Search Results (2,662)

Hydraulic thrust cylinders in hard-rock tunnel boring machines (TBMs) often exhibit slow response and sluggish acceleration during start-up, which degrades early-stage tracking performance and limits overall operational accuracy. Most existing studies primarily enhance start-up behavior through advanced control algorithms, yet the achievable improvement is ultimately constrained by the system’s flow–pressure capacity. Meanwhile, reported system-level optimization approaches are either difficult to implement under practical TBM operating conditions or fail to consistently deliver high-accuracy tracking. To address these limitations, this paper proposes a “dual-pump–single-cylinder” control framework for the TBM thrust system, where a large-displacement pump serves as the main supply and a parallel small-displacement pump provides auxiliary flow compensation to mitigate the start-up flow deficit. Building on this architecture, an adaptive compensation algorithm is developed for the auxiliary pump, with its output updated online according to the system’s dynamic states, including displacement error and velocity-related error components. Comparative simulations and test-bench experiments show that, compared with a single-pump scheme, the proposed method notably accelerates cylinder start-up while effectively suppressing overshoot and oscillations, thereby improving both transient smoothness and tracking accuracy. This study provides a feasible and engineering-oriented solution for achieving “rapid and smooth start-up” of TBM hydraulic cylinders. Full article

This study examines how Artificial Intelligence (AI) is reshaping the role of university teachers and transforming the foundations of academic work in the digital age. Building on the Dynamic Capabilities Theory (sensing–seizing–transforming), the article proposes a theoretical reframing of university teachers’ perceptions of AI. This approach allows us to bridge micro-level emotions with meso-level HR policies and macro-level sustainability goals (SDGs 4, 8, and 9). The empirical foundation includes a survey of 453 Ukrainian university teachers (2023–2025) and statistics, supplemented by a bibliometric analysis of 26,425 Scopus-indexed documents. The results indicate that teachers do not anticipate a large-scale replacement by AI within the next five years. However, their fear of losing control over AI technologies is stronger than the fear of job displacement. This divergence, interpreted through the lens of dynamic capabilities, reveals weak sensing signals regarding professional replacement but stronger signals requiring managerial seizing and institutional transformation. The bibliometric analysis further demonstrates a theoretical evolution of the university teacher’s role: from a technological adopter (2021–2022) to a mediator of ethics and integrity (2023–2024), and, finally, to a designer and architect of AI-enhanced learning environments (2025). The study contributes to theory by extending the application of Dynamic Capabilities Theory to higher education governance and by demonstrating that teachers’ perceptions of AI serve as indicators of institutional resilience. Based on Dynamic Capabilities Theory, the managerial recommendations are divided into three levels: government, institutional, and scientific-didactic (academic). Full article

Pile foundations are critical load-bearing components in bridge structures, particularly in soft, high-moisture soils susceptible to external disturbances. This study investigated the impact of large-scale soil excavation on the stability of adjacent pile foundations through comprehensive field monitoring of a newly constructed bridge during both the bridge construction and channel excavation phases. The close proximity of the excavation site to the pile caps facilitated a detailed assessment of soil–structure interaction. The results indicate that the pile axial force peaked at the pile head and decreased progressively with depth, consistent with the load transfer mechanism of friction piles. Notably, a distinct variation in axial force was observed at the bedrock interface, attributed to reduced relative displacement between the pile and the surrounding soil. Furthermore, channel water filling raised the local groundwater table, which increased the buoyancy and reduced negative skin friction, thereby decreasing the pile axial force. The study also highlighted the sensitivity of pile deformation in soft soil to unbalanced earth pressure. Asymmetric excavation and surface surcharge loading were identified as critical factors compromising pile stability and overall structural safety. These findings provide valuable insights for construction practices and offer effective strategies to mitigate adverse excavation effects, ensuring long-term structural stability. Full article

