Search Results (2,030)

A signal-processing algorithm for the detailed determination of delamination in multilayer structures is proposed in this work. The algorithm is based on calculating the phase velocity of the Lamb wave A₀ mode and estimating this velocity dispersion. Both simulation and experimental studies were conducted to validate the proposed technique. The delamination having a diameter of 81 mm on the segment of a wind turbine blade (WTB) was used for verification of the proposed technique. Four cases were used in the simulation study: defect-free, delamination between the first and second layers, delamination between the second and third layers, and defect (hole). The calculated phase velocity variation in the A₀ mode was used to determine the location and edge coordinates of the delaminations and defects. It has been found that in order to estimate the depth at which the delamination is, it is appropriate to calculate the phase velocity dispersion curves. The difference in the reconstructed phase velocity dispersion curves between the layers simulated at different depths is estimated to be about 60 m/s. The phase velocity values were compared with the delamination of the second and third layers and a hole drilled at the corresponding depth. The obtained simulation results confirmed that the drilled hole can be used as a defect corresponding to delamination. The WTB sample with a drilled hole of 81 mm was used in the experimental study. Using the proposed algorithm, detailed defect parameters were obtained. The results obtained using simulated and experimental signals indicated that the proposed new algorithm is suitable for the determination of delamination parameters in a multilayer structure. Full article

To study the influence of the spatial distribution and structure of multi-scale cracks on the mechanical behavior of rocks, triaxial compression tests and cyclic triaxial complete loading and unloading tests were conducted on sandstone, with real-time wave velocity monitoring and CT scan testing. The quantitative classification criteria for multi-scale cracks on sandstone were established, and the constraint effect of confining pressure was analyzed. The crack with a length less than 0.1 mm is considered a small-scale crack, 0.1–1 mm is a medium-scale crack, and larger than 1 mm is a large-scale crack. As the confining pressure increases, the spatial fractal dimension of large-scale cracks decreases, while that of medium-scale cracks increases, and that of small-scale cracks remains stable. The respective nonlinear models of the aspect ratio were established with the length and density of multi-scale cracks. The results indicate significant differences in the effects of cracks of different scales on rock damage. The distribution density of medium-scale cracks in the failed specimen is higher, which is the main reason to produce damage. The small-scale cracks mainly originate from relatively uniform initial cracks in rocks, mainly distributed in medium-density and low-density areas. The results of this research provide important insights into how to quantitatively evaluate the damage of rocks. Full article

An eight-element MIMO antenna with a neutralization line was utilized for future 5G mm-wave applications. The MIMO configuration was designed for two ports, four ports and eight ports to validate the desired impedance and radiation characteristics. The measured results in terms of MIMO and scattering parameters correlate well with the simulated one. The printed eight-port antenna was a miniaturized size of 44 × 70 × 0.8 mm³. Roger RT/duroid 5880 substrate was used to print antennas. The presented antenna produced a vast bandwidth of 18 GHz, varying from 28 to 46 GHz, and achieved a reduced mutual coupling of 30 dB with 6.8–8.5 dBi gain. The eight-port antenna is compared with contemporary antennas considering size, isolation, impedance bandwidth, diversity characteristics and radiation properties, confirming that the presented antenna is a promising candidate for future 5G mm-wave applications. Full article

Gesture recognition technology based on millimeter-wave radar can recognize and classify user gestures in non-contact scenarios. To address the complexity of data processing with multi-feature inputs in neural networks and the poor recognition performance with single-feature inputs, this paper proposes a gesture recognition algorithm based on ResNet Long Short-Term Memory with an Attention Mechanism (RLA). In the aspect of signal processing in RLA, a range–Doppler map is obtained through the extraction of the range and velocity features in the original mmWave radar signal. Regarding the network architecture in RLA, the relevant features of the residual network with channel and spatial attention modules are combined to prevent some useful information from being neglected. We introduce a residual attention mechanism to enhance the network’s focus on gesture features and avoid the impact of irrelevant features on recognition accuracy. Additionally, we use a long short-term memory network to process temporal features, ensuring high recognition accuracy even with single-feature inputs. A series of experimental results show that the algorithm proposed in this paper has higher recognition performance. Full article

