Accurate determination of the gamma-ray energy from naturally occurring 40K and 138La

1980 ◽  
Vol 169 (3) ◽  
pp. 631-632 ◽  
Author(s):  
Tsuneo Morii
Keyword(s):  
Gamma Ray ◽  
Accurate Determination ◽  
Naturally Occurring

scholarly journals IMPROVED HPLC RESOLUTION AND QUANTIFICATION OF ELLAGIC ACID FROM STRAWBERRY, BLACKBERRY, AND CRANBERRY

HortScience ◽  
1990 ◽  
Vol 25 (9) ◽  
pp. 1078c-1078 ◽  
Author(s):  
S. Y. Wang ◽  
J. L. Maas ◽  
E. M. Daniel ◽  
G. J. Galletta
Keyword(s):  
Ellagic Acid ◽  
Accurate Determination ◽  
Ammonium Phosphate ◽  
Solvent System ◽  
Animal Nutrition ◽  
Genetic Studies ◽  
Naturally Occurring ◽  
Chemically Induced ◽  
Improved Methods

Ellagic acid (EA) a naturally occurring polyphenol in many fruit and nut crops, is a putative inhibitor of certain chemically-induced cancers. Improved methods of extraction, detection and quantification are essential for accurate determination of EA for plant physiological and genetic studies and animal nutrition and chemopreventative studies. Column (C18) preconditioning significantly reduced column retention of EA. An ammonium phosphate/methanol solvent system was used in preference to sodium phosphate/methanol. Fruit sample determinations were 10-100 times higher than previously reported, due to the improvements in efficiency of these methods. EA levels (mg/g dry wt) were: strawberry pulp (1.55), achene (8.46), root (1.55), crown (3.32) and leaf (14.27); blackberry pulp (,2.43) and seed (3.37); and cranberry skin (1.06), pulp (0.31), seed (0.69), leaf (4.10).

Improving porosity and gamma ray prediction for the Middle Jurassic Hugin sandstones in southern Norwegian North Sea with the application of deep neural networks

2021 ◽  
pp. 1-46
Author(s):  
Satinder Chopra ◽  
Ritesh Sharma ◽  
Kurt J. Marfurt ◽  
Rongfeng Zhang ◽  
Renjun Wen
Keyword(s):  
Neural Network ◽  
North Sea ◽  
Seismic Data ◽  
Deep Neural Network ◽  
Gamma Ray ◽  
Accurate Determination ◽  
Empirical Relation ◽  
Reservoir Property ◽  
Well Data

The complete characterization of a reservoir requires accurate determination of properties such as porosity, gamma ray and density, amongst others. A common workflow is to predict the spatial distribution of properties measured by well logs to those that can be computed from the seismic data. Generally, a high degree of scatter of data points is seen on crossplots between P-impedance and porosity, or P-impedance and gamma ray suggesting large uncertainty in the determined relationship. Although for many rocks there is a well established petrophysical model correlating P-impedance to porosity, there is not a comparable model correlating P-impedance to gamma ray. To address this issue, interpreters can use crossplots to graphically correlate two seismically derived variables to well measurements plotted in color. When there are more than two seismically derived variables, the interpreter can use multilinear regression or artificial neural network (ANN) analysis that uses a percentage of the upscaled well data for training to establish an empirical relation with the input seismic data and then uses the remaining well data to validate the relationship. Once validated at the wells, this relationship can then be used to predict the desired reservoir property volumetrically. We describe the application of deep neural network (DNN) analysis for the determination of porosity and gamma ray over the Volve Field in the southern Norwegian North Sea. After employing several quality-control steps in the deep neural network workflow and observing encouraging results, we validate the final prediction of both porosity and gamma ray properties using blind well correlation. The application of this workflow promises significant improvement to the reservoir property determination for fields that have good well control and exhibit lateral variations in the sought properties.

scholarly journals Improved Protocol for an Oxygen Electrode Method for Determining Hydrogen Peroxide in Foods

1997 ◽  
Vol 80 (3) ◽  
pp. 681-687 ◽  
Author(s):  
Fumio Miyamoto ◽  
Masanobu Saeki ◽  
Takumi Yoshizawa
Keyword(s):  
Hydrogen Peroxide ◽  
Standard Method ◽  
Present Method ◽  
Accurate Determination ◽  
Oxygen Electrode ◽  
Nitrogen Gas ◽  
Naturally Occurring ◽  
Residual Hydrogen ◽  
Electrode Method

