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Effect of dual targeting procyanidins nanoparticles on metabolomics of lipopolysaccharide-stimulated inflammatory macrophages

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Food science and Human Wellness 2023年第6期12卷 2252-2262页

作者： Shanshan Tie Lijuan Zhang Bin Li Shanghua Xing Haitao Wang Yannan Chen Weina Cui Shaobin Gu Mingqian Tan Academy of Food Interdisciplinary Science School of Food Science and TechnologyDalian Polytechnic UniversityDalian 116034China College of Food and Bioengineering Henan University of Science and TechnologyLuoyang 471023China College of Food Science Shenyang Agricultural UniversityNational R&D Professional Center for Berry ProcessingShenyang 110866China

Inflammation plays an important role in the occurrence and development of many inflammatory *** purpose of this study was to evaluate the anti-inflammatory effect and metabolic behavior of the dual targeting procyanidins(PC)nanoparticles on lipopolysaccharide(LPS)-stimulated inflammatory macrophages by metabolomics *** double-targeting PC nanoparticles could specifi cally target both the CD44 receptor and mitochondria,while the single targeting PC-loaded nanoparticles that could target the CD44 receptor on the surface of *** double-targeting PC nanoparticles had better inhibitory effect than single-targeting PC nanoparticles on the leakage of lactate dehydrogenase and reactive oxygen species overexpression induced by *** acid metabolism,energy metabolism and purine metabolism were disordered in LPS-treated group,and metabolic pathway analysis indicated that the double-targeting PC nanoparticles reversed some of LPS *** changes of these potential biomarkers and their corresponding pathways are helpful to further understand the mechanism of PC nanoparticles in alleviating inflammation,and promote their application in nutrition intervention.

关键词： Procyanidins nanoparticles Metabolomics Inflammation Macrophages Lipopolysaccharide

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Gene selection and clustering of single-cell data based on Fisher score and genetic algorithm

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Journal of Supercomputing 2023年第7期79卷 7067-7093页

作者： Feng, Junhong Zhang, Jie Zhu, Xiaoshu Wang, Jian-Hong School of Computer and Information Engineering Guangdong Songshan Polytechnic Guangdong Shaoguan512126 China School of Computer Science and Engineering Yulin Normal University Guangxi Yulin537000 China Department of Computer Science and Information Engineering National Chin-Yi University of Technology Taichung Taiwan

Huge amounts of genes in single-cell RNA sequencing (scRNA-seq) data may influence the performance of data clustering. To obtain high-quality genes for data clustering, the study proposes a novel gene selection algorithm based on Fisher score and genetic algorithms with dynamic crossover (abbreviated as FDCGA). To reduce time and space complexity, FDCGA first employs Fisher score to gain the preliminary candidate genes and then utilizes genetic algorithms with dynamic crossover to select beneficial genes to data clustering and analysis. The experimental results conducted on several publicly real-world scRNA-seq datasets demonstrate that FDCGA outperforms the other several competitors in terms of both NMI and ARI metrics and possesses significant optimization performances. The experimental convergence shows that the fitness of FDCGA can increase and converge to a fixed state versus the number of iterations. The statistical analysis demonstrates that FDCGA statistically significantly outperforms the other competing methods. © 2022, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Genetic algorithms

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Influences of DRA and non-DRA vision on the visual responses of locusts stimulated by linearly polarized and unpolarized lights

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International Journal of Agricultural and Biological Engineering 2023年第3期16卷 15-22页

作者： Shengguang Zou Tao Liu Yicheng Ma Pingchuan Zhang Qihang Liu School of Computer Science&Technology Henan Institute of Science and TechnologyXinxiang 453003HenanChina Inner Mongolia Agricultural University Hohhot 010018China Key Laboratory of the Development and Resource Utilization of Biological Pesticide in Inner Mongolia Hohhot 010019China

