scholarly journals EXPRESS: Inter-Laboratory Application of Raman CO2 Densimeter Equations: Experimental Procedure and Statistical Analysis Using Bootstrapped Confidence Intervals

2021 ◽  
pp. 000370282098760
Author(s):  
Samantha Remigi ◽  
Tullio Mancini ◽  
Simona Ferrando ◽  
Maria Luce Frezzotti

Raman spectroscopy has been used extensively to calculate CO2 fluid density in many geological environments, based on the measurement of the Fermi diad split (Δ; cm-1) in the CO2 spectrum. While recent research has allowed the calibration of several Raman CO2 densimeters, there is a limit to the inter-laboratory application of published equations. These calculate two classes of density values for the same measured Δ, with a deviation of 0.09 ± 0.02 g/cm3 on average. To elucidate the influence of experimental parameters on the calibration of Raman CO2 densimeters, we propose a bottom-up approach beginning with the calibration of a new equation, to evaluate a possible instrument-dependent variability induced by experimental conditions. Then, we develop bootstrapped confidence intervals for density estimate of existing equations to move the statistical analysis from a sample-specific to a population level. We find that Raman densimeter equations calibrated based on spectra acquired with similar spectral resolution calculate CO2 density values lying within standard errors of equations and are suitable for the inter-laboratory application. The statistical analysis confirms that equations calibrated at similar spectral resolution calculate CO2 densities equivalent at 95% confidence, and that each Raman densimeter does have a limit of applicability, statistically defined by a minimum Δ value, below which the error in calculated CO2 densities is too high.

Weed Science ◽  
2015 ◽  
Vol 63 (SP1) ◽  
pp. 166-187 ◽  
Author(s):  
Christian Ritz ◽  
Andrew R. Kniss ◽  
Jens C. Streibig

There are various reasons for using statistics, but perhaps the most important is that the biological sciences are empirical sciences. There is always an element of variability that can only be dealt with by applying statistics. Essentially, statistics is a way to summarize the variability of data so that we can confidently say whether there is a difference among treatments or among regression parameters and tell others about the variability of the results. To that end, we must use the most appropriate statistics to get a “correct” picture of the experimental variability, and the best way of doing that is to report the size of the parameters or the means and their associated standard errors or confidence intervals. Simply declaring that the yields were 1 or 2 ton ha−1does not mean anything without associated standard errors for those yields. Another driving force is that no journal will accept publications without the data having been subjected to some kind of statistical analysis.


2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Ayari Takamura ◽  
Daisuke Watanabe ◽  
Rintaro Shimada ◽  
Takeaki Ozawa

Abstract Blood, as a cardinal biological system, is a challenging target for biochemical characterization because of sample complexity and a lack of analytical approaches. To reveal and evaluate aging process of blood compositions is an unexplored issue in forensic analysis, which is useful to elucidate the details of a crime. Here we demonstrate a spectral deconvolution model of near-infrared Raman spectra of bloodstain to comprehensively describe the aging process based on the chemical mechanism, particularly the kinetics. The bloodstain spectra monitored over several months at different temperatures are decomposed into significant spectral components by multivariate calculation. The kinetic schemes of the spectral components are explored and subsequently incorporated into the developed algorithm for the optimal spectral resolution. Consequently, the index of bloodstain aging is proposed, which can be used under different experimental conditions. This work provides a novel perspective on the chemical mechanisms in bloodstain aging and facilitates forensic applications.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
An Zheng ◽  
Michael Lamkin ◽  
Yutong Qiu ◽  
Kevin Ren ◽  
Alon Goren ◽  
...  

Abstract Background A major challenge in evaluating quantitative ChIP-seq analyses, such as peak calling and differential binding, is a lack of reliable ground truth data. Accurate simulation of ChIP-seq data can mitigate this challenge, but existing frameworks are either too cumbersome to apply genome-wide or unable to model a number of important experimental conditions in ChIP-seq. Results We present ChIPs, a toolkit for rapidly simulating ChIP-seq data using statistical models of key experimental steps. We demonstrate how ChIPs can be used for a range of applications, including benchmarking analysis tools and evaluating the impact of various experimental parameters. ChIPs is implemented as a standalone command-line program written in C++ and is available from https://github.com/gymreklab/chips. Conclusions ChIPs is an efficient ChIP-seq simulation framework that generates realistic datasets over a flexible range of experimental conditions. It can serve as an important component in various ChIP-seq analyses where ground truth data are needed.


2009 ◽  
Vol 101 (4) ◽  
pp. 1749-1754 ◽  
Author(s):  
Christopher M. Laine ◽  
Kevin M. Spitler ◽  
Clayton P. Mosher ◽  
Katalin M. Gothard

The amygdala plays a crucial role in evaluating the emotional significance of stimuli and in transforming the results of this evaluation into appropriate autonomic responses. Lesion and stimulation studies suggest involvement of the amygdala in the generation of the skin conductance response (SCR), which is an indirect measure of autonomic activity that has been associated with both emotion and attention. It is unclear if this involvement marks an emotional reaction to an external stimulus or sympathetic arousal regardless of its origin. We recorded skin conductance in parallel with single-unit activity from the right amygdala of two rhesus monkeys during a rewarded image viewing task and while the monkeys sat alone in a dimly lit room, drifting in and out of sleep. In both experimental conditions, we found similar SCR-related modulation of activity at the single-unit and neural population level. This suggests that the amygdala contributes to the production or modulation of SCRs regardless of the source of sympathetic arousal.


Author(s):  
Vaida Paketurytė ◽  
Vytautas Petrauskas ◽  
Asta Zubrienė ◽  
Olga Abian ◽  
Margarida Bastos ◽  
...  

2014 ◽  
Vol 3 (4) ◽  
pp. 130
Author(s):  
NI MADE METTA ASTARI ◽  
NI LUH PUTU SUCIPTAWATI ◽  
I KOMANG GDE SUKARSA

Statistical analysis which aims to analyze a linear relationship between the independent variable and the dependent variable is known as regression analysis. To estimate parameters in a regression analysis method commonly used is the Ordinary Least Square (OLS). But the assumption is often violated in the OLS, the assumption of normality due to one outlier. As a result of the presence of outliers is parameter estimators produced by the OLS will be biased. Bootstrap Residual is a bootstrap method that is applied to the residual resampling process. The results showed that the residual bootstrap method is only able to overcome the bias on the number of outliers 5% with 99% confidence intervals. The resulting parameters estimators approach the residual bootstrap values ??OLS initial allegations were also able to show that the bootstrap is an accurate prediction tool.


2000 ◽  
Vol 180 ◽  
pp. 92-96
Author(s):  
Mirel Birlan ◽  
Gheorghe Bocsa

AbstractThe statistical analysis of the O – C and the standard errors for the astrometric RRS2 standard stars, and the analysis of the standard errors for the intermediate PIRS stars for 75 extragalactic radiosource fields are presented. This study was performed at Bucharest Observatory.


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