Search Results (3,838)

Ultrasonic wind speed measurements performed in complex flow fields face challenges related to low signal-to-noise ratio (SNR) and non-stationary waveform distortion. In this study, we aim to address this issue by proposing a measurement system that employs a polyvinylidene fluoride (PVDF) piezoelectric film ultrasonic transducer integrated with a microphone (MIC). In addition, a signal processing framework is proposed based on the joint optimization of variational mode decomposition (VMD) and an extended Kalman filter (EKF) and integrating cross-correlation interpolation. By leveraging the low Q-factor and wide bandwidth characteristics of the PVDF, the system achieved omnidirectional transmission and high-fidelity reception within a compact structural design. The experimental results demonstrated that the proposed VMD-reference signal-assisted EKF method enhanced the SNR by approximately 26% and reduced the wind speed measurement error by approximately 35% compared with the conventional EKF. The proposed system exhibited superior robustness and measurement linearity across a wide wind speed range of 0–60 m/s. The proposed scheme significantly enhances the accuracy and environmental adaptability of ultrasonic wind speed measurements and provides an essential theoretical basis and engineering reference for the development of precision instruments in fields such as meteorological monitoring and wind energy assessment. Full article

Background/Objectives: The aberrant epigenetic landscape of cancer cells has attracted wide attention, motivating the search for new epigenetically active drugs both for anticancer therapy and for overcoming the drug resistance promoted by epigenetic changes. The use of epi-drugs in cancer therapy requires consideration of the influence of applied treatment on epigenetic regulation of gene expression. Therefore, it is reasonable to screen epigenetically active compounds among the drugs widely used in clinical oncology. Methods: We applied the HeLa TI cell-based assay to analyze the epigenetic activity of 40 drugs including 22 chemotherapeutic, 2 immunotherapeutic, 13 targeted, and 3 palliative agents. Reactivation of the epigenetically silenced GFP reporter gene integrated into the genome of HeLa TI cells was assessed using flow cytometry. Results: Statistically significant increases in the proportions of GFP-positive cells were demonstrated for the alkylating agent chlorambucil; the antimetabolites cytarabine, fluorouracil, gemcitabine, and pemetrexed; the platinum-based compounds cisplatin, and oxaliplatin; the topoisomerase inhibitor topotecan; and the antimicrotubule agents docetaxel, vincristine, and eribulin. Epigenetic activity was also detected for the targeted-therapy agents AZD8055, wortmannin, and cetuximab, as well as for the corticosteroid dexamethasone. Thus, epigenetic activity was revealed for 15 drugs widely used in cancer therapy, which possess different modes of action. Conclusions: Our findings show that many anticancer therapy agents modulate the epigenetic landscape of cancer cells, providing a rationale for expanding their therapeutic applications and enhancing the efficacy of combination strategies by overcoming epigenetically driven chemoresistance. Full article

Optic-fiber-based thermal flowmeters have the merits of compact size and high sensitivity, which typically require two light beams separately acting as a pump for heating the sensing unit and a probe for sensing temperature with the variation of external flow. Here, we propose a metallic nanostructure with multiple plasmonic resonance modes for the application of an optic-fiber-based thermal flowmeter. The optical properties of a nanostructure comprised of a double-width gold grating, a poly (methylmethacrylate) (PMMA) layer, and a gold film are numerically simulated in the spectral range of 600–1800 nm. The optical resonances of different modes are systematically investigated with the variation of the structural parameters. Interestingly, two optical resonance modes with distinct spectral shift under the same temperature variation, i.e., 21.34 pm/°C vs. 269.2 pm/°C, are obtained after the strategic optimization of the nanostructure. Finally, the sensitivity of the flowmeter with the proposed nanostructure is investigated by adopting the low-temperature sensitivity mode for optical pumping and the high-temperature sensitivity mode for temperature sensing, proving its significant potential as an optic-fiber-based thermal flowmeter. Full article

