Search Results (222)

The reliability of the EDS (Electric Drive System) in electric vehicles is crucial to overall vehicle performance. This study addresses the challenge of acquiring high-fidelity internal load data in the early development phase due to the absence of prototypes, overcoming the limitations of traditional road tests, which are costly, time-consuming, and unable to measure gear meshing forces. A method based on a VPG (Virtual Proving Ground) is proposed to acquire internal loads of a dual-motor EDS, analyze the impact of typical virtual fatigue durability road conditions on critical components, and generate load spectra for test bench experiments. Through point cloud data-based road modeling and rigid-flexible coupled simulation, dynamic loads are accurately extracted, with pseudo-damage contributions from eight intensified road conditions quantified using pseudo-damage calculations, and equivalent sinusoidal load spectra generated using the rainflow counting method and linear cumulative damage theory. Compared to the limitations of existing VPG methods that rely on simplified models, this study enhances the accuracy of internal load extraction, providing technical support for EDS durability testing. Building on existing research, it focuses on high-fidelity acquisition of EDS loads and load spectrum generation, improving applicability and addressing deficiencies in simulation accuracy. This study represents a novel application of VPG technology in electric drive system development, resolving the issue of insufficient early-stage load spectra. It provides data support for durability optimization and bench testing, with future validation planned using real vehicle data. Full article

The allostatic load index (AL_index) measures the cumulative physiological burden on the body due to stress. This prospective cohort study examined the relationships between certain molecular biomarkers, physical variables, and psychometric variables during deload and overload microcycles to contribute to developing an AL_index in professional team-sport athletes. Twelve elite male basketball players (18.3 [0.9] years; 77.2 [5.7] kg; 185 [9.0] cm) were monitored during two microcycles (deload and overload). Blood creatine kinase (CK) and urea levels, countermovement jump (CMJ), session-RPE (RPE × session duration [min], its exponentially weighted moving average [EWMA]), and a cumulative wellness score (sleep, stress, fatigue, muscle soreness, and mood) were assessed at different time points. Bayesian and robust statistics (Cohen’s ξ) were employed. CK rose from 222 U/L (deload) to 439 U/L (overload; +98%, large effect ξ = 0.65), while session-RPE load more than doubled (270 [269] AU to 733 [406] AU, ξ > 0.8). No difference was found in urea and wellness scores (cumulative or other components). CK levels showed moderate positive correlations with both EWMA of session-RPE (ρ = 0.346, p = 0.002) and reduced sleep quality (ρ = 0.25, p = 0.018). Bayesian modeling identified the EWMA of session-RPE as the strongest predictor of jump-defined fatigue (β = 0.012, 95% HDI [0.004, 0.021]), while CK demonstrated a small negative association (β = −0.009, HDI [−0.016, −0.001]). Finally, a principal component analysis (PCA) revealed that CK and the EWMA of session-RPE were robust indicators of physiological stress. A parsimonious index based on PCA loadings ([0.823 × CK] + [0.652 × EWMA of session-RPE]) demonstrated strong discriminative validity between microcycle phases (overload: 515, 95% HDI [442, 587] versus deload: 250, 95% HDI [218, 283], BF₁₀ > 100,000). CK and session-RPE may serve as sensitive biomarkers for inclusion in the AL_index for team sport athletes. Full article

Structural safety is of utmost importance for polar icebreakers under both navigation and icebreaking conditions. In this research, the Palmgren–Miner linear cumulative damage theory is employed to evaluate the structural fatigue lifespan of polar icebreakers. A spectral analysis, incorporating the time distribution coefficients for three load conditions, is executed to assess the fatigue damage at typical hot spots during navigation. For icebreaking activities, the ship–ice interaction loads with time history are simulated using the discrete ice element method, taking into account five sub-operating conditions. This simulation is coupled with rainflow counting to evaluate the fatigue damage. The results show that the cumulative fatigue damage during navigation is much less than that during icebreaking. Additionally, shoulder areas suffer more serious fatigue damage during icebreaking as a result of the direct impact of broken ice. Consequently, both navigation and icebreaking conditions should be considered in the design of hull structures and the assessment of fatigue strength for polar icebreakers. Full article

