Ke Zhong

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie et autres

Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high-throughput density functional theory (DFT) and interpretable machine …

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Ai-Fen Solid Dispersions: Preparation, Characterization, and Enhanced Therapeutic Efficacy in a Rat Model of Oral Ulceration

Bingnan Liu, Kailang Mu, He Meng, Yuchen Liu et autres

Background/Objectives: Recurrent oral ulceration (ROU) is the most prevalent disorder of the oral mucosa, affecting approximately 20% of the global population. Current therapies are limited by adverse effects and high recurrence rates. Ai-Fen, enriched in the anti-inflammatory monoterpenoid L-borneol (54.3% w/w), exhibits …

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Discovery of 8-quinolinesulfonamide phenylimidazole-based PKM2 agonists for the prevention and delay of aortic dissection

Junda Li, Yanyan Yang, Lei Cheng, Xu Xu et autres

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Mechanistic study of soot reduction in Fe-MOFs modified alcohol-based fuel based on optical experiments and BO-GPR predictive modeling

Mingzhang Pan, Ke Zhong, Yuede Pan, Yu Xie et autres

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Synthesis and anti-breast cancer evaluation of new bakuchiol derivatives

Hongmei Li, Jing Zhu, Ke Zhong, Jie Chen et autres

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Emission prediction of diesel /n-hexanol blended fuels with graphene oxide addition based on ITCN-TSO model

Yuede Pan, Changcheng Fu, Jinkai Gu, Ke Zhong et autres

A Review of Hybrid Vehicles Classification and Their Energy Management Strategies: An Exploration of the Advantages of Genetic Algorithms

Y. Pan, Ke Zhong, Yu Xie, Wei Guan et autres

This paper presents a comprehensive analysis of hybrid electric vehicle (HEV) classification and energy management strategies (EMS), with a particular emphasis on the application and potential of genetic algorithms (GAs) in optimizing energy management strategies for hybrid electric vehicles. Initially, the paper …

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Terahertz Reconfigurable Planar Graphene Hybrid Yagi–Uda Antenna

Qimeng Liu, Renbin Zhong, Boli Xu, Jiale Dong et autres

In this paper, we design a frequency reconfigurable antenna for terahertz communication. The antenna is based on a Yagi design, with the main radiating elements being a pair of dipole antennas printed on the top and bottom of a dielectric substrate, respectively. …

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Novel bakuchiol derivatives inhibit the migration and invasion of non-small cell lung cancer by suppressing epithelial-to-mesenchymal transition

Mengfan Xu, Ke Zhong, Jingjing Zhu, Jie Chen et autres

values of 2.23 and 5.55 µM against PC9 and H1975 cells, respectively. Compound 2f effectively suppresses tumor cell proliferation by inducing cell cycle arrest and promoting apoptosis. Additionally, various evidence after treatment with compound 2f in PC9 cells, including the inhibition of …

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Frequency Reconfigurable Terahertz Planar End-fire Antenna loaded with Parasitic Patches

Qimeng Liu, Renbin Zhong, Jiale Dong, Boli Xu et autres

This paper presents a frequency reconfigurable planar end-fire antenna in the terahertz frequency band. The antenna is loaded with parasitic patches, which are connected by GaAs Schottky diodes. Controlling the operation state of the diodes allows for the alteration of the antenna's …

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Co-Occurrence Fingerprint Data-Based Heterogeneous Transfer Learning Framework for Indoor Positioning

Jian Huang, Haonan Si, Xiansheng Guo, Ke Zhong

Distribution discrepancy is an intrinsic challenge in existing fingerprint-based indoor positioning system(s) (FIPS) due to real-time environmental variations; thus, the positioning model needs to be reconstructed frequently based on newly collected training data. However, it is expensive or impossible to collect adequate …

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OHetTLAL: An Online Transfer Learning Method for Fingerprint-Based Indoor Positioning

Hailu Tesfay Gidey, Xiansheng Guo, Ke Zhong, Lin Li et autres

In an indoor positioning system (IPS), transfer learning (TL) methods are commonly used to predict the location of mobile devices under the assumption that all training instances of the target domain are given in advance. However, this assumption has been criticized for …

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