Search Results (6,515)

Background: Electroencephalography (EEG) provides millisecond-resolution measurements of neural activity, offering a unique potential to identify biomarkers of cognition, emotion, and mental health. However, the proliferation of methodologically diverse studies necessitates systematic synthesis to establish the reliability and clinical utility of proposed EEG biomarkers. Methods: Following PRISMA 2020 guidelines, we systematically searched PubMed, PsycINFO, Web of Science, and Scopus for studies published 2015–2025 examining EEG correlates of cognitive control, learning, emotion regulation, and mental health. From 3847 initial records, k = 210 unique studies (estimated n ≈ 9935 participants across 38 countries; see Methods for sample size derivation) met the inclusion criteria. Random-effects meta-analyses estimated pooled effect sizes for primary EEG markers across five research domains. Results: Frontal-midline theta demonstrated robust effects for cognitive control (k = 12; d = 0.89, 95% CI [0.72, 1.07]; I² = 0.0%) and learning/memory (k = 10; d = 0.70, 95% CI [0.50, 0.89]). The late positive potential indexed emotional processing (k = 18; d = 0.87, 95% CI [0.75, 1.00]) and regulation success (k = 14; d = −0.65, 95% CI [−0.79, −0.51]). Neurofeedback showed very large effects for PTSD (k = 2; d = −1.98, 95% CI [−2.50, −1.47]) and moderate effects for anxiety (d = −0.62), ADHD (d = −0.60), and depression (d = −0.42). Alpha event-related desynchronization marked cognitive engagement (k = 18; d = −0.70, 95% CI [−0.85, −0.55]). Heterogeneity was negligible (I² = 0.0%) in most analyses, except for clinical interventions, which showed condition-explained heterogeneity (I² = 75.4%). Conclusions: EEG biomarkers demonstrate substantial effect sizes and a notable consistency across cognitive and clinical domains, supporting their potential as candidate neurophysiological indicators for diagnostic research, the investigation of treatment response, and intervention monitoring. Causal claims are not warranted from this evidence base alone. A four-phase implementation framework is proposed to facilitate clinical translation. Future research should prioritize methodological standardization, diverse samples, and real-world validation. Full article

This paper investigates how hybrid temples are created and transformed into tourist attractions, focusing on Wat Phothikyan Phutthathum—a Thai–Chinese temple located in Kelantan, close to Malaysia’s border with Thailand. This study aims to understand how both the local Thai minority and Chinese majority contribute to temple hybridisation, examine the influence of such temples on community identity, and explore their growing importance as tourist attractions. It highlights the negotiation and cultural exchange that shape new heritage spaces for borderland communities. Using visual analysis and interviews, the research shows that, since there are no Chinese temples nearby, Chinese Buddhists and Taoists adapt Thai temples by incorporating their own rituals and art. This results in blended iconography and practices, guided by an open-minded Thai monk. Features like large Buddha statues, staircases featuring naga-dragon designs, and murals combining different traditions reveal this fusion. The temple’s unique artwork and spiritual environment attract visitors from Muslim-majority areas and various countries like Thailand, Taiwan, and Singapore. As tourism becomes central to the temple’s role, the local authorities emphasise its religious significance and multicultural symbolism, aligning with economic interests and daily interactions among minority groups. This study offers valuable empirical and theoretical perspectives on the blending of religious heritage sites in border regions. Full article

