746 resultados para Music algorithm


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Objective: The epilepsy associated with the hypothalamic hamartomas constitutes a syndrome with peculiar seizures, usually refractory to medical therapy, mild cognitive delay, behavioural problems and multifocal spike activity in the scalp electroencephalogram (EEG). The cortical origin of spikes has been widely assumed but not specifically demonstrated. Methods: We present results of a source analysis of interictal spikes from 4 patients (age 2–25 years) with epilepsy and hypothalamic hamartoma, using EEG scalp recordings (32 electrodes) and realistic boundary element models constructed from volumetric magnetic resonance imaging (MRIs). Multifocal spike activity was the most common finding, distributed mainly over the frontal and temporal lobes. A spike classification based on scalp topography was done and averaging within each class performed to improve the signal to noise ratio. Single moving dipole models were used, as well as the Rap-MUSIC algorithm. Results: All spikes with good signal to noise ratio were best explained by initial deep sources in the neighbourhood of the hamartoma, with late sources located in the cortex. Not a single patient could have his spike activity explained by a combination of cortical sources. Conclusions: Overall, the results demonstrate a consistent origin of spike activity in the subcortical region in the neighbourhood of the hamartoma, with late spread to cortical areas.

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The problem of localizing a scatterer, which represents a tumor, in a homogeneous circular domain, which represents a breast, is addressed. A breast imaging method based on microwaves is considered. The microwave imaging involves to several techniques for detecting, localizing and characterizing tumors in breast tissues. In all such methods an electromagnetic inverse scattering problem exists. For the scattering detection method, an algorithm based on a linear procedure solution, inspired by MUltiple SIgnal Classification algorithm (MUSIC) and Time Reversal method (TR), is implemented. The algorithm returns a reconstructed image of the investigation domain in which it is detected the scatterer position. This image is called pseudospectrum. A preliminary performance analysis of the algorithm vying the working frequency is performed: the resolution and the signal-to-noise ratio of the pseudospectra are improved if a multi-frequency approach is considered. The Geometrical Mean-MUSIC algorithm (GM- MUSIC) is proposed as multi-frequency method. The performance of the GMMUSIC is tested in different real life computer simulations. The performed analysis shows that the algorithm detects the scatterer until the electrical parameters of the breast are known. This is an evident limit, since, in a real life situation, the anatomy of the breast is unknown. An improvement in GM-MUSIC is proposed: the Eye-GMMUSIC algorithm. Eye-GMMUSIC algorithm needs no a priori information on the electrical parameters of the breast. It is an optimizing algorithm based on the pattern search algorithm: it searches the breast parameters which minimize the Signal-to-Clutter Mean Ratio (SCMR) in the signal. Finally, the GM-MUSIC and the Eye-GMMUSIC algorithms are tested on a microwave breast cancer detection system consisting of an dipole antenna, a Vector Network Analyzer and a novel breast phantom built at University of Bologna. The reconstruction of the experimental data confirm the GM-MUSIC ability to localize a scatterer in a homogeneous medium.

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Direction-of-arrival (DOA) estimation is susceptible to errors introduced by the presence of real-ground and resonant size scatterers in the vicinity of the antenna array. To compensate for these errors pre-calibration and auto-calibration techniques are presented. The effects of real-ground constituent parameters on the mutual coupling (MC) of wire type antenna arrays for DOA estimation are investigated. This is accomplished by pre-calibration of the antenna array over the real-ground using the finite element method (FEM). The mutual impedance matrix is pre-estimated and used to remove the perturbations in the received terminal voltage. The unperturbed terminal voltage is incorporated in MUSIC algorithm to estimate DOAs. First, MC of quarter wave monopole antenna arrays is investigated. This work augments an existing MC compensation technique for ground-based antennas and proposes reduction in MC for antennas over finite ground as compared to the perfect ground. A factor of 4 decrease in both the real and imaginary parts of the MC is observed when considering a poor ground versus a perfectly conducting one for quarter wave monopoles in the receiving mode. A simulated result to show the compensation of errors direction of arrival (DOA) estimation with actual realization of the environment is also presented. Secondly, investigations for the effects on received MC of λ/2 dipole arrays placed near real-earth are carried out. As a rule of thumb, estimation of mutual coupling can be divided in two regions of antenna height that is very near ground 0

