Routine libraries for pattern recognition in quasispecies.

The results obtained through biological research usually need to be analyzed using computational tools, since manual analysis becomes unfeasible due to the complexity and size of these results. For instance, the study of quasispecies frequently demands the analysis of several, very lengthy sequences of nucleotides and amino acids. Therefore, bioinformatics tools for the study of quasispecies are constantly being developed due to different problems found by biologists. In the present study, we address the development of a software tool for the evaluation of population diversity in quasispecies. Special attention is paid to the localization of genome regions prone to changes, as well as of possible hot spots.

Observation of tags and hybrid layer of a single bottle conventional adhesive system and a self-etching adhesive system, on sound dentin.

This experimental light microscopy study investigated the formation of a hybrid layer and resin tags on sound dentin, after utilization of conventional and self-etching adhesive systems. After restorative procedures, the specimens were decalcified in a formic acid and sodium citrate solution, embedded in paraffin, sectioned at 6-microm thickness and stained by the Brown & Brenn method for analysis and measurement by light microscopy (AXIOPHOT) (400x). The results were statistically analyzed by analysis of variance, at a significance level of 5%. Based on the results, it could be concluded that the conventional adhesive allowed the formation of a thicker hybrid layer than the self-etching adhesive, with similar penetration into the dentinal tubules (resin tags).

Robust and fast vowel recognition using optimum-path forest

The applications of Automatic Vowel Recognition (AVR), which is a sub-part of fundamental importance in most of the speech processing systems, vary from automatic interpretation of spoken language to biometrics. State-of-the-art systems for AVR are based on traditional machine learning models such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), however, such classifiers can not deal with efficiency and effectiveness at the same time, existing a gap to be explored when real-time processing is required. In this work, we present an algorithm for AVR based on the Optimum-Path Forest (OPF), which is an emergent pattern recognition technique recently introduced in literature. Adopting a supervised training procedure and using speech tags from two public datasets, we observed that OPF has outperformed ANNs, SVMs, plus other classifiers, in terms of training time and accuracy. ©2010 IEEE.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

A sound education: Becoming aware of the sound around us

In this article it is intended to discuss the issue of noise pollution from an unusual point of view: noise pollution is not only the result of sound increase worldwide, but, particularly, the poor quality of our listening habits in modern life as well. In contemporary society we are subject to a considerable amount of stimulus to all our senses: vision, scent, taste and hearing which are becoming more and more insensible due to over exposure in our environment. These increased stimuli make us look for alternatives to reduce our ability to perceive them and be protected from injuries. However, our sensitivity will also decrease. In the specific case of environment noise, over exposure has made us forget the enchantment of certain sounds that used to give us pleasure or evoke good feelings by many ways, making us recall certain good things, bringing particular moments of our lives to our memory or even filling us with strong emotion. The Canadian composer and music educator, R. Murray Schafer, believes that noise pollution is the result of a society who became deaf. Closing our ears to noise protect us from noise pollution but also prevent us from grasping subtleties of listening. Contemporary world does not help us to be aware of sound in the space around us; acquiring this hearing ability is a matter of focus, interest and practice. Sound education exercises are aimed at children, teenagers and adults who want to improve their listening ability to environmental sounds, perceive its proprieties and learn how sound affects us and touches our feelings. The results are easy to accomplish and contribute to our awareness of the sound environment around us and to the conception of the environmental sound as a composition made by everybody and everything through positive actions, strong will and high sensitivity. Copyright © (2011) by the International Institute of Acoustics & Vibration.

Effect of bleaching on sound enamel and with early artificial caries lesions using confocal laser microscopy

The aim of this study was to evaluate effect of bleaching agents on sound enamel (SE) and enamel with early artificial caries lesions (CL) using confocal laser scanning microscopy (CLSM). Eighty blocks (4 × 5 × 5 mm) of bovine enamel were used and half of them were submitted to a pH cycling model to induce CL. Eight experimental groups were obtained from the treatments and mineralization level of the enamel (SE or CL) (n=10). SE groups: G1 - unbleached (control); G2 - 4% hydrogen peroxide (4 HP); G3 - 4 HP containing 0.05% Ca (Ca); G4 - 7.5% hydrogen peroxide (7.5 HP) containing amorphous calcium phosphate (ACP). CL groups: G5 - unbleached; G6 - 4 HP; G7 - 4 HP containing Ca; G8 - 7.5 HP ACP. G2, G3, G6, G7 were treated with the bleaching agents for 8 h/day during 14 days, while G4 and G8 were exposed to the bleaching agents for 30 min twice a day during 14 days. The enamel blocks were stained with 0.1 mM rhodamine B solution and the demineralization was quantified using fluorescence intensity detected by CLSM. Data were analyzed using ANOVA and Fisher's tests (α=0.05). For the SE groups, the bleaching treatments increased significantly the demineralization area when compared with the unbleached group. In the CL groups, no statistically significant difference was observed (p>0.05). The addition of ACP or Ca in the composition of the whitening products did not overcome the effects caused by bleaching treatments on SE and neither was able to promote remineralization of CL.

