Neural network model for designing automotive devices using SMD LED

The advantages offered by the electronic component LED (Light Emitting Diode) have resulted in a quick and extensive application of this device in the replacement of incandescent lights. In this combined application, however, the relationship between the design variables and the desired effect or result is very complex and renders it difficult to model using conventional techniques. This paper consists of the development of a technique using artificial neural networks that makes it possible to obtain the luminous intensity values of brake lights using SMD (Surface Mounted Device) LEDs from design data. This technique can be utilized to design any automotive device that uses groups of SMD LEDs. The results of industrial applications using SMD LED are presented to validate the proposed technique.

An approach based on neural networks for estimation and generalization of crossflow filtration processes

The crossflow filtration process differs of the conventional filtration by presenting the circulation flow tangentially to the filtration surface. The conventional mathematical models used to represent the process have some limitations in relation to the identification and generalization of the system behaviour. In this paper, a system based on artificial neural networks is developed to overcome the problems usually found in the conventional mathematical models. More specifically, the developed system uses an artificial neural network that simulates the behaviour of the crossflow filtration process in a robust way. Imprecisions and uncertainties associated with the measurements made on the system are automatically incorporated in the neural approach. Simulation results are presented to justify the validity of the proposed approach. (C) 2007 Elsevier B.V. All rights reserved.

Gait Pattern Adaptation for an Active Lower-Limb Orthosis Based on Neural Networks

This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011

Neural network-based H(infinity) control for fully actuated and underactuated cooperative manipulators

This paper develops H(infinity) control designs based on neural networks for fully actuated and underactuated cooperative manipulators. The neural networks proposed in this paper only adapt the uncertain dynamics of the robot manipulators. They work as a complement of the nominal model. The H(infinity) performance index includes the position errors as well the squeeze force errors between the manipulator end-effectors and the object, which represents a complete disturbance rejection scenario. For the underactuated case, the squeeze force control problem is more difficult to solve due to the loss of some degrees of manipulator actuation. Results obtained from an actual cooperative manipulator, which is able to work as a fully actuated and an underactuated manipulator, are presented. (C) 2008 Elsevier Ltd. All rights reserved.

Artificial neural networks analysis of Sao Paulo subway tunnel settlement data

Artificial neural networks have been used to analyze a number of engineering problems, including settlement caused by different tunneling methods in various types of ground mass. This paper focuses on settlement over shotcrete- supported tunnels on Sao Paulo subway line 2 (West Extension) that were excavated in Tertiary sediments using the sequential excavation method. The adjusted network is a good tool for predicting settlement above new tunnels to be excavated in similar conditions. The influence of network training parameters on the quality of results is also discussed. (C) 2007 Elsevier Ltd. All rights reserved.

Transmission lines distance protection using artificial neural networks

This work presents the development and implementation of an artificial neural network based algorithm for transmission lines distance protection. This algorithm was developed to be used in any transmission line regardless of its configuration or voltage level. The described ANN-based algorithm does not need any topology adaptation or ANN parameters adjustment when applied to different electrical systems. This feature makes this solution unique since all ANN-based solutions presented until now were developed for particular transmission lines, which means that those solutions cannot be implemented in commercial relays. (c) 2011 Elsevier Ltd. All rights reserved.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Treatment of Aqueous Effluents Containing Phenol by the O(3), O(3)-UV, and O(3)-H(2)O(2) Processes: Experimental Study and Neural Network Modeling

In this work, the oxidation of the model pollutant phenol has been studied by means of the O(3), O(3)-UV, and O(3)-H(2)O(2) processes. Experiments were carried out in a fed-batch system to investigate the effects of initial dissolved organic carbon concentration, initial, ozone concentration in the gas phase, the presence or absence of UVC radiation, and initial hydrogen peroxide concentration. Experimental results were used in the modeling of the degradation processes by neural networks in order to simulate DOC-time profiles and evaluate the relative importance of process variables.

Network of phase-locking oscillators and a possible model for neural synchronization

In order to model the synchronization of brain signals, a three-node fully-connected network is presented. The nodes are considered to be voltage control oscillator neurons (VCON) allowing to conjecture about how the whole process depends on synaptic gains, free-running frequencies and delays. The VCON, represented by phase-locked loops (PLL), are fully-connected and, as a consequence, an asymptotically stable synchronous state appears. Here, an expression for the synchronous state frequency is derived and the parameter dependence of its stability is discussed. Numerical simulations are performed providing conditions for the use of the derived formulae. Model differential equations are hard to be analytically treated, but some simplifying assumptions combined with simulations provide an alternative formulation for the long-term behavior of the fully-connected VCON network. Regarding this kind of network as models for brain frequency signal processing, with each PLL representing a neuron (VCON), conditions for their synchronization are proposed, considering the different bands of brain activity signals and relating them to synaptic gains, delays and free-running frequencies. For the delta waves, the synchronous state depends strongly on the delays. However, for alpha, beta and theta waves, the free-running individual frequencies determine the synchronous state. (C) 2011 Elsevier B.V. All rights reserved.

