Search Results (81)

Continuous monitoring of lower-limb kinematics in natural environments is essential for gait analysis and rehabilitation but remains challenging due to the limitations of optical systems and the inaccuracy of sparse inertial sensor methods. To address this, we propose a high-precision, minimalist wearable system utilizing only three inertial measurement units placed on the pelvis and shanks. In the data preprocessing stage, engineering modifications are made based on the traditional gradient descent algorithm to implement adaptive channel adjustment on the acceleration and magnetic data of a single IMU, aiming to alleviate the impact of motion acceleration and external magnetic interference on the temporal feature manifold. Subsequently, a pure Transformer neural network is utilized to capture long-range temporal dependencies, reconstructing full lower-limb kinematics without relying on rigid biomechanical assumptions. The model was optimized and deployed on an STM32N647 microcontroller to achieve real-time edge inference with a low latency of approximately 17 ms. Experimental results demonstrate that the proposed method achieves a mean absolute error of 2.41° for level walking, significantly outperforming traditional constrained Kalman filter approaches. Furthermore, it maintains high tracking robustness during complex nonlinear movements such as squatting and lunging. In conclusion, this edge-computing-enabled framework provides an accurate, comfortable, and real-time solution for unconstrained human motion capture in daily scenarios. Full article

In cardiovascular interventional procedures, real-time, precise monitoring of minute strain and temperature fluctuations at the catheter tip is essential to improving both the safety and efficacy of these interventions. Fiber Bragg grating (FBG)-based sensors present a promising solution owing to their diminutive size and immunity to electromagnetic interference; however, the inherent cross-sensitivity between strain and temperature remains a significant obstacle. This paper introduces a dual-FBG fiber optic sensing structure that leverages machine learning techniques. The system incorporates two FBGs: one set acts as the primary sensing element, positioned within a simulated catheter and affixed to the substrate under examination with cyanoacrylate adhesive to detect composite strain and temperature signals; the second set is spirally wound around the catheter surface to solely measure temperature, thus effectively isolating temperature interference. Additionally, a machine learning model is employed to learn the nonlinear mapping between the recorded FBG spectra and the actual strain and temperature parameters. Experimental validation was conducted within the physiologically relevant temperature range of 20 °C to 45 °C. The findings indicate that the proposed machine learning model can successfully decouple strain and temperature, achieving high-precision predictions even in situations where the sensing unit exhibits a slight nonlinear response due to adhesive bonding. This study substantiates the feasibility of utilizing machine learning-enhanced dual-FBG structures for multi-parameter sensing in complex environments. The proposed methodology presents a promising avenue for the development of next-generation smart optical fiber sensors intended for application in catheter systems. Full article

Microfluidic systems are increasingly used in neuroprotection research, but their clearest value may be to show why candidate compounds fail before costly downstream models. This critical framework review examines CNS-relevant microfluidic studies through a within-program triage logic linking chemistry-aware prescreening, blood-brain barrier/neurovascular unit (BBB/NVU) filtering, and timed validation in neuronal ischemia/reperfusion models, and treats non-CNS organ-on-a-chip and analytical microfluidic studies as engineering analogies only. The available evidence most strongly supports BBB/NVU chips as exposure- and safety-aware filters and compartmentalized neuronal oxygen-glucose deprivation platforms as timing-sensitive validation tools; droplet microfluidics contributes mainly upstream through dense dose mapping, aggregation assays and counterscreens for assay interference. A compound-centered reading also suggests that apparent activity often fails for distinct reasons, including timing mismatch, poor solubility, surface adsorption, optical artifact, inadequate multicellular context, or loss of efficacy under transport-aware testing. Taken together, the literature supports a cautious, within-program triage logic in which microfluidics is used not as a universal disease model, but as an operational framework for exposing transport, barrier, timing and assay liabilities early in neuroprotective discovery. Full article

To address the demand for underwater acoustic detection with hydrostatic pressure resistance, this paper proposes a fiber-optic Fabry–Perot (F-P) underwater acoustic sensor based on micro-electromechanical system (MEMS) technology. According to the F-P interference principle, the diaphragm deforms under acoustic pressure, inducing variations in the F-P cavity length which modulate the interference spectrum and enable the measurement of underwater acoustic signals. A sensing diaphragm with a composite structure consisting of a central boss and a micro-hole array is designed, which improves the optical signal quality while reducing the influence of the pressure difference between the inner and outer surfaces of the diaphragm on sensor operation. MEMS fabrication, computer numerical control (CNC) machining, and laser fusion splicing technologies are employed to achieve batch fabrication of the sensing units and adhesive-free integration of the sensor. Experimental results show that the proposed sensor exhibits a flat frequency response within ±1.5 dB over the range of 1 kHz to 10 kHz, with an average signal-to-noise ratio (SNR) of 86.35 dB. The sensitivity reaches −181.79 dB re 1 rad/μPa at 10 kHz, with a maximum nonlinearity of 0.48% F.S., a repeatability error of 0.15% F.S. and a dynamic range of 100.83 dB. The proposed sensor features miniaturization, high consistency, hydrostatic pressure self-balancing capability, and immunity to electromagnetic interference, providing a solid foundation for hydrostatic-pressure-resistant underwater acoustic measurements in deep-sea environments. Full article

