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Inferential decision-making algorithms typically assume that an underlying probabilistic model of decision alternatives and outcomes may be learned a priori or online. Furthermore, when applied to robots in real-world settings they often perform unsatisfactorily or fail to accomplish the necessary tasks because this assumption is violated and/or because they experience unanticipated external pressures and constraints. Cognitive studies presented in this and other papers show that humans cope with complex and unknown settings by modulating between near-optimal and satisficing solutions, including heuristics, by leveraging information value of available environmental cues that are possibly redundant. Using the benchmark inferential decision problem known as "treasure hunt", this paper develops a general approach for investigating and modeling active perception solutions under pressure. By simulating treasure hunt problems in virtual worlds, our approach learns generalizable strategies from high performers that, when applied to robots, allow them to modulate between optimal and heuristic solutions on the basis of external pressures and probabilistic models, if and when available. The result is a suite of active perception algorithms for camera-equipped robots that outperform treasure-hunt solutions obtained via cell decomposition, information roadmap, and information potential algorithms, in both high-fidelity numerical simulations and physical experiments. The effectiveness of the new active perception strategies is demonstrated under a broad range of unanticipated conditions that cause existing algorithms to fail to complete the search for treasures, such as unmodelled time constraints, resource constraints, and adverse weather (fog). [ABSTRACT FROM AUTHOR]

Urban areas are emerging as "strategic sites" in the ongoing sustainable energy (SE) transitions. This has rekindled the importance of urban governments in initiating this transition urgently, a departure from the actors managing more mainstream centralized energy governance. However, while there is a growing international and academic interest in urban energy transitions, the political presence of cities in the global clean energy landscape remains largely underwhelming. Scholars studying urban energy transitions or governance have often pointed toward the lack of material and knowledge capacities of the urban governments as the key barrier for their muted actions. I argue that decision-making by urban governments with respect to clean energy adoption needs deeper inspection wherein aspects such as capacity, or the lack of it, are symptoms of underlying power contestations and conflicts that are negotiated in multi-level governance systems. The scholarship of power captures the ideas of contestation, control, and acquiescence, going beyond the ideas of cooperation prevalent in multilevel governance. In this article, I juxtapose these with concepts from multi-level governance and socio-technical studies to offer an analytical framework for understanding energy decision-making by city governments. The framework presented in this article attempts to capture both direct and indirect forms of power, their operationalization, and manifestation in constituting identities, actual decisions (and indecisions) as well as the conditions of decision-making. I also use the framework to understand the role of power in sustainable energy decision-making in three cities in India as an illustration of possible application of the framework. [ABSTRACT FROM AUTHOR]

This article examines how three types of experience—personal, related others, and unrelated others—influence decision-making. We present the complexities and nuances in using these experiential sources to suggest that personal experience is preferred to the other two sources. We discuss the implications of this preference for decision-making processes, especially in contexts involving transformative outcomes. To conclude, we discuss how people rely on other experiential sources when their preferred source is limited. [ABSTRACT FROM AUTHOR]

The decision-making process involves various cognitive procedures influenced by the interplay between cognition, motivation, and attention, forming a complex neural framework. Attention is a fundamental cognitive element within decision-making mechanisms, and one of the conditions affecting the attentional system is attention deficit hyperactivity disorder (ADHD). Decision-making impairments in ADHD have significant economic consequences, necessitating effective policies and interventions to address this critical issue. Research from computational models and neuroscience suggests how cognitive functions' workings and problems affect decision-making and provide insights into the neural implications of decision-making. This article explores the intersection of decision-making, ADHD, and neuroeconomics, highlighting research gaps, potential contributions, and implications for future policies. [ABSTRACT FROM AUTHOR]

Background: Allergic rhinitis (AR) is the most common type of rhinitis, the treatment of which relies on relieving symptoms. Therefore, we aimed to assess the criteria that influence doctors' decision-making in the process of drug selection for the treatment of allergic rhinitis based on quantitative, qualitative, and cost analyses. Methods: We conducted a survey study with the participation of 300 allergologists. A self-developed questionnaire was presented during a computer-assisted telephone interview (CATI) according to standard procedures. The contingency table underwent statistical analysis using the chi-square test with Cramer's V. Results were considered statistically significant at p < 0.05. Results: Our analyses showed that doctors most often prescribe intranasal glucocorticoids and oral antihistamines to treat allergic rhinitis in patients of all ages. The most common factor that affects the decision-making related to AR treatment was the efficiency of the drug. We found a significant relationship between factors and the main workplace (X-squared = 122.81, df = 90, p -value = 0.0123, Cramer's V = 0.1787216), as well as voivodeship of the main workplace (X-squared = 440.75, df = 270, p -value = 2.378e-10, Cramer's V = 0.1954731). In our study, respondents claimed that patients are willing to pay 31–50 PLN (∼€7- €11) monthly for the treatment of mild and moderate forms of AR, while they were willing to pay 51–100 PLN (∼€11–€22) for treatment of the severe AR form. Conclusion: Our study confirms that the management of AR should be focused on the patient. One of the most important factors in choosing a drug is its effectiveness. Moreover, an important factor in the effective treatment of AR is the financial issue; as shown in our analysis, AR treatment costs can be a significant burden, especially for less wealthy citizens in Poland. [ABSTRACT FROM AUTHOR]

This study utilized eye-tracking techniques to investigate decision-making behavior in intertemporal loss scenarios under both time pressure and no time pressure conditions. Results revealed shorter decision-making times and decreased large later (LL) option selection frequency under time pressure. Participants under time pressure exhibited reduced Mean Fixation Duration (MFD) and Search Measure (SM) values, indicating altered information processing. Mediation analyses confirmed that task choice outcomes were influenced by SM and MFD, suggesting a shift towards heuristic decision-making under time pressure. [ABSTRACT FROM AUTHOR]

This study uses the newsvendor problemto investigate the correlations between thinking orientation, overconfidence, and economic outcome. We aim to shed light on possible interconnections between these variables and extend the existing conceptual models of thinking orientation and overconfidence. To test the conceptual model and the corresponding hypotheses empirically, we employed a laboratory experiment with 50 hypothetical decision periods in which 142 participants ordered a highly profitable product. We found compelling evidence that suggests overprecision as themediating variable between thinking orientation and the economic outcome. Furthermore, this research offers some practical implications. [ABSTRACT FROM AUTHOR]

Background: In basketball training, self-evaluation plays a crucial role in the decision-making and execution of movements of players. The self-evaluation of players is influenced by their perception of own basketball ability and selfconfidence state. This study aimed to explore potential discrepancies between self-confidence levels of players and their decision-making performance, while also characterizing different types of players. Method: Data was collected from 20 youth basketball players who participated in a decision-making video task and a self-confidence assessment. Based on data from their self-confidence and decision-making awareness assessment, the K-means cluster analysis was used to categorize the players into different groups. Then, ANOVA and post hoc Scheffe test were conducted to compare these clusters. Results: The cluster analysis identified four distinct profiles of players and the results of the ANOVA and post hoc Scheffe tests revealed significant differences between the four clusters. The "High Self-confidence & Low Decision-making Awareness" players might display an overconfident mindset, while the "High Self-confidence & High Decision-making Awareness" players potentially demonstrated the better performance and maintained a consistent and confident attitude. The "Low Self-confidence & High Decision-making Awareness" players appeared to lack confidence and needed to foster greater faith in their abilities. Finally, the "Low Self-confidence & Low Decision-making Awareness" players required a long-term and comprehensive training program to improve their skills. Discussion: These preliminary findings informed the development of a selfevaluation matrix, designed to help coaches better understand player profiles and design tailored interventions. Moreover, this study contributes on sport calibration and enhances understanding of the behavioral and psychological states of players. [ABSTRACT FROM AUTHOR]