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La tecnología de múltiples antenas ha evolucionado para dar soporte a los actuales y futuros sistemas de comunicaciones inalámbricas en su afán por proporcionar la calidad de señal y las altas tasas de transmisión que demandan los nuevos servicios de voz, datos y multimedia. Sin embargo, es fundamental comprender las características espaciales del canal radio, ya que son las características del propio canal lo que limita en gran medida las prestaciones de los sistemas de comunicación actuales. Por ello surge la necesidad de estudiar la estructura espacial del canal de propagación para poder diseñar, evaluar e implementar de forma más eficiente tecnologías multiantena en los actuales y futuros sistemas de comunicación inalámbrica. Las tecnologías multiantena denominadas antenas inteligentes y MIMO han generado un gran interés en el área de comunicaciones inalámbricas, por ejemplo los sistemas de telefonía celular o más recientemente en las redes WLAN (Wireless Local Area Network), principalmente por la mejora que proporcionan en la calidad de las señales y en la tasa de transmisión de datos, respectivamente. Las ventajas de estas tecnologías se fundamentan en el uso de la dimensión espacial para obtener ganancia por diversidad espacial, como ya sucediera con las tecnologías FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access) y CDMA (Code Division Multiplexing Access) para obtener diversidad en las dimensiones de frecuencia, tiempo y código, respectivamente. Esta Tesis se centra en estudiar las características espaciales del canal con sistemas de múltiples antenas mediante la estimación de los perfiles de ángulos de llegada (DoA, Direction-of- Arrival) considerando esquemas de diversidad en espacio, polarización y frecuencia. Como primer paso se realiza una revisión de los sistemas con antenas inteligentes y los sistemas MIMO, describiendo con detalle la base matemática que sustenta las prestaciones ofrecidas por estos sistemas. Posteriormente se aportan distintos estudios sobre la estimación de los perfiles de DoA de canales radio con sistemas multiantena evaluando distintos aspectos de antenas, algoritmos de estimación, esquemas de polarización, campo lejano y campo cercano de las fuentes. Así mismo, se presenta un prototipo de medida MIMO-OFDM-SPAA3D en la banda ISM (Industrial, Scientific and Medical) de 2,45 Ghz, el cual está preparado para caracterizar experimentalmente el rendimiento de los sistemas MIMO, y para caracterizar espacialmente canales de propagación, considerando los esquemas de diversidad espacial, por polarización y frecuencia. Los estudios aportados se describen a continuación. Los sistemas de antenas inteligentes dependen en gran medida de la posición de los usuarios. Estos sistemas están equipados con arrays de antenas, los cuales aportan la diversidad espacial necesaria para obtener una representación espacial fidedigna del canal radio a través de los perfiles de DoA (DoA, Direction-of-Arrival) y por tanto, la posición de las fuentes de señal. Sin embargo, los errores de fabricación de arrays así como ciertos parámetros de señal conlleva un efecto negativo en las prestaciones de estos sistemas. Por ello se plantea un modelo de señal parametrizado que permite estudiar la influencia que tienen estos factores sobre los errores de estimación de DoA, tanto en acimut como en elevación, utilizando los algoritmos de estimación de DOA más conocidos en la literatura. A partir de las curvas de error, se pueden obtener parámetros de diseño para sistemas de localización basados en arrays. En un segundo estudio se evalúan esquemas de diversidad por polarización con los sistemas multiantena para mejorar la estimación de los perfiles de DoA en canales que presentan pérdidas por despolarización. Para ello se desarrolla un modelo de señal en array con sensibilidad de polarización que toma en cuenta el campo electromagnético de ondas planas. Se realizan simulaciones MC del modelo para estudiar el efecto de la orientación de la polarización como el número de polarizaciones usadas en el transmisor como en el receptor sobre la precisión en la estimación de los perfiles de DoA observados en el receptor. Además, se presentan los perfiles DoA obtenidos en escenarios quasiestáticos de interior con un prototipo de medida MIMO 4x4 de banda estrecha en la banda de 2,45 GHz, los cuales muestran gran fidelidad con el escenario real. Para la obtención de los perfiles DoA se propone un método basado en arrays virtuales, validado con los datos de simulación y los datos experimentales. Con relación a la localización 3D de fuentes en campo cercano (zona de Fresnel), se presenta un tercer estudio para obtener con gran exactitud la estructura espacial del canal de propagación en entornos de interior controlados (en cámara anecóica) utilizando arrays virtuales. El estudio analiza la influencia del tamaño del array y el diagrama de radiación en la estimación de los parámetros de localización proponiendo, para ello, un modelo de señal basado en un vector de enfoque de onda esférico (SWSV). Al aumentar el número de antenas del array se consigue reducir el error RMS de estimación y mejorar sustancialmente la representación espacial del canal. La estimación de los parámetros de localización se lleva a cabo con un nuevo método de búsqueda multinivel adaptativo, propuesto con el fin de reducir drásticamente el tiempo de procesado que demandan otros algoritmos multivariable basados en subespacios, como el MUSIC, a costa de incrementar los requisitos de memoria. Las simulaciones del modelo arrojan resultados que son validados con resultados experimentales y comparados con el límite de Cramer Rao en términos del error cuadrático medio. La compensación del diagrama de radiación acerca sustancialmente la exactitud de estimación de la distancia al límite de Cramer Rao. Finalmente, es igual de importante la evaluación teórica como experimental de las prestaciones de los sistemas MIMO-OFDM. Por ello, se presenta el diseño e implementación de un prototipo de medida MIMO-OFDM-SPAA3D autocalibrado con sistema de posicionamiento de antena automático en la banda de 2,45 Ghz con capacidad para evaluar la capacidad de los sistemas MIMO. Además, tiene la capacidad de caracterizar espacialmente canales MIMO, incorporando para ello una etapa de autocalibración para medir la respuesta en frecuencia de los transmisores y receptores de RF, y así poder caracterizar la respuesta de fase del canal con mayor precisión. Este sistema incorpora un posicionador de antena automático 3D (SPAA3D) basado en un scanner con 3 brazos mecánicos sobre los que se desplaza un posicionador de antena de forma independiente, controlado desde un PC. Este posicionador permite obtener una gran cantidad de mediciones del canal en regiones locales, lo cual favorece la caracterización estadística de los parámetros del sistema MIMO. Con este prototipo se realizan varias campañas de medida para evaluar el canal MIMO en términos de capacidad comparando 2 esquemas de polarización y tomando en cuenta la diversidad en frecuencia aportada por la modulación OFDM en distintos escenarios. ABSTRACT