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Real-world decisions often involve partial ambiguity, where the complete picture of potential risks is unclear. In such situations, individuals must make choices by balancing the value of available information against the uncertainty of unknown risks. Our study investigates this challenge by examining how people navigate the trade-off between the favorability of limited evidence and the degree of ambiguity when making decisions under partial ambiguity. Participants (n = 77) engaged in a task where the level of ambiguity (small, medium, and large) and the favorability of the evidence (asymmetrically positive, neutral, and asymmetrically negative) were manipulated in a 3 × 3 design. We measured their attitude of ambiguity in each condition. The key finding reveals a bias in how participants perceived the unknown. They reacted to the unknown differently depending on the initial clues, filling in the missing information in a way that contradicted the evidence. When faced with positive evidence, participants were less tolerant of ambiguity than negative evidence. This means people were more careful when they received good news but less cautious when they received bad news. This bias was particularly pronounced when the ambiguity was low. [ABSTRACT FROM AUTHOR]

Senior police officers' tactical gaze control and visual attention improve with an individual video-based police firearms training. To validate the efficacy of said intervention training, a previous experiment was systematically replicated with a sample of N = 52 second-year police cadets. Participants were randomly assigned to the intervention training that focused on situational awareness, tactical gaze control, and visual attention, or an active control training that addressed traditional marksmanship skills. In a pre- and post-test, they had to engage in dynamic shoot/don't shoot video scenarios in an indoor firing range. Overall, the previous findings were replicated: Baseline levels of performance were elevated, yet the intervention group significantly improved their response time and time until the first hit. False positive decision-making cannot be reported at all; false negatives were marginal in the pre-test and eliminated after training. Further, the outcomes of the previous sample of senior officers and the present sample of cadets are compared and lead to the conclusion that the presented approach is a valuable extension of current training standards for both senior police officers and police cadets. [ABSTRACT FROM AUTHOR]

Accurate interoceptive processing in decision-making is essential to maintain homeostasis and overall health. Disruptions in this process have been associated with various psychiatric conditions, including depression. Recent studies have focused on nutrient homeostatic dysregulation in depression for effective subtype classification and treatment. Neurophysiological studies have associated changes in appetite in depression with altered activation of the mesolimbic dopamine system and interoceptive regions, such as the insular cortex, suggesting that disruptions in reward processing and interoception drive changes in nutrient homeostasis and appetite. This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. Simulations of altered interoception demonstrated behaviors similar to those of depression subtypes, such as appetite dysregulation. Specifically, reduced interoception led to decreased reward system activity and increased punishment, mirroring the neuroimaging study findings of decreased appetite in depression. Conversely, increased interoception was associated with heightened reward activity and impaired goal-directed behavior, reflecting an increased appetite. Furthermore, effects of interoception manipulation were compared with traditional reinforcement learning parameters (e.g., inverse temperature β and delay discount γ), which represent cognitive-behavioral features of depression. The results suggest that disruptions in these parameters contribute to depressive symptoms by affecting the underlying homeostatic regulation. Overall, this study findings emphasize the importance of integrating interoception and homeostasis into decision-making frameworks to enhance subtype classification and facilitate the development of effective therapeutic strategies. [ABSTRACT FROM AUTHOR]

Skilful monsoon onset forecasts are highly sought after in West Africa, due to the importance of monsoon onset for supporting agriculture, disease prevalence and energy provision. With the sub-seasonal timescale bridging the gap between weather and seasonal forecasts, sub-seasonal forecasts have the potential to provide useful decision-making information about the onset of the monsoon rainfall. This study explores sub-seasonal monsoon onset forecasts over Ghana using the European Centre for Medium Range Weather Forecasting (ECMWF) operational ensemble prediction systems. Three commonly used methods for defining monsoon onset are compared, and the benefits, challenges, and potential of real-time, sub-seasonal onset forecasting using these methods are examined. Monsoon onset forecasting at sub-seasonal timescales, and associated decision-making with shorter-term information can be challenging due to the typically single occurrence of rainfall onset within a season. Sub-seasonal forecasts of monsoon onset are shown to be particularly useful for confirming onset occurrence, at least 1–2 weeks earlier than when observations are used. Earlier confirmation of monsoon onset provided by sub-seasonal forecasts, has the potential for earlier decision-making and action that would positively impact sectors such as agriculture. [ABSTRACT FROM AUTHOR]

Balancing various objectives and navigating uncertainties, reducing CO2 emissions and enhancing energy efficiency in industry presents a complex challenge. While previous studies primarily focused on conventional optimization methods, this research introduces an innovative approach: a multi-criteria optimization framework tailored to address uncertainties. The primary objective is to optimize energy consumption, minimize emissions, and improve cost efficiency simultaneously within the petrochemical industry. To effectively manage uncertain variables, this study integrates decision-making simulations and expert insights through a hybrid methodology to yield optimal outcomes. Employing three distinct preference categories, the model formulates comprehensive decision-making strategies. Empirical findings underscore the model's efficacy in reducing CO2 emissions, bridging crucial gaps in existing research, and advocating sustainable practices in the sector. Departing from conventional methodologies, this research leverages advanced decision-making techniques adept at handling uncertainty. The framework identifies pivotal emission sources and advocates economically viable reduction strategies. Its adaptability enriches our comprehension of emission challenges by considering diverse factors and expert perspectives. Professional assessments affirm the model's success and propose a Coding-Based Prototype as a strategic tool for addressing uncertainties. These results underscore the imperative for policy reforms, such as embracing carbon capture technologies, to bolster global sustainability and foster enduring growth in the industrial domain. [ABSTRACT FROM AUTHOR]

