Search Results (68)

The Brain–Computer Interface (BCI) is a system that enables communication between the brain and external devices by translating brain activity into commands. Electroencephalography (EEG) is a commonly used modality for measuring brain activity. However, its low signal-to-noise ratio (SNR) and electrode reference problems lead to poor spatial resolution. As a result, EEG signals are often contaminated with physiological artifacts such as muscle movements. Therefore, this study used novel tripolar concentric ring electrodes (TCREs) to record brain signals related to overt and covert speech. Brain signals associated with overt and covert speech were recorded using TCRE and disc electrodes. Classification algorithms, including K-Nearest Neighbors (KNN), Fully Connected Neural Networks (FCNN), and Convolutional Neural Networks (CNN), were used to classify the TCRE and conventional EEG signals. The data were collected from 16 healthy participants, consisting of 10 males and 6 females. The experimental results demonstrate that TCREs provide superior performance compared to conventional disc electrodes. In addition, the $0.5$–$1.2\mathrm{s}$ interval, corresponding to the peak stimulus window, exhibits a maximum power of $250\mathsf{\mu }\mathrm{V}$. The average accuracy achieved during this peak epoch was $86.25\%$, whereas the remaining epoch shows an accuracy of $83.5\%$ using TCREs. Full article

Pumping stations serve as the foundation platform for large-scale vertical fluid machinery, and their structural dynamics directly govern the vibration levels and long-term reliability of the installed pump units. In low-head vertical pumping stations, the interaction among the massive underwater substructure, flexible above-ground powerhouse, and surrounding backfill soil creates a complex dynamic system whose behavior remains insufficiently characterized. This study presents a comprehensive dynamic analysis of a large-scale vertical pumping station using a high-fidelity three-dimensional finite element model that incorporates the powerhouse superstructure, submerged concrete substructure, and backfill soil. Modal analysis under four boundary condition scenarios—varying in soil participation and interface contact conditions—systematically quantifies the influence of soil–structure interaction on natural frequencies and mode shapes. Resonance verification against three primary excitation sources—rotational frequency (4.917 Hz), blade passage frequency (24.583 Hz), and rotor–stator interaction frequency (196.667 Hz)—is extended from the first 50 modes to the 400th mode to assess potential high-order resonance risks. Results show that the roof slab, with its large span and low stiffness, exhibits the highest vibration susceptibility. For the rotational frequency, modes 4–12 fall below the 20% code-specified safety margin but rapidly exceed the threshold thereafter. For the blade passage frequency, the separation ratio decreases progressively with increasing mode order within the first 50 modes, and the extended analysis up to the 400th mode shows that the separation ratio remains well above 20% throughout modes 51–400. Consequently, no substantial resonance risk exists for the blade passage frequency within the entire computed range. The rotor–stator interaction frequency remains safely separated with margins exceeding 95%. These findings demonstrate the profound influence of soil–structure interaction and confirm that, despite a decreasing trend in frequency separation at higher orders, the blade passage frequency poses no substantial resonance risk up to the 400th mode. This work provides a rigorous analytical framework for vibration-informed design and optimization of pump foundation systems, with direct implications for the reliability and operational safety of large-scale vertical fluid machinery. Full article

Small-disturbance damping characteristics have become a critical concern in renewable-dominated power systems under low short circuit ratio (SCR) conditions. In heterogeneous systems composed of grid-following photovoltaic (GFL-PV) and grid-forming energy storage system (GFM-ESS) units, strong dynamic coupling may weaken the damping of critical oscillation modes, thereby complicating stability analysis and coordinated parameter tuning. This paper proposes a damping enhancement strategy for a low-SCR GFL-PV/GFM-ESS system. The main innovation is an integrated damping-oriented framework that links detailed small-disturbance modeling, dominant-mode identification, participation-factor analysis, parameter-sensitivity evaluation, and coordinated optimization. First, a dynamic model including GFL-PV, GFM-ESS, and their coupling is established, and the corresponding linearized model is verified. Then, eigenvalue, modal, participation-factor, and sensitivity analyses are performed to identify weakly damped modes, key state variables, and sensitive parameters. Furthermore, a Joint Opposite Selection-enhanced particle swarm optimization (JOS-PSO) strategy is proposed to tune multiple coupled parameters. Simulation results under different operating conditions show that the proposed method improves damping characteristics, small-disturbance stability, and dynamic performance. Full article