Multiple-antennas technologies have been evolved to be the support of the actual and future wireless communication systems in its way to provide the high quality and high data rates required by new data, voice and data services. However, it is important to understand the behavior of the spatial characteristics of the radio channel, since the channel by itself limits the performance of the actual wireless communications systems. This drawback raises the need to understand the spatial structure of the propagation channel in order to design, assess, and develop more efficient multiantenna technologies for the actual and future wireless communications systems. Multiantenna technologies such as ‘Smart Antennas’ and MIMO systems have generated great interest in the field of wireless communications, i.e. cellular communications systems and more recently WLAN (Wireless Local Area Networks), mainly because the higher quality and the high data rate they are able to provide. Their technological benefits are based on the exploitation of the spatial diversity provided by the use of multiple antennas as happened in the past with some multiaccess technologies such as FDMA (Frequency Division Multiplexing Access), TDMA (Time Division Multiplexing Access), and CDMA (Code Division Multiplexing Access), which give diversity in the domains of frequency, time and code, respectively. This Thesis is mainly focus to study the spatial channel characteristics using schemes of multiple antennas considering several diversity schemes such as space, polarization, and frequency. The spatial characteristics will be study in terms of the direction-of-arrival profiles viewed at the receiver side of the radio link. The first step is to do a review of the smart antennas and MIMO systems technologies highlighting their advantages and drawbacks from a mathematical point of view. In the second step, a set of studies concerning the spatial characterization of the radio channel through the DoA profiles are addressed. The performance of several DoA estimation methods is assessed considering several aspects regarding antenna array structure, polarization diversity, and far-field and near-field conditions. Most of the results of these studies come from simulations of data models and measurements with real multiantena prototypes. In the same way, having understand the importance of validate the theoretical data models with experimental results, a 2,4 GHz MIMO-OFDM-SPAA2D prototype is presented. This prototype is intended for evaluating MIMO-OFDM capacity in indoor and outdoor scenarios, characterize the spatial structure of radio channels, assess several diversity schemes such as polarization, space, and frequency diversity, among others aspects. The studies reported are briefly described below. As is stated in Chapter two, the determination of user position is a fundamental task to be resolved for the smart antenna systems. As these systems are equipped with antenna arrays, they can provide the enough spatial diversity to accurately draw the spatial characterization of the radio channel through the DoA profiles, and therefore the source location. However, certain real implementation factors related to antenna errors, signals, and receivers will certainly reduce the performance of such direction finding systems. In that sense, a parameterized narrowband signal model is proposed to evaluate the influence of these factors in the location parameter estimation through extensive MC simulations. The results obtained from several DoA algorithms may be useful to extract some parameter design for directing finding systems based on arrays. The second study goes through the importance that polarization schemes can have for estimating far-field DoA profiles in radio channels, particularly for scenarios that may introduce polarization losses. For this purpose, a narrowband signal model with polarization sensibility is developed to conduct an analysis of several polarization schemes at transmitter (TX) and receiver (RX) through extensive MC simulations. In addition, spatial characterization of quasistatic indoor scenarios is also carried out using a 2.45 GHz MIMO prototype equipped with single and dual-polarized antennas. A good agreement between the measured DoA profiles with the propagation scenario is achieved. The theoretical and experimental evaluation of polarization schemes is performed using virtual arrays. In that case, a DoA estimation method is proposed based on adding an phase reference to properly track the DoA, which shows good results. In the third study, the special case of near-field source localization with virtual arrays is addressed. Most of DoA estimation algorithms are focused in far-field source localization where the radiated wavefronts are assume to be planar waves at the receive array. However, when source are located close to the array, the assumption of plane waves is no longer valid as the wavefronts exhibit a spherical behavior along the array. Thus, a faster and effective method of azimuth, elevation angles-of-arrival, and range estimation for near-field sources is proposed. The efficacy of the proposed method is evaluated with simulation and validated with measurements collected from a measurement campaign carried out in a controlled propagation environment, i.e. anechoic chamber. Moreover, the performance of the method is assessed in terms of the RMSE for several array sizes, several source positions, and taking into account the effect of radiation pattern. In general, better results are obtained with larger array and larger source distances. The effect of the antennas is included in the data model leading to more accurate results, particularly for range rather than for angle estimation. Moreover, a new multivariable searching method based on the MUSIC algorithm, called MUSA (multilevel MUSIC-based algorithm), is presented. This method is proposed to estimate the 3D location parameters in a faster way than other multivariable algorithms, such as MUSIC algorithm, at the cost of increasing the memory size. Finally, in the last chapter, a MIMO-OFDM-SPAA3D prototype is presented to experimentally evaluate different MIMO schemes regarding antennas, polarization, and frequency in different indoor and outdoor scenarios. The prototype has been developed on a Software-Defined Radio (SDR) platform. It allows taking measurements where future wireless systems will be developed. The novelty of this prototype is concerning the following 2 subsystems. The first one is the tridimensional (3D) antenna positioning system (SPAA3D) based on three linear scanners which is developed for making automatic testing possible reducing errors of the antenna array positioning. A set of software has been developed for research works such as MIMO channel characterization, MIMO capacity, OFDM synchronization, and so on. The second subsystem is the RF autocalibration module at the TX and RX. This subsystem allows to properly tracking the spatial structure of indoor and outdoor channels in terms of DoA profiles. Some results are draw regarding performance of MIMO-OFDM systems with different polarization schemes and different propagation environments.

