scholarly journals Development of a method for differential analysis of data on the arterial blood oxygenation in healthy adults

2021 ◽  
Vol 6 (4 (114)) ◽  
pp. 37-43
Author(s):  
Gennady Chuiko ◽  
Yevhen Darnapuk
Keyword(s):  
Observation Interval ◽  
Blood Oxygenation ◽  
Statistical Distributions ◽  
Differential Analysis ◽  
Special Significance ◽  
Scale Invariant ◽  
Data Set ◽  
Arterial Blood ◽  
Fourier Spectra ◽  
The Difference

Monitoring of arterial blood saturation with oxygen (oxygenation) has gained special significance as a result of the COVID-19 pandemic. A new method for computer processing of saturation records (so-called SaO2 signals), based on the study of differentials (increments) from signals, was proposed. Finding a differential for a time series involves calculating the difference between the pairs of its adjacent elements. The differential is non-zero only if the elements in a pair are different. The study of differentials together with primary signals for a set of records (20 subjects) shows that the spectrum of observed levels of blood saturation is discrete and limited (from 2 to 10 levels). In addition, changes in saturation levels (switches) occur only between the nearest levels. New indicators of the variability of blood saturation were proposed. These are the frequencies of saturation level switches (event intensities) and the intervals between them. It was established that these indicators are described by statistical distributions of Poisson and Erlang, respectively. Comparison of new variability indicators with the most reliable statistical – inter-quartile range – indicates that the new indicators also provide for the division of the data set into three subgroups according to the magnitude of variability. This division is statistically significant at a confidence level of 0.99 in both approaches, however, the division into sub-groups is slightly different in these methods. It was shown that the proposed indicators of the variability of SaO2 signals are scale-invariant, that is, they do not depend on the length of observation interval. This is a consequence of the fractality of the positions of differentials in the observation interval. The established switch frequencies for subgroups in order of increasing variability are (0.06, 0.11, and 0.20) Hz. These frequencies are manifested on Fourier spectra of differentials of SaO2

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

Event detection of different English data sources based on transfer learning

2021 ◽  
pp. 1-11
Author(s):  
Yanan Huang ◽  
Yuji Miao ◽  
Zhenjing Da
Keyword(s):  
Transfer Learning ◽  
Event Detection ◽  
Visual Analysis ◽  
Learning Algorithm ◽  
Data Sources ◽  
Data Set ◽  
Data Source ◽  
Single Data Source ◽  
The Difference ◽  
Single Data

The methods of multi-modal English event detection under a single data source and isomorphic event detection of different English data sources based on transfer learning still need to be improved. In order to improve the efficiency of English and data source time detection, based on the transfer learning algorithm, this paper proposes multi-modal event detection under a single data source and isomorphic event detection based on transfer learning for different data sources. Moreover, by stacking multiple classification models, this paper makes each feature merge with each other, and conducts confrontation training through the difference between the two classifiers to further make the distribution of different source data similar. In addition, in order to verify the algorithm proposed in this paper, a multi-source English event detection data set is collected through a data collection method. Finally, this paper uses the data set to verify the method proposed in this paper and compare it with the current most mainstream transfer learning methods. Through experimental analysis, convergence analysis, visual analysis and parameter evaluation, the effectiveness of the algorithm proposed in this paper is demonstrated.

scholarly journals Extreme geomagnetic activities: a statistical study

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Ryuho Kataoka
Keyword(s):  
Magnetic Storms ◽  
Magnetic Observatory ◽  
Statistical Distributions ◽  
Limited Data ◽  
Data Set ◽  
Sudden Commencements ◽  
The One ◽  
Log Normal ◽  
Geomagnetic Activities ◽  
Log Normal Distribution

Abstract Statistical distributions are investigated for magnetic storms, sudden commencements (SCs), and substorms to identify the possible amplitude of the one in 100-year and 1000-year events from a limited data set of less than 100 years. The lists of magnetic storms and SCs are provided from Kakioka Magnetic Observatory, while the lists of substorms are obtained from SuperMAG. It is found that majorities of events essentially follow the log-normal distribution, as expected from the random output from a complex system. However, it is uncertain that large-amplitude events follow the same log-normal distributions, and rather follow the power-law distributions. Based on the statistical distributions, the probable amplitudes of the 100-year (1000-year) events can be estimated for magnetic storms, SCs, and substorms as approximately 750 nT (1100 nT), 230 nT (450 nT), and 5000 nT (6200 nT), respectively. The possible origin to cause the statistical distributions is also discussed, consulting the other space weather phenomena such as solar flares, coronal mass ejections, and solar energetic particles.

Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F25-F34 ◽  
Author(s):  
Benoit Tournerie ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Apparent Resistivity ◽  
A Priori ◽  
Shift Factor ◽  
Static Shift ◽  
Geostatistical Model ◽  
Data Set ◽  
Resistivity Sounding ◽  
The Difference ◽  
Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

scholarly journals What Countries Select More Experienced Leaders? The PolEx Measure of Political Experience

2021 ◽  
pp. 1-10
Author(s):  
Alexander Baturo ◽  
Johan A. Elkink
Keyword(s):  
Career Paths ◽  
Latent Variable ◽  
Empirical Studies ◽  
Future Research ◽  
Variable Model ◽  
Data Set ◽  
Political Experience ◽  
National Leaders ◽  
Regime Types ◽  
The Difference

Abstract How can one assess which countries select more experienced leaders for the highest office? There is wide variation in prior career paths of national leaders within, and even more so between, regime types. It is therefore challenging to obtain a truly comparative measure of political experience; empirical studies have to rely on proxies instead. This article proposes PolEx, a measure of political experience that abstracts away from the details of career paths and generalizes based on the duration, quality and breadth of an individual's experience in politics. The analysis draws on a novel data set of around 2,000 leaders from 1950 to 2017 and uses a Bayesian latent variable model to estimate PolEx. The article illustrates how the new measure can be used comparatively to assess whether democracies select more experienced leaders. The authors find that while on average they do, the difference with non-democracies has declined dramatically since the early 2000s. Future research may leverage PolEx to investigate the role of prior political experience in, for example, policy making and crisis management.

Investigation of Regression-Based Effect Size Methods Developed in Single-Subject Studies

2021 ◽  
pp. 014544552110540
Author(s):  
Nihal Sen
Keyword(s):  
Effect Size ◽  
Experimental Studies ◽  
Single Subject ◽  
Single Subject Design ◽  
Data Set ◽  
Design Studies ◽  
Sample Data ◽  
The Difference ◽  
D Values ◽  
Effect Size Calculation

The purpose of this study is to provide a brief introduction to effect size calculation in single-subject design studies, including a description of nonparametric and regression-based effect sizes. We then focus the rest of the tutorial on common regression-based methods used to calculate effect size in single-subject experimental studies. We start by first describing the difference between five regression-based methods (Gorsuch, White et al., Center et al., Allison and Gorman, Huitema and McKean). This is followed by an example using the five regression-based effect size methods and a demonstration how these methods can be applied using a sample data set. In this way, the question of how the values obtained from different effect size methods differ was answered. The specific regression models used in these five regression-based methods and how these models can be obtained from the SPSS program were shown. R2 values obtained from these five methods were converted to Cohen’s d value and compared in this study. The d values obtained from the same data set were estimated as 0.003, 0.357, 2.180, 3.470, and 2.108 for the Allison and Gorman, Gorsuch, White et al., Center et al., as well as for Huitema and McKean methods, respectively. A brief description of selected statistical programs available to conduct regression-based methods was given.

India-2021: Middle class in pandemic conditions

2021 ◽  
pp. 14
Author(s):  
Elena A. Bragina
Keyword(s):  
Developing Countries ◽  
Middle Class ◽  
Gradual Increase ◽  
Population Group ◽  
Special Significance ◽  
Statistical Estimates ◽  
National Characteristics ◽  
The Difference ◽  
Definition Of ◽  
Sociological Studies

The article analyzes the conditions for the formation of the middle class in India. Shown is its important balancing role in the politics and economy of the country. The nature of the definition of "middle class", its special significance in developing countries is considered. Due to the difference in the applied criterion - the initial unit of account (employee, family, population group), due to the weakness of statistical services, the results of sociological studies, statistical estimates of the size of the middle class are often approximate. The work shows that the official and infor-mal (shadow) parts of the middle class coexist in the economies of developing countries in parallel.  The pressure of the COVID-19 pandemic on the development of the Indian middle class is taken into account.  The article examines the national characteristics of the formation of the middle class inherent in India. Due to the unclear definition of the criteria, the inconsistency of its assessments, the insufficient level of work of statistical organizations, information on the size of the middle class is inaccurate (according to various estimates, about 210-360 million people). Attention is paid to the formation of the rural middle class in India, rural residents make up a significant part of it (estimated at 48-66%).The forecast of the recovery of the Indian middle class ispresented. It is assumed that its quantitative growth, which was observed before the pandemic, and a gradual increase in influence will continue and will allow in the future. The topic is relevant, in demand by the Russian reader.