Background: Educational interventions are central to breast cancer survivorship care, yet adherence may vary depending on delivery modality. Objective: To compare the effectiveness of face-to-face, online, telephonic, and mixed educational modalities on patient adherence among breast cancer survivors. Methods: A systematic review of randomized controlled trials and Bayesian network meta-analysis were conducted following PRISMA 2020 guidelines. Randomized controlled trials evaluating educational interventions in breast cancer survivors were included. Methodology quality of included studies was assessed using the RoB-2 tool. Pairwise meta-analyses using random-effects models estimated Odds Ratios (ORs) for adherence. A Bayesian network meta-analysis synthesized direct and indirect evidence, and treatment rankings were calculated using SUCRA values. Results: Eleven trials comprising 963 participants were included. In pairwise meta-analysis, no modality demonstrated statistically significant superiority over usual care: face-to-face (OR 0.79; 95% CI 0.44–1.41), mixed (OR 0.42; 95% CI 0.07–2.37), online (OR 0.90; 95% CI 0.49–1.68), and telephonic (OR 0.57; 95% CI 0.18–1.78). The network meta-analysis confirmed the absence of statistically significant differences across modalities. SUCRA rankings suggested that usual care (76.7%) and online modalities (73.1%) had the highest probability of being among the best-performing strategies, followed by face-to-face (51.9%), telephonic (25.4%), and mixed (23.0%). Conclusions: No educational modality demonstrated superior adherence compared to usual care. Delivery format alone may not determine engagement in breast cancer survivorship programs. Decisions should prioritize feasibility and patient preference. Full article

Objective: To compare the efficacy and safety of gas-based therapies for chronic wounds using a systematic review and network meta-analysis (NMA). Methods: Following PRISMA 2020, we systematically searched PubMed, Embase, Web of Science, Cochrane CENTRAL, and CBM from inception to 1 October 2025, screened studies in duplicate, and resolved disagreements by arbitration (κ = 0.87). Randomized controlled trials (RCTs) enrolling adults with chronic wounds were eligible; the primary endpoint was complete wound healing. Pairwise meta-analysis used risk ratios (RRs) with 95% CIs; heterogeneity was assessed with Q/I² and random-effects models were applied when appropriate. A frequentist NMA synthesized direct and indirect evidence, and treatments were ranked with SUCRA. Publication bias (Egger/Begg) and evidence certainty (GRADE) were evaluated. Results: Twenty-seven RCTs comprising 1673 participants were included. In pairwise pooling, gas therapies significantly increased complete healing versus standard care (random-effects RR = 2.17, 95% CI 1.61–2.94), with substantial heterogeneity (I² = 75.7%); results were directionally consistent and robust to sensitivity analyses. Prespecified subgroup analyses suggested effect modification by intervention type and wound etiology. In the NMA, most gas modalities showed beneficial trends versus standard care; however, SUCRA ranking placed standard care highest (93.9%), a finding attributed by the authors to network structure and between-study variability. Ozone therapy and topical oxygen ranked next, whereas HBOT and cold atmospheric plasma ranked mid-range; CO₂ therapy ranked lowest due to sparse evidence. Small-study effects were likely (Egger p < 0.001; Begg p = 0.013), and overall certainty was graded as moderate, limited primarily by heterogeneity, imprecision, and potential publication bias. Conclusions: Across RCTs, gas therapies as a class improve the probability of complete healing in chronic wounds relative to standard care, but effect sizes vary by modality and wound type. Given heterogeneity, possible publication bias, and inconsistencies within the evidence network, these findings should be applied with caution. HBOT remains the modality supported by the broadest evidence base, while large, high-quality, multicenter RCTs are needed to refine comparative effectiveness and safety rankings across gas therapies. Full article

