974 resultados para spatial resolution
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Reasons for performing study: Obtaining magnetic resonance images of the inner hoof wall tissue at the microscopic level would enable early accurate diagnosis of laminitis and therefore more effective therapy. Objectives: To optimise magnetic resonance imaging (MRI) parameters in order to obtain the highest possible resolution of the structures beneath the equine hoof wall. Methods: Magnetic resonance microscopy (MRM) was performed in front feet from 6 cadaver horses using T-2-weighted fast spin echo (FSE-T-2), and T-1-weighted gradient echo (GRE-T-1) sequences. Results: In T-2 weighted FSE images most of the stratum medium showed no signal, however the coronary, terminal and sole papillae were visible. The stratum lamellatum was clearly visible and primary epidermal lamellae could be differentiated from dermal lamellae. Conclusion: Most structures beneath the hoof wall were differentiated. Conventional scanners for diagnostic MRI in horses are low or high field. However this study used ultra-high field scanners currently not available for clinical use. Signal-to-noise ratio (SIN) increases as a function of field strength. An increase of spatial resolution of the image results in a decreased SIN. SIN can also be improved with better coils and the resolution of high field MRI scanners will increase as technology develops and surface array coils become more readily available. Potential relevance: Although MR images with microscopic resolution were obtained ex vivo, this study demonstrates the potential for detection of lamellar pathology as it occurs. Early recognition of the development of laminitis to instigate effective therapy at an earlier stage and may improve the outcome for laminitic horses. Clinical MR is now readily available at 3 T, while 4 T, 7 T and 9 T systems are being used for human whole body applications.
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The identification of disease clusters in space or space-time is of vital importance for public health policy and action. In the case of methicillin-resistant Staphylococcus aureus (MRSA), it is particularly important to distinguish between community and health care-associated infections, and to identify reservoirs of infection. 832 cases of MRSA in the West Midlands (UK) were tested for clustering and evidence of community transmission, after being geo-located to the centroids of UK unit postcodes (postal areas roughly equivalent to Zip+4 zip code areas). An age-stratified analysis was also carried out at the coarser spatial resolution of UK Census Output Areas. Stochastic simulation and kernel density estimation were combined to identify significant local clusters of MRSA (p<0.025), which were supported by SaTScan spatial and spatio-temporal scan. In order to investigate local sampling effort, a spatial 'random labelling' approach was used, with MRSA as cases and MSSA (methicillin-sensitive S. aureus) as controls. Heavy sampling in general was a response to MRSA outbreaks, which in turn appeared to be associated with medical care environments. The significance of clusters identified by kernel estimation was independently supported by information on the locations and client groups of nursing homes, and by preliminary molecular typing of isolates. In the absence of occupational/ lifestyle data on patients, the assumption was made that an individual's location and consequent risk is adequately represented by their residential postcode. The problems of this assumption are discussed, with recommendations for future data collection.
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A high resolution optical time domain reflectometry (OTDR) based on an all-fiber chaotic source is demonstrated. We analyze the key factors limiting the operational range of such an OTDR, e.g., integral Rayleigh backscattering and the fiber loss, which degrade the optical signal to noise ratio at the receiver side, and then the guideline for counter-act such signal fading is discussed. The experimentally demonstrated correlation OTDR presents ability of 100km sensing range and 8.2cm spatial resolution (1.2 million resolved points), as a verification of the theoretical analysis. To the best of our knowledge, this is the first time that correlation OTDR measurement is performed over such a long distance with such high precision.
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We propose a high-resolution optical time domain reflectometry (OTDR) based on an all-fiber supercontinuum source. The source simply consists of a laser with moderate power and a section of fiber which has a zero dispersion wavelength near the laser's central wavelength. Spectrum and time domain properties of the source are investigated, showing that the source has great capability in nonlinear optics, such as correlation OTDR. We analyze one of the key factors limiting the operational range of such an OTDR, i.e., sampling time. Finally, we experimentally demonstrate a correlation OTDR with 25km sensing range and 5.3cm spatial resolution, as a verification of theoretical analysis.
