Morphological diversity of setae on the second maxilliped of fiddler crabs (Decapoda: Ocypodidae) from the southwestern Atlantic coast

Fiddler crabs are deposit feeders, and use the setae on their mouth appendages to manipulate sediment particles to extract food. The number of spoon-tipped setae on the second maxilliped is frequently related to the distribution of fiddler crabs on estuarine sediments, but no study has compared the morphological diversity of these setae among multiple fiddler crab species. Here, we describe and classify the setae of the second maxillipeds of the nine Uca spp. known from the Brazilian coast. The second maxilliped of each species was examined by scanning electron microscopy. Six types of setae (five papposerrate, and one pappose) were described on the meropodite of the second maxilliped. Among the papposerrate setae, one type had a spoon-like tip, and the morphology of this type, especially the degree of curvature, differed between species. Members of Uca leptodactylus, U. uruguayensis, and U. maracoani had highly concave spoon-tipped setae. In U. rapax and U. cumulanta, the setal tip was moderately curved, while in U. thayeri, U. burgersi, and U. mordax, this curvature was slight. At the other extreme, the meropodite of the second maxilliped of U. vocator lacked setae altogether. This is the first study that describes differences in the degree of curvature of spoon-tipped setae in fiddler crabs. This trait may be strongly related to the distribution of these fiddler crabs on different estuarine substrates. © 2012, The American Microscopical Society, Inc.

Characterization of esterase patterns in hepatopancreas of three species of Macrobrachium (Palaemonidae)

The genus Macrobrachium (Bate, 1868) belongs to the Palaemonidae family. These species are commonly found in lakes, floodplains and rivers in tropical and subtropical regions of South America. The Macrobrachium genus encompasses nearly 210 species of ecological and economic importance. In this study, three species of Macrobrachium (M acrobrachium jelskii, M acrobrachium amazonicum and M acrobrachium brasiliense) were studied in order to characterize the esterase patterns in the hepatopancreas, which were still unknown. Esterases are enzymes which catalyze the hydrolysis of esters. In the hepatopancreas, these enzymes play important roles in several metabolic processes involved in some functions of this organ, such as detoxification and digestion. Twelve esterase bands (EST1 to EST12) were detected in these species, and a comparison among them showed no qualitative differences in interspecific bands, or between males and females. Inhibitors were used to classify the esterase bands. The results indicated seven acetylesterases, two carboxylesterases, one arylesterase, and one cholinesterase. The EST11 band was not detected in these procedures because of its lower frequency. Statistical analyses showed no variability among the species, in either interspecific or intraspecific assays. These results support the hypothesis of a high evolutionary conservation of esterases in the hepatopancreas of these crustaceans. The data enabled us to assess the genetic structure of these species through the use of esterasic enzymes. It also contributes to our knowledge about the biology of these poorly studied species. Knowledge on the genetic structure of populations and species are essential when defining priorities for their management and conservation. © 2012 Elsevier Ltd.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

The Development of a Universal In Silico Predictor of Protein-Protein Interactions

Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

Automatic microstructural characterization and classification using artificial intelligence techniques on ultrasound signals

Secondary phases such as Laves and carbides are formed during the final solidification stages of nickel based superalloy coatings deposited during the gas tungsten arc welding cold wire process. However, when aged at high temperatures, other phases can precipitate in the microstructure, like the γ″ and δ phases. This work presents a new application and evaluation of artificial intelligent techniques to classify (the background echo and backscattered) ultrasound signals in order to characterize the microstructure of a Ni-based alloy thermally aged at 650 and 950 °C for 10, 100 and 200 h. The background echo and backscattered ultrasound signals were acquired using transducers with frequencies of 4 and 5 MHz. Thus with the use of features extraction techniques, i.e.; detrended fluctuation analysis and the Hurst method, the accuracy and speed in the classification of the secondary phases from ultrasound signals could be studied. The classifiers under study were the recent optimum-path forest (OPF) and the more traditional support vector machines and Bayesian. The experimental results revealed that the OPF classifier was the fastest and most reliable. In addition, the OPF classifier revealed to be a valid and adequate tool for microstructure characterization through ultrasound signals classification due to its speed, sensitivity, accuracy and reliability. © 2013 Elsevier B.V. All rights reserved.