The hybrid parallel operation of the grid-following (GFL) converter and the grid-forming (GFM) converter has become a typical scenario in distribution networks. The vastly different control philosophies and dynamics between the two give rise to complex small-signal stability issues, especially under weak grids. Traditional methods primarily rely on equivalent models or impedance-based approaches at fixed operating points, which struggle to reveal the system instability mechanisms when the capacity ratio between the two types of converters changes. This paper establishes a three-port dynamic average model for a grid-connected system with heterogeneous GFL-GFM converters. Using the participation factor analysis method, the system’s dominant modes are identified, and the key parameters influencing oscillations at different frequencies, as well as their formation processes, are revealed. Furthermore, a stability analysis method for variable capacity ratios is proposed. This method re-performs modal analysis based on the varying capacities of the GFM and GFL converters, revealing the dominant factors and influencing mechanisms of system instability during capacity transitions. Finally, a simulation model is built in PSCAD/EMTDC to verify the correctness of the proposed three-port model and the theoretical analysis results. Full article

Cognitive stress, also known as mental workload, constitutes a central topic within the field of psychophysiology due to its role in modulating attention, autonomic regulation, and stress reactivity. Furthermore, it bears direct relevance to practical monitoring systems that employ non-invasive sensing techniques. This study investigates whether a multimodal, non-invasive measurement setup can detect systematic physiological differences between Resting periods and short episodes of cognitive load within the same individuals. Additionally, it explores the capacity of such a system to differentiate tasks characterized by varying cognitive demands. A sequential, within-subject protocol was employed, comprising five consecutive phases (rest 1, Stroop, rest 12, subtraction, rest 3), during which five modalities were recorded concurrently: EEG, heart rate (HR), galvanic skin response (GSR), facial surface temperature, and oxygen saturation (SpO₂). Beyond phase-wise inspection of time-series data, an exploratory assessment of similarity across participants was conducted using correlation coefficients. The maximum cross-participant correlations observed were 0.88 (HR), 0.90 (GSR), 0.83 (facial temperature), and 0.77 (SpO₂); however, these correlations were used only as exploratory descriptors of inter-individual similarity and did not imply a significant phase effect. For inferential analysis, phase-wise epoch means were evaluated through one-factor repeated-measures ANOVA. The heart rate exhibited a robust main effect of phase (F(4, 32) = 10.5862, p_GG = 0.01044, ηp² = 0.5696), with higher HR observed during cognitive load epochs (e.g., 77.841 ± 11.777 bpm at rest 1 versus 83.926 ± 14.532 bpm during subtraction). The relatively large standard deviation reflects variability between subjects rather than variability within epochs. Regarding processed baseline-referenced GSR, the omnibus phase effect was not statistically significant under the conservative Greenhouse–Geisser correction; therefore, GSR was interpreted as exploratory in this dataset. Facial temperature and SpO₂ likewise did not show statistically significant omnibus phase effects under Greenhouse–Geisser correction (e.g., SpO₂: p_GG = 0.1209). EEG-derived measures provide supplementary central evidence of task engagement; entropy variations within an approximate dynamic range of 0.2 to 0.8 were observed, and the α/θ ratios demonstrated nearly a twofold distinction between rest and cognitive load epochs across different leads. Full article

Background: Intrahepatic cholangiocarcinoma (ICC) is an aggressive primary liver malignancy with limited survival, largely due to delayed diagnosis, recurrence and limited effective therapeutic options. Radiomics- and artificial intelligence (AI)-based imaging models have emerged as promising tools to improve noninvasive detection and differentiation of ICC. We conducted a systematic review and meta-analysis to evaluate the diagnostic performance of radiomics-based AI models for ICC. Methods: A systematic search of PubMed, Embase, Scopus, and the Cochrane Library was performed from inception through 2025 in accordance with PRISMA guidelines. Studies assessing radiomics- or AI-based models derived from CT, MRI, PET, or ultrasound for differentiation of ICC from other hepatic lesions were included. Pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were estimated using a bivariate random-effects model. Study quality and risk of bias were assessed using the Radiomics Quality Score (RQS) and QUADAS-2 tools. Results: Twenty retrospective studies comprising 8746 participants were included. Across pooled validation and test datasets, radiomics-based AI models demonstrated a pooled sensitivity of 0.77 (95% CI, 0.69–0.84) and specificity of 0.88 (95% CI, 0.78–0.94) for differentiating ICC from non-ICC hepatic lesions. The pooled PLR was 6.81 (95% CI, 3.51–13.2), and the pooled NLR was 0.23 (95% CI, 0.09–0.61). CT-based models showed higher diagnostic performance compared with MRI and ultrasound. Subgroup and meta-regression analyses identified imaging modality, contrast phase, segmentation strategy, and validation approach as contributors to interstudy heterogeneity. The overall methodological quality demonstrated a mean Radiomics Quality Score (RQS) of 14.0 (range 11–24), corresponding to approximately 39% of the maximum achievable score. External validation cohorts were incorporated in 60% of the studies, although adherence to standardized feature reproducibility frameworks varied. Conclusions: Radiomics-based AI models demonstrate clinically meaningful diagnostic accuracy for noninvasive differentiation of ICC and may complement conventional imaging in preoperative evaluation. Prospective, multicenter studies with standardized imaging protocols and rigorous external validation are required before routine clinical adoption. Full article

