scholarly journals Curve Fitting Derivative Method and Its Application in Mouse Growth

2019 ◽  
pp. 126-133
Author(s):  
Zhihua Li ◽  
Xin Zhao
Keyword(s):  
Curve Fitting ◽  
Derivative Method

Usefulness of a Curve Fitting Method in the Analysis of Overlapping Overtones and Combinations of CH Stretching Modes

2002 ◽  
Vol 10 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Yukiteru Katsumoto ◽  
Daisuke Adachi ◽  
Harumi Sato ◽  
Yukihiro Ozaki
Keyword(s):  
Curve Fitting ◽  
Second Derivative ◽  
Downward Shift ◽  
Fitting Method ◽  
Derivative Method ◽  
Structural Differences ◽  
Alcohol Mixtures ◽  
Curve Fitting Method ◽  
Second Derivative Method ◽  
Water Alcohol

This paper reports the usefulness of a curve fitting method in the analysis of NIR spectra. NIR spectra in the 7500–5500 cm−1 (1333–1818 nm) region were measured for water–methanol, water–ethanol and water–1-propanol mixtures with alcohol concentrations of 0–100 wt% at 25°C. The 6000–5600 cm−1 (1667–1786 nm) region, where the overtones and combinations of CH3 and CH2 stretching modes are expected to appear, shows significant band shifts with the increase in the alcohol content. To analyse the concentration-dependent spectral changes, a curve fitting method was utilised, and the results were compared with those obtained previously by a second derivative method. It was found that the first overtones of CH3 asymmetric and symmetric stretching modes of alcohols show a downward shift by about 15–30 cm−1 with the increase in the concentration of alcohols. The shifts are much larger for water–methanol mixtures than for water–ethanol and water–1-propanol mixtures. The first overtones and combinations of CH2 stretching modes of ethanol and 1-propanol also show a small downward shift. These shifts support our previous conclusion that there is an intermolecular “CH⃛O” interaction between the methyl group and water in the water–alcohol mixtures. The curve fitting method provided more feasible results for the band shifts than the second derivative method. It was revealed from the curve fitting method that the first overtone of the CH3 asymmetric stretching mode of water–methanol, water–ethanol and water–1-propanol mixtures shows different concentration-dependent plots. The first overtone of CH3 asymmetric stretching mode of water–methanol mixtures shifts more rapidly in the high methanol concentration range while that of water–1-propanol concentration shifts more markedly in the low 1-propanol concentration range. That of water–ethanol mixtures shows an intermediate trend. Based upon these differences structural differences among the three kinds of water–alcohol mixtures are discussed.

Estimating ink mileage of dry toners in electrophotography

TAPPI Journal ◽  
2013 ◽  
Vol 12 (3) ◽  
pp. 9-14
Author(s):  
RENMEI XU ◽  
CELESTE M. CALKINS
Keyword(s):  
Experimental Data ◽  
Curve Fitting ◽  
Graphite Furnace ◽  
Atomic Absorption Spectrometer ◽  
Density Region ◽  
Coated Papers ◽  
Graphite Furnace Atomic Absorption ◽  
S Model ◽  
Better Than ◽  
Film Weight

This work investigates the ink mileage of dry toners in electrophotography (EP). Four different substrates were printed on a dry-toner color production Xerox iGen3 EP press. The print layout contained patches with different cyan, magenta, yellow, and black tonal values from 10% to 100%. Toner amounts on cyan patches were measured using an analytical method. Printed patches and unprinted paper samples, as well as dry toners, were dissolved in concentrated nitric acid. The copper concentrations in the dissolved solutions were analyzed by a Zeeman graphite furnace atomic absorption spectrometer. Analytical results were calculated to determine the toner amounts on paper for different tonal values. Their corresponding reflection densities were also measured. All data were plotted with OriginPro® 8 software, and four mathematical models were used for curve fitting. It was found that the C-S model fitted the experimental data of the two uncoated papers better than the other three models. None of the four models fitted the experimental data of the two coated papers, while the linear model was found to fit the data well. Linear fitting was the best in the practical density region for the two coated papers. Ink mileage curves obtained from curve fitting were used to estimate how much ink was required to achieve a target density for each paper; hence, the ink mileage was calculated. The highest ink mileage was 3.39 times the lowest ink mileage. The rougher the paper surface, the higher the requirement for ink film weight, and the lower ink mileage. No correlation was found between ink mileage and paper porosity.

