Search Results (494)

Sleep is a cardinal biological process that backstops central nervous system function, which also plays a crucial role in regulating systemic homeostasis, including immune activities. Cytokines, particularly interleukin-1β and tumor necrosis factor-α, act as mediators bridging sleep and inflammation, also influencing both sleep architecture and sleep–wake cycle. Sleep deprivation and sleep disorders such as insomnia, narcolepsy, hypersomnia, or obstructive sleep apnoea may disrupt cytokine production, alter their circadian rhythm of release, and shift secretion peaks from night to day. These changes contribute to daytime fatigue, impaired cognitive and physical performance, increased susceptibility to infections and/or systemic inflammation. Molecular studies indicate that insufficient sleep primes immune cells to enhance pro-inflammatory responses, creating a feedback loop with neuroendocrine pathways that further exacerbates sleep patterns and inflammatory dysregulation. Understanding the bidirectional relationship between sleep and cytokines may highlight the role of sleep as an active component of immunity regulation and underscore the potential usefulness of multilevel interventions that include complementary and integrative health approaches restoring sleep, normalizing cytokine rhythms and mitigating inflammation. Full article

Resilient wheels are widely employed in metro vehicles to mitigate vibration and noise, in which rubber damping components play a critical role in load transmission and fatigue resistance. However, stress concentration and cyclic loading can significantly compromise their durability and service life. In this study, the structural optimization and fatigue life of rubber damping components in resilient wheels are systematically investigated based on finite element analysis and in-service metro operational data. A three-dimensional finite element model incorporating hyperelastic material behavior is developed to evaluate stress distributions under three representative conditions: press-fit assembly, straight-line operation, and curved-track operation. Based on the resulting stress fields, critical high-stress regions within the rubber component are identified and selected as targets for structural optimization. The Design of Experiments (DOE) methodology, integrated with the Isight 2022 optimization platform, is employed to determine the optimal geometric parameters that minimize the von Mises equivalent stress. Furthermore, a fatigue life prediction framework is established using actual metro service mileage data. Fatigue performance is assessed using Fe-safe 2022 software in conjunction with rubber fatigue crack propagation theory, and the results before and after optimization are systematically compared. This study demonstrates that stress concentrations in resilient wheel rubber damping components predominantly occur at fillet transition regions, governed by load transfer characteristics under press-fitting and service conditions. Through DOE-based structural optimization, the critical geometric parameters are effectively refined, leading to a significant reduction in stress levels in key regions. As a result, the proposed approach markedly improves fatigue performance, extending the minimum fatigue life from 1300 days to 24,322 days, thereby substantially enhancing the durability and reliability of the resilient wheel system. Full article

This paper deals with a time-domain methodology for nominal stress-based, screening-level fatigue assessment of semi-submersible FWT hulls, using a 10-MW semi-submersible FWT as a case study. A comprehensive procedure is outlined for both short- and long-term fatigue analysis, emphasizing the influence of wind and wave loads, as well as the probability distributions of environmental conditions. A fully coupled dynamic analysis of the FWT, employing a multibody floater, is conducted to compute internal global loads and time-domain nominal stresses on the hull structure. Short-term fatigue damage is evaluated across various wind-wave directions, environmental conditions, and random wind and wave samples, identifying critical loading scenarios. For long-term assessment, 10,182 one-hour time-domain simulations are conducted across three wind-wave directions for five offshore sites in the North Sea and one site in the China Sea. Fatigue damage at different locations of the hull structure is estimated for each offshore site, with results discussed in the context of screening-level nominal fatigue assessment and identification of fatigue-critical regions. The insights gained from this study form a basis for validating simplified and computationally efficient fatigue analysis procedures in an accompanying paper. Additionally, the findings support the design optimization of hull structures. Limitations of the present study are identified, pointing to future research directions aimed at mitigating fatigue risks. Full article

