Search Results (1,336)

Wine represents one of the most complex food matrices from a sensory perspective, as its appreciation emerges from the interaction between chemical composition, perceptual mechanisms, and contextual influences. Contemporary research in oenology and sensory science increasingly recognizes wine evaluation as an integrated perceptual event shaped by cognition, memory, and affect, rather than a simple response to aroma or flavor cues. Live music is widely used in hospitality settings to enhance consumer experience; however, its specific influence on wine appreciation and emotional responses remains insufficiently explored, particularly in real-world contexts. This study investigates how two contrasting musical atmospheres—melancholic/relaxing and upbeat/motivational—modulate hedonic evaluations and emotional profiles during public wine tastings, compared with a no-music condition. Data were collected across five live tasting events (5 Wednesdays of Emotions) using structured questionnaires that included hedonic ratings and multidimensional emotional measures. Statistical analyses were conducted using non-parametric tests, meta-analytic p-value combination, and cumulative link mixed models for ordinal data. The presence of music significantly enhanced overall wine appreciation compared to the silent condition, although the magnitude and direction of the effect varied across individuals and musical styles. Upbeat/motivational music generally produced stronger and more consistent increases in liking than melancholic/relaxing music. Emotional responses—particularly positive surprise—emerged as key mediators of hedonic improvement and showed strong associations with overall liking. Preference profiling revealed distinct response patterns, indicating that auditory modulation of wine perception is not uniform across consumers. These findings support a crossmodal interpretation in which music shapes wine appreciation primarily through emotion-based and expectancy-related mechanisms rather than through direct sensory enhancement. By demonstrating these effects in ecologically valid tasting environments, the study highlights the role of auditory context as a meaningful component of multisensory wine experiences. Full article

Sustainable service excellence in globalized industries requires organizations to develop workforce capabilities that support long-term relationship-building, cultural respect, and effective cross-cultural communication. This study examines how cultural intelligence functions as a mechanism for sustainable cross-cultural workforce development by investigating relationships among individual cultural values, cultural intelligence dimensions, and influence tactics among airline cabin crew members. Integrating Hofstede’s cultural dimensions framework, Ang and colleagues’ cultural intelligence model, and Yukl’s influence tactics taxonomy, we test a comprehensive mediation model using survey data from six hundred and sixty-three cabin crew members employed by international airlines operating in Turkey. The findings reveal that collectivism, long-term orientation, and uncertainty avoidance positively predict cultural intelligence development, creating foundations for sustainable cross-cultural competence. Cultural intelligence dimensions demonstrate differentiated effects on influence tactics, with metacognitive and behavioral cultural intelligence enhancing rational persuasion, behavioral cultural intelligence exclusively predicting relational tactics, and complex competitive mediation patterns for coercive tactics wherein motivational cultural intelligence reduces pressure-based influence while cognitive and behavioral dimensions increase strategic assertiveness. Cultural values directly influence tactics beyond cultural intelligence effects, with uncertainty avoidance most strongly predicting both rational and relational approaches that support relationship sustainability, while masculinity and power distance drive coercive tactics that may undermine long-term service relationships. These findings demonstrate that cultural intelligence functions as a multidimensional mediating mechanism with sometimes opposing effects, challenging assumptions that cross-cultural competencies uniformly produce sustainable outcomes. The research contributes to sustainable human resource management theory by illuminating how cultural socialization influences behavioral outcomes through complex psychological pathways, while offering practical guidance for aviation industry recruitment, training, and performance management systems seeking to build sustainable cross-cultural service capabilities. By revealing that certain cultural intelligence dimensions can enable both relationship-building and strategic coercion, the study highlights the importance of coupling cross-cultural skill development with ethical frameworks and motivational engagement to ensure that enhanced cultural capabilities support rather than undermine sustainable, respectful cross-cultural service relationships. Full article

The study investigates the impact of green shared vision and green intrinsic motivation on pro-environmental behaviour in the workplace, utilising Self-Determination Theory and Social Cognitive Theory. Despite the acknowledgement of a green shared vision as a vital organisational factor for sustainability, there is a lack of empirical studies that explain the psychological mechanisms that promote employees’ pro-environmental behaviour. This study investigated a parallel mediation model where green mindfulness and green intrinsic motivation successively mediated the correlations. Data were collected via an online survey from 154 full-time employees working in the private sector in Romania across diverse industries between October 2024 and March 2025. The hypotheses of the study were tested by using partial least squares structural equation modelling (PLS-SEM). The results demonstrate that a green shared vision significantly affects workplace pro-environmental behaviour. Additionally, the study indicates a notable parallel mediation effect: a green shared vision promotes green mindfulness, which, in turn, fosters green intrinsic motivation, ultimately resulting in enhanced pro-environmental behaviour. The study underlines the significance of shared vision, mindfulness, and intrinsic motivation as fundamental behavioural processes supporting sustainability-oriented actions by organisations, based on insights from environmental psychology and organisational behaviour. Full article