Subway train operators face the risk of cumulative cognitive stress due to factors such as visual fatigue from prolonged high-speed tunnel driving, irregular shift patterns, and the monotony of automated operations. This can lead to cognitive decline and human error accidents. Current monitoring of cognitive stress risk predominantly relies on single-modal methods, which are susceptible to environmental interference and offer limited accuracy. This study proposes an intelligent multimodal framework for cognitive stress monitoring by leveraging the symmetry principles in physiological and behavioral manifestations. The symmetry of photoplethysmography (PPG) waveforms and the bilateral symmetry of head movements serve as critical indicators reflecting autonomic nervous system homeostasis and cognitive load. By integrating these symmetry-based features, this study constructs a spatiotemporal dynamic feature set through fusing physiological signals such as PPG and galvanic skin response (GSR) with head and facial behavioral features. Furthermore, leveraging deep learning techniques, a hybrid PSO-CNN-GRU-Attention model is developed. Within this model, the Particle Swarm Optimization (PSO) algorithm dynamically adjusts hyperparameters, and an attention mechanism is introduced to weight multimodal features, enabling precise assessment of cognitive stress states. Experiments were conducted using a full-scale subway driving simulator, collecting data from 50 operators to validate the model’s feasibility. Results demonstrate that the complementary nature of multimodal physiological signals and behavioral features effectively overcomes the limitations of single-modal data, yielding significantly superior model performance. The PSO-CNN-GRU-Attention model achieved a predictive coefficient of determination (R²) of 0.89029 and a mean squared error (MSE) of 0.00461, outperforming the traditional BiLSTM model by approximately 22%. This research provides a high-accuracy, non-invasive solution for detecting cognitive stress in subway operators, offering a scientific basis for occupational health management and the formulation of safe driving intervention strategies. Full article

Background: Fibromyalgia (FM) is a chronic condition characterized by widespread pain, fatigue, cognitive difficulties, and psychological symptoms. Patients often present distinct personality traits and psychopathological patterns associated with symptom severity. Objective: To examine psychopathological profiles in FM patients based on functional, physical–somatic, and emotional impairment domains, as well as on cumulative disease severity. Materials and Methods: A cross-sectional study was conducted with 70 women clinically diagnosed with FM at a specialized Fibromyalgia Unit. Psychological functioning was assessed using the Personality Assessment Inventory, and disease impact was measured with the Fibromyalgia Impact Questionnaire. Hierarchical cluster analyses were used to classify participants into mild and severe clusters across FIQ domains, and psychological profiles were compared. Results: Patients with severe functional impairment had more affective dysregulation (76.43 vs. 70.20, p < 0.01) and somatic complaints (85.57 vs. 79.76, p < 0.05) than those with mild impairment. The severe–physical cluster showed greater mood instability, somatization, and suicidal ideation (60.94 vs. 53.61, p < 0.05). The severe–emotional cluster had higher rates of major depression (85.71% vs. 64.28%) and persistent depressive disorder (76.19% vs. 70.61%, p < 0.05). Severe showed more emotional instability and somatization, distinguishing it from mild. Greater cumulative severity intensified depressive and somatic disorders. Discussion: Findings support FM’s biopsychosocial profile, where emotional distress may relate to psychological and physical symptoms, reinforcing the need for personalized, multidisciplinary care and comprehensive assessment. Full article

Underground blasting vibrations are a critical factor influencing the stability of mine slopes. However, existing studies have yet to establish a quantitative relationship or clarify the underlying mechanisms linking blasting-induced vibrations and slope deformation. Taking the Shilu Iron Mine as a case study, this research develops a dynamic mechanical response model of slope stability that accounts for blasting loads. By integrating slope radar remote sensing data and applying the Pearson correlation coefficient, this study quantitatively evaluates—for the first time—the correlation between underground blasting activity and slope surface deformation. The results reveal that blasting vibrations are characterized by typical short-duration, high-amplitude pulse patterns, with horizontal shear stress identified as the primary trigger for slope shear failure. Both elevation and lithological conditions significantly influence the intensity of vibration responses: high-elevation areas and structurally loose rock masses exhibit greater dynamic sensitivity. A pronounced lag effect in slope deformation was observed following blasting, with cumulative displacements increasing by 10.13% and 34.06% at one and six hours post-blasting, respectively, showing a progressive intensification over time. Mechanistically, the impact of blasting on slope stability operates through three interrelated processes: abrupt perturbations in the stress environment, stress redistribution due to rock mass deformation, and the long-term accumulation of fatigue-induced damage. This integrated approach provides new insights into slope behavior under blasting disturbances and offers valuable guidance for slope stability assessment and hazard mitigation. Full article

