arXiv subjects

Yu Dai

Publications and source records attributed to Yu Dai.

At least 37 records · Page 2Linked to original sources

arXiv2024

Enhanced Peak and Extended Cooling of the Extreme-ultraviolet Late Phase in a Confined Solar Flare

We present observations and analysis of an X1.8 non-eruptive solar flare on 2012 October 23, which is characterized by an extremely large late-phase peak seen in the warm coronal extreme-ultraviolet (EUV) emissions ($\sim$ 3 MK), with the peak intensity over 1.4 times that of main flare peak. The flare is driven by a failed eruption of a magnetic flux rope (MFR), whose strong squeeze force acting on the overlying magnetic structures gives rise to an intense early heating of the late-phase loops. Based on differential emission measure (DEM) analysis, it is found that the late-phase loops experience a "longer-than-expected" cooling without the presence of any obvious additional heating, and meanwhile, their volume emission measure (EM) maintains a plateau level for a long time before turning into an evident decay. Without the need for an additional heating, we propose that the special thermodynamic evolution of the late-phase loops revealed in this flare might arise from loop cross-sectional expansions with height, which are evidenced by both direct measurements from EUV images and by magnetic field extrapolation. By blocking the losses of both heat flux and mass from the corona, such an upward cross-sectional expansion not only elongates the loop cooling time, but also more effectively sustains the loop density, therefore leading to a later-than-expected occurrence of the warm coronal late phase in combination with a sufficiently high late-phase peak. We further verify such a scenario by analytically solving the cooling process of a late-phase loop characterized by a variable cross section.

astro-ph.SR↗

arXiv2024

PSFHS Challenge Report: Pubic Symphysis and Fetal Head Segmentation from Intrapartum Ultrasound Images

Segmentation of the fetal and maternal structures, particularly intrapartum ultrasound imaging as advocated by the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) for monitoring labor progression, is a crucial first step for quantitative diagnosis and clinical decision-making. This requires specialized analysis by obstetrics professionals, in a task that i) is highly time- and cost-consuming and ii) often yields inconsistent results. The utility of automatic segmentation algorithms for biometry has been proven, though existing results remain suboptimal. To push forward advancements in this area, the Grand Challenge on Pubic Symphysis-Fetal Head Segmentation (PSFHS) was held alongside the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). This challenge aimed to enhance the development of automatic segmentation algorithms at an international scale, providing the largest dataset to date with 5,101 intrapartum ultrasound images collected from two ultrasound machines across three hospitals from two institutions. The scientific community's enthusiastic participation led to the selection of the top 8 out of 179 entries from 193 registrants in the initial phase to proceed to the competition's second stage. These algorithms have elevated the state-of-the-art in automatic PSFHS from intrapartum ultrasound images. A thorough analysis of the results pinpointed ongoing challenges in the field and outlined recommendations for future work. The top solutions and the complete dataset remain publicly available, fostering further advancements in automatic segmentation and biometry for intrapartum ultrasound imaging.

eess.IV↗

arXiv2024

NOEMA formIng Cluster survEy (NICE): Characterizing eight massive galaxy groups at $1.5 < z < 4$ in the COSMOS field