In optical sensing, electromagnetically induced transparency (EIT) and bound states in the continuum (BIC) substantially enhance light–matter interactions by leveraging high-Q resonances. This study theoretically demonstrates dual-resonance phenomena—namely, a quasi-symmetry-protected BIC (SP-BIC) and a quasi-BIC-induced EIT-like (QBIC-EIT) resonance—using a dielectric metasurface composed of pyramid-shaped lithium niobate nanoarrays operating in the near-infrared. The QBIC-EIT transmission window originates from the interference between surface lattice modes and toroidal dipole modes, triggered by symmetry breaking of the BIC state. Due to the absence of C_4v rotational symmetry in the pyramidal unit cells, the metasurface exhibits pronounced polarization-dependent responses: Under x-polarized incidence, a single quasi-SP-BIC resonance appears; under y-polarization, dual quasi-SP-BIC resonances along with a distinct QBIC-EIT resonance are observed. Both the high-Q quasi-SP-BIC resonance and the EIT-like window show strong sensitivity to changes in the ambient refractive index (RI). Specifically, the EIT-like window achieves a sensitivity of 404.9 nm/RIU, while the quasi-SP-BIC resonance delivers an exceptional sensitivity of 887.7 nm/RIU, confirming the metasurface’s performance as a high-sensitivity RI sensor. These findings establish a multi-band detection platform for advanced RI sensing and contribute to the development of high-performance metasurface-based optical sensors. Full article

With the exponential growth of natural gas reserves and utilization scale in China, underground gas storage (UGS) facilities—critical infrastructure within the natural gas production-supply-storage-sales system—have entered a phase of rapid expansion. As the core component connecting subsurface reservoirs with surface systems, wellbore integrity directly influences operational safety and service lifespan of UGS facilities. However, current leakage detection and integrity analysis methodologies for gas storage wellbores remain deficient in effective real-time monitoring capabilities. Traditional methods, however, are constrained by limited spatial coverage and insufficient precision, rendering them inadequate for comprehensive, continuous safety monitoring requirements. To address this industry challenge, this study proposes a real-time wellbore integrity monitoring framework based on distributed fiber optic sensing technology, integrating distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) devices into a synergistic monitoring system. The DTS component enables preliminary localization of potential leakage points through detection of minute temperature anomalies along the wellbore, while the DAS unit accurately identifies acoustic signatures caused by gas leakage within casings via monitoring of acoustic vibration signals propagating along the optical fiber. Through joint analysis of DTS and DAS data streams, real-time diagnosis of wellbore leakage events and integrity status can be achieved. Field trials demonstrated that this hybrid monitoring system achieved leakage localization accuracy within 1.0 m, effectively distinguishing normal operational signals from abnormal leakage characteristics. During actual monitoring operations, no indications of wellbore integrity compromise were detected; only minor noise and interference signals originating from surface construction activities were observed. Full article

To address the limitations of conventional conveyor-based systems in online detection and grading of orange soluble solids content (SSC), this study developed a novel gravity-driven detection device. Traditional systems are constrained by carrier-induced optical interference, complex mechanical structures, and large spatial requirements, limiting their application in small- and medium-sized enterprises. By introducing a gravity-driven paradigm, this research eliminates the need for fruit carriers and enables vertical spectral acquisition during gravitational descent, effectively overcoming carrier interference and spatial constraints. The integrated system comprises a synchronous-release feeding mechanism, a Vis/NIR detection module, and an intelligent grading unit. Through systematic optimization of disk rotation speed, integration time, and spot size, stable and efficient spectral acquisition was achieved, resulting in a throughput of one fruit per second. The optimized PLSR model, utilizing SG-SNV preprocessing and CARS feature selection, demonstrated excellent predictive performance, with an Rp² of 0.8746 and an RMSEP of 0.3001 °Brix. External validation confirmed 96.6% prediction accuracy within a ±1.0 °Brix error range and an overall grading accuracy of 86.6%. This system offers a compact, cost-effective, and high-performance solution for real-time fruit quality inspection, with potential applications to various spherical fruits. Full article