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With the aim of analyzing the complex physical and biogeochemical interactions at high temporal and spatial resolution in the complex estuarine waters of Alfacs Bay, a beam attenuation-based approach was used as optical proxy of different biogeochemical variables. Thus, the dataset contains the attenuation proxies as well as laboratory results from the analysis of water samples, which were used to validate our approach. In addition, the major physical forcing in the Bay was also measured.
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lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.
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In this paper, we demonstrate a digital signal processing (DSP) algorithm for improving spatial resolution of images captured by CMOS cameras. The basic approach is to reconstruct a high resolution (HR) image from a shift-related low resolution (LR) image sequence. The aliasing relationship of Fourier transforms between discrete and continuous images in the frequency domain is used for mapping LR images to a HR image. The method of projection onto convex sets (POCS) is applied to trace the best estimate of pixel matching from the LR images to the reconstructed HR image. Computer simulations and preliminary experimental results have shown that the algorithm works effectively on the application of post-image-captured processing for CMOS cameras. It can also be applied to HR digital image reconstruction, where shift information of the LR image sequence is known.
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Travel demand models are important tools used in the analysis of transportation plans, projects, and policies. The modeling results are useful for transportation planners making transportation decisions and for policy makers developing transportation policies. Defining the level of detail (i.e., the number of roads) of the transport network in consistency with the travel demand model’s zone system is crucial to the accuracy of modeling results. However, travel demand modelers have not had tools to determine how much detail is needed in a transport network for a travel demand model. This dissertation seeks to fill this knowledge gap by (1) providing methodology to define an appropriate level of detail for a transport network in a given travel demand model; (2) implementing this methodology in a travel demand model in the Baltimore area; and (3) identifying how this methodology improves the modeling accuracy. All analyses identify the spatial resolution of the transport network has great impacts on the modeling results. For example, when compared to the observed traffic data, a very detailed network underestimates traffic congestion in the Baltimore area, while a network developed by this dissertation provides a more accurate modeling result of the traffic conditions. Through the evaluation of the impacts a new transportation project has on both networks, the differences in their analysis results point out the importance of having an appropriate level of network detail for making improved planning decisions. The results corroborate a suggested guideline concerning the development of a transport network in consistency with the travel demand model’s zone system. To conclude this dissertation, limitations are identified in data sources and methodology, based on which a plan of future studies is laid out.
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The ability to grow ultrathin films layer-by-layer with well-defined epitaxial relationships has allowed research groups worldwide to grow a range of artificial films and superlattices, first for semiconductors, and now with oxides. In the oxides thin film research community, there have been concerted efforts recently to develop a number of epitaxial oxide systems grown on single crystal oxide substrates that display a wide variety of novel interfacial functionality, such as enhanced ferromagnetic ordering, increased charge carrier density, increased optical absorption, etc, at interfaces. The magnitude of these novel properties is dependent upon the structure of thin films, especially interface sharpness, intermixing, defects, and strain, layering sequence in the case of superlattices and the density of interfaces relative to the film thicknesses. To understand the relationship between the interfacial thin film oxide atomic structure and its properties, atomic scale characterization is required. Transmission electron microscopy (TEM) offers the ability to study interfaces of films at high resolution. Scanning transmission electron microscopy (STEM) allows for real space imaging of materials with directly interpretable atomic number contrast. Electron energy loss spectroscopy (EELS), together with STEM, can probe the local chemical composition as well as local electronic states of transition metals and oxygen. Both techniques have been significantly improved by aberration correctors, which reduce the probe size to 1 Å, or less. Aberration correctors have thus made it possible to resolve individual atomic columns, and possibly probe the electronic structure at atomic scales. Separately, using electron probe forming lenses, structural information such as the crystal structure, strain, lattice mismatches, and superlattice ordering