Global least‐squares analysis of large, correlated spectral data sets and application to chemical kinetics and time‐resolved fluorescence

1996 ◽  
Vol 67 (12) ◽  
pp. 4380-4386 ◽  
Author(s):  
Peter Stilbs ◽  
Kim Paulsen
Keyword(s):  
Least Squares ◽  
Spectral Data ◽  
Chemical Kinetics ◽  
Data Sets ◽  
Time Resolved Fluorescence ◽  
Time Resolved

scholarly journals Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2524 ◽  
Author(s):  
Lea Fellner ◽  
Marian Kraus ◽  
Florian Gebert ◽  
Arne Walter ◽  
Frank Duschek
Keyword(s):  
Spectral Data ◽  
Classification Accuracy ◽  
Detection System ◽  
Laser Source ◽  
Nanosecond Laser ◽  
Time Resolved Fluorescence ◽  
Data Set ◽  
Time Resolved ◽  
Standoff Detection

Laser-induced fluorescence (LIF) is a well-established technique for monitoring chemical processes and for the standoff detection of biological substances because of its simple technical implementation and high sensitivity. Frequently, standoff LIF spectra from large molecules and bio-agents are only slightly structured and a gain of deeper information, such as classification, let alone identification, might become challenging. Improving the LIF technology by recording spectral and additionally time-resolved fluorescence emission, a significant gain of information can be achieved. This work presents results from a LIF based detection system and an analysis of the influence of time-resolved data on the classification accuracy. A multi-wavelength sub-nanosecond laser source is used to acquire spectral and time-resolved data from a standoff distance of 3.5 m. The data set contains data from seven different bacterial species and six types of oil. Classification is performed with a decision tree algorithm separately for spectral data, time-resolved data and the combination of both. The first findings show a valuable contribution of time-resolved fluorescence data to the classification of the investigated chemical and biological agents to their species level. Temporal and spectral data have been proven as partly complementary. The classification accuracy is increased from 86% for spectral data only to more than 92%.

scholarly journals Analysis of multicrystal pump–probe data sets. II. Scaling of ratio data sets

2016 ◽  
Vol 72 (2) ◽  
pp. 250-260 ◽  
Author(s):  
Bertrand Fournier ◽  
Jesse Sokolow ◽  
Philip Coppens
Keyword(s):  
Least Squares ◽  
Light Exposure ◽  
Weighted Least Squares ◽  
System Response ◽  
Data Sets ◽  
Data Set ◽  
Time Resolved ◽  
Pump Probe ◽  
Scaling Procedure ◽  
Ratio Data

Two methods for scaling of multicrystal data collected in time-resolved photocrystallography experiments are discussed. The WLS method is based on a weighted least-squares refinement of laser-ON/laser-OFF intensity ratios. The other, previously applied, is based on the average absolute system response to light exposure. A more advanced application of these methods for scaling within a data set, necessary because of frequent anisotropy of light absorption in crystalline samples, is proposed. The methods are applied to recently collected synchrotron data on the tetra-nuclear compound Ag2Cu2L4withL= 2-diphenylphosphino-3-methylindole. A statistical analysis of the weighted least-squares refinement residual terms is performed to test the importance of the scaling procedure.

Smooth Factor Analysis (SFA) to Effectively Remove High Levels of Noise from Spectral Data Sets

2017 ◽  
Vol 72 (5) ◽  
pp. 765-775 ◽  
Author(s):  
Yeonju Park ◽  
Isao Noda ◽  
Young Mee Jung
Keyword(s):  
Factor Analysis ◽  
Least Squares ◽  
Spectral Data ◽  
Partial Least Squares ◽  
Noise Level ◽  
Principal Component ◽  
Noise Removal ◽  
Correlation Spectroscopy ◽  
Data Sets ◽  
Spectral Data Analysis

Smooth factor analysis (SFA) is introduced as an effective method of removing heavy noise from spectral data sets. A modified form of the nonlinear iterative partial least squares (NIPALS) algorithm involving the smoothing of factors at each step is used in SFA. Compared with the conventional smoothing techniques for individual spectra, SFA is much more effective in the treatment of very noisy spectra (∼40% noise level). Smooth factor analysis invokes a large number of smooth factors to retain pertinent spectral information for high fidelity without distortion. This approach can be used as an effective general pretreatment procedure for multivariate spectral data analysis, such as principal component analysis (PCA) and partial least squares (PLS). This SFA method was also applied to the real experimental data, and its results successfully demonstrated the powerful potential for effective noise removal. Furthermore, this treatment is found to be very helpful to assist effective interpretation of two-dimensional correlation spectroscopy (2D-COS) spectra with very high noise level, which was not possible before.

scholarly journals The influence of sugar–protein complexes on the thermostability of C-reactive protein (CRP)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andreea Lorena Mateescu ◽  
Nicolae-Bogdan Mincu ◽  
Silvana Vasilca ◽  
Roxana Apetrei ◽  
Diana Stan ◽  
...  
Keyword(s):  
Diagnostic Tests ◽  
Protein Complexes ◽  
C Reactive Protein ◽  
Time Resolved Fluorescence ◽  
Time Resolved ◽  
Reactive Protein ◽  
In Vitro Diagnostic ◽  
The Stability ◽  
Positive Controls

AbstractThe purpose of the present study was to evaluate de influence of protein–sugar complexation on the stability and functionality of C-reactive protein, after exposure to constant high temperatures, in order to develop highly stable positive controls for in-vitro diagnostic tests. C-reactive protein is a plasmatic protein used as a biomarker for the diagnosis of a series of health problems such as ulcerative colitis, cardiovascular diseases, metabolic syndrome, due to its essential role in the evolution of chronic inflammation. The sugar–protein interaction was investigated using steady state and time resolved fluorescence. The results revealed that there are more than two classes of tryptophan, with different degree of accessibility for the quencher molecule. Our study also revealed that sugar–protein complexes have superior thermostability, especially after gamma irradiation at 2 kGy, the protein being stable and functional even after 22 days exposure to 40 °C.

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