A COMPARISON OF TWO METHODS FOR MEASUREMENT OF ALDOSTERONE SECRETION RATE IN MAN

1966 ◽  
Vol 53 (2) ◽  
pp. 177-188 ◽  
Author(s):  
P. Lund-Johansen ◽  
T. Thorsen ◽  
K. F. Støa
Keyword(s):  
Urinary Excretion ◽  
Normal Subjects ◽  
Secretion Rate ◽  
Aldosterone Secretion ◽  
Simple Method ◽  
Mean Values ◽  
Pathological Conditions ◽  
Significant Difference ◽  
Derivative Method ◽  
The Mean

ABSTRACT A comparison has been made between (A), a relatively simple method for the measurement of aldosterone secretion rate, based on paper chromatography and direct densitometry of the aldosterone spot and (B) a more elaborate isotope derivative method. The mean secretion rate in 9 normal subjects was 112 ± 26 μg per 24 hours (method A) and 135 ± 35 μg per 24 hours (method B). The »secretion rate« in one adrenalectomized subject after the intravenous injection of 250 μg of aldosterone was 230 μg per 24 hours (method A) and 294 μg per 24 hours (method B). There was no significant difference in the mean values, and correlation between the two methods was good (r = 0.80). It is concluded that the densitometric method is suitable for clinical purposes as well as research, being more rapid and less expensive than the isotope derivative method. Method A also measures the urinary excretion of the aldosterone 3-oxo-conjugate, which is of interest in many pathological conditions. The densitometric method is obviously the less sensitive and a prerequisite for its use is an aldosterone secretion of 20—30 μg per 24 hours. Lower values are, however, rare in adults.

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System Performance

2012 ◽  
Vol 19 (2) ◽  
pp. 381-394
Author(s):  
José Pereira ◽  
Octavian Postolache ◽  
Pedro Girão
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Measurement System ◽  
Curve Fitting ◽  
System Performance ◽  
Redox Potentials ◽  
Voltage Sweep ◽  
Gaussian Curve ◽  
Fitting Method ◽  
Curve Fitting Method

Using A Segmented Voltage Sweep Mode and A Gaussian Curve Fitting Method to Improve Heavy Metal Measurement System PerformanceThis paper presents a voltammetric segmented voltage sweep mode that can be used to identify and measure heavy metals' concentrations. The proposed sweep mode covers a set of voltage ranges that are centered around the redox potentials of the metals that are under analysis. The heavy metal measurement system can take advantage of the historical database of measurements to identify the metals with higher concentrations in a given geographical area, and perform a segmented sweep around predefined voltage ranges or, alternatively, the system can perform a fast linear voltage sweep to identify the voltammetric current peaks and then perform a segmented voltage sweep around the set of voltages that are associated with the voltammetric current peaks. The paper also includes the presentation of two auto-calibration modes that can be used to improve system's reliability and proposes the usage of a Gaussian curve fitting of voltammetric data to identify heavy metals and to evaluate their concentrations. Several simulation and experimental results, that validate the theoretical expectations, are also presented in the paper.

On Calculation Schemes of Spatial Gradient for Spatio-temporal Derivative Method

2003 ◽  
Vol 23 (Supplement1) ◽  
pp. 21-24
Author(s):  
Yasufumi YAMAMOTO ◽  
Yuya AKAMATSU ◽  
Noriyoshi YONEHARA ◽  
Tomomasa UEMURA
Keyword(s):  
Spatial Gradient ◽  
Derivative Method ◽  
Temporal Derivative ◽  
Spatio Temporal
Sign in / Sign up

Export Citation Format

Share Document