Search Results (698)

Accurate sea clutter modeling is crucial for clutter suppression in edge radar processing. On resource-constrained edge radar platforms, spatiotemporal statistics, together with device-level computation and memory limits, hinder the learning of representative clutter features. This study presents a transformer-based generative adversarial model for sea clutter modeling. The core design of this work uses axial attention to factorize self-attention along pulse and range, preserving long-range dependencies under a reduced attention cost. It also introduces a two-dimensional variable-length spatiotemporal window that retains temporal and spatial coherence across observation lengths. Extensive experiments are conducted to verify the efficacy of the proposed method with quantitative criteria, including a cosine similarity score, spectral-parameter error, and amplitude–distribution distances. Compared with CNN-based GAN, the proposed model achieves a high consistency with real clutter in marginal amplitude distributions, spectral characteristics, and spatiotemporal correlation patterns, while incurring a lower cost than standard multi-head self-attention. The experimental results show that the proposed method achieves improvements of 9.22% and 7.8% over the traditional AR and WaveGAN methods in terms of the similarity metric, respectively. Full article

Background/Objectives: Type 2 diabetes (T2D) is associated with elevated cardiovascular risk and mortality. While physical activity can reduce cardiovascular risk, sustaining behavioral change remains challenging. Wearable activity trackers offer a scalable approach to promote physical activity, but their effects on cardiovascular outcomes in adults with T2D have not been well studied. To evaluate the impact of a wrist-worn activity tracker on physical activity, cardiovascular markers, and metabolic outcomes in adults with T2D over four weeks. Methods: This pilot randomized controlled trial included eight adults with T2D (mean age 54.9 ± 12.6 years; intervention (FIT) group: n = 5; control (CON) group: n = 3). The intervention group received an activity tracker. Both groups used the Fitbit app to track daily activity. Physical activity metrics (steps, walking distance, energy expenditure) and cardiovascular markers (blood pressure, augmentation index, pulse wave velocity, subendocardial viability ratio [SEVR]) were assessed pre- and post-intervention. Non-parametric tests and Spearman correlations were used due to the small sample size. Results: The FIT group showed significant increases in walking distance and energy expenditure and reductions in systolic/diastolic blood pressure, pulse pressure, and mean arterial pressure (all p < 0.04). SEVR trended toward improvement (p = 0.07). No significant changes were seen in the CON group. Increased physical activity was strongly correlated with reductions in pulse pressure (ρ = −0.88) and fasting glucose (ρ = −0.82; both p < 0.05). Conclusions: A brief wearable-based intervention improved physical activity and cardiovascular markers in adults with T2D, supporting feasibility for diabetes care. Full article

Optical intrabody wireless nanosensor networks (OiWNSNs) enable groundbreaking biomedical applications via optical nanocommunication within biological tissues. Synchronization is critical for accurate data recovery in these energy- and size-constrained nanonetworks. In this study, we investigate timing synchronization in a highly dispersive and noisy intravascular optical channel, particularly under an on–off keying preamble comprising Gaussian optical pulses. We proposed a synchronization scheme based on the repetitive transmission of a preamble and noncoherent detection using continuous-time moving average filters with multiple integrator windows. The simulation results reveal that increasing the communication distance degrades the synchronization performance. To counter this degradation, we can increase the number of preamble repetitions, which markedly improves the system reliability and timing accuracy due to the averaging gain, although the performance saturates due to the dispersion floor inherent in the blood channel. Moreover, we found that low-resolution nanoreceivers with fewer integrators outperform high-resolution designs in dispersive environments, as they mitigate the energy-splitting problem due to pulse broadening. This tradeoff between temporal resolution and robustness highlights the importance of channel-aware receiver design. Overall, this study provides key insights into the physical layer design of OiWNSNs and offers practical guidelines for achieving robust synchronization under realistic biological conditions. Full article

