Measure Of Information Content Research Articles

Impact of Infrared Atmospheric Sounding Interferometer (IASI) thermal infrared measurements on global ozone reanalyses

Abstract. The information content of thermal infrared measurements for tropospheric ozone (O3) estimation has already been well demonstrated. However, the impact of such measurements to constrain modelled O3 distributions within global assimilation systems is not yet unequivocal. A new tropospheric O3 reanalysis is computed for the year 2010 by means of assimilating measurements from the Infrared Atmospheric Sounding Interferometer (IASI) within the MOdéle pour la Chimie Á Grande Echelle (MOCAGE) chemical transport model. The objective is to evaluate the impact of recent methodological improvements of the data assimilation scheme on the O3 distribution. The new O3 reanalysis (named IASI-r) and its precursor (IASI-a) have been validated against ozonesondes, and compared to independent estimations of tropospheric O3 and to results from two state-of-the-art products based on detailed tropospheric chemistry (the Goddard Earth Observing System with a coupled chemistry–climate model, GEOS-CCM, and the Copernicus Atmosphere Monitoring Service, CAMS, reanalysis). The main difference between IASI-r and IASI-a concerns the treatment of IASI observations, with radiances being assimilated directly in IASI-r instead of intermediate Level 2 O3 retrievals. IASI-r is found to correct major issues with IASI-a, such as the neutral or negative impact of IASI assimilation in the extra-tropics and the presence of residual biases in the tropics. IASI-r also compares relatively well to the CAMS reanalysis, which is based on a more comprehensive chemical mechanism and the assimilation of several ultraviolet (UV) and microwave measurements.

Study on information content of light field on the object surface under various coherent states illumination

A novel approach for the measurement of information content of light field on the object surface illuminated by various coherent states source based on the statistical optics theory and Shannon’s information theory has been proposed. Firstly, we propose that the information content of light field on the object surface can be regarded as the product of the spacial freedom degrees of the object surface itself and that of the illuminating light field arriving at the object surface. Then, calculate the distribution of complex degree of coherence on the object surface under various coherent states illumination and then obtain the number of uncorrelated areas of light field on the object surface which can be used to determine the number of freedom degree of the light field. At the same time, taking into account the structure of the object itself, the freedom degree of the light field on the object surface in completely coherent, partially coherent and incoherent illumination are derived respectively.The specific algorithms for the information content of the light field illuminated by a 1D linear incoherent light source and uniform quasi monochromatic incoherent surface light source with arbitrary shape are also presented.

Information Content Measurement of ESG Factors via Entropy and Its Impact on Society and Security

We conducted a singular and sectoral vulnerability assessment of ESG factors of Dow-30-listed companies by applying the entropy weight method and analyzing each ESG factor’s information contribution to the overall ESG disclosure score. By reducing information entropy information, weaknesses in the structure of a socio-technological system can be identified and improved. The relative information gain of each indicator improves proportionally to the reduction in entropy. The social pillar contains the most crucial information, followed by the environmental and governance pillars, relative to each other. The difference between the social and economic pillars was found to be statistically not significant, while the differences between the social pillar, respective to the economic and governance pillars were statistically significant. This suggests noisy information content of the governance pillar, indicating improvement potential in governance messaging. Moreover, we found that companies with lean and flexible governance structures are more likely to convey information content better. We also discuss the impact of ESG measures on society and security.

Minimal Design Principles for Icosahedral Virus Capsids

The geometrical structures of single- and multiple-shell icosahedral virus capsids are reproduced as the targets that minimize the cost corresponding to relatively simple design functions. Capsid subunits are first identified as building blocks at a given coarse-grained scale and then represented in these functions as point particles located on an appropriate number of concentric spherical surfaces. Minimal design cost is assigned to optimal spherical packings of the particles. The cost functions are inspired by the packings favored for the Thomson problem, which minimize the electrostatic potential energy between identical charged particles. In some cases, icosahedral symmetry constraints are incorporated as external fields acting on the particles. The simplest cost functions can be obtained by separating particles in disjoint nonequivalent sets with distinct interactions, or by introducing interacting holes (the absence of particles). These functions can be adapted to reproduce any capsid structure found in real viruses. Structures absent in Nature require significantly more complex designs. Measures of information content and complexity are assigned to both the cost functions and the capsid geometries. In terms of these measures, icosahedral structures and the corresponding cost functions are the simplest solutions.

