Antimicrobial photodynamic action on dentin using a light-emitting diode light source

Objective: The aim of this study was the evaluation of two different photosensitizers activated by red light emitted by light-emitting diodes (LEDs) in the decontamination of carious bovine dentin. Materials and Methods: Fifteen bovine incisors were used to obtain dentin samples which were immersed in brain-heart infusion culture medium supplemented with 1% glucose, 2% sucrose, and 1% young primary culture of Lactobacillus acidophilus 108 CFU/mL and Streptococcus mutans 108 CFU/mL for caries induction. Three different concentrations of the Photogem solution, a hematoporphyrin derivative (1, 2, and 3 mg/mL) and two different concentrations of toluidine blue O (TBO), a basic dye (0.025 and 0.1 mg/mL) were used. To activate the photosensitizers two different light exposure times were used: 60 sec and 120 sec, corresponding respectively to the doses of 24 J/cm(2) and 48 J/cm(2). Results: After counting the numbers of CFU per milligram of carious dentin, we observed that the use of LED energy in association with Photogem or TBO was effective for bacterial reduction in carious dentin, and that the greatest effect on S. mutans and L. acidophilus was obtained with TBO at 0.1 mg/mL and a dose of 48 J/cm(2). It was also observed that the overall toxicity of TBO was higher than that of Photogem, and that the phototoxicity of TBO was higher than that of Photogem. Conclusion: Based on our data we propose a mathematical model for the photodynamic effect when different photosensitizer concentrations and light doses are used.

The MX2 macromolecular crystallography beamline: a wiggler X-ray source at the LNLS

The Brazilian Synchrotron Light Laboratory [Laboratorio Nacional de Luz Sincrotron (LNLS), Campinas, SP, Brazil] is the first commissioned synchrotron light source in the southern hemisphere. The first wiggler macromolecular crystallography beamline (MX2) at the LNLS has been recently constructed and brought into operation. Here the technical design, experimental set-up, parameters of the beamline and the first experimental results obtained at MX2 are described. The beamline operates on a 2.0 T hybrid 30-pole wiggler, and its optical layout includes collimating mirror, Si( 111) double-crystal monochromator and toroidal bendable mirror. The measured flux density at the sample position at 8.7 eV reaches 4.8 x 10(11) photons s(-1) mm(-2) (100 mA)(-1). The beamline is equipped with a MarResearch Desktop Beamline Goniostat (MarDTB) and 3 x 3 MarMosaic225 CCD detector, and is controlled by a customized version of the Blu-Ice software. A description of the first X-ray diffraction data sets collected at the MX2 LNLS beamline and used for macromolecular crystal structure solution is also provided.

Source populations in coastal crabs: parameters affecting egg production

Benthic marine invertebrates may form metapopulations connected via propagule dispersal. Conservation efforts often target potential source coastlines to indirectly benefit areas depending on allochthonous offspring production. Besides population density, adult size structure, sex ratio, brooding frequency and the proportion of breeding individuals may significantly influence the reproductive output of benthic populations, but these effects have seldom been tested. We used rocky shore crabs to assess the spatial variability of such parameters at relevant scales for conservation purposes and to test their consistency over 2 consecutive years; we then used the data to address whether bottom-up processes or biological interactions might explain the patterns observed. We decomposed egg production rates into their components for the 2 most abundant brachyuran species inhabiting the intertidal rocky habitat. Adult density and brooding frequency varied consistently among shores for both species and largely explained the overall spatial trends of egg production. Temporally consistent patterns also included among-shore differences in the size of ovigerous females of the grapsid Pachygrapsus transversus and between-bay differences in the fecundity of the spider crab Epialtus brasiliensis. Sex ratio was remarkably constant in both. We found no positive or negative correlations between adult density and brooding frequency to support either the existence of a component Allee effect (lack of mate encounters) or an effect of intra-specific competition. Likewise, shore-specific potential growth in P. transversus does not negatively correlate with frequency of ovigerous individuals, as would be expected under a critical balance between these 2 processes. The patterns observed suggest that bottom-up drivers may best explain spatial trends in the reproductive output of these species.

Building a Open Source Framework for Virtual Medical Training

This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

IS ORDINARY ELECTRIC DRILLS` VENTING PORT A POTENTIAL SOURCE OF SURGICAL INFECTION?

