Search Results (44)

Purpose: Acute exercise elicits coordinated neuroendocrine and autonomic responses that are strongly influenced by exercise modality and intensity. While cortisol and salivary alpha-amylase are widely used as peripheral indicators of hypothalamic–pituitary–adrenal (HPA) axis and sympathetic nervous system activation, respectively, salivary orexin remains an exploratory biomarker whose relationship with central orexinergic activity is not yet fully established, particularly in response to different exercise conditions. This study aimed to compare the acute salivary responses of orexin, alpha-amylase, and cortisol following distinct exercise modalities characterized by different physiological loads. Methods: A repeated-measures design was employed in a sample of physically active young women. Each participant completed four experimental sessions: high-intensity interval training (HIIT), combined exercise (CE), moderate-intensity continuous training (MICT), and yoga. Saliva samples were collected at baseline (T0), immediately post-exercise (T1), and during early recovery (T2 and T3). Biomarker concentrations were analyzed to assess temporal dynamics and modality-dependent differences. Results: All biomarkers showed modality-dependent responses. HIIT elicited the most pronounced increases in alpha-amylase and cortisol, reflecting robust sympathetic and HPA axis activation, whereas CE and MICT induced more moderate responses. Yoga was associated with minimal changes across all biomarkers. Orexin displayed a graded response across the exercise modalities, with higher post-exercise levels observed following HIIT compared to lower-intensity conditions. Temporal analyses revealed distinct kinetic profiles, with alpha-amylase peaking rapidly in the early post-exercise phase, whereas cortisol exhibited a more delayed response. Conclusions: These findings demonstrate that acute salivary responses of orexin, alpha-amylase, and cortisol are strongly modulated by exercise modality, supporting the importance of an integrated, multi-biomarker approach to characterize the physiological response to exercise. The inclusion of salivary orexin provides exploratory information on a potentially relevant arousal- and energy-regulation-related pathway, complementing established peripheral markers of autonomic and endocrine activation. This integrated perspective may contribute to a more comprehensive understanding of exercise-induced stress responses in young women. Full article

The Zeta-Minimizer Theorem provides a fully deductive variational foundation for the hydrogen oxidation reaction (HOR) and oxygen reduction reaction (ORR) in proton exchange membrane fuel cells. Starting from three primitive thermodynamic axioms and the helical geometry of the phase functional, a multi-extent dynamical system is constructed that simultaneously treats the electrochemical reaction coordinates and the adsorption extents of the participating species at the solid–electrolyte interface. The combined Hessian of the phase functional yields a complete spectrum of relaxation rates whose eigenvalues and eigenvectors emerge directly from the solid blackbox constants $C_k$ and the helical partition functions of the reactive species. Adiabatic elimination of the fast surface modes produces an effective single-extent description in which voltage (or overpotential) appears as the conjugate variable, exactly analogous to the role of pressure in the corresponding gas-phase ammonia synthesis framework. The resulting nonlinear rate law is thermodynamically consistent at all conditions, recovers the Butler–Volmer and Tafel forms as well-defined limiting cases, and incorporates the effects of temperature, dilution, and catalyst-specific interface constants without empirical activation energies or adjustable reaction orders. The framework therefore unifies equilibrium, kinetics, and modal dynamics of HOR and ORR within a single variational structure, offering a parameter-light, first-principles alternative to classical empirical electrocatalytic rate expressions while preserving transparent contact with established limiting laws. Full article

Nonlinear correlations among modal coefficients enable interpretable reduced-order models (ROMs) for microfluidic flows. In this study, flow around a cylinder in a microchannel at Re = 100 is investigated using proper orthogonal decomposition (POD), dynamic mode decomposition (DMD), and POD + DMD. The sparse identification of nonlinear dynamics (SINDy) is employed to identify nonlinear correlations among modal coefficients. The results show that the first POD mode contains 33% of the total kinetic energy, and the first 14 modes capture 99.2% of the energy. A minimal ROM with only two degrees of freedom is constructed, in which the real and imaginary parts of active modal coefficients differ in phase by π/2 and their magnitude equals the vortex-shedding fundamental frequency (1.067 Hz). Among sparse regression algorithms, the FROLS method yields the sparsest representation (sparsity rate 0.05), whereas other methods give sparsity rate > 0.3. Reducing the temporal resolution from 0.01 to 0.1 increases the manifold dynamics coefficient error from 0% to 0.56%. Only the ROMs built from POD + DMD and DMD preserve essential kinematic resolution. The POD-based ROM fails to maintain correct energy levels over long-time integration. Therefore, the nonlinear correlation between POD + DMD modal coefficients is recommended for developing ROMs in microchannel flows when accuracy, interpretability, and stability are considered together. Full article