Laser ultrasonics system for measurement of speed of sound in gases

In this work we developed a setup to measure the speed of sound in gases using a laser ultrasonics system. The mentioned setup is an all optical system composed by a Q-switched Nd:YAG laser to generate the sound waves, and a fiber optical microphone to detect them. The Nd:YAG provided a laser pulse of approximately 420 mJ energy and 9 ns of pulse width, at the wavelength of 1064 nm. The pulsed laser beam, focused by a positive lens, was used to generate an electrical breakdown (in the gas) which, in turn, generates an sound wave that traveled through a determined distance and reached the fiber optical microphone. The resulting signal was acquired in an oscilloscope and the time difference between the optical pulse and the arrival of the sound waves was used to calculate the speed of sound, since the distance was known. The system was initially tested to measure the speed of sound in air, at room pressure and temperature and it presented results in agreement with the theory, showing to be suitable to measure the speed of sound in gases. © 2012 American Institute of Physics.

Semiautomatic dental recognition using a graph-based segmentation algorithm and teeth shapes features

Dental recognition is very important for forensic human identification, mainly regarding the mass disasters, which have frequently happened due to tsunamis, airplanes crashes, etc. Algorithms for automatic, precise, and robust teeth segmentation from radiograph images are crucial for dental recognition. In this work we propose the use of a graph-based algorithm to extract the teeth contours from panoramic dental radiographs that are used as dental features. In order to assess our proposal, we have carried out experiments using a database of 1126 tooth images, obtained from 40 panoramic dental radiograph images from 20 individuals. The results of the graph-based algorithm was qualitatively assessed by a human expert who reported excellent scores. For dental recognition we propose the use of the teeth shapes as biometric features, by the means of BAS (Bean Angle Statistics) and Shape Context descriptors. The BAS descriptors showed, on the same database, a better performance (EER 14%) than the Shape Context (EER 20%). © 2012 IEEE.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

Sound pressure level in a municipal preschool

Aim: To evaluate the sound pressure level to which preschool students are exposed. Method: This was a prospective, quantitative, nonexperimental, and descriptive study. To achieve the aim of the study we used an audio dosimeter. The sound pressure level (SPL) measurements were obtained for 2 age based classrooms. Preschool I and II. The measurements were obtained over 4 days in 8-hour sessions, totaling 1920 minutes. Results: Compared with established standards, the SPL measured ranged from 40.6 dB (A) to 105.8 dB (A). The frequency spectrum of the SPL was concentrated in the frequency range between 500 Hz and 4000 Hz. The older children produced higher SPLs than the younger ones, and the levels varied according to the activity performed. Painting and writing were the quietest activities, while free activities period and games were the noisiest. Conclusion: The SPLs measured at the preschool were higher and exceeded the maximum permitted level according to the reference standards. Therefore, the implementation of actions that aim to minimize the negative impact of noise in this environment is essential.

Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Attitude of Brazilian veterinarians in the recognition and treatment of pain in horses and cattle

Objective: The objective of this study was to assess the use of analgesics, describe the attitudes of Brazilian veterinarians towards pain relief in horses and cattle and evaluate the differences due to gender, year of graduation and type of practice. Study design: Prospective survey. Methods: Questionnaires were sent to 1000 large animal veterinarians by mail, internet and delivered in person during national meetings. The survey investigated the attitudes of Brazilian veterinarians to the recognition and treatment of pain in large animals and consisted of sections asking about demographic data, use of analgesic drugs, attitudes to pain relief and to the assessment of pain. Descriptive statistics were used to analyze frequencies. Simple post hoc comparisons were performed using the chi-square test. Results: Eight hundred questionnaires were collected, but 87 were discarded because they were incomplete or blank. The opioid of choice for use in large animals was butorphanol (43.4%) followed by tramadol (39%). Flunixin (83.2%) and ketoprofen (67.6%) were the most frequently used NSAIDs by Brazilian veterinarians. Respondents indicated that horses received preoperative analgesics for laparotomy more frequently (72.9%) than cattle (58.5%). The most frequently administered preoperative drugs for laparotomy in horses were flunixin (38.4%) and xylazine (23.6%), whereas the preoperative drugs for the same surgical procedure in cattle were xylazine (31.8%) and the local administration of lidocaine (48%). Fracture repair was considered the most painful surgical procedure for both species. Most veterinarians (84.1%) believed that their knowledge in this area was not adequate. Conclusions and clinical relevance: Although these Brazilian veterinarians thought that their knowledge on recognition and treatment of pain was not adequate, the use of analgesic in large animals was similar in Brazil to that reported in other countries. © 2013 Association of Veterinary Anaesthetists and the American College of Veterinary Anesthesia and Analgesia.

Recent developments in relation to the proposal for securing the international recognition of the Caribbean Sea as a special area in the context of sustainable development

Includes bibliography