The pulsed power switch serves as a critical component in pulsed power systems. The electric radiation generated by switching operations threatens the miniaturization of pulsed power systems, causing significant electromagnetic interference (EMI) to nearby signal circuits. The pseudospark switch’s (PSS) exceptionally fast transient response, a key enabler for sophisticated pulsed power systems, is also a major source of severe EMI. This study investigated the electric field radiation from a high voltage PSS within a capacitor discharge unit (CDU), using a near-field scanning system based on an electro-optic probe. The time-frequency distribution of the radiation was characterized, identifying contributions from three sequential stages: the application of the trigger voltage, the main gap breakdown, and the subsequent oscillating high voltage. During the high-frequency oscillation stage, the distribution of the peak electric field radiation aligns with the predictions of the dipole model, with a maximum value of 43.99 kV/m measured near the PSS. The spectral composition extended to 60 MHz, featuring a primary component at 1.24 MHz and distinct harmonics at 20.14 MHz and 32.33 MHz. Additionally, the impacts of circuit parameters and trigger current on the radiated fields were discussed. These results provided essential guidance for the electromagnetic compatibility (EMC) design of highly-integrated pulsed power systems, facilitating more reliable PSS applications. Full article

The application of unmanned vehicles in civilian and military fields is increasingly widespread. Traditionally, unmanned vehicles primarily rely on Global Positioning Systems (GPSs) for positioning; however, GPS signals can be limited or completely lost in conditions such as building obstructions, indoor environments, or electronic interference. In addition, countries are actively developing GPS jamming and deception technologies for military applications, making precise positioning and navigation of unmanned vehicles in GPS-denied or constrained environments a critical issue that needs to be addressed. In this work, authors propose a method based on Visual–Inertial Odometry (VIO), integrating the extended Kalman filter (EKF), an Inertial Measurement Unit (IMU), optical flow, and feature matching to achieve drone localization in GPS-denied environments. The proposed method uses the heading angle and acceleration data obtained from the IMU as the state prediction for the EKF, and estimates relative displacement using optical flow. It further corrects the optical flow calculation errors through IMU rotation compensation, enhancing the robustness of visual odometry. Additionally, when re-selecting feature points for optical flow, it combines a KAZE feature matching technique for global position correction, reducing drift errors caused by long-duration flight. The authors also employ an adaptive noise adjustment strategy that dynamically adjusts the internal state and measurement noise matrices of the EKF based on the rate of change in heading angle and feature matching reliability, allowing the drone to maintain stable positioning in various flight conditions. According to the simulation results, the proposed method is able to effectively estimate the flight trajectory of drones without GPS. Compared to results that rely solely on optical flow or feature matching, it significantly reduces cumulative errors. This makes it suitable for urban environments, forest areas, and military applications where GPS signals are limited, providing a reliable solution for autonomous navigation and positioning of drones. Full article

The scientific community has been interested in lophine’s versatility and usage in various applications. Research has shown that humic acid is a material that exhibits interference with lophine. Humic molecules associate with each other in supramolecular conformations through weak hydrophobic interactions at alkaline or neutral pH and hydrogen bonds at low pH. This work presents the characterization of a sensitive lophine layer based on water’s hydrogen ions (pH). We conducted a spectroscopy study to analyze how the absorbance at different amounts of lophine depends on pH. This study demonstrates the hyperchromic behavior of imidazole at various pH values, which may be utilized in an intrinsic fiber optic pH sensor. The dynamic range of the fiber optic sensor was 5 to 11.3 pH units. The sensor was developed by coating a thinned fiber with a sensitive lophine layer. It achieves a sensitivity of 0.27 dB/pH and a response time of 5 s. Full article

A new series of luminescent Zn(II) complexes based on mono- and bis-imidazo[1,5-a]pyridine ligands was synthesized to investigate the correlation between structural modifications and photophysical behaviour. Systematic variations in substituent groups, coordination geometry, and π-conjugation extent enabled precise tuning of absorption and emission properties. Spectroscopic analysis revealed that Zn(II) coordination enhances molecular rigidity and induces a conformational change in the ligands, resulting in improved quantum yields (up to 37%) and significant blue shifts in emission. Notably, in bis-ligand systems, each imidazo[1,5-a]pyridine unit retains its distinct emissive signature upon complexation, demonstrating their optical and electronic independence. This modular behaviour confirms that individual emissive centres can be predictably manipulated without mutual interference, offering a powerful design strategy for multichromophoric materials. Structural, vibrational, and mass spectrometric characterizations further corroborate the stability and coordination patterns of the synthesized complexes. These insights lay the groundwork for engineering efficient and tunable Zn(II)-based luminophores for applications in optoelectronics, sensing, and bioimaging. Full article