Background/Objectives: Mental fatigue in adolescents is a growing concern in educational contexts, positioning physical education (PE) teachers as key agents in designing effective mitigation strategies. This study examined the perceptions of Spanish high school PE teachers regarding the causes, consequences, and potential countermeasures for students’ mental fatigue. Methods: A total of 116 in-service teachers (81 males and 35 females; mean teaching experience 7.8 ± 5.3 years) from 12 autonomous communities throughout Spain completed a comprehensive 34-item electronic questionnaire. The instrument assessed the perceived existence, etiology, and outcomes of mental fatigue through multiple-choice, dichotomous (yes/no), and five-point Likert scale questions, with particular attention given to the role of physical activity (PA) in symptom alleviation. A quantitative frequency analysis was conducted to examine the data. Results: The main findings reveal a strong consensus among the teachers (77.6% to 87.9%) on the prevalence of mental fatigue, with its primary causes attributed to academic pressure and sedentarism. The consequences were identified as increased irritability and reduced cognitive performance. The teachers overwhelmingly endorsed moderate intensity PA as the most effective countermeasure. However, a significant gap was identified between this theoretical awareness and the systematic implementation of targeted strategies within schools. Conclusions: These results underscore the critical need for professional development programs and structural support to translate teacher knowledge into practical intervention, suggesting important directions for future research. Full article

Online ride-hailing platforms increasingly rely on differentiated incentive mechanisms to regulate driver participation and balance supply and demand. However, drivers’ adaptive responses to such incentives introduce dynamic feedback and uncertainty that static equilibrium models fail to capture. This study develops a dual-layer Stackelberg–evolutionary game framework in which the platform acts as a strategic leader setting the order allocation rates and prices, while heterogeneous drivers adapt their working-hour strategies through evolutionary dynamics. Using operational data from Ningbo, China, we calibrated the demand elasticity and driver cost parameters and identified endogenous fatigue-cost thresholds that govern regime shifts in strategy dominance. Simulation results show that uniform incentives tend to drive the system toward single-strategy lock-in, whereas differentiated order allocation and pricing effectively sustain multi-strategy coexistence and mitigate extreme supply polarization. The findings reveal how platform-led differentiation reshapes the evolutionary fitness landscape of drivers, providing actionable guidance for incentive design aimed at stabilizing supply structures, improving platform revenue, and protecting driver welfare. Full article

Given its substantial contribution to traffic accidents, one of the main goals of intelligent driver-assistance systems has become the detection and mitigation of driver fatigue to enhance driving safety and comfort. Among various approaches, vision-based facial analysis using deep learning has emerged as an effective and non-intrusive method for identifying driver drowsiness, as a key manifestation of fatigue. However, current drowsiness detection models do not account for demographic factors like gender, even though recent research has shown gender behavioral differences such as eye closure duration, blink frequency, yawning patterns, and facial muscle relaxation. In this paper, we present a fine-grained multi-stream transformer architecture that incorporates gender-awareness and shifted-windows attention for spatial feature fusion. Integrating gender embedding, by modulating the region-based features, allows the model to effectively learn gender-conditioned drowsiness features to minimize bias and diluted representations. Using the NTHU-DDD dataset, we evaluated two-stream and three-stream variants for gender-aware and gender-agnostic across three facial region contexts: the face region with a 20% margin, bare face region, and key facial regions (face, eyes, and mouth). A comprehensive ablation study was conducted to identify the most effective model setup. The results demonstrate that incorporating gender embedding improves detection performance, achieving an accuracy of 95.47% on the evaluation set. Moreover, using the proposed three-stream model (SWT-DD-3S) produced better results. Full article

Human–robot interaction (HRI) takes place in dynamic environments where both humans and robots act as active agents, making the system inherently unpredictable. Abrupt movements can originate from either side and include human reflexes, fatigue, or unexpected reactions, as well as robot malfunctions, control errors, or task changes. These unpredictable events generate significant risks for both interaction fluency and safety, affecting not only the physical domain (e.g., collisions, excessive forces) but also cognitive aspects such as trust and predictability. Although different application areas present domain-specific challenges, a comprehensive overview of abrupt movements in HRI is still lacking, especially in the industrial scenario. This review aims to consolidate current knowledge regarding how abrupt phenomena are analyzed, prevented, and mitigated across various contexts and to offer new insights for researchers. In detail, after describing the literature search and the screening process, the review categorizes abrupt events, highlights key methodological approaches, and identifies gaps and future directions. By providing a structured synthesis of existing strategies, this work guides researchers in developing safer and more adaptive HRI frameworks capable of handling unpredictability. Full article