Background: As COVID-19 transitions to an endemic phase, long COVID symptoms remain a significant public health issue affecting both physical and mental health. A notable proportion of college students report symptoms such as fatigue, cough, and brain fog persisting for weeks or months post-infection. Objectives: This study explored the prevalence and contributing factors of long COVID symptoms among both infected and uninfected students in medicine-related departments. Methods: A cross-sectional study was conducted using online self-reported questionnaires completed by 1523 undergraduate and graduate students in medicine-related departments at a medical university. Participants who had tested positive for COVID-19 within the past three months were excluded. The survey assessed long COVID symptoms, with comparisons conducted between infected and uninfected groups. Multivariate logistic regression identified risk factors associated with long COVID symptoms. Results: Of the 1118 participants, 47.5% of those with a prior COVID-19 diagnosis reported long COVID symptoms within the past month. Significant differences between the infected and uninfected groups were observed in physical, cognitive, and psychological health. Logistic regression identified that prior COVID-19 diagnosis had an association with the presence of long COVID symptoms (odds ratio = 1.48, p = 0.024) after adjusted model analysis. Meanwhile, higher anxiety levels (odds ratio = 1.09, p < 0.001) and a BMI ≥ 24 (odds ratio = 4.50, p < 0.01) were identified as significant risk factors for post-infection syndrome among previously infected students. Sex and exercise habits also influenced symptom prevalence. Conclusions: Since late 2023, with those experiencing cumulative infections surpassing half of Taiwan’s population, long COVID symptoms have persisted as a widespread concern affecting both physical and mental health, continuing into 2025. This study underscores critical risk factors and symptom patterns among students in medicine-related departments, reinforcing the urgency of sustained surveillance and targeted interventions to facilitate comprehensive recovery. Full article

This paper investigates the interplay between rubber network damage, carbon black (CB) network damage, heat exchange, and voiding mechanisms in filled Styrene-butadiene rubber (SBR) under cyclic loading. To do so, three carbon black filled SBR composites, SBR5, SBR30 and SBR60 are studied. The study aims to quantify molecular damage and its role in inducing reversible or irreversible heat flow and voiding behavior to inform the design of more resilient rubber composites with improved fatigue life and thermal management capabilities. The study effectively demonstrated how increasing carbon black content, particularly in SBR60, leads to a shift from mostly reversible to irreversible and cumulative damage mechanisms during cyclic loading, as evidenced by thermal, volumetric, and electrical resistivity changes. In particular, we identify a critical mechanical energy of 7 MJ.m⁻³ associated with such transition. These irreversible changes are strongly linked to the damage and re-arrangement of the carbon black filler network, as well as the rubber chains network and the formation/growth of voids, while reversible mechanisms are likely related to rubber chains alignment associated with entropic elasticity. Full article

The Ti-6Al-4V alloy is a typical α + β type titanium alloy and is widely used in the manufacture of aero-engine fans, compressor discs and blades. The working life of modern aero-engine components is usually required to reach more than 10⁸ cycles, which makes the infinite life design based on the traditional fatigue limit unsafe. In this study, through symmetrical loading high-cycle fatigue tests on Ti-6Al-4V titanium alloy, a nonlinear cumulative damage life prediction model was established. Further very-high-cycle fatigue tests of titanium alloys were carried out. The variation law of plastic strain energy in the evolution process of very-high-cycle fatigue damage of titanium alloy materials was described by introducing the internal stress parameter. A prediction model for the very-high-cycle fatigue life of titanium alloys was established, and the sensitivity analysis of model parameters was carried out. The results show that the established high-cycle/very-high-cycle fatigue models can fit the test data well. Moreover, based on the optimized model parameters through sensitivity analysis, the average error of the prediction results has decreased from 59% to 38%. The research aims to provide a model or method for predicting the engineering life of titanium alloys in the high-cycle/very-high-cycle range. Full article

This paper presents a Multimodal Hidden Markov Model (MHMM) framework specifically designed for real-time human proficiency assessment, integrating physiological (Heart Rate Variability (HRV)), behavioral (Task Completion Time (TCT)), and subjective (NASA Task Load Index (NASA-TLX)) data streams to infer latent human proficiency states in industrial settings. Using published empirical data from the surgical training literature, a comprehensive simulation study was conducted, with the MHMM (Trained) achieving 92.5% classification accuracy, significantly outperforming unimodal Hidden Markov Model (HMM) variants 61–63.9% and demonstrating competitive performance with advanced models such as Long Short-Term Memory (LSTM) networks 90%, and Conditional Random Field (CRF) 88.5%. The framework exhibited robustness across stress-test scenarios, including sensor noise, missing data, and imbalanced class distributions. A key advantage of the MHMM over black-box approaches is its interpretability by providing quantifiable transition probabilities that reveal learning rates, forgetting patterns, and contextual influences on proficiency dynamics. The model successfully captures context-dependent effects, including task complexity and cumulative fatigue, through dynamic transition matrices. When demonstrated through simulation, this framework establishes a foundation for developing adaptive operator-AI collaboration systems in Industry 5.0 environments. The MHMM’s combination of high accuracy, robustness, and interpretability makes it a promising candidate for future empirical validation in real-world industrial, healthcare, and training applications in which it is critical to understand and support human proficiency development. Full article