Introduction: In the early days of the COVID-19 pandemic, individuals were asked to perform costly actions to reduce harm to strangers, even while the general population, including authorities and experts, grappled with the uncertainty surrounding thenovel virus. Many studies have examined health decision-making by experts, but the study of lay, non-expert, individual decisionmaking on a stranger's health has been left to the wayside, as ordinary citizens are usually not tasked with such decisions. Methods: We sought to capture a snapshot of this specific choice behavior by administering two surveys to the general population in the spring of 2020, when much of the global community was subject to COVID-19-related restrictions, as well as uncertainty surrounding the virus. We presented study participants with fictitious diseases varying in severity that threatened oneself, a loved one or a stranger. Participants were asked to choose between treatment options that could either provide a sure, but mild improvement (sure option) or cure the affected person at a given probability of success (risky option). Results: Respondents preferred gambles overall, but risk-seeking decreased progressively with higher expected severity of disease. This pattern was observed regardless of the recipient's identity. Distinctions between targets emerged however whendecisions were conditioned on a treatment's monetary cost, with participants preferring cheaper options for strangers. Discussion: Overall, these findings provide a descriptive model of individual decision-making under risk for others; and inform on the limits of what can be asked of an individual in service to a stranger. [ABSTRACT FROM AUTHOR]

Background: Communication is an essential aspect of high-quality patient- and family-centered care. A model for pediatric cancer communication developed in the United States defined eight communication functions. The purpose of this study was to explore the relevance of these functions in Pakistan as part of an effort to understand the role of culture in communication. Materials and methods: Semi-structured interviews were conducted with 20 clinicians and 18 caregivers of children with cancer at two major cancer centers. Interviews were conducted in Urdu or English and transcribed and translated as necessary. Two independent coders used a priori codes related to the communication model as well as novel codes derived inductively. Thematic analysis focused on operationalization of the functional communication model. Results: Clinicians and caregivers in Pakistan discussed the importance of all eight communication functions previously identified including: information exchange, decision-making, managing uncertainty, enabling family selfmanagement, responding to emotions, supporting hope, providing validation, and building relationships. The operationalization of these functions was influenced by Pakistani cultural context. For example, information-exchange included the importance of addressing preconceptions and community myths, while managing uncertainty included strong references to religion and faithbased coping. Essential to all eight functions was trust between the family and the medical team. Discussion: These findings support the use of this functional communication model in diverse pediatric oncology settings and emphasize the importance of trust. Culturally sensitive operationalization of these functions could inform the adaptation of tools to measure communication and interventions aimed at supporting the needs of parents of children with cancer. [ABSTRACT FROM AUTHOR]

It is expected that machine learning algorithms will enable better diagnosis, prognosis, and treatment in psychiatry. A central argument for deploying algorithmic methods in clinical decision-making in psychiatry is that they may enable not only faster and more accurate clinical judgments but also that they may provide a more objective foundation for clinical decisions. This article argues that the outputs of algorithms are never objective in the sense of being unaffected by human values and possibly biased choices. And it suggests that the best way to approach this is to ensure awareness of and transparency about the ethical trade-offs that must be made when developing an algorithm for mental health. [ABSTRACT FROM AUTHOR]

The question of how consciousness and behavior arise from neural activity is fundamental to understanding the brain, and to improving the diagnosis and treatment of neurological and psychiatric disorders. There is significant murine and primate literature on how behavior is related to the electrophysiological activity of the medial prefrontal cortex and its role in working memory processes such as planning and decision-making. Existing experimental designs, specifically the rodent spike train and local field potential recordings during the T-maze alternation task, have insufficient statistical power to unravel the complex processes of the prefrontal cortex. We therefore examined the theoretical limitations of such experiments, providing concrete guidelines for robust and reproducible science. To approach these theoretical limits, we applied dynamic time warping and associated statistical tests to data from neuron spike trains and local field potentials. The goal was to quantify neural network synchronicity and the correlation of neuroelectrophysiology with rat behavior. The results show the statistical limitations of existing data, and the fact that making meaningful comparison between dynamic time warping with traditional Fourier and wavelet analysis is impossible until larger and cleaner datasets are available. [ABSTRACT FROM AUTHOR]

Site selection analysis is a fundamental methodology for the regeneration of Xylella fastidiosa subsp. pauca (Xfp) infected areas, with the introduction of Xfp immune/resistant tree crop species. The diffusion of these species could be assessed by combining ecological optima data, climate and soil attributes of the study area, and GIS tools. The study aimed to evaluate the potential suitability of eight Xfp immune tree crops, including Neglected and Underutilized Species (NUS) drought-resistant and new species, as follows: carob, hawthorn, prickly pear, mulberry, loquat, walnut, persimmon, and avocado. The use of GIS tools allowed the integration of different layers, such as climate and soil, to contribute to the identification of suitable areas for the cultivation of these tree crops helping the policy-makers to define plans for land use at a regional scale. Following the ecological optima, which represents the ideal environmental conditions for each species, this analysis provided valuable insights into the compatibility of the selected tree crops with the prevailing environmental factors in the affected area. Carob revealed its remarkable adaptability and drought resistance, presenting the broadest suitability. Hawthorn and Loquat also exhibited high adaptability, indicating their potential contribution to agricultural diversification and ecological balance. Conversely, crops like Avocado, Prickly pear, and Walnut, despite their economic value, demonstrated limited adaptability due to their specific soil and climate requirements. These findings can potentially contribute to the development of strategies for the policymakers, aimed at diversifying and enhancing the resilience of agricultural systems, facing the problem of emerging quarantine pathogens and the incoming climate change, and highlighting the possibility of opening new cultivation scenarios in the zones affected by Xfp. [ABSTRACT FROM AUTHOR]

Eye movements are strongly linked to the perception of visual information and can be used to infer mental processes during decision-making. While eye-tracking technology has been available for several decades, the incorporation of eye-tracking data into computational models of decision making is relatively new in neuroeconomics. This review article provides an overview of the interaction between eye movement and choices, highlighting the value of eye-tracking data in decision-making research. First, we provide an overview of empirical work studying the interaction between eye movement and choices. In the second part, we present existing models that incorporate eye-tracking data into process models of decision-making, emphasizing their assumptions regarding the role of attention in choice formation and contrasting models that use gaze data to inform behavioral predictions with those that attempt to predict eye movements themselves. Additionally, we discuss the potential of using cognitive models to understand the connection between choice and gaze patterns and normative aspects of decision- making. Overall, this review underscores the significant role of eye-tracking data in understanding decision-making processes, particularly in the field of neuroeconomics, and its potential to provide valuable insights into individual differences in decision-making behavior. [ABSTRACT FROM AUTHOR]

