Global slowing of network oscillations in mouse neocortex by diazepam

SCHEFFZUK, C. , KUKUSHKA, V. , VYSSOTSKI, A. L. , DRAGUHN, A. , TORT, A. B. L. , BRANKACK, J. . Global slowing of network oscillations in mouse neocortex by diazepam. Neuropharmacology , v. 65, p. 123-133, 2013.

Desenvolvimento de um software de comunicação sem fio aplicado à instrumentação de unidade de elevação de petróleo tipo Plunger Lift

This dissertation aims to develop a software applied to a communication system for a wireless sensor network (WSN) for tracking analog and digital variables and control valve of the gas flow in artificial oil s elevation units, Plunger Lift type. The reason for this implementation is due to the fact that, in the studied plant configuration, the sensors communicate with the PLC (Programmable and Logic Controller) by the cables and pipelines, making any changes in that system, such as changing the layout of it, as well as inconveniences that arise from the nature of the site, such as the vicinity s animals presence that tend to destroy the cables for interconnection of sensors to the PLC. For software development, was used communication polling method via SMAC protocol (Simple Medium Access ControlIEEE 802.15.4 standard) in the CodeWarrior environment to which generated a firmware, loaded into the WSN s transceivers, present in the kit MC13193-EVK, (all items described above are owners of Freescale Semiconductors Inc.). The network monitoring and parameterization used in its application, was developed in LabVIEW software from National Instruments. The results were obtained through the observation of the network s behavior of sensors proposal, focusing on aspects such as: indoor and outdoor quantity of packages received and lost, general aspects of reliability in data transmission, coexistence with other types of wireless networks and power consumption under different operating conditions. The results were considered satisfactory, which showed the software efficiency in this communication system

Modelagem aplicada à análise de desempenho do provedor de serviços de uma rede de automação hospitalar ieee 802.3/pm-ah de tempo real

The incorporate of industrial automation in the medical are requires mechanisms to safety and efficient establishment of communication between biomedical devices. One solution to this problem is the MP-HA (Multicycles Protocol to Hospital Automation) that down a segmented network by beds coordinated by an element called Service Provider. The goal of this work is to model this Service Provider and to do performance analysis of the activities executed by in establishment and maintenance of hospital networks

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Design and analysis of an efficient neural network model for solving nonlinear optimization problems

This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it handles optimization and constraint terms in different stages with no interference from each other. Moreover, the proposed approach does not require specification for penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyse its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Midgard: um middleware baseado em componentes e orientado a recursos para redes de sensores sem fio

On the last years, several middleware platforms for Wireless Sensor Networks (WSN) were proposed. Most of these platforms does not consider issues of how integrate components from generic middleware architectures. Many requirements need to be considered in a middleware design for WSN and the design, in this case, it is possibility to modify the source code of the middleware without changing the external behavior of the middleware. Thus, it is desired that there is a middleware generic architecture that is able to offer an optimal configuration according to the requirements of the application. The adoption of middleware based in component model consists of a promising approach because it allows a better abstraction, low coupling, modularization and management features built-in middleware. Another problem present in current middleware consists of treatment of interoperability with external networks to sensor networks, such as Web. Most current middleware lacks the functionality to access the data provided by the WSN via the World Wide Web in order to treat these data as Web resources, and they can be accessed through protocols already adopted the World Wide Web. Thus, this work presents the Midgard, a component-based middleware specifically designed for WSNs, which adopts the architectural patterns microkernel and REST. The microkernel architectural complements the component model, since microkernel can be understood as a component that encapsulates the core system and it is responsible for initializing the core services only when needed, as well as remove them when are no more needed. Already REST defines a standardized way of communication between different applications based on standards adopted by the Web and enables him to treat WSN data as web resources, allowing them to be accessed through protocol already adopted in the World Wide Web. The main goals of Midgard are: (i) to provide easy Web access to data generated by WSN, exposing such data as Web resources, following the principles of Web of Things paradigm and (ii) to provide WSN application developer with capabilities to instantiate only specific services required by the application, thus generating a customized middleware and saving node resources. The Midgard allows use the WSN as Web resources and still provide a cohesive and weakly coupled software architecture, addressing interoperability and customization. In addition, Midgard provides two services needed for most WSN applications: (i) configuration and (ii) inspection and adaptation services. New services can be implemented by others and easily incorporated into the middleware, because of its flexible and extensible architecture. According to the assessment, the Midgard provides interoperability between the WSN and external networks, such as web, as well as between different applications within a single WSN. In addition, we assessed the memory consumption, the application image size, the size of messages exchanged in the network, and response time, overhead and scalability on Midgard. During the evaluation, the Midgard proved satisfies their goals and shown to be scalable without consuming resources prohibitively

Optimization of a mouse immunization protocol with Paracoccidioides brasiliensis antigens