Background/Objectives: Non-invasive spinal cord transcutaneous stimulation (scTS) has expanded the therapeutic landscape of spinal cord injury (SCI) rehabilitation, offering potential benefits beyond compensatory approaches to paralysis. Children with SCI are particularly susceptible to developing neuromuscular scoliosis due to trunk muscle paralysis and ongoing skeletal growth, making targeted interventions crucial. As demonstrated in adults and pediatrics with SCI, the ability of scTS to acutely and safely enable an upright posture and trunk control could be leveraged as a therapeutic adjunct. Activity-based locomotor training (AB-LT) alone significantly improves trunk control in children with SCIs; combining it with scTS may enhance outcomes. This pilot study evaluated the safety, feasibility, and cumulative effects of AB-LT combined with scTS on trunk control in children with SCI. Methods: Three children with SCI completed 19 to 64 sessions of combined AB-LT and scTS. Adverse effects were monitored session to session, and trunk control was assessed pre- and post-intervention. Results: Across 130 interventions in three participants, 88.5% of sessions were free from adverse effects. Reported adverse events included autonomic dysreflexia (5.4%), skin redness at electrode sites (4.6%), and headaches (1.5%). No significant impact of scTS on fatigue or central hemodynamic parameters was observed. Post-intervention, all participants demonstrated improved trunk control during quiet and perturbed sitting. Conclusions: These findings provide the first evidence supporting the safety and feasibility of this combinatorial approach in pediatric SCI rehabilitation while emphasizing the importance of monitoring skin integrity and signs of autonomic dysreflexia. This intervention shows potential synergistic benefits, warranting further research to confirm efficacy and optimize therapeutic protocols. Full article

Transcranial direct current stimulation (tDCS) is a safe, well-tolerated method of non-invasively eliciting cortical neuromodulation. It has gained recent interest, especially for its positive clinical outcomes in neurodegenerative diseases such as multiple sclerosis (MS). However, its simultaneous (during tDCS) and cumulative effects (following repeated tDCS sessions) on the regional brain activity during rest need further investigation, especially in MS. This study aims to elucidate tDCS’ underpinnings, alongside its therapeutic impact in MS patients, using concurrent tDCS-MRI methods. In total, 20 MS patients (age = 48 ± 12 years; 8 males) and 28 healthy controls (HCs; age = 36 ± 15 years; 12 males) were recruited. They participated in a tDCS-MRI session, during which resting-state functional MRI (rs-fMRI) was used to measure the levels of the fractional amplitude of low-frequency fluctuations (fALFFs), which is an index of regional neuronal activity, before and during left anodal dorsolateral prefrontal cortex (DLPFC) tDCS (2.0 mA for 15 min). MS patients were then asked to return for an identical tDCS-MRI visit (follow-up) after 20 identical at-home tDCS sessions. Simultaneous tDCS-induced changes in fALFF are seen across cortical and subcortical areas in both HC and MS patients, with some regions showing increased and others decreased brain activity. In HCs, fALFF increased in the right pre- and post-central gyrus whilst it decreased in subcortical regions. Conversely, MS patients initially displayed increases in more posterior cortical regions but decreases in the superior and temporal cortical regions. At follow-up, MS patients showed reversed patterns, emphasizing significant cumulative effects of tDCS treatment upon brain excitation. Such long-lasting changes are further supported by greater pre-tDCS fALFFs measured at follow-up compared to baseline, especially around the cuneus. The results were significant after correcting for multiple comparisons (p-FDR < 0.05). Our study shows that tDCS has both simultaneous and cumulative effects on neuronal activity measured with rs-fMRI, especially involving major brain areas distant from the site of stimulation, and it is responsible for fatigue and cognitive and motor skills. Full article