Pulsed radiofrequency (PRF) applied to the dorsal root ganglion (DRG) is commonly performed to manage lumbar radicular pain in human patients. Radiculopathy affecting the seventh lumbar spinal nerve has been identified as key predictor of lumbosacral pain in dogs, yet no published technique exists for placing a PRF electrode adjacent to its DRG to deliver PRF treatment. We describe a novel approach in canine cadavers, integrating ultrasound guidance to locate relevant landmarks and confirm cannula placement under fluoroscopy. Black Indian ink was used to create a localised tissue mark at the tip of a radiofrequency cannula, and subsequent cryosections were performed to measure the distance between the mark and the DRG, revealing a distance of 1.96 ± 1.07 mm. Because this was a cadaveric model, no conclusions can be drawn regarding clinical efficacy or safety in live animals. Nonetheless, these results demonstrate the feasibility of precise electrode positioning using combined imaging in dogs. Future research should explore whether PRF delivered through this approach can indeed alleviate lumbosacral radicular pain in dogs, as well as establish optimal electrode-to-nerve distances and potential safety considerations. Ultimately, this technique could broaden veterinary interventions for chronic spinal pain, improving the quality of life in affected dogs. Full article

Streak cameras, essential for ultrahigh temporal resolution diagnostics in laser-driven inertial confinement fusion, underpin the streak tube imaging LiDAR (STIL) system—a flash LiDAR technology offering high spatiotemporal resolution, precise ranging, enhanced sensitivity, and wide field of view. This study establishes a theoretical model of the STIL system, with numerical simulations predicting limits of temporal and spatial resolutions of ~6 ps and 22.8 lp/mm, respectively. Dynamic simulations of laser backscatter signals from targets at varying depths demonstrate an optimal distance reconstruction accuracy of 98%. An experimental STIL platform was developed, with the key parameters calibrated as follows: scanning speed (16.78 ps/pixel), temporal resolution (14.47 ps), and central cathode spatial resolution (20 lp/mm). The system achieved target imaging through streak camera detection of azimuth-resolved intensity profiles, generating raw streak images. Feature extraction and neural network-based three-dimensional (3D) reconstruction algorithms enabled target reconstruction from the time-of-flight data of short laser pulses, achieving a minimum distance reconstruction error of 3.57%. Experimental results validate the capability of the system to detect fast, low-intensity optical signals while acquiring target range information, ultimately achieving high-frame-rate, high-resolution 3D imaging. These advancements position STIL technology as a promising solution for applications that require micron-scale depth discrimination under dynamic conditions. Full article

Visible Light Positioning (VLP), leveraging Light-Emitting Diodes (LEDs) and smartphone CMOS cameras, provides a high-precision solution for indoor localization. However, existing systems face challenges in accuracy, latency, and robustness due to line-of-sight (LOS) limitations and inefficient signal encoding. To overcome these constraints, this paper introduces a real-time VLP framework that integrates Multi-Pulse Position Modulation (MPPM) with smartphone multi-sensor fusion. By employing MPPM, a high-efficiency encoding scheme, the proposed system transmits LED identifiers (LED-IDs) with reduced inter-symbol interference, enabling robust signal detection even under dynamic lighting conditions and at extended distances. The smartphone’s camera is a receiver that decodes the MPPM-encoded LED-ID, while accelerometer and magnetometer data compensate for device orientation and motion-induced errors. Experimental results demonstrate that the MPPM-driven approach achieves a decoding success rate of over 97% at distances up to 2.4 m, while maintaining a frame processing rate of 30 FPS and sub-35 ms latency. Furthermore, the method reduces angular errors through sensor fusion, yielding 2D positioning accuracy below 10 cm and vertical errors under 16 cm across diverse smartphone orientations. The synergy of MPPM’s spectral efficiency and multi-sensor correction establishes a new benchmark for VLP systems, enabling scalable deployment in real-world environments without requiring complex infrastructure. Full article