Sorption is a key process to understand the environmental fate of pollutants on soils, conduct preliminary risk assessments and fill information gaps. Quantitative Structure-Activity Relationships (QSAR) and Pedotransfer Functions (PTF) are the most common approaches used in the literature to predict sorption. Both models use different outcomes and follow different simplification strategies to represent data. However, the impact of those differences on the interpretation of sorption trends and application of models for regulatory purposes is not well understood. We conducted a systematic review to contextualize the requirements for developing, interpreting, and applying predictive models in different scenarios of environmental concern by using pesticides as a globally relevant organic pollutant model. We found disagreements between predictive model assumptions and empirical information from the literature that affect their reliability and suitability. Additionally, we found that both model procedures are complementary and can improve each other by combining the data treatment and statistical validation applied in PTF and QSAR models, respectively. Our results expose how relevant the methodological and environmental conditions and the sources of variability studied experimentally are to connect the representational value of data with the applicability domain of predictive models for scientific and regulatory decisions. We propose a set of empirical correlations to unify the sorption mechanisms within the dataset with the selection of a proper kind of model, solving apparent incompatibilities between both models, and between model assumptions and empirical knowledge. The application of our proposal should improve the representativity and quality of predictive models by adding explicit conditions and requirements for data treatment, selection of outcomes and predictor variables (molecular descriptors versus soil properties, or both), and an expanded applicability domain for pollutant-soil interactions in specific environmental conditions, helping the decision-making process in regard to both scientific and regulatory concerns (in the following, the scientific and regulatory dimensions). [ABSTRACT FROM AUTHOR]

Learning to make adaptive decisions involves making choices, assessing their consequence, and leveraging this assessment to attain higher rewarding states. Despite vast literature on value-based decision-making, relatively little is known about the cognitive processes underlying decisions in highly uncertain contexts. Real world decisions are rarely accompanied by immediate feedback, explicit rewards, or complete knowledge of the environment. Being able to make informed decisions in such contexts requires significant knowledge about the environment, which can only be gained via exploration. Here we aim at understanding and formalizing the brain mechanisms underlying these processes. To this end, we first designed and performed an experimental task. Human participants had to learn to maximize reward while making sequences of decisions with only basic knowledge of the environment, and in the absence of explicit performance cues. Participants had to rely on their own internal assessment of performance to reveal a covert relationship between their choices and their subsequent consequences to find a strategy leading to the highest cumulative reward. Our results show that the participants' reaction times were longer whenever the decision involved a future consequence, suggesting greater introspection whenever a delayed value had to be considered. The learning time varied significantly across participants. Second, we formalized the neurocognitive processes underlying decision-making within this task, combining mean-field representations of competing neural populations with a reinforcement learning mechanism. This model provided a plausible characterization of the brain dynamics underlying these processes, and reproduced each aspect of the participants' behavior, from their reaction times and choices to their learning rates. In summary, both the experimental results and the model provide a principled explanation to how delayed value may be computed and incorporated into the neural dynamics of decision-making, and to how learning occurs in these uncertain scenarios. [ABSTRACT FROM AUTHOR]

Introduction: Clinical mastitis (CM) treatment decision-making is a multifaceted process that remains relatively understudied, despite CM being one of the most prevalent diseases on dairy farms worldwide, contributing greatly to the use of antimicrobials in the dairy industry. This study aimed to gain insights into decision-making mechanisms employed by dairy farmers in British Columbia and Alberta, Canada, when dealing with CM. Methods: Interviews were held with 15 dairy farmers in the Canadian provinces of British Columbia and Alberta and analyzed using reflexive thematic analysis to develop both the decision-pathway and overarching themes influencing the CM decisions by farmers in this region. Results and discussion: The analysis generated a decision-making process that begins with identification and classification of CM, guided by visual characteristics of milk and the udder, available milk production and quality data, presence of systemic signs, and additional diagnostics. Subsequently, CM cases are assessed based on the likelihood of cure, value of the cow, and herd goals to decide whether antimicrobial treatment is desired. Next, a treatment choice is made by evaluating severity and urgency of the case, availability of drugs and timing of the case. Finally, definition of treatment success and progression over time following the treatment decision guides the termination of treatment. Three overarching themes were generated that shape the decision-making process: 'Personal attributes', including personal approach and experiential knowledge; 'Inter-actor dynamics', such as shared decision-making and dynamics among producers, veterinarians, and milkers; and 'Moving beyond protocols', which highlights the dynamic nature of mastitis decision-making. These insights have the potential to inform the development of effective interventions to improve CM antimicrobial use that align with the reality of farming operations within Western Canada, and potentially beyond. [ABSTRACT FROM AUTHOR]

This study aimed to examine how soccer referees make decisions about issuing yellow cards for fouls. The research involved 60 male participants, divided into expert (n=30) and novice (n=30) groups based on their experience and qualifications as referees. They took part in a 2x2x2 mixed-design experiment. The study looked at Decision-Making Style (DMS: Analytical Decision-Making [ADM] vs. Intuitive Decision-Making [IDM]), Video Type (yellow card foul vs. nonyellow card foul), and Referee Level (expert vs. novice) as independent variables. The dependent variables were accuracy rate (ACC), discrimination index (D), self-confidence index (C), and overconfidence index (OC). The findings showed that Analytical Decision-Making (ADM) led to higher accuracy compared to Intuitive Decision-Making (IDM). Expert referees demonstrated better accuracy than novice referees. There was also an interaction between Decision-Making Style and Referee Level, showing differences in the effectiveness of ADM and IDM between expert and novice referees. Additionally, the study revealed that both expert and novice referees showed overconfidence, with experts demonstrating significantly higher overconfidence, particularly during IDM. In conclusion, the research highlighted the complexity of referees' decisionmaking in high-pressure situations and emphasized the potential benefits of employing Analytical Decision-Making strategies. The study contributed to understanding cognitive biases in sports officiating and suggested the need for targeted training programs to help referees improve their performance and reduce overconfidence in challenging situations. [ABSTRACT FROM AUTHOR]

In the present study, a bibliometric analysis of the published literature on Ecological Niche Modelling (ENM) topic from 1992 to 2023 was carried out using Web of Science (WoS) as a data source. Analysis of the data was carried out using bibliometrix tool in R software. Additionally, VOS Viewer software was used to provide visualization of the bibliometric analysis through network maps. The results of the study revealed that a total of 3, 595 scholarly documents in the English language were published on ENM from 1992-2023, originating from 564 sources. Furthermore, a significant increase in publications was observed over the years. A total of 13,122 authors have contributed to the field, with "Peterson AT" from the University of Kansas being the most prolific author. Journal of Biogeography emerges as the most relevant source with 290 documents published, while Ecography as the most cited source with 8,485 citations. Collaboration analysis revealed that only 109 documents were single-authored, with an average of 5.07 co-authors per document and an international co-authorship rate of 50.96%. Additionally, our analysis shows that the USA leads in Multiple Country Publications (MCP). The development of sophisticated software tools and algorithms coupled with remote sensing data has democratized ENM research, enabling scientists from diverse backgrounds to contribute to the field's growth. However, like any other model ENMs have some limitations and thus the entire procedure used to create an ENM must be reliable, transparent, and repeatable in order for it to be used effectively in conservation, management and decision-making. [ABSTRACT FROM AUTHOR]

