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Objective. The goal is to consider the phenomenon of value-affective polarization of large social groups, to analyze the methodological foundations of the study of this phenomenon in Russia and abroad, as well as some empirical results in the study conducted by the authors. Background. Due to the global changes taking place in the world in the context of rapid scientific and technological progress, as well as the emergence of new means of information exchange, conditions have arisen in many countries, including Russia, for the manifestation of the phenomenon of value-affective polarization of the population. The study of this phenomenon is an extremely urgent problem, since it allows not only to describe the psychological mechanisms of political confrontation in society, but also to develop approaches to assess its development and reduce negative consequences. Study design. The article examines the attitude of respondents with different types of value polarization to the most significant political events in Russia against the background of stressful social events, such as the conduct of a special military operation and partial military mobilization. Participants. Russian sample: 548 people with higher education (60% women, 40% men), aged 21 to 47 years (M = 34,8; SD = 8,6). Measurements. Developed on the basis of the IAT (Implicit Association Test) test, a methodology that evaluates implicit (hidden or unconscious) political attitudes (IPA). The Big 5 methodology and questionnaire for assessing current events in Russia and abroad and the likelihood of their occurrence in the future. Results. A connection has been established between the results of the IPU and the direct answers of the respondents to the questionnaire questions. After the announcement of partial military mobilization in both polar subgroups ("loyal" and "disloyal"), the number of people who do not trust the Russian media, which cover events taking place on the territory of Ukraine, increased. At the same time, the level of patriotic sentiment among the population as a whole has increased. It is shown that as polarization develops, there is a tendency to irrationality of judgments of representatives of opposing parties. After the announcement of the SMO, the opinions of the respondents of the polar groups on some issues either did not change, or became more solid and pronounced. Conclusions. Currently, there is no reason to believe that the value polarization of the Russian population has a pronounced tendency to transform into affective polarization, but such a danger exists. The problem discussed in the article has not been sufficiently studied in Russian social and political psychology, however, the development of an appropriate methodology and theory, as well as methods and techniques, will allow us to study this phenomenon more deeply and effectively.

Introduction. Meaning-in-life orientations and self-reflection are important indicators of the regulation of personal meanings. In a modern rapidly changing society, individuals do not fully manage their lives due to the influence of various uncertainty factors. The COVID-19 pandemic that began in early 2020 and swept across the world is considered a global factor of uncertainty. The increased uncertainty of life associated with the pandemic is an additional stressor. This paper represents a first effort in obtaining empirical data on gender characteristics of teachers’ meaning-based regulation in the context of the coronavirus pandemic. This paper reports the results of an empirical study of differences in meaning-in-life orientations and self-reflection among teachers before and during the pandemic as different conditions of information uncertainty in their lives. Methods. The study was conducted among female teachers of secondary schools in the Rostov region in March 2017 (n = 53) and in October 2020 (n = 43), i.e. before and during the pandemic, which can be considered different conditions of information uncertainty in their lives. We used the following psychological assessment tools: (a) the Meaning-in-Life Orientations test by D. A. Leont'ev and (b) the Self-reflection Questionnaire by I. A. Stetsenko. Results. We observed an increase in all means of both tests during the pandemic, compared to the pre-pandemic values. Differences in all parameters are statistically significant (according to the Mann–Whitney U test). Discussion. Our findings indicate that the pandemic represents a surmountable stressor for the homogeneous acmeological category of female teachers surveyed in this study. Information uncertainty contributes to constructive restructuring of the processes of meaning-based regulation and psychological adaptation, which leads to an increase in the level of meaningfulness of life orientations and self-reflection among the respondents.

Forests worldwide are experiencing increasingly intense biotic disturbances; however, assessing impacts of these disturbances is challenging due to the diverse range of organisms involved and the complex interactions among them. This particularly applies to invasive species, which can greatly alter ecological processes in their invaded territories. Here we focus on the pine wood nematode (PWN, Bursaphelenchus xylophilus), an invasive pathogen that has caused extensive mortality of pines in East Asia and more recently has invaded southern Europe. It is expected to expand its range into continental Europe with heavy impacts possible.Given the unknown dynamics of PWN in continental Europe, we reviewed laboratory and field experiments conducted in Asia and southern Europe to parameterize the main components of PWN biology and host-pathogen interactions in the Biotic Disturbance Engine (BITE), a model designed to implement a variety of forest biotic agents, from fungi to large herbivores. To simulate dynamically changing host availability and conditions, BITE was coupled with the forest landscape model iLand. The potential impacts of introducing PWN were assessed in a Central European forest landscape (40,928 ​ha), likely within PWN’s reach in future decades.A parameter sensitivity analysis indicated a substantial influence of factors related to dispersal, colonization, and vegetation impact, whereas parameters related to population growth manifested a minor effect. Selection of different assumptions about biological processes resulted in differential timing and size of the main mortality wave, eliminating 40%–95% of pine trees within 100 years post-introduction, with a maximum annual carbon loss between 1.3% and 4.2%. PWN-induced tree mortality reduced the Gross Primary Productivity, increased heterotrophic respiration, and generated a distinct legacy sink effect in the recovery period. This assessment has corroborated the ecological plausibility of the simulated dynamics and highlighted the need for new strategies to navigate the substantial uncertainty in the agent’s biology and population dynamics.

