917 resultados para post-processing method
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Statistical shape models (SSMs) have been used widely as a basis for segmenting and interpreting complex anatomical structures. The robustness of these models are sensitive to the registration procedures, i.e., establishment of a dense correspondence across a training data set. In this work, two SSMs based on the same training data set of scoliotic vertebrae, and registration procedures were compared. The first model was constructed based on the original binary masks without applying any image pre- and post-processing, and the second was obtained by means of a feature preserving smoothing method applied to the original training data set, followed by a standard rasterization algorithm. The accuracies of the correspondences were assessed quantitatively by means of the maximum of the mean minimum distance (MMMD) and Hausdorf distance (H(D)). Anatomical validity of the models were quantified by means of three different criteria, i.e., compactness, specificity, and model generalization ability. The objective of this study was to compare quasi-identical models based on standard metrics. Preliminary results suggest that the MMMD distance and eigenvalues are not sensitive metrics for evaluating the performance and robustness of SSMs.
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We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.
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Forward-looking ground penetrating radar shows promise for detection of improvised explosive devices in active war zones. Because of certain insurmountable physical limitations, post-processing algorithm development is the most popular research topic in this field. One such investigative avenue explores the worthiness of frequency analysis during data post-processing. Using the finite difference time domain numerical method, simulations are run to test both mine and clutter frequency response. Mines are found to respond strongest at low frequencies and cause periodic changes in ground penetrating radar frequency results. These results are called into question, however, when clutter, a phenomenon generally known to be random, is also found to cause periodic frequency effects. Possible causes, including simulation inaccuracy, are considered. Although the clutter models used are found to be inadequately random, specular reflections of differing periodicity are found to return from both the mine and the ground. The presence of these specular reflections offers a potential alternative method of determining a mine’s presence.
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Biodegradable nanoparticles are at the forefront of drug delivery research as they provide numerous advantages over traditional drug delivery methods. An important factor affecting the ability of nanoparticles to circulate within the blood stream and interact with cells is their morphology. In this study a novel processing method, confined impinging jet mixing, was used to form poly (lactic acid) nanoparticles through a solvent-diffusion process with Pluronic F-127 being used as a stabilizing agent. This study focused on the effects of Reynolds number (flow rate), surfactant presence in mixing, and polymer concentration on the morphology of poly (lactic acid) nanoparticles. In addition to looking at the parameters affecting poly (lactic acid) morphology, this study attempted to improve nanoparticle isolation and purification methods to increase nanoparticle yield and ensure specific morphologies were not being excluded during isolation and purification. The isolation and purification methods used in this study were centrifugation and a stir cell. This study successfully produced particles having pyramidal and cubic morphologies. Despite successful production of these morphologies the yield of non-spherical particles was very low, additionally great variability existed between redundant trails. Surfactant was determined to be very important for the stabilization of nanoparticles in solution but appears to be unnecessary for the formation of nanoparticles. Isolation and purification methods that produce a high yield of surfactant free particles have still not been perfected and additional testing will be necessary for improvement.¿
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Multislice-computed tomography (MSCT) and magnetic resonance imaging (MRI) are increasingly used for forensic purposes. Based on broad experience in clinical neuroimaging, post-mortem MSCT and MRI were performed in 57 forensic cases with the goal to evaluate the radiological methods concerning their usability for forensic head and brain examination. An experienced clinical radiologist evaluated the imaging data. The results were compared to the autopsy findings that served as the gold standard with regard to common forensic neurotrauma findings such as skull fractures, soft tissue lesions of the scalp, various forms of intracranial hemorrhage or signs of increased brain pressure. The sensitivity of the imaging methods ranged from 100% (e.g., heat-induced alterations, intracranial gas) to zero (e.g., mediobasal impression marks as a sign of increased brain pressure, plaques jaunes). The agreement between MRI and CT was 69%. The radiological methods prevalently failed in the detection of lesions smaller than 3mm of size, whereas they were generally satisfactory concerning the evaluation of intracranial hemorrhage. Due to its advanced 2D and 3D post-processing possibilities, CT in particular possessed certain advantages in comparison with autopsy with regard to forensic reconstruction. MRI showed forensically relevant findings not seen during autopsy in several cases. The partly limited sensitivity of imaging that was observed in this retrospective study was based on several factors: besides general technical limitations it became apparent that clinical radiologists require a sound basic forensic background in order to detect specific signs. Focused teaching sessions will be essential to improve the outcome in future examinations. On the other hand, the autopsy protocols should be further standardized to allow an exact comparison of imaging and autopsy data. In consideration of these facts, MRI and CT have the power to play an important role in future forensic neuropathological examination.
