Search Results (1,087)

Esophageal stent insertion is a key palliative therapy for malignant esophageal strictures, but the postoperative migration rate remains as high as 40%, significantly compromising clinical outcomes. Stent migration behavior is closely related to its structure and mechanical properties; however, the underlying mechanisms remain unclear, and there is a lack of effective in vitro evaluation methods to predict migration risk. Herein, we first developed a novel biomimetic swallowing peristalsis simulation device that highly replicates human physiological environments and swallowing waveforms—addressing the limitations of existing in vitro testing methods. Using this device, we demonstrated for the first time that stent migration is co-regulated by radial force and axial bending stiffness: higher radial force enhances anchoring via increased friction, while lower bending stiffness (superior flexibility) reduces migration risk by maintaining a larger stent–esophagus contact area and improving energy dissipation during swallowing. These conclusions are supported by our theoretical derivations and test results of stents with different densities. In addition, it was found that food viscosity and tumor block also influence stent migration risk. This study elucidates the synergistic mechanism of esophageal stent migration and provides a theoretical foundation and an in vitro validation platform for the design of a new generation of anti-migration esophageal stents. Full article

This paper presents a unified perspective on Orthogonal Frequency-Division Multiplexing (OFDM)-based joint radar–communication (JRC) sensing, focusing on the efficient reuse of time and frequency resources in range–Doppler estimation and imaging scenarios. By leveraging OFDM’s inherent subcarrier orthogonality, noise-like temporal properties, and minor carrier frequency offsets, these systems can support concurrent transmissions over the same spectral and temporal resources while maintaining interference resilience. Experimental and simulation-based insights demonstrate the feasibility of simultaneous sensing across users and antennas, even in dense Radio Frequency (RF) environments. We analyze trade-offs, implementation considerations, and system-level implications to provide a consolidated foundation for designing future OFDM-based JRC systems. The feasibility of an Orthogonal Time Frequency Space (OTFS) waveform for the proposed method is also investigated. The review highlights the potential of such architectures in spectrum and time-congested applications such as Vehicle-to-Everything (V2X), indoor localization, Internet of Things (IoT), and beyond fifth-generation (5G) networks. Full article

Component tolerances in Ultra-Wideband (UWB) fuze transmitters inevitably induce waveform distortions, which propagate through the signal chain to degrade system-level tactical performance, specifically detection range and ranging resolution. Addressing the lack of quantitative mechanisms linking component variations to operational effectiveness, this study proposes an information-theoretic sensitivity analysis framework. First, we establish a physics-based mathematical model of the transmitter and rigorously validate it against circuit-level simulations to characterize the step recovery diode’s transient response under tolerance disturbances. Second, we employ the Latin Hypercube Sampling-Information Entropy (LHS-IE) method to quantify the uncertainty propagation from parameters to pulse features. Crucially, we introduce Feature Interaction Information (FII) to decode the nonlinear coupling between components. Our results reveal a strong Amplifying effect driven by inductance tolerances, where the interaction between parameters amplifies the joint uncertainty of amplitude and width beyond their individual impacts. Conversely, load resistance primarily dictates amplitude uncertainty as an independent linear factor. The proposed framework provides a theoretical basis for converting traditional tolerance design into an entropy-driven precision allocation strategy, ensuring system robustness under manufacturing constraints. Full article

This study seeks to resolve the critical yet often conflicting demands for electrical stability and mechanical tunability in flexible materials for wearable electronics. A composite conductive material was prepared based on the combination of electrospun fiber networks with tunable orientation and ion-gel phase. Through structural regulation, we achieved the designed adjustment of mechanical properties from isotropic to anisotropic while maintaining stable electrical conductivity. By adjusting the fiber orientation, Young’s modulus can be tailored to span a broad range. The fabricated composite membrane was processed into a flexible dry electrode and used for electrocardiogram (ECG) signal acquisition, achieving a high signal-to-noise ratio and stable waveform characteristics. Additionally, it can reliably monitor electromyographic signals from various static and dynamic hand gestures, including clenching, unclenching, and thumbs-up motions. This work provides a viable way to design materials and construct structures for multifunctional wearable electronic devices. Full article

To enable mains-free wireless access in confined environments such as tunnels and mines, this paper proposes and experimentally demonstrates a converged power-over-fiber (PoF) and analog radio-over-fiber (A-RoF) system over a single standard single-mode fiber (SMF). Using wavelength-division multiplexing (WDM), the system employs 1310 nm/1330 nm channels for bidirectional RF transmission and a 1550 nm channel for optical power delivery, respectively, while an ultra-simplified remote unit (RU) with a steady-state power consumption of 0.37 W is designed to match the PoF power-delivery capability. Experimental results show that for back-to-back, 1 km and 2 km links, the A-RoF performance remains essentially unaffected, with error vector magnitude (EVM) remaining stable, as the delivered PoF optical power varies from 0 to 3 W. For the 2 km transmission case, an incident PoF optical power of 2 W at the photovoltaic power converter (PPC) is sufficient to sustain stable system operation for over 10 hours. Under these conditions, using an IEEE 802.11ax MCS-7 (64QAM ) waveform, the optimum operating point yields an EVM of approximately 0.7%, satisfying the MCS-7 modulation-quality requirement. Full article