Piping systems in critical facilities, such as power plants, hospitals, and industrial sites, are essential nonstructural components determining operational continuity during seismic events. Past earthquake events, including those at Northridge, Kobe, and Chile, have repeatedly demonstrated the vulnerability of sprinklers and utility piping, wherein leakage and connection failures led to severe secondary hazards. However, existing conventional seismic evaluations based on equivalent static loading are limited in capturing the frequency-dependent dynamic characteristics and resonance potential of inherently multi-degree-of-freedom piping structures. This study proposes a modal-based dynamic screening approach to pre-emptively identify resonance-prone frequency bands by incorporating the frequency characteristics of representative earthquakes recorded in South Korea. Water supply, sprinkler, and cooling water piping systems were analyzed using three key indicators: effective modal mass participation, cumulative effective modal mass ratios, and directional translational components of mode shapes. The results demonstrate that the proposed dynamic screening approach effectively identifies resonance vulnerabilities across different piping configurations, proving its utility as a more precise seismic screening tool compared to conventional methods. This study underscores the practical necessity of modal analysis as a preliminary step for advanced dynamic evaluations and provides a rational framework for enhancing the seismic safety of nonstructural components in critical facilities. Full article

Background: Smoking is a major public health concern worldwide and is associated with adverse effects on pulmonary function, postural control, and overall physical performance. Aquatic exercise has gained increasing attention as a safe and effective training modality due to its unique physical properties. However, evidence regarding the effects of aquatic exercise on pulmonary function and dynamic balance in young adult smokers remains limited. Objective: This study aimed to investigate the effects of an 8-week aquatic exercise training program on pulmonary function parameters and dynamic balance performance in young adult smokers. Methods: Twenty-two physically inactive male smokers were randomly assigned to an experimental group (n = 11) or a control group (n = 11). The experimental group participated in an aquatic exercise program three times per week for eight weeks, while the control group maintained their usual daily activities. Pulmonary function parameters, including FEV₁, FVC, FEV₁/FVC, PEF, PIF, MVV, VC, TV, and IVC, were assessed using spirometers. Dynamic balance performance was evaluated using a portable dynamic balance platform under single-leg (right and left) and double-leg conditions. Data were analyzed using a two-way repeated-measures ANOVA. Results: Statistically significant time × group interaction effects were observed for vital capacity (VC) (p = 0.033, η²_p = 0.378) and tidal volume (TV) (p < 0.001, η²_p = 0.734), suggesting potentially greater changes in the experimental group compared to the control group. Peak expiratory flow (PEF) demonstrated significant main effects of time (p = 0.047) and group (p = 0.031). Dynamic balance performance showed statistically significant time × group interaction effects across right-leg, left-leg, and bilateral conditions (p < 0.01), with large effect sizes (η²_p = 0.762, 0.609, and 0.507, respectively). However, given the pilot nature and limited sample size of the study, these findings should be interpreted as preliminary. No significant changes were observed in FEV₁, FVC, or FEV₁/FVC ratio. Conclusions: This pilot randomized trial suggests that an 8-week aquatic exercise program is feasible and may produce preliminary improvements in selected pulmonary function parameters and dynamic balance in young adult smokers. Larger, adequately powered trials are required to confirm these findings. Full article

