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This article is devoted to the study of psychological predictors of students’ informational behavior and their peculiarities of over-coming stressful situations. The article reveals the relevance of studying this problem, the degree of study of the topic of informational behavior in various scientific fields. The necessity of studying the motivational basis of informational behavior is substantiated; the analysis of diagnostic approaches to the study of informational behavior is given. The article presents the author’s approach to studying the motivational basis of informational behavior and reveals two groups of informational behavior strategies - normative and risky. The empirical part of the article presents an analysis of the conducted research for the study of psychological predictors of students’ informational behavior in the Internet. It was revealed that the normative strategy of informational behavior “Internet as a motivating force” has the largest number of correlations with coping strategies and indicators of resilience. The results obtained can prove the adaptability of students who actively use the socially oriented strategy “Internet as a motivating force” and the level of their resilience.

The purpose of this study is investigating the role of accounting information uncertainty on investors’ reaction to earnings announcement, as well as investors’ reaction to good earnings news. For doing so, a sample of 162 listed companies in the Tehran Stock Exchange in the period 1384 to 1394 have been selected. Three criteria including information quality, cash flows’ uncertainty (traditional and matched- firm method) were used for calculating the information uncertainty. The results of hypotheses test indicated when there is high information uncertainty (compared to low uncertainty), investors’ reaction to earnings announcement is less. Also, under high uncertainty, investors display less reaction to good news that this response is consistent with the conservatism approach.

After the development of behavioral financial theory, the experimental literature in this domain has been exclusively oriented toward investigating the relationship between investors’ inclinations and variations of stocks' price. There hasn’t been any independent research on investigating factors contributing to behavioral mistakes of investors and how they can be moderated. Thus, the purpose of this paper is to investigate the effect of accounting information quality and information uncertainty on investor sentiment. To achieve this goal, the data of 560 companies during the financial periods from 2009 to 2016 is used. The results of this study showed that accounting information quality and lack of confidence in information have a significant negative and significant positive relationship with investors’ inclinations. Furthermore, the results showed that increase in the quality of accounting information and reduction of confidence in information does reduce investors’ affective behavior in racing stocks. In addition, the results of analyses showed that investors are inclined more toward more optimistic predictions for stock price with lower information quality and confidence when investors are more optimistic.

The article presents the simulation model, which, unlike available ones, considers possibility of reconfiguration of metrological complexes, as well as information uncertainty on the receipt of measurement funds for metrological service.