Accurate multi-modal traffic demand forecasting is key to optimizing intelligent transportation systems (ITSs). To overcome the shortcomings of existing methods in capturing dynamic high-order correlations between heterogeneous spatial units and decoupling intra- and inter-mode dependencies at multiple time scales, this paper proposes a Dynamic Multi-Relation Learning with Multi-Scale Hypergraph Transformer method (MST-Hype Trans). The model integrates three novel modules. Firstly, the Multi-Scale Temporal Hypergraph Convolutional Network (MSTHCN) achieves collaborative decoupling and captures periodic and cross-modal temporal interactions of transportation demand at multiple granularities, such as time, day, and week, by constructing a multi-scale temporal hypergraph. Secondly, the Dynamic Multi-Relationship Spatial Hypergraph Network (DMRSHN) innovatively integrates geographic proximity, passenger flow similarity, and transportation connectivity to construct structural hyperedges and combines KNN and K-means algorithms to generate dynamic hyperedges, thereby accurately modeling the high-order spatial correlations of dynamic evolution between heterogeneous nodes. Finally, the Conditional Meta Attention Gated Fusion Network (CMAGFN), as a lightweight meta network, introduces a gate control mechanism based on multi-head cross-attention. It can dynamically generate node features based on real-time traffic context and adaptively calibrate the fusion weights of multi-source information, achieving optimal prediction decisions for scene perception. Experiments on three real-world datasets (NYC-Taxi, -Bike, and -Subway) demonstrate that MST-Hyper Trans achieves an average reduction of 7.6% in RMSE and 9.2% in MAE across all modes compared to the strongest baseline, while maintaining interpretability of spatiotemporal interactions. This study not only provides good model interpretability but also offers a reliable solution for multi-modal traffic collaborative management. Full article

Early detection of cancer biomarkers in blood is critical for improving patient outcomes; however, conventional immunoassays often rely on complex instrumentation and are not well suited for point-of-care testing or multiplexed analysis. Herein, we present a dual-mode colorimetric–surface-enhanced Raman scattering (SERS) lateral flow immunoassay (LFIA) platform for multiplexed detection of cancer biomarkers, employing elongated rod-shaped silver nanoshells (ERNSs) as SERS nanotags. The ERNS features a rough Ag shell with internally incorporated Raman labeling compounds (RLCs), enabling plasmonic extinction for visual readout and strong SERS signals for quantitative analysis while preserving the external metal surfaces for efficient antibody conjugation. Leveraging these advantages, a multiplex LFIA capable of simultaneously detecting prostate-specific antigen (PSA) and carbohydrate antigen 19-9 (CA19-9) on a single strip was successfully demonstrated. Visual inspection enabled rapid discrimination of samples at or near clinically relevant cut-off levels, while Raman analysis achieved limits of detection of 8.0 × 10⁻³ ng/mL for PSA and 5.4 × 10⁻² U/mL for CA19-9, corresponding to approximately 500-fold and 685-fold lower concentrations than their respective clinical thresholds. This ERNS-based colorimetric–SERS LFIA integrates rapid screening and highly sensitive quantification within a single platform and offers a versatile nanoprobe design strategy for multiplex biomarker detection and liquid biopsy-based diagnostic applications, with potential relevance to point-of-care settings. Full article

Impeller blades are one of the main parts of a centrifugal pump that affect the performance of the pump. The presence of solid particles in seawater, transported through a centrifugal pump, causes wear in the blade surface that reduces blade lifetime. In the orthogonal direction, this wear is an erosion thickness of the blade. Assuming that these particles have a spherical shape, the erosion rate depends on their velocity, size, impingement angle, and material hardness index. In this work, we investigate the erosion thickness of a low-head centrifugal pump operating in pump and turbine modes, with a particle radius ranging from 4 μm to 50 μm. The numerical simulation used an RNG k–ε turbulence model, assuming a perfect bounce collision between the particle and the rotating solid wall. The study shows that the blade pressure side is impacted by a solid particle concentration higher than the suction side. In pump mode, the erosion thickness on the blade sides increases if the particle radius is above 4 μm and reaches a maximum at 40 μm. In turbine mode, the erosion thickness decreases when the particle radius is greater than 5 μm. The thickness loss is greater in turbine mode than in pump mode. The influence of particle flow rate was investigated. Below a particle radius of 10 μm, particles follow the flow directions and reside for a longer time in the blade channel. Passing from a particle radius of 50 μm to 100 μm, the blade lifetime was decreased by a factor of 11. Full article

