Automatic Baseline Subtraction of Vibrational Spectra Using Minima Identification and Discrimination via Adaptive, Least-Squares Thresholding

2012 ◽  
Vol 66 (5) ◽  
pp. 519-529 ◽  
Author(s):  
Andrew T. Weakley ◽  
Peter R. Griffiths ◽  
D. Eric Aston
Keyword(s):  
Signal To Noise Ratio ◽  
Local Level ◽  
Confidence Region ◽  
Baseline Correction ◽  
Threshold Region ◽  
Model Free ◽  
Baseline Subtraction ◽  
Surface Enhanced ◽  
Vibrational Bands ◽  
Threshold Criteria

A method of automated baseline correction has been developed and applied to Raman spectra with a low signal-to-noise ratio and surface-enhanced infrared absorption (SEIRA) spectra with bipolar bands. Baseline correction is initiated by dividing the raw spectrum into equally spaced segments in which regional minima are located. Following identification, the minima are used to generate an intermediate second-derivative spectrum where points are assigned as baseline if they reside within a locally defined threshold region. The threshold region is similar to a confidence interval encountered in statistics. To restrain baseline and band point discrimination to the local level, the calculation of the confidence region employs only a predefined number of already-accepted baseline minima as part of the sample set. Statistically based threshold criteria allow the procedure to make an unbiased assessment of baseline points regardless of the behavior of vibrational bands. Furthermore, the threshold region is adaptive in that it is further modified to consider abrupt changes in baseline. The present procedure is model-free insofar as it makes no assumption about the precise nature of the perturbing baseline nor requires treatment of spectra prior to execution.

scholarly journals Surface-enhanced mid-infrared absorption spectroscopy using miniaturized-disc metasurface

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mitchell Semple ◽  
Ashwin K. Iyer
Keyword(s):  
Infrared Spectroscopy ◽  
Signal To Noise Ratio ◽  
Low Cost ◽  
Unit Cell ◽  
Mid Infrared ◽  
Wide Range ◽  
Surface Enhanced ◽  
Identification Measurements ◽  
Vibrational Bands ◽  
On Chip

AbstractSurface-enhanced infrared spectroscopy is an important technique for improving the signal-to-noise ratio of spectroscopic material identification measurements in the mid-infrared fingerprinting region. However, the lower bound of the fingerprinting region receives much less attention due to a scarcity of transparent materials, more expensive sources, and weaker plasmonic effects. In this paper, we present a miniaturized metasurface unit cell for surface-enhanced infrared spectroscopy of the 15-$$\upmu$$ μ m vibrational band of CO$$_{2}$$ 2 . The unit cell consists of a gold disc, patterned along the edge with fine gaps/wires to create a resonant metamaterial liner. In simulation, our plasmonic metamaterial-lined disc achieves greater than $$4\times$$ 4 × the average field intensity enhancement of a comparable dipole array and a miniaturized size of $$\lambda _0/5$$ λ 0 / 5 using complex, 100-nm features that are patterned using 100-kV electron-beam lithography. In a simple experiment, the metamaterial-lined disc metasurface shows a high tolerance to fabrication imperfections and enhances the absorption of CO$$_{2}$$ 2 at 15 $$\upmu$$ μ m. The resonant wavelength and reflection magnitude can be tuned over a wide range by adjusting the liner feature sizes and the metasurface array pitch to target other vibrational bands. This work is a step toward low-cost, more compact on-chip integrated gas sensors.

scholarly journals Accuracy of a Model-Free Algorithm for Temporal InSAR Tropospheric Correction

2021 ◽  
Vol 13 (3) ◽  
pp. 409
Author(s):  
Howard Zebker
Keyword(s):  
Time Series ◽  
Signal To Noise Ratio ◽  
Artifact Reduction ◽  
Interferometric Synthetic Aperture Radar ◽  
Spatial Properties ◽  
Model Free ◽  
Weather Model ◽  
Phase Variations ◽  
Source Of Error ◽  
Signal Correlation

Atmospheric propagational phase variations are the dominant source of error for InSAR (interferometric synthetic aperture radar) time series analysis, generally exceeding uncertainties from poor signal to noise ratio or signal correlation. The spatial properties of these errors have been well studied, but, to date, their temporal dependence and correction have received much less attention. Here, we present an evaluation of the magnitude of tropospheric artifacts in derived time series after compensation using an algorithm that requires only the InSAR data. The level of artifact reduction equals or exceeds that from many weather model-based methods, while avoiding the need to globally access fine-scale atmosphere parameters at all times. Our method consists of identifying all points in an InSAR stack with consistently high correlation and computing, and then removing, a fit of the phase at each of these points with respect to elevation. A comparison with GPS truth yields a reduction of three, from a rms misfit of 5–6 to ~2 cm over time. This algorithm can be readily incorporated into InSAR processing flows without the need for outside information.