Surface solar irradiance (SSI) is a critical factor influencing the power generation capacity of photovoltaic (PV) power plants. Dynamic changes in cloud cover pose significant challenges to the accurate nowcasting of SSI, which in turn directly affects the reliability and stability of renewable energy systems. However, existing research often simplifies or overlooks changes in the optical and morphological characteristics of clouds, leading to considerable errors in SSI nowcasting. To address this limitation and improve the accuracy of ultra-short-term SSI forecasting, this study first forecasts changes in cloud optical thickness (COT) within the next 3 h based on a spatiotemporal long short-term memory model, since COT is the primary factor determining cloud shading effects, and then integrates the zenith and regional averages of COT, along with factors influencing direct solar radiation and scattered radiation, to achieve precise SSI nowcasting. To validate the proposed method, we apply it to the Albuquerque, New Mexico, United States (ABQ) site, where it yielded promising performance, with correlations between predicted and actual surface solar irradiance for the next 1 h, 2 h, and 3 h reaching 0.94, 0.92, and 0.92, respectively. The proposed method effectively captures the temporal trends and spatial patterns of cloud changes, avoiding simplifications of cloud movement trends or interference from non-cloud factors, thus providing a basis for power adjustments in solar power plants. Full article

Originally introduced in the 1960s by DISA Elektronik as a calibration tunnel for hot-wire anemometers, the Type 55D41 has now been reengineered into a versatile and modern aerodynamic test platform. While retaining key legacy components, such as the converging nozzle and the 55D42 power unit, the upgraded system features a redesigned modular test section with optical-grade quartz windows. This enhancement enables compatibility with advanced flow diagnostics and visualization methods, including PTV, DIC, and schlieren imaging. The modernized facility maintains the precision and flow stability that made the original design widely respected, while expanding its functionality to meet the demands of contemporary experimental research. Its architecture supports the aerodynamic characterization of micro-scale static pressure probes used in aerospace, propulsion, and micro gas turbine applications. Special attention is given to assessing the influence of probe tip geometry (e.g., conical, ogive), port positioning, and stem interference on measurement accuracy. Full article

This study presents a system for precisely measuring pulsed magnetic fields with high amplitude and microsecond duration with minimal interference. The system comprises a probe with an advanced magnetic field sensor and a measurement unit for signal conversion, analysis, and digitization. The sensor uses a thin nanostructured manganite La-Sr-Mn-O film exhibiting colossal magnetoresistance, which enables precise magnetic field measurement independent of its orientation. Films with different compositions were optimized and tested in pulsed magnetic fields. The measurement unit includes a pulsed voltage generator, an ADC, a microcontroller, and an amplifier unit. Two versions of the measurement unit were developed: one with a separate amplifier unit configured for the sensor positioned more than 1 m away from the measurement unit, and the other with an integrated amplifier for the sensor positioned at a distance of less than 0.5 m. A bipolar pulsed voltage supplying the sensor minimized the parasitic effects of the electromotive force induced in the probe circuit. The data were transmitted via a fiber optic cable to a PC equipped with a special software for processing and recording. Tests with 20–30 μs pulses up to 15 T confirmed the effectiveness of the system for measuring high pulsed magnetic fields. Full article

Optical sensors are a promising technology in structural and health monitoring due to their high sensitivity and immunity to electromagnetic interference. Because of their high sensitivity, they can register the responses of buildings to a wide range of motions, including those induced by ambient noise, or detect small structural changes caused by aging or environmental factors. In previous work, an FBG-based accelerometer was introduced that is suitable for use as an autonomous unit since it does not make use of any interrogator equipment. In this paper, we present the results of the characterization of this device, which yielded the best precision and accuracy. The results show the following: (i) improvements in the orthogonality of the sensor axes, which impact their cross-axis sensitivity; (ii) reductions in the electronic noise, which increase the signal-to-noise ratio. The results of our static characterization show that, in the worst case, we can obtain a correlation coefficient R² of 0.9999 when comparing the output voltage with the input acceleration for the X- and Y-axes of the sensor. We developed an analytical, non-iterative, 12-parameter matrix calibration approach based on the least-squares method, which allows compensation for different gains in its axes, offset, and cross-axis. To improve the accuracy of our sensor, we propose a table with correction terms that can be subtracted from the estimated acceleration. The mean error of each estimated acceleration component of the sensor is zero, with a maximum standard deviation of 0.018 m/s². The maximum RMSE for all tested positions is 6.7 × 10⁻³ m/s². Full article