In the aerospace industry, thin-web gears are preferred for achieving high power-density transmission. However, thin-webbed structures always lead to out-of-plane resonance during the transmission process, which commonly happens in helical gears, manifesting as severe vibration at a specific rotational speed. To address this, a shaft–web–ring dynamic model is proposed. The shaft, gear web, and gear ring are modelled based on the Timoshenko straight beam, Mindlin plate, and Timoshenko bent beam theory. Simultaneously, the potential energy caused by the time-varying meshing stiffness is coupled to the gear ring. The kinetic and potential energies of each discretized finite element of the components are derived based on elastic deformation theory, and the governing equations of each element are obtained using Hamilton’s principle. The model is verified through a modal experiment. The comparison with traditional rotor-gear models has demonstrated the significance of gear body flexibility in helical gears with thin webs. The effects of the web thickness and helix angle on dynamic response are studied, revealing that gear web elasticity and an appropriately high helix angle can effectively reduce vibrations at the support bearing, prevent excessive vibrations, and contribute to vibration and noise reduction in the transmission system. Full article

BNCT (Boron Neutron Capture Therapy) is a binary radiotherapeutic modality in which high LET (Linear Energy Transfer) particles are generated from ¹⁰B(n,α)⁷Li reaction, ideally within boron-loaded tumour cells, so the therapeutic outcome depends critically on the pharmacokinetics and biodistribution of boron carriers. In this review, boron-containing agents for BNCT, with a focus on ADMET (absorption, distribution, metabolism, excretion and toxicity) and model-informed design, were examined. Low-MW (low-molecular-weight) compounds, peptide conjugates, polymeric and nanostructured platforms and cell-based vectors were surveyed and how physicochemical properties, transporter engagement and nano–bio interactions govern tumour uptake, subcellular localisation and normal tissue exposure were discussed. A shift from maximising boron content towards optimising exposure profiles using PET (Positron Emission Tomography), PBK (physiologically based pharmacokinetic) modelling and in silico ADMET tools to define irradiation windows was also discussed. Classical agents such as BPA (Boronophenylalanine) and BSH (Sodium Borocaptate) are contrasted with newer polymeric and metallacarborane-based carriers, with attention to brain penetration, endosomal escape, linker stability, biodegradation and elimination routes, as well as platform-specific toxicities. Incontestably, further progress in BNCT will highly depend on integrating imaging-derived kinetics with PBPK-informed dose planning and engineering subcellularly precise yet degradable carriers, and that ADMET-guided design and spatiotemporal coordination are central to achieving reproducible clinical benefit from BNCT’s spatial selectivity. Full article

Background: Boron neutron capture therapy (BNCT) represents a highly selective therapeutic modality for recalcitrant cancers, leveraging the nuclear reaction initiated by thermal neutron capture in boron-10 (¹⁰B) to deliver high-linear energy transfer radiation (α-particles and ⁷Li ions) directly within tumor cell boundaries. However, the widespread clinical adoption of BNCT is critically hampered by the pharmacological challenge of achieving sufficiently high, tumor-selective intracellular ¹⁰B concentrations (20–50 μg of ¹⁰B/g tissue). Conventional small-molecule boron carriers often exhibit dose-limiting non-specificity, rapid systemic clearance, and poor cellular uptake kinetics. Methods: To overcome these delivery barriers, we synthesized and characterized a novel dual-modality nanoplatform based on highly biocompatible, functionalized graphene oxide (GO). This platform was structurally optimized via covalent conjugation with high-boron content carborane clusters (dodecacarborane derivatives) for enhanced BNCT efficacy. Crucially, the nanocarrier was further decorated with plasmonic gold nanostructures (AuNPs), endowing the system with intrinsic surface-enhanced Raman scattering (SERS) properties, enabling real-time, high-resolution intracellular tracking and quantification. Results: We evaluated the synthesized GO@Carborane@Au nanoplatforms for their stability, cytotoxicity, and internalization characteristics. Cytotoxicity assays demonstrated excellent biocompatibility against the non-malignant human keratinocyte line (HaCaT) while showing selective toxicity (upon irradiation, if tested) and high cellular uptake efficiency in the aggressive human glioblastoma tumor cell line (T98G). The integrated plasmonic component allowed for the successful, non-destructive monitoring of nanoplatform delivery and accumulation within both HaCaT and T98G cells using SERS microscopy, confirming the potential for pharmacokinetic and biodistribution studies in vivo. Conclusions: This work details the successful synthesis and preliminary in vitro validation of a unique graphene oxide-based dual-modality nanoplatform designed to address the critical delivery and monitoring challenges of BNCT. By combining highly efficient carborane delivery with an integrated photonic trace marker, this system establishes a robust paradigm for next-generation theranostic agents, significantly advancing the potential for precision, image-guided BNCT for difficult-to-treat cancers like glioblastoma. Full article