Surface Enhanced Raman Scattering (SERS) Spectroscopy Combined With Chemical Imaging Analysis For The Early Detection of Apple Valsa Canker

2021 ◽  
Author(s):  
Shiyan Fang ◽  
Junmeng Li ◽  
Yan Wang ◽  
Yanru Zhao ◽  
Keqiang Yu
Keyword(s):  
Machine Learning ◽  
Early Detection ◽  
Chemical Imaging ◽  
Baseline Correction ◽  
Imaging Analysis ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Valsa Canker ◽  
Apple Valsa Canker ◽  
Enhanced Raman Scattering

Abstract Background: Apple Valsa Canker (AVC) with early incubation characteristics is a severe apple tree disease. Therefore, early detection of the infected trees is necessary to prevent the rapid development of the disease. Surface enhanced Raman Scattering (SERS) spectroscopy is a promising technique that simplifies detection procedures and reduces detection time. Meanwhile, SERS enhance signals at low laser powers and suppress biological fluorescence. In this study, the early detection of the AVC disease was carried out by combining SERS spectroscopy with the chemometrics methods and machine learning algorithms, and then chemical distribution imaging was successfully applied to the analysis of disease dynamics.Results: Firstly, the microstructure, UV-Vis spectrum, and Raman spectrum of SERS metallic nano-substrates were proved to investigate the enhancement effects of the synthesized AgNPs. Secondly, the multiple spectral baseline correction (MSBC), the asymmetric least squares (AsLS), and the adaptive iterative reweighted penalized least squares (air-PLS) were adopted to eliminate the disturbances of the baseline offset. The correlation analysis method was employed to identify the best baseline correction algorithm, which was the air-PLS algorithm herein. Meanwhile, principal component analysis (PCA) was used to perform clustering analysis based on the healthy, early disease, and late disease sample datasets, demonstrating obvious clustering effects. After that, optimal spectral variables were selected to build machine learning models to detect AVC disease, incorporating the BP-ANN, ELM, RForest, and LS-SVM algorithms. The accuracy of these models was above 90%, showing excellent discriminant performance. Finally, SERS chemical imaging provided the spatiotemporal dynamic characteristics of changes in the cellulose and lignin of the phloem disease-health junction under AVC stress. The results suggested that cellulose and lignin in the cell walls of infected tissues reduced significantly.Conclusions: SERS spectroscopy combining with chemical imaging analysis for early detection of the AVC disease was considered feasible and promising. This study provided a practical method for the rapid diagnosis of apple orchard diseases.

Surface Enhanced Magneto-Optics in Noble Metal / Ferromagnetic Metal Multilayers

1995 ◽  
Vol 384 ◽  
Author(s):  
V. I. Safarov ◽  
V. A. Kosobukin ◽  
C. Hermann ◽  
G. Lampel ◽  
J. Peretti ◽  
...  
Keyword(s):  
Noble Metal ◽  
Figure Of Merit ◽  
Signal To Noise Ratio ◽  
Ferromagnetic Metal ◽  
Multilayer Thin Films ◽  
Kerr Rotation ◽  
Resonant Coupling ◽  
Electromagnetic Enhancement ◽  
Surface Enhanced ◽  
Resonant Feature

ABSTRACTWe present an electromagnetic enhancement mechanism for the magneto-optical response of noble metal / ferromagnetic metal multilayer thin films. When such a structure is illuminated in total reflection condition, the resonant coupling of light with the noble metal surface plasmons gives rise to an amplification of the magneto-optically induced component of the light electric field. The experimental results obtained on a 30nm-thick Au / Co / Au model system show that this resonant feature observed in the Kerr rotation and ellipticity corresponds to a strong enhancement of the magneto-optical figure of merit and signal-to-noise ratio.