Information content differentiates enhancers from silencers in mouse photoreceptors.

Enhancers and silencers often depend on the same transcription factors (TFs) and are conflated in genomic assays of TF binding or chromatin state. To identify sequence features that distinguish enhancers and silencers, we assayed massively parallel reporter libraries of genomic sequences targeted by the photoreceptor TF cone-rod homeobox (CRX) in mouse retinas. Both enhancers and silencers contain more TF motifs than inactive sequences, but relative to silencers, enhancers contain motifs from a more diverse collection of TFs. We developed a measure of information content that describes the number and diversity of motifs in a sequence and found that, while both enhancers and silencers depend on CRX motifs, enhancers have higher information content. The ability of information content to distinguish enhancers and silencers targeted by the same TF illustrates how motif context determines the activity of cis-regulatory sequences.

The Limits of Pairwise Correlation to Model the Joint Entropy. Comment on Nguyen Thi Thanh et al. Entropy Correlation and Its Impacts on Data Aggregation in a Wireless Sensor Network. Sensors 2018, 18, 3118

Information theory is a unifying mathematical theory to measure information content, which is key for research in cryptography, statistical physics, and quantum computing [...].

IMPROVING THE INFORMATIVITY OF TRAJECTORY MEASUREMENTS FOR GLONASS EPHEMERIS AND BALLISTIC SUPPORT

Possibilities of the instrumental variables method using to improve the matrix properties of algebraic equations system are shown in the article. The problem of trajectory measurements from a network of ground-based, no-demand measuring stations using GLONASS navigation satellites is considered. The need to increase information content of trajectory measurements is especially important for trajectory measurements in the southern hemisphere of the Earth with a small number of measuring stations. The numerical experiment results of trajectory measurements of the navigation satellite movement from two and three request-free measuring stations with geometric constraints with use of simulation modeling are presented. The possibility of the measurements’ information content increasing from such base stations using the instrumental variables method is shown. Comparison of an indicator of the trajectory measurements informativity is made according to the degree of the matrix conditionality of the algebraic equations system being solved. Based on the results of the numerical experiment, it is concluded that it is possible to increase the information content of trajectory measurements from a network of non-query measuring stations with geometric constraints, involving the method of instrumental variables in processing. A quantitative estimation of the increase in information content was obtained in the form of a decrease in the condition number of the system matrix being solved by more than one order of magnitude. In the future, the research is predicted on the possibility of the trajectory measurements informativeness increasing for various basic functions used as instrumental variables, and their effect on the geometric constraints reducing an uneven network of measuring stations.

Do Analysts’ Social Ties Affect the Textual Information in Their Reports? Evidence from China

ABSTRACT We develop insights into how analysts’ social ties affect their objectivity and the information content of reports, based on quantitative measures of social ties and textual information content. Using a sample ranges from January 2006 to December 2016 in China, we show that with wide social ties to fund managers, analysts’ ability to burnish their reputation with informative reports and to achieve career success with optimistic stock ratings is enhanced. Further evidence indicates that the trade-off between reputation and career success is dynamic. Specifically, after being elected as New Fortune stars, analysts attach more importance on textual information and are less subjective on stock ratings. These findings are robust across various robustness tests. Overall, our evidence highlights the role of social ties in the information-dissemination process in China A-share stock markets from the perspective of analysts and fund managers.

Disentangling the Effects of Uncertainty, Monetary Policy and Leverage Shocks on the Economy*

AbstractIn this paper, we assess the information content and predictive ability of various risk and uncertainty measures in predicting various measures of real economic activity as well as undertake a comparative analysis of the relative importance of uncertainty, monetary policy and leverage shocks in the macroeconomic business cycle. We find that the macroeconomic uncertainty index and the Chicago Fed national financial conditions risk index have the strongest predictive relationship with economic activities. Also, in the context of a Bayesian monetary structural vector autoregressive, we use the penalty function approach to a sequential identification of uncertainty, monetary policy and leverage shocks, and find that uncertainty shocks are a relatively more important source of variations in the economy than traditional monetary policy shocks. However, monetary policy shocks still outperform uncertainty shocks in explaining inflation dynamics.