Symmetry and structural balance play a fundamental role in the collective behavior of networked agent systems (NASs). In particular, cluster formation tracking, representing the emergence and maintenance of symmetric group structures, has attracted significant attention due to its wide applications in robotics and autonomous systems. However, most existing approaches assume autonomous leaders, which may not be applicable in scenarios where human intervention is required. With this in mind, this paper addresses the cluster formation tracking problem for NASs with collision avoidance, where the leader receives control inputs from a human-in-the-loop (HiTL), making the leader a non-autonomous system. A distributed control protocol is developed so that followers can track the trajectories of their designated leaders using only relative information from neighboring agents. Sufficient conditions are established to guarantee collision-free cluster formation tracking, and Lyapunov-based analysis is employed to prove the asymptotic convergence of the subgroup tracking errors. In the proposed framework, human intervention is incorporated through external commands applied to the leaders, which makes the leader dynamics non-autonomous while preserving the distributed nature of the follower controllers. Simulation studies on a 13-agent network with three subgroups show that all followers achieve the desired time-varying cluster formations under HiTL-driven leader motions, with convergence times ranging from 4.21 s to 5.12 s. Moreover, the final tracking errors of all followers are reduced below $9.07\times {10}^{-5}$, while the minimum pairwise distances within each subgroup remain strictly above the prescribed safety threshold. These quantitative results verify both the effectiveness of the proposed protocol and the practical feasibility of integrating HiTL commands into collision-free cluster formation tracking. Full article

Background: This study aimed to investigate the relationship between dental fear and mindfulness levels, and to examine how this relationship varies across different dental specialties. Methods: The Dental Fear Scale (DFS) and the Mindful Attention Awareness Scale (MAAS) were administered to 411 adult patients receiving treatment in six different clinics of the Faculty of Dentistry at Kafkas University. Data were analyzed using the Kruskal–Wallis, Mann–Whitney U, Chi-square, and Spearman’s correlation tests. Results: A moderate, significant, and negative correlation was found between MAAS and DFS scores (r = −0.41; p < 0.001). Mean scores differed significantly across clinics. Patients in the Prosthodontics Department exhibited the highest levels of fear (62.21 ± 4.62) and the lowest levels of mindfulness (3.22 ± 0.23), whereas patients in the Oral and Maxillofacial Radiology Department demonstrated the lowest fear levels (40.60 ± 15.76) and the highest mindfulness levels (4.30 ± 1.00). Consistent with these score-level differences, the distribution of dental fear categories varied across clinics, with a significantly higher prevalence of high anxiety in the Prosthodontics clinic (75.7%) compared to the Orthodontics and Radiology clinics. Conclusions: Higher levels of mindfulness were associated with lower levels of dental fear, and this relationship was consistent across all clinical settings. The study highlights that clinical context significantly influences both mindfulness and fear levels, with invasive specialties showing a higher risk profile. Brief mindfulness-based interventions may serve as effective and feasible strategies to enhance patient cooperation and improve treatment outcomes, particularly in clinics where high levels of fear are prevalent. Full article

Introduction: University students are vulnerable to psychological distress due to the academic and social demands of this life stage. Mindfulness and self-compassion are effective and adaptable strategies in an academic environment that promote emotional regulation and psychological well-being. This study aims to conduct a systematic review and meta-analysis to evaluate the combined impact of mindfulness- and self-compassion-based interventions (MBSCIs) on psychological distress. It will also analyze their role as predictors of therapeutic change, as well as the moderating influence of sociodemographic and contextual factors. Method: We systematically searched PubMed, Scopus and Web of Science for randomized controlled trials (RCTs) and single-group pre-post trials investigating the effect of MBSCI on anxiety, depression and stress in college students. Studies were combined using the inverse variance method in a random effects model. Additional subgroup and meta-regression analyses were performed, and risk of bias was assessed. The review was pre-registered (PROSPERO registration number: CRD420251003822). Results: Our review included 49 studies with a total of 5043 participants (3721 in the intervention group, and 1322 in the control group). The results provide relevant evidence on the efficacy of MBSCI in the university population, especially in reducing symptoms of stress, anxiety, and depression. The effect sizes observed were moderate-to-large for stress and small-to-moderate for anxiety and depression, supporting their clinical usefulness in university educational settings. However, these findings should be interpreted with caution, as no included study achieved low risk of bias, and heterogeneity was moderate-to-high across most outcomes. Conclusions: The results suggest that MBSCI could alleviate psychological distress in university students. However, these results are limited by some methodological issues (risk of bias, heterogeneity, lack of follow-ups, poor standardization). It would be advisable to integrate these practices into the university curriculum as workshops or complementary activities. Further studies are needed to confirm their effectiveness and explore sustained effects and differences according to individual characteristics. Full article

