Efficacy of ultrasonic, electric and manual toothbrushes in patients with fixed orthodontic appliances

Objective: This crossover study compared the efficacy of an ultrasonic toothbrush for the reduction of plaque, gingival inflammation, and levels of Streptococcus mutans, in relation to an electric and a manual toothbrush. Materials and Methods: Twenty-one patients with orthodontic appliances were divided into three groups. All patients were evaluated by a periodontist and samples of saliva were collected for quantification of S mutans. The patients received their first brushes with appropriate instructions. For each crossover leg, patients used each toothbrush for a period of 30 days. At the end of each washout period, participants received a periodontal evaluation and new samples of saliva were collected. After 15 days of using their own toothbrushes, patients received the next toothbrushes in the experimental sequence. Results: The ultrasonic brush group presented significant improvement in the reduction of visible plaque on the buccal surfaces (-6.36%, P = .007). The counts of S mutans decreased in the electric (2.04 × 105 to 1.36 × 105 colony-forming units [CFU]/mL) and ultrasonic (2.98 × 105 to 1.84 × 105 CFU/mL) groups. There were no statistical differences among the three brushes for the clinical and microbiological parameters evaluated. Conclusions: This study did not demonstrate that the ultrasonic toothbrush was better in reducing gingival inflammation in adolescent orthodontic patients, but plaque scores were lowered on buccal surfaces of teeth with orthodontic brackets. In addition, S mutans counts were markedly decreased in the electric and ultrasonic groups, which should be related to a reduced risk of oral disease. © 2006 by The EH Angle Education and Research Foundation, Inc.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Analysis of electric torque in single machine-infinite bus system using phase shifters

ResumoThe main idea of this work is based on the analysis of the electric torque through the acting of the PS in the power system, provided of a control for the compensation degree (PSC). A linear model of the single machine-infinite bus system is used with a PS installed (SMIB/PS system). The variable that represents the presence of PS in the net is associated to the phase displacement introduced in the terminal voltage of the synchronous machine by PS. For the input signals of the PSC are evaluated variations of the angular speed of the rotor, the current magnitude and the active power through the line where the PS is located. The simulations are accomplished to analyze the influence of the PS in the torque formation (synchronizing and damping), of the SMIB/PS system. The analysis are developed in the time and frequency domain.

Glycogen storage and muscle glucose transporters (GLUT-4) of mice selectively bred for high voluntary wheel running

To examine the evolution of endurance-exercise behaviour, we have selectively bred four replicate lines of laboratory mice (Mus domesticus) for high voluntary wheel running ('high runner' or HR lines), while also maintaining four non-selected control (C) lines. By generation 16, HR mice ran ∼2.7-fold more than C mice, mainly by running faster (especially in females), a differential maintained through subsequent generations, suggesting an evolutionary limit of unknown origin. We hypothesized that HR mice would have higher glycogen levels before nightly running, show greater depletion of those depots during their more intense wheel running, and have increased glycogen synthase activity and GLUT-4 protein in skeletal muscle. We sampled females from generation 35 at three times (photophase 07:00 h-19:00 h) during days 5-6 of wheel access, as in the routine selection protocol: Group 1, day 5, 16:00 h-17:30 h, wheels blocked from 13:00 h; Group 2, day 6, 02:00 h-03:30 h (immediately after peak running); and Group 3, day 6, 07:00 h-08:30 h. An additional Group 4, sampled 16:00 h-17:30 h, never had wheels. HR individuals with the mini-muscle phenotype (50% reduced hindlimb muscle mass) were distinguished for statistical analyses comparing C, HR normal, and HR mini. HR mini ran more than HR normal, and at higher speeds, which might explain why they have been favored by the selective-breeding protocol. Plasma glucose was higher in Group 1 than in Group 4, indicating a training effect (phenotypic plasticity). Without wheels, no differences in gastrocnemius GLUT-4 were observed. After 5 days with wheels, all mice showed elevated GLUT-4, but HR normal and mini were 2.5-fold higher than C. At all times and irrespective of wheel access, HR mini showed approximately three-fold higher [glycogen] in gastrocnemius and altered glycogen synthase activity. HR mini also showed elevated glycogen in soleus when sampled during peak running. All mice showed some glycogen depletion during nightly wheel running, in muscles and/or liver, but the magnitude of this depletion was not large and hence does not seem to be limiting to the evolution of even-higher wheel running.

Monitoring the dressing operation in the grinding process

This work was based on a methodology of development and experimentation, and involved monitoring the dressing operation by processing the acoustic emission and electric power signals to detect the optimal dressing moment. Dressing tests were performed in a surface grinding machine with an aluminium grinding wheel. Dressing analysis software was developed and used to process the signals collected earlier in order to analyse not only the dressing parameters but also the software's ability to indicate the instant when the dressing operation could be concluded. Parameters used in the study of burn in grinding were implemented in order to ascertain if they would also prove efficient in monitoring dressing. A comparative study revealed that some parameters are capable of monitoring the dressing operation. It was possible to verify the parameters effectiveness that today are utilised in burning to monitor dressing as well as to create new parameters for monitoring this operation. Copyright © 2009, Inderscience Publishers.

Placement and sizing evaluation of distributed generation in electric power systems

This paper presents a methodology for the placement and sizing evaluation of distributed generation (DG) in electric power systems. The candidate locations for DG placement are identified on the bases of Locational Marginal Prices (LMP's) obtained from an optimal power flow solution. The problem is formulated for two different objectives: social welfare maximization and profit maximization. For each DG unit an optimal placement is identified for each of the objectives.

