Search Results (1,874)

Urban blue-green spaces (UBGS) are crucial nature-based solutions for enhancing urban resilience and improving public health. This study examined the experiential relationships linking BGS use to human well-being among users of five urban parks in Delhi, India. Using an integrated experience-centered framework, we collected in-situ survey data (n = 411) to profile usage patterns, assess environmental quality, and quantify restorative outcomes grounded in Attention Restoration Theory (ART) and Stress Reduction Theory (SRT). Advanced analytical techniques, including ordinal logistic regression and interpretable machine learning (SHAP), were used to identify the key factors associated with user satisfaction. The results revealed that for these respondents, BGS appeared to function as an essential neighbourhood, with over 40% visiting three or more times per week. Although visual attractiveness was rated positively, deficits in noise buffering and amenities indicated a gap between aesthetic and functional qualities. Restorative benefits, including emotional calmness, mood refreshment, and fatigue recovery, were consistently reported among respondents. Analyses showed that embodied experiences, particularly post-visit relaxation and physical comfort, were more strongly associated with user satisfaction. SHAP interpretation highlighted seating adequacy, routine use, and thermal comfort as prominent contributors, suggesting somatic relief may be particularly salient. This study provides exploratory evidence from a Global South megacity and context-sensitive insights into how restorative processes operate under high-density urban conditions. The findings show that routine accessibility, basic amenities, and thermal comfort are central to the everyday functioning of blue-green spaces as urban infrastructure, underscoring the need for experience-responsive and equity-oriented urban greening policies in high-density cities. Full article

Background/Objectives: Sexual dysfunction (SD) is a common yet underrecognized consequence of multiple sclerosis (MS) with multidimensional determinants spanning neurological, physical, and psychosocial domains. However, the relative and incremental contribution of fatigue compared with disability and psychological factors remains insufficiently clarified. This study aimed to evaluate the prevalence and severity of sexual dysfunction in MS and to identify independent and incremental predictors using a hierarchical analytical framework. Methods: In this cross-sectional case–control study, 140 patients with MS and 140 age- and sex-matched healthy controls were assessed. Sexual functioning was evaluated using the Arizona Sexual Experience Scale (ASEX) and the Multiple Sclerosis Intimacy and Sexuality Questionnaire-19 (MSISQ-19). Fatigue severity, anxiety, depression, body image, self-esteem, disability (EDSS), and quality of life were measured using validated instruments. Hierarchical multiple linear regression analyses were conducted within the MS cohort to determine independent predictors of MSISQ-19 domain and total scores and to evaluate the incremental contribution of fatigue. Results: Sexual dysfunction was significantly more prevalent in the MS group compared with controls (70.7% vs. 13.6%, p < 0.001). Patients with MS demonstrated higher fatigue, anxiety, depression, and poorer body image, self-esteem, and quality of life (all p < 0.001). Within the MS cohort, individuals with sexual dysfunction exhibited greater symptom burden and disability. Hierarchical regression analyses showed that fatigue produced the largest increase in explained variance across all MSISQ-19 domains (ΔR² range: 0.11–0.19) and remained the strongest independent predictor (β range: 0.29–0.42; p ≤ 0.001). Anxiety retained independent associations with selected domains, whereas disability indices did not remain independently significant after adjustment. Conclusions: Sexual dysfunction in MS reflects a multidimensional burden extending beyond neurological impairment. Fatigue demonstrated the most consistent associations across sexual dysfunction domains, with anxiety contributing to selected aspects of functioning. Given the cross-sectional design, these findings should be interpreted as associations rather than causal relationships. Multidimensional assessment incorporating fatigue and psychological factors may improve the identification of clinically relevant and potentially modifiable determinants within comprehensive MS care. Full article