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A dedicated algorithm for sparse spectral representation of music sound is presented. The goal is to enable the representation of a piece of music signal as a linear superposition of as few spectral components as possible, without affecting the quality of the reproduction. A representation of this nature is said to be sparse. In the present context sparsity is accomplished by greedy selection of the spectral components, from an overcomplete set called a dictionary. The proposed algorithm is tailored to be applied with trigonometric dictionaries. Its distinctive feature being that it avoids the need for the actual construction of the whole dictionary, by implementing the required operations via the fast Fourier transform. The achieved sparsity is theoretically equivalent to that rendered by the orthogonal matching pursuit (OMP) method. The contribution of the proposed dedicated implementation is to extend the applicability of the standard OMP algorithm, by reducing its storage and computational demands. The suitability of the approach for producing sparse spectral representation is illustrated by comparison with the traditional method, in the line of the short time Fourier transform, involving only the corresponding orthonormal trigonometric basis.

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In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests. (c) 2010 American Institute of Physics. [doi: 10.1063/1.3487516]

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This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETS1) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection algorithm. The wavelet filter bank can divide input speech signal into several frequency bands so that the signal power level at each sub-band can be calculated. In addition, the background noise level can be estimated in each sub-band by using the wavelet de-noising method. The wavelet filter bank is also derived to detect correlated complex signals like music. Then the proposed algorithm can apply SVM to train an optimized non-linear VAD decision rule involving the sub-band power, noise level, pitch period, tone flag, and complex signals warning flag of input speech signals. By the use of the trained SVM, the proposed VAD algorithm can produce more accurate detection results. Various experimental results carried out from the Aurora speech database with different noise conditions show that the proposed algorithm gives considerable VAD performances superior to the AMR-NB VAD Options 1 and 2, and AMR-WB VAD. (C) 2009 Elsevier Ltd. All rights reserved.