The objectives of the present study were to optimize the protocol of mouse immunization with Paracoccidioides brasiliensis antigens (Rifkind's protocol) and to test the modulation effect of cyclophosphamide (Cy) on the delayed hypersensitivity response (DHR) of immunized animals. Experiments were carried out using one to four immunizing doses of either crude particulate P. brasiliensis antigen or yeast-cell antigen, followed by DHR test four or seven days after the last immunizing dose. The data demonstrated that an immunizing dose already elicited response; higher DHR indices were obtained with two or three immunizing doses; there were no differences between DHR indices of animals challenged four or seven days after the last dose. Overall the inoculation of two or three doses of the yeast-cell antigen, which is easier to prepare, and DHR test at day 4 simplify the original Rifkind's immunization protocol and shorten the duration of the experiments. The modulation effect of Cy on DHR was assayed with administration of 2.5, 20 and 100 mg/kg weight at seven day intervals starting from day 4 prior to the first immunizing dose. Only the treatment with 2.5 mg Cy increased the DHR indices. Treatment with 100 mg Cy inhibited the DHR, whereas 20 mg Cy did not affect the DHR indices. Results suggest an immunostimulating effect of low dose of Cy on the DHR of mice immunized with P. brasiliensis antigens.

On the reliability of visual communication in vertebrate-dispersed fruits

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Network reconfiguration and loss allocation in a deregulated environment of distribution systems

Low flexibility and reliability in the operation of radial distribution networks make those systems be constructed with extra equipment as sectionalising switches in order to reconfigure the network, so the operation quality of the network can be improved. Thus, sectionalising switches are used for fault isolation and for configuration management (reconfiguration). Moreover, distribution systems are being impacted by the increasing insertion of distributed generators. Hence, distributed generation became one of the relevant parameters in the evaluation of systems reconfiguration. Distributed generation may affect distribution networks operation in various ways, causing noticeable impacts depending on its location. Thus, the loss allocation problem becomes more important considering the possibility of open access to the distribution networks. In this work, a graphic simulator for distribution networks with reconfiguration and loss allocation functions, is presented. Reconfiguration problem is solved through a heuristic methodology, using a robust power flow algorithm based on the current summation backward-forward technique, considering distributed generation. Four different loss allocation methods (Zbus, Direct Loss Coefficient, Substitution and Marginal Loss Coefficient) are implemented and compared. Results for a 32-bus medium voltage distribution network, are presented and discussed.

Network node with wireless and wired interfaces: Nios II processor and uClinux to development of a NCAP embedded (IEEE 1451.1) with two interfaces, wireless (IEEE 1451.5) and wired (IEEE p1451.2)

This paper presents a NCAP embedded on DE2 kit with Nios II processor and uClinux to development of a network gateway with two interfaces, wireless (ZigBee) and wired (RS232) based on IEEE 1451. Both the communications, wireless and wired, were developed to be point-to-point and working with the same protocols, based on IEEE 1451.0-2007. The tests were made using a microcomputer, which through of browser was possible access the web page stored in the DE2 kit and send commands of control and monitoring to both TIMs (WTIM and STIM). The system describes a different form of development of the NCAP node to be applied in different environments with wired or wireless in the same node. © 2011 IEEE.

Pricing of reactive power support provided by distributed generators in transmission systems

Distributed Generation, microgrid technologies, two-way communication systems, and demand response programs are issues that are being studied in recent years within the concept of smart grids. At some level of enough penetration, the Distributed Generators (DGs) can provide benefits for sub-transmission and transmission systems through the so-called ancillary services. This work is focused on the ancillary service of reactive power support provided by DGs, specifically Wind Turbine Generators (WTGs), with high level of impact on transmission systems. The main objective of this work is to propose an optimization methodology to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). LOC occur when more reactive power is required than available, and the active power generation has to be reduced in order to increase the reactive power capacity. In the optimization process, three objectives are considered: active power generation costs of DGs, voltage stability margin of the system, and losses in the lines of the network. Uncertainties of WTGs are reduced solving multi-objective optimal power flows in multiple probabilistic scenarios constructed by Monte Carlo simulations, and modeling the time series associated with the active power generation of each WTG via Fuzzy Logic and Markov Chains. The proposed methodology was tested using the IEEE 14 bus test system with two WTGs installed. © 2011 IEEE.

The perception of brazilian researchers concerning the factors that influence the citation of their articles: A study in the field of sustainability

With growing institutional pressure from the Brazilian government to increase the impact of research that it funds, Brazilian researchers are increasingly interested in discovering factors that affect the citation of their articles. The aim of the present article was to assess the perceptions of Brazilian sustainability researchers to identify factors that influence the impacts of their research. A survey was conducted with researchers in the field of sustainability and 89 questionnaires were completed. All of those researchers have articles or research projects in the field of sustainability (mixing environmental, social and/or economical) recorded in the Scielo or Lattes Curriculum Brazilian databases. Results suggest four factors that may explain the impact of article citations: (1) prestige of the author and the research network; (2) prestige of the means of publication and indexing; (3) accessibility and quality characteristics of the article; and (4) international nature of communication and scope of the study. Surprisingly, such factors were not statistically significant in explaining the citations of the participating researchers. These results show the need to consider other factors that can explain the impact of research, discovering the missing links. © 2013 Elsevier Inc.