This paper presents an automated method for solving the initial structure of compact, high-zoom-ratio mid-wave infrared (MWIR) zoom lenses. Using differential analysis, the focal length variation process of zoom lenses under paraxial conditions is investigated, and a model for the focal power distribution and relative motion of three movable lens groups is established. The particle swarm optimization (PSO) algorithm is introduced into the zooming process analysis, and a program is developed in MATLAB to solve for the initial structure. This algorithm integrates physical constraints from lens analysis and evaluates candidate solutions based on key design parameters, such as total lens length, zoom ratio, Petzval field curvature, and focal length at tele end. The results demonstrate that the proposed method can efficiently and accurately determine the initial structure of compact MWIR zoom lenses. Using this method, a mid-wave infrared zoom lens with a zoom ratio of 50×, a total length of less than 530 mm, and the ratio of focal length to total length approximately 2:1 was successfully designed. The design validates the effectiveness and practicality of this method in solving the initial structure of zoom lenses that meet complex design requirements. Full article

Autonomous driving vehicles have strong path planning and obstacle avoidance capabilities, which provide great support to avoid traffic accidents. Autonomous driving has become a research hotspot worldwide. Depth estimation is a key technology in autonomous driving as it provides an important basis for accurately detecting traffic objects and avoiding collisions in advance. However, the current difficulties in depth estimation include insufficient estimation accuracy, difficulty in acquiring depth information using monocular vision, and an important challenge of fusing multiple sensors for depth estimation. To enhance depth estimation performance in complex traffic environments, this study proposes a depth estimation method in which point clouds and images obtained from MMwave radar and cameras are fused. Firstly, a residual network is established to extract the multi-scale features of the MMwave radar point clouds and the corresponding image obtained simultaneously from the same location. Correlations between the radar points and the image are established by fusing the extracted multi-scale features. A semi-dense depth estimation is achieved by assigning the depth value of the radar point to the most relevant image region. Secondly, a bidirectional feature fusion structure with additional fusion branches is designed to enhance the richness of the feature information. The information loss during the feature fusion process is reduced, and the robustness of the model is enhanced. Finally, parallel channel and position attention mechanisms are used to enhance the feature representation of the key areas in the fused feature map, the interference of irrelevant areas is suppressed, and the depth estimation accuracy is enhanced. The experimental results on the public dataset nuScenes show that, compared with the baseline model, the proposed method reduces the average absolute error (MAE) by 4.7–6.3% and the root mean square error (RMSE) by 4.2–5.2%. Full article

Background: The selection of an optimal referencing method in event-related potential (ERP) research has been a long-standing debate, as it can significantly influence results and lead to data misinterpretation. Such misinterpretation can produce flawed scientific conclusions, like the inaccurate localization of neural processes, and in practical applications, such as using ERPs as biomarkers in medicine, it may result in incorrect diagnoses or ineffective treatments. In line with the development and advancement of good scientific practice (GSP) in ERP research, this study sought to address several questions regarding the most suitable digital reference for investigating the N400 ERP component. Methods: The study was conducted on 17 neurotypical participants. Based on previous research, the references evaluated included the common average reference (AVE), mean earlobe reference (EARS), left mastoid reference (L), mean mastoids reference (MM), neutral infinity reference (REST), and vertex reference (VERT). Results: The results showed that all digital references, except for VERT, successfully elicited the centroparietal N400 effect in the picture–word verification task. The AVE referencing method showed the most optimal set of metrics in terms of effect size and localization, although it also produced the smallest difference waves. The most similar topographic dynamics in the N400 window were observed between the AVE and REST referencing methods. Conclusions: As the most optimal regions of interest (ROI) for the picture–word elicited N400 effect, nine electrode sites spanning from superior frontocentral to parietal regions were identified, showing consistent effects across all referencing methods except VERT. Full article