Sloshing-induced impact pressure is a key damage factor for marine liquid tanks. While research aimed at overcoming screen failure in sloshing suppression under high-frequency excitation has focused on wave height, the dataset of impact pressure remains lacking. Moreover, the pattern of pressure suppression under broadband excitation remains unclear. The primary contribution of this work is the first experimental dataset of impact pressure with vertical slat screens under broadband horizontal and vertical excitation. Second, it reveals pressure suppression patterns by screens across varying excitation frequencies and screen numbers. The results demonstrate that vertical slat screens can effectively suppress pressure. First, screen position matters more than number, proving that suppression is dominated by modal disturbance. Second, wave-height suppression does not reliably represent pressure suppression. Pressure suppression is systematically weaker. An exception occurs under vertical excitation, where pressure suppression can be stronger even when wave-height suppression fails. The results highlight the suppression mechanism dominated by modal disturbance and the instability inherent to parametric sloshing. Wave height, reflecting global potential energy, is effectively suppressed by modal disturbance. Pressure, originating from local kinetic energy, can be effectively suppressed by both modal disturbance and vortex dissipation. Full article

This study investigates a shielded reactor coolant pump (RCP) using a thermo-fluid–structure interaction approach to numerically simulate the internal flow characteristics, impeller forces, and rotor vibration modes during rapid start-up following a loss of power accident under high-temperature and high-pressure conditions. A three-dimensional fluid–structure coupling model was established, employing the SST k-ω turbulence model and a one-way fluid–structure interaction method. The effects of three different start-up acceleration rates on pump head, pressure pulsation, vortex structures, turbulent kinetic energy distribution, and dynamic stress on the impeller were systematically analyzed. The results indicate that the medium-acceleration scenario (4.5 s start-up time) exhibits the most favorable performance in terms of pressure pulsation control, vorticity suppression, and stress distribution, effectively avoiding cavitation and structural resonance while ensuring a smooth and reliable start-up process. Modal analysis reveals that the rotor system is predominantly characterized by bending vibrations with satisfactory torsional stiffness and appropriately set critical speeds, presenting no resonance risks. This research provides theoretical foundations and engineering references for the safe restart of RCPs under extreme operational conditions. Full article

Proteins elicit various metabolic and physiological functions that are related to physical performance. Due to increased need in athletes, protein supplementation has been widely used to support recovery and performance. However, the extent to which acute gains in muscle protein synthesis translate into measurable performance remains debated. This narrative review synthesizes evidence from trials on supplemental proteins across resistance, endurance, and mixed-modality training, comparing sources (whey, casein, soy, pea, and blends). Moreover, this review summarizes dosing and timing strategies, with notes for master, diabetic, and female athletes. It is well-established that supplemental protein enhances fat-free mass and, to a lesser extent, strength when baseline dietary protein is suboptimal. However, the effects are smaller when habitual intake already meets athletic targets. Whey, as a rapid protein and rich in leucine, reliably elicits an acute anabolic response, while casein provides prolonged elevated aminoacidemia. When total intake and leucine thresholds are matched, plant proteins and blends can yield comparable long-term adaptations. In addition, studies showed that the distribution and strategic timing around exercise (post-exercise first, with optional pre-sleep casein or blends) support recovery during high-frequency training or energy deficit. Protein co-ingested with carbohydrate in endurance and high-intensity functional training (HIFT) can also help glycogen restoration and attenuate muscle-damage markers, though effects on sport outcomes are inconsistent. The evidence in diabetic athletes is limited; guidance extrapolates from diabetes and athlete studies, with benefits apparent when intake, quality, or distribution are limited. Furthermore, evidence indicates that anabolic resistance in master athletes requires higher per-meal doses and distribution, with post-exercise and pre-sleep feedings valuable. Consistently, female athletes partaking in aerobic and resistance training while supplementing with protein demonstrate desired body composition adaptations. Overall, although supplemental protein helps close gaps between intake and physiological demand, various factors may influence its regimen. Protein source may help the kinetics balance, amino-acid profile, and dietary preferences. Alternatively, timing may influence the protein effects on training and recovery. Full article