Since the inception of utility-scale wind turbines, there has been a continual increase in the size of the devices used. One drawback of turbine size increase is that the weight of the rotor blades has grown dramatically. Technological advancements have allowed for the creation of light blades to overcome this issue. These lighter rotors are also less stiff than their predecessors and prone to experiencing aeroelastic vibrations that can lead to fatigue damage. Aerodynamic damping occurring during blade vibration has the potential to mitigate those oscillations; thus, understanding its underlying physics provides an extremely useful tool for future blade design. In a series of previous publications, the authors presented a novel reduced-order characterization technique for the oscillatory response of wind turbines, which allows for the analysis of rotor vibrations when excited by wind gust pulses. In this paper, the authors will apply the same gust pulse technique to analyze the physics of blade’s aerodynamic damping, identifying two physical mechanisms. The first acts either as a damper, or as an energy feeder, depending on operational conditions. The second operates in a purely dissipative manner. Results of numerical experiments on several operational scenarios illustrating these behavioral responses will be presented and discussed. Full article

To elucidate the degradation behavior of elastic modulus in normal-strength ordinary concrete under flexural fatigue loading, this study systematically examines its evolution in C50 concrete, which is widely used in engineering applications. Based on four-point bending fatigue test data of plain concrete (PC) and reinforced concrete (RC) beams, degradation curves of the relative residual elastic modulus as a function of the cycle ratio were established. To quantitatively characterize the fatigue degradation process, two integrated indicators—the area under the curve (AUC) and the stable-stage degradation slope (|$K_{mid}$|)—were introduced to represent the degree of cumulative damage and the degradation rate of elastic modulus, respectively. These indicators were subsequently employed to evaluate the effects of maximum stress level, stress ratio, and reinforcement on elastic modulus degradation. The results show that failed PC specimens exhibited a typical three-stage S-shaped degradation pattern, whereas RC specimens primarily exhibited a two-stage degradation behavior. However, the elastic modulus of runout PC specimens remained above 93% of its initial value throughout the entire loading process. For PC specimens, under the same maximum stress level, increasing the minimum stress level from 0.10 to 0.25 resulted in a 24% decrease in |$K_{mid}$| from 0.2505 to 0.1912. At the same minimum stress level, increasing the maximum stress level from 0.75 to 0.90 led to a 94% increase in |$K_{mid}$| from 0.1912 to 0.3705. The presence of reinforcement increased AUC by 3~15% and reduced |$K_{mid}$| by 54~74%, indicating that reinforcement not only mitigated overall damage accumulation but also significantly slowed the degradation rate of the elastic modulus during the stable fatigue stage. The degradation characterization approach proposed in this study provides a simplified and practical framework for fatigue analysis of concrete components based on damage mechanics. Full article

Remote tower (rTWR) operations are reshaping air traffic control but introduce significant human-factor risks, notably cognitive fatigue induced by prolonged screen-based visual surveillance. To mitigate these risks in a safety-critical domain where missed detections can be catastrophic, we propose a non-intrusive, multimodal fatigue detection framework fusing ocular and cardiac signals. A high-fidelity simulation study with 36 controllers was conducted to collect eye-tracking and electrocardiogram (ECG) data, from which a 12-dimensional feature vector—integrating gaze entropy and heart rate variability (HRV)—was extracted. Addressing the severe class imbalance and scarcity of fatigue samples in physiological data, we developed a cost-sensitive XGBoost classifier combining SMOTE oversampling with a dynamically weighted loss function. Experimental results show that the proposed framework performed well under mixed-subject evaluation and improved sensitivity to fatigue events. Although a marked performance drop was observed under LOSO evaluation, personalized calibration partially alleviated this limitation, indicating the potential of the framework for real-time fatigue monitoring in remote tower operations. Full article

