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Xiaoyu Yu

Publications and source records attributed to Xiaoyu Yu.

8 recordsLinked to original sources

Heterogeneous SAR-optical fusion for near-real-time land use and land cover mapping under cloud contamination: A novel framework and global benchmark dataset

Optical remote sensing imagery is frequently degraded by cloud and cloud-shadow contamination, which limits its reliability for near-real-time land use and land cover (LULC) mapping. Although synthetic aperture radar (SAR) can provide cloud-penetrating structural information, existing SAR-optical fusion methods often assume reliable optical observations and insufficiently address the semantic uncertainty introduced by cloud contamination. To address this issue, we propose CloudLULC-Net, an end-to-end heterogeneous SAR-optical fusion framework that directly predicts LULC maps from cloud-contaminated Sentinel-2 imagery and temporally adjacent Sentinel-1 SAR observations. The proposed network incorporates optical reliability modulation to suppress unreliable optical responses, heterogeneous information adaptive aggregation to model high-order spatial-channel interactions between optical and SAR representations, and a unified semantic mapping transformer to organize fused features in a LULC-oriented latent space. A semantic anchor-guided optimization strategy is further introduced to improve the consistency of intermediate semantic representations. To support this task, we construct CloudLULC-Set, a large-scale benchmark dataset containing 40,223 curated SAR-optical-label triplets with pixel-level LULC annotations across diverse geographic regions and cloud conditions. Experimental results show that CloudLULC-Net achieves an OA of 86.60%, an F1-score of 83.29%, and an mIoU of 73.51%, outperforming representative heterogeneous reconstruction-first and end-to-end SAR-optical mapping methods. Comparisons with existing global LULC products and analyses under different cloud-cover levels further demonstrate the robustness and practical value of CloudLULC-Net for target-date LULC mapping in cloud-prone regions.The project is publicly available at: https://github.com/RSIIPAC/CloudLULC

cs.CV

Coherent Turning Behaviors Revealed Across Adherent Cells

Adherent cells have long been known to display two modes during migration: a faster mode that is persistent in direction and a slower one where they turn. Compared to the persistent mode, the turns are less studied. Here we develop a simple yet effective protocol to isolate the turns quantitatively. With the protocol, we study different adherent cells in different morphological states and find that, during turns, the cells behave as rotors with constant turning rates but random turning directions. To perform tactic motion, the cells bias the sign of turning towards the stimuli. Our results clarify the bimodal kinematics of adherent cell migration. Compared to the rotational-diffusion-based turning dynamics - which has been widely implemented, our data reveal a distinct picture, where turns are governed by a deterministic angular velocity.

physics.bio-ph

Prototypical Few-Shot Medical Image Semantic Segmentation with Background Fusion

Few-shot Semantic Segmentation (FSS) aims to adapt a pre-trained model to new classes with as few as a single labeled training sample per class. The existing prototypical work used in natural image scenarios biasedly focus on capturing foreground's discrimination while employing a simplistic representation for background, grounded on the inherent observation separation between foreground and background. However, a frequency spectrum entropy analysis suggests that this paradigm is not applicable to medical images where the foreground and background share numerous visual features, necessitating a more detailed description for the background. In this paper, we present a new Background-fused prototype (Bro) approach for FSS in medical images. Instead of identifying a commonality of background subjects in the support image, Bro fuses this background to discriminative prototypes, with two pivot designs. Specifically, Feature Similarity Calibration (FeaC) initially reduces noise in the support image by employing feature cross-attention with the query image. Subsequently, Hierarchical Channel-Adversarial Attention (HiCA) merges the background into comprehensive prototypes. We achieve this by a channel groups-based attention mechanism, where an adversarial Mean-Offset structure encourages a coarse-to-fine fusion. Designed as a generic plug-in, our Bro can be seamlessly integrated with existing FSS models. Extensive experiments validate the specificity of the background in medical images and the efficacy of Bro in enhancing the performance of previous FSS models on standard benchmarks.

cs.CV

The Mechanism of Magnetic Flux Rope Rotation During Solar Eruption

Solar eruptions often show the rotation of filaments, which is a manifestation of the rotation of erupting magnetic flux rope (MFR). Such a rotation of MFR can be induced by either the torque exerted by a background shear-field component (which is an external cause) or the relaxation of the magnetic twist of the MFR (an internal cause). For a given chirality of the erupting field, both the external and internal drivers cause the same rotation direction. Therefore, it remains elusive from direct observations which mechanism yields the dominant contribution to the rotation. In this paper, we exploit a full MHD simulation of solar eruption by tether-cutting magnetic reconnection to study the mechanism of MFR rotation. In the simulation, the MFR's height-rotation profile suggests that the force by the external shear-field component is a dominant contributor to the rotation. Furthermore, the torque analysis confirms that it is also the only factor in driving the counterclockwise rotation. On the contrary, the Lorentz torque inside the MFR makes a negative effect on this counterclockwise rotation.