Spectral characteristics of atrial electrograms in sinus rhythm correlates with sites of ganglionated plexuses in patients with paroxysmal atrial fibrillation

Aims To verify whether spectral components of atrial electrograms (AE) during sinus rhythm (SR) correlate with cardiac ganglionated plexus (GP) sites. Methods and results Thirteen patients undergoing atrial fibrillation (AF) ablation were prospectively enrolled. Prior to radio frequency application, endocardial AE were recorded with a sequential point-by-point approach. Electrical stimuli were delivered at 20 Hz, amplitude 100 V, and pulse width of 4 ms. A vagal response was defined as a high-frequency stimulation (HFS) evoked atrioventricular block or a prolongation of RR interval. Spectral analysis was performed on single AE during SR, sampling rate of 1000 Hz, Hanning window. Overall, 1488 SR electrograms were analysed from 186 different left atrium sites, 129 of them corresponding to negative vagal response sites, and 57 to positive response sites. The electrogram duration and the number of deflections were similar in positive and negative response sites. Spectral power density of sites with vagal response was lower between 26 and 83 Hz and higher between 107 and 200 Hz compared with negative response sites. The area between 120 and 170 Hz normalized to the total spectrum area was tested as a diagnostic parameter. Receiver operating characteristic curve analysis demonstrated that an area120-170/area(total) value >0.14 identified vagal sites with 70.9% sensitivity and 72.1% specificity. Conclusion Spectral analysis of AE during SR in sites that correspond to the anatomical location of the GP is feasible and may be a simpler method of mapping the cardiac autonomic nervous system, compared with the HFS technique.

Cell surface expression of adhesins for fibronectin correlates with virulence in Sporothrix schenckii

The virulence of four Sporothrix schenckii isolates was compared in a murine model of sporotrichosis, together with the protein pattern of the yeast cell surface and the capacity to bind the extracellular matrix protein fibronectin. Virulence was determined by the mortality rate, fungal burden and histopathology. Two clinical isolates were more virulent for C57BL/6 mice, but no direct correlation was seen between virulence and the clinical or environmental origin of the isolates. The lowest virulence was observed for an isolate recovered from a patient with meningeal sporotrichosis. Although all isolates could effectively disseminate, the dissemination patterns were not similar. Using flow cytometry analysis, we investigated the interaction of all the strains with fibronectin, and showed that the binding capacity correlated with virulence. Western blot analysis of S. schenckii cell wall extracts revealed positive bands for fibronectin in the range of 3792 kDa. The 70 kDa adhesin was also recognized by a protective monoclonal antibody raised against a gp70 antigen of S. schenckii (mAb P6E7). Confocal microscopy confirmed the co-localization of fibronectin and mAb P6E7 on the yeast cell surface. To our knowledge, this is the first report identifying adhesins for fibronectin on the surface of this human pathogen.

L-Allylglycine dissociates the neural substrates of fear in the periaqueductal gray of rats

The dorsal (dPAG) and ventral (vPAG) regions of the periaqueductal gray are well known to contain the neural substrates of fear and anxiety. Chemical or electrical stimulation of the dPAG induces freezing, followed by a robust behavioral reaction that has been considered an animal model of panic attack. In contrast, the vPAG is part of a neural system, in which immobility is the usual response to its stimulation. The defense reaction induced by the stimulation of either region is accompanied by anti nociception. Although GABAergic mechanisms are known to exert tonic inhibitory control on the neural substrates of fear in the dPAG, the role of these mechanisms in the vPAG is still unclear. The present study examined defensive behaviors and antinociception induced by microinjections of an inhibitor of gamma-aminobutyric acid synthesis, L-allylglycine (L-AG; 1, 3, and 5 mu g/0.2 mu l), into either the dPAG or vPAG of rats subjected to the open field and tail-flick tests. Passive or tense immobility was the predominant behavior after L-AG (1 or 3 mu g) microinjection into the vPAG and dPAG, respectively, which was replaced with intense hyperactivity, including jumps or rearings, after injections of a higher dose (5 mu g/0.2 mu l) into the dPAG or vPAG. Moreover, whereas intra-dPAG injection of 3 mu g L-AG produced intense antinociception, only weak antinociception was induced by intra-vPAG injections of 5 mu g L-AG. These findings suggest that GABA mechanisms are involved in the mediation of antinociception and behavioral inhibition to aversive stimulation of the vPAG and exert powerful control over the neural substrates of fear in the dPAG to prevent a full-blown defense reaction possibly associated with panic disorder. (C) 2009 Elsevier Inc. All rights reserved.