The non-invasive recording of spinal cord neuronal activity, also known as electrospinography (ESG), using high-density surface electromyography (HD-sEMG) is a promising emerging biosensing modality. However, these recordings often contain electrocardiographic (ECG) artifacts that must be removed for accurate analysis. Given the emerging nature of ESG and the lack of dedicated signal processing methods, this study assesses the performance of seven established EMG denoising algorithms for their ability to preserve the broad spectral bandwidth needed for future ESG characterization: Template Subtraction (TS), Adaptive Template Subtraction (ATS), High-Pass Filtering at 200 Hz (HP200), ATS combined with HP200, Second-Order Extended Kalman Smoother (EKS2), Stationary Wavelet Transform (SWT), and Empirical Mode Decomposition (EMD). Performance was quantified using six metrics: Relative Error (RE), Signal-to-Noise Ratio (SNR), Cross-Correlation (CC), Spectral Distortion (SD), and Kurtosis Ratio (KR2) and its variation ($\Delta$KR2). ESG data were recorded from nine healthy participants at brachial and lumbar plexus sites with various electrode configurations. ATS consistently outperformed all other methods in suppressing cardiac artifacts of varying shapes. Although it did not fully preserve low-frequency content, ATS achieved the best balance between artifact removal and signal integrity. Algorithm performance improved when ECG contamination was lower, especially in brachial plexus recordings with closer reference electrodes. Full article

Objective: The aim was to evaluate the effects of two high-resistance training (RT) protocols combined with curcumin supplementation on antioxidant capacity, systemic inflammation, bone and muscle health, and body composition. Methods: Eighty-one apparently healthy older adults [(68.2 ± 4.6 years (57% women); BMI 26.4 ± 4.8 kg/m²; minimally active according to IPAQ] were randomly allocated to accentuated eccentric (Aecc), maximal strength (Max), or a non-training control (C). Additionally, participants received either a bio-optimized curcumin formulation (Cur) or a placebo (Pla), resulting in six study groups: Aecc-Cur, Aecc-Pla, Max-Cur, Max-Pla, C-Cur, and C-Pla. Participants underwent pre- and post-intervention assessments of oxidative stress, inflammation, and bone health parameters, whole-body composition, and muscle function. Aecc and Max performed six familiarization sessions and a 16-week intervention. Participants in the curcumin groups received 500 mg/day of a bio-optimized curcumin formulation (Cursol^TM; 2 × 250 mg capsules per day, corresponding to 10.50 mg/day of curcumin) throughout the intervention. Data were analyzed using three-way repeated-measures ANOVA/ANCOVA with time (pre–post) as the within-subject factor and training group and supplementation as between-subject factors, with Least Significant Difference post hoc comparisons and effect sizes (Hedges’ g, ηp²) reported, and the significance level set at p < 0.05. Results: Aecc was the most effective in improving antioxidant capacity (glutathione; F = 25.57, p ≤ 0.001, ηp² = 0.262) and bone biomarkers (serum-procollagen type I N-propeptide—P1NP, p ≤ 0.001, ηp² = 0.504; serum beta C-terminal cross-linked telopeptide of type I collagen—β-CTX—p = 0.022, ηp² = 0.074, and their ratio—P1NP/β-CTX—p ≤ 0.001, ηp² = 0.605). Interleukin-6 (IL-6) decreased more in Aecc (p ≤ 0.001, ηp² = 0.584) and tumor necrosis factor-alpha (TNF-α) in Max (p ≤ 0.001, ηp² = 0.471). Both groups similarly improved body composition and muscle function. Bone mineral density was generally unchanged. Overall, curcumin supplementation enhanced the benefits of high-RT programs (further glutathione increase in Aecc [Hedge’s g: 0.49]; IL-6 decrease in both modalities [Hedge’s g: 0.48–1.27]; decrease in TNF-α in controls [Hedge’s g: 0.47]; better outcomes in P1NP/β-CTX in all groups [Hedge’s g: 0.46–1.46]; among others). Conclusions: Aecc is recommended for supporting antioxidant capacity and bone health, while the choice between Aecc and Max may depend on the individual’s inflammatory profile. Curcumin supplementation further amplifies the benefits of both RT protocols across most outcome variables. Full article

