114 resultados para Penalized Least Squares
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GPS active networks are more and more used in geodetic surveying and scientific experiments, as water vapor monitoring in the atmosphere and lithosphere plate movement. Among the methods of GPS positioning, Precise Point Positioning (PPP) has provided very good results. A characteristic of PPP is related to the modeling and / or estimation of the errors involved in this method. The accuracy obtained for the coordinates can reach few millimeters. Seasonal effects can affect such accuracy if they are not consistent treated during the data processing. Coordinates time series analyses have been realized using Fourier or Harmonics spectral analyses, wavelets, least squares estimation among others. An approach is presented in this paper aiming to investigate the seasonal effects included in the stations coordinates time series. Experiments were carried out using data from stations Manaus (NAUS) and Fortaleza (BRFT) which belong to the Brazilian Continuous GPS Network (RBMC). The coordinates of these stations were estimated daily using PPP and were analyzed through wavelets for identification of the periods of the seasonal effects (annual and semi-annual) in each time series. These effects were removed by means of a filtering process applied in the series via the least squares adjustment (LSQ) of a periodic function. The results showed that the combination of these two mathematical tools, wavelets and LSQ, is an interesting and efficient technique for removal of seasonal effects in time series.
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Objective: This case-control study analyzed mass spectrometry fingerprinting patterns of culture media samples used for embryo culture to predict embryo implantation. Methods: The culture medium harvested after embryo transfer of 22 embryos from 13 patients was used for the experiments. After embryo transfer, the remaining culture media were collected and samples were split in positive (n=8) and negative (n=14) implantation groups according to implantation outcomes (100% or 0% of implantation). Samples were individually diluted and injected directly to the Electrospray ionization (ESI) MS coupled to a Quadrupole Time-of-flight MS (Q-ToF-MS).Ions relative intensities of each spectrum were considered. Data analysis was conducted in MatLab 7.0 version using Partial Least Squares - Discriminant Analysis toolbox. Results: There were 3027 observed ions at 100% and 0% implantation groups by ESI-Q-ToF-MS. The statistical model could categorize the samples in two clusters, based on their positive and negative implantation outcomes. Less intense ions present in the mass spectra with statistical significance have contributed to the major differences to group distinction. Conclusions: Positive and negative implantation embryos showed a specific biochemical pattern present in culture media, which could be detected as a fast, simple and non-invasive way. This biochemical profile could help the selection of the most viable embryo, improving single embryo transfer and thus eliminating the risk and undesirable outcomes of multiple pregnancies. © Todos os direitos reservados a SBRA - Sociedade Brasileira de Reprodução Assistida.
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This paper presents an approach for structural health monitoring (SHM) by using adaptive filters. The experimental signals from different structural conditions provided by piezoelectric actuators/sensors bonded in the test structure are modeled by a discrete-time recursive least square (RLS) filter. The biggest advantage to use a RLS filter is the clear possibility to perform an online SHM procedure since that the identification is also valid for non-stationary linear systems. An online damage-sensitive index feature is computed based on autoregressive (AR) portion of coefficients normalized by the square root of the sum of the square of them. The proposed method is then utilized in a laboratory test involving an aeronautical panel coupled with piezoelectric sensors/actuators (PZTs) in different positions. A hypothesis test employing the t-test is used to obtain the damage decision. The proposed algorithm was able to identify and localize the damages simulated in the structure. The results have shown the applicability and drawbacks the method and the paper concludes with suggestions to improve it. ©2010 Society for Experimental Mechanics Inc.
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When searching for prospective novel peptides, it is difficult to determine the biological activity of a peptide based only on its sequence. The trial and error approach is generally laborious, expensive and time consuming due to the large number of different experimental setups required to cover a reasonable number of biological assays. To simulate a virtual model for Hymenoptera insects, 166 peptides were selected from the venoms and hemolymphs of wasps, bees and ants and applied to a mathematical model of multivariate analysis, with nine different chemometric components: GRAVY, aliphaticity index, number of disulfide bonds, total residues, net charge, pI value, Boman index, percentage of alpha helix, and flexibility prediction. Principal component analysis (PCA) with non-linear iterative projections by alternating least-squares (NIPALS) algorithm was performed, without including any information about the biological activity of the peptides. This analysis permitted the grouping of peptides in a way that strongly correlated to the biological function of the peptides. Six different groupings were observed, which seemed to correspond to the following groups: chemotactic peptides, mastoparans, tachykinins, kinins, antibiotic peptides, and a group of long peptides with one or two disulfide bonds and with biological activities that are not yet clearly defined. The partial overlap between the mastoparans group and the chemotactic peptides, tachykinins, kinins and antibiotic peptides in the PCA score plot may be used to explain the frequent reports in the literature about the multifunctionality of some of these peptides. The mathematical model used in the present investigation can be used to predict the biological activities of novel peptides in this system, and it may also be easily applied to other biological systems. © 2011 Elsevier Inc.