A new method of producing metal powders for additive manufacturing by the atomization of free-falling melt streams using pulsed cross-flow gaseous shock or detonation waves is proposed. The method allows the control of shock/detonation wave intensity (from Mach number 4 to about 7), as well as the composition and temperature of the detonation products by choosing proper fuels and oxidizers. The method is implemented in laboratory and industrial setups and preliminarily tested for melts of three materials, namely zinc, aluminum alloy AlMg5, and stainless steel AISI 304, possessing significantly different properties in terms of density, surface tension, and viscosity. Pulsed shock and detonation waves used for the atomization of free-falling melt streams are generated by the pulsed detonation gun (PDG) operating on the stoichiometric mixture of liquid hydrocarbon fuel and gaseous oxygen. The analysis of solidified particles and particle size distribution in the powder is studied by sifting on sieves, optical microscopy, laser diffraction wet dispersion method (WDM), and atomic force microscopy (AFM). The operation process is visualized by a video camera. The minimal size of the powders obtained by the method is shown to be as low as 0.1 to 1 μm, while the maximum size of particles exceeds 400–800 μm. The latter is explained by the deficit of energy in the shock-induced cross-flow for the complete atomization of the melt stream, in particular dense and thick (8 mm) streams of the stainless-steel melt. The mass share of particles with a fraction of 0–10 μm can be at least 20%. The shape of the particles of the finest fractions (0–30 and 30–70 μm) is close to spherical (zinc, aluminum) or perfectly spherical (stainless steel). The shape of particles of coarser fractions (70–140 μm and larger) is more irregular. Zinc and aluminum powders contain agglomerates in the form of particles with fine satellites. The content of agglomerates in stainless-steel powders is very low. In general, the preliminary experiments show that the proposed method for the production of finely dispersed metal powders demonstrates potential in terms of powder characteristics. Full article

In this work, a unified design methodology for front-end RF/mmWave receivers is presented, aiming to significantly accelerate the design procedure of the front-end RF blocks in complex RX/TX chain implementations. The proposed design methodology is based on optimization loops with well-defined cost functions so as to minimize the design iterations that may be encountered during specification tuning. As proof of concept, two essential RF blocks widely used in RF receivers, a low-noise amplifier (LNA) and a voltage-controlled oscillator (VCO), were designed using the proposed unified methodology with a 65 nm RF-CMOS processing node. Finally, the derived designs were compared to similar designs in the literature, proving that the proposed unified methodology is capable of synthesizing RF/mmWave LNAs and VCOs with industry-standard specifications within a significantly faster time frame. Full article

The advent of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems, coupled with reconfigurable intelligent surfaces (RISs), presents a significant opportunity for advancing wireless communication technologies. This integration enhances data transmission rates and broadens coverage areas, but challenges in channel estimation (CE) remain due to the limitations of the signal processing capabilities of RIS. To address this, we propose an adaptive channel estimation framework comprising two algorithms: log-sum normalized least mean squares (Log-Sum NLMS) and hybrid normalized least mean squares-normalized least mean fourth (Hybrid NLMS-NLMF). These algorithms leverage the sparse nature of mmWave channels to improve estimation accuracy. The Log-Sum NLMS algorithm incorporates a log-sum penalty in its cost function for faster convergence, while the Hybrid NLMS-NLMF employs a mixed error function for better performance across varying signal-to-noise ratio (SNR) conditions. Our analysis also reveals that both algorithms have lower computational complexity compared to existing methods. Extensive simulations validate our findings, with results illustrating the performance of the proposed algorithms under different parameters, demonstrating significant improvements in channel estimation accuracy and convergence speed over established methods, including NLMS, sparse exponential forgetting window least mean square (SEFWLMS), and sparse hybrid adaptive filtering algorithms (SHAFA). Full article

Bamboo was carbonized and further modified via co-doping with graphene oxide (GO) and polyaniline (PANI) to prepare microwave absorption composites (GO/PANI/CB) by in situ polymerization of 1R-(-)-Camphorsulfonic acid (L-CSA). The conductivity of GO/PANI/CB reached 2.17 ± 0.05 S/cm under the optimized process conditions. The oxygen-containing group of GO reacts with PANI to form hydrogen bonds and thus polymerize. The GO and PANI particles covered the carbonized bamboo (CB) surface in a disordered aggregation form. Based on the measuring method of the vector network analyzer (VNA), the microwave-absorption performance of GO/PANI/CB was investigated. With 30% addition of GO/PANI/CB, the minimum reflection loss (RL_min) at 7.12 GHz with a thickness of 3.5 mm of samples reached −49.83 dB. The effective absorption bandwidth (<−10 dB) is as high as 4.72 GHz with a frequency range of 11.68–16.40 GHz and a thickness of 2 mm. Compared with many PANI based electromagnetic wave absorbing materials reported in recent years, GO/PANI/CB provides improved microwave-absorption performance while maintaining high absorption bandwidth. GO/PANI/CB exhibited the advantages of simple preparation, low cost, renewability, light texture, thinness, wide absorption bandwidth, and strong absorption ability, and can be used for new microwave absorption materials. Full article