The physical-chemical monitoring of vast oceanic areas aims at assessing the status and evolution of the environmental resource for its exploration, protection and/or better understanding. However, the interpretation of monitoring data is affected by ocean seasonality and heterogeneity, and by the quality of sampling and characterization tools used to study the environment. All these factors contribute to the uncertainty of collected information that should be expressed in determined parameter values or trends. A trend of a studied parameter quantified by values difference is significant if the observed absolute value of the difference is larger than their expanded uncertainty. The correlation of studied parameters, useful for their interpretation, is equality affected by the mentioned sources of uncertainty. This work describes the metrologically sound evaluation of trends and correlations of physicochemical parameters of vast oceanic areas where all uncertainty sources affecting the information are considered by simulating their complex impact by the Monte Carlo Method. The described methodology was successfully used to study the impact of summer upwelling in an 800 km 2 coastal area offshore two large cities in Portugal. Nutrients, conductivity, salinity and temperature trends and correlations are distinguished from system heterogeneity, sampling and sample analysis uncertainty for a 99% confidence level., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Dong Yeong Shin,1 Robert Weech-Maldonado,2 Jongwha Chang3 1Department of Public Health Sciences, New Mexico State University, Las Cruces, NM, USA; 2Department of Health Services Administration, University of Alabama, Birmingham, AL, USA; 3Department of Pharmaceutical Sciences., University of Texas, El Paso, TX, USACorrespondence: Jongwha Chang Department of Pharmaceutical SciencesSchool of Pharmacy, University of Texas at El Paso, 500 W. University Ave, El Paso, TX 79968, USATel +1 915-747-8241Email jchang@utep.eduPurpose: Due to a limited number of studies with generalizable findings on the relationships between market conditions and RN staffing levels in hospitals, this study examined such relationships employing a longitudinal design with a representative national sample.Materials and Methods: We used longitudinal panel datasets from 2006 to 2010, drawn from various datasets including the American Hospital Association Annual Survey Database and the Area Health Resource File. A random-effects linear regression model was used to measure the influence of market conditions on RN staffing levels.Results: The results of this study showed that market conditions were significantly associated with RN staffing levels in hospitals. First, an increase in per capita income and being located in urban rather than rural areas were associated with a greater number of RNs per 1,000 inpatient days and a higher ratio of RNs to LPNs and nursing aides. In addition, an increase in the number of physician specialists was associated with an increase in the number of RNs per 1,000 inpatient days. Second, an increase in Medicare HMO penetration in the environment was related to an increase in the RNs to LPNs and nursing aides ratio. Lastly, an increase in market competition was associated with an increase in the number RNs per 1,000 inpatient days and the ratio of RNs to LPNs and nursing aides.Conclusion: The findings of this study suggest that staffing decision makers in hospitals should consider how to best align their RN staffing levels with their operating environment. In addition, health policy makers may improve the levels the RN supply in communities that needs more RNs by modulating external environmental forces (eg, specialist resources) that influence RN staffing levels in hospitals.Keywords: market condition, external environment, munificence, dynamism, complexity, RN staffing, hospital

This case report describes entropy based on statistics of the novel coronavirus infection in the Russian Federation. Entropy (in bits) determined on the basis of the ratio of patients with clinical manifestations of the disease and asymptomatic carrier state, increased from 0.7219 by April 1, 2020, when the ratio of such patients was 4/5 to 1/5, to 0.8813 by April 14, 2020, when the ratio of the two groups of patients was 7/10 to 3/10. On May 3, 2020, the ratio of the two groups leveled off, reaching ½ to ½, so the entropy was 1.0000. An analysis of the data from April 19, 2020 to June 1, 2020 allowed us to clarify the average proportion between patients with and without symptoms, which is 14/25 to 11/25 with a certain bias towards patients with clinical manifestations of the novel coronavirus infection, and the entropy for this ratio is 0.9896. We found a transformation of entropy of the novel coronavirus infection which is explained by different proportions of patients with and without symptoms of the disease.

This study investigates the relation between information uncertainty and investors’ under reaction, in other words, whether information uncertainty results in higher investors' under-reaction which is one of the abnormalities of efficient capital market. The sample includes 106 firms listed in Tehran Stock Exchange over the period from 2007 to 2011. We used a sample of 106 companies to test hypotheses. In this research, we used abnormal return volatility, earning forecast dispersion, and earning forecast error as three proxies for measuring information uncertainty. These three criterions are weighted by using factor analysis method and applied as one single factor. We used Equality of Tow Means Test for statistical analysis of research hypothesis. The results indicate that information uncertainty has a positive relationship with investors’ under-reaction.

The cognitive control network (CCN) that comprises regions of the frontoparietal network, the cingulo-opercular network, and other sub-cortical regions as core structures is commonly activated by events with an increase in information uncertainty. However, it is not clear whether this CCN activation is associated with both information entropy that represents the information conveyed by the context formed by a sequence of events and the surprise that quantifies the information conveyed by a specific type of event in the context. We manipulated entropy and surprise in this functional magnetic resonance imaging study by varying the probability of occurrence of two types of events in both the visual and auditory modalities and measured brain response as a function of entropy and surprise. We found that activation in regions of the CCN increased as a function of entropy and surprise in both the visual and auditory tasks. The frontoparietal network and additional structures in the CCN mediated the relationship between these information measures and behavioral response. These results suggest that the CCN is a high-level modality-general neural entity for the control of the processing of information conveyed by both context and event.