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Abstract Background Individuals’ stress in responding to the current COVID-19 pandemic may be exacerbated by information uncertainty driven by inconsistent, unverified, and conflicting news from various sources. The current study aims to test if information uncertainty during the COVID-19 outbreak was related to acute stress disorder (ASD) over and above other psychosocial stressors. Methods An anonymous online survey was conducted with 7800 college students throughout China from January 31 through February 11, 2020. Existing scales were modified to measure ASD and six potential stressors including information uncertainty during the COVID-19 outbreak. Hierarchical regression analysis was conducted to assess the unique association of information uncertainty with ASD. To minimize the effect of large sample size and also to get a sense of whether the effects of information uncertainty were similar to people at the center of the epidemic, we repeated the hierarchical regression among 10% of the students who were randomly selected from the entire sample (“10% random sample”; n = 780) and 226 students from Hubei Province where the outbreak started. Results Information uncertainty was highly prevalent among the respondents (64%). It was significantly associated with ASD beyond other key variables and potential stressors across three samples. In the hierarchical regression among the entire sample, demographic variables accounted for 9.4% of the variance in ASD. The other five stressors added 5.1% of the variance. The information uncertainty (β = .159; p

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.

National differences in uncertainty, inequality, and trust have been accentuated by COVID-19. There are indications that the pandemic has impacted societies characterized by high uncertainty, inequality, and low trust harder than societies characterized by low uncertainty, equality, and high trust. This study investigates differential response strategies to COVID-19 as reflected in news media of two otherwise similar low uncertainty societies: Denmark and Sweden. The comparison is made using a recent approach to information dynamics in unstructured data. The main findings are that the news dynamics generally mirror public-health policies, capture fundamental socio-cultural variables related to uncertainty and trust, and may provide a measure of societal uncertainty. The findings can provide insights into evolutionary trajectories of decision-making under high uncertainty and, from a methodological level, be used to develop a media-based index of uncertainty and trust.

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.

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.

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

As the negative environmental impacts of transportation systems become more severe, governments and environmental groups are seeking more sustainable transportation options, such as replacing fuel-powered vehicles with electric vehicles and expanding public transportation systems to reduce the number of people driving on their own, in order to reduce the environmental impacts of transportation systems. At present, the rapid expansion of public transportation systems is not an easy task and requires a long period of time to plan for expansion and construction, so people are increasingly looking to find means of transportation that meet sustainable conditions as solutions. In this context, electric bicycles are one of the solutions that people can choose, with benefits such as energy saving, carbon reduction, effective air pollution reduction, and simple and labor-saving riding. However, in Taiwan, despite the many benefits of electric bicycles, their popularity is not high. Therefore, this study focuses on the factors that affect the purchase of electric bicycles in Taiwan. The Influential Network Relation Map (INRM) generated by the Z-based Decision-making Trial and Evaluation Laboratory (Z-DEMATEL) technique is used to describe the influence relationships among the factors and to establish the key evaluation criteria of electric bicycle purchase intention. The results indicate that vehicle price, safety, motor performance, battery life, and battery durability are the most important factors in purchasing electric bicycles. Furthermore, the power of motor is considered as the factor that most significantly affects other criteria, while safety and price are most likely to be affected by other criteria. This study has contributed to academia and industry, for the dependency weights of these factors are set to provide a scientific and systematic way to show how consumers think in the decision-making process and to provide more reliable information and management implications for the electric bicycle industry.

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.

Information uncertainty has been an old topic in finance literature. Information uncertainty means ambiguity about a firm’s fundamental value, which may arise from two conventional sources: 1) characteristics of the business or industry, and 2) the company’s disclosure policy. The first source related to growth options and second source related to information asymmetry. From investors’ perspective the mechanisms and outcomes of every source are quite different. In this research we use from earning forecast dispersion as a proxy for measuring information uncertainty. We use stock turnover and price impact as proxies for information asymmetry. To control firm’s growth options, we use firm age, market-to-book ratio, and capital expenditure over total assets and Tobin’s Q. We use panel data regression model to analyze information. Our results indicate that information uncertainty has a positive relationship with information asymmetry and growth options.

This study investigated the effect of income smoothing on information uncertainty, stock return and cost of equity. For income smoothing two indices are used: total accruals smoothing and discretionary accruals smoothing. With accurate study of literature we hypothesized three possibilities and selected 111 companies listed in Tehran stock exchange as our survey for a period of three years, 1385-1387. In this study, Ohlson and Juttner- Narouth models were used to collect data. Our hypotheses were analyzed using multiple liner regressions and F and T tests. Our results showed that income smoothing caused reduction in information uncertainty in selected companies. It also showed that when fluctuations related to unexpected stock earnings are controlled, income smoothing 5 days before and after earnings announcement has no effect on companies' stock return. Finally our data showed that income smoothing has no effect on cost of equity.

