Search Results (550)

Magnetorheological fluids (MRFs) are multiphase materials whose viscosity can be controlled via magnetic fields. However, particle sedimentation undermines their long-term stability. This review examines stabilization strategies based on the interaction between ultrasonic waves and time-varying magnetic fields, analyzed through advanced mathematical models. The propagation of acoustic waves in spherical and cylindrical domains is studied, including effects such as cavitation, acoustic radiation forces, and viscous attenuation. The Biot–Stoll poroelastic model is employed to describe saturated granular media, while magnetic field modulation is investigated as a means to balance gravitational settling. The analysis highlights how acousto-magnetic coupling supports the design of programmable and self-stabilizing intelligent fluids for complex applications. Full article

Background: The relationship between spleen and bone marrow stiffness, and other features of abnormal myeloproliferation has long been described. However, the scientific knowledge in this area remains very superficial. This review evaluated the diagnostic effectiveness of various ultrasound (US) methods in the assessment of neoplastic myeloproliferation using spleen stiffness measurement (SSM). Aim: To explore the diagnostic accuracy of US techniques in assessing spleen stiffness, determining which of them may be suitable for the diagnosis of myeloproliferative diseases in adults. Methods: The review included original retrospective or prospective studies published in the last five years (2019–2024) in peer-reviewed medical journals that reported receiver operating characteristics (ROCs) for SSM and the articles concerning the relation between SSM values and neoplastic myeloproliferation. The studies were identified through PubMed searches on 1 July and 1 December 2024. Quality was assessed using the QUADAS-2 tool. Results were tabulated according to the diagnostic method separately for myeloproliferative neoplasms (MNs) and for other clinical findings. Results: The review included 52 studies providing ROCs for SSM or compatibility between operators, and five studies covering the relation between SSM values and MNs. Conclusions: Acoustic radiation force impulse (ARFI), two-dimensional shear wave elastography (2D-SWE), transient elastography (TE), and point shear wave elastography (p-SWE) are promising methods for measuring SSM that can be incorporated into the diagnosis, screening, and monitoring system in MNs. Full article

Firstly, this paper reviews the fundamental theories of solid surface wettability and contact angle hysteresis. Subsequently, it further introduces four typical wettability-engineered surfaces with low hysteresis (superhydrophobic, superamphiphobic, super-slippery, and liquid-like smooth surfaces). Finally, it focuses on the latest research progress in the field of droplet manipulation on open planar surfaces with engineered wettability. To achieve droplet manipulation, the core driving forces primarily stem from natural forces guided by bioinspired gradient surfaces or the regulatory effects of external fields. In terms of bioinspired self-propelled droplet movement, this paper summarizes research inspired by natural organisms such as desert beetles, cacti, self-aligning floating seeds of emergent plants, or water-walking insects, which construct bioinspired special gradient surfaces to induce Laplace pressure differences or wettability gradients on both sides of droplets for droplet manipulation. Moreover, this paper further analyzes the mechanisms, advantages, and limitations of these self-propelled approaches, while summarizing the corresponding driving force sources and their theoretical formulas. For droplet manipulation under external fields, this paper elaborates on various external stimuli including electric fields, thermal fields, optical fields, acoustic fields, and magnetic fields. Among them, electric fields involve actuation mechanisms such as directly applied electrostatic forces and indirectly applied electrocapillary forces; thermal fields influence droplet motion through thermoresponsive wettability gradients and thermocapillary effects; optical fields cover multiple wavelengths including near-infrared, ultraviolet, and visible light; acoustic fields utilize horizontal and vertical acoustic radiation pressure or acoustic wave-induced acoustic streaming for droplet manipulation; the magnetic force acting on droplets may originate from their interior, surface, or external substrates. Based on these different transport principles, this paper comparatively analyzes the unique characteristics of droplet manipulation under the five external fields. Finally, this paper summarizes the current challenges and issues in the research of droplet manipulation on the open planar surfaces and provides an outlook on future development directions in this field. Full article