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We present an algorithm for estimating dense image correspondences. Our versatile approach lends itself to various tasks typical for video post-processing, including image morphing, optical flow estimation, stereo rectification, disparity/depth reconstruction, and baseline adjustment. We incorporate recent advances in feature matching, energy minimization, stereo vision, and data clustering into our approach. At the core of our correspondence estimation we use Efficient Belief Propagation for energy minimization. While state-of-the-art algorithms only work on thumbnail-sized images, our novel feature downsampling scheme in combination with a simple, yet efficient data term compression, can cope with high-resolution data. The incorporation of SIFT (Scale-Invariant Feature Transform) features into data term computation further resolves matching ambiguities, making long-range correspondence estimation possible. We detect occluded areas by evaluating the correspondence symmetry, we further apply Geodesic matting to automatically determine plausible values in these regions.
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Magnetic resonance imaging, with its exquisite soft tissue contrast, is an ideal modality for investigating spinal cord pathology. While conventional MRI techniques are very sensitive for spinal cord pathology, their specificity is somewhat limited. Diffusion MRI is an advanced technique which is a very sensitive and specific indicator of the integrity of white matter tracts. Diffusion imaging has been shown to detect early ischemic changes in white matter, while conventional imaging demonstrates no change. By acquiring the complete apparent diffusion tensor (ADT), tissue diffusion properties can be expressed in terms of quantitative and rotationally invariant parameters. ^ Systematic study of SCI in vivo requires controlled animal models such as the popular rat model. To date, studies of spinal cord using ADT imaging have been performed exclusively in fixed, excised spinal cords, introducing inevitable artifacts and losing the benefits of MRI's noninvasive nature. In vivo imaging reflects the actual in vivo tissue properties, and allows each animal to be imaged at multiple time points, greatly reducing the number of animals required to achieve statistical significance. Because the spinal cord is very small, the available signal-to-noise ratio (SNR) is very low. Prior spin-echo based ADT studies of rat spinal cord have relied on high magnetic field strengths and long imaging times—on the order of 10 hours—for adequate SNR. Such long imaging times are incompatible with in vivo imaging, and are not relevant for imaging the early phases following SCI. Echo planar imaging (EPI) is one of the fastest imaging methods, and is popular for diffusion imaging. However, EPI further lowers the image SNR, and is very sensitive to small imperfections in the magnetic field, such as those introduced by the bony spine. Additionally, The small field-of-view (FOV) needed for spinal cord imaging requires large imaging gradients which generate EPI artifacts. The addition of diffusion gradients introduces yet further artifacts. ^ This work develops a method for rapid EPI-based in vivo diffusion imaging of rat spinal cord. The method involves improving the SNR using an implantable coil; reducing magnetic field inhomogeneities by means of an autoshim, and correcting EPI artifacts by post-processing. New EPI artifacts due to diffusion gradients described, and post-processing correction techniques are developed. ^ These techniques were used to obtain rotationally invariant diffusion parameters from 9 animals in vivo, and were validated using the gold-standard, but slow, spinecho based diffusion sequence. These are the first reported measurements of the ADT in spinal cord in vivo . ^ Many of the techniques described are equally applicable toward imaging of human spinal cord. We anticipate that these techniques will aid in evaluating and optimizing potential therapies, and will lead to improved patient care. ^
Bathymetric map of Heron Reef, Australia, derived from airborne hyperspectral data at 1 m resolution
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A simple method for efficient inversion of arbitrary radiative transfer models for image analysis is presented. The method operates by representing the shape of the function that maps model parameters to spectral reflectance by an adaptive look-up tree (ALUT) that evenly distributes the discretization error of tabulated reflectances in spectral space. A post-processing step organizes the data into a binary space partitioning tree that facilitates an efficient inversion search algorithm. In an example shallow water remote sensing application, the method performs faster than an implementation of previously published methodology and has the same accuracy in bathymetric retrievals. The method has no user configuration parameters requiring expert knowledge and minimizes the number of forward model runs required, making it highly suitable for routine operational implementation of image analysis methods. For the research community, straightforward and robust inversion allows research to focus on improving the radiative transfer models themselves without the added complication of devising an inversion strategy.