Locust and grasshopper plagues pose a serious threat to crop production in many areas ***,there is a lack of effective,quick-acting methods to control such *** exploiting the phototactic response of these insects are receiving increasing *** current study investigated the effect of linearly polarized and unpolarized light on locust phototactic and polarotactic responses,in particular the function of their dorsal rim area(DRA)and non-DRA visual *** results showed that the polarotactic function weight of DRA vision was stimulated by linearly polarized ultraviolet(UV)and violet light,the phototactic function weight was induced by blue,green,and orange light,and under linearly polarized light,the functional effect of DRA vision was strongest in response to linearly polarized violet ***,the locust visual response effect was related to spectral light attributes,with the linear polarization effect intensifying in response to the short-range vision sensitivity of non-DRA visual fields,whereas DRA vision regulated the short-range sensitivity of compound eye *** illumination increased,the synergistic enhancement effects of linearly polarized ultraviolet and violet light were significant,whereas the visual sensitivity was restricted significantly by linearly polarized blue,green,or orange ***,non-DRA vision determined,while DRA vision enhanced,the phototactic response sensitivity,whereas,in linearly polarized UV or violet light,non-DRA vision determined,while DRA vision enhanced,the visual trend and polarotaxic aggregation sensitivity,with opposite effects in linearly polarized blue,green,or orange *** illumination increased,there was a driving effect caused by linearly polarized violet light on non-DRA vision,whereas at short-wave lengths,the control effect induced by linearly polarized orange light was optimal;however,the photo-induced effect of linearly polarized violet light and the visual distan

关键词： Locusta migratoria linearly polarized light spectral light visual response DRA and non-DRA vision

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A Multi-strategy Improved Osprey Optimization Algorithm for UAV path Planning 7

A Multi-strategy Improved Osprey Optimization Algorithm for ...

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7th International Conference on Robotics, Control and Automation Engineering, RCAE 2024

作者： Yang, Long Wang, Weimin Xu, Binzi School of Computer Jiangsu University of Science and Technology Zhenjiang212000 China School of Electrical Engineering Anhui Polytechnic University Wuhu24100 China

ISBN: (纸本)9798350355642

Addressing the challenges of reduced population diversity and susceptibility to local optima in the later iterations of the Osprey algorithm, this paper presents a Multi-Strategy Improved Osprey Algorithm (IOOA). Firstly, Piecewise mapping is employed to initialize the population, providing a robust foundation for global search. Secondly, during the exploration stage, we design an adaptive parameter Levy exploration method based on the fishhawk leader. Additionally, we integrate a random disturbance strategy inspired by trigonometric functions to enhance population diversity and improve global exploration capacity. During the exploring phase, we propose nonlinear control parameters to effectively balance exploration and exploitation, thus decreasing the risk of the algorithm stagnating to local optimum. Additionally, we introduce an update formula based on the positions of elite leaders to expedite convergence. Finally, we conduct simulation experiments and statistical tests on 13 benchmark test functions, comparing the performance of IOOA with seven popular algorithms. Simultaneously, we apply IOOA to the UAV path planning problem to validate its optimization performance in practical scenarios. The results indicate that IOOA exhibits faster convergence speed and higher effectiveness compared to other optimizers. © 2024 IEEE.

关键词： Motion planning

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GLOBAL SOLUTIONS TO A 3D AXISYMMETRIC COMPRESSIBLE NAVIER-STOKES SYSTEM WITH DENSITY-DEPENDENT VISCOSITY

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Acta Mathematica Scientia 2022年第2期42卷 521-539页

作者： Mei WANG Zilai LI Zhenhua GUO School of Sciences Xi’an University of TechnologyXi’an 710048China School of Mathematics and Information Science Henan Polytechnic UniversityJiaozuo 454000China School of Mathematics and Information Science Guangxi UniversityNanning 530004China

In this paper,we consider the 3D compressible isentropic Navier-Stokes equations when the shear viscosityμis a positive constant and the bulk viscosity is λ(ρ)=ρ^(β) with β>2,which is a situation that was first introduced by Vaigant and Kazhikhov in[1].The global axisymmetric classical solution with arbitrarily large initial data in a periodic domain Ω={(r,z)|r=√x^(2)+y^(2),(x,y,z)∈R^(3),r∈I⊂(0,+∞),-∞0 when z→±∞.Our results also show that the solution will not develop the vacuum state in any finite time,provided that the initial density is uniformly away from the vacuum.

