Quantitative measure of the isospin splitting of the effective nucleon mass

2021 ◽  
Author(s):  
S. Haddad
Keyword(s):  
Root Mean Square ◽  
Asymmetry Parameter ◽  
Quantitative Measure ◽  
Nuclear Interaction ◽  
Mass Splitting ◽  
Nucleon Mass ◽  
Mean Square ◽  
Coupling Channel ◽  
Isospin Splitting ◽  
The Asymmetry

The effective nucleon mass splits into two components, one for the proton and another for the neutron, in the case of adding the isovector coupling channel of the nuclear interaction, while being the same in the case of considering only the isoscalar coupling. A quantitative measure of the splitting is defined by the root mean square (RMS) value of the effective nucleon mass splitting and applied to the effective nucleon mass splitting in lead and tin isotopes. The isospin splitting of the effective nucleon mass is found to increase almost linearly with the asymmetry parameter.

A Simple Index for Representing the Discrepancy between Simulations of Physiological Pharmacokinetic Models and Experimental Data

1995 ◽  
Vol 11 (4) ◽  
pp. 413-421 ◽  
Author(s):  
Kannan Krishnan ◽  
Sami Haddad ◽  
Michael Pelekis
Keyword(s):  
Experimental Data ◽  
Root Mean Square ◽  
Pbpk Model ◽  
Quantitative Measure ◽  
Sampling Point ◽  
Mean Square ◽  
Data Set ◽  
Model Simulations ◽  
Pbpk Models ◽  
Experimental Values

The objective of this study was to develop an index that would provide a quantitative measure of the degree of discrepancy between simulations of physiologically based pharmacokinetic (PBPK) models and experimental data. The approach we developed involves the calculation of the root mean square of the error (representing the difference between the individual simulated and experimental values for each sampling point in a time course curve), and dividing it by the root mean square of the experimental values. The resulting numerical values of discrepancy measures for several data sets (each corresponding to an end point) obtained in a single experimental study are then combined on the basis of a weighting proportional to the number of data points contained in each data set. Such consolidated discrepancy indices obtained from several experiments (e.g., exposure scenarios, doses, routes, species) are averaged to get an overall discrepancy index, referred to as the PBPK index. This empirical index reflects the overall, weighted average percent difference between the a priori PBPK model simulations and experimental data. The proposed methodology is illustrated using previously published experimental and simulated data on dichloromethane pharmacokinetics in humans. The application of this kind of a "quantitative" method should help remove the ambiguity in communicating the degree of concordance or discrepancy between PBPK model simulations and experimental data.

The Relationship of Root Mean Square Value of Electromyography and Isometric Torque of Quadriceps in Normal Subjects

2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Normal Subjects ◽  
Mean Square ◽  
Isometric Torque ◽  
Relationship Of ◽  
The Relationship

The Asymmetry Parameter and Aggregate Particles

1997 ◽  
Author(s):  
Gorden Videen ◽  
Ronald G. Pinnick ◽  
Dat Ngo ◽  
Qiang Fu ◽  
Petr Chylek
Keyword(s):  
Asymmetry Parameter ◽  
The Asymmetry ◽  
Aggregate Particles

scholarly journals Estimation of Apple Flowering Frost Loss for Fruit Yield Based on Gridded Meteorological and Remote Sensing Data in Luochuan, Shaanxi Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 1630
Author(s):  
Yaohui Zhu ◽  
Guijun Yang ◽  
Hao Yang ◽  
Fa Zhao ◽  
Shaoyu Han ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Minimum Temperature ◽  
Price Regulation ◽  
Flowering Period ◽  
Mean Square ◽  
Prevention Measures ◽  
Agricultural Insurance

With the increase in the frequency of extreme weather events in recent years, apple growing areas in the Loess Plateau frequently encounter frost during flowering. Accurately assessing the frost loss in orchards during the flowering period is of great significance for optimizing disaster prevention measures, market apple price regulation, agricultural insurance, and government subsidy programs. The previous research on orchard frost disasters is mainly focused on early risk warning. Therefore, to effectively quantify orchard frost loss, this paper proposes a frost loss assessment model constructed using meteorological and remote sensing information and applies this model to the regional-scale assessment of orchard fruit loss after frost. As an example, this article examines a frost event that occurred during the apple flowering period in Luochuan County, Northwestern China, on 17 April 2020. A multivariable linear regression (MLR) model was constructed based on the orchard planting years, the number of flowering days, and the chill accumulation before frost, as well as the minimum temperature and daily temperature difference on the day of frost. Then, the model simulation accuracy was verified using the leave-one-out cross-validation (LOOCV) method, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized root mean square error (NRMSE) were 0.69, 18.76%, and 18.76%, respectively. Additionally, the extended Fourier amplitude sensitivity test (EFAST) method was used for the sensitivity analysis of the model parameters. The results show that the simulated apple orchard fruit number reduction ratio is highly sensitive to the minimum temperature on the day of frost, and the chill accumulation and planting years before the frost, with sensitivity values of ≥0.74, ≥0.25, and ≥0.15, respectively. This research can not only assist governments in optimizing traditional orchard frost prevention measures and market price regulation but can also provide a reference for agricultural insurance companies to formulate plans for compensation after frost.

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

Intersession reliability of GPS-based and accelerometer-based physical variables in small-sided games with and without the offside rule

2021 ◽  
pp. 175433712098764
Author(s):  
Igor Junio de Oliveira Custódio ◽  
Gibson Moreira Praça ◽  
Leandro Vinhas de Paula ◽  
Sarah da Glória Teles Bredt ◽  
Fabio Yuzo Nakamura ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Positioning System ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Mean Square ◽  
Physical Demands ◽  
Intraclass Correlation Coefficients ◽  
Total Distance ◽  
Global Positioning ◽  
High Level

This study aimed to analyze the intersession reliability of global positioning system (GPS-based) distances and accelerometer-based (acceleration) variables in small-sided soccer games (SSG) with and without the offside rule, as well as compare variables between the tasks. Twenty-four high-level U-17 soccer athletes played 3 versus 3 (plus goalkeepers) SSG in two formats (with and without the offside rule). SSG were performed on eight consecutive weeks (4 weeks for each group), twice a week. The physical demands were recorded using a GPS with an embedded triaxial accelerometer. GPS-based variables (total distance, average speed, and distances covered at different speeds) and accelerometer-based variables (Player Load™, root mean square of the acceleration recorded in each movement axis, and the root mean square of resultant acceleration) were calculated. Results showed that the inclusion of the offside rule reduced the total distance covered (large effect) and the distances covered at moderate speed zones (7–12.9 km/h – moderate effect; 13–17.9 km/h – large effect). In both SSG formats, GPS-based variables presented good to excellent reliability (intraclass correlation coefficients – ICC > 0.62) and accelerometer-based variables presented excellent reliability (ICC values > 0.89). Based on the results of this study, the offside rule decreases the physical demand of 3 versus 3 SSG and the physical demands required in these SSG present high intersession reliability.

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