Cluster analysis and artificial neural network on the superovulatory response prediction in mice

Complex biological systems require sophisticated approach for analysis, once there are variables with distinct measure levels to be analyzed at the same time in them. The mouse assisted reproduction, e.g. superovulation and viable embryos production, demand a multidisciplinary control of the environment, endocrinologic and physiologic status of the animals, of the stressing factors and the conditions which are favorable to their copulation and subsequently oocyte fertilization. In the past, analyses with a simplified approach of these variables were not well succeeded to predict the situations that viable embryos were obtained in mice. Thereby, we suggest a more complex approach with association of the Cluster Analysis and the Artificial Neural Network to predict embryo production in superovulated mice. A robust prediction could avoid the useless death of animals and would allow an ethic management of them in experiments requiring mouse embryo.

Neuropsychiatric symptoms in Alzheimer's disease are related to functional connectivity alterations in the salience network

Neuropsychiatric syndromes are highly prevalent in Alzheimer's disease (AD), but their neurobiology is not completely understood. New methods in functional magnetic resonance imaging, such as intrinsic functional connectivity or resting-state analysis, may help to clarify this issue. Using such approaches, alterations in the default-mode and salience networks (SNs) have been described in Alzheimer's, although their relationship with specific symptoms remains unclear. We therefore carried out resting-state functional connectivity analysis with 20 patients with mild to moderate AD, and correlated their scores on neuropsychiatric inventory syndromes (apathy, hyperactivity, affective syndrome, and psychosis) with maps of connectivity in the default mode network and SN. In addition, we compared network connectivity in these patients with that in 17 healthy elderly control subjects. All analyses were controlled for gray matter density and other potential confounds. Alzheimer's patients showed increased functional connectivity within the SN compared with controls (right anterior cingulate cortex and left medial frontal gyrus), along with reduced functional connectivity in the default-mode network (bilateral precuneus). A correlation between increased connectivity in anterior cingulate cortex and right insula areas of the SN and hyperactivity syndrome (agitation, irritability, aberrant motor behavior, euphoria, and disinhibition) was found. These findings demonstrate an association between specific network changes in AD and particular neuropsychiatric symptom types. This underlines the potential clinical significance of resting state alterations in future diagnosis and therapy. © 2013 Wiley Periodicals, Inc.

Artificial neural network model of discharge lamps in the power quality context

This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA.

Measures for controlling traffic congestion

Traffic congestion has become a severe scourge in large cities, in both the industrialized and developing countries. Increasing demand for urban transport and transit has led to longer travel times, and a greater incidence of accidents, environmental problems and deterioration in the quality of life than is considered acceptable for citizens. A multidisciplinary approach is required in order to keep the negative effects of congestion under control and to ensure standards of living remain sustainable. In view of the seriousness of the problem, ECLAC with the support of the German Agency for Technical Cooperation (GTZ) is carrying out a project to study measures that contribute to traffic control. As part of this project, initiatives regarding the supply of, and the demand for, transport have been examined, and a programme to disseminate information is being conducted.For further information, please contact Mr Alberto Bull .

Alternatives for controlling urban traffic congestion

Traffic congestion is nothing new in Latin American cities but has worsened in recent years. Eliminating it is a pipedream, but it should be brought under control. Many economists and transport planners think electronic road pricing would be the best way of tackling it, now that the appropriate technology for implementing it is available. On the other hand, experience shows that, for political reasons, it would be better to begin by adopting simpler methods. To start with, simple road pricing would seem to be the best option. But, over 20 years of experience in London and more than six in Santiago, Chile, made it clear that socio-political barriers have to be surmounted before even this option can be applied in practice. There is more political support for measures to control parking, due in part to the fact that the legal powers do not normally extend to restricting the number of parking spaces available to high-income and influential motorists who have the right to park near their offices and who cause a great deal of the congestion whilst getting there. In Latin America, the relative importance of taxis also diminishes the effectiveness of measures geared to parking, since taxis contribute to congestion although but they do not park. The problem of congestion cannot be solved by using tame measures. The time has come for something bolder, i.e., measures that, at the very least, exercise control over those parking spaces, which so far have been beyond the reach of governments and local authorities, ideally, simple road pricing systems would be even more effective.

Influence of distance, geometry and number of control stations on quality of local geodetic networks for the purpose of georeferencing of rural properties

The implementation of local geodetic networks for georeferencing of rural properties has become a requirement after publication of the Georeferencing Technical Standard by INCRA. According to this standard, the maximum distance of baselines to GNSS L1 receivers is of 20 km. Besides the length of the baseline, the geometry and the number of geodetic control stations are other factors to be considered in the implementation of geodetic networks. Thus, this research aimed to examine the influence of baseline lengths higher than the regulated limit of 20 km, the geometry and the number of control stations on quality of local geodetic networks for georeferencing, and also to demonstrate the importance of using specific tests to evaluate the solution of ambiguities and on the quality of the adjustment. The results indicated that the increasing number of control stations has improved the quality of the network, the geometry has not influenced on the quality and the baseline length has influenced on the quality; however, lengths higher than 20 km has not interrupted the implementation, with GPS L1 receiver, of the local geodetic network for the purpose of georeferencing. Also, the use of different statistical tests, both for the evaluation of the resolution of ambiguities and for the adjustment, have enabled greater clearness in analyzing the results, which allow that unsuitable observations may be eliminated.