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This paper describes the UPM system for translation task at the EMNLP 2011 workshop on statistical machine translation (http://www.statmt.org/wmt11/), and it has been used for both directions: Spanish-English and English-Spanish. This system is based on Moses with two new modules for pre and post processing the sentences. The main contribution is the method proposed (based on the similarity with the source language test set) for selecting the sentences for training the models and adjusting the weights. With system, we have obtained a 23.2 BLEU for Spanish-English and 21.7 BLEU for EnglishSpanish
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El estudio de materiales, especialmente biológicos, por medios no destructivos está adquiriendo una importancia creciente tanto en las aplicaciones científicas como industriales. Las ventajas económicas de los métodos no destructivos son múltiples. Existen numerosos procedimientos físicos capaces de extraer información detallada de las superficie de la madera con escaso o nulo tratamiento previo y mínima intrusión en el material. Entre los diversos métodos destacan las técnicas ópticas y las acústicas por su gran versatilidad, relativa sencillez y bajo coste. Esta tesis pretende establecer desde la aplicación de principios simples de física, de medición directa y superficial, a través del desarrollo de los algoritmos de decisión mas adecuados basados en la estadística, unas soluciones tecnológicas simples y en esencia, de coste mínimo, para su posible aplicación en la determinación de la especie y los defectos superficiales de la madera de cada muestra tratando, en la medida de lo posible, no alterar su geometría de trabajo. Los análisis desarrollados han sido los tres siguientes: El primer método óptico utiliza las propiedades de la luz dispersada por la superficie de la madera cuando es iluminada por un laser difuso. Esta dispersión produce un moteado luminoso (speckle) cuyas propiedades estadísticas permiten extraer propiedades muy precisas de la estructura tanto microscópica como macroscópica de la madera. El análisis de las propiedades espectrales de la luz laser dispersada genera ciertos patrones mas o menos regulares relacionados con la estructura anatómica, composición, procesado y textura superficial de la madera bajo estudio que ponen de manifiesto características del material o de la calidad de los procesos a los que ha sido sometido. El uso de este tipo de láseres implica también la posibilidad de realizar monitorizaciones de procesos industriales en tiempo real y a distancia sin interferir con otros sensores. La segunda técnica óptica que emplearemos hace uso del estudio estadístico y matemático de las propiedades de las imágenes digitales obtenidas de la superficie de la madera a través de un sistema de scanner de alta resolución. Después de aislar los detalles mas relevantes de las imágenes, diversos algoritmos de clasificacion automatica se encargan de generar bases de datos con las diversas especies de maderas a las que pertenecían las imágenes, junto con los márgenes de error de tales clasificaciones. Una parte fundamental de las herramientas de clasificacion se basa en el estudio preciso de las bandas de color de las diversas maderas. Finalmente, numerosas técnicas acústicas, tales como el análisis de pulsos por impacto acústico, permiten complementar y afinar los resultados obtenidos con los métodos ópticos descritos, identificando estructuras superficiales y profundas en la madera así como patologías o deformaciones, aspectos de especial utilidad en usos de la madera en estructuras. La utilidad de estas técnicas esta mas que demostrada en el campo industrial aun cuando su aplicación carece de la suficiente expansión debido a sus altos costes y falta de normalización de los procesos, lo cual hace que cada análisis no sea comparable con su teórico equivalente de mercado. En la actualidad gran parte de los esfuerzos de investigación tienden a dar por supuesto que la diferenciación entre especies es un mecanismo de reconocimiento propio del ser humano y concentran las tecnologías en la definición de parámetros físicos (módulos de elasticidad, conductividad eléctrica o acústica, etc.), utilizando aparatos muy costosos y en muchos casos complejos en su aplicación de campo. Abstract The study of materials, especially the biological ones, by non-destructive techniques is becoming increasingly important in both scientific and industrial applications. The economic advantages of non-destructive methods are multiple and clear due to the related costs and resources necessaries. There are many physical processes capable of extracting detailed information on the wood surface with little or no previous treatment and minimal intrusion into the material. Among the various methods stand out acoustic and optical techniques for their great versatility, relative simplicity and low cost. This thesis aims to establish from the application of simple principles of physics, surface direct measurement and through the development of the more appropriate decision algorithms based on statistics, a simple technological solutions with the minimum cost for possible application in determining the species and the wood surface defects of each sample. Looking for a reasonable accuracy without altering their work-location or properties is the