scholarly journals Optical Dating of Eolian Dune Sand from the Canadian Prairies*

2004 ◽  
Vol 56 (2-3) ◽  
pp. 191-202 ◽  
Author(s):  
Olav B. Lian ◽  
David J. Huntley ◽  
Stephen A. Wolfe
Keyword(s):  
Near Infrared ◽  
Correction Method ◽  
Dune Sand ◽  
Optical Dating ◽  
Canadian Prairies ◽  
Thermal Transfer ◽  
South Central ◽  
Sedimentary Deposit ◽  
Infrared Excitation ◽  
Better Than

Abstract Optical dating is a well-established method that is used to determine the time elapsed since quartz or feldspar grains were last exposed to sunlight, which usually dates the time elapsed since their burial in a sedimentary deposit. Only a few seconds of direct sunlight are needed to reset the “mineral clock”, making the method ideal for dating the formation of eolian landforms. In this paper we describe how we use violet luminescence that is emitted in response to near-infrared excitation of sand-sized K-feldspar grains to date the time of formation of eolian dunes on the Canadian prairies. Using the multiple-aliquot with thermal transfer correction method, together with a test for sufficient sunlight exposure, and a correction for anomalous fading, we are able to produce accurate optical ages ranging from 150 years to more than 11 ka with precision usually better than 10 % at 2σ. Ages are given for dunes in the Dundurn and Elbow sand hills of south-central Saskatchewan, the climatic significance of which is provided in a paper also in the present volume. Knowledge of when the dunes were stable, and when they were not, is used to help understand the nature and timing of Holocene climate change in the area.

scholarly journals Optical Dating of Modern and Late Holocene Dune Sands in the Brandon Sand Hills, Southwestern Manitoba*

2004 ◽  
Vol 56 (2-3) ◽  
pp. 203-214 ◽  
Author(s):  
Stephen A. Wolfe ◽  
David J. Huntley ◽  
Jeff Ollerhead
Keyword(s):  
Late Holocene ◽  
Buried Soils ◽  
Optical Dating ◽  
Dune Sands ◽  
Thermal Transfer ◽  
Surface Samples ◽  
Road Section ◽  
Sand Hills ◽  
Infrared Excitation ◽  
Dune Activity

Abstract For any suite of optical dating samples two issues that must be considered are: do zero-age samples yield an optical age of zero, and are the optical ages consistent with independent stratigraphic and chronologic information? A test of the zero-age of dune sands was performed by dating samples from the crest, lee slope and stoss slope of an active dune in southwestern Manitoba. Three surface samples showed that, using 1.4 eV (infrared) excitation of K-feldspars, the equivalent dose, and hence “age”, depended on whether the bleach used for the thermal transfer correction was infrared/red or sunlight, leading to an age uncertainty of about ±40 years. Optical ages for samples 50 cm below these, and calculated relative to them, were 8 ± 8, 1 ± 7, and 38 ± 7 years, independent of the bleach used. These ages are consistent with expectations for the crest, lee slope and stoss slope, respectively. Optical ages of late Holocene dune sand units at the Brookdale Road section, southwestern Manitoba, were consistent with radiocarbon ages from organic matter within intervening buried soils. The suite of optical and radiocarbon ages from the Brandon Sand Hills provides a record of dune activity and stability for the region, and tentatively identifies periods of eolian activity at about 2 ka, 3.1 to 4.0 ka, and prior to 5.2 ka.

Quasi-Continuous Wave Near-Infrared Excitation of Upconversion Nanoparticles for Optogenetic Manipulation ofC. elegans

Small ◽  
2016 ◽  
Vol 12 (13) ◽  
pp. 1732-1743 ◽  
Author(s):  
Akshaya Bansal ◽  
Haichun Liu ◽  
Muthu Kumara Gnanasammandhan Jayakumar ◽  
Stefan Andersson-Engels ◽  
Yong Zhang
Keyword(s):  
Near Infrared ◽  
Continuous Wave ◽  
Upconversion Nanoparticles ◽  
Infrared Excitation

Applying Artificial Neural Networks. I. Estimating Nicotine in Tobacco from near Infrared Data