In the context of Uganda, this study delves into gender-based strategies aimed at enhancing women's engagement in milk safety, value addition, and marketing within smallholder livestock farming. The objectives were two-fold: first, to document the current practices of women in milk safety, value addition, and marketing channels; second, to examine the constraints, opportunities, and strategies related to the production of safe milk and milk products, along with accessing sustainable markets. Conducted in four sub-counties of the Kiruhura district, this research employed both qualitative participatory methods and structured questionnaires, including 12 focused group discussions and 20 key informant interviews with both women and men. Notably, 217 structured questionnaires were administered. The findings illuminate that women played a central role in milk processing, water provisioning, sanitation, and hygiene practices and were the primary contributors to milk value addition, particularly in the production of butter and ghee. Despite their active involvement, women face challenges in accessing adequate milk quantities, employ traditional labor-intensive procedures, and encounter difficulties in marketing their processed products. Men, often the household heads, held decision-making authority over milk consumption and controlled the selling of milk, contributing to gender disparities. Addressing these challenges necessitates comprehensive support, including training and capacity-building initiatives for both men and women in milk value addition, credit access, and market entry. The study underscores the potential for improved women's access to milk quantities, particularly for butter and ghee production, to strengthen rural livelihoods and boost dairy production in Uganda. [ABSTRACT FROM AUTHOR]

Introduction: In team sports, athletes' ability to make quick decisions plays a crucial role. Decision-making proficiency relies on the intricate balance of athletes' perceptual and cognitive abilities, enabling them to assess the competitive environment swiftly and select the most appropriate actions from various options. Virtual reality (VR) technology is emerging as a valuable tool for evaluating and refining athletes' decision-making skills. This study systematically examined the integration of VR technology into decision-making processes in team sports, aiming to identify more effective methods for presenting and interacting with virtual decision-making systems, thus enhancing the evaluation and refinement of athletes' decision making abilities. Methods: Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, a thorough search of respected research databases, including Web of Science, PubMed, SPORTDiscus, ScienceDirect, PsycINFO, and IEEE, was conducted using carefully selected keywords. Results: Twenty research papers meeting predefined inclusion criteria were included after careful evaluation. These papers were systematically analyzed to delineate the attributes of virtual decision-making task environments, the interactive dynamics inherent in motor decision-making tasks, and the significant findings. Discussion: This review indicate that (1) the effectiveness of VR technology in assessing and improving athletes' decision-making skills in team sports; (2) the construction of virtual environments using the Head-Mounted Display (HMD) system, characterized by enhanced ease and efficiency; (3) the potential for future investigations to explore computer simulations to create more expansive virtual motion scenarios, thus efficiently generating substantial task scenario material, diverging from the constraints posed by 360-degree panoramic videos; and (4) the integration of motion capture technology for identifying and monitoring athletes' decision-making behaviors, which not only enhances ecological validity but also augments the transfer validity of virtual sports decision-making systems. Future research endeavors could explore integrating eye-tracking technology with virtual reality to gain insights into the intrinsic cognitive-action associations exhibited by athletes. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to describe the fixation location and the time of the longer fixation of expert and novice futsal coaches before the ball was in play in futsal set pieces. Methods: A total of 10 experts (ages 48 ± 5) and 10 novice coaches (ages 40 ± 7) participated in the study. They observed that 38 video clips were created to mimic the attack and defensive set-piece moments of the game. Data were collected in a standardized video analysis task using the pupil invisible eye tracker and processed through the pupil cloud platform. The Mann-Whitney test was conducted to evaluate differences in gaze duration between game moments (attack and defense set pieces) and groups (expert vs. novice). Gaze duration was also compared for gaze location between groups. For further comparisons, the game moments (attack and defense set pieces) and the gaze location were summarized in two-dimensional graphics using correspondence analysis. Results and discussion: The results revealed higher values of gaze duration for attack and defense set pieces for the group of experts than for novices. When considering gaze duration, expert coaches had higher values than novices for the attacker 3, defender 3, barrier 1st, and barrier 2nd gaze locations. The correspondence analysis showed different strategies of visual search and, consequently, gaze locations for attack and defense set pieces. In particular, there was different correspondence for free kicks between the level of expertise and gaze location, while corner and sideline kicks revealed some correspondence between the groups and the gaze location. In free kicks, coaches should be particularly concerned about the relationship between attacker and defender three and the barrier 1st and 2nd line positions. In corner and sideline kicks, coaches should be particularly aware of the relationship between attackers' and defenders' positions. [ABSTRACT FROM AUTHOR]

Negative and positive urgency are two closely related personality traits that reflect the tendency for an individual to engage in maladaptive risk-taking in response to extreme negative and positive emotions, respectively. However, other prominent emotion theories describe how emotions contribute to adaptive, rather than maladaptive, decision-making. This conceptual review considers how Urgency Theory can be integrated with these broader existing emotion theories. We proceed as follows: a) briefly define what is meant by emotions in science and summarize basic human neuroscience underlying emotions; b) briefly describe select theories and research linking emotions to adaptive decision-making, including brain correlates of this effect; c) review Urgency Theory, including contrasting evidence that emotions lead to maladaptive outcomes and brain correlates of this effect; d) discuss how urgency can be integrated into theories that view emotions as both adaptive and maladaptive for decision-making; and e) propose future directions to advance research in this field. We identified four, not mutually exclusive, viable options to integrate Urgency Theory into existing theories: urgency as model-free emotion regulation, urgency as being driven by incidental emotions, urgency as a reflexive response to emotions, or urgency as an individual difference factor. We conclude that although all four options are viable, individual difference and model-free emotion regulation have the most empirical support to date. Importantly, the other two options are less well-researched. Direct tests comparing these integrations is necessary to determine the most accurate way to integrate urgency with existing emotion theories. We believe that this research can identify mechanisms underlying urgency and help inform future intervention and prevention development to reduce negative effects of urgency across numerous maladaptive behaviors and clinical disorders. [ABSTRACT FROM AUTHOR]

Decisions made by millions of refugees about where to go, how to make a living and how to secure a future are fundamental drivers of secondary movements. While a substantial body of literature addresses factors contributing to migrants' decision-making, a comprehensive understanding of the central role of refugees in secondary mobility decision-making, including agency and strategies employed, remains underexplored. This is partly due to the belief that refugees are constrained by external and structural factors and cannot exercise agency, which we challenge. This article provides a systematic analysis of the literature on refugees' secondary mobility decision-making processes. Using a systematic literature review (SLR) methodology, it presents an in-depth analysis of 40 peerreviewed, English-language research articles selected from the Web of Science and Scopus databases published before September 2022. The article critically examines the drivers, prevailing dichotomies and conceptual frameworks surrounding refugee categorization, agency, and mobility. By synthesizing a wide range of literature, our paper presents emerging alternative concepts and frameworks that shed light on the complex dynamics of decision-making. [ABSTRACT FROM AUTHOR]

Introduction: Individual differences in social learning impact many important decisions, from voting behavior to polarization. Prior research has found that there are consistent and stable individual differences in social information use. However, the underlying mechanisms of these individual differences are still poorly understood. Methods: We used two complementary exploratory machine learning approaches to identify brain volumes related to individual differences in social information use. Results and discussion: Using lasso regression and random forest regression we were able to capture linear and non-linear brain-behavior relationships. Consistent with previous studies, our results suggest there is a robust positive relationship between the volume of the left pars triangularis and social information use. Moreover, our results largely overlap with common social brain network regions, such as the medial prefrontal cortex, superior temporal sulcus, temporal parietal junction, and anterior cingulate cortex. Besides, our analyses also revealed several novel regions related to individual differences in social information use, such as the postcentral gyrus, the left caudal middle frontal gyrus, the left pallidum, and the entorhinal cortex. Together, these results provide novel insights into the neural mechanisms that underly individual differences in social learning and provide important new leads for future research. [ABSTRACT FROM AUTHOR]