can be measured by nanoarea electron diffraction (NED). The combination of STEM, EELS, and NED techniques allows us to gain a fundamental understanding of the properties of oxide superlattices and ultrathin films and their relationship with the corresponding atomic and electronic structure. In this dissertation, I use the aforementioned electron microscopy techniques to investigate several oxide superlattice and ultrathin film systems. The major findings are summarized below. These results were obtained with stringent specimen preparation methods that I developed for high resolution studies, which are described in Chapter 2. The essential materials background and description of electron microscopy techniques are given in Chapter 1 and 2. In a LaMnO3-SrMnO3 superlattice, we demonstrate the interface of LaMnO3-SrMnO3 is sharper than the SrMnO3-LaMnO3 interface. Extra spectral weights in EELS are confined to the sharp interface, whereas at the rougher interface, the extra states are either not present or are not confined to the interface. Both the structural and electronic asymmetries correspond to asymmetric magnetic ordering at low temperature. In a short period LaMnO3-SrTiO3 superlattice for optical applications, we discovered a modified band structure in SrTiO3 ultrathin films relative to thick films and a SrTiO3 substrate, due to charge leakage from LaMnO3 in SrTiO3. This was measured by chemical shifts of the Ti L and O K edges using atomic scale EELS. The interfacial sharpness of LaAlO3 films grown on SrTiO3 was investigated by the STEM/EELS technique together with electron diffraction. This interface, when prepared under specific conditions, is conductive with high carrier mobility. Several suggestions for the conductive interface have been proposed, including a polar catastrophe model, where a large built-in electric field in LaAlO3 films results in electron charge transfer into the SrTiO3 substrate. Other suggested possibilities include oxygen vacancies at the interface and/or oxygen vacancies in the substrate. The abruptness of the interface as well as extent of intermixing has not been thoroughly investigated at high resolution, even though this can strongly influence the electrical transport properties. We found clear evidence for cation intermixing through the LaAlO3-SrTiO3 interface with high spatial resolution EELS and STEM, which contributes to the conduction at the interface. We also found structural defects, such as misfit dislocations, which leads to increased intermixing over coherent interfaces.
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Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures
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We used the results of the Spanish Otter Survey of 1994–1996, a Geographic Information System and stepwise multiple logistic regression to model otter presence/absence data in the continental Spanish UTM 10 10-km squares. Geographic situation, indicators of human activity such as highways and major urban centers, and environmental variables related with productivity, water availability, altitude, and environmental energy were included in a logistic model that correctly classified about 73% of otter presences and absences. We extrapolated the model to the adjacent territory of Portugal, and increased the model’s spatial resolution by extrapolating it to 1 1-km squares in the whole Iberian Peninsula. The model turned out to be rather flexible, predicting, for instance, the species to be very restricted to the courses of rivers in some areas, and more widespread in others. This allowed us to determine areas where otter populations may be more vulnerable to habitat changes or harmful human interventions. # 2003 Elsevier Ltd. All rights reserved.
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Diagnostic imaging techniques play an important role in assessing the exact location, cause, and extent of a nerve lesion, thus allowing clinicians to diagnose and manage more effectively a variety of pathological conditions, such as entrapment syndromes, traumatic injuries, and space-occupying lesions. Ultrasound and nuclear magnetic resonance imaging are becoming useful methods for this purpose, but they still lack spatial resolution. In this regard, recent phase contrast x-ray imaging experiments of peripheral nerve allowed the visualization of each nerve fiber surrounded by its myelin sheath as clearly as optical microscopy. In the present study, we attempted to produce high-resolution x-ray phase contrast images of a human sciatic nerve by using synchrotron radiation propagation-based imaging. The images showed high contrast and high spatial resolution, allowing clear identification of each fascicle structure and surrounding connective tissue. The outstanding result is the detection of such structures by phase contrast x-ray tomography of a thick human sciatic nerve section. This may further enable the identification of diverse pathological patterns, such as Wallerian degeneration, hypertrophic neuropathy, inflammatory infiltration, leprosy neuropathy and amyloid deposits. To the best of our knowledge, this is the first successful phase contrast x-ray imaging experiment of a human peripheral nerve sample. Our long-term goal is to develop peripheral nerve imaging methods that could supersede biopsy procedures.