Abstract An oxygen electrode method for determining residual hydrogen peroxide in foods has been further improved. Pretreatment, which includes extraction and neutralization, is done in a hydrogen peroxide extraction apparatus with nitrogen gas bubbling. The hydrogen peroxide concentration of the sample is corrected by subtracting the sample blank value, obtained for the sample through catalase treatment. Bubbling with nitrogen gas effectively minimized the sample blank value, making this method suitable for accurate determination of trace amounts of hydrogen peroxide in foods. Recoveries of hydrogen peroxide added at 1-10 μg/g were 77.8-107.1% by the present method. These recoveries are similar to or higher than those by the Japanese standard method and by another modified oxygen electrode method. Concentrations of naturally occurring hydrogen peroxide in solid foods were <0.87 μg/g by the present method, lower than those by either the standard method or another modified oxygen electrode method.

scholarly journals Natural isotope correction improves analysis of protein modification dynamics

2021 ◽  
Author(s):  
Jörn Dietze ◽  
Alienke van Pijkeren ◽  
Anna-Sophia Egger ◽  
Mathias Ziegler ◽  
Marcel Kwiatkowski ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Modification ◽  
High Resolution Mass Spectrometry ◽  
Accurate Determination ◽  
Mass Spectrometry Data ◽  
Stable Isotope Labelling ◽  
Isotope Labelling ◽  
Naturally Occurring ◽  
Correct Estimation

AbstractStable isotope labelling in combination with high-resolution mass spectrometry approaches are increasingly used to analyze both metabolite and protein modification dynamics. To enable correct estimation of the resulting dynamics, it is critical to correct the measured values for naturally occurring stable isotopes, a process commonly called isotopologue correction or deconvolution. While the importance of isotopologue correction is well recognized in metabolomics, it has received far less attention in proteomics approaches. Although several tools exist that enable isotopologue correction of mass spectrometry data, the majority is tailored for the analysis of low molecular weight metabolites. We here present PICor which has been developed for isotopologue correction of complex isotope labelling experiments in proteomics or metabolomics and demonstrate the importance of appropriate correction for accurate determination of protein modifications dynamics, using histone acetylation as an example.

Accurate determination of gamma-ray energies for E≤2 MeV

1985 ◽  
Author(s):  
E. G. Kessler ◽  
G. L. Greene ◽  
R. D. Deslattes ◽  
H. G. Börner
Keyword(s):  
Gamma Ray ◽  
Accurate Determination

scholarly journals An LC-MS/MS Method to Measure S-Methyl-l-Cysteine and S-Methyl-l-Cysteine Sulfoxide in Human Specimens Using Isotope Labelled Internal Standards

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2427 ◽  
Author(s):  
Tharsini Sivapalan ◽  
Antonietta Melchini ◽  
Jack Coode-Bate ◽  
Paul W. Needs ◽  
Richard F. Mithen ◽  
...  
Keyword(s):  
Accurate Determination ◽  
Correlation Coefficients ◽  
Sulphur Compounds ◽  
Internal Standards ◽  
Limits Of Detection ◽  
Naturally Occurring ◽  
Plasma And Urine Samples ◽  
Quantification Accuracy ◽  
Cysteine Sulfoxide

This is the first report describing an analytical method for quantitative analysis of two naturally occurring sulphur compounds, S-methyl-l-cysteine (SMC) and S-methyl-l-cysteine sulfoxide (SMCSO), in human body fluids using isotope-labelled internal standards and liquid chromatography-mass spectrometry (LC-MS)/MS techniques. This method was validated according to the guideline of the Royal Society of Chemistry Analytical Methods Committee. It offers significant advantages including simple and fast preparation of human biological samples. The limits of detection of SMC were 0.08 µM for urine and 0.04 µM for plasma. The limits of detection of SMCSO were 0.03 µM for urine and 0.02 µM for plasma. The calibration curves of all matrices showed linearity with correlation coefficients r2 > 0.9987. The intra and inter day precisions in three levels of known concentrations were >10% and >20%, respectively. The quantification accuracy was 98.28 ± 5.66%. The proposed method would be beneficial for the rapid and accurate determination of the SMC and SMCSO in human plasma and urine samples using by isotope labelled internal standards.

scholarly journals Calculation Improvement of the Clay Content in the Hydrocarbon Formation Rocks

2020 ◽  
Author(s):  
Sudad H Al-Obaidi
Keyword(s):  
Gamma Radiation ◽  
Oil And Gas ◽  
Gamma Ray ◽  
Accurate Determination ◽  
Clay Content ◽  
Clay Material ◽  
Reservoir Rocks ◽  
Content Determination ◽  
Hydrocarbon Formation

Natural radioactivity of reservoir rocks of oil and gas East Baghdad is due not only to their content of clay material, but also the existence of uranium that located in the skeleton of rocks. In connection with this, for the shale content determination of reservoir rocks, it is necessary to exclude the uranium contribution from the overall intensity of the gamma radiation. The paper presents the results of a research, using the data of spectral (standard) gamma ray logs-SGR, in which more accurate determination of the shaliness in the productive zones of the Zubair section of EastBaghdad fields (In Iraq) is proposed. With the help of a computer program, a formula that allows us to remove the effect of uranium, which affects the readings of gamma ray logging, is obtained.

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