Introduction: As life expectancy and expected years in retirement rise and family structures change, the need for personal financial protections, such as long term care (LTC) insurance, in managing financial risks associated with later life is expected to increase. Roughly half of American households are at risk of not being able to maintain their present standards of living post-retirement. Because both public and private health insurance programs typically do not cover LTC needs, which are associated with significant costs, the potential demand for LTC further exacerbates the retirement savings crisis. Methods: Using an original survey experiment, in this high-powered study (N = 1,450), we examine the impact of a 2×3 framing intervention on participants' attitudes, emotions, and behavioral intentions toward LTC insurance. Results: Results indicated that direct framing effects were present for people's reported emotions: those who received a loss frame (compared to a gain frame) were more likely to report anxiety-related emotions, and those who were exposed to a care choice narrative frame (compared to a family or a financial frame) were more likely to report calmness-related emotions. There were no significant interaction effects between loss/gain and narrative frames. A mediation analysis suggested that the framing impacts acted through these two different emotional pathways to yield more positive attitudes toward and behavioral intentions around LTC. Implications: The study results underscore the need to examine how different frames affect emotional arousal as a potential pathway to impacting attitudes and behaviors. We found that both a loss framing and a narrative framing, operating through different emotional pathways, have the potential to be helpful to nudge people to hedge against a financial risk associated with older age. [ABSTRACT FROM AUTHOR]

Introduction: The rate of sexual activity among adolescents is very high, with serious repercussions such as human immunodeficiency virus (HIV) and sexually transmitted diseases. Understanding the factors that influence adolescents' engagement in sexual activity is crucial for promoting healthy sexual attitudes and behaviors in schools, sex education programs, communities, and families. This study aimed to examine the factors influencing sexual decision-making among Cambodian adolescents. Methods: In accordance with the Standards for Reporting Qualitative Research (SRQR), this study used a descriptive qualitative methodology with individual interviews. The participants in the study were 30 Cambodian adolescents (15 males and 15 females) who were all unmarried and sexually active. They were recruited using various methods, including social networking services, and interviewed to explore their sexual decision-making processes. Results: The analysis revealed that the decision-making process was influenced by both internal and external factors. Internal factors included sexually explicit Internet material and arousal from sexy outfits, while external factors included foreign vs. Khmer culture, the surrounding environment including community, peers, and family, and educational advice received at school. Gender differences were noted in responses to stimuli like sexy outfits and perceptions of cultural norms. Conclusions: This study underscores the complexity of adolescent sexual decision-making in Cambodia. It highlights the need for sex education that is not only comprehensive but also culturally sensitive, addressing the diverse influences on these adolescents. Future research should include a broader demographic group, including rural adolescents, to gain more comprehensive insights. Implications for practice: This study uncovers how cultural norms, peers, and the media impact sexual behaviors, emphasizing the significant gender differences in these aspects. The findings shed light on the necessity of culturally sensitive and comprehensive sex education and the urgent need for tailored approaches to health promotion and education. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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 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]

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]

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]

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]

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]

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]

Senior police officers' tactical gaze control and visual attention improve with an individual video-based police firearms training. To validate the efficacy of said intervention training, a previous experiment was systematically replicated with a sample of N = 52 second-year police cadets. Participants were randomly assigned to the intervention training that focused on situational awareness, tactical gaze control, and visual attention, or an active control training that addressed traditional marksmanship skills. In a pre- and post-test, they had to engage in dynamic shoot/don't shoot video scenarios in an indoor firing range. Overall, the previous findings were replicated: Baseline levels of performance were elevated, yet the intervention group significantly improved their response time and time until the first hit. False positive decision-making cannot be reported at all; false negatives were marginal in the pre-test and eliminated after training. Further, the outcomes of the previous sample of senior officers and the present sample of cadets are compared and lead to the conclusion that the presented approach is a valuable extension of current training standards for both senior police officers and police cadets.

