Situations Of High Uncertainty Research Articles

Evaluating the robustness of multimodal task load estimation models

Numerous studies have focused on constructing multimodal machine learning models for estimating a person's cognitive load. However, a prevalent limitation is that these models are typically evaluated on data from the same scenario they were trained on. Little attention has been given to their robustness against data distribution shifts, which may occur during deployment. The aim of this paper is to investigate the performance of these models when confronted with a scenario different from the one on which they were trained. For this evaluation, we utilized a dataset encompassing two distinct scenarios: an n-Back test and a driving simulation. We selected a variety of classic machine learning and deep learning architectures, which were further complemented by various fusion techniques. The models were trained on the data from the n-Back task and tested on both scenarios to evaluate their predictive performance. However, the predictive performance alone may not lead to a trustworthy model. Therefore, we looked at the uncertainty estimates of these models. By leveraging these estimates, we can reduce misclassification by resorting to alternative measures in situations of high uncertainty. The findings indicate that late fusion produces stable classification results across the examined models for both scenarios, enhancing robustness compared to feature-based fusion methods. Although a simple logistic regression tends to provide the best predictive performance for n-Back, this is not always the case if the data distribution is shifted. Finally, the predictive performance of individual modalities differs significantly between the two scenarios. This research provides insights into the capabilities and limitations of multimodal machine learning models in handling distribution shifts and identifies which approaches may potentially be suitable for achieving robust results.

COVID-19 Information Platform for Primary Care: Emergence and Development of a Web-based Knowledge Platform in the COVID-19 Pandemic

The SARS-Cov-2 outbreak in the spring of 2020 challenged the health care system, and thus primary care, on an unprecedented scale. Knowledge about the new disease was low, whereas the dynamics of knowledge generation were high and inhomogeneous. A number of new primary care tasks related to the pandemic situation emerged. Guidance in the management of COVID-19 was therefore needed, although robust evidence was not yet available. The information required concerned not only the virus and the new disease COVID-19, but also regulatory requirements and organizational issues. In this situation, a flexible, web-based information tool, easy to update and usable at the point of care, was developed at Karl Landsteiner Private University Krems and put online under the name of "COVID-19: prevention and management in primary care practices" on March 25, 2020. In a retrospective process description, we describe the needs-triggered process of developing and disseminating a practice-based tool to support practicing primary care physicians in a period of high uncertainty with an urgent need for information. Afterwards, we reflect on the learning process from a purely pragmatic to an increasingly structured approach and try to draw conclusions regarding optimization possibilities in terms of creation and dissemination. In situations of high uncertainty combined with an acute need for action and decision-making, there is a significant need for information that is as reliable as possible. Science transfer must be done in such a way that information can be implemented quickly. Dissemination, as always, plays an essential role. Gaps must be accepted. A structured process of quality assurance must be established in parallel. Funds and resources for knowledge transfer should be included in future pandemic plans.

Maximization delays decision-making in acute care nursing

The maximization personality trait refers to the tendency to face decision-making situations along a continuum from exhaustively analysing all the options (maximize) to choosing the one that exceeds a subjective threshold of acceptability (satisfy). Research has revealed the influence of maximizing on decision making, although little is known about its possible role in high risk and high uncertainty situations. A sample of 153 active Spanish nurses, with an average experience of 11 years, completed a maximization questionnaire and responded to written vignettes depicting time-demanding decision making in which three options were offered, representing delayed action, non-action, and immediate action. Two vignettes presented critical situations related to acute care during the COVID-19 pandemic, whilst two vignettes presented non-nursing scenarios. People high in maximization took longer to choose and were more likely to choose non-action. No relationship was found between maximization score and the subjective experience of the person making the choice. Maximization had no significant correlation with years of experience nor perceived expertise. Greater perceived expertise was associated with lower indecision and greater confidence. When participants answered nursing vignettes, they took longer to respond, but chose less delayed action and more immediate action. Our results suggest that maximization plays only a relative role in acute care decision-making in nursing, as compared to contextual variables and expertise. They also support a domain general approach to this personality trait. Findings are consistent with Nibbelink and Reed's Practice-Primed Decision Model for nursing.