astro-ph.SR

GRB 220408B: A Three-Episode Burst from a Precessing Jet

Jet precession has previously been proposed to explain the apparently repeating features in the light curves of a few gamma-ray bursts (GRBs). In this {\it Letter}, we further apply the precession model to a bright GRB 220408B by examining both its temporal and spectral consistency with the predictions of the model. As one of the recently confirmed GRBs observed by our GRID CubeSat mission, GRB 220408B is noteworthy as it exhibits three apparently similar emission episodes. Furthermore, the similarities are reinforced by their strong temporal correlations and similar features in terms of spectral evolution and spectral lags. Our analysis demonstrates that these features can be well explained by the modulated emission of a Fast-Rise-Exponential-Decay (FRED) shape light curve intrinsically produced by a precessing jet with a precession period of $18.4 \pm 0.2$ seconds, a nutation period of $11.1 \pm 0.2$ seconds and viewed off-axis. This study provides a straightforward explanation for the complex yet similar multi-episode GRB light curves.

astro-ph.HE

Resolving Two Distinct Thermal X-ray Components in A compound Solar Flare

X-ray emission provides the most direct diagnostics of the energy-release process in solar flares. Occasionally, a superhot X-ray source is found to be above hot flare loops of ~10 MK temperature. While the origin of the superhot plasma is still elusive, it has conjured up an intriguing image of in-situ plasma heating near the reconnection site high above the flare loops, in contrast to the conventional picture of chromospheric evaporation. Here we investigate an extremely long-duration solar flare, in which EUV images show two distinct flare loop systems that appear successively along a Gamma-shaped polarity inversion line (PIL). When both flare loop systems are present, the HXR spectrum is found to be well fitted by combining a hot component (Te ~12 MK) and a superhot component (Te ~30 MK). Associated with a fast CME, the superhot X-ray source is located at top of the flare arcade that appears earlier, straddling and extending along the long "arm" of the Gamma-shaped PIL. Associated with a slow CME, the hot X-ray source is located at the top of the flare arcade that appears later and sits astride the short "arm" of the Gamma-shaped PIL. Aided by observations from a different viewing angle, we are able to verify that the superhot X-ray source is above the hot one in projection, but the two sources belong to different flare loop systems. Thus, this case study provides a stereoscopic observation explaining the co-existence of superhot and hot X-ray emitting plasmas in solar flares.

astro-ph.SR

Regulation of interferon production as a potential strategy for COVID-19 treatment

Regulating the upstream of the cytokines production could be a promising strategy to the treatment of COVID-19. We suggest to pay more attention to the dysregulated IFN-I production in COVID-19 and to considerate cGAS, ALK and STING as potential therapeutic targets preventing cytokine storm. Approved drugs like suramin and ALK inhibitors are worthy of clinical trials.

q-bio.MN

A Data-Center FPGA Acceleration Platform for Convolutional Neural Networks

Intensive computation is entering data centers with multiple workloads of deep learning. To balance the compute efficiency, performance, and total cost of ownership (TCO), the use of a field-programmable gate array (FPGA) with reconfigurable logic provides an acceptable acceleration capacity and is compatible with diverse computation-sensitive tasks in the cloud. In this paper, we develop an FPGA acceleration platform that leverages a unified framework architecture for general-purpose convolutional neural network (CNN) inference acceleration at a data center. To overcome the computation bound, 4,096 DSPs are assembled and shaped as supertile units (SUs) for different types of convolution, which provide up to 4.2 TOP/s 16-bit fixed-point performance at 500 MHz. The interleaved-task-dispatching method is proposed to map the computation across the SUs, and the memory bound is solved by a dispatching-assembling buffering model and broadcast caches. For various non-convolution operators, a filter processing unit is designed for general-purpose filter-like/pointwise operators. In the experiment, the performances of CNN models running on server-class CPUs, a GPU, and an FPGA are compared. The results show that our design achieves the best FPGA peak performance and a throughput at the same level as that of the state-of-the-art GPU in data centers, with more than 50 times lower latency.

cs.CV