Mutual Information-driven Triple Interaction Network for Efficient Image Dehazing

Multi-stage architectures have exhibited efficacy in image dehazing, which usually decomposes a challenging task into multiple more tractable sub-tasks and progressively estimates latent hazy-free images. Despite the remarkable progress, existing methods still suffer from the following shortcomings: (1) limited exploration of frequency domain information; (2) insufficient information interaction; (3) severe feature redundancy. To remedy these issues, we propose a novel Mutual Information-driven Triple interaction Network (MITNet) based on spatial-frequency dual domain information and two-stage architecture. To be specific, the first stage, named amplitude-guided haze removal, aims to recover the amplitude spectrum of the hazy images for haze removal. And the second stage, named phase-guided structure refined, devotes to learning the transformation and refinement of the phase spectrum. To facilitate the information exchange between two stages, an Adaptive Triple Interaction Module (ATIM) is developed to simultaneously aggregate cross-domain, cross-scale, and cross-stage features, where the fused features are further used to generate content-adaptive dynamic filters so that applying them to enhance global context representation. In addition, we impose the mutual information minimization constraint on paired scale encoder and decoder features from both stages. Such an operation can effectively reduce information redundancy and enhance cross-stage feature complementarity. Extensive experiments on multiple public datasets exhibit that our MITNet performs superior performance with lower model complexity.The code and models are available at https://github.com/it-hao/MITNet.Comment: Accepted in ACM MM 202

Adaptive Dynamic Filtering Network for Image Denoising

In image denoising networks, feature scaling is widely used to enlarge the receptive field size and reduce computational costs. This practice, however, also leads to the loss of high-frequency information and fails to consider within-scale characteristics. Recently, dynamic convolution has exhibited powerful capabilities in processing high-frequency information (e.g., edges, corners, textures), but previous works lack sufficient spatial contextual information in filter generation. To alleviate these issues, we propose to employ dynamic convolution to improve the learning of high-frequency and multi-scale features. Specifically, we design a spatially enhanced kernel generation (SEKG) module to improve dynamic convolution, enabling the learning of spatial context information with a very low computational complexity. Based on the SEKG module, we propose a dynamic convolution block (DCB) and a multi-scale dynamic convolution block (MDCB). The former enhances the high-frequency information via dynamic convolution and preserves low-frequency information via skip connections. The latter utilizes shared adaptive dynamic kernels and the idea of dilated convolution to achieve efficient multi-scale feature extraction. The proposed multi-dimension feature integration (MFI) mechanism further fuses the multi-scale features, providing precise and contextually enriched feature representations. Finally, we build an efficient denoising network with the proposed DCB and MDCB, named ADFNet. It achieves better performance with low computational complexity on real-world and synthetic Gaussian noisy datasets. The source code is available at https://github.com/it-hao/ADFNet.Comment: 9 pages, Accepted in AAAI Conference on Artificial Intelligence (AAAI) 202

(R P,R P)-Bis[(3-menthyloxy)(phenyl)­phosphino­yl] disulfide

The molecule of the title compound, C32H48O4P2S2, has 2 symmetry, the mid-point of the S—S bond being located on a twofold rotation axis. The two tetra­hedral P units are linked by a S—S bond with a P—S—S—P torsion angle is 131.19 (6)°. The dihedral angle between two phenyl rings is 12.66 (13)°. The cyclo­hexane ring of the menthoxyl group displays a chair conformation. Weak inter­molecular C—H⋯O hydrogen bonding is present in the crystal structure

Time scales of epidemic spread and risk perception on adaptive networks

Incorporating dynamic contact networks and delayed awareness into a contagion model with memory, we study the spreading patterns of infectious diseases in connected populations. It is found that the spread of an infectious disease is not only related to the past exposures of an individual to the infected but also to the time scales of risk perception reflected in the social network adaptation. The epidemic threshold $p_{c}$ is found to decrease with the rise of the time scale parameter s and the memory length T, they satisfy the equation $p_{c} =\frac{1}{T}+ \frac{\omega T}{a^s(1-e^{-\omega T^2/a^s})}$. Both the lifetime of the epidemic and the topological property of the evolved network are considered. The standard deviation $\sigma_{d}$ of the degree distribution increases with the rise of the absorbing time $t_{c}$, a power-law relation $\sigma_{d}=mt_{c}^\gamma$ is found

Recent Advances in Flame Retardant and Mechanical Properties of Polylactic Acid: A Review.

The large-scale application of ecofriendly polymeric materials has become a key focus of scientific research with the trend toward sustainable development. Mechanical properties and fire safety are two critical considerations of biopolymers for large-scale applications. Polylactic acid (PLA) is a flammable, melt-drop carrying, and strong but brittle polymer. Hence, it is essential to achieve both flame retardancy and mechanical enhancement to improve safety and broaden its application. This study reviews the recent research on the flame retardant functionalization and mechanical reinforcement of PLA. It classifies PLA according to the type of the flame retardant strategy employed, such as surface-modified fibers, modified nano/micro fillers, small-molecule and macromolecular flame retardants, flame retardants with fibers or polymers, and chain extension or crosslinking with other flame retardants. The functionalization strategies and main parameters of the modified PLA systems are summarized and analyzed. This study summarizes the latest advances in the fields of flame retardancy and mechanical reinforcement of PLA.pre-print3656 K