Search Results (4,925)

This paper presents an analytical model for the hereditary vibrations of a coupled circular plate system interconnected by viscoelastic creep layers. The system is represented as a discrete-continuous chain of thin, isotropic plates with time-dependent material properties. Based on the theory of hereditary viscoelasticity and D’Alembert’s principle, a system of partial integro-differential equations is derived and reduced to ordinary integro-differential equations using Bernoulli’s method and Laplace transforms. Analytical expressions for natural frequencies, mode shapes, and time-dependent response functions are obtained. The results reveal the emergence of multi-frequency vibration regimes, with modal families remaining temporally uncoupled. This enables the identification of resonance conditions and dynamic absorption phenomena. The fractional parameter serves as a tunable damping factor: lower values result in prolonged oscillations, while higher values cause rapid decay. Increasing the kinetic stiffness of the coupling layers raises vibration frequencies and enhances sensitivity to hereditary effects. This interplay provides deeper insight into dynamic behavior control. The model is applicable to multilayered structures in aerospace, civil engineering, and microsystems, where long-term loading and time-dependent material behavior are critical. The proposed framework offers a powerful tool for designing systems with tailored dynamic responses and improved stability. Full article

Thin film/substrate structures based on the principle of buckling mechanics exhibit both excellent stretchability and mechanical stability, and they have been recognized as a critical configuration in the design of flexible electronic devices. During application, flexible electronic devices are usually subjected to complex dynamic environments. Therefore, it is of great significance to investigate the dynamic behavior of thin film/substrate structures for the design of flexible electronic devices. The bending energy, membrane energy, and kinetic energy of the thin film and the elastic energy of the substrate were calculated. On this basis, the dynamic equation of the thin film/substrate structure with a checkerboard wrinkled pattern was derived by applying the principle of minimum energy combined with the Lagrangian function. Numerical simulations were conducted on the system to analyze the effect of pre-strain and the Young’s modulus of substrate on the system’s potential energy function, simulate the temporal response of the system’s dynamic behavior, and investigate the influences of pre-strain and the Young’s modulus of substrate on system stability and the chaos critical value. Theoretical support is expected to be provided for the design of two-dimensional (2D) thin film/substrate structures through this research. Full article

This study explores the factors that influence Gen Z consumers’ green purchasing behavior, addressing a gap in current research by combining the Theory of Planned Behavior, the Theory of Consumption Values, and Generational Theory, and applying them to the touristic accommodation context. Based on a quantitative survey of Gen Z tourists from Spain, Norway, and Lithuania, the study examined traditional constructs of the Theory of Planned Behavior alongside subjective knowledge, environmental consciousness, perceived value, and green trust. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results indicate a significant role for price-based functional value and emotional value in shaping Gen Z’s attitudes toward sustainable accommodation. Furthermore, subjective knowledge and environmental consciousness strengthen green trust, which in turn contributes to a more positive attitude toward sustainable touristic options. Attitude, subjective norms, and perceived behavioral control significantly predict behavioral intention, while both perceived behavioral control and behavioral intention directly influence actual purchasing behavior. The findings suggest that tourism marketers should focus on enhancing price-related and emotionally meaningful value propositions, while also fostering trust through clear communication of environmental performance. Overall, the study offers a comprehensive understanding of the drivers behind Gen Z’s sustainable accommodation choices and provides practical implications for promoting environmentally responsible tourism. Full article

As vital components of urban rail transit networks, subway stations are widely scattered across diverse urban districts, whose sustainability performance exerts a notable impact on the overall urban ecological and environmental quality. This study constructs a three-dimensional numerical model to conduct a comparative assessment of the seismic behavior of subway stations adopting different bearing systems at beam-column joints. The seismic responses of two typical structural configurations, a traditional rigid-jointed subway station and another equipped with rubber isolation bearings, are examined under a series of ground motions, with due consideration of amplitude scaling effects and material nonlinearity. A comprehensive evaluation is carried out on key performance parameters, including structural acceleration responses, column rotation angles, damage evolution processes, and internal force distributions. Based on this analysis, the research clarifies the sustainability implications by establishing quantitative correlations between seismic response indices (i.e., deformation extent, damage degree, and internal force magnitudes) and post-earthquake outcomes, such as repair complexity, material requirements, carbon emissions, and socioeconomic effects. The results can advance the integrated theory of seismic-resilient and sustainable design for underground infrastructure, providing evidence-based guidance for the optimization of future subway station construction projects. Full article