The decision-making of soccer referees is one of the typical forms influenced by factors such as environmental pressure and individual emotions. While previous studies have explored how common factors like personal anxiety and on-field pressure affect the decisions of soccer referees, the mechanisms by which anxiety influences decision-making under pressure remain unclear. This study developed a penalty task based on real soccer match scenarios and recruited 76 experienced soccer referees. These referees were divided into two groups, high anxiety and low anxiety, based on their anxiety levels, to perform decisionmaking tasks under different pressure environments simulated to mimic real matches. Additionally, this research employed Event-Related Potential (ERP) technology to compare the brain signals of soccer referees with different levels of anxiety when facing foul play under various pressure environments. It was found that referees with high levels of anxiety displayed larger P300 and N400 amplitudes in a low-pressure environment (p = 0.0059, t = 2.9437). However, no significant differences in P300 and N400 amplitudes were observed between referees with high and low levels of anxiety under high-pressure conditions (p = 0.1890, t = 1.3411). This study not only reveals the complex mechanisms of anxiety in the decision-making process of referees but also emphasizes the importance of understanding and managing the psychological state of referees in competitive sports to improve the quality of their decisions. Our findings provide an empirical basis for future efforts to mitigate the impact of anxiety and optimize the decision-making process in similar high-pressure environments. [ABSTRACT FROM AUTHOR]

Introduction: The present study conducts a retrospective bibliometric analysis to examine the quantifiable and qualitative evolution of the concept of tolerance to ambiguity (TA) over time. Additionally, a scientometric analysis using quantitative methods on scientific measurements and trends aims to profile and identify the concept, as well as its development in research themes. The relevance of this study is underscored by the growing interest and development of research on TA, particularly in fields like entrepreneurship where psychological factors are significant. Methods: The research includes highly relevant literature, such as Budner and Frenkel-Brunswick, which define TA as a predisposition to perceive ambiguous situations as desirable and as a personality variable centered on the emotional and perceptual domain, respectively. Data was obtained from the eight indices comprising the main Web of Science collection, covering research from 1975 to December 2022. A total of 378 articles were identified. Results: The analysis reveals that scientific production peaked in 2022 with 45 articles. In terms of citations, 7,773 were found, with the highest concentration in 2022, totaling 1,203 citations. This indicates a significant increase in research interest and output related to TA. Discussion: The study highlights the growing exploration of the concept of TA, emphasizing its importance across multiple disciplines in dealing with uncertainty. The research demonstrates that TA significantly influences decisionmaking and adaptability, highlighting its value in business and educational settings. By analyzing leading publications, authors, and research centers, the study shows the diversity of approaches to understanding TA, indicating a promising direction for future research. [ABSTRACT FROM AUTHOR]

Background/aimArtificial Intelligence (AI) is the capability of computational systems to perform tasks that require human-like cognitive functions, such as reasoning, learning, and decision-making. Unlike human intelligence, AI does not involve sentience or consciousness but focuses on data processing, pattern recognition, and prediction through algorithms and learned experiences. In healthcare including neuroscience, AI is valuable for improving prevention, diagnosis, prognosis, and surveillance.MethodsThis qualitative study aimed to investigate the acceptability of AI in Medicine (AIIM) and to elucidate any technical and scientific, as well as social and ethical issues involved. Twenty-five doctors from various specialties were carefully interviewed regarding their views, experience, knowledge, and attitude toward AI in healthcare.ResultsContent analysis confirmed the key ethical principles involved: confidentiality, beneficence, and non-maleficence. Honesty was the least invoked principle. A thematic analysis established four salient topic areas, i.e., advantages, risks, restrictions, and precautions. Alongside the advantages, there were many limitations and risks. The study revealed a perceived need for precautions to be embedded in healthcare policies to counter the risks discussed. These precautions need to be multi-dimensional.ConclusionThe authors conclude that AI should be rationally guided, function transparently, and produce impartial results. It should assist human healthcare professionals collaboratively. This kind of AI will permit fairer, more innovative healthcare which benefits patients and society whilst preserving human dignity. It can foster accuracy and precision in medical practice and reduce the workload by assisting physicians during clinical tasks. AIIM that functions transparently and respects the public interest can be an inspiring scientific innovation for humanity.

In real-world vision, objects may appear for a short period, such as in conjunction with visual search. Presumably, this puts a premium on rapid categorization. We designed a visual categorization task cued by briefly presented images to study how visual categorization is processed in an ethologically relevant context. We compared the performance of monkeys with bilateral area TE lesions, and those with bilateral rhinal cortex lesions, to control animals. TE lesions impaired the accuracy but not the speed of visual categorization. In contrast, rhinal cortex lesions did not affect the accuracy but reduced the speed of visual categorization. A generalized drift-diffusion model (GDDM) with collapsing bounds was fitted to the data. The drift rate was equivalent across all groups, but the decision bounds collapsed more slowly in the rhinal group than in the other two groups. This suggests that, although evidence is accumulated at the same rate in all groups, the rhinal lesion results in slower decision-making.

Inferential decision-making algorithms typically assume that an underlying probabilistic model of decision alternatives and outcomes may be learned a priori or online. Furthermore, when applied to robots in real-world settings they often perform unsatisfactorily or fail to accomplish the necessary tasks because this assumption is violated and/or because they experience unanticipated external pressures and constraints. Cognitive studies presented in this and other papers show that humans cope with complex and unknown settings by modulating between near-optimal and satisficing solutions, including heuristics, by leveraging information value of available environmental cues that are possibly redundant. Using the benchmark inferential decision problem known as “treasure hunt”, this paper develops a general approach for investigating and modeling active perception solutions under pressure. By simulating treasure hunt problems in virtual worlds, our approach learns generalizable strategies from high performers that, when applied to robots, allow them to modulate between optimal and heuristic solutions on the basis of external pressures and probabilistic models, if and when available. The result is a suite of active perception algorithms for camera-equipped robots that outperform treasure-hunt solutions obtained via cell decomposition, information roadmap, and information potential algorithms, in both high-fidelity numerical simulations and physical experiments. The effectiveness of the new active perception strategies is demonstrated under a broad range of unanticipated conditions that cause existing algorithms to fail to complete the search for treasures, such as unmodelled time constraints, resource constraints, and adverse weather (fog).

The decision-making process involves various cognitive procedures influenced by the interplay between cognition, motivation, and attention, forming a complex neural framework. Attention is a fundamental cognitive element within decision-making mechanisms, and one of the conditions affecting the attentional system is attention deficit hyperactivity disorder (ADHD). Decision-making impairments in ADHD have significant economic consequences, necessitating effective policies and interventions to address this critical issue. Research from computational models and neuroscience suggests how cognitive functions’ workings and problems affect decision-making and provide insights into the neural implications of decision-making. This article explores the intersection of decision-making, ADHD, and neuroeconomics, highlighting research gaps, potential contributions, and implications for future policies.

This article examines how three types of experience—personal, related others, and unrelated others—influence decision-making. We present the complexities and nuances in using these experiential sources to suggest that personal experience is preferred to the other two sources. We discuss the implications of this preference for decision-making processes, especially in contexts involving transformative outcomes. To conclude, we discuss how people rely on other experiential sources when their preferred source is limited.