Wide-area security assessment based on informative variables of power system

In a power system, lack of efficacious information about operating conditions is a key challenge for power network operator. Especially, when this weakness coincides with increasing consumers' dependency on electric power, operating in adjacent of security constraints, and also occurrence of critical disturbances in the power system. In these circumstances, the role of secure operation, which contains High Information Content (HIC) about the operating space, becomes more prominent. However, power system variables of the operating space are monitored by dispatcher using Phasor Measurement Units (PMUs). Therefore, by identification of the informative variables, the power system can be operated in a low-dimensional space of security region. Indeed, by extraction of hidden information based on Entropy theory, descriptor variables of security region are recognizable. For this purpose, behavior of power system loadability is studied in the face of stressing power network in a low dimensional D-parametric space. Then, the informative variables are accessible using the measurement of information content of the power system variables in the operating space. Thus, the power system operator just by tracking a few number of descriptor variables guarantees a safe operation of power system even by occurrence of critical disturbances.

Conceptual model of radio engineering system of trajectory measurements based on technology of formation of continuous measuring scales

When creating a ground-based complex of trajectory measurements for a space geodetic system, the task of increasing the accuracy of measurements and information content of the signals used is urgent. The article proposes a conceptual model of a radio-technical system of trajectory measurements, based on the technology of forming non-multiple measuring scales. Approaches to the creation of interrogated and non-interrogated radio engineering systems that implement code and phase multiscale measurements are determined. A measurement method using phase-shift keyed signals with quadrature multiplexing is proposed. The possibility of using the technology of forming non-multiple scales in the ground-based complex of trajectory measurements of the space geodetic system is considered. Estimates of the information content of measurements are given, based on the technology of forming nonmultiple scales, which makes it possible to improve the accuracy and increase the range of unambiguous range measurements.

Predicting Cognitive Impairment in Cerebrovascular Disease Using Spoken Discourse Production

Purpose: Dementia due to cerebrovascular disease (CVD) is common. Detecting early cognitive decline in CVD is critical because addressing risk factors may slow or prevent dementia. This study used a multidomain discourse analysis approach to determine the spoken language signature of CVD-related cognitive impairment. Method: Spoken language and neuropsychological assessment data were collected prospectively from 157 participants with CVD as part of the Ontario Neurodegenerative Disease Research Initiative, a longitudinal, observational study of neurodegenerative disease. Participants were categorized as impaired (n = 92) or cognitively normal for age (n = 65) based on neuropsychology criteria. Spoken language samples were transcribed orthographically and annotated for 13 discourse features, across five domains. Discriminant function analyses were used to determine a minimum set of discourse variables, and their estimated weights, for maximizing diagnostic group separation. Results: The optimal discriminant function that included 10 of 13 discourse measures correctly classified 78.3% of original cases (69.4% cross-validated cases) with a sensitivity of 77.2% and specificity of 80.0%. Conclusion: Spoken discourse appears to be a sensitive measure for detecting cognitive impairment in CVD with measures of productivity, information content, and information efficiency heavily weighted in the final algorithm.

Registration of the dispersed composition of aerosol media by the holographic method

The article describes a device based on the holographic method for measuring the parameters of dispersed aerosols. In the proposed device, the measured particle is irradiated with two beams perpendicular to the main radiation axis, while the resulting holographic image in each of the projections gives an increased amount of information (in contrast to existing solutions) about the parameters of the particles. The information obtained is processed layer by layer using digital holography methods to form a volumetric representation of the aerosol under study, which significantly increases the information content of measurements in comparison with existing devices. Methods and algorithms for layer-by-layer processing of the obtained holographic images are described, which make it possible to reconstruct the parameters of aerosols of complex shapes. The design of the device and an algorithm for layer-by-layer reconstruction of aerosol images are proposed.

Data-Driven, Visual Framework for the Characterization of Aphasias Across Stroke, Post-resective, and Neurodegenerative Disorders Over Time.

