996 resultados para Infrared data


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Context. The ESO public survey VISTA variables in the Via Lactea (VVV) started in 2010. VVV targets 562 sq. deg in the Galactic bulge and an adjacent plane region and is expected to run for about five years. Aims. We describe the progress of the survey observations in the first observing season, the observing strategy, and quality of the data obtained. Methods. The observations are carried out on the 4-m VISTA telescope in the ZYJHK(s) filters. In addition to the multi-band imaging the variability monitoring campaign in the K-s filter has started. Data reduction is carried out using the pipeline at the Cambridge Astronomical Survey Unit. The photometric and astrometric calibration is performed via the numerous 2MASS sources observed in each pointing. Results. The first data release contains the aperture photometry and astrometric catalogues for 348 individual pointings in the ZYJHK(s) filters taken in the 2010 observing season. The typical image quality is similar to 0 ''.9-1 ''.0. The stringent photometric and image quality requirements of the survey are satisfied in 100% of the JHK(s) images in the disk area and 90% of the JHK(s) images in the bulge area. The completeness in the Z and Y images is 84% in the disk, and 40% in the bulge. The first season catalogues contain 1.28 x 10(8) stellar sources in the bulge and 1.68 x 10(8) in the disk area detected in at least one of the photometric bands. The combined, multi-band catalogues contain more than 1.63 x 10(8) stellar sources. About 10% of these are double detections because of overlapping adjacent pointings. These overlapping multiple detections are used to characterise the quality of the data. The images in the JHK(s) bands extend typically similar to 4 mag deeper than 2MASS. The magnitude limit and photometric quality depend strongly on crowding in the inner Galactic regions. The astrometry for K-s = 15-18 mag has rms similar to 35-175 mas. Conclusions. The VVV Survey data products offer a unique dataset to map the stellar populations in the Galactic bulge and the adjacent plane and provide an exciting new tool for the study of the structure, content, and star-formation history of our Galaxy, as well as for investigations of the newly discovered star clusters, star-forming regions in the disk, high proper motion stars, asteroids, planetary nebulae, and other interesting objects.

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Time-averaged discharge rates (TADR) were calculated for five lava flows at Pacaya Volcano (Guatemala), using an adapted version of a previously developed satellite-based model. Imagery acquired during periods of effusive activity between the years 2000 and 2010 were obtained from two sensors of differing temporal and spatial resolutions; the Moderate Resolution Imaging Spectroradiometer (MODIS), and the Geostationary Operational Environmental Satellites (GOES) Imager. A total of 2873 MODIS and 2642 GOES images were searched manually for volcanic “hot spots”. It was found that MODIS imagery, with superior spatial resolution, produced better results than GOES imagery, so only MODIS data were used for quantitative analyses. Spectral radiances were transformed into TADR via two methods; first, by best-fitting some of the parameters (i.e. density, vesicularity, crystal content, temperature change) of the TADR estimation model to match flow volumes previously estimated from ground surveys and aerial photographs, and second by measuring those parameters from lava samples to make independent estimates. A relatively stable relationship was defined using the second method, which suggests the possibility of estimating lava discharge rates in near-real-time during future volcanic crises at Pacaya.

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Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

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The main objective of this work was to develop a novel dimensionality reduction technique as a part of an integrated pattern recognition solution capable of identifying adulterants such as hazelnut oil in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. A novel Continuous Locality Preserving Projections (CLPP) technique is proposed which allows the modelling of the continuous nature of the produced in-house admixtures as data series instead of discrete points. The maintenance of the continuous structure of the data manifold enables the better visualisation of this examined classification problem and facilitates the more accurate utilisation of the manifold for detecting the adulterants. The performance of the proposed technique is validated with two different spectroscopic techniques (Raman and Fourier transform infrared, FT-IR). In all cases studied, CLPP accompanied by k-Nearest Neighbors (kNN) algorithm was found to outperform any other state-of-the-art pattern recognition techniques.