Infrared moving maritime vessel segmentation is a crucial image processing task for maritime security, which is a challenging problem due to the complex backgrounds and targets with varying sizes. To address these issues, we propose an end-to-end segmentation network based on a multi-scale spatiotemporal vision transformer (ST-VT) for segmenting the moving maritime vessels in the infrared image sequence. Specifically, in the feature extraction module, we introduce a multi-scale feature encoding structure that combines a multi-scale backbone and Feature Pyramid Network technology. Then, the multi-scale deformable encoder structure and a cross-scale fusion module with the pixel decoder are proposed to generate the multi-scale spatiotemporal features. Subsequently, we employ the improved attention blocks that are the core blocks of the coarse-to-fine framework (across scales) of the prompt decoder to obtain the prompts. Finally, a multi-scale mask decoder is applied to achieve the final target segmentation. The experiments are conducted on the benchmark dataset IPATCH and our labeled dataset LAS-MassMIND. The results demonstrate that the proposed method achieves state-of-the-art performance, especially within complex backgrounds and targets of varying sizes. Full article

This paper develops Tone as Ontology, a structural account of being grounded in the invariants of generative systems. We articulate the ontological significance of tone, distinguishing this foundational work from a companion paper that explores its methodological application and formalization. We redefine “tone” as the structural profile of constraints that allows entities to maintain coherence under transformation. The tonal ontology formalizes three invariants—Resonance, Responsibility, and Closure—as conditions of persistence that bridge operational and metaphysical ontology. Concretely, we specify Resonance (relational continuity via recursive feedback), Responsibility (traceable accountability that conserves integrity across transformations), and Closure (recursive self-consistency enabling bounded openness). In contrast to informational or substance-based views, tonal being is understood as the conservation of structure through change. The resulting framework unites physical coherence, informational integrity, and ontological continuity into a generative ontology of integrity, suggesting that to exist is to maintain one’s tone. This paper addresses fundamental questions in meta-ontology, demonstrates how tone generates classical ontological frameworks, and advances a conceptual reorientation for understanding existence as resonant persistence. It outlines testable implications across philosophy of mind, AI ethics, and social/environmental theory. Overall, tonal ontology is presented as a post-informational, structurally grounded account of being. Full article

Objective: The aim of this study was to evaluate the positive predictive value of endocervical curettage (ECC) during colposcopic examination in a dysplasia unit since the implementation of the new cervical cancer screening program in Germany (January 2020). Methods: A total of 202 patients who presented for colposcopy at the Dysplasia Unit of the University Hospital Aachen, Germany, between January 2020 and October 2023, who had cervical intraepithelial neoplasia 1+ (CIN1+) in the endocervical curettage and received a loop-excisional procedure of the cervix (LEEP), were included in a retrospective cohort analysis using machine learning techniques (random forest analysis and leave-one-out cross-validation). Results: There was a low agreement between the results of the ECC and the CIN status after LEEP (kappa 0.0239). A positive result in the histological specimen of the excisional procedure of the cervix (CIN2+) was obtained in 73.7% in case of CIN1 detection in the ECC, 69.4% in case of CIN2 detection in the ECC, and 80.6% in case of CIN3 in the ECC. In the multivariate analysis, the result of colposcopy and the transformation zone, especially combined (kappa 0.259, p = 0.0004), had the highest predictive value with regard to the CIN status. Conclusions: ECC is associated with a low agreement rate in comparison to the final histological result of the LEEP, which should be kept in mind when counseling patients. A finding of CCIN1in an ECC obtained during colposcopy following abnormal HPV-based cervical cancer screening results should be considered an indication of a possible intracervical dysplasia. Full article