The NOEMA formIng Cluster survEy (NICE) is a large program targeting 69 massive galaxy group candidates at $z>2$ in six deep fields. We report spectroscopic confirmation of eight groups at $1.65\leq z\leq3.61$ in COSMOS. Homogeneously selected as significant overdensities of red IRAC sources with red Herschel colors, four groups are confirmed by CO and [CI] with NOEMA 3mm observations, three are confirmed with ALMA, and one is confirmed by H$α$ from Subaru/FMOS. We constructed the integrated FIR SEDs for the eight groups, obtaining total IR SFR $=260-1300~{\rm M_\odot}$~yr$^{-1}$. We adopted six methods to estimate the dark matter masses, including stellar mass to halo mass relations, overdensity with galaxy bias, and NFW profile fitting to radial stellar mass density. We found the radial stellar mass density are consistent with a NFW profile, supporting that they are collapsed structures hosted by a single dark matter halo. The best halo mass estimates are $\log(M_{\rm h}/{\rm M_\odot})=12.8-13.7$ with uncertainty of 0.3 dex. From halo mass estimates, we derive baryonic accretion rate ${\rm BAR}=(1-8)\times10^{3}\,{\rm M_{\odot}/yr}$ for this sample. We find a quasi-linear correlation between the integrated SFR/BAR and the theoretical halo mass limit for cold streams, $M_{\rm stream}/M_{\rm h}$, with ${\rm SFR/BAR}=10^{-0.46\pm0.22}\left({M_{\rm stream}/M_{\rm h}}\right)^{0.71\pm0.16}$ with a scatter of $0.40\,{\rm dex}$. Further, we compare halo masses and stellar masses with simulations, and find all structures are consistent with being progenitors of $M_{\rm h}(z=0)>10^{14}\,{\rm M_{\odot}}$ galaxy clusters, and the most massive central galaxies have stellar masses consistent with brightest cluster galaxies (BCGs) progenitors in the TNG300 simulation. The results strongly suggest these structures are forming massive galaxy clusters via baryonic and dark matter accretion.

astro-ph.GA↗

arXiv2024

Noema formIng Cluster survEy (NICE): Discovery of a starbursting galaxy group with a radio-luminous core at z=3.95

The study of distant galaxy groups and clusters at the peak epoch of star formation is limited by the lack of a statistically and homogeneously selected and spectroscopically confirmed sample. Recent discoveries of concentrated starburst activities in cluster cores have opened a new window to hunt for these structures based on their integrated IR luminosities. Hereby we carry out the large NOEMA (NOrthern Extended Millimeter Array) program targeting a statistical sample of infrared-luminous sources associated with overdensities of massive galaxies at z>2, the Noema formIng Cluster survEy (NICE). We present the first result from the ongoing NICE survey, a compact group at z=3.95 in the Lockman Hole field (LH-SBC3), confirmed via four massive (M_star>10^10.5M_sun) galaxies detected in CO(4-3) and [CI](1-0) lines. The four CO-detected members of LH-SBC3 are distributed over a 180 kpc physical scale, and the entire structure has an estimated halo mass of ~10^13Msun and total star formation rate (SFR) of ~4000Msun/yr. In addition, the most massive galaxy hosts a radio-loud AGN with L_1.4GHz, rest = 3.0*10^25W/Hz. The discovery of LH-SBC3 demonstrates the feasibility of our method to efficiently identify high-z compact groups or forming cluster cores. The existence of these starbursting cluster cores up to z~4 provides critical insights into the mass assembly history of the central massive galaxies in clusters.

astro-ph.GA↗

arXiv2024

A model for heating the super-hot corona in solar active regions

What physical mechanisms heat the outer solar or stellar atmosphere to million-Kelvin temperatures is a fundamental but long-standing open question. In particular, the solar corona in active region cores contains an even hotter component reaching ten million Kelvin, manifesting as persistent coronal loops in extreme ultraviolet and soft X-ray images, which imposes a more stringent energy budget. Here, we present a self-consistent coronal heating model using a state-of-the-art three-dimensional radiative magnetohydrodynamics simulation. We find that the continuous magnetic flux emergence in active regions keeps driving magnetic reconnections that release energy impulsively but, on time average, persistently. As a result, numerous sub-structures are heated to ten million Kelvin and then evolve independently, which collectively form long-lived and stable coronal loops as in observations. This provides a heating model explaining the origin of the super-hot coronal plasma and the persistence of hot coronal loops in emerging active regions.

astro-ph.SR↗

arXiv2024

Slightly Shift New Classes to Remember Old Classes for Video Class-Incremental Learning

Recent video class-incremental learning usually excessively pursues the accuracy of the newly seen classes and relies on memory sets to mitigate catastrophic forgetting of the old classes. However, limited storage only allows storing a few representative videos. So we propose SNRO, which slightly shifts the features of new classes to remember old classes. Specifically, SNRO contains Examples Sparse(ES) and Early Break(EB). ES decimates at a lower sample rate to build memory sets and uses interpolation to align those sparse frames in the future. By this, SNRO stores more examples under the same memory consumption and forces the model to focus on low-semantic features which are harder to be forgotten. EB terminates the training at a small epoch, preventing the model from overstretching into the high-semantic space of the current task. Experiments on UCF101, HMDB51, and UESTC-MMEA-CL datasets show that SNRO performs better than other approaches while consuming the same memory consumption.