Acute toxicity and environmental risk of teflubenzuron to Daphnia magna, Poecilia reticulata and Lemna minor in the absence and presence of sediment

This study aimed to estimate the acute toxicity of teflubenzuron (1-(3,5-dichloro-2,4-difluorophenyl)-3-(2,6-difluorobenzoyl)urea) (TFB) for Daphnia magna, Lemna minor and Poecilia reticulata, in the absence and presence of sediment; evaluate the effect of sediment on the TFB bioavailability; and to classify this insecticide according to its environmental poisoning risk for agricultural and aquaculture uses. The tests of TFB acute toxicity were conducted in static system in a completely randomized design with increasing TFB concentrations, and a control group. The TFB has been classified according to the estimated values of EC50 and LC50 by its acute toxicity and environmental risk. The sediment significantly reduced toxicity and bioavailability of TFB in water column. Therefore, the insecticide can be classified as being highly toxic to Daphnia magna, which means the agricultural and aquacultural uses of TFB pose a high risk of environmental toxicity to non-target organisms. However, it was practically non-toxic to L. minor and P. reticulata. © 2013 Copyright Taylor and Francis Group, LLC.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Validity and feasibility of qualitative behavior assessment for the evaluation of Nellore cattle temperament

The aims of this study were to assess the validity and the feasibility of the qualitative behavior assessment (QBA) method as indicator of Nellore cattle temperament under field conditions, evaluating its associations with four other traditional methods and weight gain. The temperament and live weight of 2229 Nellore cattle was assessed at approximately 550 days of age. Five measurements of cattle temperament were recorded: flight speed test (FS, in m/s), visual scores of movement in the crush (MOV), crush score (CS), temperament score (TS), and the qualitative behavior assessment method (QBA), by using a list of 12 behavioral based adjectives as descriptors of temperament. Average daily weight gain (ADG) was calculated for each animal. For statistical analysis of QBA data, the Principal Component Analysis was used. A temperament index (TI) was defined for each animal using the scores for the first principal component. Pearson's correlation coefficients were estimated between TI with FS and ADG. A mixed model ANOVA was used to analyze the TI variation as a function of TS, CS, and MOV. The score plot for the first and second principal components was used to classify the cattle in four groups (from very bad to very good temperament). The first principal component explained 49.50% of the variation in the data set, with higher positive loadings for the adjectives 'agitated' and 'active', and higher negative loadings for 'calm' and 'relaxed'. TI was significantly correlated with FS (r=0.49; P<0.01) and ADG (r=-0.10; P<0.01). The means of ADG, FS, and the temperament scores (CS, TS, MOV) differed significantly (P<0.01) among the four groups, from very bad to very good temperament. The QBA method could discriminate different behavioral profiles of Nellore cattle and were in agreement with other traditional methods used as indicators of cattle temperament. Additional studies are needed to assess the inter- and intra-observers reliability and to study its association with physiological parameters. © 2013 Elsevier B.V.

Automatic segmentation and classification of human intestinal parasites from microscopy images

Human intestinal parasites constitute a problem in most tropical countries, causing death or physical and mental disorders. Their diagnosis usually relies on the visual analysis of microscopy images, with error rates that may range from moderate to high. The problem has been addressed via computational image analysis, but only for a few species and images free of fecal impurities. In routine, fecal impurities are a real challenge for automatic image analysis. We have circumvented this problem by a method that can segment and classify, from bright field microscopy images with fecal impurities, the 15 most common species of protozoan cysts, helminth eggs, and larvae in Brazil. Our approach exploits ellipse matching and image foresting transform for image segmentation, multiple object descriptors and their optimum combination by genetic programming for object representation, and the optimum-path forest classifier for object recognition. The results indicate that our method is a promising approach toward the fully automation of the enteroparasitosis diagnosis. © 2012 IEEE.