Background/Objectives: Nomophobia, the irrational fear of being without a mobile phone, is increasingly prevalent among university students and has emerged as a concerning form of digital dependence. Among nursing students, this condition is particularly relevant due to the emotional demands and cognitive challenges of healthcare education. Nomophobia has been linked with adverse psychological outcomes, sleep disturbances, and impaired academic and clinical performance. However, existing evidence remains fragmented and lacks an integrated conceptual synthesis. This review aimed to synthesize current evidence on the prevalence, correlates, and outcomes of nomophobia among nursing students. Methods: An integrative review was conducted following Whittemore and Knafl’s methodology and PRISMA guidelines. A systematic search was performed in PubMed, CINAHL, PsycINFO, PsycArticles, and Medline (between 2015 and 2025), supplemented by Google Scholar. Cross-sectional studies and literature focusing on nomophobia in nursing students were included. The primary studies and selected review articles were considered when no overlap with the included primary evidence was identified. Methodological quality appraisal was assessed using validated tools (QuADS and JBI). Results: Twenty-two studies were included (19 cross-sectional and 3 reviews). Four thematic areas emerged: prevalence and severity (50–90% moderate to severe); psychological correlates (anxiety, depression, stress, insomnia, alexithymia, fear of missing out); academic and cognitive outcomes (impaired performance, procrastination, reduced decision-making); and behavioural predictors (excessive smartphone use and emotional dysregulation). The Nomophobia Questionnaire (NMP-Q) was the most frequently used instrument. Conclusions: Nomophobia represents a relevant dimension of the mind–technology relationship in nursing education, with implications for students’ mental health, academic engagement, and clinical readiness. Addressing nomophobia may support healthier learning environments and contribute to the development of emotionally competent and safe future healthcare professionals. However, significant gaps remain, particularly regarding longitudinal evidence and intervention-based approaches. Full article

Accurately assessing dynamic water resource carrying capacity (WRCC) is essential and challenging, particularly in regions like the Gansu sections of the Yellow River Basin (GSYRB), a core water source protection zone in the arid northwest of China, due to its pressing challenge of balancing water resources for socioeconomic needs and ecological security. This study proposes a novel integrated computational assessment framework named SD-VIKOR to address the complexities arising from nonlinear interactions within the “water resources–socioeconomic–ecological environment” (W–S–E) system. The core of this framework is the tight coupling of a system dynamics (SD) simulation model with a VIKOR multi-criteria evaluation module, where indicator weights are objectively–subjectively determined via an Analytic Hierarchy Process (AHP)–entropy weight method. This integrated SD-VIKOR engine enables dynamic, scenario-based WRCC trajectory simulation. To move beyond simulation and enable mechanistic insight, the framework further incorporates a diagnostic suite: a Geodetector module quantifies dominant drivers and their interactions; an obstacle degree model pinpoints key limiting factors; and a coupling coordination degree model evaluates subsystem synergies. Together, they form a closed-loop “dynamic simulation → multi-criteria assessment → driving mechanism analysis and constraint diagnosis → subsystem coordination analysis” workflow. Applied to the GSYRB from 2012 to 2030 under five development scenarios, the framework demonstrated high efficacy. It successfully captured path-dependent WRCC evolution, revealing that the ecological-priority scenario (B2), which shifts system drivers from economic-scale expansion to resource-efficiency and environmental governance, yielded optimal WRCC and the highest system coordination. In contrast, business-as-usual and single-minded economic expansion scenarios underperformed. Six key obstacle factors were quantitatively identified, linking WRCC constraints to natural endowments, economic patterns, and domestic demand. The results reveal pronounced spatial–temporal heterogeneity in WRCC across the GSYRB, with socioeconomic development, water resource use efficiency, and ecological conditions acting as the primary joint drivers of WRCC evolution. Critically, several key indicators are identified as persistent constraints on regional water sustainability. In contrast to conventional static evaluations, the integrated framework captures the complex dynamics and multi-subsystem interactions governing WRCC, offering a more robust diagnostic of resource–environment systems. These insights provide a transferable analytical basis for designing sustainable water management strategies in arid river basins. Full article