Aphasia classifications and specialized language batteries differ across the fields of neurodegenerative disorders and lesional brain injuries, resulting in difficult comparisons of language deficits across etiologies. In this study, we present a simplified framework, in which a widely-used aphasia battery captures clinical clusters across disease etiologies and provides a quantitative and visual method to characterize and track patients over time. The framework is used to evaluate populations representing three disease etiologies: stroke, primary progressive aphasia (PPA), and post-operative aphasia. A total of 330 patients across three populations with cerebral injury leading to aphasia were investigated, including 76 patients with stroke, 107 patients meeting criteria for PPA, and 147 patients following left hemispheric resective surgery. Western Aphasia Battery (WAB) measures (Information Content, Fluency, answering Yes/No questions, Auditory Word Recognition, Sequential Commands, and Repetition) were collected across the three populations and analyzed to develop a multi-dimensional aphasia model using dimensionality reduction techniques. Two orthogonal dimensions were found to explain 87% of the variance across aphasia phenotypes and three disease etiologies. The first dimension reflects shared weighting across aphasia subscores and correlated with aphasia severity. The second dimension incorporates fluency and comprehension, thereby separating Wernicke's from Broca's aphasia, and the non-fluent/agrammatic from semantic PPA variants. Clusters representing clinical classifications, including late PPA presentations, were preserved within the two-dimensional space. Early PPA presentations were not classifiable, as specialized batteries are needed for phenotyping. Longitudinal data was further used to visualize the trajectory of aphasias during recovery or disease progression, including the rapid recovery of post-operative aphasic patients. This method has implications for the conceptualization of aphasia as a spectrum disorder across different disease etiology and may serve as a framework to track the trajectories of aphasia progression and recovery.

Improvement of Statistical Performance of Ordinal Multiscale Entropy Techniques Using Refined Composite Downsampling Permutation Entropy.

Multiscale Permutation Entropy (MPE) analysis is a powerful ordinal tool in the measurement of information content of time series. MPE refinements, such as Composite MPE (cMPE) and Refined Composite MPE (rcMPE), greatly increase the precision of the entropy estimation by modifying the original method. Nonetheless, these techniques have only been proposed as algorithms, and are yet to be described from the theoretical perspective. Therefore, the purpose of this article is two-fold. First, we develop the statistical theory behind cMPE and rcMPE. Second, we propose an alternative method, Refined Composite Downsampling Permutation Entropy (rcDPE) to further increase the entropy estimation’s precision. Although cMPE and rcMPE outperform MPE when applied on uncorrelated noise, the results are higher than our predictions due to inherent redundancies found in the composite algorithms. The rcDPE method, on the other hand, not only conforms to our theoretical predictions, but also greatly improves over the other methods, showing the smallest bias and variance. By using MPE, rcMPE and rcDPE to classify faults in bearing vibration signals, rcDPE outperforms the multiscaling methods, enhancing the difference between faulty and non-faulty signals, provided we apply a proper anti-aliasing low-pass filter at each time scale.

Разработка и исследование профилографа для измерения отклонений формы поверхности изделий методом лазерного спиралевидного сканирования

Introduction. The paper deals with the development of a Profile recorder and measurement of deviations in the shape of the surface of products by laser spiral scanning. Analysis of the scientific literature shows that at present, the issues of monitoring and evaluating deviations in the shape of the surface of products require further research, since the use of well-known devices and methods does not always provide the necessary accuracy, manufacturability and sufficient information content of measurements. The research urgency is caused by the fact that existing methods of measuring form deviations of the surfaces does not allow to define a set of parameters with the required accuracy and submit it to two-dimensional and three-dimensional form. Objective: to develop a new method for evaluating a three-dimensional profile by implementing the method of laser spiral scanning and study the Profile recorder to improve the accuracy and productivity of measuring deviations in the shape of the product surface. Methods. The paper proposes a new method for evaluating a three-dimensional surface profile in order to directly determine the shape of the surface of products, to control the quality of the surface of products, regardless of its location. To implement the method, a Profile recorder of an original design is developed and investigated, which provides measurement of two parameters along the Archimedean spiral. Optimization of the design and the method of presenting information for measuring deviations in the shape of the surface of products are performed. Results and discussion. A method of statistical estimation of equations for describing the shape of metal surfaces based on the use of classical laws is proposed. In the case of a flat surface, deviations from flatness are evaluated: undulation, warping, twisting, convexity, concavity, curvature, etc. A Profile recorder is developed to implement the proposed method. The automated mechatronic device and the proposed method are tested on corrugated surfaces. Various equations obtained as a result of statistical processing were compared with each other, and the equation with the highest coefficient of determination is selected. The Profile recorder in Cartesian coordinates is studied in order to obtain reliable and accurate data for estimating shape deviations. The values of the deflection and the size of the corrugation along the height of the C-9 corrugated sheet are determined by laser spiral scanning.

