878 resultados para Parallel processing (Electronic computers)


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The present study compared the accuracy of three electronic apex locators (EALs) - Elements Diagnostic®, Root ZX® and Apex DSP® - in the presence of different irrigating solutions (0.9% saline solution and 1% sodium hypochlorite). The electronic measurements were carried out by three examiners, using twenty extracted human permanent maxillary central incisors. A size 10 K file was introduced into the root canals until reaching the 0.0 mark, and was subsequently retracted to the 1.0 mark. The gold standard (GS) measurement was obtained by combining visual and radiographic methods, and was set 1 mm short of the apical foramen. Electronic length values closer to the GS (± 0.5 mm) were considered as accurate measures. Intraclass correlation coefficients (ICCs) were used to verify inter-examiner agreement. The comparison among the EALs was performed using the McNemar and Kruskal-Wallis tests (p < 0.05). The ICCs were generally high, ranging from 0.8859 to 0.9657. Similar results were observed for the percentage of electronic measurements closer to the GS obtained with the Elements Diagnostic® and the Root ZX® EALs (p > 0.05), independent of the irrigating solutions used. The measurements taken with these two EALs were more accurate than those taken with Apex DSP®, regardless of the irrigating solution used (p < 0.05). It was concluded that Elements Diagnostic® and Root ZX® apex locators are able to locate the cementum-dentine junction more precisely than Apex DSP®. The presence of irrigating solutions does not interfere with the performance of the EALs.

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Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

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Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

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The n→π* absorption transition of formaldehyde in water is analyzed using combined and sequential classical Monte Carlo (MC) simulations and quantum mechanics (QM) calculations. MC simulations generate the liquid solute-solvent structures for subsequent QM calculations. Using time-dependent density functional theory in a localized set of gaussian basis functions (TD-DFT/6-311++G(d,p)) calculations are made on statistically relevant configurations to obtain the average solvatochromic shift. All results presented here use the electrostatic embedding of the solvent. The statistically converged average result obtained of 2300 cm-1 is compared to previous theoretical results available. Analysis is made of the effective dipole moment of the hydrogen-bonded shell and how it could be held responsible for the polarization of the solvent molecules in the outer solvation shells.

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This study addressed the use of conventional and vegetable origin polyurethane foams to extract C. I. Acid Orange 61 dye. The quantitative determination of the residual dye was carried out with an UV/Vis absorption spectrophotometer. The extraction of the dye was found to depend on various factors such as pH of the solution, foam cell structure, contact time and dye and foam interactions. After 45 days, better results were obtained for conventional foam when compared to vegetable foam. Despite presenting a lower percentage of extraction, vegetable foam is advantageous as it is considered a polymer with biodegradable characteristics.

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A new tetraruthenated copper(II)-tetra(3,4-pyridyl)porphyrazine species, [CuTRPyPz]4+, has been synthesized and fully characterized by means of analytical, spectroscopic and electrochemical techniques. This À-conjugated system contrasts with the related meso-tetrapyridylporphyrins by exhibiting strong electronic interaction between the coordinated peripheral complexes and the central ring. Based on favorable À-stacking and electrostatic interactions, layer-by-layer assembled films were successfully generated from the appropriate combination of [CuTRPyPz]4+ with copper(II)-tetrasulfonated phtalocyanine, [CuTSPc]4-. Their conducting and electrocatalytic properties were investigated by means of impedance spectroscopy and rotating disc voltammetry, exhibiting metallic behavior near the Ru(III/II) redox potential, as well as enhanced catalytic activity for the oxidation of nitrite and sulphite ions.

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This paper describes a new food classification which assigns foodstuffs according to the extent and purpose of the industrial processing applied to them. Three main groups are defined: unprocessed or minimally processed foods (group 1), processed culinary and food industry ingredients (group 2), and ultra-processed food products (group 3). The use of this classification is illustrated by applying it to data collected in the Brazilian Household Budget Survey which was conducted in 2002/2003 through a probabilistic sample of 48,470 Brazilian households. The average daily food availability was 1,792 kcal/person being 42.5% from group 1 (mostly rice and beans and meat and milk), 37.5% from group 2 (mostly vegetable oils, sugar, and flours), and 20% from group 3 (mostly breads, biscuits, sweets, soft drinks, and sausages). The share of group 3 foods increased with income, and represented almost one third of all calories in higher income households. The impact of the replacement of group 1 foods and group 2 ingredients by group 3 products on the overall quality of the diet, eating patterns and health is discussed.