To reveal the meso-mechanical essence of deep rock mass failure and capture precursor information, this study focuses on soft rock failure mechanisms. Based on the discontinuous medium discrete element method (DEM), we employed digital image correlation (DIC) technology, acoustic emission (AE) monitoring, and particle flow code (PFC) numerical simulation to investigate the failure evolution characteristics and AE quantitative representation of soft rocks. Key findings include the following: Localized high-strain zones emerge on specimen surfaces before macroscopic crack visualization, with crack tip positions guiding both high-strain zones and crack propagation directions. Strong force chain evolution exhibits high consistency with the macroscopic stress response—as stress increases and damage progresses, force chains concentrate near macroscopic fracture surfaces, aligning with crack propagation directions, while numerous short force chains coalesce into longer chains. The spatial and temporal distribution characteristics of acoustic emissions were explored, and the damage types were quantitatively characterized, with ring-down counts demonstrating four distinct stages: sporadic, gradual increase, stepwise growth, and surge. Shear failures predominantly occurred along macroscopic fracture surfaces. At the same time, there is a phenomenon of acoustic emission silence in front of the stress peak in the surrounding rock of deep soft rock roadway, as a potential precursor indicator for engineering disaster early warning. These findings provide critical theoretical support for deep engineering disaster prediction. Full article

The mechanisms by which rotation influences zonal flows (ZFs) in plasma are incompletely understood, presenting a significant challenge in the study of plasma dynamics. This research addresses this gap by investigating the role of non-inertial effects—specifically centrifugal and Coriolis forces—on Geodesic Acoustic Modes (GAMs) and ZFs in rotating tokamak plasmas. While previous studies have linked centrifugal convection to plasma toroidal rotation, they often overlook the Coriolis effects or inconsistently incorporate non-inertial terms into magneto-hydrodynamic (MHD) equations. In this work, we derive self-consistent drift-ordered two-fluid equations from the collisional Vlasov equation in a non-inertial frame, and we modify the Hermes cold ion code to simulate the impact of rotation on GAMs and ZFs. Our simulations reveal that toroidal rotation enhances ZF amplitude and GAM frequency, with Coriolis convection playing a critical role in GAM propagation and the global structure of ZFs. Analysis of simulation outcomes indicates that centrifugal drift drives parallel velocity growth, while Coriolis drift facilitates radial propagation of GAMs. This work may provide valuable insights into momentum transport and flow shear dynamics in tokamaks, with implications for turbulence suppression and confinement optimization. Full article

Migrastatic strategies are considered as candidate therapeutic approaches to suppress cancer invasion into local surrounding tissues and metastatic spread. The F-actin cytoskeleton is responsible for key properties regulating (cancer) cell migration. The cortical F-actin network controls cell stiffness, which, in turn, determines cell migration strategies and efficiency. Moreover, the dynamic remodeling of F-actin networks mediating filopodia, lamellipodia, and F-actin stress fibers is crucial for cell migration. Here, we have used a conditional knockout approach to delete cofilin, an F-actin-binding protein that controls severing. We find that the deletion of cofilin prevents the migration of cancer cells from tumoroids into the surrounding extracellular matrix without affecting their viability. This identifies cofilin as a candidate target to suppress metastatic spread. Pharmacological inhibitors interfering with F-actin dynamics have been developed but their effects are pleiotropic, including severe toxicity, and their impact on 3D tumor cell migration has not been tested or separated from this toxicity. Using concentration ranges of a panel of inhibitors, we select cytochalasins based on the suppression of 2D migration at non-toxic concentrations. We then show that these attenuate the escape of tumor cells from tumoroids and their migration into the surrounding extracellular matrix without toxicity in 3D cultures. This effect is accompanied by suppression of cell stiffness at such non-toxic concentrations, as measured by acoustic force spectroscopy. These findings identify cytochalasins B and D as candidate migrastatic drugs to suppress metastatic spread. Full article