Sweeping jet actuators (SJAs) are promising for active flow control in aerospace systems, but integrating actuator-resolved unsteady CFD into full-configuration simulations is often impractical due to small geometric scales and $\mathcal{O}({10}^2)$ Hz oscillations that demand fine grids and small time steps. This work develops a reduced-order modeling (ROM) framework to generate time-resolved boundary conditions at the actuator exit from SJA flow data. Dynamic mode decomposition (DMD) is particularly attractive for this purpose because it provides a linear, data-driven input–output representation of the actuator effect, even though it does not explicitly model the underlying nonlinear switching mechanism. We introduce an eigenvalue-sorted dynamic mode decomposition (ES-DMD) method that performs stability-aware mode ranking based on the discrete-time DMD eigenvalues, prioritizing modes with $\Re (\lambda )$ closest to unity to retain near-neutrally stable oscillatory dynamics, improving robustness relative to conventional amplitude-based selections for high-frequency oscillatory flows. The method is evaluated across multiple operating conditions, with detailed analysis performed for the highest mass-flow case ($\dot{m}=0.01$ lb/s), representing the most dynamically demanding condition considered. Across multiple operating conditions, ES-DMD yields consistent reconstructions of the dominant switching dynamics. For one-dimensional exit-plane profiles, combining ES-DMD with time-delay embedding enables accurate reconstruction and multi-period prediction using only 20 modes (7.6% of the full system rank). The proposed approach provides a practical pathway to incorporate unsteady SJA effects into large-scale aerospace CFD through compact, predictive boundary-condition models. Full article

The swimming tilt angle of fish is one of the key factors influencing the estimation of target strength (TS). Therefore, understanding how TS varies with changes in swimming tilt angle is essential. This study employed the Kirchhoff-ray-mode (KRM) model to estimate TS and examine variations in the swimming tilt angle of sardines under flowing water conditions. Swimming tilt angles were measured at flow velocities of 30 and 50 cm/s. The KRM model was utilized to estimate TS for 17 sardine samples (total length: 13.0–24.6 cm) across four frequency bands (38, 70, 120, and 200 kHz). At a flow velocity of 30 cm/s, sardines swimming against the flow exhibited a mean swimming tilt angle of 4.0° ± 14.0°, with normalized mean TS_cm values of −64.7 dB at 38 kHz, −65.7 dB at 70 kHz, −66.4 dB at 120 kHz, and −66.9 dB at 200 kHz. At a flow velocity of 50 cm/s, sardines swimming against the flow showed a mean swimming tilt angle of −2.2° ± 10.1°, with normalized mean TS_cm values of −62.9 dB at 38 kHz, −63.7 dB at 70 kHz, −64.3 dB at 120 kHz, and −64.8 dB at 200 kHz. Considering the results of this study and the swimming behavior of sardines against the flow, the target strength of sardines swimming with the flow may be of less concern. Therefore, when conducting acoustic surveys, it is more efficient to account for flow velocity conditions rather than swimming direction. Full article

The downscaling of VLSI technologies has exacerbated the susceptibility of integrated circuits (ICs) to radiation-induced Single-Event Transients (SETs). This work presents UPSET, a comprehensive and technology-independent EDA framework for probabilistic SET analysis using Static Timing Analysis (STA). Unlike traditional simulation-based methods that suffer from prohibitive runtimes, UPSET leverages graph-based propagation with advanced logical, electrical, and timing-window masking models to evaluate circuit sensitivity efficiently. Key contributions include a novel “Electrical Masking Window” (EMW) criterion that effectively filters non-full-rail pulses early in reconvergent logic and a TimeStamp-based propagation mode that accurately handles complex signal reconvergence with Boolean evaluation. The experimental results over some featured benchmarks demonstrate a speedup of more than 25,000× compared with SPICE while maintaining a tight 4.56% error bound in pulse width estimation. Moreover, experimental validation on 50 benchmarks across varying complexities showcases that EMW enhancement reduces the pessimism to circuit sensitivity by up to 25% on average, providing tighter upper bounds while maintaining scalability to million-gate designs. By integrating seamlessly with standard industrial formats (LEF, DEF, LIB, or SPEF), UPSET enables scalable, accurate soft SET sensitivity assessment for modern digital designs, establishing a robust foundation for automated radiation hardening flows. Full article