Ultrahigh dose rate (UHDR) radiotherapy, also known as FLASH radiotherapy (FLASH-RT), has shown potential for increasing tumor control while sparing normal tissue. In parallel, gold nanoparticles (GNPs) have been extensively explored as radiosensitizers due to their high atomic number and ability to enhance the generation of reactive oxygen species (ROS) through water radiolysis. In this study, we investigate the synergistic effects of UHDR electron beams and GNP-mediated radiosensitization using Monte Carlo (MC) simulations based on the Geant4-DNA code. A spherical water phantom with embedded GNPs of varying sizes (5–100 nm) was irradiated using pulsed electron beams (100 keV and 1 MeV) at dose rates of 60, 100, and 150 Gy/s. The chemical yield of ROS near the GNPs was quantified and compared to an equivalent water nanoparticle model, and the yield enhancement factor (YEF) was used to evaluate radiosensitization. Results demonstrated that YEF increased with smaller GNP sizes and at lower UHDR, particularly for 1 MeV electrons. A maximum YEF of 1.25 was observed at 30 nm from the GNP surface for 5 nm particles at 60 Gy/s. The elevated ROS concentration near GNPs under FLASH conditions is expected to intensify DNA damage, especially double-strand breaks, due to increased hydroxyl radical interactions within nanometric distances of critical biomolecular targets. These findings highlight the significance of nanoparticle size and beam parameters in optimizing ROS production for FLASH-RT. The results provide a computational basis for future experimental investigations into the combined use of GNPs and UHDR beams in nanoparticle-enhanced radiotherapy. Full article

Laser-induced breakdown spectroscopy (LIBS) has been used to explore the chemistry of three regions of Mars on respective missions by NASA and CNSA, with CNES contributions. All three LIBS instruments use ~100 mm diameter telescopes projecting pulsed infrared laser beams of 10–14 mJ to enable LIBS at 2–10 m distances, eliminating the need to position the rover and instrument directly onto targets. Over 1.3 million LIBS spectra have been used to provide routine compositions for eight major elements and several minor and trace elements on >3000 targets on Mars. Onboard calibration targets common to all three instruments allow careful intercomparison of results. Operating over thirteen years, ChemCam on Curiosity has explored lacustrine sediments and diagenetic features in Gale crater, which was a long-lasting (>1 My) lake during Mars’ Hesperian period. SuperCam on Perseverance is exploring the ultramafic igneous floor, fluvial–deltaic features, and the rim of Jezero crater. MarSCoDe on the Zhurong rover investigated for one year the local blocks, soils, and transverse aeolian ridges of Utopia Planitia. The pioneering work of these three stand-off LIBS instruments paves the way for future space exploration with LIBS, where advantages of light-element (H, C, N, O) quantification can be used on icy regions. Full article

Robust maritime radar object detection and tracking in maritime clutter environments is critical for maritime safety and security. Conventional Constant False Alarm Rate (CFAR) detectors have limited performance in processing complex-valued radar echoes, especially in complex scenarios where phase information is critical and in the real-time processing of successive echo pulses, while existing deep learning methods usually lack native support for complex-valued data and have inherent shortcomings in real-time compared to conventional methods. To overcome these limitations, we propose a dual-branch sequence feature fusion (DFF) detector designed specifically for complex-valued continuous sea-clutter signals, drawing on commonly used methods in video pattern recognition. The DFF employs dual parallel complex-valued U-Net branches to extract multilevel spatiotemporal features from distance profiles and Doppler features from distance–Doppler spectrograms, preserving the critical phase–amplitude relationship. Subsequently, the sequential feature-extraction module (SFEM) captures the temporal dependence in both feature streams. Next, the Adaptive Weight Learning (AWL) module dynamically fuses these multimodal features by learning modality-specific weights. Finally, the detection module generates the object localisation output. Extensive evaluations on the IPIX and SDRDSP datasets show that DFF performs well. On SDRDSP, DFF achieves 98.76% accuracy and 68.75% in F1 score, which significantly outperforms traditional CFAR methods and state-of-the-art deep learning models in terms of detection accuracy and false alarm rate (FAR). These results validate the effectiveness of DFF for reliable maritime object detection in complex clutter environments through multimodal feature fusion and sequence-dependent modelling. Full article