main objetive. There are three different work lines: Empirical characterization of wood surfaces by means of iterative autocorrelation of laser speckle patterns: A simple and inexpensive method for the qualitative characterization of wood surfaces is presented. it is based on the iterative autocorrelation of laser speckle patterns produced by diffuse laser illumination of the wood surfaces. The method exploits the high spatial frequency content of speckle images. A similar approach with raw conventional photographs taken with ordinary light would be very difficult. A few iterations of the algorithm are necessary, typically three or four, in order to visualize the most important periodic features of the surface. The processed patterns help in the study of surface parameters, to design new scattering models and to classify the wood species. Fractal-based image enhancement techniques inspired by differential interference contrast microscopy: Differential interference contrast microscopy is a very powerful optical technique for microscopic imaging. Inspired by the physics of this type of microscope, we have developed a series of image processing algorithms aimed at the magnification, noise reduction, contrast enhancement and tissue analysis of biological samples. These algorithms use fractal convolution schemes which provide fast and accurate results with a performance comparable to the best present image enhancement algorithms. These techniques can be used as post processing tools for advanced microscopy or as a means to improve the performance of less expensive visualization instruments. Several examples of the use of these algorithms to visualize microscopic images of raw pine wood samples with a simple desktop scanner are provided. Wood species identification using stress-wave analysis in the audible range: Stress-wave analysis is a powerful and flexible technique to study mechanical properties of many materials. We present a simple technique to obtain information about the species of wood samples using stress-wave sounds in the audible range generated by collision with a small pendulum. Stress-wave analysis has been used for flaw detection and quality control for decades, but its use for material identification and classification is less cited in the literature. Accurate wood species identification is a time consuming task for highly trained human experts. For this reason, the development of cost effective techniques for automatic wood classification is a desirable goal. Our proposed approach is fully non-invasive and non-destructive, reducing significantly the cost and complexity of the identification and classification process.
Resumo:
Corrosion of reinforcing steel in concrete due to chloride ingress is one of the main causes of the deterioration of reinforced concrete structures. Structures most affected by such a corrosion are marine zone buildings and structures exposed to de-icing salts like highways and bridges. Such process is accompanied by an increase in volume of the corrosión products on the rebarsconcrete interface. Depending on the level of oxidation, iron can expand as much as six times its original volume. This increase in volume exerts tensile stresses in the surrounding concrete which result in cracking and spalling of the concrete cover if the concrete tensile strength is exceeded. The mechanism by which steel embedded in concrete corrodes in presence of chloride is the local breakdown of the passive layer formed in the highly alkaline condition of the concrete. It is assumed that corrosion initiates when a critical chloride content reaches the rebar surface. The mathematical formulation idealized the corrosion sequence as a two-stage process: an initiation stage, during which chloride ions penetrate to the reinforcing steel surface and depassivate it, and a propagation stage, in which active corrosion takes place until cracking of the concrete cover has occurred. The aim of this research is to develop computer tools to evaluate the duration of the service life of reinforced concrete structures, considering both the initiation and propagation periods. Such tools must offer a friendly interface to facilitate its use by the researchers even though their background is not in numerical simulation. For the evaluation of the initiation period different tools have been developed: Program TavProbabilidade: provides means to carry out a probability analysis of a chloride ingress model. Such a tool is necessary due to the lack of data and general uncertainties associated with the phenomenon of the chloride diffusion. It differs from the deterministic approach because it computes not just a chloride profile at a certain age, but a range of chloride profiles for each probability or occurrence. Program TavProbabilidade_Fiabilidade: carries out reliability analyses of the initiation period. It takes into account the critical value of the chloride concentration on the steel that causes breakdown of the passive layer and the beginning of the propagation stage. It differs from the deterministic analysis in that it does not predict if the corrosion is going to begin or not, but to quantifies the probability of corrosion initiation. Program TavDif_1D: was created to do a one dimension deterministic analysis of the chloride diffusion process by the finite element method (FEM) which numerically solves Fick’second