CLIP-based Synergistic Knowledge Transfer for Text-based Person Retrieval

Text-based Person Retrieval (TPR) aims to retrieve the target person images given a textual query. The primary challenge lies in bridging the substantial gap between vision and language modalities, especially when dealing with limited large-scale datasets. In this paper, we introduce a CLIP-based Synergistic Knowledge Transfer (CSKT) approach for TPR. Specifically, to explore the CLIP's knowledge on input side, we first propose a Bidirectional Prompts Transferring (BPT) module constructed by text-to-image and image-to-text bidirectional prompts and coupling projections. Secondly, Dual Adapters Transferring (DAT) is designed to transfer knowledge on output side of Multi-Head Attention (MHA) in vision and language. This synergistic two-way collaborative mechanism promotes the early-stage feature fusion and efficiently exploits the existing knowledge of CLIP. CSKT outperforms the state-of-the-art approaches across three benchmark datasets when the training parameters merely account for 7.4% of the entire model, demonstrating its remarkable efficiency, effectiveness and generalization.Comment: ICASSP2024(accepted). minor typos revision compared to version 1 in arxi

Asymptotic stability for nn-dimensional isentropic compressible MHD equations without magnetic diffusion

Whether the global well-posedness of strong solutions of $n$-dimensional compressible isentropic magnetohydrodynamic (MHD for short) equations without magnetic diffusion holds true or not remains an challenging open problem, even for the small initial data. In recent years, stared from the pioneer work by Wu and Wu [Adv. Math. 310 (2017), 759--888], much more attention has been paid to the system when the magnetic field near an equilibrium state (the background magnetic field for short). In particular, when the background magnetic field satisfies the Diophantine condition (see (1.3) for details), Wu and Zhai [Math. Models Methods Appl. Sci. 33 (2023), no. 13, 2629--2656] established the decay estimates and asymptotic stability for smooth solutions of the 3D compressible isentropic MHD system without magnetic diffusion in $H^{4r+7}(\mathbb{T}^3)$ with $r>2$ by exploiting a wave structure. In this paper, a new dissipative mechanism is found out and applied so that we can improve the spaces where the decay estimates and asymptotic stability of solutions are taking place by Wu and Zhai. More precisely, we establish the decay estimates of solutions in $H^{r+1}(\mathbb{T}^n)$ and asymptotic stability result in $H^{\left(3r+3\right)^+}(\mathbb{T}^n)$ for any dimensional periodic domain $\mathbb{T}^n$ with $n\geq 2$ and $r>n-1$. Our results provide an approach for establishing the decay estimates and asymptotic stability in the Sobolev spaces with much lower regularity and uniform dimension, which can be used to study many other related models such as the compressible non-isentropic MHD system without magnetic diffusion and so on.Comment: 39 page

Study on the relationship between bitterness and taste intensity of beverages using dynamic sensory evaluation

十文字学園女子大学博士（栄養学）令和5年度doctoral thesi

Sharp decay estimates and asymptotic stability for incompressible MHD equations without viscosity or magnetic diffusion

Whether the global existence and uniqueness of strong solutions of $n$-dimensional incompressible magnetohydrodynamic (MHD for short) equations with only kinematic viscosity or magnetic diffusion holds true or not remains an outstanding open problem. In recent years, more attention has been paid to the case when the magnetic field close to an equilibrium state (the background magnetic field for short). Specifically, when the background magnetic field satisfies the Diophantine condition (see (1.2) for details), Chen, Zhang and Zhou [Sci. China Math. 41 (2022), pp.1-10] first studied the perturbation system and established the decay estimates and stability of its solutions in 3D periodic domain $\mathbb{T}^3$, which was then improved to $H^{(3+2\beta)r+5+(\alpha+2\beta)}(\mathbb{T}^2)$ for 2D periodic domain $\mathbb{T}^2$ and any $\alpha>0$, $\beta>0$ by Zhai [J. Differ. Equ. 374 (2023), pp.267-278]. In this paper, we seek to find the optimal decay estimates and improve the space where the global stability is taking place. Through deeply exploring and fully utilizing the structure of perturbation system, we discover a new dissipative mechanism, which enables us to establish the decay estimates in Sobolev space with much lower regularity. Based on the above discovery, we greatly reduce the initial regularity requirement of aforementioned two works from $H^{4r+7}(\mathbb{T}^3)$ and $H^{(3+2\beta)r+5+(\alpha+2\beta)}(\mathbb{T}^2)$ to $H^{(3r+3)^+}(\mathbb{T}^n)$ for $r>n-1$ when $n=3$ and $n=2$ respectively. Additionally, we first present the linear stability result via the method of spectral analysis in this paper. From which, the decay estimates obtained for the nonlinear system can be seen as sharp in the sense that they are in line with those for the linearized system.Comment: 24 page

water resource allocation for the Songhua River Region, China under the uncertainty of water supply