The functional biogeography of species: Biogeographical species roles of birds in Wallacea and the West Indies

Biogeographical systems can be analyzed as networks of species and geographical units. Within such a biogeographical network, individual species may differ fundamentally in their linkage pattern, and therefore hold different topological roles. To advance our understanding of the relationship between species traits and large-scale species distribution patterns in archipelagos, we use a network approach to classify birds as one of four biogeographical species roles: peripherals, connectors, module hubs, and network hubs. These roles are based upon the position of species within the modular network of islands and species in Wallacea and the West Indies. We test whether species traits - including habitat requirements, altitudinal range-span, feeding guild, trophic level, and body length - correlate with species roles. In both archipelagos, habitat requirements, altitudinal range-span and body length show strong relations to species roles. In particular, species that occupy coastal- and open habitats, as well as habitat generalists, show higher proportions of connectors and network hubs and thus tend to span several biogeographical modules (i.e. subregions). Likewise, large body size and a wide altitudinal range-span are related to a wide distribution on many islands and across several biogeographical modules. On the other hand, species restricted to interior forest are mainly characterized as peripherals and, thus, have narrow and localized distributions within biogeographical modules rather than across the archipelago-wide network. These results suggest that the ecological amplitude of a species is highly related to its geographical distribution within and across bio geographical subregions and furthermore supports the idea that large-scale species distributions relate to distributions at the local community level. We finally discuss how our biogeographical species roles may correspond to the stages of the taxon cycle and other prominent theories of species assembly. © 2013 The Authors.

Temporomandibular disorders, sleep bruxism, and primary headaches are mutually associated.

To investigate the association among temporomandibular disorders (TMD), sleep bruxism, and primary headaches, assessing the risk of occurrence of primary headaches in patients with or without painful TMD and sleep bruxism. The sample consisted of 301 individuals (253 women and 48 men) with ages varying from 18 to 76 years old (average age of 37.5 years). The Research Diagnostic Criteria for Temporomandibular Disorders were used to classify TMD. Sleep bruxism was diagnosed by clinical criteria proposed by the American Academy of Sleep Medicine, and primary headaches were diagnosed according to the International Classification of Headache Disorders-II. Data were analyzed by chi-square and odds ratio tests with a 95% confidence interval, and the significance level adopted was .05. An association was found among painful TMD, migraine, and tension-type headache (P < .01). The magnitude of association was higher for chronic migraine (odds ratio = 95.9; 95% confidence intervals = 12.51-734.64), followed by episodic migraine (7.0; 3.45-14.22) and episodic tension-type headache (3.7; 1.59-8.75). With regard to sleep bruxism, the association was significant only for chronic migraine (3.8; 1.83-7.84). When the sample was stratified by the presence of sleep bruxism and painful TMD, only the presence of sleep bruxism did not increase the risk for any type of headache. The presence of painful TMD without sleep bruxism significantly increased the risk in particular for chronic migraine (30.1; 3.58-252.81), followed by episodic migraine (3.7; 1.46-9.16). The association between painful TMD and sleep bruxism significantly increased the risk for chronic migraine (87.1; 10.79-702.18), followed by episodic migraine (6.7; 2.79-15.98) and episodic tension-type headache (3.8; 1.38-10.69). The association of sleep bruxism and painful TMD greatly increased the risk for episodic migraine, episodic tension-type headache, and especially for chronic migraine.

Caracterização e classificação da deglutição orofaríngea do idoso institucionalizado: avaliaçao clínica fonoaudiológica

Pós-graduação em Bases Gerais da Cirurgia - FMB

Avaliação ecotoxicológica e risco ambiental dos inseticidas utilizados no controle da larva de Aedes aegypti para Daphnia magna, Lemna minor e peixes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Toxicidade aguda e risco ambiental do diflubenzuron para Daphnia magna, Poecilia reticulata e Lemna minor na ausência e presença de sedimento

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ecotoxicidade e eficácia da oxitetraciclina e do florfenicol contra infecção experimental por Aeromonas hydrophila e aspectos histopatológicos em pacu (Piaractus mesopotamicus)

Pós-graduação em Aquicultura - FCAV