In aerospace applications, the vibration of aircraft structures results in a reduction in their fatigue life. Vibration-suppression technology utilizing macro fiber composite (MFC) materials constitutes a significant research direction. Aiming at the specific requirements of the MFC actuator operating in the asymmetric high-voltage range of −500 V to 1500 V and the miniaturization of the drive system for aircraft, this study designs a compact self-tuning digital high-voltage controller which adopts a discontinuous conduction mode (DCM) flyback topology as the fundamental model for the switching power supply high-voltage controller, uses the STM32G431 chip as the main controller, and incorporates a Type-II digital compensator designed to enhance the system stability under constant parameters. A Backpropagation (BP) neural network is proposed to enable dynamic adjustment of the digital compensator control parameters, thereby achieving self-tuning, while also supporting program download and real-time data transmission. The high-voltage controller effectively addresses the size and weight constraints in vibration active control systems. Laboratory tests demonstrated its excellent transient response and robust load-driving capability. Vibration-suppression experiments on a high-aspect-ratio UAV wing achieved a 74% vibration attenuation rate, validating the effectiveness of the proposed high-voltage controller. Full article

Forest waste is globally abundant and holds significant potential for valorisation in various sectors. This paper investigates its use in urban road infrastructures, utilising enzymatic lignin, a by-product from forest waste bioethanol production, as a bitumen extender for warm-mix asphalt. Since this asphalt concrete is produced at about 40 °C below the traditional hot-mix asphalt temperature, this study evaluates lignin’s ability to ensure the required mechanical performance of asphalt concrete in both aged and non-aged states. The TEAGE—TEcnico accelerated AGEing device—applied UV radiation and wet/dry cycles to virgin bitumen, a lignin blend, and compacted asphalt concrete specimens to replicate urban weathering. Cylindrical specimens underwent indirect tensile tests to assess water sensitivity, while beam samples underwent four-point bending tests to evaluate stiffness and fatigue resistance. The results indicate that this warm-mix asphalt, with lower atmospheric emissions during manufacturing and pavement construction, meets the mechanical demands of urban roads, particularly with respect to fatigue and water resistance. However, the findings also show that asphalt concrete containing lignin experiences excessive ageing of small specimens, and further testing on compacted slabs is needed to better simulate exposure to UV radiation in pavement layers. Overall, the study concludes that lignin lowers asphalt production temperatures and partially substitutes conventional binders, with promising applications in urban pavement technologies. Full article

GH3536 superalloy is widely used in the high-temperature components of aerospace applications for its excellent high-temperature strength and corrosion resistance. However, under such a harsh environment, surface defects can make the superalloy prone to corrosion and fatigue fractures. Therefore, it is important to eliminate surface defects through polishing. However, the existing polishing methods usually suffer from some issues such as surface integrity damage, low efficiency, and poor environmental sustainability. More importantly, these methods fail to account for the requirement of surface roughness below 0.05 μm in some high-precision aerospace components. Herein, the plasma electrolytic polishing (PEP) of GH3536 superalloy is systematically investigated and optimized through single-factor experiments and response surface methodology (RSM). A minimum surface roughness Ra of 0.044 μm with a mirror-like surface was achieved at a voltage of 303.8 V, electrolyte temperature of 66.2 °C, polishing time of 5 min, and submersion depth of 7.5 cm. At the same optimized condition, the material removal rate was 59.12 mg·min⁻¹. After polishing, the surface composition of GH3536 superalloy varied negligibly, while its corrosion resistance improved markedly, with a 53.72% increase in polarization resistance and a 43.46% decrease in corrosion current density. Meanwhile, the microhardness slightly decreased due to the removal of the work-hardened layer and the compressive residual stress exhibited a more uniform distribution across the surface, contributing to improved near-surface mechanical stability. This study establishes an optimized PEP parameter for improving the surface quality of GH3536 superalloy, offering a practical method for the precision finishing of aerospace-grade superalloy components. Full article