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Au cours des dernières décennies, l’effort sur les applications de capteurs infrarouges a largement progressé dans le monde. Mais, une certaine difficulté demeure, en ce qui concerne le fait que les objets ne sont pas assez clairs ou ne peuvent pas toujours être distingués facilement dans l’image obtenue pour la scène observée. L’amélioration de l’image infrarouge a joué un rôle important dans le développement de technologies de la vision infrarouge de l’ordinateur, le traitement de l’image et les essais non destructifs, etc. Cette thèse traite de la question des techniques d’amélioration de l’image infrarouge en deux aspects, y compris le traitement d’une seule image infrarouge dans le domaine hybride espacefréquence, et la fusion d’images infrarouges et visibles employant la technique du nonsubsampled Contourlet transformer (NSCT). La fusion d’images peut être considérée comme étant la poursuite de l’exploration du modèle d’amélioration de l’image unique infrarouge, alors qu’il combine les images infrarouges et visibles en une seule image pour représenter et améliorer toutes les informations utiles et les caractéristiques des images sources, car une seule image ne pouvait contenir tous les renseignements pertinents ou disponibles en raison de restrictions découlant de tout capteur unique de l’imagerie. Nous examinons et faisons une enquête concernant le développement de techniques d’amélioration d’images infrarouges, et ensuite nous nous consacrons à l’amélioration de l’image unique infrarouge, et nous proposons un schéma d’amélioration de domaine hybride avec une méthode d’évaluation floue de seuil amélioré, qui permet d’obtenir une qualité d’image supérieure et améliore la perception visuelle humaine. Les techniques de fusion d’images infrarouges et visibles sont établies à l’aide de la mise en oeuvre d’une mise en registre précise des images sources acquises par différents capteurs. L’algorithme SURF-RANSAC est appliqué pour la mise en registre tout au long des travaux de recherche, ce qui conduit à des images mises en registre de façon très précise et des bénéfices accrus pour le traitement de fusion. Pour les questions de fusion d’images infrarouges et visibles, une série d’approches avancées et efficaces sont proposés. Une méthode standard de fusion à base de NSCT multi-canal est présente comme référence pour les approches de fusion proposées suivantes. Une approche conjointe de fusion, impliquant l’Adaptive-Gaussian NSCT et la transformée en ondelettes (Wavelet Transform, WT) est propose, ce qui conduit à des résultats de fusion qui sont meilleurs que ceux obtenus avec les méthodes non-adaptatives générales. Une approche de fusion basée sur le NSCT employant la détection comprime (CS, compressed sensing) et de la variation totale (TV) à des coefficients d’échantillons clairsemés et effectuant la reconstruction de coefficients fusionnés de façon précise est proposée, qui obtient de bien meilleurs résultats de fusion par le biais d’une pré-amélioration de l’image infrarouge et en diminuant les informations redondantes des coefficients de fusion. Une procédure de fusion basée sur le NSCT utilisant une technique de détection rapide de rétrécissement itératif comprimé (fast iterative-shrinking compressed sensing, FISCS) est proposée pour compresser les coefficients décomposés et reconstruire les coefficients fusionnés dans le processus de fusion, qui conduit à de meilleurs résultats plus rapidement et d’une manière efficace.

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A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

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A method using the ring-oven technique for pre-concentration in filter paper discs and near infrared hyperspectral imaging is proposed to identify four detergent and dispersant additives, and to determine their concentration in gasoline. Different approaches were used to select the best image data processing in order to gather the relevant spectral information. This was attained by selecting the pixels of the region of interest (ROI), using a pre-calculated threshold value of the PCA scores arranged as histograms, to select the spectra set; summing up the selected spectra to achieve representativeness; and compensating for the superimposed filter paper spectral information, also supported by scores histograms for each individual sample. The best classification model was achieved using linear discriminant analysis and genetic algorithm (LDA/GA), whose correct classification rate in the external validation set was 92%. Previous classification of the type of additive present in the gasoline is necessary to define the PLS model required for its quantitative determination. Considering that two of the additives studied present high spectral similarity, a PLS regression model was constructed to predict their content in gasoline, while two additional models were used for the remaining additives. The results for the external validation of these regression models showed a mean percentage error of prediction varying from 5 to 15%.