cs.CV↗

arXiv2024

ESKNet-An enhanced adaptive selection kernel convolution for breast tumors segmentation

Breast cancer is one of the common cancers that endanger the health of women globally. Accurate target lesion segmentation is essential for early clinical intervention and postoperative follow-up. Recently, many convolutional neural networks (CNNs) have been proposed to segment breast tumors from ultrasound images. However, the complex ultrasound pattern and the variable tumor shape and size bring challenges to the accurate segmentation of the breast lesion. Motivated by the selective kernel convolution, we introduce an enhanced selective kernel convolution for breast tumor segmentation, which integrates multiple feature map region representations and adaptively recalibrates the weights of these feature map regions from the channel and spatial dimensions. This region recalibration strategy enables the network to focus more on high-contributing region features and mitigate the perturbation of less useful regions. Finally, the enhanced selective kernel convolution is integrated into U-net with deep supervision constraints to adaptively capture the robust representation of breast tumors. Extensive experiments with twelve state-of-the-art deep learning segmentation methods on three public breast ultrasound datasets demonstrate that our method has a more competitive segmentation performance in breast ultrasound images.

eess.IV↗

arXiv2024

Enhanced α particle generation via proton-boron fusion reactions in laser-modulated plasma

Aneutronic and nonradioactive properties make the proton-boron fusion a prospective candidate for fusion energy production through reactions following p+$^{11}$B$\rightarrow$3$α$ (p-$^{11}$B). However, it is difficult to achieve a thermal fusion ignition, since the low reaction cross-sections for center-of-mass energy below $\sim$100 keV. To realize fusion energy gain, it is essential to consider utilization of the maximum cross-section at the resonant peak of p-$^{11}$B fusion, and explore the nuclear reactions in plasma environment. In this work, p-$^{11}$B reactions triggered by interactions between energetic proton beams and laser-ablated boron plasma have been investigated. More than 200 times enhancement of $α$ particle emission efficiency (number ratio of escaping $α$ particles and boron nuclei) in plasma has been observed, compared with the cold boron. The proton beam transport path modulated by strong electro-magnetic fields in plasma could dominate the enhanced $α$ particle generation, due to a longer collisional length. In addition, an $α$ particle yield up to 1$\times$10$^{10}$ /sr has been measured via the pitcher-catcher scheme in plasma. This work could benefit understanding of the plasma effects on nuclear reaction dynamics, and also enable opportunities to explore physics in laser fusion associated with advanced fusion fuels.

physics.plasm-ph↗

arXiv2023

Observations of a Failed Solar Filament Eruption Involving External Reconnection

We report a failed solar filament eruption that involves external magnetic reconnection in a quadrupolar magnetic configuration. The evolution exhibits three kinematic evolution phases: a slow-rise phase, an acceleration phase, and a deceleration phase. In the early slow rise, extreme-ultraviolet (EUV) brightenings appear at the expected null point above the filament and are connected to the outer polarities by the hot loops, indicating the occurrence of a breakout reconnection. Subsequently, the filament is accelerated outward, accompanied by the formation of low-lying high-temperature post-flare loops ($>$ 15 MK), complying with the standard flare model. However, after 2--3 minutes, the erupting filament starts to decelerate and is finally confined in the corona. The important finding is that the confinement is closely related to an external reconnection as evidenced by the formation of high-lying large-scale hot loops ($>$ 10 MK) with their brightened footpoints at the outer polarities, the filament fragmentation and subsequent falling along the newly formed large-scale loops, as well as a hard X-ray source close to one of the outer footpoint brightenings. We propose that, even though the initial breakout reconnection and subsequent flare reconnection commence and accelerate the filament eruption, the following external reconnection between the erupting flux rope and overlying field, as driven by the upward filament eruption, makes the eruption finally failed, as validated by the numerical simulation of a failed flux rope eruption.