Navigating Uncertainty in Clinical Practice: A Structured Approach.

The practice of clinical medicine is imbued with uncertainty. The ways in which clinicians and patients think about, communicate about, and act within situations of heightened uncertainty can have significant implications for the therapeutic alliance and for the trajectory and outcomes of clinical care. Despite this, there is limited guidance about the best methods for physicians to recognize, acknowledge, communicate about, and manage uncertainty in clinical settings. In this paper, we propose a structured approach for discussing and managing uncertainty within the context of a clinician-patient relationship. The approach involves four steps: Recognize, Acknowledge, Partner, and Seek Support (i.e., the RAPS framework). The approach is guided by existing literature on uncertainty as well as our own experience as clinicians working at different stages of career. We define each component of the approach and present sample language and actions for how to implement it in practice. Our aim is to empower clinicians to regard situations of high uncertainty as an opportunity to deepen the therapeutic alliance with the patient, and simultaneously to grow and learn as practitioners.

Changes in Sustainable Development in Manufacturing in Cases of Unexpected Occurrences—A Systematic Review

Nowadays, managers are facing the challenge of operating in situations of high uncertainty: delayed deliveries, lack of energy or rising energy and gas costs, the need to replace energy sources, and changing supply and sales markets. In the literature, two dominant trends in the activities of enterprises in the face of crises can be distinguished: (I) changes in supply chain management (increased flexibility by searching for local suppliers); and (II) transition to digital production and investment in technologies in the concept of Industry 4.0 or even Industry 5.0, such as artificial intelligence, 3D printing, robots, cyber-physical systems, digital manufacturing, and blockchain. A gap in the research has been observed in examining the impacts of these actions on the implementation of sustainable solutions and designating organizational changes in manufacturing. The main goal of this study is to review the literature using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) for data collection and, secondly, the methodology of Systematic Literature Review (SLR) and Mapping in Literature Reviews (MLR). Our literature review of the selected databases is based on 566 published articles in 2020–2022. The achieved results indicate the main organizational changes in the context of sustainable development in manufacturing, namely in the business management area (adopting Sustainable Project Management (SPM), Sustainable Supply Chain Management practices, Sustainable Supplier Selection (SSS), and Resilient Manufacturing Strategy (RMS)) and in the production area (adopting Internet of Things (IoT)-enabled Additive Manufacturing assists, simulation software, and Life Cycle Assessment. The findings of our study revealed key relationships between the adoption of fifth-generation industrial technologies and the sustainable development of manufacturing.

Development of a Korean offshore wind power HSE risk assessment module based on systems engineering approach

This study provides an in-depth comparison of various risk assessment models widely used in modern industry and proposes the most suitable models for offshore wind power risk assessment, focusing on the characteristics and requirements of the offshore wind power industry. The selection of the assessment models is based on various factors, such as the purpose of risk assessment, the stakeholder requirements, and the characteristics of offshore wind power. This study emphasizes the importance of using a combination of different risk assessment models in situations of high uncertainty. Using model-based systems engineering, risk assessment module is designed and implemented with traceability from requirements to detailed functionality. The risk assessment module supports organic conversion between risk assessment models to assess the risks of offshore wind power generation. The functionality and usability of the offshore wind risk assessment module were verified through the evaluation and the field test.

Optimization of Neutrosophic EOQ Model for Effective Demand Management in Uncertain Environment Using Genetic Optimization