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Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

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Objective: This study investigated and correlated the kinetic expression of vascular endothelial growth factor (VEGF)-A(165) messenger ribonucleic acid (mRNA) with the associated use or not of an infrared laser and a visible red laser during the wound healing in rats. Background Data: There is a lack of scientific evidence demonstrating the influence of low-level laser therapy (LLLT) on the expression of VEGF mRNA in vivo. Materials and Methods: Forty-five Wistar rats were randomly allocated to one of three groups: I (n = 5, nonoperated animals), II (n = 25, operated animals), and III (n = 25, animals operated and subjected to laser irradiation). A surgical wound was performed using a scalpel in the right side of the tongue of operated animals. In group III, two sessions of laser irradiation were performed, one right after the surgical procedure (infrared laser, 780 nm, 70mW, 35 J/cm(2)) and the other 48 h later (visible red laser, 660 nm, 40mW, 5J/cm(2)). Five animals each were sacrificed 1, 3, 5, and 7 days postoperatively in groups II and III, and samples of tongue tissue were obtained. The animals of group I were sacrificed on day 7. Total RNA was extracted using guanidine-isothiocyanate-phenol-chloroform method. The results of horizontal electrophoresis after reverse transcription polymerase chain reaction permitted the ratio of VEGF-A(165) mRNA and glyceraldehyde 3-phosphate dehydrogenase mRNA expression for groups I, II, and III to be assessed (two-way analysis of variance and Tukey test, p<0.05). Results: The expression of VEGF-A(165) mRNA in group II (0.770 +/- 0.098) was statistically greater than that observed in groups I (0.523 +/- 0.164) and III (0.504 +/- 0.069) in the first day after surgery (p<0.05). Significant differences between the groups were not observed in other time periods. Conclusion: LLLT influenced the expression of VEGF-A(165) mRNA during wound healing after a surgical procedure on the tongue of Wistar rats.

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Context. The analysis and interpretation of the H(2) line emission from planetary nebulae have been done in the literature by assuming that the molecule survives only in regions where the hydrogen is neutral, as in photodissociation, neutral clumps, or shocked regions. However, there is strong observational and theoretical evidence that at least part of the H(2) emission is produced inside the ionized region of these objects. Aims. The aim of the present work is to calculate and analyze the infrared line emission of H(2) produced inside the ionized region of planetary nebulae using a one-dimensional photoionization code. Methods. The photoionization code Aangaba was improved in order to calculate the statistical population of the H(2) energy levels, as well as the intensity of the H(2) infrared emission lines in the physical conditions typical of planetary nebulae. A grid of models was obtained and the results then analyzed and compared with the observational data. Results. We show that the contribution of the ionized region to the H(2) line emission can be important, particularly in the case of nebulae with high-temperature central stars. This result explains why H(2) emission is more frequently observed in bipolar planetary nebulae (Gatley's rule), since this kind of object typically has hotter stars. Collisional excitation plays an important role in populating the rovibrational levels of the electronic ground state of H(2) molecules. Radiative mechanisms are also important, particularly for the upper vibrational levels. Formation pumping can have minor effects on the line intensities produced by de-excitation from very high rotational levels, especially in dense and dusty environments. We included the effect of the H(2) molecule on the thermal equilibrium of the gas, concluding that, in the ionized region, H(2) only contributes to the thermal equilibrium in the case of a very high temperature of the central star or a high dust-to-gas ratio, mainly through collisional de-excitation.