IntroductionThe growing competitiveness and the importance of data availability for organizations have created a demand for intelligent information systems capable of analyzing data to support strategy and decision-making. Organizations are generating more and more data due to new technologies associated with Industry 4.0 and Logistics 4.0, making it essential to transform this data into relevant information to streamline decision-making processes. This paper examines the influence of these technologies on gaining a competitive advantage, specifically in a logistics company, which is scarce in the literature.MethodsA case study was conducted in a Portuguese company using the Delphi method with 61 participants—employees who use the company’s integrated BI tool daily. The participants were presented with a questionnaire via the online platform Welphi, requiring qualitative responses to various statements based on the literature review and the results of semi-structured meetings with the company.ResultsThe study aimed to identify areas where employees believe more investment/ development is needed to optimize processes and improve the use of the BI tool in the future. The results indicate that BI is a crucial technology when aligned with a company’s objectives and needs, highlighting the necessity of top management’s involvement in optimizing the BI tool. Encouraging employees to use the BI tool emerged as a significant factor, underscoring the importance of leadership in innovative projects to achieve greater competitive advantage for the company.DiscussionThis study aims to understand the importance of Business Intelligence (BI) and how its functionalities should be adapted according to a company’s strategy and objectives to optimize decision-making processes. Thereby, the discussion focused on the essential role of BI technologies in leveraging the company’s competitive advantage.

IntroductionEffective delivery of healthcare depends on timely and accurate triage decisions, directing patients to appropriate care pathways and reducing unnecessary visits. Artificial Intelligence (AI) solutions, particularly those based on Large Language Models (LLMs), may enable non-experts to make better triage decisions at home, thus easing the healthcare system's load. We investigate how LLM-powered conversational agents influence non-experts in making triage decisions, further studying different persona profiles embedded via prompting.MethodsWe designed a randomized experiment where participants first assessed patient symptom vignettes independently, then consulted one of the two agent profiles—rational or empathic—for advice, and finally revised their triage ratings. We used linear models to quantify the effect of the agent profile and confidence on the weight of advice. We examined changes in confidence and accuracy of triage decisions, along with participants' perceptions of the agents.ResultsIn a study with 49 layperson participants, we found that persona profiles can be differentiated in LLM-powered conversational agents. However, these profiles did not significantly affect the weight of advice. Notably, less confident participants were more influenced by LLM advice, leading to larger adjustments to initial decisions. AI guidance improved alignment with correct triage levels and boosted confidence in participants' decisions.DiscussionWhile LLM advice improves triage recommendations accuracy, confidence plays an important role in its adoption. Our findings raise design considerations for human-AI interfaces, highlighting two key aspects: encouraging appropriate alignment with LLMs' advice and ensuring that people are not easily swayed in situations of uncertainty.

This study uses the newsvendor problem to investigate the correlations between thinking orientation, overconfidence, and economic outcome. We aim to shed light on possible interconnections between these variables and extend the existing conceptual models of thinking orientation and overconfidence. To test the conceptual model and the corresponding hypotheses empirically, we employed a laboratory experiment with 50 hypothetical decision periods in which 142 participants ordered a highly profitable product. We found compelling evidence that suggests overprecision as the mediating variable between thinking orientation and the economic outcome. Furthermore, this research offers some practical implications.

BackgroundAllergic rhinitis (AR) is the most common type of rhinitis, the treatment of which relies on relieving symptoms. Therefore, we aimed to assess the criteria that influence doctors’ decision-making in the process of drug selection for the treatment of allergic rhinitis based on quantitative, qualitative, and cost analyses.MethodsWe conducted a survey study with the participation of 300 allergologists. A self-developed questionnaire was presented during a computer-assisted telephone interview (CATI) according tostandard procedures. The contingency table underwent statistical analysis using the chi-square test with Cramer’s V. Results were considered statistically significant at p < 0.05.ResultsOur analyses showed that doctors most often prescribe intranasal glucocorticoids and oral antihistamines to treat allergic rhinitis in patients of all ages. The most common factor that affects the decision-making related to AR treatment was the efficiency of the drug. We found a significant relationship between factors and the main workplace (X-squared = 122.81, df = 90, p-value = 0.0123, Cramer’s V = 0.1787216), as well as voivodeship of the main workplace (X-squared = 440.75, df = 270, p-value = 2.378e-10, Cramer’s V = 0.1954731). In our study, respondents claimed that patients are willing to pay 31–50 PLN (∼€7- €11) monthly for the treatment of mild and moderate forms of AR, while they were willing to pay 51–100 PLN (∼€11–€22) for treatment of the severe AR form.ConclusionOur study confirms that the management of AR should be focused on the patient. One of the most important factors in choosing a drug is its effectiveness. Moreover, an important factor in the effective treatment of AR is the financial issue; as shown in our analysis, AR treatment costs can be a significant burden, especially for less wealthy citizens in Poland.

This study explored video-based decision-making and eye-movement behavior as a complementary method to assess the decision-making skills and knowledge of elite junior Australian Rules (AR) Football players. Performance was measured twice over an 18-month period. This approach tested a practical and reliable assessment of decision-making and game knowledge that does not contribute to physical training load. N = 59 participants were categorized based on their training age groups, U14 (N = 38, Mage13.37 ± 0.47) and U16 (N = 21, Mage14.80 ± 0.39). Participants watched 14 brief video clips and provided action choices while wearing eye-movement recording glasses that captured visual search patterns (e.g., fixations). Decision accuracy and speed of decision-making were also recorded. Participants with accurate decisions made significantly faster decisions compared to less skilled players (p < 0.001). Further, skilled participants had significantly fewer fixations of shorter duration compared to less skilled participants at both the initial and follow-up testing sessions (p < 0.0001). This suggests that eye-movement characteristics, remain a relatively stable measure over moderate periods of time. With the ability to differentiate between more and less skilled decision-makers, this proof-of-concept study proposes that examining eye movements in relation to decision-making and game knowledge is a viable tool for Talent Identification and Development (TID) to complement current measures. We provide a platform for further development and research in the quest for efficient and effective talent identification processes. [ABSTRACT FROM AUTHOR]

One of the cognitive abilities most affected by substance abuse is decisionmaking. Behavioral tasks such as the Iowa Gambling Task (IGT) provide a means to measure the learning process involved in decision-making. To comprehend this process, three hypotheses have emerged: (1) participants prioritize gains over losses, (2) they exhibit insensitivity to losses, and (3) the capacity of operational storage or working memory comes into play. A dynamic model was developed to examine these hypotheses, simulating sensitivity to gains and losses. The Linear Operator model served as the learning rule, wherein net gains depend on the ratio of gains to losses, weighted by the sensitivity to both. The study further proposes a comparison between the performance of simulated agents and that of substance abusers (n = 20) and control adults (n = 20). The findings indicate that as the memory factor increases, along with high sensitivity to losses and low sensitivity to gains, agents prefer advantageous alternatives, particularly those with a lower frequency of punishments. Conversely, when sensitivity to gains increases and the memory factor decreases, agents prefer disadvantageous alternatives, especially those that result in larger losses. Human participants confirmed the agents' performance, particularly when contrasting optimal and sub-optimal outcomes. In conclusion, we emphasize the importance of evaluating the parameters of the linear operator model across diverse clinical and community samples. [ABSTRACT FROM AUTHOR]

