30 resultados para spectral regression

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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It is unclear whether anti-VEGF monotherapy in age-related macular degeneration (AMD) achieves morphologic CNV regression or only stops further CNV growth. In this study, spectral domain-optical coherence tomography (SD-OCT) was used to image CNV structure before and after anti-VEGF treatment.

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Soil degradation is a major problem in the agriculturally dominated country of Tajikistan, which makes it necessary to determine and monitor the state of soils. For this purpose a soil spectral library was established as it enables the determination of soil properties with relatively low costs and effort. A total of 1465 soil samples were collected from three 10x10 km test sites in western Tajikistan. The diffuse reflectance of the samples was measured with a FieldSpec PRO FR from ASD in the spectral range from 380 to 2500 nm in laboratory. 166 samples were finally selected based on their spectral information and analysed on total C and N, organic C, pH, CaCO₃, extractable P, exchangeable Ca, Mg and K, and the fractions clay, silt and sand. Multiple linear regression was used to set up the models. Two third of the chemically analysed samples were used to calibrate the models, one third was used for hold-out validation. Very good prediction accuracy was obtained for total C (R² = 0.76, RMSEP = 4.36 g kg⁻¹), total N (R² = 0.83, RMSEP = 0.30 g kg⁻¹) and organic C (R² = 0.81, RMSEP = 3.30 g kg⁻¹), good accuracy for pH (R² = 0.61, RMSEP = 0.157) and CaCO3(R² = 0.72, RMSEP = 4.63 %). No models could be developed for extractable P, exchangeable Ca, Mg and K, and the fractions clay, silt and sand. It can be concluded that the spectral library approach has a high potential to substitute standard laboratory methods where rapid and inexpensive analysis is required.

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Over the last ~20 years, soil spectral libraries storing near-infrared reflectance (NIR) spectra from diverse soil samples have been built for many places, since almost 10 years also for Tajikistan. Many calibration approaches have been reported and used for prediction from large and heterogeneous libraries, but most are hampered by the high diversity of the soils, where the mineral background is heavily influencing spectral features. In such cases, local learning strategies have the advantage of building locally adapted calibrations, which can deal better with nonlinearities. Therefore, it was our major aim to identify the most efficient approach to develop an accurate and stable locally weigthed calibration model using a spectral library compiled over the past years. Keywords: Tajikistan, Near-Infrared spectroscopy (NIRS), soil organic carbon, locally weighted regression, regional and local spectral library.

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We present an independent calibration model for the determination of biogenic silica (BSi) in sediments, developed from analysis of synthetic sediment mixtures and application of Fourier transform infrared spectroscopy (FTIRS) and partial least squares regression (PLSR) modeling. In contrast to current FTIRS applications for quantifying BSi, this new calibration is independent from conventional wet-chemical techniques and their associated measurement uncertainties. This approach also removes the need for developing internal calibrations between the two methods for individual sediments records. For the independent calibration, we produced six series of different synthetic sediment mixtures using two purified diatom extracts, with one extract mixed with quartz sand, calcite, 60/40 quartz/calcite and two different natural sediments, and a second extract mixed with one of the natural sediments. A total of 306 samples—51 samples per series—yielded BSi contents ranging from 0 to 100 %. The resulting PLSR calibration model between the FTIR spectral information and the defined BSi concentration of the synthetic sediment mixtures exhibits a strong cross-validated correlation ( R2cv = 0.97) and a low root-mean square error of cross-validation (RMSECV = 4.7 %). Application of the independent calibration to natural lacustrine and marine sediments yields robust BSi reconstructions. At present, the synthetic mixtures do not include the variation in organic matter that occurs in natural samples, which may explain the somewhat lower prediction accuracy of the calibration model for organic-rich samples.

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To observe detailed changes in neurosensory retinal structure after anti-VEGF upload in age-related macular degeneration (AMD), by using spectral domain optical coherence tomography (SD-OCT).

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The introduction of spectral-domain optical coherence tomography (SD-OCT) has improved the clinical value for assessment of the eyes with macular disease. This article reviews the advances of SD-OCT for the diagnostic of various macular diseases. These include vitreomacular traction syndrome, cystoid macular edema/diabetic macular edema, epiretinal membranes, full-thickness macular holes, lamellar holes, pseudoholes, microholes, and schisis from myopia. Besides offering new insights into the pathogenesis of macular abnormalities, SD-OCT is a valuable tool for monitoring macular disease.

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To evaluate the capability of spectral computed tomography (CT) to improve the characterization of cystic high-attenuation lesions in a renal phantom and to test the hypothesis that spectral CT will improve the differentiation of cystic renal lesions with high protein content and those that have undergone hemorrhage or malignant contrast-enhancing transformation.

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The aim of this work is to assess the repeatability of spectral-domain-OCT (SD-OCT) retinal nerve fiber layer thickness (RNFL) thickness measurements in a non-glaucoma group and patients with glaucoma and to compare these results to conventional time-domain-OCT (TD-OCT).