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This paper focuses on the scale imbalance problem of semi-supervised object detection(SSOD) in aerial images. Compared to natural images, objects in aerial images show smaller sizes and larger quantities per image, increasing the difficulty of manual annotation. Meanwhile, the advanced SSOD technique can train superior detectors by leveraging limited labeled data and massive unlabeled data, saving annotation costs. However, as an understudied task in aerial images, SSOD suffers from a drastic performance drop when facing a large proportion of small objects. By analyzing the predictions between small and large objects, we identify three imbalance issues caused by the scale bias, i.e., pseudo-label imbalance, label assignment imbalance, and negative learning imbalance. To tackle these issues, we propose a novel Scale-discriminative Semi-Supervised Object Detection (S^3OD) learning pipeline for aerial images. In our S^3OD, three key components, Size-aware Adaptive Thresholding (SAT), Size-rebalanced Label Assignment (SLA), and Teacher-guided Negative Learning (TNL), are proposed to warrant scale unbiased learning. Specifically, SAT adaptively selects appropriate thresholds to filter pseudo-labels for objects at different scales. SLA balances positive samples of objects at different scales through resampling and reweighting. TNL alleviates the imbalance in negative samples by leveraging information generated by a teacher model. Extensive experiments conducted on the DOTA-v1.5 benchmark demonstrate the superiority of our proposed methods over state-of-the-art competitors. Codes will be released soon.

The early afterglow of a Gamma-ray burst (GRB) can provide critical information on the jet and progenitor of the GRB. The extreme brightness of GRB 221009A allows us to probe its early afterglow in unprecedented detail. In this letter, we report comprehensive observation results of the early afterglow of GRB 221009A (from $T_0$+660 s to $T_0$+1860 s, where $T_0$ is the \textit{Insight}-HXMT/HE trigger time) in X/$\gamma$-ray energy band (from 20 keV to 20 MeV) by \textit{Insight}-HXMT/HE, GECAM-C and \textit{Fermi}/GBM. We find that the spectrum of the early afterglow in 20 keV-20 MeV could be well described by a cutoff power-law with an extra power-law which dominates the low and high energy bands respectively. The cutoff power-law $E_{\rm peak}$ is $\sim$ 30 keV and the power-law photon index is $\sim$ 1.8 throughout the early afterglow phase. By fitting the light curves in different energy bands, we find that a significant achromatic break (from keV to TeV) is required at $T_0$ + 1246$^{+27}_{-26}$ s (i.e. 1021 s since the afterglow starting time $T_{\rm AG}$=$T_0$+225 s), providing compelling evidence of a jet break. Interestingly, both the pre-break and post-break decay slopes vary with energy, and these two slopes become closer in the lower energy band, making the break less identifiable. Intriguingly, the spectrum of the early afterglow experienced a slight hardening before the break and a softening after the break. These results provide new insights into the understanding of this remarkable GRB., Comment: Accepted for publication in ApJ Letters on 19-Jan-2024, 11 pages, 7 figures and 2 tables

Advancements in sensor technology, artificial intelligence (AI), and augmented reality (AR) have unlocked opportunities across various domains. AR and large language models like GPT have witnessed substantial progress and are increasingly being employed in diverse fields. One such promising application is in operations and maintenance (O&M). O&M tasks often involve complex procedures and sequences that can be challenging to memorize and execute correctly, particularly for novices or under high-stress situations. By marrying the advantages of superimposing virtual objects onto the physical world, and generating human-like text using GPT, we can revolutionize O&M operations. This study introduces a system that combines AR, Optical Character Recognition (OCR), and the GPT language model to optimize user performance while offering trustworthy interactions and alleviating workload in O&M tasks. This system provides an interactive virtual environment controlled by the Unity game engine, facilitating a seamless interaction between virtual and physical realities. A case study (N=15) is conducted to illustrate the findings and answer the research questions. The results indicate that users can complete similarly challenging tasks in less time using our proposed AR and AI system. Moreover, the collected data also suggests a reduction in cognitive load and an increase in trust when executing the same operations using the AR and AI system., Comment: 36 pages

GRB 221009A is the brightest gamma-ray burst ever detected since the discovery of this kind of energetic explosions. However, an accurate measurement of the prompt emission properties of this burst is very challenging due to its exceptional brightness. With joint observations of \textit{Insight}-HXMT and GECAM-C, we made an unprecedentedly accurate measurement of the emission during the first $\sim$1800 s of GRB 221009A, including its precursor, main emission (ME, which dominates the burst in flux), flaring emission and early afterglow, in the hard X-ray to soft gamma-ray band from $\sim$ 10 keV to $\sim$ 6 MeV. Based on the GECAM-C unsaturated data of the ME, we measure a record-breaking isotropic equivalent energy ($E_{\rm iso}$) of $\bf \sim 1.5 \times 10^{55}$ erg, which is about eight times the total rest-mass energy of the Sun. The early afterglow data require a significant jet break between 650 s and 1100 s, most likely at $\sim950$ s from the afterglow starting time $T_{AG}$, which corresponds to a jet opening angle of $\sim {0.7^\circ} \ (\eta_\gamma n)^{1/8}$, where $n$ is the ambient medium density in units of $\rm cm^{-3}$ and $\eta_\gamma$ is the ratio between $\gamma$-ray energy and afterglow kinetic energy. The beaming-corrected total $\gamma$-ray energy $E_{\gamma}$ is $\sim 1.15 \times10^{51} \ (\eta_\gamma n)^{1/4}$ erg, which is typical for long GRBs. These results suggest that this GRB may have a special central engine, which could launch and collimate a very narrowly beamed jet with an ordinary energy budget, leading to exceptionally luminous gamma-ray radiation per unit solid angle. Alternatively, more GRBs might have such a narrow and bright beam, which are missed by an unfavorable viewing angle or have been detected without distance measurement., Comment: Submitted to National Science Review. This paper is under press embargo, contact the corresponding author for details