Background: Shenqi granule (SQG) was used clinically to strengthen the spleen and boost energy, alleviating physical weakness and limb fatigue caused by energy deficiency. However, the specific effects and potential molecular mechanisms of SQG in myocardial infarction (MI) treatment remain to be clarified. Methods: This study thoroughly evaluates SQG’s role in improving MIRI in rats using a biological approach. Network pharmacology, weighted gene co-expression network analysis (WGCNA), receiver operating characteristic (ROC), and immune landscape analysis were used to analyze components and key molecular targets. The therapeutic targets of SQG were then validated through molecular docking, molecular dynamics simulation, and experiments. Results: SQG reduced myocardial infarct size and improved myocardial function in rats. Network pharmacology analysis found that six bioactive compounds in SQG could target four proteins. Using WGCNA and ROC, two key targets of SQG were identified, MMP9 and ADH1C. Importantly, integrating PPI network prediction, molecular docking, and expression correlation analyses, MMP9 and ADH1C demonstrate strong physical binding potential and expression association, suggesting their possible involvement in MIRI-related pathways through the immune microenvironment. Molecular experiments and other methods confirmed that the five active ingredients in SQG (luteolin, quercetin, hederagenin, 7-O-methylisomucronulatol, and stigmasterol) can exert cardioprotective effects by stably binding to MMP9/ADH1C. Conclusions: SQG reduces myocardial infarct volume and enhances myocardial function in MIRI rats, likely via inhibiting MMP9 and ADH1C expression. This suggests SQG’s potential as a therapeutic agent for MI, with findings offering strong scientific support for SQG’s use in cardiovascular disease research. Full article

It is difficult to effectively evaluate the technology used to test fatigue in face gears due to their complexity, the lack of experimental data, and weak life evaluation methods. In this paper, we study fatigue experiment technology and carry out a life evaluation for hot rolling straight face gears. A hot rolling forming test was completed by analyzing and simulating the rolling formation of face gears, and the bending stress and fatigue life of face gears was simulated. We designed an experimental scheme and test bench for testing fatigue in straight face gears; this is the first bending fatigue life experiment carried out on hot rolling straight face gears in China. The BP neural network–Bootstrap sample expansion method and GM(1,1) model were carried out to evaluate the fatigue life of hot rolling straight face gears under information-poor conditions. A comparative analysis was carried out with skiving-formed straight face gears, which verifies the feasibility and superiority of hot rolling forming for straight face gears. This study provides a theoretical basis and technological support for the study of fatigue resistance in face gears, and applications for machine installations are provided. 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

Background: Fatigue is a multidimensional and subjective experience, and it is one of the most common symptoms of multiple sclerosis (MS), affecting up to 80% of patients and acting as a major driver of work disability. Despite its clinical significance, existing assessment tools often lack conceptual clarity or remain too lengthy for routine clinical use. Objective: To develop and evaluate a new patient-reported outcome instrument designed to assess multidimensional fatigue domains in patients with multiple sclerosis (MS) for use in clinical practice. Methods: This study was carried out in three research stages. Stage 1 (Concept Elicitation) involved qualitative interviews (n = 19) to identify core fatigue domains based on patient experience. Stage 2 (Cognitive Interviews) consisted of interviews with 50 patients to ensure the relevance and clarity of the items. Stage 3 (Exploratory Factor Analysis) and internal consistency testing (Cronbach’s alpha) were performed on the same sample of 50 patients to examine the preliminary factor structure and reliability. Results: Concept elicitation identified lack of energy and persistent exhaustion as core symptoms. The resulting 14-item instrument covers three subdomains: Psychosocial, Physical, and Cognitive. Exploratory factor analysis supported a three-factor solution explaining 75% of the total variance (Factor 1: 28%; Factor 2: 27%; Factor 3: 20%). Internal consistency was high across all factors: Psychosocial (α = 0.923), Physical (α = 0.895), and Cognitive (α = 0.844). Conclusions: This new instrument is a conceptually robust tool that captures the interconnected nature of fatigue in multiple sclerosis (MS). These initial findings support its internal structure and conceptual foundation, providing a practical tool for symptom monitoring in neurological consultations. Full article