This paper presents a comprehensive study on the control law design for the turbine-to-ramjet mode transition in an adaptive-cycle turbine-based combined cycle (TBCC) engine, aiming to mitigate the persistent “thrust gap” challenge. An integrated conceptual configuration of a hypersonic vehicle with a parallel-duct TBCC system, which replaces the conventional turbofan with a three-bypass adaptive cycle engine (ACE), is proposed. High-fidelity performance models for both the ACE and the scramjet are developed, with a Kriging surrogate model employed to accelerate the computationally intensive ACE simulations during the transition. A co-optimization framework is established, defining a comprehensive performance index that balances thrust tracking accuracy and control smoothness under rigorous intake-engine flow matching constraints. Using sequential quadratic programming (SQP), the control schedules for the ACE’s variable geometries are optimized. Comparative analyses reveal that the ACE, with its flexible bypass management and multiple adjustable mechanisms, can actively adapt its airflow demand to match the restricted intake supply. Consequently, the optimized ACE-based TBCC reduces total airflow fluctuation during the Mach 3–3.5 transition from 106% (conventional turbofan baseline) to 42.5%, while maintaining required thrust. This work quantitatively demonstrates the superior flow-handling capability of adaptive cycle technology, providing a viable and effective solution for ensuring stable and efficient mode transition in future hypersonic TBCC propulsion systems. Full article

Hydrogen-fueled gas turbines face challenges related to flashback risk, nitrogen oxide (NO_x) emissions, and operational flexibility. In this study, a Center-Graded Spiral Micromixing (CGSM) combustor was designed and experimentally investigated to enhance the robustness of fuel–air mixing under hydrogen-rich conditions. The proposed CGSM concept employs spiral microtubes to induce curvature-driven secondary flows, promoting mixing through airflow-controlled mechanisms rather than relying solely on fuel jet momentum. Numerical simulations were conducted to qualitatively analyze the internal flow and mixing characteristics of the spiral microtubes, followed by pressurized combustor experiments at an inlet pressure of 0.3 MPa and elevated air temperatures. The experimental results demonstrate stable combustion of pure hydrogen under lean conditions, with NO_x emissions being maintained below 25 ppm, corrected to 15% O₂, without observable flashback or combustion oscillations within the designated operating range (from ignition to full load). The combustor further exhibits stable operation with blended hydrogen–methane and hydrogen–ammonia fuels, enabling online fuel switching without hardware modification. Application tests on an 80 kW micro-gas turbine indicate that the CGSM combustor can support stable operation across the full range of load conditions, from ignition to full-load operation, under both simple- and reheat-cycle modes, with performance characteristics that are consistent with established operational standards for micro-gas turbines. These results suggest that the CGSM concept provides a feasible micromixing strategy for hydrogen and hydrogen-rich fuels at a moderate pressure and micro-gas turbine scale. Full article

The most important segment of the electric arc furnace (EAF) steelmaking process is the stirring and decarburization of the molten bath during the oxidation stage, with the bath temperature typically ranging from 1550 to 1600 °C. The coherent jet is a key factor influencing the stirring and decarburization of the molten bath. The factors affecting the impact capability of coherent jets have been widely studied, including the nozzle flow parameters and arrangement methods. However, there are few studies on the combustion chamber structure of the coherent jet oxygen lance. In order to study the effect of the combustion chamber structure on the characteristics of the coherent jet, a method combining numerical simulation and combustion experiments is used to study the flow fields of the coherent jet for a combustion chamber under different length and inclination angle conditions. The results show that the flow field characteristics of the coherent jet are influenced by the length and inclination angle of the combustion chamber. Compared with the coherent jet oxygen lance without a combustion chamber, the potential core length of the main oxygen jet under the short-distance horizontal combustion chamber condition is longer, but the potential core length of the main oxygen jet with the excessively long horizontal combustion chamber is shorter. The influence of the inclination angle on the potential core length of the main oxygen jet is complex. The influence mode is different depending on the length of the combustion chamber. Finally, it is found that the combined horizontal and inclined combustion chamber can achieve the best effect on prolonging the potential core length of the main oxygen jet. Full article