Dogs show exceptional olfactory sensitivity and are widely used in medical, rescue, military, and forensic applications, yet the determinants of individual and breed-level scent-work performance remain incompletely characterized. This review integrates evidence from the anatomy and physiology of the canine olfactory organ, neurobiological mechanisms of odor transduction and coding, and links between olfaction, memory, and emotion, alongside molecular genetics, evolution, domestication, and selective breeding. We synthesize findings indicating that complex nasal turbinates and specialized airflow patterns enhance odorant capture, while olfactory bulb circuitry and downstream connections to limbic and frontal networks support discrimination, learning, and affective modulation. Comparative and breed-focused studies suggest that skull morphology and breeding priorities can alter olfactory capacity, with shortened nasal anatomy associated with reduced functional potential in some lines. In applied contexts, detection success is strongly shaped by behavioral traits such as motivation, persistence, independence, and reward value, as well as by physical condition and environmental stressors that can impair search efficiency. Emerging literature further suggests that the gastrointestinal and upper airway microbiome, together with diet, housing, temperature, and workload, may influence sensory and cognitive readiness, although direct causal links to detection outcomes remain limited. Overall, canine olfactory performance reflects interactions among genetic–anatomical capacity, neurobehavioral factors, and environment, underscoring the value of standardized selection, training, welfare management, and future integrative research. Full article

Problem Statement: Two global trends, including aging populations and the acceleration of global warming, are increasing the risk of heat-related illness, challenging the health of populations, and the sustainability of healthcare systems. Global warming refers to the increase in the Earth’s average surface temperature, generally attributed to the greenhouse effect, which is occurring at three times the rate of the pre-industrial era. The global population of older adults, defined here as individuals aged 60 and over, is expected to reach over 2 billion by mid-century. This population is particularly vulnerable to heat-related illness, specifically disruption of thermoregulation from excessive exposure to environmental heat due to metabolic and cognitive changes associated with aging. Objectives: This review examines heat-related illness and its impact on older adults within a socio-ecological framework, considering both drivers and mitigation strategies related to global warming, the built environment, social determinants of health, healthcare system responses, and the individual. The authors were motivated to create a conceptual model within this framework drawing on their lived experiences as healthcare providers interacting with older adults in a large urban area of the southwestern US, known for its extreme heat and extensive heat island effects. Based on this framework, the authors suggest actionable strategies supported by the literature to reduce the risks of morbidity and mortality. Methods: The literature search utilized a wide lens to identify evidence supporting various aspects of the hypothesized framework. In this sense, this review differs from systematic and scoping reviews, which seek a complete synthesis of the available literature or a mapping of the evidence. The first author conducted the literature search and synthesis, while the second and third authors reviewed and added publications to the initial search and conceptualized the socio-ecological framework. Discussion: This study is unique in its focus on a global trend that threatens the well-being of a growing population. The population health focus underscores social determinants of health and limitations of existing healthcare systems to guide healthcare providers in reducing older adults’ vulnerability to heat-related illness. This includes patient education regarding age-related declines in extreme heat tolerance, safe and unsafe physical activity habits, the impact of prescription drugs on heat tolerance, and, importantly, identifying the symptoms of heatstroke, which is a medical emergency. Additional strategies for improving survivability and quality of life for this vulnerable population include improved emergency response systems, better social support, and closer attention to evidence-based treatment for heat-related health conditions. Full article