The Chang 7 shale oil reservoirs of the Yanchang Formation in the Heishui Area of the Ordos Basin display typical tight sandstone characteristics, marked by complex microscopic pore structures and limited flow capacity, which severely constrain efficient development. Using a suite of laboratory techniques—including nuclear magnetic resonance, mercury intrusion porosimetry, oil–water relative permeability, spontaneous imbibition experiments, scanning electron microscopy, and thin section analysis—this study systematically characterizes representative tight sandstone samples and examines the microscopic distribution of remaining oil, flow behavior, and their controlling factors. Results indicate that residual oil is mainly stored in nanoscale micropores, whereas movable fluids are predominantly concentrated in medium to large pores. The bimodal or trimodal T₂ spectra reflect the presence of multiscale pore–fracture systems. Spontaneous imbibition and relative permeability experiments reveal low displacement efficiency (average 41.07%), with flow behavior controlled by capillary forces and imbibition rates exhibiting a three-stage pattern. The primary factors influencing movable fluid distribution include mineral composition (quartz, feldspar, lithic fragments), pore–throat structure (pore size, sorting, displacement pressure), physical properties (porosity, permeability), and heterogeneity (fractal dimension). High quartz and illite contents enhance effective flow pathways, whereas lithic fragments and swelling clay minerals significantly impede fluid migration. Overall, this study clarifies the coupled “lithology–pore–flow” control mechanism, providing a theoretical foundation and practical guidance for the fine characterization and efficient development of tight oil reservoirs. The findings can directly guide the optimization of hydraulic fracturing and enhanced oil recovery strategies by identifying high-mobility zones and key mineralogical constraints, enabling targeted stimulation and improved recovery in the Chang 7 and analogous tight reservoirs. Full article

Perfluorooctane sulfonate (PFOS), a persistent and bioaccumulative perfluoroalkyl substance, poses significant environmental and human health risks due to the extraordinary stability of its C–F bonds. Conventional remediation strategies largely fail to achieve mineralization, instead transferring contamination or producing secondary waste streams. In this study, we investigate neutron irradiation as a potential destructive approach for PFOS remediation in both solid and aqueous matrices. Samples were exposed to thermal neutrons (flux: 3.2 × 10⁹ n·cm⁻²·s⁻¹, 0.0025 eV) at the Argonauta reactor for 6 h. Raman and FTIR spectroscopy revealed that PFOS in powder form remained largely resistant to degradation, with only minor structural perturbations observed. In contrast, aqueous PFOS solutions exhibited pronounced spectral changes, including attenuation of C–F and S–O vibrational signatures, the emergence of carboxylate and carbonyl functionalities, and enhanced O–H stretching, consistent with radiolytic oxidation and partial defluorination. Notably, clear peak shifts were predominantly observed for PFOS in aqueous solution after irradiation (overall displacement toward higher wavenumbers), whereas in powdered PFOS the main spectral signature of irradiation was the attenuation of CF₂ and S–O related bands with comparatively limited band relocation. To evaluate the biological relevance of these structural alterations, cell viability assays (MTT) were performed using human umbilical vein endothelial cells. Non-irradiated PFOS induced marked cytotoxicity at 100 and 50 μg/mL (p < 0.0001), whereas neutron-irradiated PFOS no longer exhibited significant toxicity, with cell viability comparable to the control. These findings indicate a matrix-dependent response: neutron scattering in solids yields negligible molecular breakdown, whereas radiolysis-driven pathways in water facilitate measurable PFOS transformation. The cytotoxicity assay demonstrates that neutron irradiation promotes sufficient molecular degradation of PFOS in aqueous media to suppress its cytotoxic effects. Although complete mineralization was not achieved under the tested conditions, the combined spectroscopic and biological evidence supports neutron-induced radiolysis as a promising pathway for perfluoroalkyl detoxification. Future optimization of neutron flux, irradiation duration, and synergistic catalytic systems may enhance mineralization efficiency. Because PFOS concentration, fluoride release (F⁻), and TOC were not quantified in this study, remediation was assessed through spectroscopic fingerprints of transformation and the suppression of cytotoxicity, rather than by mass-balance mineralization metrics. This study highlights neutron irradiation as a promising strategy for perfluoroalkyl destruction in contaminated water sources. Full article

This paper investigates optical resonance wavelength (ORW) shifts in large-element, fiber-tip surface-micromachined optical ultrasound transducers (SMOUTs) induced by changes in ambient pressure and temperature. The displacement behavior of the SMOUT top membrane under varying pressure and temperature conditions is analyzed and modeled, and simulation results are presented for fiber-tip SMOUTs with four diameters (200, 400, 600, and 800 µm). Fabricated and assembled fiber-tip SMOUTs are experimentally characterized using two dedicated setups to measure their reflectivity spectra and ORW shifts over ambient pressures from 80 kPa to 120 kPa and temperatures from 25 °C to 45 °C. The experimental data show good agreement with the simulation results. These findings provide a solid basis for active control and compensation of ORW shifts via pressure and temperature adjustment. By stabilizing the reflectivity spectrum and minimizing ORW drift, the use of non-tunable high-power light sources to interrogate arrays of fiber-tip SMOUTs with enhanced operational stability and sensitivity is enabled. Full article

