scholarly journals Invariance principle and rigidity of high entropy measures

2018 ◽  
Vol 371 (2) ◽  
pp. 1231-1251 ◽  
Author(s):  
Ali Tahzibi ◽  
Jiagang Yang
Keyword(s):  
Invariance Principle ◽  
High Entropy ◽  
Entropy Measures

scholarly journals Evidence from mass-transactional data that chaotic spending behaviour precedes consumer financial distress

2020 ◽  
Author(s):  
Naomi Kate Muggleton ◽  
Edika G Quispe-Torreblanca ◽  
David Leake ◽  
John Gathergood ◽  
Neil Stewart
Keyword(s):  
Financial Distress ◽  
Financial Institution ◽  
Ecological Validity ◽  
Psychological Traits ◽  
High Entropy ◽  
Entropy Measures ◽  
Candidate Personality ◽  
Data Source ◽  
Chaotic Nature ◽  
Transactional Data

The prevalence of digital footprints can allow researchers to study the personalities of millions of individuals with improved ecological validity. We present spending entropy as a candidate personality trait derived as a feature of an objective big data source---mass-transactional data from millions of bank accounts. Entropy measures the unpredictability of spending and acts as a measure of the chaotic nature of a person's life. Over and above how much money people spend, and what the money is spent on, spending entropy positively relates to future financial distress. High entropy leads to increased probability of missed payments across financial products. Entropy temporally relates to future distress three months ahead including more severe measures of distress. We replicate our findings in personal current account, loan, and mortgage holders in a second financial institution. Our findings suggest that high-dimensional data can be used to build psychological traits that predict outcomes in novel situations.

Abstract 2168: Efficient Detection of Atrial Fibrillation and Congestive Heart Failure in Single-Lead Devices

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Randall Moorman ◽  
Yuping Xiao ◽  
Douglas Lake
Keyword(s):  
Heart Failure ◽  
Atrial Fibrillation ◽  
Congestive Heart Failure ◽  
Primary Prevention ◽  
Rr Intervals ◽  
High Entropy ◽  
Efficient Detection ◽  
Entropy Measures ◽  
Ectopic Beats ◽  
Roc Area

Patients receiving primary prevention single lead ICDs are at risk for atrial fibrillation (AF) and congestive heart failure (CHF). No such device reports AF burden, and only a single CHF measure, trans-thoracic impedance, is available. Entropy measures that count the number of matching RR intervals have promise, as AF is random (high entropy) and CHF is often marked by reduced heart rate variability (RR intervals with many matches) and ectopic beats (few matches). We designed entropy-based measures to detect AF (high entropy) and CHF (mixture of RR intervals with many and with few matches). For real-world implementation, we used only 12 RR intervals, and calculated the result every 30 minutes in 24-hour Holter monitor records from the MIT-BIH databases. The Figure shows distinction among AF, NSR and CHF records using HR and S.D. (panel A) or the new entropy-based measures. Panel A shows poor diagnostic performance of conventional measures. In Panel B, the y-axis, COSEn, is the coefficient of sample entropy. The AF records all have higher values, and the ROC area is 1.00. The x-axis is a measure of template match counts. It distinguishes between normals and CHF patients with ROC area 0.92. With only 12 RR intervals every 30 minutes, entropy calculations allow for efficient detection of AF and CHF. We propose that single lead devices can be employed as monitors in the primary prevention population, where risk of AF and CHF is high.

scholarly journals Entropy Mapping Approach for Functional Reentry Detection in Atrial Fibrillation: An In-Silico Study

Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 194 ◽  
Author(s):  
Juan Ugarte ◽  
Catalina Tobón ◽  
Andrés Orozco-Duque
Keyword(s):  
Atrial Fibrillation ◽  
Action Potential ◽  
Approximate Entropy ◽  
Human Action ◽  
Fractional Diffusion ◽  
Observation Window ◽  
High Entropy ◽  
Promising Tool ◽  
Entropy Measures ◽  
In Silico Study