An integrated physiological model would be useful for monitoring internal load in functional fitness, including formats like CrossFit and Hyrox. Traditional performance metrics often neglect internal strain, energy system engagement, and neuromuscular fatigue, central to these modalities. Oxygen uptake kinetics, metabolic profiling, heart rate and heart rate variability monitoring, and neuromuscular fatigue assessment can be employed for load monitoring. Breath-by-breath oxygen uptake analysis characterizes aerobic activation and recovery. Metabolic stress is estimated via indirect calorimetry and capillary blood lactate to quantify oxidative, glycolytic, and phosphagen contributions. Heart rate is tracked continuously to assess session intensity, while heart rate variability provides insights into autonomic recovery. Neuromuscular fatigue can be assessed via countermovement jump performance, offering sensitive measures of recovery and training tolerance. Portable tools such as the Cosmed K5™, Lactate Pro 2, heart rate sensors, and force platforms support real-time monitoring in training and competitions. Rather than advocating for the continuous use of advanced tools, the model promotes strategic integration of high-precision methods for research, and practical, low-cost alternatives (e.g., heart rate monitoring, session rating of perceived exertion, or jump analysis apps) for day-to-day coaching. This approach enables early detection of maladaptation, supports individualized training adjustments, and improves safety and performance outcomes. Ultimately, this framework bridges physiological science and real-world practice, providing value across both applied and research settings. Full article

The cooling system is a core component for a vehicle’s powertrains to operate smoothly and maintain a satisfying noise, vibration, and harshness (NVH) performance. However, advances in new energy vehicles bring with them complex requirements for the cooling fan design due to new issues such as increased heat load, dynamic variations, and high-speed vibrations, which demand the optimization of fan dynamics over a wide range of parameters. In this paper, by thoroughly checking the effect of rigid–flexible coupling and the geometrically complex elastic frame of the fan, we propose a combined modeling approach to reduce the computational time of broad-range parameter variation analysis and examine the vibration problem in the cooling fans under various external excitations. First, the complicated frame of the fan is simplified through virtual prototyping based on an experiment. Then, modal transition is applied, reducing the complex kinetic expression, and a time-invariant system model is derived with multi-blade coordinate transformation. Stability and bifurcation analysis are performed regarding different excitation couplings from the rotor, powertrain, and road. The results of the simulation and experiment illustrate that the proposed methodology achieves a substantial reduction in computational time, and all degrees of freedom (DOFs) are divided into two groups including symmetrical and asymmetrical types. The results also imply the great potential for the optimization and control of the high-speed fan’s vibration for new energy cars. Full article

This work presents a numerical investigation of Richtmyer–Meshkov instability (RMI) in shock-driven single-mode stratified heavy fluid layers, with emphasis on the influence of the Atwood number. High-order modal discontinuous Galerkin simulations are carried out for Atwood numbers ranging from $A=0.30$ to $0.72$, allowing a systematic study of interface evolution, vorticity dynamics, and mixing. The analysis considers diagnostic quantities such as interface trajectories, normalized interface length and amplitude, vorticity extrema, circulation, enstrophy, and kinetic energy. The results demonstrate that the Atwood number plays a central role in instability development. At low A, interface deformation remains smooth and coherent, with weaker vorticity deposition and delayed nonlinear roll-up. As A increases, baroclinic torque intensifies, leading to rapid perturbation growth, stronger vortex roll-ups, and earlier onset of secondary instabilities such as Kelvin–Helmholtz vortices. Enstrophy, circulation, and interface measures show systematic amplification with increasing density contrast, while the total kinetic energy exhibits relatively weak sensitivity to A. Overall, the study highlights how the Atwood number governs the transition from linear to nonlinear dynamics, controlling both large-scale interface morphology and the formation of small-scale vortical structures. These findings provide physical insight into shock–interface interactions and contribute to predictive modeling of instability-driven mixing in multicomponent flows. Full article