Effect of Endurance Training on Different Mechanical Efficiency Indices During Submaximal Cycling in Subjects Unaccustomed to Cycling

2005 ◽  
Vol 30 (5) ◽  
pp. 520-528 ◽  
Author(s):  
Frédérique Hintzy ◽  
Laurent Mourot ◽  
Stéphane Perrey ◽  
Nicolas Tordi
Keyword(s):  
Endurance Training ◽  
Mechanical Efficiency ◽  
Peak Oxygen Uptake ◽  
Cycle Ergometer ◽  
Baseline Correction ◽  
Baseline Subtraction ◽  
Work Cycle ◽  
Before And After ◽  
Resting Metabolism ◽  
Sedentary Women

The purpose of this study was to evaluate different efficiency indices, i.e., gross (GE: no baseline correction), net (NE: resting metabolism as baseline correction), and work (WE: unloaded exercise as baseline correction), to reveal the effect of endurance training on mechanical efficiency. Nine healthy sedentary women undertook an incremental test and submaximal cycling exercise, at an intensity corresponding to 50% of the pretraining peak oxygen uptake, before and after 6 weeks of endurance training (18 sessions of 45 min). The training effects on efficiency indices were tested by comparisons based on GE, NE, and WE as well as by the differences between the percentage changes of all indices (% GE, % NE, % WE). Endurance training resulted in significantly higher GE (+ 11.1%; p <  0.001) and NE (+ 9.1%; P <  0.01). Only minor significant improvement (+ 2.4%; p <  0.05) was observed with the WE index because the value used for baseline subtraction was significantly reduced by the training sessions, due perhaps to improvement in pedaling skill. As a consequence, % WE was significantly lower than % GE (p <  0.01) and % NE (p <  0.05), while % GE and % NE were not significantly different. We conclude that mechanical efficiency of cycling increases with training in women previously unfamiliar with cycling, and that the WE index is less sensitive to this training effect than GE and NE indices. Key words: gross efficiency, net efficiency, work efficiency, internal work, cycle ergometer

scholarly journals Waveguide excitation and collection of surface-enhanced Raman scattering from a single plasmonic antenna

Nanophotonics ◽  
2018 ◽  
Vol 7 (7) ◽  
pp. 1299-1306 ◽  
Author(s):  
Frédéric Peyskens ◽  
Pieter Wuytens ◽  
Ali Raza ◽  
Pol Van Dorpe ◽  
Roel Baets
Keyword(s):  
Signal To Noise Ratio ◽  
Single Mode ◽  
Surface Enhanced Raman Spectroscopy ◽  
Sers Spectrum ◽  
Plasmonic Enhancement ◽  
Detection Scheme ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Enhanced Raman Scattering ◽  
On Chip

AbstractThe integration of plasmonic antennas on single-mode silicon nitride waveguides offers great perspective for integrated surface-enhanced Raman spectroscopy (SERS). However, the few reported experimental demonstrations still require multiple plasmonic antennas to obtain a detectable SERS spectrum. Here, we show, for the first time, SERS signal detection by a single nanoplasmonic antenna integrated on a single-mode SiN waveguide. For this purpose, we investigated a backscattering detection scheme in combination with background noise reduction, which allowed an optimization of the signal-to-noise ratio (SNR) of this platform. Furthermore, a comparison with the free-space SERS spectrum of the same antenna shows that the conversion efficiency from pump power to total radiated Stokes power is twice as efficient in the case of waveguide excitation. As such, we explored several important aspects in the optimization of on-chip SERS sensors and experimentally demonstrated the power of exciting nanoplasmonic antennas using the evanescent field of a waveguide. This observation not only is useful for Raman sensing but also could be beneficial for any process involving plasmonic enhancement.

scholarly journals Clustering of fMRI data: the elusive optimal number of clusters

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5416 ◽  
Author(s):  
Mohamed L. Seghier
Keyword(s):  
Signal To Noise Ratio ◽  
Building Blocks ◽  
Optimal Number ◽  
Hierarchical Organization ◽  
Fmri Data ◽  
Full Description ◽  
Number Of Clusters ◽  
High Data ◽  
Model Free ◽  
True Number

Model-free methods are widely used for the processing of brain fMRI data collected under natural stimulations, sleep, or rest. Among them is the popular fuzzy c-mean algorithm, commonly combined with cluster validity (CV) indices to identify the ‘true’ number of clusters (components), in an unsupervised way. CV indices may however reveal different optimal c-partitions for the same fMRI data, and their effectiveness can be hindered by the high data dimensionality, the limited signal-to-noise ratio, the small proportion of relevant voxels, and the presence of artefacts or outliers. Here, the author investigated the behaviour of seven robust CV indices. A new CV index that incorporates both compactness and separation measures is also introduced. Using both artificial and real fMRI data, the findings highlight the importance of looking at the behavior of different compactness and separation measures, defined here as building blocks of CV indices, to depict a full description of the data structure, in particular when no agreement is found between CV indices. Overall, for fMRI, it makes sense to relax the assumption that only one unique c-partition exists, and appreciate that different c-partitions (with different optimal numbers of clusters) can be useful explanations of the data, given the hierarchical organization of many brain networks.