Background/Objectives: Mindfulness-based interventions show promise for treating childhood ADHD, yet the mechanisms through which they produce effects remain unclear. This study provides the first direct comparison of treatment mechanisms between a mindfulness-based family intervention (MYmind) and methylphenidate. Methods: Data were drawn from a preregistered trial combining randomized and preference arms, comparing MYmind (2-month parallel parent–child mindfulness training) with 4-month methylphenidate in children aged 8–18 with ADHD (N = 120 children, 224 parents). Families were assessed at baseline, 2, 4 and 10 months. Multilevel mediation analyses tested whether treatment effects on ADHD symptoms were transmitted through 111 treatment-to-mediator-to-outcome pathways across three mechanism categories: child emotion regulation and coping (all children); adolescent self-regulation and mindfulness (ages 11+); and parent-level mechanisms, including mindful parenting, parental mindfulness, parenting style and self-compassion. Results: Direct treatment effects favored methylphenidate for ADHD symptom reduction at 4 months, with mindfulness catching up by 10 months. MYmind produced significantly greater improvements than methylphenidate in adolescent healthy self-regulation, parental self-compassion, mindful parenting and over-reactive parenting. Treatment did not differentially affect the remaining mechanisms. Across model sets, observed emotion regulation, maladaptive coping, parental self-compassion and mindful parenting each predicted ADHD outcomes. Across 111 pathways tested in 18 models, numerous significant individual pathways were consistent with theoretical predictions, yet no complete mediation chains reached statistical significance. Conclusions: MYmind engages distinct psychological and family-level processes compared to methylphenidate that are separately associated with ADHD symptom improvement. The absence of significant mediation effects likely reflects power limitations. These findings support mindfulness-based family intervention as a viable alternative to medication and highlight the need for larger-scale mechanism research. Full article

The widespread commercialization of wireless chargers for electric vehicles generally suffers from one main problem, which is the perfect alignment between the two coils, leading to a decrease in mutual inductance, which causes a drop in magnetic coupling and even a failure to transfer power. To address this persistent problem, this work proposes a comprehensive and integrated method for optimizing the coils and control architecture for reliable and safe battery charging. To address the challenges of a complex, nonlinear design space and the need for misalignment-tolerant geometries, we employ a memetic algorithm (MA) that hybridizes Particle Swarm Optimization (PSO) for broad global exploration with Mesh Adaptive Direct Search (MADS) for precise local refinement. This combination effectively avoids poor local solutions—a limitation of standalone PSO or GA approaches reported in recent studies—while efficiently converging to coil geometries that maintain strong magnetic coupling under misalignment. After the coils have been designed, electromagnetic validation is tested using finite element analysis (FEA), which allows the magnetic field distribution to be evaluated, as well as the coupling coefficient under different scenarios of misalignment and variation in the air gap between the ground side and the vehicle side. At the same time, a comprehensive control strategy for the primary side of the system has been developed. This control method ensures power management on the primary side, enabling system interoperability for charging multiple types of vehicles, as well as reducing vehicle weight for greater range. All this is combined with an innovative pulsed current charging method, chosen for its advantages in terms of thermal stability, ensuring safe and efficient recharging that is mindful of battery health. Simulation and experimental validation demonstrate that the proposed framework maintains stable wireless power transfer and achieves over 87% DC–DC efficiency under lateral misalignments up to 100 mm, fully complying with SAE J2954 alignment tolerance requirements. Full article