Background/Objectives: Geographic Information Systems (GIS) offer essential capabilities for identifying spatial concentrations of vulnerability and strengthening context-aware prevention strategies. This manuscript describes a geospatial architecture designed to generate anticipatory, place-based risk identification applicable across diverse community and institutional environments. Interpersonal Violence (IPV), one of several preventable harms that benefit from this spatially informed analysis, remains a critical public health challenge shaped by structural, ecological, and situational factors. Methods: The conceptual framework presented integrates de-identified surveillance data, ecological indicators, environmental and temporal dynamics into a unified spatial epidemiological model. Multilevel data layers are geocoded, spatially matched, and analyzed using clustering (e.g., Getis-Ord Gi*), spatial dependence metrics (e.g., Moran’s I), and contextual modeling to support anticipatory identification of elevated vulnerability. Framework Outputs: The model is designed to identify spatial clustering, mobility-linked risk patterns, and emerging escalation zones using neighborhood disadvantage, built-environment factors, and situational markers. Outputs are intended to support both clinical decision-making (e.g., geocoded trauma screening, and context-aware discharge planning), and community-level prevention (e.g., targeted environmental interventions and cross-sector resource coordination). Conclusions: This framework synthesizes behavioral theory, spatial epidemiology, and prevention science into an integrative architecture for coordinated public health response. As a conceptual foundation for future empirical research, it advances the development of more dynamic, spatially informed, and equity-focused prevention systems. Full article

This article sets out to investigate how individuals process their experiences of covert aggression in their workplace. Covert aggression is operationalized within this article as behaviors that are subversive, mal-intended behaviors which attempt to undermine an individual’s confidence within the social milieu of their workplace and their capabilities and knowledge within the context of their job role. Using the critical incident technique embedded in a semi-structured interview format, the findings pointed to the targets of covert aggression undergoing a process of realizing they are experiencing covert aggression, sensemaking of why this is happening to them, self-monitoring their behaviors and responses around the aggressor, and creating scripts as a way to manage their working relationship with their aggressor. This cognitive process that we unveil in this article establishes a baseline for further investigations into the experiences of being targeted by covert aggression. Full article

This study examines the functional degradation of crystalline silicon photovoltaic cells after 17 years of field exposure in the Adrar Desert, Algeria. Harsh thermal, radiative, and mechanical conditions accelerate aging, affecting electrical performance and structural stability. Monocrystalline silicon cells were extracted and analyzed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Raman spectroscopy, electrical resistivity measurements, and vibrating sample magnetometry (VSM). SEM revealed microcracks, delamination, and corrosion products. EDS showed Ag, Si, O, and C signals, while Raman indicated silicon features and signatures consistent with encapsulant (EVA) degradation. The temperature-dependent resistivity displayed a dual behavior with a minimum near ~72 °C, above which resistivity increased, consistent with a transition in the dominant transport mechanisms. VSM measurements showed an overall diamagnetic response with a weak hysteresis loop suggestive of defect-related contributions. The observed aging is primarily associated with oxidation, metal migration, and encapsulant degradation. These findings motivate more robust materials and interfaces for desert climates, alongside improved thermal management and active monitoring. Full article

Ceramic matrix composites (CMCs) exhibit excellent high-temperature strength, oxidation resistance, and fracture toughness, making them superior to traditional metals and single-phase ceramics in extreme environments such as aerospace, nuclear energy equipment, and high-temperature protection systems. The mechanical properties of CMCs directly influence the reliability and service life of structures; thus, accurately predicting their mechanical response and service behavior has become a core issue in current research. However, the multi-phase heterogeneity of CMCs leads to highly complex stress distribution and deformation behavior in traditional mechanical property testing, resulting in significant uncertainty in the measurement of key mechanical parameters such as strength and modulus. Additionally, the high manufacturing cost and limited experimental data further constrain material design and performance evaluation based on experimental data. Therefore, the development of effective numerical simulation and mechanical modeling methods is crucial. This paper provides an overview of the research hotspots and future directions in the field of CMCs numerical simulation and mechanical modeling through bibliometric analysis using the CiteSpace software. The analysis reveals that China, the United States, and France are the leading research contributors in this field, with 422, 157, and 71 publications and 6170, 3796, and 2268 citations, respectively. At the institutional level, Nanjing University of Aeronautics and Astronautics (166 publications; 1700 citations), Northwestern Polytechnical University (72; 1282), and the Centre National de la Recherche Scientifique (CNRS) (49; 1657) lead in publication volume and/or citation influence. Current research hotspots focus on finite element modeling, continuum damage mechanics, multiscale modeling, and simulations of high-temperature service behavior. In recent years, emerging research frontiers such as interface debonding mechanism modeling, acoustic emission monitoring and damage correlation, multiphysics coupling simulations, and machine learning-driven predictive modeling reflect the shift in CMCs research, from traditional experimental mechanics and analytical methods to intelligent and predictive modeling. Full article