Acoustic coupling agents serve as critical interfacial materials connecting piezoelectric transducers with microfluidic chips in acoustofluidic systems. Their performance directly impacts acoustic wave transmission efficiency, device reusability, and reliability in biomedical applications. Considering the rapidly growing body of research in the field of acoustic microfluidics, this review aims to serve as an all-in-one reference on the role of acoustic coupling agents and relevant considerations pertinent to acoustofluidic devices for anyone working in or seeking to enter the field of disposable acoustofluidic devices. To this end, this review seeks to summarize and categorize key aspects of acoustic couplants in the implementation of acoustofluidic devices by examining their underlying physical mechanisms, material classifications, and core applications of coupling agents in acoustofluidics. Gel-based coupling agents are particularly favored for their long-term stability, high coupling efficiency, and ease of preparation, making them integral to acoustic flow control applications. In practice, coupling agents facilitate microparticle trapping, droplet manipulation, and biosample sorting through acoustic impedance matching and wave mode conversion (e.g., Rayleigh-to-Lamb waves). Their thickness and acoustic properties (sound velocity, attenuation coefficient) further modulate sound field distribution to optimize acoustic radiation forces and thermal effects. However, challenges remain regarding stability (evaporation, thermal degradation) and chip compatibility. Further aspects of research into gel-based agents requiring attention include multilayer coupled designs, dynamic thickness control, and enhancing biocompatibility to advance acoustofluidic technologies in point-of-care diagnostics and high-throughput analysis. Full article

The vibration and noise of friction pairs are severe when cutting titanium alloy with cemented carbide tools, and the surface micro-texture can significantly reduce noise and friction. Therefore, it is very important to clarify the correlation mechanism between friction noise and friction force for processing quality control. Consequently, investigating the underlying mechanisms that link friction noise and friction is of considerable importance. This study focuses on the friction and wear acoustic signals generated by micro-textured cemented carbide–titanium alloy. A friction testing platform specifically designed for the micro-textured cemented carbide grinding of titanium alloy has been established. Acoustic sensors are employed to capture the acoustic signals, while ultra-depth-of-field microscopy and scanning electron microscopy are utilized for surface analysis. A novel approach utilizing the dung beetle algorithm (DBO) is proposed to optimize the parameters of variational mode decomposition (VMD), which is subsequently combined with wavelet packet threshold denoising (WPT) to enhance the quality of the original signal. Continuous wavelet transform (CWT) is applied for time–frequency analysis, facilitating a discussion on the underlying mechanisms of micro-texture. Additionally, features are extracted from the time domain, frequency domain, wavelet packet, and entropy. The Relief-F algorithm is employed to identify 19 significant features, leading to the development of a hybrid model that integrates Bayesian optimization (BO) and Transformer-LSTM for predicting friction. Experimental results indicate that the model achieves an R² value of 0.9835, a root mean square error (RMSE) of 0.2271, a mean absolute error (MAE) of 0.1880, and a mean bias error (MBE) of 0.1410 on the test dataset. The predictive performance and stability of this model are markedly superior to those of the BO-LSTM, LSTM–Attention, and CNN–LSTM–Attention models. This research presents a robust methodology for predicting friction in the context of friction and wear of cemented carbide–titanium alloys. Full article

Cantonese Automatic Speech Recognition (ASR) is hindered by tonal complexity, acoustic diversity, and a lack of labelled data. This study proposes a phoneme-aware hierarchical augmentation framework that enhances performance without additional annotation. A Phoneme Substitution Matrix (PSM), built from Montreal Forced Aligner alignments and Tacotron-2 synthesis, injects adversarial phoneme variants into both transcripts and their aligned audio segments, enlarging pronunciation diversity. Concurrently, a semantic-aware SpecAugment scheme exploits wav2vec 2.0 attention heat maps and keyword boundaries to adaptively mask informative time–frequency regions; a reinforcement-learning controller tunes the masking schedule online, forcing the model to rely on a wider context. On the Common Voice Cantonese 50 h subset, the combined strategy reduces the character error rate (CER) from 26.17% to 16.88% with wav2vec 2.0 and from 38.83% to 23.55% with Zipformer. At 100 h, the CER further drops to 4.27% and 2.32%, yielding relative gains of 32–44%. Ablation studies confirm that phoneme-level and masking components provide complementary benefits. The framework offers a practical, model-independent path toward accurate ASR for Cantonese and other low-resource tonal languages. This paper presents an intelligent sensing-oriented modeling framework for speech signals, which is suitable for deployment on edge or embedded systems to process input from audio sensors (e.g., microphones) and shows promising potential for voice-interactive terminal applications. Full article