From Qualitative to Quantitative Analysis of Activity and Property Landscapes.

Activity or, more generally, property landscapes (PLs) have been considered as an attractive way to visualize and explore structure-property relationships (SPRs) contained in large data sets of chemical compounds. For graphical analysis, three-dimensional representations reminiscent of natural landscapes are particularly intuitive. So far, the use of such landscape models has essentially been confined to qualitative assessment. We describe recent efforts to analyze PLs in a more quantitative manner, which make it possible to calculate topographical similarity values for comparison of landscape models as a measure of relative SPR information content.

The Expectancy Dynamics of Anti-Tonal Twelve-Tone Rows: A Commentary and Reanalysis of von Hippel & Huron (2020)

This commentary provides two methodological expansions of von Hippel and Huron's (2020) empirical report on (anti-)tonality in twelve-tone rows by Arnold Schoenberg, Anton Webern, and Alban Berg. First, motivated by the theoretical importance of equality between all pitch classes in twelve-tone music, a full replication of their findings of "anti-tonality" in rows by Schoenberg and Webern is offered using a revised tonal fit measure which is not biased towards row-initial and row-final sub-segments. Second, motivated by a long-standing debate in music cognition research between distributional and sequential/dynamic tonality concepts, information-theoretic measures of entropy and information content are estimated by a computational model and pitted against distributional tonal fit measures. Whereas Schoenberg's rows are characterized by low distributional tonal fit, but do not strongly capitalize on tonal expectancy dynamics, Berg's rows exhibit tonal traits in terms of low unexpectedness, and Webern's rows achieve anti-tonal traits by combining high uncertainty and low unexpectedness through prominent use of the semitone interval. This analysis offers a complementary–and arguably more nuanced–picture of dodecaphonic compositional practice.

Information content of liquidity and volatility measures

This paper aims to compare the mutual information shared by various liquidity and volatility estimators within each group separately. Our sample covers forty one blue-chip companies from the Warsaw Stock Exchange. In terms of their information content, volatility measures are much more coherent, while liquidity ones are more dispersed. The Garman–Klass volatility estimator seems to be the broadest measure of volatility, while Amihud illiquidity and Volatility over volume share the highest amount of mutual information among liquidity proxies. The latter proxy shares approximately the same amount of information with both volatility estimates and liquidity proxies. The possibility to forecast volatility or liquidity, measured by the transfer entropy, with the help of the other volatility or liquidity proxies is limited.

Entropic Ranks: A Methodology for Enhanced, Threshold-Free, Information-Rich Data Partition and Interpretation

Background: Here, we propose a threshold-free selection method for the identification of differentially expressed features based on robust, non-parametric statistics, ensuring independence from the statistical distribution properties and broad applicability. Such methods could adapt to different initial data distributions, contrary to statistical techniques, based on fixed thresholds. This work aims to propose a methodology, which automates and standardizes the statistical selection, through the utilization of established measures like that of entropy, already used in information retrieval from large biomedical datasets, thus departing from classical fixed-threshold based methods, relying in arbitrary p-value and fold change values as selection criteria, whose efficacy also depends on degree of conformity to parametric distributions,. Methods: Our work extends the rank product (RP) methodology with a neutral selection method of high information-extraction capacity. We introduce the calculation of the RP entropy of the distribution, to isolate the features of interest by their contribution to its information content. Goal is a methodology of threshold-free identification of the differentially expressed features, which are highly informative about the phenomenon under study. Conclusions: Applying the proposed method on microarray (transcriptomic and DNA methylation) and RNAseq count data of varying sizes and noise presence, we observe robust convergence for the different parameterizations to stable cutoff points. Functional analysis through BioInfoMiner and EnrichR was used to evaluate the information potency of the resulting feature lists. Overall, the derived functional terms provide a systemic description highly compatible with the results of traditional statistical hypothesis testing techniques. The methodology behaves consistently across different data types. The feature lists are compact and rich in information, indicating phenotypic aspects specific to the tissue and biological phenomenon investigated. Selection by information content measures efficiently addresses problems, emerging from arbitrary thresh-holding, thus facilitating the full automation of the analysis.