How does the complex, adaptive, and autonomous organization of life emerge from the laws of physics and information? This review argues that the answer lies in a convergent set of universal organizational principles that constitute a physical and informational grammar of the living. Living systems are dissipative structures that achieve organizational closure—materially and energetically open, yet causally closed—thereby attaining genuine autonomy and agency. Their architecture exhibits fractal and modular scaling laws that maximize energy flow, robustness, and evolvability under universal physical constraints. Critically, organisms operate at critical transitions—zones of controlled instability where fluctuations amplify information processing, transforming noise into adaptive signal. This self-organized criticality enables functional degeneracy, relational redundancy, and evolutionary antifragility. Cognition emerges as a distributed process of active inference, operating through a predictive–corrective cycle that integrates perception, action, and learning under the Free Energy Principle. From molecular networks to ecosystems, the same physico-informational grammars unfold recursively, revealing a deep organizational holography: the principles of organization are replicated across scales. Evolution under the Law of Increasing Functional Information is not random drift, but a directional expansion of functional complexity—a thermodynamic gradient towards greater agency. This synthesis challenges biological exceptionalism: the trajectory from thermodynamics to cognition is continuous, physically constrained, and potentially inevitable. Life does not violate physical laws—it fulfills them in regimes of high informational complexity, instantiating fundamental principles in self-organized architectures capable of prediction, memory, and purpose. The objective of this work is to articulate how the synthesis of these principles not only unifies physics and biology, but also illuminates the profound continuity between thermodynamics, chemistry, informational constraints, organization, and the mind. Full article

Meditation-related difficulties have been systematically documented in contemporary contemplative science, yet the prescriptive resources preserved in the ancient Buddhist commentarial literature remain underutilized in comparative research. This study analyzes the case of five hundred monks in the Paramatthajotikā I’s commentary on the Karaṇīya-metta-sutta. During intensive practice, these monks experienced complex psychosomatic symptoms—perceptual disturbances, fear, somatic distress, and cognitive impairment—and received from the Buddha an integrated prescription of five protective practices (pañca rakkhā). Through Pāli textual and comparative analysis with Lindahl et al.’s taxonomy of meditation-related difficulties, this study demonstrates that the monks’ symptoms correspond systematically to the perceptual, affective, somatic, and cognitive domains of the modern taxonomy, with the critical difference residing in interpretive frameworks rather than in the phenomena themselves. The five practices—loving-kindness meditation, protective chant recitation, contemplation of impurity, mindfulness of death, and the arousal of religious urgency—constitute a sequentially structured system progressing from the emotional reframing of fear to the deconstruction of bodily and existential attachment, culminating in the restoration of soteriological motivation. This study argues that Paramatthajotikā I’s prescriptive system provides a historically grounded, soteriologically oriented complement to contemporary contemplative science, particularly in bridging the gap between phenomenological classification and meaning-centered intervention. Full article

Background/Objectives: People with mobility limitations face disproportionately high rates of chronic health conditions and demonstrate lower adherence to wellness interventions. Digital programs such as MENTOR offer accessible alternatives but often face high rates of attrition. This study applied machine learning (ML) methods to predict adherence to the eight-week MENTOR telewellness program and identify key predictors of participant attendance. Methods: Data were drawn from 1218 adults enrolled in MENTOR (2023–2024). Adherence was defined as the percentage of 40 sessions attended. Baseline demographic, socioeconomic, psychosocial, mindfulness, resilience, health status, and physical activity variables were included as predictors. Following preprocessing and imputation, 13 ML regression models were trained using an 80/20 train–test split. The best-performing model was identified using mean absolute error (MAE), followed by feature selection and SHAP interpretability analyses. Pairwise synergy analysis quantified interactions between top predictors. Results: Model performance was modest overall. Bayesian ridge regression achieved the best performance (MAE 20.98; RMSE 25.26; R² = 0.12). SHAP analyses revealed that education, race, emotional support, Area Deprivation Index, household size, mindfulness, life satisfaction, and disability onset were the strongest predictors of adherence. Higher emotional support, mindfulness, and life satisfaction were associated with greater adherence, while socioeconomic disadvantage predicted lower adherence. Synergy analyses showed the strongest predictive interactions between low education and psychosocial resources (emotional support and life satisfaction). Conclusions: Baseline characteristics alone modestly predicted adherence to a digital wellness program. However, psychosocial and socioeconomic factors emerged as meaningful predictors, underscoring the need for personalized support strategies to reduce dropout among participants with mobility limitations. Full article