Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

Numerical study on mixed convection in a horizontal flow past a square porous cavity using UNIFAES scheme

Mixed convection on the flow past a heated length and past a porous cavity located in a horizontal wall bounding a saturated porous medium is numerically simulated. The cavity is heated from below. The steady-state regime is studied for several intensities of the buoyancy effects due to temperature variations. The influences of Péclet and Rayleigh numbers on the flow pattern and the temperature distributions are examined. Local and global Nusselt numbers are reported for the heated surface. The convective-diffusive fluxes at the volume boundaries are represented using the UNIFAES, Unified Finite Approach Exponential-type Scheme, with the Power-Law approximation to reduce the computing time. The conditions established by Rivas for the quadratic order of accuracy of the central differencing to be maintained in irregular grids are shown to be extensible to other quadratic schemes, including UNIFAES, so that accuracy estimates could be obtained.

Bubble-Bubble Interaction in Horizontal Two-Phase Slug Flow

Modelling of the slug structure requires a new effort on fundamental research. To clarify some aspects of the horizontal slug flow, an experimental study of the behaviour of two isolated bubbles in a single-phase liquid flow was performed. This procedure was adopted to avoid the overlap of different phenomena induced by a train of long bubbles. The experimental facility consists of a 90-m horizontal PVC pipe with internal diameter of 0,053 m. The behaviour of two single air bubbles travelling in a water flow was studied. Focus was given on the influence of the distance between the bubbles on the velocity of the second bubble. This study allows the understanding of the mechanism of overtaking that takes place right after the slug formation and that precedes the coalescence of bubbles in a slug flow. The results show that bubbles placed behind a liquid slug smaller than a critical value move faster than the leading one. Otherwise, they move slower than the leading one.

Horizontal Slug Flow in a Large-Size Pipeline: Experimentation and Modeling

The knowledge of the slug flow characteristics is very important when designing pipelines and process equipment. When the intermittences typical in slug flow occurs, the fluctuations of the flow variables bring additional concern to the designer. Focusing on this subject the present work discloses the experimental data on slug flow characteristics occurring in a large-size, large-scale facility. The results were compared with data provided by mechanistic slug flow models in order to verify their reliability when modelling actual flow conditions. Experiments were done with natural gas and oil or water as the liquid phase. To compute the frequency and velocity of the slug cell and to calculate the length of the elongated bubble and liquid slug one used two pressure transducers measuring the pressure drop across the pipe diameter at different axial locations. A third pressure transducer measured the pressure drop between two axial location 200 m apart. The experimental data were compared with results of Camargo's1 algorithm (1991, 1993), which uses the basics of Dukler & Hubbard's (1975) slug flow model, and those calculated by the transient two-phase flow simulator OLGA.

Control of transients in water distribution networks by H¥ Control

In this work, a controller for regulating the transients in water distribution networks is established. The control technique is the H¥ Control. The developed controller is applied to a water distribution network and the results of this application demonstrate that the technique allowed the establishment of a robust controller, capable of attenuating the disturbances in a suitable way, being effective in controlling the oscillations of the state variables in question.

Horizontal and vertical tree community structure in a lowland atlantic rain forest, southeastern Brazil

The horizontal and vertical tree community structure in a lowland Atlantic Rain Forest was investigated through a phytosociological survey in two 0.99 ha plots in the Intervales State Park, São Paulo State. All trees > 5 cm diameter at breast height were recorded. 3,078 individuals belonging to 172 species were identified and recorded. The Shannon diversity index was H' = 3.85 nat.ind.-1. The Myrtaceae family showed the greatest floristic richness (38 species) and the highest density (745 individuals) in the stand. Euterpe edulis Mart. had the highest importance value (33.98%) accounting for 21.8% of all individuals recorded. The quantitative similarity index was higher than the qualitative index, showing little structural variation between plots. However, the large number of uncommon species resulted in pronounced floristic differences. A detrended correspondence analysis (DCA) generated three arbitrary vertical strata. Stratum A (> 26 m), where Sloanea guianensis (Aubl.) Benth. and Virola bicuhyba (Schott. ex A.DC.) Warb. were predominant showed the lowest density. Stratum B (8 m < h < 26 m) had the greatest richness and diversity, and stratum C (< 8 m) showed the highest density. Euterpe edulis, Guapira opposita (Vell.) Reitz, Garcinia gardneriana (Planch. & Triana) Zappi, and Eugenia mosenii (Kausel) Sobral were abundant in strata B and C. The occurrence of strata in tropical forests is discussed and we recommend the use of DCA for others studies of the vertical distribution of tropical forest tree communities.