astro-ph.SR↗

arXiv2023

An Atypical Plateau-like Extreme-ultraviolet Late-phase Solar Flare Driven by the Non-radial Eruption of a Magnetic Flux Rope

Recent observations in extreme-ultraviolet (EUV) wavelengths reveal an EUV late phase in some solar flares, which is characterized by a second peak in the warm coronal emissions (about 3 MK) occurring several tens of minutes to a few hours after the corresponding main flare peak. We aim to clarify the physical origin of an atypical plateau-like EUV late phase in an X1.8-class solar flare occurring on 2011 September 7 from active region (AR) 11283. We first characterize the plateau-like late phase using EUV Variability Experiment (EVE) full-disk integrated irradiance observations and Atmospheric Imaging Assembly (AIA) spatially-resolved imaging observations on board the Solar Dynamics Observatory (SDO). Then we perform a nonlinear force-free-field (NLFFF) extrapolation, from which a filament-hosting magnetic flux rope (MFR) is revealed. The eruption of the MFR is tracked both in the plane of the sky (POS) and along the line of sight (LOS) through visual inspection and spectral fitting, respectively. Finally, we carry out differential emission measure (DEM) analysis to explore the thermodynamics of the late-phase loops. The MFR shows a non-radial eruption from a fan-spine magnetic structure. The eruption of the MFR and its interaction with overlying arcades invoke multiple magnetic reconnections, which are responsible for the production of different groups of late-phase loops. Afterwards, the late-phase loops enter a long-lasting cooling stage, appearing sequentially in AIA passbands of decreasing response temperatures. Due to their different lengths, the different groups of late-phase loops cool down at different cooling rates, which makes their warm coronal emission peaks temporally separated from each other. Combing the emissions from all late-phase loops together, an elongated plateau-like late phase is formed.

astro-ph.SR↗

arXiv2023

Towards Continual Egocentric Activity Recognition: A Multi-modal Egocentric Activity Dataset for Continual Learning

With the rapid development of wearable cameras, a massive collection of egocentric video for first-person visual perception becomes available. Using egocentric videos to predict first-person activity faces many challenges, including limited field of view, occlusions, and unstable motions. Observing that sensor data from wearable devices facilitates human activity recognition, multi-modal activity recognition is attracting increasing attention. However, the deficiency of related dataset hinders the development of multi-modal deep learning for egocentric activity recognition. Nowadays, deep learning in real world has led to a focus on continual learning that often suffers from catastrophic forgetting. But the catastrophic forgetting problem for egocentric activity recognition, especially in the context of multiple modalities, remains unexplored due to unavailability of dataset. In order to assist this research, we present a multi-modal egocentric activity dataset for continual learning named UESTC-MMEA-CL, which is collected by self-developed glasses integrating a first-person camera and wearable sensors. It contains synchronized data of videos, accelerometers, and gyroscopes, for 32 types of daily activities, performed by 10 participants. Its class types and scale are compared with other publicly available datasets. The statistical analysis of the sensor data is given to show the auxiliary effects for different behaviors. And results of egocentric activity recognition are reported when using separately, and jointly, three modalities: RGB, acceleration, and gyroscope, on a base network architecture. To explore the catastrophic forgetting in continual learning tasks, four baseline methods are extensively evaluated with different multi-modal combinations. We hope the UESTC-MMEA-CL can promote future studies on continual learning for first-person activity recognition in wearable applications.