The submerged waterjet exhibits advantages such as uniform inflow, minimal flow distortion, and excellent acoustic performance, making it particularly suitable for high-speed vessels. This study investigates the open-water characteristics of the submerged waterjet and develops a body force model for the submerged waterjet propulsion system. First, under uniform inflow conditions, numerical simulations were performed using the body force method by replacing the rotor with a virtual blade and simultaneously replacing both the rotor and stator. The results of the body force model were then compared in detail with those obtained using the sliding mesh method. Second, the influence of the inflow velocity plane position on the results of the body force model was analyzed. The results indicate that the body force method, which replaces both the rotor and stator with a virtual blade, fails to accurately simulate the forces acting on various components of the propeller and the true distribution of the propeller’s flow field. In contrast, the method that replaces only the rotor with a virtual blade produces results for component forces and flow fields that are largely consistent with the results of the sliding mesh method, demonstrating the stability and reliability of the body force model. Additionally, the position of the inflow velocity plane has no significant effect on the model’s computational results. Full article

As open-pit mining extends to greater depths, slope stability is becoming a critical factor in ensuring safe production. This issue is particularly pronounced in geological settings with weak interlayers, where sudden slope failures are more likely to occur, demanding precise and reliable stability assessment methods. In this study, a typical open-pit slope with weak interlayers was investigated. Acoustic testing and ground-penetrating radar were employed to identify rock mass structural features and delineate loose zones, enabling detailed rock mass zoning and the development of numerical simulation models for stability analysis. The results indicate that (1) the slope exhibits poor overall integrity, dominated by blocky to fragmented structures with well-developed joints and significant weak interlayers, posing a severe threat to stability; (2) in the absence of support, the slope’s dissipated energy, displacement, and plastic zone volume all exceeded the failure threshold (Δ < 0), and the safety factor was only 0.962, indicating a near-failure state; after implementing support measures, the safety factor increased to 1.31, demonstrating a significant improvement in stability; (3) prior to excavation, the energy damage index (ds) in the 1195–1240 m platform zone reached 0.82, which dropped to 0.48 after reinforcement, confirming the effectiveness of support in reducing energy damage and enhancing slope stability; (4) field monitoring data of displacement and anchor rod forces further validated the stabilizing effect of the support system, providing strong assurance for safe mine operation. By integrating cusp catastrophe theory with energy-based analysis, this study establishes a comprehensive evaluation framework for slope stability under complex geological conditions, offering substantial practical value for deep open-pit mining projects. Full article

To investigate the degradation mechanisms of the surrounding rock in abandoned mine roadways used for oil storage, this study combined uniaxial compression tests with digital image correlation (DIC), scanning electron microscopy (SEM), and other techniques to analyze the evolution of the rock mechanical properties under the coupled effects of oil–water soaking and initial damage. The results indicate that oil–water soaking induces the loss of silicon elements and the deterioration of microstructure, leading to surface peeling, crack propagation, and increased porosity of the sample. The compressive strength decreases linearly with the soaking time. Acoustic emission (AE) monitoring showed that after 24 h of soaking, the maximum ringing count rate and cumulative count decreased by 81.7% and 80.4%, respectively, compared to the dry state. As the liquid saturation increases, the failure mode transitions from tension dominated to shear failure. The synergistic effect of initial damage and oil–water erosion weakens the rock’s energy storage capacity, with the energy storage limit decreasing by 45.6%, leading to reduced resistance to external forces. Full article