This study systematically investigates the structural optimization and control strategies of a plasma power supply-based rotating electrical machine. Firstly, stress simulation analysis was conducted on both conventional and optimized motor structures using ANSYS 2025 R1 software. The results demonstrate the maximum stress at the motor bearings decreased from 1.295 MPa to 0.865 MPa after optimization, representing a 33.2% reduction. Secondly, dynamic balance simulation performed with Adams 2024 software revealed that the centroid offset range of the optimized motor was reduced from ±0.05 mm to ±0.0175 mm, achieving a 65% improvement. Furthermore, a motor driver board supporting SVPWM and FOC algorithm was designed and implemented, featuring wide voltage input, multiple output channels, and comprehensive protection functions. Experimental verification confirmed that the developed control system could generate ideal three-phase saddle wave and sinusoidal current waveforms, ensuring smooth motor operation. The system demonstrated excellent dyne pen test results on plasma-sprayed acrylic plates, effectively validating the feasibility of both structural optimization and control strategies. The research outcomes provide theoretical foundations and technical support for high-performance motor design in demanding applications such as plasma spraying. Full article

Quasi-resonant (QR) DC–DC converters with PWM control achieve soft switching by shaping the commutation transient through a local resonant process. This paper proposes a symmetry-based unified perspective on classical QR converters by interpreting zero-voltage switching (ZVS) and zero-current switching (ZCS) as dual commutation symmetries: ZVS restores voltage symmetry at turn-on, whereas ZCS restores current symmetry at turn-off. Building on this viewpoint, we organize QR Buck, Boost, and Buck–Boost converters through two complementary forms of symmetry: (i) commutation symmetry (ZVS vs. ZCS) and (ii) topological duality (Buck ↔ Boost and the self-dual nature of Buck–Boost). The framework is anchored in normalized parameter spaces commonly used in QR analyses and is illustrated using representative ZVS and ZCS Buck cases, including waveform-stage symmetry and loss/stress implications. Furthermore, we discuss the “cost of symmetry” via stress and conduction-loss metrics, highlighting how soft-switching conditions trade voltage and current stresses in dual fashions. The proposed organization offers a compact conceptual map that links operating regimes, design degrees of freedom, and expected stress/loss trends across the main classical QR-PWM converter families. Full article

Background: Full field electroretinography (ERG) is an essential tool for assessing retinal function and diagnosing retinal diseases. In recent years, mydriasis-free handheld ERG devices have emerged as portable, non-invasive alternatives to traditional ERG systems. Their main application has been in the screening and monitoring of diabetic retinopathy (DR), particularly in settings with limited access to standard ERG equipment and in pediatric populations where conventional testing may be difficult to perform. This review aims to evaluate the current evidence on handheld ERG devices in ocular diseases, with a focus on their reliability, diagnostic accuracy, and inherent limitations. Methods: A review was conducted to identify studies evaluating handheld ERG devices in diverse clinical settings, including retinal diseases, DR, pediatric populations, and conditions such as glaucoma. A comprehensive search of the Pubmed and Embase databases was performed for studies published up to December 2024. Search terms included “mydriasis free ERG”, “handheld ERG”, “portable ERG”, “RETeval”, “healthy subjects”, “retinal diseases”, “diabetic retinopathy”, “glaucoma”, and “pediatric diseases”, as well as relevant MeSH terms and synonyms. Case reports, conference abstracts, non-human studies, and letters were excluded. After screening titles and abstracts, additional studies not meeting the inclusion criteria were excluded. Of 279 records that were initially identified, 55 met the eligibility criteria and were included in the final review. Results were synthesized narratively due to heterogeneity in the study design, populations, and outcomes. Findings were organized thematically according to clinical context. Results: A total of 57 studies were included in the review: 19 conducted in healthy subjects, 13 in diabetic retinopathy, eight in selected retinopathies, eight in glaucoma, and 14 in pediatric cohorts. Five studies overlapped between groups due to shared populations or study designs. No meta-analysis was performed due to heterogeneity in study design and outcome measures; therefore, findings were summarized narratively across disease categories. Handheld ERG devices have been evaluated in healthy subjects, patients with DR, other retinal pathologies, glaucoma and pediatric cohorts. Evidence indicates that these devices provide a rapid, non-invasive assessment of retinal function and are particularly valuable where conventional ERG is difficult to implement and potentially well-suited for screening purposes. They show good sensitivity and reasonable specificity for detecting functional changes, making them suitable for screening purposes. However, limitations exist: reduced performance in detecting early-stage disease and cone dysfunction, risk of false positives, and variability in waveform morphology and amplitude compared with traditional ERG systems. Reproducibility challenges are noted among pediatric patients and individuals with poor fixation or unstable eye movements. These discrepancies highlight the need for establishing robust normative datasets for both healthy subjects and specific disease states. Conclusions: Handheld ERG devices provide a rapid, accessible and user-friendly option for retinal assessment. While not a replacement for conventional ERG, they serve as complementary tools, particularly in early disease and in contexts where standard testing is less feasible. Further research is required to refine testing protocols, improve diagnostic accuracy, and validate their application across a broader spectrum of ocular diseases. Full article