1995 ◽  
Vol 3 (3) ◽  
pp. 133-142 ◽  
Author(s):  
M. Hana ◽  
W.F. McClure ◽  
T.B. Whitaker ◽  
M. White ◽  
D.R. Bahler
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Near Infrared ◽  
Back Propagation ◽  
Linear Network ◽  
Data Set ◽  
Input Layer ◽  
Propagation Network ◽  
Better Than

Two artificial neural network models were used to estimate the nicotine in tobacco: (i) a back-propagation network and (ii) a linear network. The back-propagation network consisted of an input layer, an output layer and one hidden layer. The linear network consisted of an input layer and an output layer. Both networks used the generalised delta rule for learning. Performances of both networks were compared to the multiple linear regression method MLR of calibration. The nicotine content in tobacco samples was estimated for two different data sets. Data set A contained 110 near infrared (NIR) spectra each consisting of reflected energy at eight wavelengths. Data set B consisted of 200 NIR spectra with each spectrum having 840 spectral data points. The Fast Fourier transformation was applied to data set B in order to compress each spectrum into 13 Fourier coefficients. For data set A, the linear regression model gave better results followed by the back-propagation network which was followed by the linear network. The true performance of the linear regression model was better than the back-propagation and the linear networks by 14.0% and 18.1%, respectively. For data set B, the back-propagation network gave the best result followed by MLR and the linear network. Both the linear network and MLR models gave almost the same results. The true performance of the back-propagation network model was better than the MLR and linear network by 35.14%.

Near Infrared Spectroscopy Estimation of Feeding Value of Forage Perennial Grasses in Breeding Programmes by Global and Specific Calibrations. Estimation of Chemical Composition and Digestibility

1998 ◽  
Vol 6 (1) ◽  
pp. 153-165 ◽  
Author(s):  
Y. Naydenova ◽  
P. Tomov ◽  
P. Dardenne
Keyword(s):  
Cell Wall ◽  
Chemical Composition ◽  
Predictive Models ◽  
Near Infrared ◽  
Perennial Grasses ◽  
Standard Errors ◽  
Breeding Programmes ◽  
Feeding Value ◽  
Pre Treatment ◽  
Better Than

Near infrared (NIR) spectral analysis with a NIRSystems 6500 monochromator was applied to evaluate accuracy of predictive models for forage quality in clone breeding processes of the original Bulgarian varieties over different cuts and years. The varieties were the perennial grasses: Dactylis glomerata L., Festuca arundinacea Schreb. and Bromus inermis Leyss. Global calibrations for the 418 perennial grass samples and specific calibrations for each single grass species and internal cross-validations were performed by the PLS regression method. The effect of different spectral data pre-treatments was investigated on the residual standard errors of the NIR predictive models. Among 60 calibration equations, the model with the lowest SECV value was retained for each parameter in each database. No particular data pre-treatment was really better than the other ones. Generally, the best results of the global calibrations were obtained with SNVD and MSC. For the specific calibrations, SNVD and WMSC were the best treatments. In both cases, the first or second derivatives were needed after the first pre-treatment. Chemical composition and in vitro enzymatic digestibility of clones were predicted with accuracy similar to that of classical laboratory methods. For the cell wall component contents, the standard errors of cross-validation SECV(%DM) ranged from 0.49 for ADL ( Festuca) to 2.02 for NDF ( Dactylis). The digestibilities of dry and organic matter, IVDMD and IVOMD, were estimated with SECVs from 2.6 to 3.0%, the relative intake, from 0.06 to 0.09 rel% body weight and the relative feeding value, from 4.39 to 5.64 rel%. The global calibration models offer an acceptable accuracy for the estimation of the cell wall nutrient contents, the digestibility and the nutritive value. The standard errors of prediction of specific single species calibrations with smaller numbers of terms were lower in 60% of the cases than those obtained from the best global calibrations with higher numbers of terms. On average, SECVs from specific calibrations are better than those from global calibrations, but the differences are quite small, and for the prediction of totally new samples (new crops, another year), the global calibrations will detect less outlier samples. Even with very high variability between cuts and years, NIR spectroscopy is able via ANOVA GL Models to sort clones on their feeding value and to provide relevant information for the breeding programmes.

scholarly journals Field methods in the evaluation of obesity in children and adolescents

