Research on Multi-Channel Spectral Prediction Model for Printed Matter Based on HMSSA-BP Neural Network by Dandan Fan, Hongwu Zhan, Fang Xu, Yifei Zou, Yankang Zhang

“…However, traditional Chromaticity-based prediction fades in metamerism problem inevitably. Moreover, there is no single quality index that significantly outperforms others or provides the best performance in all situations. …”
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Investigation of Free Vibration in Fluid-Loaded Cylindrical Shells with a Three-Layer Sandwich Wall and an Auxetic Central Layer by Korosh Khorshidi, Saboor Savvafi, Sadegh Zobeid

“…To model this problem, we employ a modified high-order shear deformation theory (HSDT). …”
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Prob-sparse self-attention extraction of time-aligned dynamic functional connectivity for ASD diagnosis by Hongwu Chen, Fan Feng, Pengwei Lou, Ying Li, MingLi Zhang, Feng Zhao

“…Additionally, we construct a time-aligned DFC matrix to mitigate the time sensitivity of DFC and extend the dataset, thereby alleviating model overfitting. …”
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Spatiotemporal Flood Hazard Classification in Bangkok Using Graph Convolutional Network and Temporal Fusion Transformer by Pakpoom Chaimook, Nirattaya Khamsemanan, Cholwich Nattee, Alice Sharp

“…The GCN component learns spatial dependencies from a graph constructed based on district relations, while the TFT learns temporal sequences based on spatiotemporal inputs. …”
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Determination of the angular position of the signal source in distributed reception at the background of non-Gaussian noise by T.V. Vorobkalo, O.S. Gavrish, V.V. Filipov, S.S. Martynenko, P.A. Klopotovskyi

“…This is a statistical problem, and it is solved as an estimation of the signal phase in each receiving element using the method of polynomial maximization. …”
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Transferable Feature Representation for Visible-to-Infrared Cross-Dataset Human Action Recognition by Yang Liu, Zhaoyang Lu, Jing Li, Chao Yao, Yanzi Deng

“…Motivated by the idea of transfer learning, an infrared human action recognition framework using auxiliary data from visible light is proposed to solve the problem of limited infrared action data. In the proposed framework, we first construct a novel Cross-Dataset Feature Alignment and Generalization (CDFAG) framework to map the infrared data and visible light data into a common feature space, where Kernel Manifold Alignment (KEMA) and a dual aligned-to-generalized encoders (AGE) model are employed to represent the feature. …”
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The fractional solitary wave profiles and dynamical insights with chaos analysis and sensitivity demonstration by Muhammad Idrees Afridi, Muhammad Amin Sadiq Murad, Waqas Ali Faridi, Mujahid Iqbal, Ferdous Tawfiq, Ahmed H. Arnous

“…A variety of traveling wave and soliton solutions are constructed, including kink, bell, bright, and dark soliton solutions. …”
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Identification and Application of Wave Field Characteristics of Channel Waves in Extra-Thick Coal Seams by Tao Ding, Yanhui Wu, Yiran Hu, Zhen Nie, Xianhua Hou, Mianping Zheng

“…Channel wave seismic activity often occurs with thin and medium-thick coal seams being the main target layer. To address the problem of channel wave applicability detection in extremely thick coal seams, the propagation and identification characteristics of channel waves remain the focus of research. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…This study provides a new optimization approach for knowledge graph and semantic-driven recommendation systems, enabling more accurate capture of user preferences and alleviating the problem of noise interference.…”
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Production of SARS-CoV-2 virus-like particles as a vaccine candidate in stable cell lines through inducible E and M protein expression by Yu Liu, Zhian Chen, Li Yang, Chunmei Gan, Jieshi Tang, Zhaoyue Zheng, JingYa Ye, C. Alexander Valencia, Hoi Yee Chow, Biao Dong

“…SARS-CoV-2 VLPs production is achieved via transient transfection of genes encoding viral structural proteins, but is costly and difficult to scale up. To address this problem, stable VLPs-producing cell lines are desirable. …”
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Anti-tumour effects of red blood cell membrane-camouflaged black phosphorous quantum dots combined with chemotherapy and anti-inflammatory therapy by Xueyuan Huang, Bin Wu, Jian Li, Yinghui Shang, Wansong Chen, Xinmin Nie, Rong Gui