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The aim of this work is to evaluate the influence of point measurements in images, with subpixel accuracy, and its contribution in the calibration of digital cameras. Also, the effect of subpixel measurements in 3D coordinates of check points in the object space will be evaluated. With this purpose, an algorithm that allows subpixel accuracy was implemented for semi-automatic determination of points of interest, based on Fõrstner operator. Experiments were accomplished with a block of images acquired with the multispectral camera DuncanTech MS3100-CIR. The influence of subpixel measurements in the adjustment by Least Square Method (LSM) was evaluated by the comparison of estimated standard deviation of parameters in both situations, with manual measurement (pixel accuracy) and with subpixel estimation. Additionally, the influence of subpixel measurements in the 3D reconstruction was also analyzed. Based on the obtained results, i.e., on the quantification of the standard deviation reduction in the Inner Orientation Parameters (IOP) and also in the relative error of the 3D reconstruction, it was shown that measurements with subpixel accuracy are relevant for some tasks in Photogrammetry, mainly for those in which the metric quality is of great relevance, as Camera Calibration.
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The objective of this paper is to show a methodology to estimate transmission line parameters. The method is applied in a single-phase transmission line using the method of least squares. In this method the longitudinal and transversal parameters of the line are obtained as a function of a set of measurements of currents and voltages (as well as their derivatives with respect to time) at the terminals of the line during the occurrence of a short-circuit phase-ground near the load. The method is based on the assumption that a transmission line can be represented by a single circuit π. The results show that the precision of the method depends on the length of the line, where it has a better performance for short lines and medium length. © 2012 IEEE.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Four experiments evaluated the effects of vaccination against bovine herpesvirus-1 (BoHV-1), bovine viral diarrhea virus (BVDV), and Leptospira spp. on reproductive performance of lactating dairy cows without (experiments 1, 2, and 3) or with previous vaccination against these diseases (experiment 4). Cows were assigned to a fixed-time AI protocol (FTAI; d -11 to 0) in all experiments, as well as AI 12. h upon estrus detection in experiment 3. Pregnancy status was determined with transrectal ultrasonography on d 30 and 71 (d 60 for experiment 3) after AI. Pregnancy loss was considered in cows pregnant on d 30 but non-pregnant on the subsequent evaluation. In experiment 1, 853 cows received (VAC) or not (CON) vaccination against BoHV-1, BVDV, and Leptospira spp. at the beginning of the FTAI (d -11) and 30. d after AI. Pregnancy loss was reduced (P=0.03) in VAC cows compared with CON. In experiment 2, 287 cows received VAC or CON 30. d prior to (d -41) and at the beginning (d -11) of the FTAI. Pregnancy rates on d 30 and 71 were greater (P≤0.03) in VAC cows compared with CON. In experiment 3, 1680 cows with more than 28. d in milk were randomly assigned to receive VAC or CON with doses administered 14. d apart, and inseminated within 15-135. d after the second dose. Pregnancy rates on d 30 and 60 were greater (P≤0.02) in VAC cows compared with CON. In experiment 4, 820 cows received (REVAC) or not (CON) revaccination against BoHV-1, BVDV, and Leptospira spp. at the beginning of the FTAI protocol (d -11). Pregnancy rates and loss were similar (P≥0.54) between treatments. Hence, vaccinating naïve cows against BoHV-1, BVDV, and Leptospira spp. improved reproductive efficiency in dairy production systems, particularly when both doses were administered prior to AI. © 2013 Elsevier B.V.