This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. Four established selection criteria—modal kinetic energy (MKE), modal strain energy (MSE), modal assurance criterion (MAC) sensitivity, and mutual information (MI)—are used to evaluate DOF sensitivity and generate candidate pools. These are followed by one of four optimization algorithms—greedy, genetic algorithm (GA), particle swarm optimization (PSO), or simulated annealing (SA)—to identify the optimal subset of sensor locations. A key feature of the proposed approach is the incorporation of constraint dynamics using the Udwadia–Kalaba (U–K) generalized inverse formulation, which enables the accurate expansion of structural responses from sparse sensor data. The framework assumes a noise-free environment during the initial sensor design phase, but robustness is verified through extensive Monte Carlo simulations under multiple noise levels in a numerical experiment. This combined methodology offers an effective and flexible solution for data-driven sensor deployment in structural health monitoring. To clarify the rationale for using the Udwadia–Kalaba (U–K) generalized inverse, we note that unlike conventional pseudo-inverses, the U–K method incorporates physical constraints derived from partial mode shapes. This allows a more accurate and physically consistent reconstruction of unmeasured responses, particularly under sparse sensing. To clarify the benefit of using the U–K generalized inverse over conventional pseudo-inverses, we emphasize that the U–K method allows the incorporation of physical constraints derived from partial mode shapes directly into the reconstruction process. This leads to a constrained dynamic solution that not only reflects the known structural behavior but also improves numerical conditioning, particularly in underdetermined or ill-posed cases. Unlike conventional Moore–Penrose pseudo-inverses, which yield purely algebraic solutions without physical insight, the U–K formulation ensures that reconstructed responses adhere to dynamic compatibility, thereby reducing artifacts caused by sparse measurements or noise. Compared to unconstrained least-squares solutions, the U–K approach improves stability and interpretability in practical SHM scenarios. Full article

This study presents high-fidelity numerical simulations of the shock-accelerated single-mode Richtmyer–Meshkov instability (RMI) in a light helium layer confined between two interfaces and surrounded by nitrogen gas. A high-order modal discontinuous Galerkin method is employed to solve the two-dimensional compressible Euler equations, enabling detailed investigation of interface evolution, vorticity dynamics, and flow structure development under various physical conditions. The effects of helium layer thickness, initial perturbation amplitude, and incident shock Mach number are systematically explored by analyzing interface morphology, vorticity generation, enstrophy, and kinetic energy. The results show that increasing the helium layer thickness enhances vorticity accumulation and interface deformation by delaying interaction with the second interface, allowing more sustained instability growth. Larger initial perturbation amplitudes promote earlier onset of nonlinear deformation and stronger baroclinic vorticity generation, while higher shock strengths intensify pressure gradients across the interface, accelerating instability amplification and mixing. These findings highlight the critical interplay between layer confinement, perturbation strength, and shock strength in governing the nonlinear evolution of RMI in light fluid layers. Full article

Dual-energy CT (DECT) has emerged as a novel imaging modality that offers a multiparametric approach for noninvasive adrenal lesion characterization. This narrative review examines recent advances in DECT—including virtual non-contrast imaging, iodine density quantification, spectral curve analysis, and material density mapping—for differentiating benign adrenal adenomas from metastases. Conventional CT techniques rely primarily on unenhanced attenuation measurements and contrast washout kinetics; however, these methods may be limited in evaluating lipid-poor adenomas, and in cases where imaging features overlap with metastatic lesions. Although virtual non-contrast imaging with DECT tends to overestimate attenuation relative to true non-contrast scans, the recalibration of diagnostic thresholds and integration with complementary parameters, such as the iodine density-to-virtual non-contrast attenuation ratio, can significantly enhance sensitivity and specificity. Additional parameters, including fat fraction analysis and the evaluation of attenuation changes across energy spectra, further refine tissue characterization by quantifying intracellular lipid content and vascularity. Material density analysis has demonstrated near-perfect diagnostic accuracy in select studies. By tailoring imaging evaluation to the unique spectral and compositional features of each adrenal lesion, DECT contributes to a more personalized diagnostic approach. This individualization allows for better differentiation between benign and malignant findings, potentially avoiding unnecessary interventions and enabling more targeted clinical management. Despite these promising developments, challenges remain regarding the standardization of acquisition protocols, optimization of diagnostic thresholds, and minimization of interobserver variability. Emerging radiomics and machine learning applications may further automate lesion classification and improve diagnostic accuracy. Thus, DECT holds considerable potential to improve diagnostic confidence, reduce radiation exposure, and streamline the management of patients with adrenal incidentalomas, although further multicenter validation is warranted. Full article