Inventory management is characterized by a continuous struggle to lower goods levels and related costs while also providing customers with the goods they need. However, reducing costs while simultaneously striving for ideal inventory levels is difficult, notably in the current situation of high unpredictability of goods demand and lead time. Traditional inventory models are not strong enough to endure changes like goods demand and lead-time demand. As a result, it must be adjusted to achieve results. The oeuvre below presents a new kind of inventory model that deals with uncertainty in the demand for goods and lead time. In this regard, the presented work, the novel Neutrosophic Economic Order Quantity approach is a mechanism to account for the likely imprecision in the model. Specifically, the Neutrosophic set theory is integrated into the EOQ model so that it can handle variations in the demand and lead-time pattern successfully. An objective function is established for obtaining economical order quantities that include demand, lead-time, and other necessary components’ irregularities. The process variables in the model are given the final values using genetic algorithms and simulated annealing. To highlight the impact of the proposed Neutrosophic approach, it is then applied to several realistic examples. This will provide the audience a sense of how effective inventory management may be in high-uncertainty situations. The rapid evolution of organizations necessitates innovative inventory control tactics to meet growing demands

Universal coordinates and methods of reformatting an ambiguous humanitarian paradigm

The main problem: In the conditions of market uncertainty, the coronavirus pandemic, the absence of an officially articulated national idea, national interests and ideology in Kazakhstan, the problem of the lack of logically justified and coordinated coordinates of systemic thinking, an unambiguous paradigm of humanitarian thinking (analytical, pedagogical, managerial, economic, etc.) is becoming more and more clearly realized. as the most important conditions for personal, civil and professional self-determination. Purpose: to substantiate the general logical coordinates and methods of reformatting the ambiguous humanitarian paradigm used in the activity. Methods: the ontological principle of genetically meaningful logic, the method of transformation of concrete images of objects based on their abstract essence, the method of ascent from the abstract to the concrete, the speculative language of schematic images of thought and the language of methodological theory of activity. The results and their significance: logically justified universal abstract-concrete coordinates of universal motion are given. In relation to life and the world of activity, they can be concretized by coordinates: "standard of living – efficiency of activity", or "efficiency of activity – time", or "results – costs", or "quality – quantity", etc. The use of motion vectors in the logic of descent from the concrete to the abstract (NCA), ascent from the abstract to the concrete (AAC), as well as in their combination – logic CAC gives certainty to thinking. As an example, the scheme of the qualitative difference between educational (pre-professional) activities from professional ones using these methods and paired dialectical categories is given. The scheme and description of the functional model of the system object, considered as a rubicon of the transformation of educational activity into professional activity, are given. To reformat the indefinite, ambiguous paradigms of the humanities used in the activity into functional-logical, visible, constructive and unambiguous, it is recommended to use abstract-concrete coordinates, the methods given, the language of schematic images and the paradigm of the methodological theory of activity. As an example, the concept of a typical unit of activity development is given. A visible unambiguous paradigm is a necessary, but not sufficient prerequisite for adequate personal, civil and professional self-determination of a person in situations of high uncertainty. A sufficient prerequisite is the acquisition by subjects of appropriate reflexive-thinking abilities for self-determination, self-organization, self-regulation, etc.

Modulation of prefrontal couplings by prior belief-related responses in ventromedial prefrontal cortex.

Humans and other animals can maintain constant payoffs in an uncertain environment by steadily re-evaluating and flexibly adjusting current strategy, which largely depends on the interactions between the prefrontal cortex (PFC) and mediodorsal thalamus (MD). While the ventromedial PFC (vmPFC) represents the level of uncertainty (i.e., prior belief about external states), it remains unclear how the brain recruits the PFC-MD network to re-evaluate decision strategy based on the uncertainty. Here, we leverage non-linear dynamic causal modeling on fMRI data to test how prior belief-dependent activity in vmPFC gates the information flow in the PFC-MD network when individuals switch their decision strategy. We show that the prior belief-related responses in vmPFC had a modulatory influence on the connections from dorsolateral PFC (dlPFC) to both, lateral orbitofrontal (lOFC) and MD. Bayesian parameter averaging revealed that only the connection from the dlPFC to lOFC surpassed the significant threshold, which indicates that the weaker the prior belief, the less was the inhibitory influence of the vmPFC on the strength of effective connections from dlPFC to lOFC. These findings suggest that the vmPFC acts as a gatekeeper for the recruitment of processing resources to re-evaluate the decision strategy in situations of high uncertainty.