2009 ◽  
Vol 9 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Míriam Akemi Sampei ◽  
Dirce Maria Sigulem
Keyword(s):  
Body Mass Index ◽  
Body Composition ◽  
Waist Circumference ◽  
Body Fat ◽  
Direct Relationship ◽  
Near Infrared ◽  
Field Methods ◽  
Large Samples ◽  
Infrared Methods ◽  
Better Than

In large samples, the methods for obtaining information on obesity need to be simple, inexpensive and reasonably accurate. This review deals with articles focusing on various field methods for the evaluation of body composition. The Bioimpedance and Near Infrared methods are simple to execute but their advantage in relation to Body Mass Index is obscure. Although the Bioimpedance and near infrared methods provide estimates of fat content, they may be no better than waist circumference measurements. The latter does not distinguish body fat but points to a more direct relationship concerning health risk. Regardless of the advantages, waist circumference continues to be under discussion: there is a lack of standardization and no reference populations or cutoff points have been established. No perfect method exists, but the number of errors could be reduced, if care were taken in drawing up protocols, standardization, and the analysis of sample properties.

Identification of Liquor Brands Based on near Infrared Spectroscopy

2013 ◽  
Vol 834-836 ◽  
pp. 935-938
Author(s):  
Lian Shun Zhang ◽  
Chao Guo ◽  
Bao Quan Wang
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Principal Components ◽  
Near Infrared ◽  
Scatter Correction ◽  
Principal Component ◽  
Component Analysis ◽  
Correction Method ◽  
Variance Contribution

In this paper, the liquor brands were identified based on the near infrared spectroscopy method and the principal component analysis. 60 samples of 6 different brands liquor were measured by the spectrometer of USB4000. Then, in order to eliminate the noise caused by the external factors, the smoothing method and the multiplicative scatter correction method were used. After the preprocessing, we got the revised spectra of the 60 samples. The difference of the spectrum shape of different brands is not much enough to classify them. So the principal component analysis was applied for further analysis. The results showed that the first two principal components variance contribution rate had reached 99.06%, which can effectively represent the information of the spectrums after preprocessing. From the scatter plot of the two principal components, the 6 different brands of liquor were identified more accurate and easier than the spectra curves.

scholarly journals Demonstrated Wavelength Portability of Raman Reference Data for Explosives and Chemical Detection

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Timothy J. Johnson ◽  
Yin-Fong Su ◽  
Kristin H. Jarman ◽  
Brenda M. Kunkel ◽  
Jerome C. Birnbaum ◽  
...  
Keyword(s):  
Near Infrared ◽  
Reference Data ◽  
Current Sensor ◽  
Data Sets ◽  
Reference Library ◽  
Wavelength Calibration ◽  
Intensity Response ◽  
Excitation Laser ◽  
Key Issues ◽  
Infrared Excitation

As Raman spectroscopy continues to evolve, questions arise as to the portability of Raman data: dispersive versus Fourier transform, wavelength calibration, intensity calibration, and in particular the frequency of the excitation laser. While concerns about fluorescence arise in the visible or ultraviolet, most modern (portable) systems use near-infrared excitation lasers, and many of these are relatively close in wavelength. We have investigated the possibility of porting reference data sets from one NIR wavelength system to another: We have constructed a reference library consisting of 145 spectra, including 20 explosives, as well as sundry other compounds and materials using a 1064 nm spectrometer. These data were used as a reference library to evaluate the same 145 compounds whose experimental spectra were recorded using a second 785 nm spectrometer. In 128 cases of 145 (or 88.3% including 20/20 for the explosives), the compounds were correctly identified with a mean “hit score” of 954 of 1000. Adding in criteria for when to declare a correct match versus when to declare uncertainty, the approach was able to correctly categorize 134 out of 145 spectra, giving a 92.4% accuracy. For the few that were incorrectly identified, either the matched spectra were spectroscopically similar to the target or the 785 nm signal was degraded due to fluorescence. The results indicate that imported data recorded at a different NIR wavelength can be successfully used as reference libraries, but key issues must be addressed: the reference data must be of equal or higher resolution than the resolution of the current sensor, the systems require rigorous wavelength calibration, and wavelength-dependent intensity response should be accounted for in the different systems.

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