For the pulsed data streams emitted by multiple signal sources that generate aliasing, traditional density clustering algorithms have the problems of poor clustering effect, heavy reliance on manual experience to set the parameters, and the need to carry out density clustering every time new data are input, resulting in a huge amount of computation. Therefore, an online density clustering algorithm based on the improved golden sine whale optimization is proposed. First, by adding new parameters to the density clustering algorithm, the neighborhood is changed from a single parameter Eps to a joint decision of the parameters Eps and $\theta$, which avoids cross-cluster expansion by more flexibly delimiting the neighborhood range. The improved golden sine whale optimization algorithm is then used to obtain the optimal parameter solution of the DBSCAN algorithm. Finally, the idea of flow clustering is introduced to determine whether a pulse belongs to a valid library, an outlier library, or an inactive library by comparing the distance between the input pulse and each cluster center, effectively reducing the number of pulses required for analysis. The experiment proves that the algorithm improves the sorting accuracy by 57.7% compared to the DBSCAN algorithm and 37.8% compared to the WOA-DBSCAN algorithm. Full article

Background: To evaluate and compare cardiorespiratory function, assessed by the 6-minute walk test (6MWT), and musculoskeletal function, assessed by the handgrip strength test and the sit-to-stand test (STS10) in post-coronavirus disease 2019 (COVID-19) patients. Participants were stratified based on the time since infection (≤6 months and >6 months) and compared with matched healthy controls. Methods: A total of 111 participants were recruited and divided into three groups (n = 37/group). Cardiorespiratory function was assessed using the 6MWT, while musculoskeletal function was evaluated through the handgrip strength test and the STS10. Results: All three groups had normal body mass index values. Group 2 demonstrated significantly lower handgrip strength and a shorter 6MWT distance compared to both Group 1 and Group 3. Additionally, Group 2 required significantly more time to complete the STS10 than Group 1. Following the 6MWT, Group 2 exhibited significantly higher heart rate and systolic blood pressure compared to both Group 1 and Group 3. Diastolic blood pressure was significantly lower in Group 3 compared to the other two groups. Furthermore, Group 2 had significantly lower pulse oxygen saturation than both Group 1 and Group 3. The rate of perceived exertion was significantly lower in Group 1 than in Group 2. Additionally, leg fatigue was significantly lower in Group 1 compared to both Group 2 and Group 3. Conclusions: These findings highlight significant differences in physical performance and physiological responses between post-COVID-19 patients and healthy individuals, emphasizing the potential long-term effects of SARS-CoV-2 infection on cardiorespiratory and musculoskeletal function. Full article

The Red River Jig is a traditional Métis dance practiced among Indigenous and non-Indigenous Peoples. While exercise improves physical health and fitness, the impacts of cultural dances on wholistic health are less clear. This study aimed to investigate the psychosocial (cultural and mental), social, physical function, and physical fitness benefits of a Red River Jig intervention. In partnership with Li Toneur Nimiyitoohk Métis Dance Group, Indigenous and non-Indigenous adults (N = 40, 39 ± 15 years, 32 females) completed an 8-week Red River Jig intervention. Social support, cultural identity, memory, and mental wellbeing questionnaires, seated blood pressure and heart rate, weight, pulse-wave velocity, heart rate variability, baroreceptor sensitivity, jump height, sit-and-reach flexibility, one-leg and tandem balance, and six-minute walk test were assessed pre- and post-intervention. Community, family, and friend support scores, six-minute walk distance (553.0 ± 88.7 m vs. 602.2 ± 138.6 m, p = 0.002), jump, leg power, and systolic blood pressure low-to-high-frequency ratio increased after the intervention. Ethnic identity remained the same while affirmation and belonging declined, leading to declines in overall cultural identity, as learning about Métis culture through the Red River Jig may highlight gaps in cultural knowledge. Seated systolic blood pressure (116.5 ± 7.3 mmHg vs. 112.5 ± 10.7 mmHg, p = 0.01) and lower peripheral pulse-wave velocity (10.0 ± 2.0 m·s⁻¹ vs. 9.4 ± 1.9 m·s⁻¹, p = 0.04) decreased after the intervention. Red River Jig dance training can improve social support, physical function, and physical fitness for Indigenous and non-Indigenous adults. Full article