Background/Objectives: Mothers of preterm infants face complex postpartum challenges, yet their needs are often overlooked in neonatal care. This review synthesizes evidence on maternal health needs, service utilization, perceived adequacy, and barriers to care. Methods: A systematic search of PubMed, CINAHL, and PsycINFO identified 16 peer-reviewed studies published between 2007 and 2025 on mothers of preterm infants. A narrative synthesis integrated quantitative and qualitative findings from NICU settings. Results: Across 16 included studies, all reported psychological and emotional needs, with anxiety, distress, and fear for infant survival frequently highlighted. Informational needs were identified in 11 studies, particularly regarding infant care and postpartum guidance. Physical needs were reported in 10 studies, including fatigue and pain affecting NICU engagement. Nursing support and lactation services were consistently accessed, whereas psychosocial services and postpartum follow-up were reported in fewer than half of the studies. Perceived adequacy depended on empathetic, individualized communication, while structural and contextual barriers, such as transportation, financial burden, and NICU policies, limited maternal engagement. Despite available services, gaps in emotional, informational, and practical support persisted. Conclusions: Mothers of preterm infants experience substantial postpartum health needs that are insufficiently addressed within current NICU-centered care structures. Integrating maternal-focused, continuous, and psychosocially informed postpartum care into neonatal services is essential to reduce care gaps and support maternal well-being during NICU hospitalization. Full article

The rapid rise in cryptocurrencies has created an investment environment marked by unprecedented levels of information volume, fragmentation, and volatility. While prior research has examined drivers of trust and adoption in crypto markets, far less is known about the psychological consequences of information overload on investor decision-making. This study addresses this gap through nineteen semi-structured interviews with individual cryptocurrency investors, analyzed using an inductive, manually conducted thematic approach. Findings reveal four interconnected dynamics: decision fatigue and paralysis, heuristic reliance on influencers and peers, emotional strain characterized by anxiety and fear of missing out (FOMO), and diverse coping strategies ranging from selective filtering to withdrawal. These results demonstrate that crypto investing is not only a financial process but also a cognitively and emotionally taxing experience. By linking investor narratives to broader theories of decision fatigue, bounded rationality, and consumer vulnerability, the study contributes to interdisciplinary debates in marketing, behavioral finance, and consumer psychology. Practically, the findings highlight the need for clearer communication strategies, supportive platform design, and financial education initiatives that help investors manage cognitive strain and decision fatigue. In a market where credibility is fluid and decisions are often made under conditions of overload, understanding the psychological dimensions of investment behavior is essential. Full article

A great deal of effort has been made to investigate and develop approaches to address driver behavior, fatigue, and sleepiness for different road users worldwide. However, very little research has been conducted to explore these issues in the context of Bus Rapid Transit (BRT) drivers in a low-income countries such as Mexico. The present study fills this gap. The aim of this study is to identify the human factors contributing to aberrant driver behavior (ADB) among BRT professional drivers in Mexico City. A total of 152 drivers participated in a self-reported survey. Exploratory factor analysis was performed on the BRT-ADBQ to identify the behavioral factors, and the Checklist Individual Strength (CIS–Fatigue) subscale was employed to assess the fatigue of drivers. The key findings were the following: (a) the created BRT-ABDQ identified two ADBs (violations and errors); (b) violations factors, but not errors, contributed to accident involvement; (c) ADB, fatigue, poor sleep and age (30–39) were predictors to accidents and (d) a linear trend has been revealed indicating that as the hours of sleep decreased, the experience of fatigue increased proportionally. The conclusion of the study is that ADB, sleepiness, and fatigue are real and existent among BRT drivers and should be a matter of concern for the case of the BRT organization that participated in the study. More generally, organizations running these systems should intervene by implementing sleep and fatigue reduction strategies to mitigate the adverse impact of these and thereby contribute to sustainable traffic safety and urban mobility. Full article