关键词： Navier-Stokes equations axisymmetric density-dependent classical solution

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Two-Stage Traffic Sign Classification System 2

Two-Stage Traffic Sign Classification System

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2nd International Conference on Machine Learning and Data Engineering, ICMLDE 2023

作者： Suresha, R. Manohar, N. Jipeng, Tian Department of Computer Science School of Computing Amrita Vishwa Vidyapeetham Mysuru Campus India Computer Science College Zhongyuan University of Technology Henan Province Zhengzhou China

Traffic Sign Recognition (TSR) has received widespread attention due to increased traffic accidents caused by a failure to recognize road traffic signs. Most Traffic Sign Recognition remains challenging due to the illumination of natural scenes, and the diversity in traffic signs [31]. To solve the problem, we proposed a two-stage classification system to overcome the above-mentioned challenges and classify the traffic sign boards efficiently. During the first phase, colour based histogram equalizations applied to eliminates the illumination factors and then traffic sign boards are classified into many shapes, which includes circular, triangular, hexagonal, and diamond traffic signs boards based on the modified HOG feature descriptors and various machine learning classifiers are compared [12]. In the second phase, circular and triangular traffic signs are further categorized into specific subclasses using circular and triangular signs trained Convolutional Neural Network (CNN) respectively to overcome intra-class variation among the similar sign board. Experimentation was conducted on German Traffic Sign Recognition Benchmark dataset (GTSRB) [30] and the results show 99.96% top-1 accuracy during the first stage of classification. In the second stage, there is accuracy of 99.40% for circular traffic signs and 97.50% for triangular traffic signs. © 2024 Elsevier B.V.. All rights reserved.

关键词： Traffic signs

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Digital Dissemination of Information Based on Knowledge Graph Recommendation Algorithm

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Informatica (Slovenia) 2024年第19期48卷 31-44页

作者： Wang, Lu Zhang, Yunzhen Department of Investigation Henan Police College Zhengzhou450046 China College of Computer Science and Information Engineering Anyang Institute of Technology Anyang455000 China School of Energy and Intelligence Engineering Henan University of Animal Husbandry and Economy Zhengzhou450046 China

The rapid advancement of technology has made recommendation systems a research focus in modern information processing. To enhance the accuracy of recommendation systems and effectively capture and recommend user interests in complex data environments, this study starts with the combination of knowledge graphs and graph neural networks. Firstly, the water wave network algorithm is introduced to diffuse user interest information and fully utilize the global information of the knowledge graph. Secondly, the processed knowledge graph is input into the graph neural network for deep feature learning, and finally, a recommendation algorithm combining the ripple network and graph neural network is proposed. The test results showed that when the final recommendation results of the model were 5, 10, 15, 20, 25, and 30, the matching degrees of the recommendation results were 99.2%, 98.3%, 97.4%, 96.5%, 95.8%, and 95.2%, respectively. On the 100% dataset, the improved model had a 7.52% higher hit rate than the original knowledge graph convolutional network, and the mean reciprocal ranking value increased by 14.29. The normalized discounted cumulative gain on different datasets has increased by an average of 7.0%. Experiments have shown that by combining knowledge graphs and graph neural networks, the dynamic adaptability and recommendation quality of recommendation systems have been effectively improved, providing an efficient and accurate solution for information recommendation. © 2024 Slovene Society Informatika. All rights reserved.

关键词： Knowledge graph

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Hybrid Shunted Transformer embedding UNet for remote sensing image semantic segmentation

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Neural Computing and Applications 2024年第25期36卷 15705-15720页

作者： Zhou, Huacong Xiao, Xiangling Li, Huihui Liu, Xiaoyong Liang, Peng School of Computer Science Guangdong Polytechnic Normal University Guangdong Guangzhou510630 China Guangdong Provincial Key Laboratory of Intellectual Property and Big Data Guangdong Polytechnic Normal University Guangdong Guangzhou510665 China School of Data Science and Engineering Guangdong Polytechnic Normal University Guangdong Guangzhou510630 China Academy of Heyuan Guangdong Polytechnic Normal University Guangdong Heyuan517099 China The Cyberspace Institute of Advanced Technology Guangzhou University Guangdong Guangzhou510006 China