Background: Endothelial and microvascular dysfunction play a central role in the pathogenesis of both cardiovascular and neurodegenerative disorders. However, whether impaired peripheral endothelial function independently predicts cognitive decline, cerebral small-vessel disease (SVD) progression, or stroke remains uncertain. Methods: We conducted a systematic review and meta-analysis of prospective cohort studies assessing the prognostic value of non-invasive peripheral endothelial tests—flow-mediated dilation (FMD), peripheral arterial tonometry (PAT/EndoPAT), and sublingual microcirculatory imaging—for cognitive or cerebrovascular outcomes. Databases (PubMed, Embase, Scopus, Web of Science) were searched from inception through 30 September 2025. Study quality was appraised using the Newcastle–Ottawa Scale (NOS), and evidence certainty was graded via GRADE. Random-effects models (DerSimonian–Laird or REML) pooled hazard ratios (HRs) using inverse-variance weighting. PROSPERO-registered (CRD42025211876). Results: Fifteen prospective cohorts (n = 13,972 participants; median follow-up 4.3 years) met inclusion criteria. Across all modalities, impaired endothelial or microvascular function predicted cognitive decline, SVD progression, or cerebrovascular events (pooled HR = 1.72, 95% CI 1.38–2.14, p < 0.001; I² = 57%). Subgroup analyses confirmed consistent associations for FMD (HR = 1.59, 95% CI 1.27–1.98) and PAT/EndoPAT (HR = 1.84, 95% CI 1.40–2.41). Evidence certainty was rated moderate-to-high according to GRADE. Conclusions: Peripheral endothelial dysfunction, measured by validated non-invasive techniques, independently predicts future cognitive and cerebrovascular events. These findings support the concept of a vascular–neural continuum, suggesting that endothelial health represents a modifiable biomarker for early neurovascular risk stratification. Routine assessment of endothelial function may help identify high-risk individuals and guide preventive interventions aimed at preserving brain and vascular health. Full article

Vibration control systems are extensively utilized in structures to enhance their resilience against earthquakes and wind forces. However, structures with significant damping exhibit atypical damping behaviors, which impose constraints on the effectiveness of traditional modal analysis methods for discerning modal responses and estimating properties. To surmount this challenge, a novel State-Space-Based Modal Decomposition approach is proposed in this study. The State-Space-Based Modal Decomposition technique adeptly extracts modal responses and identifies modal attributes from acquired data of highly damped structures. The approach accurately calculates damping ratios and natural frequencies by scrutinizing the power spectrum within the deconstructed modal response. The validity of this method is confirmed through a numerical simulation with a three-degree-of-freedom system equipped with oil dampers and experimentation of a structure outfitted with a tuned mass damper system. The findings underscore that the transfer function of the modal response in state-space encompasses both displacement and velocity transfer functions. The results demonstrate that precise estimation of modal parameters can be accomplished by suitably evaluating the participation ratio of the two response components. Full article

Background: Plantar fasciitis (PF) is a common enthesopathy in patients with ankylosing spondylitis (AS). Shear wave elastography (SWE) and the Belgrade ultrasound enthesitis score (BUSES) may detect PF, but their comparative diagnostic performance is unclear. Objective: To compare SWE with the BUSES for identifying PF in individuals with and without AS. Methods: In this cross-sectional study, 96 participants were stratified into AS and non-AS populations, each further divided based on the presence or absence of clinical PF. Demographic data, the American Orthopedic Foot and Ankle Society Score (AOFAS), and the BASDAI score were recorded. All subjects underwent grayscale ultrasonography, the BUSES scoring, and SWE assessment of the plantar fascia. Logistic regression models were constructed for each population, controlling for age, body mass index (BMI), and fascia–skin distance. ROC curve analyses were performed to evaluate diagnostic accuracy. Results: In both AS and non-AS groups, SWE and the BUSES were significant predictors of PF (p < 0.05). SWE demonstrated slightly higher diagnostic accuracy, with area under the curve (AUC) values of 0.845 (AS) and 0.837 (non-AS), compared to the BUSES with AUCs of 0.785 and 0.831, respectively. SWE also showed stronger adjusted odds ratios in regression models. The interobserver agreement was good to excellent for both modalities. Conclusions: Both SWE and the BUSES are effective for PF detection, with SWE offering marginally superior diagnostic performance, particularly in AS patients. SWE may enhance the early identification of biomechanical changes in the plantar fascia. Full article