This study investigates the selection and scaling of recorded strong ground motions in the time-domain spectral matching framework to realistically represent the seismic demands on the superstructure and secondary systems in the seismic design of complex facilities such as marine ports. The time-domain spectral matching method iteratively adjusts the original record in the time domain by adding wavelets with limited durations and specific period ranges to achieve compatibility with the specified target acceleration response spectrum. A site-specific probabilistic seismic hazard analysis (PSHA) was performed for a port facility in İskenderun Bay, an area affected by the 6 February 2023 earthquakes. Horizontal Ground-Motion Response Spectra (GMRS) were derived for different return periods. Based on the hazard deaggregation, recorded ground motions compatible with the seismotectonic context of the region and the site conditions were selected. These records were then processed using time-domain spectral matching (TDSM) to match their elastic response spectra with the target GMRS over specific period ranges. The method utilizes spectral matching in the time domain to improve the match with the target spectrum while preserving the phase information and non-stationary nature of the records. The results show that the mean spectral acceleration curves of the scaled records are highly consistent with the target GMRS over a wide range of periods and that near-fault pulse-like characteristics, when present, are reasonably preserved. These results confirm that time-domain spectral matching provides a reliable framework for the performance-based assessments of complex port infrastructures by achieving high compatibility with the target spectra while preserving the physical characteristics of the waveforms Full article

Finite element analysis (FEA) remains the gold standard for simulating piezoelectric microactuators because it resolves coupled electromechanical fields with high fidelity. However, transient FEA becomes prohibitively expensive when thousands of actuators must be simulated. This work presents a data-driven surrogate modeling framework for tileable, PZT-5H microactuators enabling fast, dynamic, and parallel predictions of actuator displacement over multi-step horizons from short displacement history windows, augmented with the corresponding prescribed voltage and traction samples over that same history window. High-fidelity COMSOL simulations are used to generate a dataset aiming to encompass the full operational envelope of our actuator under stochastically sampled and procedurally generated input waveform families. From these families, we construct a supervised learning dataset of time histories, displacement, and applied loads. From this, we train a recurrent sequence-to-sequence neural network that predicts a multi-step open-loop displacement rollout conditioned on the most recent electromechanical history. The resulting model can be leveraged to perform batched inference for millions of actuators on GPU hardware, opening up a wide range of new applications such as reinforcement learning via digital twins, scalable design and simulation for piezoelectric artificial-muscle systems, and accelerated optimization. Full article

In February 2024, the European Union published its Industrial Carbon Management Strategy, setting ambitious goals for carbon capture and storage (CCS), carbon capture and utilisation (CCU), and related technologies. Industrial decarbonisation will require a mix of solutions, CCUS, electrification, hydrogen and hydrogen-derived fuels, and energy efficiency, which are all dependent on affordable clean energy. Although carbon management technologies could contribute substantially to climate targets, their deployment has been slowed by technical barriers and public concerns. Sotacarbo has created a research centre dedicated to developing and testing carbon capture, utilisation, and storage technologies. Within this framework, the new Sotacarbo Fault Laboratory (SFL) was designed to investigate gas migration in faults and to test monitoring systems capable of detecting potential short- and long-term CO₂ leakages. This paper presents a preliminary study, including seismic full-waveform simulations for time-lapse surveys before and after CO₂ injection, and a suite of geophysical methods used to characterise the Matzaccara Fault within the Eocene Sulcis Basin. The results of the application of integrated geophysical methods support the selection of a safe and suitable injection-well location and demonstrate the value of these methods for detailed fault characterisation in CCUS applications. Full article