Память о 90-х как ресурс адаптации к новому кризису: анализ дискурсов российских СМИ

The article is devoted to the problem of memory functioning as a symbolic resource for adaptation to a crisis as a situation of high uncertainty. The author analyzes public practices of articulating memory about the early period of the post-Soviet transformation when discussing social and economic problems associated with the special military operation in Ukraine, that was declared by president Vladimir Putin on 24 February, 2022, and subsequent unprecedented extension of international sanctions. The study is based on Iwona Irwin-Zarecka’s theory of frames of remembrance. By revealing typical ways of framing the experience of the 1990s in media discourse during the first six months after 24 February, 2022, the author attempts to identify how this experience was tied to the current problems and thus determine the role of memory as a resource for adaptation to the new crisis. The analysis is based on publications in printed and online media that target different audiences. In order to reveal ways of framing statements about the 1990s, the author utilized the method of qualitative content analysis using the MAXQDA application. The results of the study confirm that in a situation of uncertainty caused by the forced restructuring of economic relations, social expectations and political goal-setting, the memory of a collective traumatic experience acts as an adaptation resource, which is associated with a partial transformation of its semantic framework. At the same time, the ideological splits tied to the memory of the 1990s persist and continue to determine the structure of the public discourse about the past.

The effects of uncertainty shocks on income and wealth inequality

ABSTRACT This paper assesses the impact of uncertainty on income and wealth inequality in Germany, France, Italy and Spain. For that purpose, mixed-frequency SVAR models are used. The results show that uncertainty shocks lead to heterogeneous responses across countries. A positive uncertainty shock increases income inequality in Spain, but reduces it in Germany and France. In the case of wealth, the response is statistically significant only in Spain and Italy, where an increase in inequality is experienced. Overall, these results highlight the important role of macroeconomic stabilisation policies in situations of high uncertainty.

Influence of elite rotation on authoritarian resilience

ABSTRACT This article proposes the use of the indicator of elite rotation to deepen the understanding of the phenomenon of authoritarian cooptation. The high frequency of changes in the ruling coalition can have a twofold effect on authoritarian regimes. On the one hand, it makes it possible to include new leaders in the ruling coalition in a timely fashion, remove potential opponents and maintain loyalty among the nobility. On the other hand, constant rotation creates a situation of high uncertainty and deprives some elites of access to previously received benefits. This study offers an empirical test of these assumptions: an analysis of all authoritarian regimes that existed between 1968 and 2010 (as well as all dictators who ruled between 1968 and 2008) leads to the conclusion that a low level of elite rotation generally contributes to the resilience of authoritarian regimes and leaders.

Avoidant authority: The effect of organizational power on decision-making in high-uncertainty situations.

Individuals in positions of power are often required to make high-stakes decisions. The approach-inhibition theory of social power holds that elevated power activates approach-related tendencies, leading to decisiveness and action orientation. However, naturalistic decision-making research has often reported that increased power often has the opposite effect and causes more avoidant decision-making. To investigate the potential activation of avoidance-related tendencies in response to elevated power, this study employed an immersive scenario-based battery of least-worst decisions (the Least-Worst Uncertain Choice Inventory for Emergency Responses; LUCIFER) with members of the United States Armed Forces. In line with previous naturalistic decision-making research on the effect of power, this research found that in conditions of higher power, individuals found decisions more difficult and were more likely to make an avoidant choice. Furthermore, this effect was more pronounced in domain-specific decisions for which the individual had experience. These findings expand our understanding of when, and in what contexts, power leads to approach vs. avoidant tendencies, as well as demonstrate the benefits of bridging methodological divides that exist between "in the lab" and "in the field" when studying high-uncertainty decision-making.