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In this paper, a musical learning application for mobile devices is presented. The main objective is to design and develop an application capable of offering exercises to practice and improve a selection of music skills, to users interested in music learning and training. The selected music skills are rhythm, melodic dictation and singing. The application includes an audio signal analysis system implemented making use of the Goertzel algorithm which is employed in singing exercises to check if the user sings the right musical note. This application also includes a graphical interface to represent musical symbols. A set of tests were conducted to check the usefulness of the application as musical learning tool. A group of users with different music knowledge have tested the system and reported to have found it effective, easy and accessible.

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Pitch Estimation, also known as Fundamental Frequency (F0) estimation, has been a popular research topic for many years, and is still investigated nowadays. The goal of Pitch Estimation is to find the pitch or fundamental frequency of a digital recording of a speech or musical notes. It plays an important role, because it is the key to identify which notes are being played and at what time. Pitch Estimation of real instruments is a very hard task to address. Each instrument has its own physical characteristics, which reflects in different spectral characteristics. Furthermore, the recording conditions can vary from studio to studio and background noises must be considered. This dissertation presents a novel approach to the problem of Pitch Estimation, using Cartesian Genetic Programming (CGP).We take advantage of evolutionary algorithms, in particular CGP, to explore and evolve complex mathematical functions that act as classifiers. These classifiers are used to identify piano notes pitches in an audio signal. To help us with the codification of the problem, we built a highly flexible CGP Toolbox, generic enough to encode different kind of programs. The encoded evolutionary algorithm is the one known as 1 + , and we can choose the value for . The toolbox is very simple to use. Settings such as the mutation probability, number of runs and generations are configurable. The cartesian representation of CGP can take multiple forms and it is able to encode function parameters. It is prepared to handle with different type of fitness functions: minimization of f(x) and maximization of f(x) and has a useful system of callbacks. We trained 61 classifiers corresponding to 61 piano notes. A training set of audio signals was used for each of the classifiers: half were signals with the same pitch as the classifier (true positive signals) and the other half were signals with different pitches (true negative signals). F-measure was used for the fitness function. Signals with the same pitch of the classifier that were correctly identified by the classifier, count as a true positives. Signals with the same pitch of the classifier that were not correctly identified by the classifier, count as a false negatives. Signals with different pitch of the classifier that were not identified by the classifier, count as a true negatives. Signals with different pitch of the classifier that were identified by the classifier, count as a false positives. Our first approach was to evolve classifiers for identifying artifical signals, created by mathematical functions: sine, sawtooth and square waves. Our function set is basically composed by filtering operations on vectors and by arithmetic operations with constants and vectors. All the classifiers correctly identified true positive signals and did not identify true negative signals. We then moved to real audio recordings. For testing the classifiers, we picked different audio signals from the ones used during the training phase. For a first approach, the obtained results were very promising, but could be improved. We have made slight changes to our approach and the number of false positives reduced 33%, compared to the first approach. We then applied the evolved classifiers to polyphonic audio signals, and the results indicate that our approach is a good starting point for addressing the problem of Pitch Estimation.

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Les techniques des directions d’arrivée (DOA) sont une voie prometteuse pour accroitre la capacité des systèmes et les services de télécommunications en permettant de mieux estimer le canal radio-mobile. Elles permettent aussi de suivre précisément des usagers cellulaires pour orienter les faisceaux d’antennes dans leur direction. S’inscrivant dans ce contexte, ce présent mémoire décrit étape par étape l’implémentation de l’algorithme de haut niveau MUSIC (MUltiple SIgnal Classification) sur une plateforme FPGA afin de déterminer en temps réel l’angle d’arrivée d’une ou des sources incidentes à un réseau d’antennes. Le concept du prototypage rapide des lois de commande (RCP) avec les outils de XilinxTM System generator (XSG) et du MBDK (Model Based Design Kit) de NutaqTM est le concept de développement utilisé. Ce concept se base sur une programmation de code haut niveau à travers des modèles, pour générer automatiquement un code de bas niveau. Une attention particulière est portée sur la méthode choisie pour résoudre le problème de la décomposition en valeurs et vecteurs propres de la matrice complexe de covariance par l’algorithme de Jacobi. L’architecture mise en place implémentant cette dernière dans le FPGA (Field Programmable Gate Array) est détaillée. Par ailleurs, il est prouvé que MUSIC ne peut effectuer une estimation intéressante de la position des sources sans une calibration préalable du réseau d’antennes. Ainsi, la technique de calibration par matrice G utilisée dans ce projet est présentée, en plus de son modèle d’implémentation. Enfin, les résultats expérimentaux du système mis à l’épreuve dans un environnement réel en présence d’une source puis de deux sources fortement corrélées sont illustrés et analysés.

