ZS-SRT: An Efficient Zero-Shot Super-Resolution Training Method for Neural Radiance Fields

Neural Radiance Fields (NeRF) have achieved great success in the task of synthesizing novel views that preserve the same resolution as the training views. However, it is challenging for NeRF to synthesize high-quality high-resolution novel views with low-resolution training data. To solve this problem, we propose a zero-shot super-resolution training framework for NeRF. This framework aims to guide the NeRF model to synthesize high-resolution novel views via single-scene internal learning rather than requiring any external high-resolution training data. Our approach consists of two stages. First, we learn a scene-specific degradation mapping by performing internal learning on a pretrained low-resolution coarse NeRF. Second, we optimize a super-resolution fine NeRF by conducting inverse rendering with our mapping function so as to backpropagate the gradients from low-resolution 2D space into the super-resolution 3D sampling space. Then, we further introduce a temporal ensemble strategy in the inference phase to compensate for the scene estimation errors. Our method is featured on two points: (1) it does not consume high-resolution views or additional scene data to train super-resolution NeRF; (2) it can speed up the training process by adopting a coarse-to-fine strategy. By conducting extensive experiments on public datasets, we have qualitatively and quantitatively demonstrated the effectiveness of our method

High-frequency ultrasound combined with shear wave elastography to evaluate the efficacy of lymphaticovenular anastomosis in patients with secondary lymphedema

PurposeHigh-frequency ultrasound combined with shear wave elastography (SWE) was used to evaluate the efficacy of lymphaticovenular anastomosis (LVA) in treating secondary lymphedema.Materials and methodsThis study included 40 patients with secondary lymphedema who underwent LVA at the Department of Vascular Surgery, Henan Provincial People's Hospital, from October 2023 to October 2024. Limb circumference measurements, bioelectrical impedance analysis (BIA), and high-frequency ultrasound combined with SWE were conducted before and after treatment. Changes in subcutaneous echo-free space (SEFS) grading and elastic parameters were analyzed pre- and post-treatment.ResultsFollowing LVA, the percentage of excess volume (PEV) and the extracellular water/total body water (ECW/TBW) ratio in the affected limb significantly decreased (P < 0.001). SEFS scores of the subcutaneous tissue also showed statistically significant changes (P < 0.001). Additionally, the shear wave velocity (SWV) of the dermis decreased, while that of the subcutaneous tissue layer increased, both with statistical significance (P < 0.001). The difference in SEFS scores between pre- and post-treatment was statistically significant (P < 0.001), supporting the finding that SWV decreased in the dermis and increased in the subcutaneous tissue layer (P < 0.001).ConclusionThe reduction in SEFS in the affected limb after LVA, along with the decreased SWV in the dermis and increased SWV in the subcutaneous tissue layer, suggests that LVA effectively reduces lymphatic fluid retention across all tissue layers. This provides novel ultrasonographic evidence for assessing and refining treatment efficacy and follow-up

LEO Satellite Downlink Distributed Jamming Optimization Method Using a Non-Dominated Sorting Genetic Algorithm

Due to their low orbit, low-Earth-orbit (LEO) satellites possess advantages such as minimal transmission delay, low link loss, flexible deployment, diverse application scenarios, and low manufacturing costs. Moreover, by increasing the number of satellites, the system capacity can be enhanced, making them the core of future communication systems. However, there have been instances where malicious actors used LEO satellite communication equipment to illegally broadcast events in large sports stadiums or engage in unauthorized leakage of military secrets in sensitive military areas. This has become an urgent issue in the field of communication security. To combat and prevent abnormal and illegal communication activities using LEO satellites, this study proposes a LEO satellite downlink distributed jamming optimization method using a non-dominated sorting genetic algorithm. Firstly, a distributed jamming system model for the LEO satellite downlink is established. Then, using a non-dominated sorting genetic algorithm, the jamming parameters are optimized in the power, time, and frequency domains. Field jamming experiments were conducted in the southwest outskirts of Xi’an, China, targeting the LEO constellation of the China Satellite Network. The results indicate that under the condition that the jamming coverage rate is no less than 90%, the proposed method maximizes jamming power, minimizes time delay, and minimizes frequency compensation compared to existing jamming optimization methods, effectively improving the real-time jamming performance and success rate