With the development of deep learning, Remote Sensing Image (RSI) semantic segmentation has produced significant advances. However, due to the sparse distribution of the objects and the high similarity between classes, the task of semantic segmentation in RSI is still extremely challenging. In this paper, we propose a novel semantic segmentation framework for RSI called HST-UNet that can overcome the shortcomings of the existing models and extract and recover the global and local features of RSI, which is a hybrid semantic segmentation model with Shunted Transformer as encoder and Multi-Scale Convolutional Attention Network (MSCAN) as decoder. Then, to better fuse the information from the Encoder and the Decoder and alleviate the ambiguity, we design a Learnable Weighted Fusion (LWF) module to effectively connect to the decoder features. Extensive experiments demonstrate that the proposed HST-UNet outperforms the state-of-the-art methods, achieving F1 score/MIoU accuracy of 71.44%/83.00% on the ISPRS Vaihingen dataset and 77.36%/87.09% on ISPRS Potsdam dataset. The code will be available at https://***/HC-Zhou/HST-UNet. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Semantic Segmentation

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Data-driven iterative learning trajectory tracking control for wheeled mobile robot under constraint of velocity saturation

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IET Cyber-Systems and Robotics 2023年第2期5卷 37-47页

作者： Xiaodong Bu Xisheng Dai Rui Hou The School of Automation Guangxi University of Science and TechnologyLiuzhouChina The Department of Automation College of Mechatronics Engineering and AutomationShanghai UniversityShanghaiChina The School of Electrical Engineering&Automation Henan Polytechnic UniversityJiaozuoChina

Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with ***,the authors designed an outer loop controller to provide virtual velocity for the inner loop according to the position and pose tracking error of the WMR kinematic ***,the authors employed dynamic linearisation to transform the dynamic model into an online data‐driven model along the iterative *** on the measured input and output data of the dynamic model,the authors identified the parameters of the inner loop *** authors considered the velocity saturation constraints;we adjusted the output velocity of the WMR online,providing effective solutions to the problem of velocity saltation and the saturation constraint in the tracking ***,the inner loop controller only uses the output data and input of the dynamic model,which not only enables the reliable control of WMR trajectory tracking,but also avoids the influence of inaccurate model identification processes on the tracking *** authors analysed the algorithm's convergence in theory,and the results show that the tracking errors of position,angle and velocity can converge to zero in the iterative ***,the authors used a simulation to demonstrate the effectiveness of the algorithm.

关键词： data-driven control dynamic model iterative learning control trajectory tracking velocity saturation wheeled mobile robot

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An Adaptive Denoising Recommendation Algorithm for Causal Separation Bias 11th

An Adaptive Denoising Recommendation Algorithm for Causal Se...

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11th Chinese National Conference on Social Media Processing, SMP 2023

作者： Zhang, Qiuling Xu, Huayang Wang, Jianfang School of Computer Science and Technology Henan Polytechnic University Jiaozuo454000 China

ISBN: (纸本)9789819975952

In recommender systems, user selection bias often influences user-item interactions, e.g., users are more likely to rate their previously preferred or popular items. Existing methods can leverage the impact of selection bias in user ratings on the evaluation and optimization of recommendation system. However, these methods either inevitably contain a large amount of noise in the sampling process or suffer from the confound between users’ conformity and interests. Inspired by the recent success of causal inference, in this work we propose a novel method to separate popularity biases for recommendation, named adaptive denoising and causal inference algorithm (ADA). We first compute the average rating of all feedback items of each user as the basis in converting explicit feedback to implicit feedback, and then obtain the true positive implicit data through adaptive denoising method. In addition, we separate the confounding of users’ conformity and interest in the selection bias by causal inference. Specifically, we construct a multi-task learning model with regularization loss functions. Experimental results on the two datasets demonstrate the superiority of our ADA model over state-of-the-art methods in recommendation accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Recommender systems

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