Matching Pursuit for Denoising Raman Spectra, Based on Genetic Algorithm and Hermite Atoms.

Due to its various advantages, Raman spectroscopy has become a powerful tool in different fields of science and engineering; however, in specific applications, this technique's limiting factor is closely related to the inherent noise of the Raman spectra. To eliminate the noise of a Raman spectrum, preserving its position, intensity, and width characteristic, we propose using a genetic matching pursuit-Hermite atoms (GMP-HAs) algorithm in this work. This algorithm helps recover Raman spectra immersed in Gaussian noise with the least number of atoms. The noise-free Raman signal is reconstructed with the GMP-HAs algorithm, transforming the typical best-matching atom search into an optimization problem. Specifically, we maximize the fitness function, defined as the correlation between current residual and Hermite atoms, with the genetic algorithm MI-LXPM encoded in a real domain and avoiding local maxima, by adding a stopping criterion based on an exponential adjustment according to the algorithm's behavior in the presence of noise. Simulated and biological Raman spectra are used to evaluate the proposed algorithm and compare its performance with typically known methods for denoising, such as the Savitzky- Golay filter (SG) and basis pursuit denoising. Using the signal-to-noise ratio (S/N)metric resulted in a 0.31 dB advantage in the S/N product for the proposed algorithm with respect to SG. Additionally, it is shown that the algorithm uses only 25.3% of the number of atoms needed by the matching pursuit algorithm. The results indicate that the GMP-HAs algorithm has better denoising capabilities, and at the same time, the Raman spectra are decomposed with fewer atoms compared to known sparse algorithms.

Assessment of a computed tomography imaging spectrometer using an optimized expectation-maximization algorithm.

We designed and built a homemade computed tomography imaging spectrometer (CTIS) of 250×250pixels of spatial resolution and 2 nm spectral resolution. The optical design considers a CTIS optical array coupled to a digital reflex camera. We reconstructed the intensity spectra of a fluorescent source, the diffuse reflectance of a ColorChecker, and samples of Capsicum annuum of three different colors, using the expectation-maximization sequential algorithm, optimized utilizing an array of indices to reduce the reconstruction time. The results obtained with a ColorChecker indicate a high positive correlation of 0.9745 with an average residual difference of 1.31% concerning the spectra obtained with a commercial integrating sphere spectrometer. The feasibility of the proposed CTIS system shows how to detect and evaluate the physiological changes resulting from the decomposition of the green fruit of the Capsicum annuum in a range from 500 to 650 nm.

On the estimation of sugars concentrations using Raman spectroscopy and artificial neural networks.

In this paper, we present an analysis of the performance of Raman spectroscopy, combined with feed-forward neural networks (FFNN), for the estimation of concentration percentages of glucose, sucrose, and fructose in water solutions. Indeed, we analysed our method for the estimation of sucrose in three solid industrialized food products: donuts, cereal, and cookies. Concentrations were estimated in two ways: using a non-linear fitting system, and using a classifier. Our experiments showed that both the classifier and the fitting systems performed better than a Support Vector Machine (SVM), a Linear Discriminant Analysis (LDA), a Linear Regression (LR), and interval Partial Least Squares (iPLS). The best-case obtained by an FFNN for water solutions was 93.33% of classification and 3.51% of Root Mean Square Error in Prediction (RMSEP), compared with 82.22% obtained by a LDA. Our proposed method got an RMSEP of 1% for the best-case obtained with the food products.

Characterization of glycated hemoglobin based on Raman spectroscopy and artificial neural networks.

The World Health Organization has declared the glycated hemoglobin (HbA1c) as a gold standard biomarker for diabetes diagnosis; this has led to relevant research on the spectral behavior and characterization of HbA1c. This paper presents an analysis of Raman peaks of commercial lyophilized HbA1c, diluted in distilled water, using concentrations of 4.76% and 9.09%, as well as pure powder (100% concentration). Vibrational Raman peak positions of HbA1c powder were found at 1578, 1571, 1536, 1436, 1311, 1308, 1230, 1222, 1114, 1106, 969, 799 and 665 cm-1; these values are consistent with results reported in other works. Besides, a nonlinear regression model based on a Feed-Forward Neural Network (FFNN) was built to quantify percentages of HbA1c for unknown concentrations. Using the Raman spectra as independent variables, the regression provided a Root Mean Square Error in Cross-Validation (RMSECV) of 0.08% ±â€¯0.04. We also include a detailed molecular assignment of the average spectra of lyophilized powder of HbA1c.