This paper proposes an optical three-dimensional (3D) point cloud acquisition and sketching system, which is not limited by the measurement size, unlike traditional 3D object measurement techniques. The system employs an optical displacement sensor for surface displacement scanning and a six-axis inertial sensor (accelerometer and gyroscope) for spatial attitude perception. A microprocessor control unit (MCU) is responsible for acquiring, merging, and calculating data from the sensors, converting it into 3D point clouds. Butterworth filtering and Mahoney complementary filtering are used for sensor signal preprocessing and calculation, respectively. Furthermore, a human–machine interface is designed to visualize the point cloud and display the scanning path and measurement trajectory in real time. Compared to existing works in the literature, this system has a simpler hardware architecture, more efficient algorithms, and better operation, inspection, and observation features. The experimental results show that the maximum measurement error on 2D planes is 4.7% with a root mean square (RMS) error of 2.1%, corresponding to the reference length of 10.3 cm. For 3D objects, the maximum measurement error is 5.3% with the RMS error of 2.4%, corresponding to the reference length of 9.3 cm. Finally, it was verified that this system can also be applied to large-sized 3D objects for outlines. Full article

Large-scale storage solutions play a critical role in the ongoing energy transition, with Underground Hydrogen Storage (UHS) emerging as a possible option. UHS can benefit from existing natural gas storage expertise; however, key differences in hydrogen’s behavior compared to CH₄ must be characterized at the pore scale to optimize the design and the management of these systems. This work investigates two-phase (gas–water) flow behavior using microfluidic devices mimicking reservoir rocks’ pore structure. Microfluidic tests provide a systematic side-by-side comparison of H₂–water and CH₄–water displacement under the same pore-network geometries, wettability, and flow conditions, focusing on the drainage phase. While all experiments fall within the transitional flow regime between capillary and viscous fingering, clear quantitative differences between H₂ and CH₄ emerge. Indeed, the results show that hydrogen’s lower viscosity enhances capillary fingering and snap-off events, while methane exhibits more stable viscous-dominated behavior. Both gases show rapid breakthrough; however, H₂’s flow instability—especially at low capillary numbers (Ca)—leads to spontaneous water imbibition, suggesting stronger capillary forces. Relative permeability endpoints are evaluated when steady state conditions are reached: they show dependence on Ca, not just saturation, aligning with recent scaling laws. Despite H₂ showing a different displacement regime, closer to capillary fingering, H₂ mobility remains comparable to CH₄. These findings highlight differences in flow behavior between H₂ and CH₄, emphasizing the need for tailored strategies for UHS to manage trapping and optimize recovery. Full article

A growing number of fires and explosions in energy storage plants have been triggered by the thermal runaway of lithium-ion batteries. Owing to the complex physicochemical properties of these batteries, their fire safety issues remain unresolved and constitute a major obstacle to the large-scale deployment of energy storage systems. Compared with conventional extinguishing media, liquid nitrogen (LN₂) offers a dual suppression mechanism, i.e., rapid endothermic vaporization and oxygen displacement by inert nitrogen gas, making it highly suitable for lithium-ion battery fire control. However, the key operational parameters governing its suppression efficiency remain unclear, leading to excessive or insufficient LN₂ use in practice. This study established a dedicated experimental platform and designed 10 experimental conditions, each repeated three times, to investigate the propagation of thermal runaway between adjacent batteries and to quantify the suppression performance of LN₂ under varying nozzle diameters and injection strategies. Results demonstrate that under identical injection pressures, larger nozzle diameters significantly outperform smaller ones in cooling and suppression efficiency. The optimal nozzle diameter was found to be 14 mm, achieving a cooling efficiency of 40%. Furthermore, intermittent LN₂ injection of equal total mass outperformed continuous injection, with a 45 s intermittent duration achieving a cooling efficiency of 63%, 23% higher than continuous injection. These findings provide quantitative guidance for the design of LN₂-based suppression systems in large-scale lithium-ion battery energy storage modules. Full article