scholarly journals Evaluation of Serum Protein Profiling by Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass Spectrometry for the Detection of Prostate Cancer: I. Assessment of Platform Reproducibility

2005 ◽  
Vol 51 (1) ◽  
pp. 102-112 ◽  
Author(s):  
O John Semmes ◽  
Ziding Feng ◽  
Bao-Ling Adam ◽  
Lionel L Banez ◽  
William L Bigbee ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Signal To Noise Ratio ◽  
Laser Desorption ◽  
Mass Accuracy ◽  
Signal To Noise ◽  
Ionization Time ◽  
Flight Mass Spectrometry ◽  
Peak Intensity ◽  
Surface Enhanced ◽  
Tof Ms

Abstract Background: Protein expression profiling for differences indicative of early cancer has promise for improving diagnostics. This report describes the first stage of a National Cancer Institute/Early Detection Research Network-sponsored multiinstitutional evaluation and validation of this approach for detection of prostate cancer. Methods: Two sequential experimental phases were conducted to establish interlaboratory calibration and standardization of the surface-enhanced laser desorption (SELDI) instrumental and assay platform output. We first established whether the output from multiple calibrated Protein Biosystem II SELDI-ionization time-of-flight mass spectrometry (TOF-MS) instruments demonstrated acceptable interlaboratory reproducibility. This was determined by measuring mass accuracy, resolution, signal-to-noise ratio, and normalized intensity of three m/z “peaks” present in a standard pooled serum sample. We next evaluated the ability of the calibrated and standardized instrumentation to accurately differentiate between selected cases of prostate cancer and control by use of an algorithm developed from data derived from a single site 2 years earlier. Results: When the described standard operating procedures were established at all laboratory sites, the across-laboratory measurements revealed a CV for mass accuracy of 0.1%, signal-to-noise ratio of ∼40%, and normalized intensity of 15–36% for the three pooled serum peaks. This was comparable to the intralaboratory measurements of the same peaks. The instrument systems were then challenged with sera from a selected group of 14 cases and 14 controls. The classification agreement between each site and the established decision algorithm were examined by use of both raw peak intensity boosting and ranked peak intensity boosting. All six sites achieved perfect blinded classification for all samples when boosted alignment of raw intensities was used. Four of six sites achieved perfect blinded classification with ranked intensities, with one site passing the criteria of 26 of 28 correct and one site failing with 19 of 28 correct. Conclusions: These results demonstrate that “between-laboratory” reproducibility of SELDI-TOF-MS serum profiling approaches that of “within-laboratory” reproducibility as determined by measuring discrete m/z peaks over time and across laboratories.

The Use of Surface Enhanced Raman Scattering for the Detection of Dipicolinic Acid on Silver Nanoparticles

2002 ◽  
Vol 738 ◽  
Author(s):  
Terry E. Phillips ◽  
Jennifer L. Sample ◽  
Peter F. Scholl ◽  
Joseph Miragliotta
Keyword(s):  
Raman Scattering ◽  
Dipicolinic Acid ◽  
Adsorbed Molecule ◽  
Surface Enhanced Raman Scattering ◽  
Solution Chemistry ◽  
Colloid Solution ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Vibrational Bands ◽  
Enhanced Raman Scattering

ABSTRACTWe report on the use of surface enhanced Raman scattering (SERS) for the detection of dipicolinic acid (DPA) adsorbed on a silver (Ag) nanoparticle substrate. We have examined the interaction of DPA with Ag nanoparticles in a slightly basic, aqueous solution and determined that the molecule adsorbs as a dipicolinate anion on the metal surface. For micro molar or lower DPA concentrations in the colloid solution, no SERS activity from the adsorbed molecule was observed until nanoparticle aggregation was induced by reducing the pH with the addition of nitric acid. Following aggregation, the SERS response exhibited vibrational bands associated with both the pyridine ring and the carboxylate moieties in the adsorbed dipicolinate species. With proper control of the colloidal solution chemistry, the dipicolinate vibrational features could be observed in the SERS spectra at concentrations as low as 20 nano molar, a limit determined by the presence of solution-based contaminants on the Ag surface. In addition to the controlled DPA analyte studies, SERS was also able to detect the release of this molecule from Bacillus globigii spores, a non-toxic simulant for Bacillus anthracis, which demonstrated the potential of this optical spectroscopy for the detection of biological and chemical agents.

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