Impact of insecticide resistance on the field control of Aedes aegypti in the State of São Paulo

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

Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes

Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process monitoring, among them, UV–Vis spectroscopy has found scarce applications. This work aimed to define artificial neural networks architecture and fit its parameters to predict some nutrients and metabolites, as well as viable cell concentration based on UV–Vis spectral data of mammalian cell bioprocess using phenol red in culture medium. The BHK-21 cell line was used as a mammalian cell model. Off-line spectra of supernatant samples taken from batches performed at different dissolved oxygen concentrations in two bioreactor configurations and with two pH control strategies were used to define two artificial neural networks. According to absolute errors, glutamine (0.13 ± 0.14 mM), glutamate (0.02 ± 0.02 mM), glucose (1.11 ± 1.70 mM), lactate (0.84 ± 0.68 mM) and viable cell concentrations (1.89 105 ± 1.90 105 cell/mL) were suitably predicted. The prediction error averages for monitored variables were lower than those previously reported using different spectroscopic techniques in combination with partial least squares or artificial neural network. The present work allows for UV–VIS sensor development, and decreases cost related to nutrients and metabolite quantifications.

Neuroglia and their roles in central respiratory control; an overview

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Development of CAN-based distributed control system for variable rate technology in agricultural machinery

The number of electronic devices connected to agricultural machinery is increasing to support new agricultural practices tasks related to the Precision Agriculture such as spatial variability mapping and Variable Rate Technology (VRT). The Distributed Control System (DCS) is a suitable solution for decentralization of the data acquisition system and the Controller Area Network (CAN) is the major trend among the embedded communications protocols for agricultural machinery and vehicles. The application of soil correctives is a typical problem in Brazil. The efficiency of this correction process is highly dependent of the inputs way at soil and the occurrence of errors affects directly the agricultural yield. To handle this problem, this paper presents the development of a CAN-based distributed control system for a VRT system of soil corrective in agricultural machinery. The VRT system is composed by a tractor-implement that applies a desired rate of inputs according to the georeferenced prescription map of the farm field to support PA (Precision Agriculture). The performance evaluation of the CAN-based VRT system was done by experimental tests and analyzing the CAN messages transmitted in the operation of the entire system. The results of the control error according to the necessity of agricultural application allow conclude that the developed VRT system is suitable for the agricultural productions reaching an acceptable response time and application error. The CAN-Based DCS solution applied in the VRT system reduced the complexity of the control system, easing the installation and maintenance. The use of VRT system allowed applying only the required inputs, increasing the efficiency operation and minimizing the environmental impact.

Co-simulation tools for networked control systems: revision and utilization

Networked control systems (NCSs) are distributed control systems in which the sensors, actuators, and controllers are physically separated and connected through an industrial network. The main challenge related to the development of NCSs is the degenerative effects caused by the inclusion of this communication network in the closed loop control. In order to mitigate these effects, co-simulation tools for NCS have been developed to study the network influence in the NCS. This paper presents a revision about co-simulation tools for NCS and the application of two of these tools for the design and evaluation of NCSs. The TrueTime and Jitterbug tools were used together to evaluate the main configuration parameter that affects the performance of CAN-based NCS and to verify the NCS quality of control under various timing conditions including different transmission period of messages and network delays. Therefore, the simulation results led to the conclusion that despite the transmission period of messages is the most significant factor among the analyzed in the design of NCS, its influence is related to the kind of system with greater effects in NCSs with fast dynamics.

Towards biological control strategies for the bronze bug, Thaumastocoris peregrinus, on eucalyptus plantations in South America

The bronze bug is an invasive Australian pest that has reached eucalypt production areas worldwide in <10 years. The fi rst record in South America was in 2005 in Argentina. Collaboration in the region towards a unifi ed strategy for the management of the bronze bug started soon after the dispersal of the pest into Brazil and Uruguay was confi rmed. Here, we present the main achievements of this collaboration in four main topics: 1) biology of the pest, 2) monitoring, 3) biological control, and 4) cooperative networks. Two mass rearing procedures have been implemented in the region with relative success, allowing basic biological studies on the pest. Continuous monitoring in the region for >5 years has provided a reasonable knowledge on seasonal patterns of T. peregrinus. Biological control strategies developed include the use of local natural enemies of T. peregrinus, the development of biopesticides, and the introduction of Cleruchoides noackae, an egg parasitoid of T. peregrinus from Australia. We review the main achievements in each country. Finally, a regional network of institutions, researchers, and students has strengthened in the region, providing a solid background for future collaboration.

Relationship among social support, treatment adherence and metabolic control of diabetes mellitus patients

This cross-sectional and quantitative study aimed to analyze the relationship among social support, adherence to non-pharmacological (diet and physical exercise) and pharmacological treatments (insulin and/or oral anti-diabetic medication) and clinical and metabolic control of 162 type 2 diabetes mellitus patients. Data were collected through instruments validated for Brazil. Social support was directly correlated with treatment adherence. Adherence to non-pharmacological treatment was inversely correlated with body mass index, and medication adherence was inversely correlated with diastolic blood pressure. There were no associations between social support and clinical and metabolic control variables. Findings indicate that social support can be useful to achieve treatment adherence. Studies with other designs should be developed to broaden the analysis of relations between social support and other variables.

A scheme for synchronizing clocks connected by a packet communication network

Consider a communication system in which a transmitter equipment sends fixed-size packets of data at a uniform rate to a receiver equipment. Consider also that these equipments are connected by a packet-switched network, which introduces a random delay to each packet. Here we propose an adaptive clock recovery scheme able of synchronizing the frequencies and the phases of these devices, within specified limits of precision. This scheme for achieving frequency and phase synchronization is based on measurements of the packet arrival times at the receiver, which are used to control the dynamics of a digital phase-locked loop. The scheme performance is evaluated via numerical simulations performed by using realistic parameter values. (C) 2011 Elsevier By. All rights reserved.

Modeling the Emergence of Circadian Rhythms in a Clock Neuron Network

Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.