<span class="MedBlackText">Water resources allocation (WRA) is a useful and yet complicated topic in water resources management. The solution of WRA may be uncertain due to the uncertainty of the input, the structure itself, and the parameters of the models. So far, very few studies deal with the topic about how much these uncertainties influence the solution and how to adapt the situation. By using Dependent-Chance Goal Programming (DCGP), this paper built a WRA under the uncertainty of water supply for the Songhua River Region (SHRR) located in the northeast of China, one of China's most important commercial grain bases. Two sets of WRA results were obtained under the two ranges of uncertainty relative to bad (S1) and good (S2) water supply situations. Situation SI takes a higher water shortage rate and S2 takes a lower water shortage rate than the routine WRA results by the SHRR Commission's comprehensive plan, but all keeping the rate of water resources exploitation approaching or lower than the international standards. The result helps SHRR to make a more resilient decision to the change of water supply condition in meeting the national needs of Newly Increasing Yield of 10 &times; 10¹¹ Jin. </span

ShuffleMix: Improving Representations via Channel-Wise Shuffle of Interpolated Hidden States

Mixup style data augmentation algorithms have been widely adopted in various tasks as implicit network regularization on representation learning to improve model generalization, which can be achieved by a linear interpolation of labeled samples in input or feature space as well as target space. Inspired by good robustness of alternative dropout strategies against over-fitting on limited patterns of training samples, this paper introduces a novel concept of ShuffleMix -- Shuffle of Mixed hidden features, which can be interpreted as a kind of dropout operation in feature space. Specifically, our ShuffleMix method favors a simple linear shuffle of randomly selected feature channels for feature mixup in-between training samples to leverage semantic interpolated supervision signals, which can be extended to a generalized shuffle operation via additionally combining linear interpolations of intra-channel features. Compared to its direct competitor of feature augmentation -- the Manifold Mixup, the proposed ShuffleMix can gain superior generalization, owing to imposing more flexible and smooth constraints on generating samples and achieving regularization effects of channel-wise feature dropout. Experimental results on several public benchmarking datasets of single-label and multi-label visual classification tasks can confirm the effectiveness of our method on consistently improving representations over the state-of-the-art mixup augmentation

Differential Expression Levels of Genes Related to Myogenesis During Embryogenesis of Quail and Chicken

The present study was designed to investigate the expression dynamics of genes during myogenesis in quail and chicken. Real-time PCR was used to detect mRNA expressions of MyoD, MyoG, MLP and MSTN in breast muscle of quail and chicken embryos during the period of embryonic days E7-17. Results showed that expression profiles of each gene displayed similar trend in the experiment period between quail and chicken, however, the expression concentration between the two species differed at the same time detected. MyoD mRNA expression in quail was significantly lower in the early phase of the experiment period (E7-9) (P<0.01 on E7; P<0.05 on both E8 and E9). For MyoG and MLP, the mRNA expressions were both lower in quail than that in chicken during the experiment period. Additionally, the embryonic day when quail reached its peak expression was earlier than that in chicken (MyoG: quail E12 vs. chicken E13; MLP: quail E14 vs. chicken E15), and the peak expression for both in quail was significantly lower than that in chicken (P<0.01 for both). For MSTN, expression in quail was significantly higher in quail than that in chicken at each time detected (P<0.01). It is concluded that differential expression of these genes might or at least partially contributed to the different development of muscle development in quail and chicken

Capture and sorting of multiple cells by polarization-controlled three-beam interference

For the capture and sorting of multiple cells, a sensitive and highly efficient polarization-controlled three-beam interference set-up has been developed. With the theory of superposition of three beams, simulations on the influence of polarization angle upon the intensity distribution and the laser gradient force change with different polarization angles have been carried out. By controlling the polarization angle of the beams, various intensity distributions and different sizes of dots are obtained. We have experimentally observed multiple optical tweezers and the sorting of cells with different polarization angles, which are in accordance with the theoretical analysis. The experimental results have shown that the polarization angle affects the shapes and feature sizes of the interference patterns and the trapping force

Random Walk on Multiple Networks

Random Walk is a basic algorithm to explore the structure of networks, which can be used in many tasks, such as local community detection and network embedding. Existing random walk methods are based on single networks that contain limited information. In contrast, real data often contain entities with different types or/and from different sources, which are comprehensive and can be better modeled by multiple networks. To take advantage of rich information in multiple networks and make better inferences on entities, in this study, we propose random walk on multiple networks, RWM. RWM is flexible and supports both multiplex networks and general multiple networks, which may form many-to-many node mappings between networks. RWM sends a random walker on each network to obtain the local proximity (i.e., node visiting probabilities) w.r.t. the starting nodes. Walkers with similar visiting probabilities reinforce each other. We theoretically analyze the convergence properties of RWM. Two approximation methods with theoretical performance guarantees are proposed for efficient computation. We apply RWM in link prediction, network embedding, and local community detection. Comprehensive experiments conducted on both synthetic and real-world datasets demonstrate the effectiveness and efficiency of RWM.Comment: Accepted to IEEE TKD