To improve the accuracy of three-dimensional (3D) reconstruction under microscopic conditions for laser-induced breakdown spectroscopy (LIBS), this study developed a novel visual platform by integrating an industrial CCD camera with a microscope. A customized microscale calibration target was designed to calibrate intrinsic and extrinsic camera parameters accurately. Based on the pinhole imaging model, disparity maps were obtained via pixel matching to reconstruct high-precision 3D ablation morphology. A mathematical model was established to analyze how key imaging parameters—baseline distance, focal length, and depth of field—affect reconstruction accuracy in micro-imaging environments. Focusing on trace element detection in WC-Co alloy samples, the reconstructed ablation craters enabled the precise calculation of ablation volumes and revealed their correlations with laser parameters (energy, wavelength, pulse duration) and the physical-chemical properties of the samples. Multivariate regression analysis was employed to investigate how ablation morphology and plasma evolution jointly influence LIBS quantification. A nonlinear calibration model was proposed, significantly suppressing matrix effects, achieving R² = 0.987, and reducing RMSE to 0.1. This approach enhances micro-scale LIBS accuracy and provides a methodological reference for high-precision spectral analysis in environmental and materials applications. Full article

Mud pulse telemetry (MPT) systems are a promising approach to transmitting downhole data to the ground. During transmission, the amplitudes of pressure waves decay exponentially with distance, and the channel is often frequency-selective due to reflection and multipath effect. To address these issues, this work proposes a fractional Fourier transform (FrFT)-based channel estimation and equalization method. Leveraging the energy aggregation of linear frequency-modulated signals in the fractional Fourier domain, the time delay and attenuation parameters of the multipath channel can be estimated accurately. Furthermore, a fractional Fourier domain equalizer is proposed to pre-filter the frequency-selective fading channel using fractionally spaced decision feedback equalization. The effectiveness of the proposed method is evaluated through a simulation analysis and field experiments. The simulation results demonstrate that this method can significantly reduce multipath effects, effectively control the impact of noise, and facilitate subsequent demodulation. The field experiment results indicate that the demodulation of real data achieves advanced data rate communication (over 12 bit/s) and a low bit error rate (below 0.5%), which meets engineering requirements in a 3000 m drilling system. Full article

This study focuses on the analysis of soliton solutions within the framework of the time-fractional cubic–quintic nonlinear Schrödinger equation (TFCQ-NLSE), a powerful model with broad applications in complex physical phenomena such as fiber optic communications, nonlinear optics, optical signal processing, and laser–tissue interactions in medical science. The nonlinear effects exhibited by the model—such as self-focusing, self-phase modulation, and wave mixing—are influenced by the combined impact of the cubic and quintic nonlinear terms. To explore the dynamics of this model, we apply a robust analytical technique known as the sub-ODE method, which reveals a diverse range of soliton structures and offers deep insight into laser pulse interactions. The investigation yields a rich set of explicit soliton solutions, including hyperbolic, rational, singular, bright, Jacobian elliptic, Weierstrass elliptic, and periodic solutions. These waveforms have significant real-world relevance: bright solitons are employed in fiber optic communications for distortion-free long-distance data transmission, while both bright and dark solitons are used in nonlinear optics to study light behavior in media with intensity-dependent refractive indices. Solitons also contribute to advancements in quantum technologies, precision measurement, and fiber laser systems, where hyperbolic and periodic solitons facilitate stable, high-intensity pulse generation. Additionally, in nonlinear acoustics, solitons describe wave propagation in media where amplitude influences wave speed. Overall, this work highlights the theoretical depth and practical utility of soliton dynamics in fractional nonlinear systems. Full article