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Lipidic mixtures present a particular phase change profile highly affected by their unique crystalline structure. However, classical solid-liquid equilibrium (SLE) thermodynamic modeling approaches, which assume the solid phase to be a pure component, sometimes fail in the correct description of the phase behavior. In addition, their inability increases with the complexity of the system. To overcome some of these problems, this study describes a new procedure to depict the SLE of fatty binary mixtures presenting solid solutions, namely the Crystal-T algorithm. Considering the non-ideality of both liquid and solid phases, this algorithm is aimed at the determination of the temperature in which the first and last crystal of the mixture melts. The evaluation is focused on experimental data measured and reported in this work for systems composed of triacylglycerols and fatty alcohols. The liquidus and solidus lines of the SLE phase diagrams were described by using excess Gibbs energy based equations, and the group contribution UNIFAC model for the calculation of the activity coefficients of both liquid and solid phases. Very low deviations of theoretical and experimental data evidenced the strength of the algorithm, contributing to the enlargement of the scope of the SLE modeling.

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PURPOSE: To compare the Full Threshold (FT) and SITA Standard (SS) strategies in glaucomatous patients undergoing automated perimetry for the first time. METHODS: Thirty-one glaucomatous patients who had never undergone perimetry underwent automated perimetry (Humphrey, program 30-2) with both FT and SS on the same day, with an interval of at least 15 minutes. The order of the examination was randomized, and only one eye per patient was analyzed. Three analyses were performed: a) all the examinations, regardless of the order of application; b) only the first examinations; c) only the second examinations. In order to calculate the sensitivity of both strategies, the following criteria were used to define abnormality: glaucoma hemifield test (GHT) outside normal limits, pattern standard deviation (PSD) <5%, or a cluster of 3 adjacent points with p<5% at the pattern deviation probability plot. RESULTS: When the results of all examinations were analyzed regardless of the order in which they were performed, the number of depressed points with p<0.5% in the pattern deviation probability map was significantly greater with SS (p=0.037), and the sensitivities were 87.1% for SS and 77.4% for FT (p=0.506). When only the first examinations were compared, there were no statistically significant differences regarding the number of depressed points, but the sensitivity of SS (100%) was significantly greater than that obtained with FT (70.6%) (p=0.048). When only the second examinations were compared, there were no statistically significant differences regarding the number of depressed points, and the sensitivities of SS (76.5%) and FT (85.7%) (p=0.664). CONCLUSION: SS may have a higher sensitivity than FT in glaucomatous patients undergoing automated perimetry for the first time. However, this difference tends to disappear in subsequent examinations.

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The network of HIV counseling and testing centers in São Paulo, Brazil is a major source of data used to build epidemiological profiles of the client population. We examined HIV-1 incidence from November 2000 to April 2001, comparing epidemiological and socio-behavioral data of recently-infected individuals with those with long-standing infection. A less sensitive ELISA was employed to identify recent infection. The overall incidence of HIV-1 infection was 0.53/100/year (95% CI: 0.31-0.85/100/year): 0.77/100/year for males (95% CI: 0.42-1.27/100/year) and 0.22/100/ year (95% CI: 0.05-0.59/100/year) for females. Overall HIV-1 prevalence was 3.2% (95% CI: 2.8-3.7%), being 4.0% among males (95% CI: 3.3-4.7%) and 2.1% among females (95% CI: 1.6-2.8%). Recent infections accounted for 15% of the total (95% CI: 10.2-20.8%). Recent infection correlated with being younger and male (p = 0.019). Therefore, recent infection was more common among younger males and older females.

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This work develops a method for solving ordinary differential equations, that is, initial-value problems, with solutions approximated by using Legendre's polynomials. An iterative procedure for the adjustment of the polynomial coefficients is developed, based on the genetic algorithm. This procedure is applied to several examples providing comparisons between its results and the best polynomial fitting when numerical solutions by the traditional Runge-Kutta or Adams methods are available. The resulting algorithm provides reliable solutions even if the numerical solutions are not available, that is, when the mass matrix is singular or the equation produces unstable running processes.