Background/Objectives: Chronic obstructive pulmonary disease (COPD) remains a condition with high morbidity, mortality, and misdiagnosis. The gold standard pulmonary function testing with spirometry has limited availability. This study seeks to test a novel diagnostic test based on auscultatory mapping of pulmonary dynamics. This NIH-funded study aimed to develop a COPD detection technology, using mobile phone auscultation, for situations in which spirometry is not available. Methods: This prospective study collected mobile phone auscultation data on patients presenting for spirometry and evaluation by a pulmonologist. All subjects had same-day or recent (less than 6 months) spirometry in one PFT laboratory. After informed consent, the subjects underwent respiratory auscultation using a selection of mobile phone brands. The auscultation methods included normal breathing observed at the left axillary site and egophony observed at the right supra clavicular fossa. The team created models from the recordings using Time Series Dynamics (TSD), proprietary software that uses computational nonlinear dynamics to characterize the respiratory biofluid dynamics implied by the acoustic data. Results: We enrolled a total of 108 patients (34.3% male), from 19 to 85 years of age (median 61 years). Among the patients, 64 (59.3%) subjects identified as White, 43 (39.8%) as Black, and 1 as Asian. Among the two cohorts with diverse comorbidities, 52 subjects had confirmed COPD and 56 did not. The cohorts differed significantly in age and body mass index, but not in race, number of comorbidities, or COPD assessment test scores. They had significant differences in forced expiratory volume in 1 s (FEV1), the FEV1/FVC (forced vital capacity) ratio, but not FVC. The recordings from the egophonic and axillary sites were initially modeled separately and then combined in a single composite model. The modeling produced excellent results with 90%+ AUC and sensitivity in both the test and train sets relative to the gold standard. Conclusions: Evidence suggests that a mobile phone auscultation device can accurately determine COPD diagnosis. In frontline applications where the availability of gold standard pulmonary function testing is limited, the device could improve the detection of COPD, a condition with significant over- and under-diagnosis. Future trials will investigate the ability of patients to self-record. Success would support remote COPD testing using transmitted telehealth recording data, bringing diagnosis to patients in underserved populations. Full article

Ultrasound technology has emerged as a transformative tool in modern food science, offering non-destructive, real-time assessment and enhancement of food quality attributes. This review systematically explores the fundamental mechanisms by which ultrasound interacts with food matrices, including mechanical effects such as acoustic cavitation, localized shear forces, and microstreaming, as well as thermal and acoustic attenuation phenomena. Applications of ultrasound in food texture evaluation are discussed across multiple sectors, with particular emphasis on its role in assessing moisture distribution, fat content, structural integrity, and microstructural alterations in meat, dairy, fruits, and vegetables. The versatility of ultrasound—spanning low-intensity quality assessments to high-intensity processing interventions—makes it an invaluable technology for both quality control and product innovation. Moreover, emerging innovations such as ultrasound-assisted extraction, non-thermal pasteurization, and real-time quality monitoring are highlighted, demonstrating the synergy between ultrasound and advanced technologies like AI-driven data interpretation and portable, handheld sensing devices. Despite these advances, challenges related to technical limitations in heterogeneous food systems, high initial investment costs, scalability, and the absence of standardized protocols remain critical barriers to widespread adoption. The future directions emphasize the integration of ultrasound with multi-modal approaches, the development of miniaturized and cost-effective equipment, and the establishment of global regulatory standards to facilitate its broader application. Overall, ultrasound is positioned as a key enabler for sustainable, efficient, and non-invasive quality assurance across the global food industry. Full article

Background: Chronic obstructive pulmonary disease (COPD) is projected to be the third-leading cause of death by 2030. Traditional spirometry for the monitoring of the forced expiratory volume in one second (FEV1) can provoke discomfort and anxiety. This study aimed to validate AI models using daily audio recordings as an alternative for FEV1 estimation in home settings. Methods: Twenty-three participants with moderate to severe COPD recorded daily audio readings of standardized texts and measured their FEV1 using spirometry over nine months. Participants also recorded biomarkers (heart rate, temperature, oxygen saturation) via tablet application. Various machine learning models were trained using acoustic features extracted from 2053 recordings, with K-nearest neighbor, random forest, XGBoost, and linear models evaluated using 10-fold cross-validation. Results: The K-nearest neighbors model achieved a root mean square error of 174 mL/s on the validation data. The limit of agreement (LoA) ranged from −333.21 to 347.26 mL/s. Despite an error range of −1252 to 1435 mL/s, most predictions fell within the LoA, indicating good performance in estimating the FEV1. Conclusions: The predictive model showed promising results, with a narrower LoA compared to traditional unsupervised spirometry methods. The AI models effectively used audio to predict the FEV1, suggesting a viable non-invasive approach for COPD monitoring that could enhance patient comfort and accessibility in home settings. Full article