cs.CV↗

arXiv2022

Rethinking the Unpretentious U-net for Medical Ultrasound Image Segmentation

Breast tumor segmentation is one of the key steps that helps us characterize and localize tumor regions. However, variable tumor morphology, blurred boundary, and similar intensity distributions bring challenges for accurate segmentation of breast tumors. Recently, many U-net variants have been proposed and widely used for breast tumors segmentation. However, these architectures suffer from two limitations: (1) Ignoring the characterize ability of the benchmark networks, and (2) Introducing extra complex operations increases the difficulty of understanding and reproducing the network. To alleviate these challenges, this paper proposes a simple yet powerful nested U-net (NU-net) for accurate segmentation of breast tumors. The key idea is to utilize U-Nets with different depths and shared weights to achieve robust characterization of breast tumors. NU-net mainly has the following advantages: (1) Improving network adaptability and robustness to breast tumors with different scales, (2) This method is easy to reproduce and execute, and (3) The extra operations increase network parameters without significantly increasing computational cost. Extensive experimental results with twelve state-of-the-art segmentation methods on three public breast ultrasound datasets demonstrate that NU-net has more competitive segmentation performance on breast tumors. Furthermore, the robustness of NU-net is further illustrated on the segmentation of renal ultrasound images. The source code is publicly available on https://github.com/CGPzy/NU-net.

eess.IV↗

arXiv2022

AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultrasound Images

Various deep learning methods have been proposed to segment breast lesion from ultrasound images. However, similar intensity distributions, variable tumor morphology and blurred boundaries present challenges for breast lesions segmentation, especially for malignant tumors with irregular shapes. Considering the complexity of ultrasound images, we develop an adaptive attention U-net (AAU-net) to segment breast lesions automatically and stably from ultrasound images. Specifically, we introduce a hybrid adaptive attention module, which mainly consists of a channel self-attention block and a spatial self-attention block, to replace the traditional convolution operation. Compared with the conventional convolution operation, the design of the hybrid adaptive attention module can help us capture more features under different receptive fields. Different from existing attention mechanisms, the hybrid adaptive attention module can guide the network to adaptively select more robust representation in channel and space dimensions to cope with more complex breast lesions segmentation. Extensive experiments with several state-of-the-art deep learning segmentation methods on three public breast ultrasound datasets show that our method has better performance on breast lesion segmentation. Furthermore, robustness analysis and external experiments demonstrate that our proposed AAU-net has better generalization performance on the segmentation of breast lesions. Moreover, the hybrid adaptive attention module can be flexibly applied to existing network frameworks.

eess.IV↗

arXiv2022

Calibration procedures for the CHASE/HIS science data

The Hα line is an important optical line in solar observations containing the information from the photosphere to the chromosphere. To study the mechanisms of solar eruptions and the plasma dynamics in the lower atmosphere, the Chinese Hα Solar Explorer (CHASE) was launched into a Sun-synchronous orbit on October 14, 2021. The scientific payload of the CHASE satellite is the Hα Imaging Spectrograph (HIS). The CHASE/HIS acquires, for the first time, seeing-free Hα spectroscopic observations with high spectral and temporal resolutions. It consists of two observational modes. The raster scanning mode provides full-Sun or region-of-interest spectra at Hα (6559.7-6565.9 Å) and Fe I (6567.8-6570.6 Å) wavebands. The continuum imaging mode obtains full-Sun photospheric images at around 6689 Å. In this paper, we present detailed calibration procedures for the CHASE/HIS science data, including the dark-field and flat-field correction, slit image curvature correction, wavelength and intensity calibration, and coordinate transformation. The higher-level data products can be directly used for scientific research.

astro-ph.SR↗

arXiv2022

BAGNet: Bidirectional Aware Guidance Network for Malignant Breast lesions Segmentation

Breast lesions segmentation is an important step of computer-aided diagnosis system, and it has attracted much attention. However, accurate segmentation of malignant breast lesions is a challenging task due to the effects of heterogeneous structure and similar intensity distributions. In this paper, a novel bidirectional aware guidance network (BAGNet) is proposed to segment the malignant lesion from breast ultrasound images. Specifically, the bidirectional aware guidance network is used to capture the context between global (low-level) and local (high-level) features from the input coarse saliency map. The introduction of the global feature map can reduce the interference of surrounding tissue (background) on the lesion regions. To evaluate the segmentation performance of the network, we compared with several state-of-the-art medical image segmentation methods on the public breast ultrasound dataset using six commonly used evaluation metrics. Extensive experimental results indicate that our method achieves the most competitive segmentation results on malignant breast ultrasound images.

eess.IV↗

arXiv2019

Extreme-ultraviolet Late Phase Caused by Magnetic Reconnection over Quadrupolar Magnetic Configuration in a Solar Flare