Carbon dots (CDs) have emerged as a distinct class of fluorescent nanomaterials distinguished by their tunable physicochemical properties, ultrasmall size, exceptional photoluminescence, versatile surface chemistry, high biocompatibility, and chemical stability, positioning them as promising candidates for biomedical applications ranging from sensing and imaging to drug delivery and theranostics. As CDs increasingly transition toward biological and clinical use, a fundamental understanding of their interactions with biological membranes becomes essential, as cellular membranes govern nanoparticle uptake, intracellular transport, and therapeutic performance. Model membrane systems, such as phospholipid vesicles and liposomes, offer controllable platforms to elucidate CD-membrane interactions by isolating key physicochemical variables otherwise obscured in complex biological environments. Recent studies demonstrate that CD surface chemistry, charge, heteroatom doping, size, and hydrophobicity, together with membrane composition, packing density, and phase behavior, dictate nanoparticle adsorption, insertion, diffusion, and membrane perturbation. In addition, CD-liposome hybrid systems have gained momentum as multifunctional nanoplatforms that couple the fluorescence and traceability of CDs with the encapsulation capacity and biocompatibility of lipid vesicles, enabling imaging-guided drug delivery and responsive theranostic systems. This review consolidates current insights into the mechanistic principles governing CD interactions with model membranes and highlights advances in CD-liposome hybrid nanostructures. By bridging fundamental nanoscale interactions with translational nanomedicine strategies, this work provides a framework for the rational design of next-generation CD-based biointerfaces with optimized structural, optical, and biological performance. Full article

Background: Patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) or depression both frequently report debilitating exhaustion, yet the two conditions differ in their etiological and diagnostic clarity, and clinical management. This study aimed to examine differences in the use and perceived helpfulness of a broad range of conventional treatments and complementary interventions, including nutritional approaches, between patients with ME/CFS and depression. Methods: A cross-sectional online survey was conducted in 2024. A total of 819 participants self-identified as having either ME/CFS (n = 576) or depression (n = 243). Participants (80% female) reported their use and perceived helpfulness of 52 treatments and interventions, encompassing behavioral therapies, medications, and dietary supplements. Group differences were examined using multivariate analyses of variance and covariance (MANOVA/MANCOVA). Open-ended responses were analyzed descriptively using thematic grouping and frequency counts. Results: Participants with depression most commonly reported the use of psychotherapy (M = 2.49, SD = 1.00) and antidepressant medication (M = 2.44, SD = 2.30), and they rated fewer interventions as helpful compared to participants with ME/CFS. In contrast, participants with ME/CFS reported a significantly broader engagement with diverse intervention modalities, particularly pacing (M = 2.73, SD = 0.80) and dietary supplements (M = 2.43, SD = 1.09), and perceived many of them as helpful. Group differences remained significant after controlling for age, gender, and whether treatment was medically recommended. Supplements targeting energy metabolism (e.g., CoQ10, NADH) were especially favored among ME/CFS participants. Conclusions: Findings suggest that participants with ME/CFS tend to adopt an exploratory and expansive intervention approach, potentially reflecting the lack of standardized guidelines and limited effectiveness of available treatment options. Participants with depression, in contrast, appeared to follow more guideline-concordant, evidence-based treatment pathways. Taken together, the findings point to a need for further development and evaluation of empirically supported, patient-centered treatment and intervention strategies for ME/CFS and suggest differences in clinical care structures between ME/CFS and depression. Full article

There are almost no studies that investigate the flexural behavior of existing reinforced concrete (RC) beams with insufficient concrete strength using machine learning methods. This study investigates the flexural response of low-strength concrete (LSC) RC beams reinforced exclusively with steel rebars, focusing on the effectiveness of three different longitudinal reinforcement configurations. Nine beams, each measuring 150 × 200 × 1100 mm and cast with C10-grade low-strength concrete, were divided into three groups according to their reinforcement layout: Group 1 (L2L) with two Ø12 mm rebars, Group 2 (L3L) with three Ø12 mm rebars, and Group 3 (F10L3L) with three Ø10 mm rebars. All specimens were tested under three-point bending to evaluate their load–deflection characteristics and failure mechanisms. The experimental findings were compared with ML approaches. To enhance predictive understanding, several ML regression models were developed and trained using the experimental datasets. Among them, the Light Gradient Boosting, K Neighbors Regressor and Adaboost Regressor exhibited the best predictive performance, estimating beam deflections with R² values of 0.89, 0.90, 0.94, 0.74, 0.84, 0.64, 0.70, 0.82, and 0.72, respectively. The results highlight that the proposed ML models effectively capture the nonlinear flexural behavior of RC beams and that longitudinal reinforcement configuration plays a significant role in the flexural performance of low-strength concrete beams, providing valuable insights for both design and structural assessment. Full article

