893 resultados para Feature Extraction Algorithms


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Objectives: The purpose of this study was to determine the incidence and clinical symptoms associated with sharp mandibular bone irregularities (SMBI) after lower third molar extraction and to identify possible risk factors for this complication. Study Design: A mixed study design was used. A retrospective cohort study of 1432 lower third molar extractions was done to determine the incidence of SMBI and a retrospective case-control study was done to determine potential demographic and etiologic factors by comparing those patients with postoperative SMBI with controls. Results: Twelve SMBI were found (0.84%). Age was the most important risk factor for this complication. The operated side and the presence of an associated radiolucent image were also significantly related to the development of mandibular bone irregularities. The depth of impaction of the tooth might also be an important factor since erupted or nearly erupted third molars were more frequent in the SMBI group. Conclusions: SMBI are a rare postoperative complication after lower third molar removal. Older patients having left side lower third molars removed are more likely to develop this problem. The treatment should be the removal of the irregularity when the patient is symptomatic

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Objective. Recently, significant advances have been made in the early diagnosis of Alzheimer’s disease from EEG. However, choosing suitable measures is a challenging task. Among other measures, frequency Relative Power and loss of complexity have been used with promising results. In the present study we investigate the early diagnosis of AD using synchrony measures and frequency Relative Power on EEG signals, examining the changes found in different frequency ranges. Approach. We first explore the use of a single feature for computing the classification rate, looking for the best frequency range. Then, we present a multiple feature classification system that outperforms all previous results using a feature selection strategy. These two approaches are tested in two different databases, one containing MCI and healthy subjects (patients age: 71.9 ± 10.2, healthy subjects age: 71.7 ± 8.3), and the other containing Mild AD and healthy subjects (patients age: 77.6 ± 10.0; healthy subjects age: 69.4± 11.5). Main Results. Using a single feature to compute classification rates we achieve a performance of 78.33% for the MCI data set and of 97.56 % for Mild AD. Results are clearly improved using the multiple feature classification, where a classification rate of 95% is found for the MCI data set using 11 features, and 100% for the Mild AD data set using 4 features. Significance. The new features selection method described in this work may be a reliable tool that could help to design a realistic system that does not require prior knowledge of a patient's status. With that aim, we explore the standardization of features for MCI and Mild AD data sets with promising results.

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In the literature on housing market areas, different approaches can be found to defining them, for example, using travel-to-work areas and, more recently, making use of migration data. Here we propose a simple exercise to shed light on which approach performs better. Using regional data from Catalonia, Spain, we have computed housing market areas with both commuting data and migration data. In order to decide which procedure shows superior performance, we have looked at uniformity of prices within areas. The main finding is that commuting algorithms present more homogeneous areas in terms of housing prices.

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Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.

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Antioxidant enzymes are involved in important processes of cell detoxification during oxidative stress and have, therefore, been used as biomarkers in algae. Nevertheless, their limited use in fluvial biofilms may be due to the complexity of such communities. Here, a comparison between different extraction methods was performed to obtain a reliable method for catalase extraction from fluvial biofilms. Homogenization followed by glass bead disruption appeared to be the best compromise for catalase extraction. This method was then applied to a field study in a metal-polluted stream (Riou Mort, France). The most polluted sites were characterized by a catalase activity 4–6 times lower than in the low-polluted site. Results of the comparison process and its application are promising for the use of catalase activity as an early warning biomarker of toxicity using biofilms in the laboratory and in the field

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Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

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A solid phase extraction procedure using Amberlite XAD-1180/Pyrocatechol violet (PV) chelating resin for the determination of iron and lead ions in various environmental samples was established. The procedure is based on the sorption of lead(II) and iron(III) ions onto the resin at pH 9, followed by elution with 1 mol/L HNO3 and determination by flame atomic absorption spectrometry. The influence of alkaline, earth alkaline and some transition metals, as interferents, are discussed. The recoveries for the spiked analytes were greater than 95%. The detection limits for lead and iron by FAAS were 0.37 µg/L and 0.20 µg/L, respectively. Validation of the method described here was performed by using three certified reference materials (SRM 1515 Apple Leaves, SRM 2711 Montana Soil and NRCC-SLRS-4 Riverine Water). The procedure was successfully applied to natural waters and human hair.