Integrated planning of electric power distribution networks

In this work, a heuristic model for integrated planning of primary distribution network and secondary distribution circuits is proposed. A Tabu Search (TS) algorithm is employed to solve the planning of primary distribution networks. Evolutionary Algorithms (EA) are used to solve the planning model of secondary networks. The planning integration of both networks is carried out by means a constructive heuristic taking into account a set of integration alternatives between these networks. These integration alternatives are treated in a hierarchical way. The planning of primary networks and secondary distribution circuits is carried out based on assessment of the effects of the alternative solutions in the expansion costs of both networks simultaneously. In order to evaluate this methodology, tests were performed for a real-life distribution system taking into account the primary and secondary networks.

On the efficiency of an alternative codification for multiobjective service restoration in electric distribution networks

This paper proposes an alternative codification to solve the service restoration in electric power distribution networks using a SPEA2 multiobjective evolutionary algorithm, assuming the minimization of both the load not supplied and the number of switching operations involved in the restoration plan. Constrains as the line, power source and voltage drop limits in order to avoid the activation of protective devices are all included in the proposed algorithm. Experimental results have shown the convenience on considering these new representations in the sense of feasibility maintenance and also in the sense of better approximation to the Pareto set. ©2009 IEEE.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

To estimate the electric field near electric energy transmission systems by use simple software

The main objective this article is describe a methodology for the calculation of the profile of the electric field in the level soil and proximities originated by electric energy transmission systems real and in operation in the country. It also is commented the equation used and your computational implementation in order to agile and to optimize the studies. The results of simulations were just presented for the transmission system in the voltage class 500 kV for simplify the understanding and space restriction in the article, very although five others types of configurations have also been used in the complete study with very voltages and respective classes. The results were animating and very nearby of values well-known of electric field of other and publications traditional in the area. The graphic exits of program for better visual comprehension and understanding went in accomplished in the plan and in the space © 2010 IEEE.

Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders

This paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE.

Modeling of a MIT for the application of a frequency inverter of the electric vehicle

Nowadays, drives that use a combination of induction motors and frequency inverters are very common, a fact due to the financial practicality and viability in purchasing and operating that system. This system modeling and simulation becomes important when it wants to evaluate the performance, to calculate and correct parameters, and it has a fundamental role in functionality and viability analysis for application of new configurations and technologies. This work is about to elaborate a simple induction motor model based in the torque versus speed characteristic, using the linearization method for application in a specific operation range to be controlled by a frequency inverter. © 2011 Springer-Verlag Berlin Heidelberg.

Harmonic propagation analysis in electric energy distribution systems

An important alteration of the equivalent loads profile has been observed in the electrical energy distribution systems, for the last years. Such fact is due to the significant increment of the electronic processors of electric energy that, in general, behave as nonlinear loads, generating harmonic distortions in the currents and voltages along the electric network. The effects of these nonlinear loads, even if they are concentrated in specific sections of the network, are present along the branch circuits, affecting the behavior of the entire electric network. For the evaluation of this phenomenon it is necessary the analysis of the harmonic currents flow and the understanding of the causes and effects of the consequent voltage harmonic distortions. The usual tools for calculation the harmonic flow consider one-line equivalent networks, balanced and symmetrical systems. Therefore, they are not tools appropriate for analysis of the operation and the influence/interaction of mitigation elements. In this context, this work proposes the development of a computational tool for the analysis of the three-phase harmonic propagation using Norton modified models and considering the real nature of unbalanced electric systems operation. © 2011 IEEE.

Anfis applied to the prediction of surface roughness in grinding of advanced ceramics

This paper introduces a methodology for predicting the surface roughness of advanced ceramics using Adaptive Neuro-Fuzzy Inference System (ANFIS). To this end, a grinding machine was used, equipped with an acoustic emission sensor and a power transducer connected to the electric motor rotating the diamond grinding wheel. The alumina workpieces used in this work were pressed and sintered into rectangular bars. Acoustic emission and cutting power signals were collected during the tests and digitally processed to calculate the mean, standard deviation, and two other statistical data. These statistics, as well the root mean square of the acoustic emission and cutting power signals were used as input data for ANFIS. The output values of surface roughness (measured during the tests) were implemented for training and validation of the model. The results indicated that an ANFIS network is an excellent tool when applied to predict the surface roughness of ceramic workpieces in the grinding process.

Short-term planning of electric power distribution networks using multiobjective genetic algorithim

The high active and reactive power level demanded by the distribution systems, the growth of consuming centers, and the long lines of the distribution systems result in voltage variations in the busses compromising the quality of energy supplied. To ensure the energy quality supplied in the distribution system short-term planning, some devices and actions are used to implement an effective control of voltage, reactive power, and power factor of the network. Among these devices and actions are the voltage regulators (VRs) and capacitor banks (CBs), as well as exchanging the conductors sizes of distribution lines. This paper presents a methodology based on the Non-Dominated Sorting Genetic Algorithm (NSGA-II) for optimized allocation of VRs, CBs, and exchange of conductors in radial distribution systems. The Multiobjective Genetic Algorithm (MGA) is aided by an inference process developed using fuzzy logic, which applies specialized knowledge to achieve the reduction of the search space for the allocation of CBs and VRs.