Enhanced cosmic-ray antihelium production from dark matter annihilation through light mediators

Cosmic-ray (CR) antihelium is an important probe for the indirect search of dark matter (DM) annihilation in the Galaxy. However, due to stringent constraints from the measurements of CR antiprotons and $\gamma$-rays, the flux of CR antihelium from the conventional DM direct annihilation into Standard Model final states is expected to be far below the sensitivity of the current experiments. We show that the production of antihelium can be significantly enhanced if the DM particles annihilate through light mediator particles with a mass $m_\phi \approx 8$ GeV close to the antihelium production threshold. After taking into account the constraints from the AMS-02 antiproton data and the Fermi-LAT $\gamma$-ray data on the spheroidal dwarf galaxies, we find that in this scenario the CR antihelium flux can be enhanced by three orders of magnitude, which makes it within the sensitivity of the ongoing AMS-02 experiment.Comment: 20 pages, 5 figures, 3 table

Theoretical Systematics of Future Baryon Acoustic Oscillation Surveys

Future Baryon Acoustic Oscillation surveys aim at observing galaxy clustering over a wide range of redshift and galaxy populations at great precision, reaching tenths of a percent, in order to detect any deviation of dark energy from the \LCDM model. We utilize a set of paired quasi-\Nb\, FastPM simulations that were designed to mitigate the sample variance effect on the BAO feature and evaluated the BAO systematics as precisely as $\sim 0.01\%$. We report anisotropic BAO scale shifts before and after density field reconstruction in the presence of redshift-space distortions over a wide range of redshift, galaxy/halo biases, and shot noise levels. We test different reconstruction schemes and different smoothing filter scales, and introduce physically-motivated BAO fitting models. For the first time, we derive a Galilean-invariant infrared resummed model for halos in real and redshift space. We test these models from the perspective of robust BAO measurements and non-BAO information such as growth rate and nonlinear bias. We find that pre-reconstruction BAO scale has moderate fitting-model dependence at the level of $0.1\%-0.2\%$ for matter while the dependence is substantially reduced to less than $0.07\%$ for halos. We find that post-reconstruction BAO shifts are generally reduced to below $0.1\%$ in the presence of galaxy/halo bias and show much smaller fitting model dependence. Different reconstruction conventions can potentially make a much larger difference on the line-of-sight BAO scale, upto $0.3\%$. Meanwhile, the precision (error) of the BAO measurements is quite consistent regardless of the choice of the fitting model or reconstruction convention.Comment: 33 pages, 19 figures, 4 tables. Submitted to MNRAS. Matches version accepted to MNRAS. Moderate changes were made during revision including a comparison between TreePM and FastPM BAO featur

A selective pretreatment method for determination of endogenous active brassinosteroids in plant tissues: double layered solid phase extraction combined with boronate affinity polymer monolith microextraction

BACKGROUND: Brassinosteriods (BRs), a group of important phytohormones, have various effects on plant growth and development. However, their physiological functions in plants have not been fully understood to date. Endogenous BRs in plant tissue are extremely low and the elucidation of BRs functions relies on sensitive detection method. Reported methods for the determination of BRs required large amount of plant tissue, tedious pretreatment process, and were lack of selectivity. Therefore, development of a simple and selective method for the sensitive quantification of BRs is highly needed. RESULTS: We established a pretreatment method of BRs in plant tissues by employing double layered solid phase extraction (DL/SPE) combined with boronate affinity polymer monolith microextraction (BA/PMME). After the initial depigmentation with DL/SPE cartridge, BA/PMME was employed to selectively extract BRs from sample matrix. Uniquely, most sample matrix was successfully removed by BA monolith purification. Using this method, BRs was determined by liquid chromatography-mass spectrometry (LC-MS). Endogenous active BRs could be detected in only 1 g fresh weigh (FW) leaves or 0.5 g FW flower tissues. CONCLUSION: A DL/SPE-BA/PMME pretreatment method for the determination of endogenous brassinosteroids in plant tissues was developed and validated. The proposed method was sensitive and selective. Besides, it may be further developed for the determination of other BRs including their precursors and conjugates

Multi-modal Facial Affective Analysis based on Masked Autoencoder

Human affective behavior analysis focuses on analyzing human expressions or other behaviors to enhance the understanding of human psychology. The CVPR 2023 Competition on Affective Behavior Analysis in-the-wild (ABAW) is dedicated to providing high-quality and large-scale Aff-wild2 for the recognition of commonly used emotion representations, such as Action Units (AU), basic expression categories(EXPR), and Valence-Arousal (VA). The competition is committed to making significant strides in improving the accuracy and practicality of affective analysis research in real-world scenarios. In this paper, we introduce our submission to the CVPR 2023: ABAW5. Our approach involves several key components. First, we utilize the visual information from a Masked Autoencoder(MAE) model that has been pre-trained on a large-scale face image dataset in a self-supervised manner. Next, we finetune the MAE encoder on the image frames from the Aff-wild2 for AU, EXPR and VA tasks, which can be regarded as a static and uni-modal training. Additionally, we leverage the multi-modal and temporal information from the videos and implement a transformer-based framework to fuse the multi-modal features. Our approach achieves impressive results in the ABAW5 competition, with an average F1 score of 55.49\% and 41.21\% in the AU and EXPR tracks, respectively, and an average CCC of 0.6372 in the VA track. Our approach ranks first in the EXPR and AU tracks, and second in the VA track. Extensive quantitative experiments and ablation studies demonstrate the effectiveness of our proposed method