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Glass-ceramics are prepared by controlled separation of crystal phases in glasses, leading to uniform and dense grain structures. On the other hand, chemical leaching of soluble crystal phases yields porous glass-ceramics with important applications. Here, glass/ceramic interfaces of niobo-, vanado- and titano-phosphate glasses were studied by micro-Raman spectroscopy, whose spatial resolution revealed the multiphase structures. Phase-separation mechanisms were also determined by this technique, revealing that interface composition remained unchanged as the crystallization front advanced for niobo- and vanadophosphate glasses (interface-controlled crystallization). For titanophosphate glasses, phase composition changed continuously with time up to the equilibrium composition, indicating a spinodal-type phase separation.
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Context. The star HD 87643, exhibiting the ""B[e] phenomenon"", has one of the most extreme infrared excesses for this object class. It harbours a large amount of both hot and cold dust, and is surrounded by an extended reflection nebula. Aims. One of our major goals was to investigate the presence of a companion in HD87643. In addition, the presence of close dusty material was tested through a combination of multi-wavelength high spatial resolution observations. Methods. We observed HD 87643 with high spatial resolution techniques, using the near-IR AMBER/VLTI interferometer with baselines ranging from 60 m to 130 m and the mid-IR MIDI/VLTI interferometer with baselines ranging from 25 m to 65 m. These observations are complemented by NACO/VLT adaptive-optics-corrected images in the K and L-bands, and ESO-2.2m optical Wide-Field Imager large-scale images in the B, V and R-bands. Results. We report the direct detection of a companion to HD 87643 by means of image synthesis using the AMBER/VLTI instrument. The presence of the companion is confirmed by the MIDI and NACO data, although with a lower confidence. The companion is separated by similar to 34 mas with a roughly north-south orientation. The period must be large (several tens of years) and hence the orbital parameters are not determined yet. Binarity with high eccentricity might be the key to interpreting the extreme characteristics of this system, namely a dusty circumstellar envelope around the primary, a compact dust nebulosity around the binary system and a complex extended nebula suggesting past violent ejections.
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The VISTA near infrared survey of the Magellanic System (VMC) will provide deep YJK(s) photometry reaching stars in the oldest turn-off point throughout the Magellanic Clouds (MCs). As part of the preparation for the survey, we aim to access the accuracy in the star formation history (SFH) that can be expected from VMC data, in particular for the Large Magellanic Cloud (LMC). To this aim, we first simulate VMC images containing not only the LMC stellar populations but also the foreground Milky Way (MW) stars and background galaxies. The simulations cover the whole range of density of LMC field stars. We then perform aperture photometry over these simulated images, access the expected levels of photometric errors and incompleteness, and apply the classical technique of SFH-recovery based on the reconstruction of colour-magnitude diagrams (CMD) via the minimisation of a chi-squared-like statistics. We verify that the foreground MW stars are accurately recovered by the minimisation algorithms, whereas the background galaxies can be largely eliminated from the CMD analysis due to their particular colours and morphologies. We then evaluate the expected errors in the recovered star formation rate as a function of stellar age, SFR(t), starting from models with a known age-metallicity relation (AMR). It turns out that, for a given sky area, the random errors for ages older than similar to 0.4 Gyr seem to be independent of the crowding. This can be explained by a counterbalancing effect between the loss of stars from a decrease in the completeness and the gain of stars from an increase in the stellar density. For a spatial resolution of similar to 0.1 deg(2), the random errors in SFR(t) will be below 20% for this wide range of ages. On the other hand, due to the lower stellar statistics for stars younger than similar to 0.4 Gyr, the outer LMC regions will require larger areas to achieve the same level of accuracy in the SFR( t). If we consider the AMR as unknown, the SFH-recovery algorithm is able to accurately recover the input AMR, at the price of an increase of random errors in the SFR(t) by a factor of about 2.5. Experiments of SFH-recovery performed for varying distance modulus and reddening indicate that these parameters can be determined with (relative) accuracies of Delta(m-M)(0) similar to 0.02 mag and Delta E(B-V) similar to 0.01 mag, for each individual field over the LMC. The propagation of these errors in the SFR(t) implies systematic errors below 30%. This level of accuracy in the SFR(t) can reveal significant imprints in the dynamical evolution of this unique and nearby stellar system, as well as possible signatures of the past interaction between the MCs and the MW.