Objective: To evaluate the potential risk of surgical contamination by the venting port of ordinary electric drills (ED) employed in orthopaedic surgeries. Materials and Methods: an experimental laboratory, randomized study was developed to analyze EDs in surgical practice and new cleaned and sterilized equipment, which were contaminated with Bacillus atrophaeus spores at a concentration of 84 X 10(6) UFC. The air generated by the engine of each drill was collected and cultivated on sterile agar plates. Results: Positive culture was identified in two ED in surgical practice, as well as a positive culture to Bacillus atrophaeus with 1 CFU growth (1, 19 X 10(-8)). Conclusion: In the conditions of the experiment, the air generated by the venting port of the ED`s engine does not consist of a source of contamination for the surgical site.

Correlation of Modified Natural Rubber Properties by Artificial Neural Networks

Natural rubber (NR) is a raw material largely used by the modern industry; however, it is common that chemical modifications must be made to NR in order to improve properties such as hydrophobicity or mechanical resistance. This work deals with the correlation of properties of NR modified with dimethylaminoethylmethacrylate or methylmethacrylate as grafting agents. Dynamic-mechanical behavior and stress/strain relations are very important properties because they furnish essential characteristics of the material such as glass transition temperature and rupture point. These properties are concerned with different physical principles; for this reason, normally they are not related to each other. This work showed that they can be correlated by artificial neural networks (ANN). So, from one type of assay, the properties that as a rule only could be obtained from the other can be extracted by ANN correlation. POLYM. ENG. SCI., 49:499-505, 2009. (c) 2009 Society of Plastics Engineers

SAB(IO): A BIOLOGICALLY PLAUSIBLE CONNECTIONIST APPROACH TO AUTOMATIC TEXT SUMMARIZATION

An implementation of a computational tool to generate new summaries from new source texts is presented, by means of the connectionist approach (artificial neural networks). Among other contributions that this work intends to bring to natural language processing research, the use of a more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may bring an increase in computational efficiency when compared to the sa-called biologically implausible algorithms.

Optimization of the AZO dyes decoloration process through neural networks: Determination of the H2O2 addition critical point

The concentration of hydrogen peroxide is an important parameter in the azo dyes decoloration process through the utilization of advanced oxidizing processes, particularly by oxidizing via UV/H2O2. It is pointed out that, from a specific concentration, the hydrogen peroxide works as a hydroxyl radical self-consumer and thus a decrease of the system`s oxidizing power happens. The determination of the process critical point (maximum amount of hydrogen peroxide to be added) was performed through a ""thorough mapping"" or discretization of the target region, founded on the maximization of an objective function objective (constant of reaction kinetics of pseudo-first order). The discretization of the operational region occurred through a feedforward backpropagation neural model. The neural model obtained presented remarkable coefficient of correlation between real and predicted values for the absorbance variable, above 0.98. In the present work, the neural model had, as phenomenological basis the Acid Brown 75 dye decoloration process. The hydrogen peroxide addition critical point, represented by a value of mass relation (F) between the hydrogen peroxide mass and the dye mass, was established in the interval 50 < F < 60. (C) 2007 Elsevier B.V. All rights reserved.

Embedded DSP-Based Compact Fuzzy System and Its Application for Induction-Motor V/f Speed Control

This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.

Harmonic identification using parallel neural networks in single-phase systems

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

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.

Data Mining Applied to Harmonic Current Sources Identification in Residential Consumers

This work proposes a method based on both preprocessing and data mining with the objective of identify harmonic current sources in residential consumers. In addition, this methodology can also be applied to identify linear and nonlinear loads. It should be emphasized that the entire database was obtained through laboratory essays, i.e., real data were acquired from residential loads. Thus, the residential system created in laboratory was fed by a configurable power source and in its output were placed the loads and the power quality analyzers (all measurements were stored in a microcomputer). So, the data were submitted to pre-processing, which was based on attribute selection techniques in order to minimize the complexity in identifying the loads. A newer database was generated maintaining only the attributes selected, thus, Artificial Neural Networks were trained to realized the identification of loads. In order to validate the methodology proposed, the loads were fed both under ideal conditions (without harmonics), but also by harmonic voltages within limits pre-established. These limits are in accordance with IEEE Std. 519-1992 and PRODIST (procedures to delivery energy employed by Brazilian`s utilities). The results obtained seek to validate the methodology proposed and furnish a method that can serve as alternative to conventional methods.

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