Law. Despite of the different FEM solver already developed in one dimension, the decision to create a new code (TavDif_1D) was taken because of the need to have a solver with friendly interface for pre- and post-process according to the need of IETCC. An innovative tool was also developed with a systematic method devised to compare the ability of the different 1D models to predict the actual evolution of chloride ingress based on experimental measurements, and also to quantify the degree of agreement of the models with each others. For the evaluation of the entire service life of the structure: a computer program has been developed using finite elements method to do the coupling of both service life periods: initiation and propagation. The program for 2D (TavDif_2D) allows the complementary use of two external programs in a unique friendly interface: • GMSH - an finite element mesh generator and post-processing viewer • OOFEM – a finite element solver. This program (TavDif_2D) is responsible to decide in each time step when and where to start applying the boundary conditions of fracture mechanics module in function of the amount of chloride concentration and corrosion parameters (Icorr, etc). This program is also responsible to verify the presence and the degree of fracture in each element to send the Information of diffusion coefficient variation with the crack width. • GMSH - an finite element mesh generator and post-processing viewer • OOFEM – a finite element solver. The advantages of the FEM with the interface provided by the tool are: • the flexibility to input the data such as material property and boundary conditions as time dependent function. • the flexibility to predict the chloride concentration profile for different geometries. • the possibility to couple chloride diffusion (initiation stage) with chemical and mechanical behavior (propagation stage). The OOFEM code had to be modified to accept temperature, humidity and the time dependent values for the material properties, which is necessary to adequately describe the environmental variations. A 3-D simulation has been performed to simulate the behavior of the beam on both, action of the external load and the internal load caused by the corrosion products, using elements of imbedded fracture in order to plot the curve of the deflection of the central region of the beam versus the external load to compare with the experimental data.
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Reverberation chambers are well known for providing a random-like electric field distribution. Detection of directivity or gain thereof requires an adequate procedure and smart post-processing. In this paper, a new method is proposed for estimating the directivity of radiating devices in a reverberation chamber (RC). The method is based on the Rician K-factor whose estimation in an RC benefits from recent improvements. Directivity estimation relies on the accurate determination of the K-factor with respect to a reference antenna. Good agreement is reported with measurements carried out in near-field anechoic chamber (AC) and using a near-field to far-field transformation.
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In this paper, a new method is presented to ensure automatic synchronization of intracardiac ECG data, yielding a three-stage algorithm. We first compute a robust estimate of the derivative of the data to remove low-frequency perturbations. Then we provide a grouped-sparse representation of the data, by means of the Group LASSO, to ensure that all the electrical spikes are simultaneously detected. Finally, a post-processing step, based on a variance analysis, is performed to discard false alarms. Preliminary results on real data for sinus rhythm and atrial fibrillation show the potential of this approach.
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Existen en el mercado numerosas aplicaciones para la generación de reverberación y para la medición de respuestas al impulso acústicas. Sin embargo, éstas son de precios muy elevados y/o no se permite acceder a su código y, mucho menos, distribuir de forma totalmente libre. Además, las herramientas que ofrecen para la medición de respuestas al impulso requieren de un tedioso proceso para la generación de la señal de excitación, su reproducción y grabación y, finalmente, su post-procesado. Este procedimiento puede llevar en ocasiones al usuario a cometer errores debido a la falta de conocimientos técnicos. El propósito de este proyecto es dar solución a algunos de los inconvenientes planteados. Con tal fin se llevó a cabo el desarrollo e implementación de un módulo de reverberación por convolución particionada en tiempo real, haciendo uso de software gratuito y de libre distribución. En concreto, se eligió la estación digital de trabajo (DAW. Digital Audio Worksation) REAPER de la compañía Cockos. Además de incluir las funcionalidades básicas de edición y secuenciación presentes en cualquier DAW, el programa incluye un entorno para la implementación de efectos de audio en lenguaje JS (Jesusonic), y se distribuye con licencias completamente gratuitas y sin limitaciones de uso. Complementariamente, se propone una extensión para REAPER que permite la medición de respuestas al impulso de recintos acústicos de una forma completamente automatizada y amigable para el usuario. Estas respuestas podrán ser almacenadas y