Non-Linear Unsteady Aerodynamic Response Approximation Using Multi-Layer Functionals

Non-linear functional representation of the aerodynamic response provides a convenient mathematical model for motion-induced unsteady transonic aerodynamic loads response, that accounts for both complex non-linearities and time-history effects. A recent development, based on functional approximation theory, has established a novel functional form; namely, the multi-layer functional. For a large class of non-linear dynamic systems, such multi-layer functional representations can be realised via finite impulse response (FIR) neural networks. Identification of an appropriate FIR neural network model is facilitated by means of a supervised training process in which a limited sample of system input-output data sets is presented to the temporal neural network. The present work describes a procedure for the systematic identification of parameterised neural network models of motion-induced unsteady transonic aerodynamic loads response. The training process is based on a conventional genetic algorithm to optimise the network architecture, combined with a simplified random search algorithm to update weight and bias values. Application of the scheme to representative transonic aerodynamic loads response data for a bidimensional airfoil executing finite-amplitude motion in transonic flow is used to demonstrate the feasibility of the approach. The approach is shown to furnish a satisfactory generalisation property to different motion histories over a range of Mach numbers in the transonic regime.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Redes neurais e suas aplicações em calibração multivariada

Neural Networks are a set of mathematical methods and computer programs designed to simulate the information process and the knowledge acquisition of the human brain. In last years its application in chemistry is increasing significantly, due the special characteristics for model complex systems. The basic principles of two types of neural networks, the multi-layer perceptrons and radial basis functions, are introduced, as well as, a pruning approach to architecture optimization. Two analytical applications based on near infrared spectroscopy are presented, the first one for determination of nitrogen content in wheat leaves using multi-layer perceptrons networks and second one for determination of BRIX in sugar cane juices using radial basis functions networks.

Outbreak of infectious laryngotracheitis in large multi-age egg layer chicken flocks in Minas Gerais, Brazil

A recent (November 2010) outbreak of infectious laryngotracheitis (ILT) in a multi-age laying hen facility in Minas Gerais state, Brazil, is described. Previous ILT outbreak in laying hens was only notified in São Paulo state, Brazil, in 2002. In the outbreak described here, the affected population was approximately eight million hens, with flock sizes ranging from 100,000 to 2,900,000 chickens. The average mortality ranged from 1 to 6%, and morbidity was around 90% (most of the twenty seven farms of the area were positive for ILT virus). Three multi-age laying farms from one company were selected for this report. Clinical signs included prostration, dyspnea, conjunctivitis, occasional swelling of the paranasal sinuses and bloody mucous nasal discharge. Severely affected chickens presented with dyspnea, gasping and became cyanotic before death. At necropsy, these chickens had fibrinous exudate blocking the larynx and the lumen of cranial part of the trachea. In addition, conjunctivitis with intense hyperemia, edema and sinuses with caseous exudate were present. On histopathology, there were marked necrosis and desquamation of respiratory ephitelium and conjunctiva with numerous syncytial cells formation and fibrinous exudate. Moderate to marked non suppurative (especially lymphocytes and plasma cells) infiltration in the lamina propria also was observed. Sixteen out of 20 examined chickens, eosinophilic intranuclear inclusion bodies were observed in the syncytial cells. The DNA extracted from larynx and trachea produced positive PCR results for ILT virus (ILTV) DNA using formalin-fixed, paraffin embedded (FFPE) samples. Amplicons from a small region of ICP4 gene were submitted to sequencing and showed 100% identity with ILTV EU104910.1 (USA strain), 99% with ILTV JN596963.1 (Australian strain) and 91% with ILTV JN580316.1 (Gallid herpesvirus 1 CEO vaccine strain) and JN580315.1 (Gallid herpesvirus 1 TCO vaccine strain).

Multi-level governance and social cohesion in the European Union: the assessment of local agents, a study case inside Galicia

Implementing multi-level governance has been a key priority in EU cohesion policy. This study assesses the perceived achievements and shortcomings in implementing European Social Fund by analyzing the deficits and weaknesses as well as the poor participation of local agents who are in direct contact with the beneficiaries in order to design and implement this fund, which is the main financial instrument of EU social policy.

Soil mineral N dynamics beneath mixtures of leaves from legume and fruit trees in Central Amazonian multi-strata agroforests

Long term applications of leguminous green mulch could increase mineralizable nitrogen (N) beneath cupuaçu trees produced on the infertile acidic Ultisols and Oxisols of the Amazon Basin. However, low quality standing cupuaçu litter could interfere with green mulch N release and soil N mineralization. This study compared mineral N, total N, and microbial biomass N beneath cupuaçu trees grown in two different agroforestry systems, north of Manaus, Brazil, following seven years of different green mulch application rates. To test for net interactions between green mulch and cupuaçu litter, dried gliricidia and inga leaves were mixed with senescent cupuaçu leaves, surface applied to an Oxisol soil, and incubated in a greenhouse for 162 days. Leaf decomposition, N release and soil N mineralization were periodically measured in the mixed species litter treatments and compared to single species applications. The effect of legume biomass and cupuaçu litter on soil mineral N was additive implying that recommendations for green mulch applications to cupuaçu trees can be based on N dynamics of individual green mulch species. Results demonstrated that residue quality, not quantity, was the dominant factor affecting the rate of N release from leaves and soil N mineralization in a controlled environment. In the field, complex N cycling and other factors, including soil fauna, roots, and microclimatic effects, had a stronger influence on available soil N than residue quality.