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In this paper is reported the use of the chromatographic profiles of volatiles to determine disease markers in plants - in this case, leaves of Eucalyptus globulus contaminated by the necrotroph fungus Teratosphaeria nubilosa. The volatile fraction was isolated by headspace solid phase microextraction (HS-SPME) and analyzed by comprehensive two-dimensional gas chromatography-fast quadrupole mass spectrometry (GC. ×. GC-qMS). For the correlation between the metabolic profile described by the chromatograms and the presence of the infection, unfolded-partial least squares discriminant analysis (U-PLS-DA) with orthogonal signal correction (OSC) were employed. The proposed method was checked to be independent of factors such as the age of the harvested plants. The manipulation of the mathematical model obtained also resulted in graphic representations similar to real chromatograms, which allowed the tentative identification of more than 40 compounds potentially useful as disease biomarkers for this plant/pathogen pair. The proposed methodology can be considered as highly reliable, since the diagnosis is based on the whole chromatographic profile rather than in the detection of a single analyte. © 2013 Elsevier B.V..
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Fifty-nine Nellore bulls from low and high residual feed intake (RFI) levels were studied with the objective of evaluating meat quality traits. Animals were slaughtered when ultrasound-measured backfat thickness reached 4. mm, and samples of Longissimus were collected. A mixed model including RFI as fixed effect and herd and diet as random effects was used, and least square means were compared by t-test. More efficient animals consumed 0.730. kg dry matter/day less than less efficient animals, with similar performance. No significant differences in carcass weight, prime meat cuts proportion, chemical composition, pH, sarcomere length, or color were observed between RFI groups. Shear force, myofibrillar fragmentation index and soluble collagen content were influenced by RFI, with a higher shear force and soluble collagen content and a lower fragmentation index in low RFI animals. Feedlot-finished low RFI young Nellore bulls more efficiently convert feed into meat, presenting carcasses within quality standards. © 2012 Elsevier Ltd.
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Lubricating oils are crucial in the operation of automotive engines because they both reduce friction between moving parts and protect against corrosion. However, the performance of lubricant oil may be affected by contaminants, such as gasoline, diesel, ethanol, water and ethylene glycol. Although there are many standard methods and studies related to the quantification of contaminants in lubricant oil, such as gasoline and diesel oil, to the best of our knowledge, no methods have been reported for the quantification of ethanol in used Otto cycle engine lubrication oils. Therefore, this work aimed at the development and validation of a routine method based on partial least-squares multivariate analysis combined with attenuated total reflectance in the mid-infrared region to quantify ethanol content in used lubrication oil. The method was validated based on its figures of merit (using the net analyte signal) as follows: limit of detection (0.049%), limit of quantification (0.16%), accuracy (root mean square error of prediction=0.089% w/w), repeatability (0.05% w/w), fit (R 2 =0.9997), mean selectivity (0.047), sensitivity (0.011), inverse analytical sensitivity (0.016% w/w-1) and signal-to-noise ratio (max: 812.4 and min: 200.9). The results show that the proposed method can be routinely implemented for the quality control of lubricant oils. © 2013 Elsevier B.V. All rights reserved.
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Introduction Jatropha gossypifolia has been used quite extensively by traditional medicine for the treatment of several diseases in South America and Africa. This medicinal plant has therapeutic potential as a phytomedicine and therefore the establishment of innovative analytical methods to characterise their active components is crucial to the future development of a quality product. Objective To enhance the chromatographic resolution of HPLC-UV-diode-array detector (DAD) experiments applying chemometric tools. Methods Crude leave extracts from J. gossypifolia were analysed by HPLC-DAD. A chromatographic band deconvolution method was designed and applied using interval multivariate curve resolution by alternating least squares (MCR-ALS). Results The MCR-ALS method allowed the deconvolution from up to 117% more bands, compared with the original HPLC-DAD experiments, even in regions where the UV spectra showed high similarity. The method assisted in the dereplication of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. Conclusion The MCR-ALS method is shown to be a powerful tool to solve problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd. Extracts from J. gossypifolia were analyzed by HPLC-DAD and, dereplicated applying MCR-ALS. The method assisted in the detection of three C-glycosylflavones isomers: vitexin/isovitexin, orientin/homorientin and schaftoside/isoschaftoside. The application of MCR-ALS allowed solving problems of chromatographic band overlapping from complex mixtures such as natural crude samples. Copyright © 2013 John Wiley & Sons, Ltd.
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Pós-graduação em Ciências Cartográficas - FCT
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Pós-graduação em Engenharia Elétrica - FEIS
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)