Catheter ablation of critical electrical propagation sites is a promising tool for reducing the recurrence of atrial fibrillation (AF). The spatial identification of the arrhythmogenic mechanisms sustaining AF requires the evaluation of electrograms (EGMs) recorded over the atrial surface. This work aims to characterize functional reentries using measures of entropy to track and detect a reentry core. To this end, different AF episodes are simulated using a 2D model of atrial tissue. Modified Courtemanche human action potential and Fenton–Karma models are implemented. Action potential propagation is modeled by a fractional diffusion equation, and virtual unipolar EGM are calculated. Episodes with stable and meandering rotors, figure-of-eight reentry, and disorganized propagation with multiple reentries are generated. Shannon entropy ( S h E n ), approximate entropy ( A p E n ), and sample entropy ( S a m p E n ) are computed from the virtual EGM, and entropy maps are built. Phase singularity maps are implemented as references. The results show that A p E n and S a m p E n maps are able to detect and track the reentry core of rotors and figure-of-eight reentry, while the S h E n results are not satisfactory. Moreover, A p E n and S a m p E n consistently highlight a reentry core by high entropy values for all of the studied cases, while the ability of S h E n to characterize the reentry core depends on the propagation dynamics. Such features make the A p E n and S a m p E n maps attractive tools for the study of AF reentries that persist for a period of time that is similar to the length of the observation window, and reentries could be interpreted as AF-sustaining mechanisms. Further research is needed to determine and fully understand the relation of these entropy measures with fibrillation mechanisms other than reentries.

D-test: A New Test for Analyzing Scale Invariance Using Symbolic Dynamics and Symbolic Entropy

Methodology ◽  
2011 ◽  
Vol 7 (3) ◽  
pp. 88-95 ◽  
Author(s):  
Jose A. Martínez ◽  
Manuel Ruiz Marín
Keyword(s):  
Symbolic Dynamics ◽  
Scale Invariance ◽  
Rating Scales ◽  
Rating Scale ◽  
Marketing Research ◽  
Response Patterns ◽  
Measurement Scales ◽  
Improve Measurement ◽  
Entropy Measures ◽  
The Difference

The aim of this study is to improve measurement in marketing research by constructing a new, simple, nonparametric, consistent, and powerful test to study scale invariance. The test is called D-test. D-test is constructed using symbolic dynamics and symbolic entropy as a measure of the difference between the response patterns which comes from two measurement scales. We also give a standard asymptotic distribution of our statistic. Given that the test is based on entropy measures, it avoids smoothed nonparametric estimation. We applied D-test to a real marketing research to study if scale invariance holds when measuring service quality in a sports service. We considered a free-scale as a reference scale and then we compared it with three widely used rating scales: Likert-type scale from 1 to 5 and from 1 to 7, and semantic-differential scale from −3 to +3. Scale invariance holds for the two latter scales. This test overcomes the shortcomings of other procedures for analyzing scale invariance; and it provides researchers a tool to decide the appropriate rating scale to study specific marketing problems, and how the results of prior studies can be questioned.

Layered High-Entropy Oxide Structures for Reversible Energy Storage

2020 ◽  
Author(s):  
Junbo Wang ◽  
Yanyan Cui ◽  
Qingsong Wang ◽  
Kai Wang ◽  
Xiaohui Wang ◽  
...  
Keyword(s):  
Energy Storage ◽  
Cathode Material ◽  
Spray Pyrolysis ◽  
Lattice Structure ◽  
Oxide Materials ◽  
High Entropy ◽  
New Class ◽  
Nebulized Spray Pyrolysis

<p>Layered Li<i><sub>x</sub></i>MO<sub>2</sub> materials, a new class of high-entropy oxides, have been synthesized by nebulized spray pyrolysis. Specifically, the lattice structure of Li(Ni<sub>1/3</sub>Mn<sub>1/3</sub>Co<sub>1/3</sub>)O<sub>2</sub> (NCM111) cathode material has been replicated successfully while increasing the number of cations in equimolar proportions, thereby allowing transition to high-entropy oxide materials.</p>

High-Entropy Alloys as Catalysts for the CO2 and CO Reduction Reactions

2019 ◽  
Author(s):  
Jack Pedersen ◽  
Thomas Batchelor ◽  
Alexander Bagger ◽  
Jan Rossmeisl
Keyword(s):  
Density Functional ◽  
Rational Design ◽  
Hydrogen Adsorption ◽  
Co Adsorption ◽  
Reduction Reaction ◽  
Supervised Machine Learning ◽  
High Entropy Alloys ◽  
High Entropy ◽  
Co Reduction ◽  
Disordered Alloy

Using the high-entropy alloys (HEAs) CoCuGaNiZn and AgAuCuPdPt as starting points we provide a framework for tuning the composition of disordered multi-metallic alloys to control the selectivity and activity of the reduction of carbon dioxide (CO2) to highly reduced compounds. By combining density functional theory (DFT) with supervised machine learning we predicted the CO and hydrogen (H) adsorption energies of all surface sites on the (111) surface of the two HEAs. This allowed an optimization for the HEA compositions with increased likelihood for sites with weak hydrogen adsorption{to suppress the formation of molecular hydrogen (H2) and with strong CO adsorption to favor the reduction of CO. This led to the discovery of several disordered alloy catalyst candidates for which selectivity towards highly reduced carbon compounds is expected, as well as insights into the rational design of disordered alloy catalysts for the CO2 and CO reduction reaction.

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