Psychological research on norms has shown that norms are highly relevant for individuals' decision-making. Yet, there is so far little understanding of how norms change over time. Knowledge about how norms change may help better understanding their potential for as well as limitations in guiding decision-making and changing behavior. The present work investigated change in individuals' cooperation norms. As an indicator of different underlying processes of norm change, the temporal dynamics of different types of norms were examined. It was assumed that participants' social norms are adapted quickly whenever the social situation changes, while personal norms change more slowly and gradually, abstracting part of the situational learning in interaction with one's personality. In an experimental study, participants played a repeated prisoner's dilemma game with artificial co-players representing a predominantly cooperative or uncooperative social setting, depending on the experimental condition. The condition was expected to affect slow learning of personal norms. Additionally, the cooperativeness of the social setting was varied repeatedly within conditions, expected to result in fast changes in social norms. Participants' personal and social norms were assessed throughout the game. As predicted, the temporal dynamics differed between norms with social norms changing quickly and personal norms more slowly. Personal norms strongly predicted behavioral decision-making and were predicted by situational and personality factors. Potential qualitative differences of the underlying norm change processes are discussed. [ABSTRACT FROM AUTHOR]

The Energy-Water-Food (EWF) nexus is a complex and multidimensional system, in which the energy, water and food resources are strongly interconnected. EWF nexus systems are seriously threatened by natural hazards (e.g., climate change and extreme weather events) along with other human-driven threats, including rapid population growth, urbanization, terrorism, and geopolitical uncertainty. As such, integrated analysis, as encouraged by the EWF nexus can facilitate the identification of essential connections and potential conflicts that may arise in the planning and operation of resource systems. Moreover, in order to consider immediate shocks and long-term pressures, it is imperative to prioritize the strengthening of EWF system resilience by incorporating robust and efficient resource management strategies, which consider various dimensions of sustainability and security such as technical, environmental, economic, and societal aspects. Decentralization is one concept that has the potential of improving the resilience of nexus systems faced to the multiple risks governing them through reducing single points of failure and enabling swifter responses to sudden shocks and continuous volatilities. However, in order to achieve a holistic system resilience through decentralization, the assessment of the different risks impacting each nexus sector is fundamental, yet it can be particularly challenging. Therefore, the objective of this study is to review the currently available resilience assessment methods for the EWF nexus system. The systematic literature review will connect various assessment methods used within decentralization studies that are applied to improve the resilience performance of the EWF nexus system. A total of 84 journal papers were evaluated. The review demonstrates that the deployment of multi-criteria decision-making framework based on composite indicators can be effective in addressing risks and uncertainties within EWF systems. Furthermore, findings of this review illustrate complementary connections between decentralization and resilience concepts, which when integrated with the EWF nexus approach, can be effectively utilized for integrated sustainable resource management. [ABSTRACT FROM AUTHOR]

By definition, ill and injured animals are on the negative valence of animal welfare. For beef cattle kept in feedlot settings, advances in cattle health management have resulted in a greater understanding and prevention of illness and injury. However, the management of cattle once they become ill and injured is an understudied area, and there are gaps in knowledge that could inform evidence-based decision-making and strengthen welfare for this population. The aim of this review is to provide a comprehensive overview of the acquired knowledge regarding ill and injured feedlot cattle welfare, focusing on existing knowledge gaps and implications for hospital and chronic pen management and welfare assurance. Ill and injured feedlot cattle consist of acutely impaired animals with short-term health conditions that resolve with treatment and chronically impaired animals with long-term health conditions that may be difficult to treat. A literature search identified 110 articles that mentioned welfare and ill and injured feedlot cattle, but the population of interest in most of these articles was healthy cattle, not ill and injured cattle. Articles about managing ill and injured cattle in specialized hospital (n = 12) or chronic (n = 2) pens were even more sparse. Results from this literature search will be used to outline the understanding of acutely and chronically ill and injured feedlot cattle, including common dispositions and welfare considerations, behavior during convalescence, and strategies for identifying and managing ill and injured cattle. Finally, by working through specific ailments common in commercial feedlot environments, we illustrate how the Five Domains Model can be used to explore feelings and experiences and subsequent welfare state of individual ill or injured feedlot cattle. Using this approach and our knowledge of current industry practices, we identify relevant animal-based outcomes and critical research questions to strengthen knowledge in this area. A better understanding of this overlooked topic will inform future research and the development of evidencebased guidelines to help producers care for this vulnerable population. [ABSTRACT FROM AUTHOR]

Researchers investigating the psychological effects of choice have provided extensive empirical evidence that having choice comes with many advantages, including better performance, more motivation, and greater life satisfaction and disadvantages, such as avoidance of decisions and regret. When the decision task difficulty exceeds the natural cognitive resources of human mind, the possibility to choose becomes more a source of unhappiness and dissatisfaction than an opportunity for a greater well-being, a phenomenon referred to as choice overload. More recently, internal and external moderators that impact when choice overload occurs have been identified. This paper reviews seminal research on the advantages and disadvantages of choice and provides a systematic qualitative review of the research examining moderators of choice overload, laying out multiple critical paths forward for needed research in this area. We organize this literature review using two categories of moderators: the choice environment or context of the decision as well as the decision-maker characteristics. [ABSTRACT FROM AUTHOR]

Introduction: The brain mechanisms of deceptive behavior are relatively well studied, and the key brain regions involved in its processing were established. At the same time, the brain mechanisms underlying the processes of preparation for deception are less known. Methods: We studied BOLD-signal changes during the presentation of the opponent's feedback to a previous deceptive or honest action during the computer game. The goal of the game was to mislead the opponent either by means of deception or by means of telling the truth. Results: As a result, it was shown that several brain regions that were previously demonstrated as involved in deception execution, such as the left anterior cingulate cortex and anterior insula, also underlie processes related to deception preparation. Discussion: The results obtained also allowed us to suggest that brain regions responsible for performance monitoring, intention assessment, suppression of non-selected solutions, and reward processing could be involved in shaping future action selection and preparation for deception. By shedding light on the brain mechanisms underlying deception, our study contributes to a deeper understanding of this complex cognitive process. Furthermore, it emphasizes the significance of exploring brain mechanisms governing the choice between deception and truth at various stages of decision-making. [ABSTRACT FROM AUTHOR]

Reinforcement Learning (RL) is a method that teaches agents to make informed decisions in diverse environments through trial and error, aiming to maximize a reward function and discover the optimal Q-learning function for decisionmaking. In this study, we apply RL to a rule-based water management simulation, utilizing a deep learning approach for the Q-learning value function. The trained RL model can learn from the environment and make real-time decisions. Our approach offers an unbiased method for analyzing complex watershed scenarios, providing a reward function as an analytical metric while optimizing decisionmaking time. Overall, this work underscores RL's potential in addressing complex problems, demanding exploration, sequential decision-making, and continuous learning. External variables such as policy shifts, which are not readily integrated into the model, can substantially influence outcomes. Upon establishing a model with the requisite minimal states and actions, the subsequent learning process is relatively straightforward, depending on the selection of appropriate RL model algorithms. Its application depends on the specific problem. The primary challenge in this modeling approach lies in model definition, specifically in devising agents and actions that apply to complex scenarios. Our specific example was designed to address recent decision-making challenges related to constructing dams due to water scarcity. We present two examples: one from a nationwide perspective in Mexico and the other focused on Baja California Sur, the state with the highest water stress. Our results demonstrate our capability to prioritize watersheds effectively for the most significant benefits, particularly dam construction. [ABSTRACT FROM AUTHOR]

