Electrolipólise mediada por TENS e microcorrente em associação com exercício físico

Introdução: A gordura visceral e subcutânea do abdómen poderá aumentar o risco de diferentes patologias. Objectivo: Verificar se a lipólise induzida pela corrente eléctrica, é eficaz na redução de massa gorda. Métodos: Vinte e três mulheres foram divididas em três grupos: controlo só com exercício físico, experimental com TENS e exercício físico e experimental com microcorrente e exercício físico. Resultados: Nos grupos experimentais, aumentaram os triglicerídeos (p<0,05), diminuiu a prega supra-ilíca (p>0,05) e observaram-se valores tendencialmente menores de parâmetros específicos e globais. No grupo da Microcorrente diminuiu a prega abdominal (p>0,05). Conclusão: A electrolipólise poderá ter efeito coadjuvante ao exercício físico, na redução da massa gorda.

Distribuição dos receptores da adenosina no plexo mioentérico – músculo longitudinal do íleo de rato: implicações funcionais

A acetilcolina (ACh) é o neurotransmissor mais importante no controlo da motilidade gastrointestinal. A libertação de ACh dos neurónios entéricos é regulada por receptores neuronais específicos (De Man et al., 2003). Estudos prévios demonstraram que a adenosina exerce um papel duplo na libertação de ACh dos neurónios entéricos através da activação dos receptores inibitórios A1 e facilitatórios A2A (Duarte-Araújo et al., 2004). O potencial terapêutico dos compostos relacionados com a adenosina no controlo da motilidade e da inflamação intestinal, levou-nos a investigar o papel dos receptores com baixa afinidade para a adenosina, A2B e A3, na libertação de acetilcolina induzida por estimulação eléctrica nos neurónios mioentéricos. Estudos de imunolocalização mostraram que os receptores A2B exibem um padrão de distribuição semelhante ao do marcador de células gliais (GFAP). No que respeita aos receptores A1 e A3, estes encontram-se distribuídos principalmente nos corpos celulares dos neurónios ganglionares mioentéricos, enquanto os receptores A2A estão localizados predominantemente nos terminais nervosos colinérgicos. Neste trabalho mostrou-se que a modulação da libertação de ACh-[3H] (usando os antagonistas selectivos DPCPX, ZM241385 e MRS1191) é balanceada através da activação tónica dos receptores inibitórios (A1) e facilitatórios (A2A e A3) pela adenosina endógena. O antagonista selectivo dos receptores A2B, PSB603, não foi capaz de modificar o efeito inibitório da NECA (análogo da adenosina com afinidade para receptores A2). O efeito facilitatório do agonista dos receptores A3, 2-Cl-IB MECA (1-10 nM), foi atenuado pelo MRS1191 e pelo ZM241385, os quais bloqueiam respectivamente os receptores A3 e A2A. Contrariamente à 2-Cl-IB MECA, a activação dos receptores A2A pelo CGS21680C, atenuou a facilitação da libertação de ACh induzida pela activação dos receptores nicotínicos numa situação em que a geração do potencial de acção neuronal foi bloqueada pela tetrodotoxina. A localização diferencial dos receptores excitatórios A3 e A2A ao longo dos neurónios mioentéricos explica porque razão a estimulação dos receptores A3 (com 2-Cl-IB MECA) localizados nos corpos celulares dos neurónios mioentéricos exerce um efeito sinérgico com os receptores facilitatórios A2A dos terminais nervosos no sentido de aumentarem a libertação de ACh. Os resultados apresentados consolidam e expandem a compreensão actual da distribuição e função dos receptores da adenosina no plexo mioentérico do íleo de rato, e devem ser tidos em consideração para a interpretação de dados relativos às implicações fisiopatológicas da adenosina nos transtornos da motilidade intestinal.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

An intelligent tutoring approach to support students and technicians in electrical installation design

Designing electric installation projects, demands not only academic knowledge, but also other types of knowledge not easily acquired through traditional instructional methodologies. A lot of additional empirical knowledge is missing and so the academic instruction must be completed with different kinds of knowledge, such as real-life practical examples and simulations. On the other hand, the practical knowledge detained by the most experienced designers is not formalized in such a way that is easily transmitted. In order to overcome these difficulties present in the engineers formation, we are developing an Intelligent Tutoring System (ITS), for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students.

Adaptable control for electrical generation at irregural wind speeds

The main aims of this work are the development and the validation of one generic algorithm to provide the optimal control of small power wind generators. That means up to 40 kW and blades with fixed pitch angle. This algorithm allows the development of controllers to fetch the wind generators at the desired operational point in variable operating conditions. The problems posed by the variable wind intensity are solved using the proposed algorithm. This is done with no explicit measure of the wind velocity, and so no special equipment or anemometer is required to compute or measure the wind velocity.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Information and communication technologies in education – a web-based intelligent tutoring system on teaching and learning electrical project

Electrical activity is extremely broad and distinct, requiring by one hand, a deep knowledge on rules, regulations, materials, equipments, technical solutions and technologies and assistance in several areas, as electrical equipment, telecommunications, security and efficiency and rational use of energy, on the other hand, also requires other skills, depending on the specific projects to be implemented, being this knowledge a characteristic that belongs to the professionals with relevant experience, in terms of complexity and specific projects that were made.

A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.