Background/Objectives: The dopaminergic system regulates motivation, executive functions, motor learning, and emotional responses—processes that are key in both sport and esports. Although many studies analyse dopaminergic gene polymorphisms, their impact on psychophysical predispositions remains unclear. This narrative review aims to summarise current knowledge about the mechanisms of dopamine action and genetic determinants that may influence athletic and cognitive performance. Methods: The PubMed, Scopus, and Web of Science databases (publications from January 2010 to December 2025) were searched using keywords related to the DRD1–DRD5, COMT, SLC6A3/DAT1, and TH genes, as well as the terms ‘sport’ and ‘esport.’ Studies of athletes were included in which the relationship between dopaminergic polymorphisms and motivational and personality traits was assessed, and the results of neuroimaging and epigenetic studies were also considered. Results: Dopaminergic polymorphisms are associated with differences in reward processing, cognitive flexibility, motivation, and stress resilience. The most essential critical effects concern the DRD2 and DRD4 variants, which are associated with novelty seeking, reward dependence, and coping with stress. The COMT Val158Met polymorphism affects dopamine levels in the prefrontal cortex, modulating executive functions. The effects of individual polymorphisms are moderate, and conclusions regarding esports remain speculative due to limited research in this area. Conclusions: Dopaminergic predispositions involve interactions among genetics, neural activity, and the environment. However, current evidence is limited by small sample sizes, a predominance of European populations, scarce data on esports players, and difficulties in separating genetic effects from training-related adaptations. Full article

Background/Objectives: Social media’s impact on adult well-being varies by engagement patterns, highlighting the need for evidence to inform digital well-being strategies. This study examines the association between social media use and self-esteem, a key psychological indicator linked to adult well-being, with the aim of identifying modifiable behavioral targets relevant to clinical, workplace, and public health contexts. Methods: A cross-sectional survey of 81 Greek adults assessed daily social media use, engagement patterns, and self-esteem using the Rosenberg Self-Esteem Scale. Analyses included linear and exploratory quadratic regression models, multiple regression with demographic covariates (age, gender), and descriptive group comparisons. Results: A small but statistically significant negative association was observed between daily social media use and self-esteem (R² = 0.078), indicating limited explanatory power. Exploratory analyses did not provide strong evidence of non-linear effects. Demographic factors and usage categories were not significant predictors, likely reflecting limited statistical power. Participant self-reports highlighted potentially disruptive patterns such as intensive use at specific times/conditions, perceived sleep impact, and cognitive preoccupation with social media, as well as motivation to reduce or stop use. Conclusions: Time spent online is a weak predictor of self-esteem, underscoring the importance of engagement quality over frequency. From a management perspective, the findings support shifting attention from generic screen-time reduction to targeting specific potentially high-risk patterns of engagement in future policy and practice. This exploratory pilot study provides initial, hypothesis-generating evidence within a Greek adult sample and highlights the need for larger, population-based studies to confirm and extend these findings. Full article

Large Language Models (LLMs) have demonstrated impressive capabilities in structured reasoning and symbolic tasks, with coding emerging as a particularly successful application. This progress has naturally motivated efforts to extend these models to mathematics, both in its traditional form, expressed through natural-style mathematical language, and in its formalized counterpart, expressed in a symbolic syntax suitable for automatic verification. Yet, despite apparent parallels between programming and proof construction, advances in formalized mathematics have proven significantly more challenging. This gap raises fundamental questions about the nature of reasoning in current LLM architectures, the role of supervision and feedback, and the extent to which such models maintain an internal notion of computational or deductive state. In this article, we review the current state-of-the-art in mathematical reasoning with LLMs, focusing on recent models and benchmarks. We explore three central issues at the intersection of machine learning and mathematical cognition: (i) the trade-offs between traditional and formalized mathematics as training and evaluation domains; (ii) the structural and methodological reasons why proof synthesis remains more brittle than code generation; and (iii) whether LLMs genuinely represent or merely emulate a notion of evolving logical state. Our goal is not to draw rigid distinctions but to clarify the present boundaries of these systems and outline promising directions for their extension. Full article

In the aftermath of the COVID-19 pandemic, instructors in higher education have reported a decline in foundational reading habits, particularly in STEM courses where dense, technical texts are common. This study examines a low-barrier instructional intervention that used generative AI (GenAI) to support pre-class preparation in two upper-division biology courses. Weekly AI-generated audio overviews—“podcasts”—were paired with timed, textbook-based online quizzes. These tools were not intended to replace reading, but to scaffold engagement, reduce preparation anxiety, and promote early familiarity with course content. We analyzed student engagement, perceptions, and performance using pre/post surveys, quiz scores, and exam outcomes. Students reported that the podcasts helped manage time constraints, improved their readiness for lecture, and increased their motivation to read. Those who consistently completed the quizzes performed significantly better on closed-book, in-class exams and earned higher final course grades. Our findings suggest that GenAI tools, when integrated intentionally, can reintroduce structured learning behaviors in post-pandemic classrooms. By meeting students where they are—without compromising cognitive rigor—audio-based scaffolds may offer inclusive, scalable strategies for improving academic performance and reengaging students with scientific content in an increasingly attention-fragmented educational landscape. Full article