The straddle packer fracturing technique represents a core technology for reservoir stimulation in horizontal wells targeting deep shale gas formations. However, the fracturing string constrained by dual packers is highly susceptible to severe vibrations induced by high-pressure pulsating fluid flow, which subsequently leads to collisions between the string and the casing. These collisions may compromise the sealing integrity of the packers or cause fatigue damage to the string. The existing design of packer spacing primarily relies on static mechanical experience and lacks the support of nonlinear dynamics theory. As a result, it is difficult to maximize operational efficiency while ensuring safety. Therefore, this paper establishes a fluid–solid coupling fracturing string model that takes into account fluid pulsation, geometric nonlinearity and gap collision constraints. Using the Galerkin discretization and the fourth-order Runge–Kutta algorithm, the influence laws of packer spacing and flow rate on the system stability are systematically studied. Studies have shown that the spacing of packers non-monotonically controls the system stability. Both too short or too long packer spacings will induce chaotic instability. However, there exists a highly robust, stable contact window near the ratio. Within this interval, the fracturing string is locked onto a stable period-doubling orbit. Based on this proposed optimization criterion, compared with the traditional conservative design, the spacing of the packers can be extended by approximately 90%. This not only avoids the risk of chaos but also significantly improves the efficiency of the fracturing operation. Full article

Background/Objectives: Mindfulness-Based Cognitive Therapy (MBCT) is a well-documented treatment option for chronic pain. However, few studies have examined the emotional state experienced by participants with chronic pain during the sessions. This study aimed to assess the trajectory of mood experiences in an MBCT program and evaluate the effect on temporal mood state. Methods: The Temporary Mood Scale (TMS) was used to assess vigor, fatigue, anger-hostility, depression-dejection, tension-anxiety, and confusion before and after each MBCT session from July 2018 to May 2019. A total of 33 patients with chronic pain who attended the MBCT program were included in the study. A mixed-effect model was used to identify single-session and overall effects on each mood state. Pearson’s correlation analysis was used to examine the associations between changes in the six mood states and baseline conditions, including pain-related factors. Results: The mixed-effect model identified significant improvements in single-session effects on all mood states (p < 0.001). Significant overall effects were identified on vigor (p < 0.01), depression-dejection (p < 0.01), tension-anxiety (p < 0.001), and confusion (p < 0.05) states throughout the sessions. Moreover, participants with higher tension-anxiety at baseline showed significantly greater improvements in anger-hostility (p < 0.05), depression-dejection (p < 0.01), tension-anxiety (p < 0.05), and confusion (p < 0.01). Conclusions: Individual sessions and the overall MBCT program significantly improved the mood states of patients with chronic pain. Patients with higher tension-anxiety are likely to be effective treatment targets for MBCT programs. Full article

The operational reliability of the elastic wheel, essential for specialized vehicle mobility on complex terrain, is critically constrained by fatigue failure under multi-axis ground loads. While high-fidelity physics-based simulation provides an accurate assessment, its “one-simulation-per-test” paradigm is inefficient for exploring multi-condition, multi-parameter designs. Conversely, purely data-driven methods are hindered by the scarcity of high-quality fatigue data. This paper proposes LightGBM-CH, an integrated framework that couples Discrete Element Method–Multi-Body Dynamics (DEM-MBD) simulation with an enhanced LightGBM model to overcome these limitations. The framework first converts high-fidelity simulations into a configurable data generator, producing batches of dynamic load–stress response data. A physics-informed feature engineering scheme then extracts 122 discriminative features characterizing six-dimensional loads, fatigue damage metrics, and load–stress coupling. To address the “small-sample, high-dimensional” challenge, a tailored training strategy incorporating robust scaling, correlation-based feature selection, and stability-constrained hyperparameter optimization is developed. Simulation experiments demonstrate that the LightGBM-CH model achieves a determination coefficient of 0.9251 and a root mean square error of 67.06, significantly outperforming benchmark models in accuracy and generalization. The study validates the framework’s engineering efficacy, identifies key influencing factors such as peak–stress ratio, and provides an intelligent, data-informed pathway for fatigue-resistant elastic wheel design. Full article