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Given the limitations of different types of remote sensing images, automated land-cover classifications of the Amazon várzea may yield poor accuracy indexes. One way to improve accuracy is through the combination of images from different sensors, by either image fusion or multi-sensor classifications. Therefore, the objective of this study was to determine which classification method is more efficient in improving land cover classification accuracies for the Amazon várzea and similar wetland environments - (a) synthetically fused optical and SAR images or (b) multi-sensor classification of paired SAR and optical images. Land cover classifications based on images from a single sensor (Landsat TM or Radarsat-2) are compared with multi-sensor and image fusion classifications. Object-based image analyses (OBIA) and the J.48 data-mining algorithm were used for automated classification, and classification accuracies were assessed using the kappa index of agreement and the recently proposed allocation and quantity disagreement measures. Overall, optical-based classifications had better accuracy than SAR-based classifications. Once both datasets were combined using the multi-sensor approach, there was a 2% decrease in allocation disagreement, as the method was able to overcome part of the limitations present in both images. Accuracy decreased when image fusion methods were used, however. We therefore concluded that the multi-sensor classification method is more appropriate for classifying land cover in the Amazon várzea.

Síndrome Metabólica, Strain e Redução da Função Miocárdica: Multi-Ethnic Study of Atherosclerosis

Fundamento: A doença cardiovascular subclínica é prevalente em pacientes com síndrome metabólica (SM). O strain circunferencial (εCC) e o strain longitudinal (εLL) do ventriculo esquerdo (VE), avaliados pelo ecocardiograma com speckle tracking (STE), são índices de função sistólica: o encurtamento das fibras circunferenciais e longitudinais do VE é indicado por um valor negativo do strain. Portanto, quanto mais negativo o strain, melhor a função sistólica do VE. O εCC e o εLL têm sido usados para demonstrar disfunção ventricular subclínica em vários distúrbios clínicos. Objetivo: Levantamos a hipótese de que a SM está associada com comprometimento da função miocárdica, quando avaliada pelo STE. Métodos: Este estudo analisou participantes do Multi-Ethnic Study of Atherosclerosis (MESA) que realizaram o STE e foram avaliados para todos os componentes da SM. Resultados: Entre os 133 participantes incluídos (mulheres: 63%; idade: 65 ± 9 anos), a prevalência de SM foi de 31% (41/133). Indivíduos com SM apresentaram valores menores do εCC e do εLL que aqueles sem SM (-16,3% ± 3,5% vs. -18,4% ± 3,7%, p < 0,01; e -12,1% ± 2,5% vs. -13,9% ± 2,3%, p < 0,01, respectivamente). A fração de ejeção do VE (FEVE) foi semelhante nos dois grupos (p = 0,09). Na análise multivariada, a SM associou-se a um valor mais baixo do strain circunferencial (B = 2,1%, IC 95%: 0,6-3,5; p < 0,01), mesmo após ajuste para idade, etnia, massa VE e FEVE. De maneira semelhante, a presença de SM (B = 1,3%, IC 95%: 0,3-2,2; p < 0,01) e a massa do VE (B = 0,02%, IC 95%: 0,01 0,03; p = 0,02) associaram-se a um valor menor do strain longitudinal após ajuste para etnia, FEVE e creatinina. Conclusão: O εCC e o εLL do VE, marcadores de doença cardiovascular subclínica, estão comprometidos em indivíduos assintomáticos com SM e sem história prévia de infarto miocárdico, insuficiência cardíaca e/ou de FEVE < 50%.

Vaccination against schistosomiasis and fascioliasis with the new recombinant antigen Sm14: potential basis of a multi-valent anti-helminth vaccine?

Molecular cloning of components of protective antigenic preparations have suggested that related parasite fatty acid binding proteins could form the basis of the well documented protective, immune cross reactivity between the parasitic trematode worms Fasciola hepatica and Schistosoma mansoni. We have now confirmed the cross protective potential of parasite fatty acid binding proteins and suggest that it may be possible to produce a single vaccine that would be effective against at least two parasites, F. hepatica and S. mansoni of veterinary and human importance respectively.

Molecular Genetic Analysis of Multi-drug Resistance in Indian Isolates of Mycobacterium tuberculosis

A total of 116 isolates from patients attending the out-patient department at the All India Institute of Medical Sciences, New Delhi and the New Delhi Tuberculosis Centre, New Delhi, India were collected. They were analyzed for resistance to drugs prescribed in the treatment for tuberculosis. The drug resistance was initially determined by microbiological techniques. The Bactec 460TB system was employed to determine the type and level of resistance in each isolate. The isolates were further characterized at molecular level. The multi-drug loci corresponding to rpo b, gyr A, kat G were studied for mutation(s) by the polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) technique. The SSCP positive samples were sequenced to characterize the mutations in rpo b, and gyr A loci. While previously reported mutations in the gyr A and rpo b loci were found to be present, several novel mutations were also scored in the rpo b locus. Interestingly, analysis of the gyr A locus showed the presence of point mutation(s) that could not be detected by PCR-SSCP. Furthermore, rifampicin resistance was found to be an important marker for checking multi-drug resistance (MDR) in clinical isolates of Mycobacterium tuberculosis. This is the first report on molecular genetic analysis of MDR tuberculosis one from India, highlights the increasing incidence of MDR in the Indian isolates of M. tuberculosis.