. The average consumption of fiber was higher in the eutrophic group (20.7 g) when compared to the obese group (14.8 g). The dietary fiber was strongly correlated with the number of servings of beans (r = 0.77), when compared to fruits (r = 0.44) and leafy vegetables (r = 0.13). It was also observed that the higher the consumption of fiber and beans, the lower the proportion of dietary fat (r = -0.22) in the diet. Generally, there was a low consumption of fiber (20.7 g = eutrophic group/14.8 g = obese group), beans (1.1 portions in the eutrophic and obese groups), fruits (0.7 portions eutrophic group and 0.6 obese group) and vegetables (1.3 eutrophic group and 1.1 obese group). Conclusions: It is concluded that the obesity was more related to a dietary pattern of low intake of dietary fiber than excessive energy consumption and macronutrients imbalance. © 2011 de Oliveira et al; licensee BioMed Central Ltd.

A snoring classifier based on heart rate variability analysis

The effect of snoring on the cardiovascular system is not well-known. In this study we analyzed the Heart Rate Variability (HRV) differences between light and heavy snorers. The experiments are done on the full-whole-night polysomnography (PSG) with ECG and audio channels from patient group (heavy snorer) and control group (light snorer), which are gender- and age-paired, totally 30 subjects. A feature Snoring Density (SND) of audio signal as classification criterion and HRV features are computed. Mann-Whitney statistical test and Support Vector Machine (SVM) classification are done to see the correlation. The result of this study shows that snoring has close impact on the HRV features. This result can provide a deeper insight into the physiological understand of snoring. © 2011 CCAL.