[Delayed recurrence of a phaechromocytoma with metastasis as a cause of severe hypertension in a woman with a surgically intervened retroperitoneal tumour]. / Recidiva tardía de feocromocitoma con metástasis como causa de hipertensión arterial severa en mujer intervenida quirúrgicamente de tumor retroperitoneal.

We present the case of a woman with a previous history of hypertension and retroperitoneal tumour. The histology was reported as a paraganglioma. There was no clinical follow-up. Years later, there was a recurrence of the phaeochromocytoma after presenting with a difficult to control hypertension, along with elevation of urinary catecholamines. The case aims to highlight the importance of performing a clinical follow-up in these patients, due to the risk of recurrence.

Raman spectroscopy and PCA-SVM as a non-invasive diagnostic tool to identify and classify qualitatively glycated hemoglobin levels in vivo.

In this study we identify and classify high and low levels of glycated hemoglobin (HbA1c) in healthy volunteers (HV) and diabetic patients (DP). Overall, 86 subjects were evaluated. The Raman spectrum was measured in three anatomical regions of the body: index fingertip, right ear lobe, and forehead. The measurements were performed to compare the difference between the HV and DP (22 well controlled diabetic patients (WCDP) (HbA1c <6.5%), and 49 not controlled diabetic patients (NCDP) (HbA1c ≥6.5%)). Multivariable methods such as principal components analysis (PCA) combined with support vector machine (SVM) were used to develop effective diagnostic algorithms for classification among these groups. The forehead of HV versus WCDP showed the highest sensitivity (100%) and specificity (100%). Sensitivity (100%) and specificity (60%), were highest in the forehead of WCDP, versus NCDP. In HV versus NCDP, the fingertip had the highest sensitivity (100%) and specificity (80%). The efficacy of the diagnostic algorithm by receiver operating characteristic (ROC) curve was confirmed. Overall, our study demonstrated that the combination of Raman spectroscopy and PCA-SVM are feasible non-invasive diagnostic tool in diabetes to classify qualitatively high and low levels of HbA1c in vivo.

Exact Calculation of the Circle of Least Confusion of a Rotationally Symmetric Mirror. II.

We compute the radius and the position of the center of the circle of least confusion, in an exact way and by using the third-order approximation, of a rotationally symmetric mirror when the point source is located at any position on the optical axis. For the spherical case we find that for some positions of the point source there is a considerable difference between the exact computations and those obtained by working up to third-order aberrations.

Optical alignment of segmented mirrors to the fluorescence detectors of the Pierre Auger observatory.

Segmented mirrors will be used in the telescopes of the Pierre Auger Fluorescence detector. To align the segments, we have developed four methods in which (a) the image of the stop border, (b) the image of a screen with concentric circles, and (c) the Ronchi pattern are used. In addition to these, we have developed a new method, (d), in which instead of the Ronchi ruling, we have used a circular grid. In this case we obtain a moiré pattern for each segment by means of which the experimental setup is simplified, and the sensitivity of the alignment is improved.

Exact Design of Aplanatic Microscope Objectives consisting of Two Conic Mirrors.

The necessary equations are derived for the design of aplanatic microscope objectives consisting of two mirrors, one concave and the other convex. The first-order parameters are calculated along with the conic constants of the mirrors, determined by means of an exact analysis to arrive at an aplanatic system.

Exact calculation of the circle of least confusion of a rotationally symmetric mirror.

The position and dimensions of the circle of least confusion (CLC) on axis for a lensless Schmidt camera telescope operating at F(0.82) are calculated. The camera is to be used in the fluorescence detector of the Pierre Auger Observatory. Our analysis was developed for an aspherical mirror for any on-axis position of the point light source. Our technique uses the intersection of the marginal ray from one side of the aperture with the caustic produced by the intermediate rays from the opposite side of the aperture to locate the CLC.

Multiple-path telescope: third-order design.

Exact results for the magnification and effective focal length of a multiple-path telescope are presented. We present analytical results for the third-order design of this system, using the Seidel sums for the five aberration terms. Numerical calculations are used throughout to corroborate these results. Third-order aberrations remain small or at least stable as the number of paths is increased.