Structural and Biochemical Correlates of Na(+), K(+)-ATPase Driven Ion Uptake Across the Posterior Gill Epithelium of the True Freshwater Crab, Dilocarcinus pagei (Brachyura, Trichodactylidae)

To better comprehend the structural and biochemical underpinnings of ion uptake across the gills of true freshwater crabs, we performed an ultrastructural, ultracytochemical and morphometric investigation, and kinetically characterized the Na(+), K(+)-ATPase, in posterior gill lamellae of Dilocarcinus pagei. Ultrastructurally, the lamellar epithelia are markedly asymmetrical: the thick, mushroom-shaped, proximal ionocytes contain elongate mitochondria (41% cell volume) associated with numerous (approximate to 14 mu m(2) membrane per mu m(3) cytoplasm), deep invaginations that house the Na(+), K(+)-ATPase, revealed ultracytochemically. Their apical surface is amplified (7.5 mu m(2) mu m(-2)) by stubby evaginations whose bases adjoin mitochondria below the subcuticular space. The apical membrane of the thin, distal ionocytes shows few evaginations (1.6 mu m(2) mu m(-2)), each surrounding a mitochondrion, abundant in the cytoplasm below the subcuticular space; basolateral invaginations and mitochondria are few. Fine basal cytoplasmic bridges project across the hemolymph space, penetrating into the thick ionocytes, suggesting ion movement between the epithelia. Microsomal Na(+), K(+)-ATPase specific activity resembles marine crabs but is approximate to 5-fold less than in species from fluctuating salinities, and freshwater shrimps, suggesting ion loss compensation by strategies other than Na(+) uptake. Enzyme apparent K(+) affinity attains 14-fold that of marine crabs, emphasizing the relevance of elevated K(+) affinity to the conquest of fresh water. Western blotting and biphasic ouabain inhibition disclose two alpha-subunit isoforms comprising distinct functional isoenzymes. While enzyme activity is not synergistically stimulated by NH(4)(+) and K(+), each increases affinity for the other, possibly assuring appropriate intracellular K(+) concentrations. These findings reveal specific structural and biochemical adaptations that may have allowed the establishment of the Brachyura in fresh water. J. Exp. Zool. 313A:508-523, 2010. (C) 2010 Wiley-Liss, Inc.

Depression in women living with HIV: clinical and psychosocial correlates

The number of Brazilian women living with HIV has increased significantly in past years, rendering studies of their particular care demands including psychiatric issues. This study measures the prevalence of major depression, using the Structured Clinical Interview for DSM-IV Axis I Disorders, in a sample of 120 women living with HIV in treatment at a reference centre in So Paulo. Socio-demographic variables, HIV-related clinical and laboratory data, including CD4+ cell counts and HIV plasma viral loads, as well as psychosocial features (intimate relationships, disclosure of HIV serostatus, partner`s serostatus and patient`s emotional and financial support) were investigated as factors potentially associated with depression. The prevalence of major depression at the time of evaluation was 25.8% (95% CI 18.2-33.4%). Clinical status (p = 0.002), lack of emotional support (p = 0.02), use of antidepressants (p = 0.028) and length of time since HIV diagnosis (p = 0.05) were associated with major depression in univariate analysis. In multivariate multiple-regression model, HIV clinical status, lack of emotional support and higher plasma viral loads were associated with depression. Sixty per cent of the women have a major depression diagnosis during lifetime. We conclude that major depression is highly prevalent among women living with HIV, but it is still underdiagnosed and undertreated.

Eating Disorders in Patients with Obsessive-Compulsive Disorder: Prevalence and Clinical Correlates

Objective: The objective is to evaluate the prevalence and associated clinical characteristics of eating disorders (ED) in patients with obsessive compulsive disorder (OCD). Method: This is a cross-sectional study comparing 815 patients with OCD. Participants were assessed with structured interviews and scales: SCID-I, Y-BOCS, Dimensional Y-BOCS, BABS, Beck Depression and Anxiety Inventories. Results: Ninety-two patients (11.3%) presented the following EDs: binge-eating disorders [= 59 (7.2%)], bulimia nervosa [= 16 (2.0%)], or anorexia nervosa [= 17 (2.1%)]. Compared to OCD patients without ED (OCD-Non-ED), OCD-ED patients were more likely to be women with previous psychiatric treatment. Mean total scores in Y-BOCS, Dimensional Y-BOCS, and BABS were similar within groups. However, OCD-ED patients showed higher lifetime prevalence of comorbid conditions, higher anxiety and depression scores, and higher frequency of suicide attempts than did the OCD-Non-ED group. Primarily diagnosed OCD patients with comorbid ED may be associated with higher clinical severity. Discussion: Future longitudinal studies should investigate dimensional correlations between OCD and ED. (C) 2009 by Wiley Periodicals, Inc.