Horizontal projections of area 17 in Cebus monkeys: metric features, and modular and laminar distribution

Metric features and modular and laminar distributions of intrinsic projections of area 17 were studied in Cebus apella. Anterogradely and retrogradely labeled cell appendages were obtained using both saturated pellets and iontophoretic injections of biocytin into the operculum. Laminar and modular distributions of the labeled processes were analyzed using Nissl counterstaining, and/or cytochrome oxidase and/or NADPH-diaphorase histochemistry. We distinguished three labeled cell types: pyramidal, star pyramidal and stellate cells located in supragranular cortical layers (principally in layers IIIa, IIIb a, IIIb ß and IIIc). Three distinct axon terminal morphologies were found, i.e., Ia, Ib and II located in granular and supragranular layers. Both complete and partial segregation of group I axon terminals relative to the limits of the blobs of V1 were found. The results are compatible with recent evidence of incomplete segregation of visual information flow in V1 of Old and New World primates

Effects of mercury intoxication on the response of horizontal cells of the retina of thraira fish (Hoplias malabaricus)

Methyl mercury (MeHg) is highly neurotoxic, affecting visual function in addition to other central nervous system functions. The effect of mercury intoxication on the amplitude of horizontal cell responses to light was studied in the retina of the fish Hoplias malabaricus. Intracellular responses were recorded from horizontal cells of fish previously intoxicated with MeHg by intraperitoneal injection (IP group) or by trophic exposure (T group). Only one retina per fish was used. The doses of MeHg chloride administered to the IP group were 0.01, 0.05, 0.1, 1.0, 2.0, and 6.0 mg/kg. The amplitudes of the horizontal cell responses were lower than control in individuals exposed to 0.01 (N = 4 retinas), 0.05 (N = 2 retinas) and 0.1 mg/kg (N = 1 retina), whereas no responses were recorded in the 1.0, 2.0, and 6.0 mg/kg groups. T group individuals were fed young specimens of Astyanax sp previously injected with MeHg corresponding to 0.75 (N = 1 retina), 0.075 (N = 8 retinas) or 0.0075 (N = 4 retinas) mg/kg fish body weight. After 14 doses, one every 5 days, the amplitude of the horizontal cell response was higher than control in individuals exposed to 0.075 and 0.0075 mg/kg, and lower in individuals exposed to 0.75 mg/kg. We conclude that intoxication with MeHg affects the electrophysiological response of the horizontal cells in the retina, either reducing or increasing its amplitude compared to control, and that these effects are related to the dose and/or to the mode of administration.

Synergistic control of forearm based on accelerometer data and artificial neural networks

In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941). For all other movements, prediction was low (range, 0.0316-0.8302). Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

Artificial neural networks (ANN): prediction of sensory measurements from instrumental data

The objective of this study was to predict by means of Artificial Neural Network (ANN), multilayer perceptrons, the texture attributes of light cheesecurds perceived by trained judges based on instrumental texture measurements. Inputs to the network were the instrumental texture measurements of light cheesecurd (imitative and fundamental parameters). Output variables were the sensory attributes consistency and spreadability. Nine light cheesecurd formulations composed of different combinations of fat and water were evaluated. The measurements obtained by the instrumental and sensory analyses of these formulations constituted the data set used for training and validation of the network. Network training was performed using a back-propagation algorithm. The network architecture selected was composed of 8-3-9-2 neurons in its layers, which quickly and accurately predicted the sensory texture attributes studied, showing a high correlation between the predicted and experimental values for the validation data set and excellent generalization ability, with a validation RMSE of 0.0506.