A second emission enhancement in warm coronal extreme-ultraviolet (EUV) lines (about 2-7 MK) during some solar flares is known as the EUV late phase. Imaging observations confirm that the late phase emission originates from a set of longer or higher loops than the main flare loops. Nevertheless, some questions remain controversial: What is the relationship between these two loop systems? What is the heating source of late phase emission, a heating accompany the main phase heating or occuring quite later? In this paper, we present clear evidence for heating source in a late-phase solar flare: magnetic reconnection of overlying field in a quadrupolar magnetic configuration. The event is triggered by an erupted core structure that eventually leads to a coronal mass ejection (CME). Cusp feature and its shrinkage motion high in the late-phase emission region are the manifestation of the later phase reconnection following the main flare reconnection. Using the enthalpy-based thermal evolution of loops (EBTEL) model, we reasonably reproduce the late-phase emissions in some EUV lines. We suggest that a continuous additional heating is responsible for the appearance of the elongated EUV late phase.

astro-ph.SR↗

arXiv2018

Extremely Large Extreme-ultraviolet Late Phase Powered by Intense Early Heating in a Non-eruptive Solar Flare

We analyzed and modeled an M1.2 non-eruptive solar flare on 2011 September 9. The flare exhibits a strong late-phase peak of the warm coronal emissions ($\sim$3~MK) of extreme-ultraviolet (EUV), with peak emission over 1.3 times that of the main flare peak. Multiple flare ribbons are observed, whose evolution indicates a two-stage energy release process. A non-linear force-free field (NLFFF) extrapolation reveals the existence of a magnetic null point, a fan-spine structure, and two flux ropes embedded in the fan dome. Magnetic reconnections involved in the flare are driven by the destabilization and rise of one of the flux ropes. In the first stage, the fast ascending flux rope drives reconnections at the null point and the surrounding quasi-separatrix layer (QSL), while in the second stage, reconnection mainly occurs between the two legs of the field lines stretched by the eventually stopped flux rope. The late-phase loops are mainly produced by the first-stage QSL reconnection, while the second-stage reconnection is responsible for the heating of main flaring loops. The first-stage reconnection is believed to be more powerful, leading to an extremely strong EUV late phase. We find that the delayed occurrence of the late-phase peak is mainly due to the long cooling process of the long late-phase loops. Using the model enthalpy-based thermal evolution of loops (EBTEL), we model the EUV emissions from a late-phase loop. The modeling reveals a peak heating rate of 1.1~erg~cm$^{-3}$~s$^{-1}$ for the late-phase loop, which is obviously higher than previous values.

astro-ph.SR↗

arXiv2018

Probing the Production of Extreme-ultraviolet Late-Phase Solar Flares by Using the Model Enthalpy-Based Thermal Evolution of Loops

Recent observations in extreme-ultraviolet (EUV) wavelengths reveal an EUV late phase in some solar flares that is characterized by a second peak in warm coronal emissions ($\sim3$~MK) several tens of minutes to a few hours after the soft X-ray (SXR) peak. Using the model enthalpy-based thermal evolution of loops (EBTEL), in this paper we numerically probe the production of EUV late-phase solar flares. Starting from two main mechanisms of producing the EUV late phase, i.e., long-lasting cooling and secondary heating, we carry out two groups of numerical experiments to study the effects of these two processes on the emission characteristics in late-phase loops. In either of the two processes an EUV late-phase solar flare that conforms to the observational criteria can be numerically synthesized. However, the underlying hydrodynamic and thermodynamic evolutions in late-phase loops are different between the two synthetic flare cases. The late-phase peak due to a long-lasting cooling process always occurs during the radiative cooling phase, while that powered by a secondary heating is more likely to take place in the conductive cooling phase. We then propose a new method for diagnosing the two mechanisms based on the shape of EUV late-phase light curves. Moreover, from the partition of energy input, we discuss why most solar flares are not EUV late flares. Finally, by addressing some other factors that may potentially affect the loop emissions, we also discuss why the EUV late phase is mainly observed in warm coronal emissions.

astro-ph.SR↗