Decision-making performance and self-generated knowledge in handball-defense patterns: a case of representational redescription

In sport games, perceptual–cognitive skills are discussed as a decisive aspect of players’ expertise. However, an understanding of the relationship between these skills and actual game performance is limited, particularly, regarding the role of pattern identification and situational-probability estimation in performance. The present study thus aimed to examine how identification of teammates’ defensive qualities relates to decision-making performance in a 3:3 virtual-reality defensive task. Examining data collected in two previously published studies, we analyzed the relationship between explicit pattern detection and response correctness, and also as a function of players’ experience. Experience was operationalized as either expertise level (Experiment 1) or task-specific experience (Experiment 2). As expected, the explicit detection of a game-specific pattern was found to be facilitated by experience. However, the results imply that it is accumulated experience that enhances decision-making performance rather than the degree of self-generated explicit knowledge. This finding supports the notion of “representational redescription” as introduced by Karmiloff-Smith (1994). For sports practice, this suggests that the pattern identification demonstrated by skilled athletes should not be overestimated as a predictor of game performance, while the explicit provision of knowledge might be beneficial for less-skilled athletes, particularly in situations of high uncertainty.

Effectuation, causation, and machine learning in co-creating entrepreneurial opportunities

In creating innovative entrepreneurial opportunities, entrepreneurs are characterized by limited information processing capabilities and local search routines that are immanent to humans. Machine learning (ML) offers the opportunity to overcome these limitations while reshaping the innovation process. It is indisputable that ML alone cannot realize entrepreneurial opportunities, but that close collaboration with the human entrepreneur is required. While entrepreneurs usually act according to the principles of effectuation logic in situations of high uncertainty and according to the principles of causation logic in situations of risk, it remains unclear how co-creation with ML affects the entrepreneur's decision-making behavior. By contrasting the functionalities of four different ML paradigms with the principles of the two decision logics, it is shown that supervised ML supports causation logic, while unsupervised and reinforcement ML support effectuation logic in their approach. As a fourth, semi-supervised ML is classified somewhere between effectuation and causation. However, in relation to the situational context of different types of uncertainty, ML may also prove limiting for effectuation by transitioning to causation in the medium-term.

Виртуальные среды для моделирования взаимодействия операторов с БПЛА в закрытых пространствах в потенциально опасных ситуациях

The effective interaction between humans and robotic devices is designed to provide a timely response to potentially dangerous situations arising in complex environments. One example is the use of Unmanned Aerial Vehicles (UAVs) by human operators to inspect enclosed spaces. These units allow the search and identification of target objects, helping a human operator identify signs of Potentially Dangerous Situations (PDSs). At the same time in a closed (and often cluttered) space to control the emerging situations it is necessary to involve developed means of conducting spatial orientation based on Artificial Intelligence Technology, Computer Vision, 3D-visualization, Local Positioning And Navigation, etc. Despite the progress made in autonomous UAVs control, active human participation in detecting signs of PDSs is an important condition for maintaining the security of the internal environment of controlled premises. Human decision-making in situations of high uncertainty and incomplete data largely depends on means to improve his Situational Awareness (external conditions of activity) and Professional Competencies (internal conditions of activity). To form them, it is necessary to develop methodology and tools for building UAVs application scenarios to give operators the necessary user experience on simulation models in the Virtual Environment of Activity. The paper investigated the development of the Virtual Environment Systems (VES) for the implementation of UAVs application scenarios in enclosed spaces in relation to multicopters that allow both autonomous and manual control. As a result of this research, prototypes of UAVs for inspection of enclosed spaces have been identified; the prospects of quadcopters use under various PDSs scenarios have been shown; the composition of promising technologies ensuring UAVs use in enclosed environments has been described; the method of design and 3D visualization of UAVs application scenarios using the original VES (named VirSim) has been proposed. The advantages of the proposed approach to modeling the use of UAVs in PDSs are the multivariate scenarios of operators' activities, which contributes to the accumulation of user experience of human interaction with flying robots.