Purpose: We present the five-year in-orbit background evolution of Insight-HXMT since the launch, as well as the effects of the background model in data analysis. Methods: The backgrounds of the three main payloads, i.e., Low-Energy Telescope, Medium-Energy Telescope and High-Energy Telescope, are described, respectively. The evolution of the background over time is obtained by simply comparing the background in every year during the in-orbit operation of Insight-HXMT. Results: The major observational characteristics of the Insight-HXMT in-orbit background are presented, including the light curve, spectrum, geographical distribution, and long-term evolution. The systematic error in background estimation is investigated for every year. Conclusion: The observational characteristics of the five-year in-orbit background are consistent with our knowledge of the satellite design and the space environment, and the background model is still valid for the latest observations of Insight-HXMT., Comment: 22 pages, 25 figures, accepted for publication in RDTM

Many new physics scenarios beyond the Standard Model (BSM) necessitate the existence of new neutral and/or charged scalar fields, which might couple to the SM charged leptons (but not hadrons), and thus, can give rise to BSM signals while evading strong constraints mostly coming from the hadronic sector. I show that future lepton colliders provide a clean environment to probe these leptophilic new scalars via multi-lepton final states, including some interesting lepton flavor violating (LFV) channels. I also study the kinematic distributions of the final state leptons to distinguish the BSM contributions from neutral and doubly-charged scalars giving rise to the same final state, as well as from the irreducible SM background.

Purpose: The High-Energy X-ray telescope (HE), one of the three main payloads of the \textit{Insight}-HXMT mission, is composed of eighteen NaI(Tl)/CsI(Na) phoswich detectors, where NaI(Tl) serves as the primary detector covering 20--250\,keV, and CsI(Na) is used as an active shield detector to suppress the background of NaI(Tl) and also serves as an all-sky gamma-ray burst monitor covering 0.2--3\,MeV. In this paper, we review the in-orbit performance of HE in the first 5 years since \textit{Insight}-HXMT was launched on June 15, 2017. Methods: The major performances we concern include the gain and energy resolution of NaI(Tl) and CsI(Na) detectors, the performance of pulse-shape-discriminator (PSD) and system dead-time. In this work, we investigate these performances mainly using the data of blank-sky observations and the data when the telescope in earth occultation. Results: The overall performance of HE/NaI(Tl) is very stable in the first 5 years, whereas the gain of HE/CsI(Na) shows a continuously increasing trend and should be calibrated regularly. Conclusion: In general, HE is still in good health and well-calibrated status after five-year's operation. The in-orbit performance of HE has no significant deviation from expectation. HE is expected to be in operation healthily for another several years of extended mission life., Comment: 19 pages, 16 figures, Accepted by Insight-HXMT special issue on RDTM

In this paper, we introduce Planet-CR, a benchmark dataset for high-resolution cloud removal with multi-modal and multi-resolution data fusion. Planet-CR is the first public dataset for cloud removal to feature globally sampled high resolution optical observations, in combination with paired radar measurements as well as pixel-level land cover annotations. It provides solid basis for exhaustive evaluation in terms of generating visually pleasing textures and semantically meaningful structures. With this dataset, we consider the problem of cloud removal in high resolution optical remote sensing imagery by integrating multi-modal and multi-resolution information. Existing multi-modal data fusion based methods, which assume the image pairs are aligned pixel-to-pixel, are hence not appropriate for this problem. To this end, we design a new baseline named Align-CR to perform the low-resolution SAR image guided high-resolution optical image cloud removal. It implicitly aligns the multi-modal and multi-resolution data during the reconstruction process to promote the cloud removal performance. The experimental results demonstrate that the proposed Align-CR method gives the best performance in both visual recovery quality and semantic recovery quality. The project is available at https://github.com/zhu-xlab/Planet-CR, and hope this will inspire future research.

The longstanding muon $(g-2)$ anomaly, as well as the persistent hints of lepton flavor universality violation in $B$-meson decays, could be signaling new physics beyond the Standard Model (SM). A minimal $R$-parity-violating supersymmetric framework with light third-generation sfermions (dubbed as 'RPV3') provides a compelling solution to these flavor anomalies, while simultaneously addressing other pressing issues of the SM. We propose a new RPV3 scenario for the solution of the muon $(g-2)$ anomaly, which leads to an interesting LHC signal of $\mu^+\mu^-\tau^+\tau^-$ final state. We analyze the Run-2 LHC multilepton data to derive stringent constraints on the sneutrino mass and the relevant RPV coupling in this scenario. We then propose dedicated selection strategies to improve the bound even with the existing dataset. We also show that the high-luminosity LHC will completely cover the remaining muon $(g-2)$-preferred parameter space, thus providing a robust, independent test of the muon $(g-2)$ anomaly., Comment: 13 pages, 5 figures; version to appear in Phys. Lett. B