Reliability-based multiobjective optimization (RBMO) is a method that integrates multiobjective optimization with a reliability analysis. The method is useful for a large or complicated design problem such as aerospace structure design. Reliability analysis generally requires the probabilistic distribution parameters of random variables such as the mean and standard deviation. However, for an actual design problem, the probabilistic parameters are sometimes estimated with insufficient accuracy because of a limited number of experiments. In that case, the uncertainty in the distribution parameter is not negligible. This study proposes the evaluation method to estimate the effect of the information uncertainty at first, where the uncertainty is evaluated by using the confidence interval. Some numerical examples illustrates the effectiveness of the proposed method in comparison with a conventional method, Gibbs sampling. Then, the effect of the parameter uncertainty on the RBMO is illustrated through numerical examples. The RBMO problem is formulated by using the satisficing trade-off method (STOM), where the multiobjective optimization problem is transformed into the equivalent single-objective optimization method. For the reliability-based design optimization, a modified SLSV (single-loop-single-vector) method is adopted for the computational efficiency. The effects of the parameter uncertainty on the selected Pareto solutions according to the aspiration level are investigated by using the confidence intervals of the Pareto solutions.

Purpose. The article highlights development of the methodological basis for simulation the processes of cars accumulation in solving operational planning problems under conditions of initial information uncertainty for assessing the sustainability of the adopted planning scenario and calculating the associated technological risks. Methodology. The solution of the problem under investigation is based on the use of general scientific approaches, the apparatus of probability theory and the theory of fuzzy sets. To achieve this purpose, the factors influencing the entropy of operational plans are systematized. It is established that when planning the operational work of railway stations, sections and nodes, the most significant factors that cause uncertainty in the initial information are: a) external conditions with respect to the railway ground in question, expressed by the uncertainty of the timing of cars arrivals; b) external, hard-to-identify goals for the functioning of other participants in the logistics chain (primarily customers), expressed by the uncertainty of the completion time with the freight cars. These factors are suggested to be taken into account in automated planning through statistical analysis – the establishment and study of the remaining time (prediction errors). As a result, analytical dependencies are proposed for rational representation of the probability density functions of the time residual distribution in the form of point, piecewise-defined and continuous analytic models. The developed models of cars accumulation, the application of which depends on the identified states of the predicted incoming car flow to the accumulation system, are presented below. In addition, the last proposed model is a general case of models of accumulation processes with an arbitrary level of reliability of the initial information for any structure of the incoming flow of cars. In conclusion, a technique for estimating the results of simulation the cars accumulation was proposed to optimize the transportation process, depending on the chosen criterion. Findings. The developed methodology of simulation of cars accumulation process was reflected in the dynamic models created with the participation of the author and implemented on the Belarusian Railroad on the basis of IAS SMD CT. They are designed to provide operational planning of the transportation process on the basis of methods that allow assessing technological risks. Originality. The innovative component of the work is due to the expansion of existing models of the accumulation of cars for cases of uncertainty of the initial information. Thus, the earlier deterministic models are particular cases of the proposed model. Also, unlike existing ones, the technique allows to take into account the influence of random processes in a complex manner. Due to this, technological risks can be further assessed and the necessary regulatory measures can be implemented promptly. In general, the results obtained by modeling the proposed method allow to improve the quality of output solutions in the system of shift and daily operational planning, increasing the reliability of operational plans. Practical value. To date, there is a favorable opportunity to use the proposed methodology of modeling in existing in the railway transport systems of automated operational planning for operational work, including the optimization of local railways and the solution of a number of urgent tasks of train formation.

This article examines the information environment of ritual-like games. Using tools from library and information science and the cognitive study of religion, it shows that certain key phenomena in games can be modeled as patterns of information and thus examined to a deeper level than before. This is of particular use to game scholars wishing to understand the intricacies of the play experience and to educational simulation/game researchers wanting to develop more efficient role-play based learning. Of particular significance to these so-called liminal games is boundary control, a system of maintaining the necessary fictional reality within the magic circle. Its maintenance results from a shared need to preserve the game-reality intact, an understanding of what is relevant to play, and a heightened reliance on information sources within the game-space. Continual boundary control makes the play function as a self-referential system, where the activity becomes rewarding and meaningful to the players because of the very limitations it contains. This condition, along with the manipulation of uncertainty about information needs during play, is then used to explain processes that take place while being engrossed in/absorbed by playing a ritualistic game as well as in game-based learning in liminal environments. (Contains 6 notes.)

National differences in uncertainty, inequality, and trust have been accentuated by COVID-19. There are indications that the pandemic has impacted societies characterized by high uncertainty, inequality, and low trust harder than societies characterized by low uncertainty, equality, and high trust. This study investigates differential response strategies to COVID-19 as reflected in news media of two otherwise similar low uncertainty societies: Denmark and Sweden. The comparison is made using a recent approach to information dynamics in unstructured data. The main findings are that the news dynamics generally mirror public-health policies, capture fundamental socio-cultural variables related to uncertainty and trust, and may provide a measure of societal uncertainty. The findings can provide insights into evolutionary trajectories of decision-making under high uncertainty and, from a methodological level, be used to develop a media-based index of uncertainty and trust. [ABSTRACT FROM AUTHOR]