AI Recommender Systems (RecSys) function as personalised forecasting engines, predicting user preferences to reduce information overload. However, the efficacy of these systems is often bottlenecked by the “Last Mile” of forecasting: the end-user’s willingness to adopt and rely on the prediction. While the existing literature often assumes that algorithmic accuracy (e.g., low RMSE) automatically drives utilisation, empirical evidence suggests that users frequently reject accurate forecasts due to a lack of trust or cognitive friction. This study challenges the utilitarian view that users adopt systems simply because they are useful, instead proposing that sustainable adoption requires a state of Cognitive Absorption—a psychological flow state enabled by the Cognitive Economy of trust. Grounded in the Motivation–Opportunity–Ability (MOA) framework, we developed the Trust–Absorption–Intention (TAI) model. We analysed data from 366 users of a major predictive platform using Partial Least Squares Structural Equation Modelling (PLS-SEM). The Disjoint Two-Stage Approach was employed to model the reflective–formative Higher-Order Constructs. The results demonstrate that Cognitive Trust (specifically the relational dimensions of Benevolence and Integrity) operates via a dual pathway. It drives adoption directly, serving as a mechanism of Cognitive Economy where users suspend vigilance to rely on the AI as a heuristic, while simultaneously freeing mental resources to enter a state of Cognitive Absorption. Affective Trust further drives this immersion by fostering curiosity. Crucially, Cognitive Absorption partially mediates the relationship between Cognitive Trust and adoption intention, whereas it fully mediates the impact of Affective Trust. This indicates that while Cognitive Trust can drive reliance directly as a rational shortcut, Affective Trust translates to adoption only when it successfully triggers a flow state. This study bridges the gap between algorithmic forecasting and behavioural adoption. It introduces the Cognitive Economy perspective: Trust reduces the cognitive cost of verifying predictions, allowing users to outsource decision-making to the AI and enter a state of effortless immersion. For designers of AI forecasting agents, the findings suggest that maximising accuracy may be less effective than minimising cognitive friction for sustaining long-term adoption. To solve the cold start problem, platforms should be designed for flow by building emotional rapport and explainability, thereby converting sporadic users into continuous data contributors. Full article

Background: By exploring the principles of Gestalt psychology, the neural mechanisms of perception, and computational models, scientists aim to unravel the complex processes that enable us to perceive a coherent and organized world. This multidisciplinary approach continues to advance our understanding of how the brain constructs a perceptual world from sensory inputs. Objectives and Methods: This study investigates the nature of visual perception through an experimental paradigm and method based on a comparative analysis of human and artificial intelligence (AI) responses to a series of modified square images. We introduce the concept of a “phenomenal gradient” in human visual perception, where different attributes of an object are organized syntactically and hierarchically in terms of their perceptual salience. Results: Our findings reveal that human visual processing involves complex mechanisms including shape prioritization, causal inference, amodal completion, and the perception of visible invisibles. In contrast, AI responses, while geometrically precise, lack these sophisticated interpretative capabilities. These differences highlight the richness of human visual cognition and the current limitations of model-generated descriptions in capturing causal, completion-based, and context-dependent inferences. The present work introduces the notion of a ‘phenomenal gradient’ as a descriptive framework and provides an initial comparative analysis that motivates testable hypotheses for future behavioral and computational studies, rather than direct claims about improving AI systems. Conclusions: By bridging phenomenology, information theory, and cognitive science, this research challenges existing paradigms and suggests a more integrated approach to studying visual consciousness. Full article