Fiber-reinforced laminates composed of a thermoset matrix have seen widespread use in industries such as the aerospace, wind power, and automotive industries, due to their strength-to-weight ratios and ease of formability. For optimal performance, the instantaneous cure state must be sufficient such that the component will not deform during or after molding, a state that can vary based on many manufacturing-related factors. Thus, monitoring the cure process non-destructively in situ is key to manufacturing composite laminates to achieve the as-designed properties while balancing the cycle time reduction. The current work presents a pulse-echo ultrasound method to correlate the acoustic waveform to the thermoset resin cure state and the instantaneous structural properties, specifically the resin storage and loss moduli. This latter information provides a fabricator knowledge of when a part can be successfully demolded, allowing for optimizing part cycle times. The present paper provides the results for the neat resin specimen and fiberglass specimen impregnated with the same resin system. The results provide a direct correlation between the acoustic and the viscoelastic properties. Interestingly, it is noted that there is a direct correlation between the peak signal attenuation and the peak gelation of the material, thus providing a means to predictively schedule the demolding time while maintaining proper curing cycles. Full article

Accurate core loss evaluation is essential in the design of magnetic components. Core loss is critically influenced by excitation waveform, temperature, and magnetic material; therefore, we develop a waveform equivalence coefficient, a temperature polynomial, and an electrical conductivity term to revise the Steinmetz Equation and propose a physics–data dual-driven core loss model across materials and operating conditions. The waveform equivalence coefficient achieved 100% waveform classification, and temperature polynomial modification reduced the mean square error by an order of magnitude. Using three-way analysis of variance (ANOVA), we measured the individual and synergistic impacts of the three key factors on core loss. The waveform exerts the greatest individual influence while waveform and material, as a combination, exerts the greatest synergistic influence. Given the discovery that Material 1 demonstrates a property transition point under triangular waveform, the dual-objective optimization result indicates that using Material 1 under operating conditions of 90 °C, 501,180 Hz frequency, 0.0047 T peak flux density, and a triangular excitation waveform enables the magnetic component to achieve minimum core loss with maximum transmitted magnetic energy. Full article

Artificial intelligence (AI) is rapidly reshaping adult cardiac surgery, enabling more accurate diagnostics, personalized risk assessment, advanced surgical planning, and proactive postoperative care. Preoperatively, deep-learning interpretation of ECGs, automated CT/MRI segmentation, and video-based echocardiography improve early disease detection and refine risk stratification beyond conventional tools such as EuroSCORE II and the STS calculator. AI-driven 3D reconstruction, virtual simulation, and augmented-reality platforms enhance planning for structural heart and aortic procedures by optimizing device selection and anticipating complications. Intraoperatively, AI augments robotic precision, stabilizes instrument motion, identifies anatomy through computer vision, and predicts hemodynamic instability via real-time waveform analytics. Integration of the Hypotension Prediction Index into perioperative pathways has already demonstrated reductions in ventilation duration and improved hemodynamic control. Postoperatively, machine-learning early-warning systems and physiologic waveform models predict acute kidney injury, low-cardiac-output syndrome, respiratory failure, and sepsis hours before clinical deterioration, while emerging closed-loop control and remote monitoring tools extend individualized management into the recovery phase. Despite these advances, current evidence is limited by retrospective study designs, heterogeneous datasets, variable transparency, and regulatory and workflow barriers. Nonetheless, rapid progress in multimodal foundation models, digital twins, hybrid OR ecosystems, and semi-autonomous robotics signals a transition toward increasingly precise, predictive, and personalized cardiac surgical care. With rigorous validation and thoughtful implementation, AI has the potential to substantially improve safety, decision-making, and outcomes across the entire cardiac surgical continuum. Full article

Accurate analysis of commutation phenomena in permanent magnet DC (PMDC) motors requires simultaneous consideration of electromagnetic field distribution and armature circuit dynamics. Classical circuit-based models are unable to properly capture transient effects occurring in short-circuited coils during commutation, while purely field-based models neglect the influence of the supply circuit. In this paper, a coupled field–circuit model of a PMDC motor with an innovative magnetic circuit based on rectangular NdFeB permanent magnets is presented. The model combines a two-dimensional finite element electromagnetic analysis with a segmented armature circuit and dynamic commutator switching, allowing the electromotive force to be computed individually for each coil based on the actual magnetic field distribution. The novelty of the proposed approach lies in the integration of a non-standard rectangular permanent magnet topology with a coil-resolved field–circuit commutation model, validated on a physical motor prototype. Simulation results are compared with experimental measurements obtained from a laboratory prototype at rotational speeds of 850 and 1000 r/min. The predicted electromagnetic torque shows good agreement with measurements, with deviations below 5%, while the armature current is estimated with an error of up to approximately 20%, primarily due to model simplifications. The developed model provides direct access to transient commutation waveforms and constitutes a practical tool for the analysis and design optimization of PMDC motors operating under dynamic conditions, particularly in cost-sensitive and reliability-oriented applications. Full article