Aims: This investigation aimed to clarify the intricate relationship among depression, cognitive function, adverse childhood experiences (ACEs), and their combined influence on methamphetamine use disorder (MUD). Methods: Utilizing a battery of psychological tests, this study ascertained the impact of ACEs on the condition of 76 people with MUD who meet the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, aged 42.17 on average. The Iowa Gambling Task (IGT), Conners' Continuous Performance-II (CPT-II), the self-report Severity of Dependence Scale (SDS), and the Beck Depression Inventory-II (BDI-II) were used for these evaluations. Individuals involved in the study were categorized into two discrete cohorts, mild (ME) and severe (SE), based on the extent of their ACEs exposure. This study employed the PROCESS regression, the independent t-test andχ2 tests for the analysis. Results: The findings revealed notable discrepancies in the psychological consequences between the two groups with different degrees of ACEs; however, no substantial differences were observed in the demographic parameters. The SE group exhibited elevated BDI-II scores, more evident indications of MUD, and a higher degree of CPT-II cognitive perseveration. The PROCESS model revealed that cognitive perseveration moderated the impact of depression on ACEs and subjective MUD severity, explaining 20.2% of the variance. The ACEs and depression predicted 28.6% of the variance in MUD symptoms. However, no statistically significant differences were detected between the two groups regarding the parameters in the IGT-2 assessment. Conclusions: These results indicate that the interaction between cognitive and depressive factors mediates the effect of ACEs on subjective MUD severity but not on MUD symptoms. The ACEs significant impact on mental health severity perception is explained by cognitive and depressive factors. This implies that MUD treatment and rehabilitation should address cognitive dysfunction and developmental trauma. [ABSTRACT FROM AUTHOR]

Introduction: The electricity generated from nuclear plants and petroleum- based products has a negative influence on the environment as a whole. It has shown the utility to search out and promote the utilization of renewable, environmentally friendly, and sustainable energy sources such as solar, wind, and geothermal. Nowadays, Wind energy resource has quickly emerged as the world's fastest-growing energy source. Methods: However, the selection of the most suitable places for developing a wind farm is a crucial challenge that can be seen as a problem of site selection, which involves numerous conflicting variables. Therefore, it is classified as an MCDM (multi-criteria decision-making) problem. The main objective of this research is to determine the best locations in Burundi for the installation of wind farms. The Fuzzy Analytic Hierarchy Process (FAHP) was used to weigh the criteria considering their relative importance. This study considers several key factors when determining the optimal location for a wind farm. These factors include wind speed, slope, proximity to the grid network, distance to roads, and land use/land cover (LULC). Furthermore, a geographic information system (GIS) is utilized to generate the final suitability wind farm locations map. Results and Discussion: The obtained results indicate that 20.91% of the whole study area is suitable nevertheless, only 1.96% is tremendously suitable for wind turbine placement. The western part of Burundi is the optimal area for constructing a wind farm, and the most is in Lake Tanganyika. [ABSTRACT FROM AUTHOR]

At present, the marine ecological environment is facing enormous pressure from human activities, and there is an urgent need for coordinated governance by multiple entities to ensure that the marine ecological environment can continuously meet the needs of sustainable development. Marine ecological environmental governance plays multiple roles in the sustainable development of the ocean characteristics. Most existing studies have explored this field from the perspective of the government and public, while failing to adequately account for the factors influencing enterprises' participation in marine ecological environmental governance. This paper is an effort to provide some empirical research on the influencing factors of enterprises' participation in marine ecological environmental governance. Based on existing literature, empirical research (213 middle managers were surveyed from 68 coastal enterprises in Zhejiang, China), this study extracts eight core factors that influence corporate participation in marine ecosystems and uses the Fuzzy Decision-making Trial and Evaluation Laboratory approach (Fuzzy DEMATEL). Furthermore, experts from Chinese backgrounds elucidated the complex interdependencies among the factors, based on which key influencing factors were identified. The empirical results indicate that government attention and support, legal and regulatory requirements, and cost-benefit accounting have a positive net effect on corporate participation in marine ecosystem management; when these factors are improved, they drive improvements in other factors(Corporate Capital Capability, Corporate Social Responsibility, Government Enforcement and Appraisal, The Attention of Corporate Leaders, Corporate Internal Management System). Additionally, interviews with Chinese business people support the robustness of the findings and suggest that policymakers cannot ignore government enforcement and assessment efforts. Overall, the study findings can help advance corporate participation in marine environmental governance. [ABSTRACT FROM AUTHOR]

Effective methods to improve decision-making in sports officiating, particularly with the current and ongoing issues with in-person training, means new remote training methods must be developed. Traditional training of officials occurs primarily as "in-person coaching" at matches, with supporting training manuals and 2D broadcast analysis. However, live matches present difficulties in implementation, while manuals and 2D broadcast videos may not sufficiently ensure learning transfers to real situations. Due to its ease of use, first-person perspective, and ability to analyze live and post-event remotely, 360° virtual reality video technology (360° VR) offers an alternative technological solution for developing decision-making accuracy for sports officials across multiple sports. This study sought to assess the ecological validity (EV) of using 360° VR technology to enable remote teaching of decision-making. Decision-making quality and accuracy in softball umpires were similar when using 360° VR and the traditional method (2D broadcast footage), but 360° VR received significantly higher EV values than the 2D broadcast videos. In addition, interviewed participants expressed excitement about using 360° VR to augment traditional umpiring manuals and rulebooks. The results show that 360° VR has the potential to enhance or replace traditional remote learning methods for decision-making in softball umpires and allow softball learning to reach a much wider umpire audience. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has brought about significant changes to the life of most individuals, worldwide. This study explores the cultural factors influencing decision-making during the pandemic, and is part of the CORNER Project, funded by the Research Council of Norway, aimed at understanding institutional response in the early phases of the Covid-19 emergency in Norway, Sweden, and Italy. Semi-structured interviews with key political-administrative leaders in Italy (N = 35) were conducted and content-analyzed, allowing the identification of the underlying cultural dynamics that played a role in these decisions. Thematic analysis was used to assess the influence of cultural factors on the crisis management and early reaction of institutions and citizens to the spread of Covid. In line with previous studies, and as expected, the individualism vs. collectivism dimension can explain differential health outcomes during the outbreak. In this paper we argue that individualism-collectivism cultural values can also play a pivotal role in public compliance with Covid-19 restrictions, and psychological responses during the pandemic. [ABSTRACT FROM AUTHOR]

Sometimes, policing requires a quick and correct assessment of potentially hazardous situations. The training of tactical gaze control and visual attention, and its positive impact on efficient shoot/don’t shoot decisions in police cadets’ use of firearms has recently been demonstrated. On this basis, we designed an individual video-based police firearms training that was grounded on the Four-Component Instructional Design Model (4C/ID). We shifted toward an individual blended learning approach where we applied an intervention training focused on situational awareness, tactical gaze control, and visual attention. In a preregistered lab experiment, N  =  45 senior police officers were randomly allocated to the intervention training or an active control training that resembled a traditional police firearms training. Both groups watched a self-produced educational video before proceeding to the practical training in our indoor firing range. In a pre- and post-test, they engaged in realistic shoot/don’t shoot video scenarios. Both groups did very well regarding decision-making, the optimal muzzle position, and the tactical conduct to keep both eyes open before shooting. Although both groups performed on a comparable level in the pre-test’s shoot scenarios, the intervention group significantly improved their response times and time until the first hit. Overall, we were able to provide an adapted, didactically based police firearms training that supplements current standards. We demonstrated that experts are still susceptible to innovative training concepts and therefore substantiate the recommendation to devote more attention to approaches that emphasize the importance of situational awareness, tactical gaze control, and visual attention in police firearms training. [ABSTRACT FROM AUTHOR]