THE SIGNIFICANCE OF TEACHERS’ PSYCHOLOGICAL READINESS FOR INNOVATIVE CLASSROOM ACTIVITIES AND ITS SOCIO PSYCHOLOGICAL BACKGROUND

The article is devoted to the consideration of theoretical aspects of studying the psychological readiness of teachers for innovative activities. Psychological and pedagogical studies devoted to the study of this phenomenon are analyzed. An attempt has been made to identify the structure of the teacher's psychological readiness for innovative activity, which will make it possible to determine and develop psychological and pedagogical technologies for its formation among teachers. The results of scientific research on the topical problem of the development of innovative readiness in the conditions of the socio-psychological climate of teaching staff of higher educational institutions are touched upon. In a situation of high uncertainty in the system of higher professional education, the problem of the psychological readiness of a teacher in the context of optimizing the socio-psychological climate of teaching staff of universities is of particular importance and relevance, since it is the main and necessary factor in the development of the innovative potential of modern educational institutions.

L’exercice de la médecine générale à l’épreuve des crises sanitaires : de Lubrizol à la COVID

Following the fire of the chemical products stored by the Lubrizol (Seveso upper tier) and Normandie Logistique companies on 26September 2019 in Rouen, a research group bringing together general practitioners (GP), anthropologists and sociologists has undertaken a multidisciplinary qualitative investigation of general practitioners. The initial objective was to study the practice of primary care health professionals following the event. Initiated in February 2020, this survey was strongly transformed by the COVID-19 pandemic. COVID-19 changed the object of this study, imposed a reflection and a link between the two crises, where GPs found themselves once again on the front line. To analyze the practices of general practitioners in situations of uncertainty in the context of these extraordinary events, namely an industrial fire and a viral pandemic. Eighteen general practitioners were interviewed between February and July 2019 in semi-structured interviews conducted by a pair of researchers (sociologist and GP). An analysis inspired by the grounded theory was carried out on three levels (individual thematic analysis, paired confrontation, and collective restitution). In the health crisis contexts studied, GPs were confronted with more recurrent complaints while they had relatively little robust knowledge on which to base their responses. Finally, physicians responded to these situations of high uncertainty by drawing in original ways on their personal experiences of these crises.

Situational uncertainty interacts with anxiety sensitivity and distress intolerance to predict anticipated worry and preparation for a hurricane

ABSTRACT Background There is evidence for the impact of emotional intolerance on reactivity to stressors, but it is unknown whether the level of situational uncertainty may moderate this relationship. We examined whether situational uncertainty moderated the relationship between emotional intolerance and anticipated anxious responding to hurricane forecasts, considering three aspects of emotional tolerance: anxiety sensitivity, distress intolerance, and hurricane-specific distress intolerance. Methods Participants (N = 358) were Florida residents who experienced Hurricane Irma. Participants were presented with two hypothetical storm forecasts that varied in level of uncertainty: 5-day forecast (high uncertainty) and 3-day forecast (low uncertainty). Participants rated their anticipated worry and preparation for each forecast. Results Significant interactions between forecast uncertainty and both anxiety sensitivity and hurricane-specific distress intolerance emerged on anticipated worry, such that there was a stronger relationship in the high uncertainty condition. Forecast uncertainty also moderated the relationship between anxiety sensitivity and anticipated preparation in the same direction. There were no significant interactions between forecast uncertainty and distress intolerance on either anticipated worry or preparation. Conclusions Specific aspects of emotional intolerance appear to have a stronger influence on anticipated worry and preparatory behavior in high uncertainty situations. These findings suggest that distinct emotional tolerance factors may influence these responses.

The impact of COVID-19 on European tourists' attitudes to air travel and the consequences for tourist destination evoked set formation

We study how risk conditions derived from the COVID-19 pandemic may impact on both the desire to travel and intention to visit of tourists and, therefore, on different stages of the destination choice process. We analyse 5134 million flight searches and 379 million flight picks during 2020 for the 17 largest European tourism source markets. An unweighted index number is employed to measure the average variation for searches and picks, for the year 2020, in relation to the reference base period (year 2019). This is done for air travel in general and to Spain specifically. The study then proceeds to conduct an analysis of 17 international travel destinations that are in the evoked sets of the two largest outbound markets in Europe (Germany and UK). We also identify which markets are most favourable to Spain. The research design can inform cost-efficient marketing decisions in a situation of high uncertainty.