To achieve an atomically clean surface of single-crystal aluminum nitride (AlN) substrates, this study systematically evaluated the effects of each step in ex situ wet chemical cleaning (solvent, piranha solution, HF, HCl) and in situ hydrogen annealing. X-ray photoelectron spectroscopy (XPS) and atomic force microscopy (AFM) analyses revealed that while the combination of solvent and piranha solution exposed step morphology, its effectiveness in removing organic contaminants was limited. HF cleaning efficiently removed the oxide layer but introduced fluorine residues, whereas HCl cleaning left no chlorine residues but exhibited lower efficiency in oxide removal. In situ hydrogen annealing significantly reduced carbon and oxygen contamination, albeit accompanied by a transformation of the surface morphology from step to island mode. By modulating the low V/III ratio during low-temperature metal–organic chemical vapor deposition (MOCVD) growth, a controlled transition from 3D island growth to 2D step-flow growth was achieved. This research provides a basis for optimizing AlN substrate surface treatment, offering important insights for advancing nitride-based optoelectronic and power devices. Full article

Understanding the crack development and rainfall infiltration in loess under wetting–drying cycles is crucial for assessing slope stability and promoting sustainable land management in ecologically vulnerable regions. This study employed a three-dimensional column model (Φ₂₄ × 50 cm) with 64 buried electrodes to simulate short-term heavy rainfall by changing the light duration (10 h/d and 5 h/d) and using 100 mm rainfall water. Results indicate that dry–wet cycles cause cumulative damage, significantly altering soil infiltration properties. After four cycles, the rainfall infiltration recharge coefficient increased from an initial 0.44% to 45.58%, a more than 100-fold rise. Resistivity imaging revealed a shift in water transport mode: from uniform matrix flow initially to preferential flow dominated by crack networks as cracks developed. During drying, crack zones exhibited high resistivity (ρ > 150 Ω·m), while water-filled cracks during infiltration showed low resistivity (ρ < 50 Ω·m). Resistivity is an excellent comprehensive index to quantify multi-field coupling damage, and its change (ρ∝ 1/w^1.86 × 1/(1 + 0.032 width)) synchronously responds to water content, crack development and dry–wet process. Low water content (w < 15%) and medium crack width (4–6 mm) are the most sensitive states. Longer illumination (10 h/d) promoted greater crack development and higher infiltration capacity compared to shorter cycles (5 h/d). The developed resistivity–moisture relationship provides a non-destructive monitoring tool for slope moisture dynamics, supporting not only geotechnical stability assessment but also optimized irrigation scheduling and adaptive land-use planning. These insights contribute directly to the sustainable management of soil and water resources in loess landscapes, aligning with sustainability goals in fragile ecosystems. Full article

This study systematically investigates the effects of rope length, lifting position, and load on the dynamic behavior and wind-induced fatigue life of flat-jib tower cranes. Firstly, natural frequencies of a representative crane (40 m tower, 66 m jib) were accurately identified via on-site stress measurements. Subsequently, a finite element model was developed to analyze free vibration characteristics under various operational conditions. Fluctuating along-wind loads were simulated using harmonic synthesis, and transient dynamic analysis provided the wind-induced response. Finally, fatigue life of critical components was assessed through rain-flow counting, S–N curves per Chinese and European standards, and Miner’s linear damage rule. The results indicate that the first-order natural frequency in the along-wind direction decreases by approximately 12.5% and 14.2% with increasing lifted load and rope length, respectively, while the frequency at the jib tip is reduced by up to 37% compared to that at the jib root. Structural responses are more pronounced in the along-wind direction, predominantly exciting the first-order mode. Under operational conditions, stress in the jib’s main chord increases by approximately 30% to 50%, whereas stress fluctuations in other jib sections remain minimal. The fatigue life of tower crane components decreases by 13% to 21% relative to the unloaded state, with rope length exerting a greater influence than lifting load magnitude. Full article