Recently, with concern for the environment and the request for sustainable materials, more researchers and manufacturers have focused on the substitute solution of synthetic fiber reinforcement composites in industry applications. Green hybrid composites with natural components can present excellent sustainability, possess superior mechanical behavior, and reduce hazards. Hybridization technology allows new materials to inherit their raw materials’ characteristics and generate new properties. The current study designed novel double-walled shell structures (DS1R4L, DS2R8L, and DS5R12L), containing two thin walls and different numbers of ring and longitudinal stiffeners, as unmanned maritime vehicle (UMV) components. A normal single-walled cylindrical shell was used as a control. These models will be made of hybrid kenaf/flax/glass-fiber-reinforced composites, GKFKG and GFKFG, created in the ANSYS Workbench. The mechanical responses (deformation, stress, and strain characteristics) of models were examined under three loading conditions (end force, end torque, and hydrostatic pressure) to evaluate the influence of both material change and structural configuration. Compared to the single-walled structure, the double-walled configurations display minimized deflection and torsional angle. Moreover, GKFKG-made structures are better than GFKFG-made ones. The research contributes positively to advancing the application of hybrid kenaf/flax/glass-fiber-reinforced composites in UMV structures and promotes the development of green sustainable materials. Full article

Understanding consciousness requires bridging theoretical models and clinically measurable brain dynamics. This review integrates three complementary frameworks that converge on a dynamical view of conscious processing: continuous formulations of Integrated Information Theory (IIT), attractor-landscape modeling of brain-state transitions, and perturbational complexity metrics from transcranial magnetic stimulation combined with electroencephalography (TMS-EEG). Continuous-time IIT formalizes how integrated information evolves across temporal hierarchies, while dynamical-systems approaches show that consciousness emerges near criticality, where metastable attractors enable flexible transitions between partially synchronized states. Perturbational-complexity indices capture these properties empirically, quantifying the brain’s capacity for integration and differentiation even without behavioral responsiveness. Across anesthesia, disorders of consciousness, epilepsy, and neurodegeneration, TMS-EEG biomarkers reveal reduced complexity and altered synchronization consistent with structural and functional disconnection. Integrating multimodal data—diffusion MRI, fMRI, EEG, and causal perturbations—is consistent with individualized modeling of consciousness-related dynamics. Standardized protocols, mechanistically interpretable machine learning, and longitudinal validation are essential for clinical translation. By uniting information-theoretic, dynamical, and empirical perspectives, this framework offers a reproducible foundation for consciousness biomarkers that mechanistically link brain dynamics to subjective experience, paving the way for precision applications in neurology, psychiatry, and anesthesia. Full article

In recent years, green hydrogen production via water electrolysis driven by renewable energy sources has garnered increasingly significant attention. Among the various water electrolysis technologies, proton-exchange membrane water electrolysis (PEMWE) distinguishes itself owing to the unique advantages, including the compact architecture, high efficiency, rapid dynamic response, and high purity of the generated hydrogen. The membrane electrode assembly (MEA) serves as the core component of a PEM electrolyzer. And only a high-performance and stable MEA can provide a reliable platform for investigating the mass transport behavior within the porous transport layer (PTL). In this study, the MEA fabrication method was optimized by varying the ionomer-to-carbon (I/C) ratio, coating strategy, and anode Ir mass loading. As a result, the cell voltage was reduced from 1.679 V to 1.645 V at 1.0 A cm⁻², with a small degradation of 1.3% over 70 h of operation. Based on the optimized MEA, the effects of the structure and porosity of PTL on the mass transport behavior were further analyzed. After the PTL parameter optimization, the cell voltage was further reduced to 1.630 V at 1.0 A cm⁻², while a high-speed camera captured bubble dynamics in real time, showing the fast detachment of small oxygen bubbles. The integrated electrochemical and visualization results provide a useful guideline to designing both MEA and PTL for efficient PEMWE. Full article

Many children with cancer referred to physical therapy (PT) do not attend the service. We conducted a pilot study, comprising a cross-sectional survey and interviews with parents of children with acute lymphoblastic leukemia. The survey explored parents’ (1) views on PT service delivery for their child, (2) perspectives on barriers and facilitators, (3) preferred timing to introduce PT, and (4) views on virtual services. Questions were designed based on the Theoretical Domains Framework, and responses were mapped onto the Capability, Opportunity, Motivation–Behavior Change Model. Twenty parents participated in the survey. Although all parents would consider their child accessing PT if deficits were present, access depended on a convenient location (70%) and availability of virtual delivery (45%). While half of the parents preferred PT treatment to be introduced during the maintenance phase of chemotherapy, findings also support earlier introduction during the consolidation phase when services are framed as part of standard care. While most parents perceived that it would be manageable to support home-based PT, barriers included a lack of child’s motivation without therapist support. Seven parents participated in semi-structured interviews. They identified time constraints, distance, and costs as common barriers. Most parents responded positively to hybrid PT models and connections with community locations to mitigate these challenges. Full article