Objectives: This study aims to explore the facilitators and barriers in the process of using AI agents for disease management in older COPD patients. Methods: Based on the normalization process theory, a descriptive qualitative study was used to conduct semi-structured interviews with 28 older patients with COPD recruited from June to August 2025 in a Class A tertiary hospital in Wuxi, Jiangsu Province. Results: A total of 28 interviews were conducted. Four themes (Coherence, Cognitive Participation, Collective Action, Reflexive Monitoring), nine subthemes (recognition of intelligent technology;supported by policy discourse and the background of national-level projects; the creation of a family atmosphere; recommendations from HCPs; relief and social connection; new “doctor”–patient relationship and communication; eliminate the burden and return to life; benefit and value perception; right self-decision by AI) in facilitators and nine subthemes (privacy conflicts and trust deficiency; blurred boundaries of human–machine responsibility and authority; non-high-quality services are chosen reluctantly; technical anxiety; lack of motivation for continued engagement; extra burden; limitations of the physical environment; human–machine dialogue frustration; a sense of uncertainty about the future of AI) in barriers were extracted. Conclusions: This study identified key factors influencing the use of AI agents in chronic disease management in older patients with COPD. The results provide directions for improving the implementation and sustainable use of AI health technologies. Full article

Expanded and intensified agriculture is a major driver of habitat loss for endangered species such as the Oriental White Stork (Ciconia boyciana), making wildlife-friendly farming an increasingly important approach for reconciling biodiversity conservation with agricultural development. Building on a 2018 feasibility study in the Sanjiang Plain, this research employs a choice experiment to examine how preferences for Oriental White Stork-friendly farming have evolved among urban consumers and residents of stork habitats under expanding green consumption and increasing experience with environmentally friendly farming. The results reveal pronounced preference heterogeneity and persistent cognitive separation between wildlife conservation and agricultural production, particularly among urban consumers, despite a stable group being willing to pay a premium for stork-friendly products. Rural residents’ decisions remain largely economically driven, though younger farmers with prior experience in environmentally friendly practices show more positive attitudes. Significant urban–rural differences suggest policy complementarities, whereby price-oriented incentives may encourage price-sensitive farmers to adopt green agriculture, while intrinsically motivated farmers require support through an Oriental White Stork-oriented value chain. Overall, the findings demonstrate that Wildlife-Friendly Farming cannot be effectively promoted through a one-size-fits-all approach; instead, stratified, group-specific policy and market mechanisms are essential for aligning producer incentives with consumer demand and supporting the long-term viability of biodiversity-friendly agricultural systems. Full article

Background: Adolescents in residential care frequently face functional challenges, yet few interventions integrate functional-cognitive models with motivational theories to support their daily function. Methods: This mixed-methods feasibility study is an innovative conceptual integration that links motivational and metacognitive approaches with growth-mindset principles to address both beliefs about the ability to change and functional performance. Quantitative data were collected from staff (n = 44), alumnae (n = 5), and current residents (n = 3), assessing mindset and functional-skill confidence among three focus groups (n = 16). The qualitative insights highlighted the motivational processes, strategy use, and barriers each group faced. Results: The findings informed the development of structured intervention psychoeducation protocol to facilitate goal-setting and reflective questioning. The feasibility and acceptability were tested by a pilot study among five staff members. Before implementation, staff demonstrated lower confidence in promoting daily autonomy and providing strategy-focused feedback. Alumnae and residents reported high emotional support, yet persistent gaps in functional independence. Conclusions: The pilot findings may inform the development of structured staff practices for delivering functional guidance, pending further evaluation. This study offers a novel conceptual contribution by positioning growth mindset as an active mechanism that supports functional-cognitive processes to enhance autonomy among adolescents in residential care settings. Full article

Engineering laboratory courses are essential for developing conceptual understanding and practical skills; however, the time students spend assembling prototypes and troubleshooting wiring issues often reduces opportunities for analysis, programming, and reflective learning. To address this limitation, this study designed and evaluated an integrated STM32-based educational laboratory that consolidates the main peripherals required in a microcontroller course into a single Printed Circuit Board (PCB) platform. A quasi-experimental intervention was implemented with 40 engineering students divided into a control group using traditional STM32 Blue Pill and breadboard connections and an experimental group using the integrated platform. Throughout ten laboratory sessions, data were collected through pre- and post-tests, laboratory logs, and the Motivated Strategies for Learning Questionnaire Short Form (MSLQ-SF). Results showed that the experimental group achieved a Hake normalized learning gain of 40.09% compared with 16.22% in the control group, also showing that it completed the sessions an average of 27 min faster and facilitated a substantial reduction in hardware- and connection-related errors. Significant improvements were also observed in metacognitive and improved motivational and self-regulated learning scores. Overall, the findings indicate that reducing operational barriers in laboratory work enhances both cognitive and motivational learning processes, supporting the adoption of integrated educational hardware to optimize learning outcomes in engineering laboratory courses. Full article