A probabilistic methodology for distributed generation location in isolated electrical service area

Distributed generation unlike centralized electrical generation aims to generate electrical energy on small scale as near as possible to load centers, interchanging electric power with the network. This work presents a probabilistic methodology conceived to assist the electric system planning engineers in the selection of the distributed generation location, taking into account the hourly load changes or the daily load cycle. The hourly load centers, for each of the different hourly load scenarios, are calculated deterministically. These location points, properly weighted according to their load magnitude, are used to calculate the best fit probability distribution. This distribution is used to determine the maximum likelihood perimeter of the area where each source distributed generation point should preferably be located by the planning engineers. This takes into account, for example, the availability and the cost of the land lots, which are factors of special relevance in urban areas, as well as several obstacles important for the final selection of the candidates of the distributed generation points. The proposed methodology has been applied to a real case, assuming three different bivariate probability distributions: the Gaussian distribution, a bivariate version of Freund’s exponential distribution and the Weibull probability distribution. The methodology algorithm has been programmed in MATLAB. Results are presented and discussed for the application of the methodology to a realistic case and demonstrate the ability of the proposed methodology for efficiently handling the determination of the best location of the distributed generation and their corresponding distribution networks.

Photoluminescence and electrical study of fluctuating potentials in Cu2ZnSnS4-based thin films

In this work, we investigated structural, morphological, electrical, and optical properties from a set of Cu2ZnSnS4 thin films grown by sulfurization of metallic precursors deposited on soda lime glass substrates coated with or without molybdenum. X-ray diffraction and Raman spectroscopy measurements revealed the formation of single-phase Cu2ZnSnS4 thin films. A good crystallinity and grain compactness of the film was found by scanning electron microscopy. The grown films are poor in copper and rich in zinc, which is a composition close to that of the Cu2ZnSnS4 solar cells with best reported efficiency. Electrical conductivity and Hall effect measurements showed a high doping level and a strong compensation. The temperature dependence of the free hole concentration showed that the films are nondegenerate. Photoluminescence spectroscopy showed an asymmetric broadband emission. The experimental behavior with increasing excitation power or temperature cannot be explained by donor-acceptor pair transitions. A model of radiative recombination of an electron with a hole bound to an acceptor level, broadened by potential fluctuations of the valence-band edge, was proposed. An ionization energy for the acceptor level in the range 29–40 meV was estimated, and a value of 172 ±2 meV was obtained for the potential fluctuation in the valence-band edge.

Ibuprofen-loaded poly(trimethylene carbonate-co-ϵ- caprolactone) electrospun fibres for nerve regeneration

The development of scaffolds that combine the delivery of drugs with the physical support provided by electrospun fibres holds great potential in the field of nerve regeneration. Here it is proposed the incorporation of ibuprofen, a well-known non-steroidal anti-inflammatory drug, in electrospun fibres of the statistical copolymer poly(trimethylene carbonate-co-ε-caprolactone) [P(TMC-CL)] to serve as a drug delivery system to enhance axonal regeneration in the context of a spinal cord lesion, by limiting the inflammatory response. P(TMC-CL) fibres were electrospun from mixtures of dichloromethane (DCM) and dimethylformamide (DMF). The solvent mixture applied influenced fibre morphology, as well as mean fibre diameter, which decreased as the DMF content in solution increased. Ibuprofen-loaded fibres were prepared from P(TMC-CL) solutions containing 5% ibuprofen (w/w of polymer). Increasing drug content to 10% led to jet instability, resulting in the formation of a less homogeneous fibrous mesh. Under the optimized conditions, drug-loading efficiency was above 80%. Confocal Raman mapping showed no preferential distribution of ibuprofen in P(TMC-CL) fibres. Under physiological conditions ibuprofen was released in 24h. The release process being diffusion-dependent for fibres prepared from DCM solutions, in contrast to fibres prepared from DCM-DMF mixtures where burst release occurred. The biological activity of the drug released was demonstrated using human-derived macrophages. The release of prostaglandin E2 to the cell culture medium was reduced when cells were incubated with ibuprofen-loaded P(TMC-CL) fibres, confirming the biological significance of the drug delivery strategy presented. Overall, this study constitutes an important contribution to the design of a P(TMC-CL)-based nerve conduit with anti-inflammatory properties.

Application of fractional order concepts in the study of electrical potential

The Maxwell equations, expressing the fundamental laws of electricity and magnetism, only involve the integer-order calculus. However, several effects present in electromagnetism, motivated recently an analysis under the fractional calculus (FC) perspective. In fact, this mathematical concept allows a deeper insight into many phenomena that classical models overlook. On the other hand, genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. In this work we use FC and GA to implement the electrical potential of fractional order. The performance of the GA scheme and the convergence of the resulting approximations are analyzed.

Application of genetic algorithms in the design of an electrical potential of fractional order

Fractional calculus (FC) is currently being applied in many areas of science and technology. In fact, this mathematical concept helps the researches to have a deeper insight about several phenomena that integer order models overlook. Genetic algorithms (GA) are an important tool to solve optimization problems that occur in engineering. This methodology applies the concepts that describe biological evolution to obtain optimal solution in many different applications. In this line of thought, in this work we use the FC and the GA concepts to implement the electrical fractional order potential. The performance of the GA scheme, and the convergence of the resulting approximation, are analyzed. The results are analyzed for different number of charges and several fractional orders.