Shandong University of Science & Technology

Movie scene detection is challenging because it requires accurately measuring the relationship among shots to find scene boundaries. Most existing methods measure it based on similarity, which may result in the inability to distinguish between similar shots from different scenes and overlook the relationship between dissimilar shots within the same scene. In this paper, we propose a movie scene detection method based on Clue Relationship and Constrained Shot Description (CRCSD) to address the above challenges. First, we propose self-clue and entangled-clue, and rebalance the relationship among shots through clue relevance (CR) to distinguish similar shots from different scenes and bridge dissimilar shots in the same scene. We utilize the information of an entire clue rather than discrete shots for movie scene detection, which is more in line with human thinking habits. Second, we propose Shotboard, which adds constraints with metadata and shot properties to generate descriptions of shots from the camera's perspective. A BEncoder is used to extract board features of these shot descriptions, thereby establishing latent associations across shots, which can further alleviate the above challenges. Finally, we build two modal clue graphs, transfer weights between graphs, and propagate messages within graphs to learn shot features with clue context to identify the ending shot of a scene. Experiments on multiple public datasets show that our method can significantly improve the performance of movie scene detection. For example, we improve the Average Precision (AP) by 5.5% on the MovieNet dataset. The code is available at https://github.com/KJWQYY/CRCSD.

Sulfadiazine (SDZ), a kind of emerging contaminants, is highly enriched in the environment, posing serious risks to ecosystems and human health. Studies have shown that cytochrome P450 enzymes (CYPs) can degrade SDZ, but the detailed degradation mechanism remains unclear, and the degradation efficiency needs improvement. This study uses dynamic simulations, quantum mechanics/molecular mechanics methods and density functional theory to investigate the degradation mechanism and pathways of SDZ catalyzed by CYP120A1. The mechanisms involved in the hydrogen abstraction reaction are hydrogen atom transfer (HAT) and proton-coupled electron transfer (PCET), with the enzyme environment tend to inhibit the HAT reaction but promote the PCET reaction. Hydroxyl rebound and Smiles rearrangement are the rate-determining steps for the two mechanisms, respectively. Intrinsic electric field promotes hydroxyl rebound but interferes Smiles rearrangement. Residues THR258A and VAL318A are key amino acids in the reaction mechanism. This work aims to improve the degradation mechanism of emerging contaminants like sulfonamides, contributing to a better understanding of their environmental transformation process and providing theoretical support for developing green bioremediation technologies for emerging contaminants.

The commercialization of lithium‑sulfur (Li-S) batteries are limited by the high catalytic conversion barriers and severe shuttle effect of soluble lithium polysulfides (LiPSs). Herein, we well-design and prepare a metal-organic framework nanoarray of nickel-hexaiminotriphenylene grown vertically on carbon nanotubes (Ni-HTP/CNTs) to serve host catalyst in Li-S batteries. Carbon nanotubes not only provide a three-dimensional conductive network, but also enables epitaxial growth of Ni-HTP, resulting in massive exposed Ni-N₄ active sites. The obtained Ni-HTP/CNTs exhibit strong electronic interactions between Ni-HTP and CNTs, which induce electronic rearrangements and optimize the d-orbital energy levels. This unique nanostructure/electronic structure synergistically enhances the adsorption capacity and catalytic conversion efficiency of LiPSs, as well as promotes the nucleation/decomposition kinetics of Li₂S upon charging and discharging. As a result, the assembled Li-S battery with Ni-HTP/CNTs@S cathode delivers high initial discharge capacity of 1520 mAh g^-1 and stable cycle performance with a capacity decay of only 0.042 % per cycle near 900 cycles. This work provides new perspectives for the design of metal-organic frameworks-based host for advanced Li-S batteries and beyond.