To investigate the mechanical behavior and damage mechanism of notch–stud connectors in timber–concrete composites under fatigue loading, fifteen push-out specimens in five groups were designed with load cycles as the key variable. Fatigue failure modes and mechanisms were analyzed to examine fatigue life, stiffness degradation, and cumulative damage laws of connectors. Numerical simulations with up to 100 load cycles explored timber/concrete damage effects on stud fatigue performance. Based on the results, an S-N curve was established, a fatigue damage model developed, and a fatigue design method proposed for such connectors. Primary failure modes were stud fracture and local concrete crushing in notches. Stiffness degradation followed an inverted “S”-shaped “fast–slow–fast” pattern. Using residual slip as the damage variable, a two-stage fatigue damage evolution model was constructed from the damage–cycle ratio relationship, offering a new method for shear connector fatigue damage calculation in timber–concrete composites and enabling remaining life prediction for similar composite beam connectors. Finite element simulations of push-out specimens showed high consistency between calculated and experimental fatigue life/damage results, validating the conclusions. Full article

Objectives: The present study aimed to investigate changes in forearm muscle activity associated with short-term go-kart driving (680 m) and its potential effect on muscle activation patterns. Methods: Eleven male karting league drivers (mean age: 23.18 ± 1.40 years; body mass: 83.27 ± 10.98 kg; height: 182.73 ± 5.66 cm) volunteered to participate. Electromyographic (EMG) activity was recorded from four muscles: extensor carpi radialis (ECR), extensor carpi ulnaris (ECU), flexor carpi radialis (FCR), and flexor carpi ulnaris (FCU). Baseline EMG was measured before the intervention, followed by two consecutive kart-driving sessions on a 680 m closed track. Post-exercise EMG data were then collected. A repeated-measures analysis of covariance (ANCOVA) was used to analyze the effects of time (pre vs. post) while controlling for cumulative race time as a covariate. Results: A significant time effect with cumulative time as a covariate was observed, particularly in the ECR and ECU muscles on both the left and right sides. Notable findings include increases in maximum and mean activity of the left and right ECR (e.g., ECR right max: F = 51.57; p < 0.001; η² = 0.851) and ECU (e.g., ECU right max: F = 36.170; p < 0.001; η² = 0.801). Additionally, a significant increase was found in the maximum activation of the left FCR (F = 11.019; p = 0.009; η² = 0.550, which remained significant after controlling for total driving time. This heightened activation likely reflects an acute neuromuscular fatigue response to the demands of kart steering, rather than a long-term adaptation. Conclusions: The findings suggest that even short bouts of kart driving can induce measurable changes in neuromuscular activation of the forearm muscles, particularly in those involved in grip control and steering stability. This highlights the physical demands of karting and its potential impact on the upper limb muscle conditioning. Full article

Background: A glioblastoma (GBM) is a type of tumor originating from the glial brain cells, the astrocytes, and thus belongs to the astrocytoma group. Bevacizumab (BV) is a treatment for GBM. BV is the active ingredient in the drugs Avastin^®, Alymsys^®, Mvasi^® and ZiraBev^®. It is currently approved as second-line treatment for GBM recurrence in combination with radiotherapy, and as first-line treatment for other cancers, including advanced colorectal cancer, metastatic breast cancer and advanced non-small-cell lung cancer. The objective of this systematic review was to analyze the scientific evidence from the science-based literature on the therapeutic effect and adverse effects of the drug BV in patients with GBM or GBM multiforme. Methods: We systematically searched electronic databases for the literature search, including the MEDLINE (via PubMed), SCOPUS, Google Scholar, the Cumulative Index to Nursing and Allied Health Literature and Web of Science databases, covering records from their earliest data to December 2024. Randomized or controlled clinical trials that were published in English or Spanish were included. The following keywords were used in different combinations: “Bevacizumab therapy”, “Bevacizumab pharmaceutical”, “Glioblastoma”, “Glioma” and “multiform glioblastoma”. Results: The use of Bevacizumab has been extensively studied in the scientific literature, with beneficial effects in symptom control. However, the adverse effects of BV vary across different types of carcinomas, which is why it has already been established that these adverse effects must be taken into consideration. In our meta-analysis of adverse effects, we found 14 adverse effects and estimated their prevalence, with an average of 19% (CI: 4 to 44%). The most significant vascular adverse effect was thromboembolism, which led to a greater number of complications for patients with GBM. Finally, the most common adverse effects were nausea, vomiting, fatigue and hypertension. Conclusions: While the beneficial properties of this pharmacological therapy have been observed, its adverse effect profile requires constant evaluation, as it includes vascular, blood and symptomatic adverse effects, which must be analyzed on a case-by-case basis and with great attention, especially in the case of more serious complications such as thromboembolic events. Full article