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The A1763 superstructure at z = 0.23 contains the first galaxy filament to be directly detected using mid-infrared observations. Our previous work has shown that the frequency of starbursting galaxies, as characterized by 24 mu m emission is much higher within the filament than at either the center of the rich galaxy cluster, or the field surrounding the system. New Very Large Array and XMM-Newton data are presented here. We use the radio and X-ray data to examine the fraction and location of active galaxies, both active galactic nuclei (AGNs) and starbursts (SBs). The radio far-infrared correlation, X-ray point source location, IRAC colors, and quasar positions are all used to gain an understanding of the presence of dominant AGNs. We find very few MIPS-selected galaxies that are clearly dominated by AGN activity. Most radio-selected members within the filament are SBs. Within the supercluster, three of eight spectroscopic members detected both in the radio and in the mid-infrared are radio-bright AGNs. They are found at or near the core of A1763. The five SBs are located further along the filament. We calculate the physical properties of the known wide angle tail (WAT) source which is the brightest cluster galaxy of A1763. A second double lobe source is found along the filament well outside of the virial radius of either cluster. The velocity offset of the WAT from the X-ray centroid and the bend of the WAT in the intracluster medium are both consistent with ram pressure stripping, indicative of streaming motions along the direction of the filament. We consider this as further evidence of the cluster-feeding nature of the galaxy filament.

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Background data: Technology and physical exercise can enhance physical performance during aging. Objective: The purpose of this study was to investigate the effects of infrared-light-emitting diode (LED) illumination (850 nm) applied during treadmill training. Materials and methods: Twenty postmenopausal women participated in this study. They were randomly divided into two groups. The LED group performed treadmill training associated with infrared-LED illumination (n = 10) and the control group performed only treadmill training (n = 10). The training was performed during 3 months, twice a week during 30 min at intensities between 85 and 90% of maximal heart rate. The irradiation parameters were 31 mW/cm(2), treatment time 30 min, 14,400 J of total energy and 55.8 J/cm(2) of fluence. Physiological, biomechanical, and body composition parameters were measured at the baseline and after 3 months. Results: Both groups improved the time of tolerance limit (Tlim) (p < 0.05) during submaximal constant-speed testing. The peak torque did not differ between groups. However, the results showed significantly higher values of power [from 56 +/- 10 to 73 +/- 8W (p = 0.002)] and total work [from 1,537 +/- 295 to 1,760 +/- 262 J (p = 0.006)] for the LED group when compared to the control group [power: from 58 +/- 14 to 60 +/- 15W (p >= 0.05) and total work: from 1,504 +/- 404 to 1,622 +/- 418 J (p >= 0.05)]. The fatigue significantly increased for the control group [from 51 +/- 6 to 58 +/- 5 % (p = 0.04)], but not for the LED group [from 60 +/- 10 to 60 +/- 4 % (p >= 0.05)]. No significant differences in body composition were observed for either group. Conclusions: Infrared-LED illumination associated with treadmill training can improve muscle power and delay leg fatigue in postmenopausal women.

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We present rigorous upper and lower bounds for the momentum-space ghost propagator G(p) of Yang-Mills theories in terms of the smallest nonzero eigenvalue (and of the corresponding eigenvector) of the Faddeev-Popov matrix. We apply our analysis to data from simulations of SU(2) lattice gauge theory in Landau gauge, using the largest lattice sizes to date. Our results suggest that, in three and in four space-time dimensions, the Landau gauge ghost propagator is not enhanced as compared to its tree-level behavior. This is also seen in plots and fits of the ghost dressing function. In the two-dimensional case, on the other hand, we find that G(p) diverges as p(-2-2 kappa) with kappa approximate to 0.15, in agreement with A. Maas, Phys. Rev. D 75, 116004 (2007). We note that our discussion is general, although we make an application only to pure gauge theory in Landau gauge. Our simulations have been performed on the IBM supercomputer at the University of Sao Paulo.

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We present rigorous upper and lower bounds for the zero-momentum gluon propagator D(0) of Yang-Mills theories in terms of the average value of the gluon field. This allows us to perform a controlled extrapolation of lattice data to infinite volume, showing that the infrared limit of the Landau-gauge gluon propagator in SU(2) gauge theory is finite and nonzero in three and in four space-time dimensions. In the two-dimensional case, we find D(0)=0, in agreement with Maas. We suggest an explanation for these results. We note that our discussion is general, although we apply our analysis only to pure gauge theory in the Landau gauge. Simulations have been performed on the IBM supercomputer at the University of Sao Paulo.