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The amphiphilic nature of metal extractants causes the formation of micelles and other microscopic aggregates when in contact with water and an organic diluent. These phenomena and their effects on metal extraction were studied using carboxylic acid (Versatic 10) and organophosphorus acid (Cyanex 272) based extractants. Special emphasis was laid on the study of phase behaviour in a pre neutralisation stage when the extractant is transformed to a sodium or ammonium salt form. The pre neutralised extractants were used to extract nickel and to separate cobalt and nickel. Phase diagrams corresponding to the pre neutralisation stage in a metal extraction process were determined. The maximal solubilisation of the components in the system water(NH3)/extractant/isooctane takes place when the molar ratio between the ammonia salt form and the free form of the extractant is 0.5 for the carboxylic acid and 1 for the organophosphorus acid extractant. These values correspond to the complex stoichiometry of NH4A•HA and NIi4A, respectively. When such a solution is contacted with water a microemulsion is formed. If the aqueous phase contains also metal ions (e.g. Ni²+), complexation will take place on the microscopic interface of the micellar aggregates. Experimental evidence showing that the initial stage of nickel extraction with pre neutralised Versatic 10 is a fast pseudohomogeneous reaction was obtained. About 90% of the metal were extracted in the first 15 s after the initial contact. For nickel extraction with pre neutralised Versatic 10 it was found that the highest metal loading and the lowest residual ammonia and water contents in the organic phase are achieved when the feeds are balanced so that the stoichiometry is 2NH4+(org) = Nit2+(aq). In the case of Co/Ni separation using pre neutralised Cyanex 272 the highest separation is achieved when the Co/extractant molar ratio in the feeds is 1 : 4 and at the same time the optimal degree of neutralisation of the Cyanex 272 is about 50%. The adsorption of the extractants on solid surfaces may cause accumulation of solid fine particles at the interface between the aqueous and organic phases in metal extraction processes. Copper extraction processes are known to suffer of this problem. Experiments were carried out using model silica and mica particles. It was found that high copper loading, aromacity of the diluent, modification agents and the presence of aqueous phase decrease the adsorption of the hydroxyoxime on silica surfaces.

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This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

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The aim of this work is to obtain, purify and characterize biochemically a peroxidase from Copaifera langsdorffii leaves (COP). COP was obtained by acetone precipitation followed by ion-exchange chromatography. Purification yielded 3.5% of peroxidase with the purification factor of 46.86. The COP optimum pH is 6.0 and the temperature is 35 ºC. COP was stable in the pH range of 4.5 to 9.3 and at temperatures below 50.0 ºC. The apparent Michaelis-Menten constants (Km) for guaiacol and H2O2 were 0.04 mM and 0.39 mM respectively. Enzyme turnover was 0.075 s-1 for guaiacol and 0.28 s-1 for hydrogen peroxide. Copaifera langsdorffii leaves showed to be a rich source of active peroxidase (COP) during the whole year. COP could replace HRP, the most used peroxidase, in analytical determinations and treatment of industrial effluents at low cost.

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A simple cloud point extraction procedure is presented for the preconcentration of copper in various samples. After complexation by 4-hydroxy-2-mercapto-6-propylpyrimidine (PTU), copper ions are quantitatively extracted into the phase rich in Triton X-114 after centrifugation. Methanol acidified with 0.5 mol L-1 HNO3 was added to the surfactant-rich phase prior to its analysis by flame atomic absorption spectrometry (FAAS). Analytical parameters including concentrations for PTU, Triton X-114 and HNO3, bath temperature, centrifugation rate and time were optimized. The influences of the matrix ions on the recoveries of copper ions were investigated. The detection limits (3SDb/m, n=4) of 1.6 ng mL-1 along with enrichment factors of 30 for Cu were achieved. The proposed procedure was applied to the analysis of environmental samples.

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A liquid chromatography-tandem mass spectrometry method with atmospheric pressure chemical ionization (LC-APCI/MS/MS) was validated for the determination of etoricoxib in human plasma using antipyrin as internal standard, followed by on-line solid-phase extraction. The method was performed on a Luna C18 column and the mobile phase consisted of acetonitrile:water (95:5, v/v)/ammonium acetate (pH 4.0; 10 mM), run at a flow rate of 0.6 mL/min. The method was linear in the range of 1-5000 ng/mL (r²>0.99). The lower limit of quantitation was 1 ng/mL. The recoveries were within 93.72-96.18%. Moreover, method validation demonstrated acceptable results for the precision, accuracy and stability studies.

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Liquid-liquid extraction is a mass transfer process for recovering the desired components from the liquid streams by contacting it to non-soluble liquid solvent. Literature part of this thesis deals with theory of the liquid-liquid extraction and the main steps of the extraction process design. The experimental part of this thesis investigates the extraction of organic acids from aqueous solution. The aim was to find the optimal solvent for recovering the organic acids from aqueous solutions. The other objective was to test the selected solvent in pilot scale with packed column and compare the effectiveness of the structured and the random packing, the effect of dispersed phase selection and the effect of packing material wettability properties. Experiments showed that selected solvent works well with dilute organic acid solutions. The random packing proved to be more efficient than the structured packing due to higher hold-up of the dispersed phase. Dispersing the phase that is present in larger volume proved to more efficient. With the random packing the material that was wetted by the dispersed phase was more efficient due to higher hold-up of the dispersed phase. According the literature, the behavior is usually opposite.

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Lettuce is worldwide known as the most important vegetable. In this context, most farmers are searching new techniques for best quality products including hydropony. However, nitrate is of great concern, since it has a negative impact on human metabolism. The main objective of the present work was to evaluate the nitrate content of lettuce produced by conventional and hydroponic systems. The determination was conducted by ion chromatography and a new method of extraction was tested using microwave oven digestion. The results indicated that nitrate level produced in the conventional system was lower than in the hydroponic system.

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Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.