“…Tumour microenvironment (TME) plays a critical role in tumour development and drug resistance. To address this problem, we constructed a novel anti-tumour nanoparticle platform RBC@BPQDs-DOX/KIR, black phosphorus nanoparticle quantum dots (BPQDs) with one of the chemotherapeutics (doxorubicin, DOX) and an anti-inflammatory traditional Chinese medicine active component (Kirenol, KIR). …”
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Halal or Not: Knowledge Graph Completion for Predicting Cultural Appropriateness of Daily Products by Van Thuy Hoang, Tien-Bach-Thanh do, Jinho Seo, Seung Charlie Kim, Luong Vuong Nguyen, Duong Nguyen Minh Huy, Hyeon-Ju Jeon, O-Joun Lee

“…Specifically, we first construct a cosmetic knowledge graph representing the relations between various cosmetics, ingredients, and their properties. …”
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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure by Juan Cruz-Martinez, Aron Jansen, Gijs van Oord, Tanjona R Rabemananjara, Carlos M R Rocha, Juan Rojo, Roy Stegeman

“…While focusing on proton structure, our method is fully general and is applicable to any deep learning problem relying on hyperparameter optimisation for an ensemble of models.…”
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Composition Design and Property Prediction for AlCoCrCuFeNi High-Entropy Alloy Based on Machine Learning by Cuixia Liu, Meng Meng, Xian Luo

“…This study solves the problem of revealing the mutual relationship between the element contents and hardness of high-entropy alloys in the case of a lack of alloy data and provides theoretical guidance for further improving the performance of high-entropy alloys.…”
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A multi-modal graph-based framework for Alzheimer’s disease detection by Najmeh Mashhadi, Razvan Marinescu

“…Abstract We propose a compositional graph-based Machine Learning (ML) framework for Alzheimer’s disease (AD) detection that constructs complex ML predictors from modular components. …”
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Overabundant suburban deer, invertebrates, and the spread of an invasive exotic plant by Jeffrey P. Duguay, Cheryl Farfaras

“…Abstract White‐tailed deer (Odocoileus virginianus) overabundance is a problem of serious concern for wildlife managers. …”
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Dynamic Simulation Modeling of Industrial Robot Kinematics in Industry 4.0 by Guang Jin, Shuai Ma, Zhenghui Li

“…The error model is established based on the MD-H method and the principle of differential transformation, and then the function of uniform variation of six joint angles with time t is constructed to ensure that each linkage geometric parameter is involved in the motion causing error accumulation. …”
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Application of Large-Scale Cognitive Social Networks Based on Cooperative Transmission Mechanisms in Exploration of Flipped Classroom Teaching Strategy by Chen Zeng

“…The source-destination node distribution is constructed with a model based on node affinity to restore the actual network node distribution architecture. …”
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The impact of HCV therapy in a high HIV-HCV prevalence population: A modeling study on people who inject drugs in Ho Chi Minh City, Vietnam. by Ruthie B Birger, Thuy Le, Roger D Kouyos, Bryan T Grenfell, Timothy B Hallett

“…<h4>Background</h4>Human Immunodeficiency Virus (HIV) and Hepatitis C Virus (HCV) coinfection is a major global health problem especially among people who inject drugs (PWID), with significant clinical implications. …”
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A novel multi-class classification method for arrhythmias using Hankel dynamic mode decomposition and long short-term memory networks by Chuchu Liang, Majid Khan Majahar Ali, Lili Wu

“…In this paper, we propose a new model for the multiclassification task of arrhythmia, which combines Hankel Dynamic Modal Decomposition (HDMD) and Long Short-Term Memory Network (LSTM).HDMD is used to construct the Hankel matrix, the optimal delay parameter is selected based on 90% of the energy of the singular values, and dynamic modal features extracted from it are used as the input sequences of LSTM. …”
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