scholarly journals Nonhepatic response to portal glucose delivery in conscious dogs

2000 ◽  
Vol 279 (6) ◽  
pp. E1271-E1277 ◽  
Author(s):  
Mary Courtney Moore ◽  
Po-Shiuan Hsieh ◽  
Doss W. Neal ◽  
Alan D. Cherrington
Keyword(s):  
Glucose Uptake ◽  
Glucose Infusion ◽  
Glucose Load ◽  
Arterial Blood ◽  
Hepatic Glucose ◽  
The Difference ◽  
Arterial Plasma ◽  
Arterial Blood Glucose ◽  
Blood Glucose Concentrations ◽  
Hepatic Glucose Uptake

The glycemic and hormonal responses and net hepatic and nonhepatic glucose uptakes were quantified in conscious 42-h-fasted dogs during a 180-min infusion of glucose at 10 mg · kg−1 · min−1 via a peripheral (Pe10, n = 5) or the portal (Po10, n = 6) vein. Arterial plasma insulin concentrations were not different during the glucose infusion in Pe10 and Po10 (37 ± 6 and 43 ± 12 μU/ml, respectively), and glucagon concentrations declined similarly throughout the two studies. Arterial blood glucose concentrations during glucose infusion were not different between groups (125 ± 13 and 120 ± 6 mg/dl in Pe10 and Po10, respectively). Portal glucose delivery made the hepatic glucose load significantly greater (36 ± 3 vs. 46 ± 5 mg · kg−1 · min−1 in Pe10 vs. Po10, respectively, P < 0.05). Net hepatic glucose uptake (NHGU; 1.1 ± 0.4 vs. 3.1 ± 0.4 mg · kg−1 · min−1) and fractional extraction (0.03 ± 0.01 vs. 0.07 ± 0.01) were smaller ( P < 0.05) in Pe10 than in Po10. Nonhepatic (primarily muscle) glucose uptake was correspondingly increased in Pe10 compared with Po10 (8.9 ± 0.4 vs. 6.9 ± 0.4 mg · kg−1 · min−1, P < 0.05). Approximately one-half of the difference in NHGU between groups could be accounted for by the difference in hepatic glucose load, with the remainder attributable to the effect of the portal signal itself. Even in the absence of somatostatin and fixed hormone concentrations, the portal signal acts to alter partitioning of a glucose load among the tissues, stimulating NHGU and reducing peripheral glucose uptake.

scholarly journals The Impact of Teachers Unions on Teachers’ Well-Being Under Various Legal Institutions: Evidence From District–Teacher Matched Data

AERA Open ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 233285841986729 ◽  
Author(s):  
Eunice S. Han
Keyword(s):  
Multilevel Models ◽  
Causal Effect ◽  
Well Being ◽  
Legal Environment ◽  
Legal Institutions ◽  
Data Set ◽  
Teachers Unions ◽  
The Difference ◽  
Matched Data ◽  
The Impact

This article examines how teachers unions affect teachers’ well-being under various legal institutions. Using a district–teacher matched data set, this study identifies the union effects by three approaches. First, I contrast teacher outcomes across different state laws toward unions. Second, I compare the union–nonunion differentials within the same legal environment, using multilevel models and propensity score matching. Finally, unexpected legal changes restricting the collective bargaining of teachers in four states form a natural experiment, allowing me to use the difference-in-difference estimation to identify the causal effect of weakening unionism on teacher outcomes. I find that (a) many teachers join unions even when bargaining is rarely or never available, and meet-and-confer or union membership rate affects teachers’ lives in the absence of a bargaining contract; (b) how unions influence teacher outcomes vary greatly by different legal environment; and (c) the changes in public policy limiting teachers’ bargaining rights significantly decrease teacher compensation.

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