Accurate interoceptive processing in decision-making is essential to maintain homeostasis and overall health. Disruptions in this process have been associated with various psychiatric conditions, including depression. Recent studies have focused on nutrient homeostatic dysregulation in depression for effective subtype classification and treatment. Neurophysiological studies have associated changes in appetite in depression with altered activation of the mesolimbic dopamine system and interoceptive regions, such as the insular cortex, suggesting that disruptions in reward processing and interoception drive changes in nutrient homeostasis and appetite. This study aimed to explore the potential of computational psychiatry in addressing these issues. Using a homeostatic reinforcement learning model formalizing the link between internal states and behavioral control, we investigated the mechanisms by which altered interoception affects homeostatic behavior and reward system activity via simulation experiments. Simulations of altered interoception demonstrated behaviors similar to those of depression subtypes, such as appetite dysregulation. Specifically, reduced interoception led to decreased reward system activity and increased punishment, mirroring the neuroimaging study findings of decreased appetite in depression. Conversely, increased interoception was associated with heightened reward activity and impaired goal-directed behavior, reflecting an increased appetite. Furthermore, effects of interoception manipulation were compared with traditional reinforcement learning parameters (e.g., inverse temperature β and delay discount γ), which represent cognitive-behavioral features of depression. The results suggest that disruptions in these parameters contribute to depressive symptoms by affecting the underlying homeostatic regulation. Overall, this study findings emphasize the importance of integrating interoception and homeostasis into decision-making frameworks to enhance subtype classification and facilitate the development of effective therapeutic strategies.

Skilful monsoon onset forecasts are highly sought after in West Africa, due to the importance of monsoon onset for supporting agriculture, disease prevalence and energy provision. With the sub-seasonal timescale bridging the gap between weather and seasonal forecasts, sub-seasonal forecasts have the potential to provide useful decision-making information about the onset of the monsoon rainfall. This study explores sub-seasonal monsoon onset forecasts over Ghana using the European Centre for Medium Range Weather Forecasting (ECMWF) operational ensemble prediction systems. Three commonly used methods for defining monsoon onset are compared, and the benefits, challenges, and potential of real-time, sub-seasonal onset forecasting using these methods are examined. Monsoon onset forecasting at sub-seasonal timescales, and associated decision-making with shorter-term information can be challenging due to the typically single occurrence of rainfall onset within a season. Sub-seasonal forecasts of monsoon onset are shown to be particularly useful for confirming onset occurrence, at least 1–2 weeks earlier than when observations are used. Earlier confirmation of monsoon onset provided by sub-seasonal forecasts, has the potential for earlier decision-making and action that would positively impact sectors such as agriculture.

Balancing various objectives and navigating uncertainties, reducing CO2 emissions and enhancing energy efficiency in industry presents a complex challenge. While previous studies primarily focused on conventional optimization methods, this research introduces an innovative approach: a multi-criteria optimization framework tailored to address uncertainties. The primary objective is to optimize energy consumption, minimize emissions, and improve cost efficiency simultaneously within the petrochemical industry. To effectively manage uncertain variables, this study integrates decision-making simulations and expert insights through a hybrid methodology to yield optimal outcomes. Employing three distinct preference categories, the model formulates comprehensive decision-making strategies. Empirical findings underscore the model’s efficacy in reducing CO2 emissions, bridging crucial gaps in existing research, and advocating sustainable practices in the sector. Departing from conventional methodologies, this research leverages advanced decision-making techniques adept at handling uncertainty. The framework identifies pivotal emission sources and advocates economically viable reduction strategies. Its adaptability enriches our comprehension of emission challenges by considering diverse factors and expert perspectives. Professional assessments affirm the model’s success and propose a Coding-Based Prototype as a strategic tool for addressing uncertainties. These results underscore the imperative for policy reforms, such as embracing carbon capture technologies, to bolster global sustainability and foster enduring growth in the industrial domain.

IntroductionThe rate of sexual activity among adolescents is very high, with serious repercussions such as human immunodeficiency virus (HIV) and sexually transmitted diseases. Understanding the factors that influence adolescents’ engagement in sexual activity is crucial for promoting healthy sexual attitudes and behaviors in schools, sex education programs, communities, and families. This study aimed to examine the factors influencing sexual decision-making among Cambodian adolescents.MethodsIn accordance with the Standards for Reporting Qualitative Research (SRQR), this study used a descriptive qualitative methodology with individual interviews. The participants in the study were 30 Cambodian adolescents (15 males and 15 females) who were all unmarried and sexually active. They were recruited using various methods, including social networking services, and interviewed to explore their sexual decision-making processes.ResultsThe analysis revealed that the decision-making process was influenced by both internal and external factors. Internal factors included sexually explicit Internet material and arousal from sexy outfits, while external factors included foreign vs. Khmer culture, the surrounding environment including community, peers, and family, and educational advice received at school. Gender differences were noted in responses to stimuli like sexy outfits and perceptions of cultural norms.ConclusionsThis study underscores the complexity of adolescent sexual decision-making in Cambodia. It highlights the need for sex education that is not only comprehensive but also culturally sensitive, addressing the diverse influences on these adolescents. Future research should include a broader demographic group, including rural adolescents, to gain more comprehensive insights.Implications for practiceThis study uncovers how cultural norms, peers, and the media impact sexual behaviors, emphasizing the significant gender differences in these aspects. The findings shed light on the necessity of culturally sensitive and comprehensive sex education and the urgent need for tailored approaches to health promotion and education.

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).

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]

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]

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]

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]