The evolution of the THz waveform generated from the two-color air filament was experimentally investigated by moving an iris along the plasma channel. By taking the differentiation of the measured THz waveforms, the local longitudinally resolved THz waves along a 54 mm-long filament were obtained. The local THz pulse underwent periodic phase shifts. A theoretical deduction indicates that the phase shifts are mainly caused by the dispersion in the plasma channel which plays a dominant role in the evolution of the local THz waveforms. Full article

Background: Recent research highlights the potential role of sex-specific variations in cardiovascular disease. The gut microbiome has been shown to differ between the sexes in patients with cardiovascular risk factors. Objectives: The main objective of this study is to analyze the differences between women and men in the relationship between gut microbiota and measures of arterial stiffness. Methods: We conducted a cross-sectional study in Spain, selecting 180 subjects (122 women, 58 men) aged between 45 and 74. Subjects with arterial stiffness were identified by the presence of at least one of the following: carotid–femoral pulse wave velocity (cf-PWV) above 12 mm/s, cardio–ankle vascular index (CAVI) above nine, or brachial–ankle pulse wave velocity (ba-PWV) above 17.5 m/s. All other cases were considered subjects without arterial stiffness. The composition of the gut microbiome in fecal samples was determined by 16S rRNA sequencing. Results: We found that women have a more diverse microbiome than men (Shannon, p < 0.05). There is also a significant difference in gut microbiota composition between sexes (Bray–Curtis, p < 0.01). Dorea, Roseburia, and Agathobacter, all of them short-chain fatty-acid producers, were more abundant in women’s microbiota (log values > 1, p-value and FDR < 0.05). Additionally, Blautia was more abundant in women when only the subjects with arterial stiffness were considered. According to logistic regression, Roseburia was negatively associated with arterial stiffness in men, while Bifidobacterium and Subdoligranulum were positively related to arterial stiffness. Conclusions: In the Spanish population under study, women had higher microbiome diversity and potentially protective genera. The host’s gender determines the influence of the same bacteria on arterial stiffness. Trial Registration Number: NCT03900338. Full article

Frequency-modulated continuous-wave (FMCW) millimeter-wave (mmWave) radar systems are increasingly utilized in environmental sensing due to their high range resolution and robust sensing ability in severe weather environments. However, mutual interference among radar systems significantly degrades the target detection capability. Recent advancements in interference mitigation utilizing deep learning (DL) approaches have demonstrated promising results. DL-based approaches typically have high computational costs, which makes them unsuitable for real-time applications with strict latency requirements and limited computing resources. In this paper, we propose an efficient solution for real-time radar interference mitigation. A lightweight transformer, which is smaller and faster than the baseline transformer, is designed to reduce interference. The integration of linear attention mechanisms with depthwise separable convolutions significantly reduces the network’s computational complexity while maintaining a comparable performance. In addition, a two-stage knowledge distillation (KD) process is deployed to compress the network and enhance its efficiency. The staged distillation approach alleviates the training difficulties associated with substantial differences between the teacher and student networks. Both simulated and real-world experiments demonstrate that the proposed method outperforms the state-of-the-art methods while achieving high processing speeds. Full article

An ultrafast microwave ranging method based on optically generated frequency-modulated microwave pulses is proposed in this study. The theoretical analysis demonstrated that nanosecond-scale linear frequency modulation microwave pulse can be obtained by femtosecond laser interference under the condition of unbalanced dispersion, which can be used to achieve a high temporal resolution of the displacement change in the measurement by the principle of frequency modulation continuous wave (FMCW) radar. The proof-of-principle experiment successfully measured the displacement change with an error of 2.5 mm and a range of 0.6 m, with a response time of 468 ns. Compared to existing microwave ranging technologies, the temporal resolution was improved by two orders of magnitude, which greatly improves the temporal resolution of distance measurement in the field of microwave FMCW radar. Full article