Deepwater drilling operations face critical challenges including narrow pore-fracture pressure windows, wellbore instability, and environmental concerns from drilling discharge. This paper presents a comprehensive systematic review of Riserless Mud Recovery (RMR) technology, tracing its evolution from its conceptual origins to its current applications, critically analyzing its technical limitations, and identifying future research directions. A systematic literature review was conducted covering peer-reviewed journals, SPE/IADC conference proceedings, industry technical reports, and independent academic studies from 1990 to 2025. Databases searched included Web of Science, Scopus, OnePetro, and Google Scholar, supplemented by Derwent Innovation Index for patents. After screening over 100 publications, approximately 60 references were selected following a two-step process excluding vendor-only promotional materials. Key findings reveal the following: (1) RMR technology has evolved through three distinct hardware generations—flexible hose systems, steel-pipe return lines with tandem pumps enabling deepwater breakthrough to 1419 m, and hybrid riser configurations for conceptual designs beyond 3000 m; (2) documented field benefits include 70% drilling fluid reduction, 9 days’ time savings per well, and successful mitigation of shallow geohazards across more than 1000 global well applications; (3) integration with casing-while-drilling and managed pressure cementing has enabled record-breaking performance of 1710 m in a single run; (4) independent academic validation confirms fatigue mechanisms affecting mud return lines; (5) systematic failure mode analysis identifies critical reliability issues in suction hoses, seals, and control systems; (6) quantitative economic analysis shows RMR cost-effectiveness depends on water depth, geological conditions, and environmental regulations. RMR technology has matured into a reliable drilling solution, yet its continued evolution requires addressing hardware limitations, developing dedicated well-control protocols, expanding to ultra-deepwater and emerging applications, and integrating digitalization for real-time optimization. Full article

The accelerated integration of digital technologies in schools over the past decade has significantly increased levels of technostress among teachers, impacting their psychological well-being and professional engagement. In this context, engagement and technostress emerge as critical constructs for understanding the well-being and quality of teaching in primary and secondary school teachers. However, the available evidence is fragmented across rural and urban contexts, making it difficult to gain a comprehensive understanding of this relationship. A systematic review was conducted following the PRISMA 2020 guidelines, including 13 studies published between 2015 and 2025, with a total of 6630 participants. The PEC model was used to define eligibility criteria and search strategies in five databases (Web of Science (n = 18), Scopus (n = 734), PsycNet (n = 32), SciELO (n = 0), PubMed (n = 135)). Methodological quality was assessed using the EACSH Scale, and the analysis integrated qualitative and quantitative descriptive approaches. A consistent inverse relationship was found between technostress and teaching engagement, moderated by contextual factors, educational level, and technological infrastructure. Technostress was associated with digital fatigue, reduced vigor, and lower professional dedication. Protective factors supporting engagement included digital self-efficacy, institutional support, adaptive emotion regulation, and a sense of meaning in work. Teachers in digitally demanding environments maintained high engagement when they had adequate personal and organizational resources. These findings highlight the urgent need for training and psychosocial support policies that mitigate technostress and strengthen teaching engagement across diverse territorial contexts. Within the broader landscape of digital transformation, including emerging artificial intelligence applications in education, this review underscores the importance of preparing teachers not only for technical proficiency but for sustainable digital practice. This literature review identifies research gaps on rural dynamics and the longitudinal nature of the phenomenon. Full article

To investigate the relationship between operator fatigue and collision risk under human–machine interaction (HMI) in intelligent tower crane operations, and to reveal the mitigating effects of HMI on fatigue-induced collision risks, a comprehensive data acquisition approach integrating eye-tracking signals, risk indicators, and fatigue scale assessments was proposed and validated through scenario-based experiments. First, two experimental scenarios—traditional mechanical operation and HMI operation—were established. Based on a review of existing studies, representative eye-movement metrics and fatigue scale indicators were selected. Subsequently, operator fatigue states were classified into three levels: low fatigue, moderate fatigue, and high fatigue. A total of 28 participants were recruited to complete fatigue assessments and subsequently perform tower crane lifting tasks under both experimental scenarios. Finally, collision risk under different scenarios was quantitatively evaluated using the safety distance between the crane hook and the rigger, as well as the frequency of collision alarms. The results indicate that, under traditional mechanical operation, increasing fatigue levels were associated with a significant reduction in safety distance between the crane hook and the rigger, accompanied by a marked increase in collision alarm occurrences, resulting in a relatively high overall collision risk. In contrast, under the HMI operation scenario, participants demonstrated superior operational control at equivalent fatigue levels. Specifically, under moderate fatigue, collision risk was reduced from low risk to no risk, while under high fatigue, collision risk decreased from high risk to low risk. These results indicate that, under laboratory-simulated conditions, human–machine interaction can mitigate, to a certain extent, the increasing trend of collision risk when operators perform tower crane lifting operations under fatigue. These findings provide a scientific basis for further optimization of intelligent tower crane operational modes and the development of enhanced safety management strategies. Full article