posteriormente cargadas en el módulo de reverberación, permitiendo aplicar sobre nuestras pistas de audio la respuesta acústica de cualquier recinto en el que se hayan realizado medidas. La implementación del sistema de medida de respuestas se llevó a cabo empleando la herramienta ReaScript de REAPER, que permite la ejecución de pequeños scripts Python. El programa genera un Barrido Sinusoidal Logarítmico que excita el recinto acústico cuya respuesta se desea medir, grabando la misma en un archivo .wav. Este procedimiento es sencillo, intuitivo y está al alcance de cualquier usuario doméstico, ya que no requiere la utilización de sofisticado instrumental de medida. ABSTRACT. There are numerous applications in the market for the generation of reverb and measurement of acoustic impulse responses. However, they are usually very costly and closed source. In addition, the provided tools for measuring impulse responses require tedious processes for the generation and reproduction of the excitation signal, the recording of the response and its final post-processing. This procedure can sometimes drive the user to make mistakes due to the lack of technical knowledge. The purpose of this project is to solve some of the mentioned problems. To that end we developed and implemented a real-time partitioned convolution reverb module using free open source software. Specifically, the chosen software was the Cockos’ digital audio workstation (DAW) REAPER. In addition to the basic features included in any DAW, such as editing and sequencing, the program includes an environment for implementing audio effects in JS (Jesusonic) language of free distribution and features an unrestricted license. As an extension for REAPER, we propose a fully automated and user-friendly method for measuring rooms’ acoustic impulse responses. These will be stored and then loaded into the reverb module, allowing the user to apply the acoustical response of any room where measurement have been taken to any audio track. The implementation of the impulse response measurement system was done using REAPER’s ReaScript tool that allows the execution of small Python scripts. The program generates a logarithmic sine sweep that excites the room and its response is recorded in a .wav file. This procedure is simple, intuitive and it is accessible to any home user as it does not require the use of sophisticated measuring equipment.
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A grande prevalência do consumo de álcool por mulheres em idade reprodutiva aliada à gravidez não planejada expõe a gestante a um elevado risco de se alcoolizar em algum momento da gestação, principalmente no início do período gestacional em que a maioria delas ainda não tomou ciência do fato. Assim, torna-se extremamente relevante o desenvolvimento de métodos de detecção precoce de recém-nascidos em risco de desenvolvimento de problemas do espectro dos transtornos relacionados à exposição fetal ao álcool. O objetivo desse estudo foi desenvolver, validar e avaliar a eficácia de um método de quantificação de ésteres etílicos de ácidos graxos (FAEEs) no mecônio de recém-nascidos para avaliação da exposição fetal ao álcool. Os FAEEs avaliados foram: palmitato de etila, estearato de etila, oleato de etila e linoleato de etila.O método consistiu no preparo das amostras pela extração líquido-líquido utilizando água, acetona e hexano, seguida de extração em fase sólida empregando cartuchos de aminopropilsilica. A separação e quantificação dos analitos foi realizada por cromatografia em fase gasosa acoplada à espectrometria de massas. Os limites de quantificação (LQ) variaram entre 50-100ng/g. A curva de calibração foi linear de LQ até 2000ng/g para todos os analitos. A recuperação variou de 69,79% a 106,57%. Os analitos demonstraram estabilidade no ensaio de pós-processamento e em solução. O método foi aplicado em amostras de mecônio de 160 recém-nascidos recrutados em uma maternidade pública de Ribeirão Preto-SP. O consumo de álcool materno foi reportado utilizando questionários de rastreamento validados T-ACE e AUDIT e relatos retrospectivos da quantidade e frequência de álcool consumida ao longo da gestação. A eficácia do método analítico em identificar os casos positivos foi determinada pela curva Receiver Operating Characteristic (ROC). O consumo alcoólico de risco foi identificado pelo T-ACE em 31,3% das participantes e 50% reportaram o uso de álcool durante a gestação. 51,3% dos recém-nascidos apresentaram FAEEs em seu mecônio, sendo que 33,1% apresentaram altas concentrações para a somatória dos FAEEs (maior que 500ng/g), compatível com um consumo abusivo de álcool. O oleato de etila foi o biomarcador mais prevalente e o linoleato de etila foi o biomarcador que apresentou as maiores concentrações. Houve uma variabilidade no perfil de distribuição dos FAEEs entre os indivíduos, e discordâncias entre a presença de FAEEs e o consumo reportado pela mãe. A concentração total dos FAEEs nos mecônio mostrou-se como melhor indicador da exposição fetal ao álcool quando comparado com o uso de um único biomarcador. O ponto de corte para esta população foi de aproximadamente 600ng/g para uso tipo binge (três ou mais doses por ocasião) com sensibilidade de 71,43% e especificidade de 84,37%. Este estudo reforça a importância da utilização de métodos laboratoriais na identificação da exposição fetal ao álcool.