Background and Clinical Significance: Giant sphenoid wing meningiomas are generally viewed as skull base masses that compress frontal centers and their respective pathways gradually enough to cause a dysexecutive–apathetic syndrome, which can mimic primary neurodegenerative disease. The aim of this report is to illustrate how bedside phenotyping and multimodal imaging can disclose similar clinical presentations as surgically treatable network lesions. Case Presentation: An independent, right-handed older female developed an incremental, two-year decline of her ability to perform executive functions, extreme apathy, lack of instrumental functioning, and a frontal-based gait disturbance, culminating in a first generalized seizure and a newly acquired left-sided upper extremity pyramidal sign. Standardized neuropsychological evaluation revealed a predominant frontal-based dysexecutive profile with intact core language skills, similar to behavioral-variant frontotemporal dementia (bvFTD). MRI demonstrated a large, right fronto-temporo-basal extra-axial tumor attached to the sphenoid wing with homogeneous postcontrast enhancement, significant vasogenic edema within the frontal projection pathways, and a marked midline displacement of structures with an open venous pathway. With the use of a skull-base flattening pterional craniotomy with early devascularization followed by staged internal debulking, arachnoid preserving dissection, and conservative venous preservation, the surgeon accomplished a Simpson Grade I resection. Sequential improvements in the patient’s frontal “re-awakening” were demonstrated through postoperative improvements on standardized stroke, cognitive and functional assessment scales that correlated well with persistent decompression and symmetric ventricles on follow-up images. Conclusions: This case illustrates the possibility of a non-dominant sphenoid wing meningioma resulting in a pseudo-degenerative frontal syndrome and its potential for reversal if recognized as a network lesion and treated with tailored, venous-sparing skull-base surgery. Contrast-enhanced imaging and routine frontal testing in atypical “dementia” presentations may aid in identifying additional patients with potentially surgically remediable cases. Full article

The use of large-aperture scanning mirrors for high-resolution and wide-swath imaging represents a major trend in Earth observation technology. However, to improve dynamic response performance, scanning mirror assemblies are highly lightweighted, resulting in reduced overall stiffness. This makes the mirror surface susceptible to thermal and inertial loads during operation, leading to degraded surface accuracy and poor imaging quality. Moreover, dynamic scanning mirror has the multi-disciplinary coupling effects and non-circular structural characteristics. It poses significant challenges for surface figure analysis. To address these issues, this paper proposes a surface analysis method for high-dynamic scanning mirrors under multi-physics coupling in non-circular domains. First, a finite element model of the mirror assembly is established based on the minimum aperture and angular velocity parameters. Through finite element analysis, the surface response of the scanning mirror assembly under thermal loads, dynamic inertial loads, and their coupled effects is quantitatively investigated. Subsequently, an analytical approach, which combines rigid-body displacement separation and Gram–Schmidt orthogonalization, is developed to construct non-circular Zernike polynomials, enabling high-precision fitting and reconstruction of the mirror’s dynamic surface distortions. Numerical experiments validate the accuracy of the model. Results show that for a scanning mirror with an aperture of 466 mm × 250 mm under the coupled condition of a 5 °C temperature rise and 50 N·mm torque, the surface figure achieves RMS < 2 nm and PV < 22 nm, with a fitting accuracy achieves 10⁻⁶. These results verify the accuracy and reliability of the proposed method. The surface analysis approach presented in this study provides theoretical guidance and a design framework for subsequent image quality evaluation and assurance. Full article

This study aims to demonstrate the feasibility of a hybrid measurement system that combines Laser Doppler Vibrometry (LDV) and conventional accelerometers for operational modal analysis (OMA) of civil engineering structures. The proposed approach addresses the limitations of traditional accelerometer-based systems, particularly for large-scale or inaccessible structures, by integrating non-contact LDV measurements with conventional sensor data. Experimental tests were conducted on a cantilever beam and a pedestrian laboratory footbridge to validate the hybrid system. The LDV was used to measure velocity at key points, while accelerometers provided complementary reference acceleration measurements. Reflective targets were employed to facilitate non-contact data collection, allowing for the subsequent reuse of these targets for repeated measurements. The velocity data from the LDV were differentiated to obtain acceleration and integrated to estimate displacement, enabling a direct combination with accelerometer data. ARTeMIS Modal software was utilized to process and analyze the collected data, successfully identifying the natural frequencies and vibration modes of both structures. The results demonstrate that the LDV–accelerometer hybrid system effectively captures the dynamic behavior of structures, offering a comprehensive solution for modal analysis without extensive sensor deployment. This approach provides significant advantages in scenarios where traditional methods are impractical, positioning the hybrid system as a promising tool for dynamic analysis and infrastructure monitoring of complex structures. Full article