Mental fatigue is a psychobiological state induced by sustained effortful cognitive efforts during daily life activities. Yet research efforts in exercise science have focused primarily on performance implications for athletes to the point of exclusion of vulnerable populations for which mental fatigue may be a health risk. This narrative review aims to clarify the role of mental fatigue on population health. Evidence suggest mental fatigue predisposes people to acute events related to temporary performance impairments (e.g., falls), and chronic diseases related to sedentarism (e.g., stroke, diabetes), as mental fatigue de-motivates people to engage in physical activity. Major risks are experienced by people with higher fatigability (i.e., people for whom mental fatigue is induced by less effortful tasks) and lower performance capacity. However, the few available information about moderators of fatigability and the lack of a normative protocol to assess mental fatigue are limiting the prevention of mental fatigue. Several strategies are used to counter mental fatigue acutely (e.g., caffeine ingestion); however, enduring countermeasures intended to alter psychobiological sequelae of mental fatigue, such as Brain Endurance and other trainings, are the only proved long-term countermeasures for mental fatigue. Yet the effectiveness of these interventions should be tested in populations with major risk for mental fatigue. We present a model identifying putative pathways through which mental fatigue may contribute to health risks to guide future investigations seeking to (a) evaluate the role of mental fatigue as a threat to health and well-being and (b) design interventions to mitigate the effects of mental fatigue in vulnerable populations. Full article

Under dual challenges of global infrastructure expansion and industrial solid waste management, alkali-activated polymers (AAP), as industrial solid-waste-based low-carbon cementitious materials, exhibit immense potential in grouting engineering applications. This review synthesizes current research progress through three critical dimensions: reaction mechanisms, performance characteristics, and grouting applications (grouting for reinforcement and water-blocking). The reaction mechanism universally comprises three stages: dissolution, depolymerization, and polycondensation. Key performance determinants include precursor composition (e.g., slag, fly ash, metakaolin) and alkaline activator properties (type, modulus, concentration). The multifunctional advantages of AAP are fundamentally governed by their microstructural evolution. Specifically, the rapid formation of highly cross-linked C-(A)-S-H and N-A-S-H gels directly contributes to rapid setting and high early strength development, with high-calcium precursors such as slag exhibiting faster strength gain than low-calcium systems, such as fly ash and metakaolin. Furthermore, the absence of vulnerable calcium hydroxide phases, combined with a densified, low-porosity aluminosilicate network, provides superior thermal stability, corrosion resistance, frost durability, and low permeability. Nevertheless, pronounced autogenous shrinkage and drying shrinkage, driven by mesopore moisture loss and the highly viscoelastic solid skeleton, remain primary constraints for field implementation. In grouting reinforcement, AAP can effectively enhance the strength and structural integrity of weak soils, such as soft clay, loess, and sulfate-rich saline soils. For grouting water-blocking, particularly in sodium-silicate-based binary systems, AAP achieves rapid gelation, superior washout resistance, and high anti-seepage pressure, proving optimal for groundwater inflow control. Future research must prioritize (i) standardized mix design protocols for performance consistency, (ii) advanced shrinkage mitigation strategies, (iii) systematic durability assessment under coupled environmental stressors (e.g., wet–dry cycling, chemical attack, thermal fatigue), and (iv) cross-disciplinary collaboration for industrial-scale validation. Full article