With the rapid development of mobile robotics, wheeled bipedal robots, which combine the terrain adaptability of legged robots with the high mobility of wheeled systems, have attracted increasing research attention. To address the balance control problem during both standing and locomotion while reducing the influence of noise on control performance, this paper proposes a balance control framework based on a Linear Quadratic Regulator integrated with an Extended Kalman Filter (KLQR). Specifically, a baseline LQR controller is designed using the robot’s dynamic model, where the control input is generated in the form of wheel-hub motor torques. To mitigate measurement noise and suppress oscillatory behavior, an Extended Kalman Filter is applied to smooth the LQR torque output, which is then used as the final control command. Filtering experiments demonstrate that, compared with median filtering and other baseline methods, the proposed EKF-based approach significantly reduces high-frequency torque fluctuations. In particular, the peak-to-peak torque variation is reduced by more than 60%, and large-amplitude torque spikes observed in the baseline LQR controller are effectively eliminated, resulting in continuous and smooth torque output. Static balance experiments show that the proposed KLQR algorithm reduces the pitch-angle oscillation amplitude from approximately ±0.03 rad to ±0.01 rad, corresponding to an oscillation reduction of about threefold. The estimated RMS value of the pitch angle is reduced from approximately 0.010 rad to 0.003 rad, indicating improved convergence and steady-state stability. Furthermore, experiments involving constant-speed straight-line locomotion and turning indicate that the KLQR algorithm maintains stable motion with velocity fluctuations limited to within ±0.05 m/s. The lateral displacement deviation during locomotion remains below 0.02 m, and no abrupt acceleration or deceleration is observed throughout the experiments. Overall, the results demonstrate that applying Extended Kalman filtering to smooth the control torque effectively improves the smoothness and stability of LQR-based balance control for wheeled bipedal robots. Full article

Background: Submacular hemorrhage (SMH) is a vision-threatening condition most associated with neovascular age-related macular degeneration (nAMD), although it may also arise from polypoidal choroidal vasculopathy, pathological myopia, retinal vascular diseases, trauma, and systemic factors. Rapid management is essential because subretinal blood induces photoreceptor toxicity, clot organization, and fibroglial scarring, leading to irreversible visual loss. The choice and urgency of treatment depend on hemorrhage size, duration, and underlying pathology, and the patient’s surgical risk category, which can influence the invasiveness of the selected procedure. This review aims to provide an updated synthesis of recent advances in the surgical and pharmacological management of SMH, focusing on evidence from the past five years and comparing outcomes across major interventional approaches. Methods: A narrative review of 27 recent clinical and multicentre studies was conducted. The included literature evaluated pneumatic displacement (PD), pars plana vitrectomy (PPV), subretinal or intravitreal recombinant tissue plasminogen activator (rtPA), anti-VEGF therapy, and hybrid techniques. Studies were analyzed about indications, surgical methods, timing of intervention, anatomical and functional outcomes, and complication and patient risk stratification. Results: Outcomes varied depending on the size and duration of hemorrhage, as well as the activity of underlying macular neovascularization. PD with intravitreal rtPA was reported as effective for small and recent SMH. PPV combined with subretinal rtPA, filtered air, and anti-VEGF therapy demonstrated favorable displacement and visual outcomes in medium to large hemorrhages or those associated with active nAMD. Hybrid techniques further improved clot mobilization in selected cases. Across studies, delayed intervention beyond 14 days correlated with reduced visual recovery due to blood organization and photoreceptor loss. Potential risks, including recurrent bleeding and rtPA-associated toxicity, were reported but varied across studies. Conclusions: Management should be individualized, considering hemorrhage characteristics and surgical risk. Laser therapy, including PDT, may serve as an adjunct in the perioperative or postoperative period, particularly in PCV patients. Early, tailored intervention typically yields the best functional outcomes. Full article

Although PINNs have demonstrated strong predictive capabilities in forward problems, their performance in inverse problems remains inadequate, largely due to unquantifiable noise encountered during the multi-parameter identification of prestressed concrete beams. Experimental measurements are often noisy, sparse, or asymmetric, while numerical or analytical models, although physically consistent, are typically approximate and lack regularization from well-defined multi-fidelity data. To address this limitation, this paper proposed a multi-fidelity data and prior-enhanced physics-informed neural network (MF-rPINN), which integrates multi-fidelity data with physics prior relational constraints to guide parameter identification using only sparse experimental observations. The MF-rPINN architecture is designed to enforce consistency between each training iteration and a prescribed set of experimental measurements, while embedding the second-order displacement function into the loss function. Experimental results demonstrate that the proposed MF-rPINN achieves accurate parameter identification even under noisy and incomplete observations, owing to the combined regularization effects of governing physical laws and the second-order displacement prior. The minimum relative errors of the elastic modulus are −6.49% and −9.32% under different and identical loading conditions, respectively, while the minimum relative errors of the prestress force are 0.65% and 4.51%. Compared with classical analytical approaches, MF-rPINN exhibits superior robustness and is capable of predicting continuous displacement fields of prestressed concrete beams while simultaneously identifying prestress force and elastic modulus. These advantages highlight the potential of MF-rPINN as a reliable surrogate modeling tool for practical engineering applications. Full article