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Social Robot Detection Method with Improved Graph Neural Networks

Computers, Materials & Continua 2024年第2期78卷 1773-1795页

作者： Zhenhua Yu Liangxue Bai ou Ye Xuya Cong Institute of Systems Security and Control College of Computer Science and TechnologyXi’an University of Science and TechnologyXi’an710054China

Social robot accounts controlled by artificial intelligence or humans are active in social networks,bringing negative impacts to network security and social life.Existing social robot detection methods based on graph neural networks suffer from the problem of many social network nodes and complex relationships,which makes it difficult to accurately describe the difference between the topological relations of nodes,resulting in low detection accuracy of social robots.This paper proposes a social robot detection method with the use of an improved neural network.First,social relationship subgraphs are constructed by leveraging the user’s social network to disentangle intricate social relationships effectively.Then,a linear modulated graph attention residual network model is devised to extract the node and network topology features of the social relation subgraph,thereby generating comprehensive social relation subgraph features,and the feature-wise linear modulation module of the model can better learn the differences between the nodes.Next,user text content and behavioral gene sequences are extracted to construct social behavioral features combined with the social relationship subgraph features.Finally,social robots can be more accurately identified by combining user behavioral and relationship features.By carrying out experimental studies based on the publicly available datasets TwiBot-20 and Cresci-15,the suggested method’s detection accuracies can achieve 86.73%and 97.86%,respectively.Compared with the existing mainstream approaches,the accuracy of the proposed method is 2.2%and 1.35%higher on the two datasets.The results show that the method proposed in this paper can effectively detect social robots and maintain a healthy ecological environment of social networks.

关键词： Social robot detection social relationship subgraph graph attention network feature linear modulation behavioral gene sequences

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Free-moving-state microscopic imaging of cerebral oxygenation and hemodynamics with a photoacoustic fiberscope

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Light(Science & Applications) 2024年第1期13卷 33-46页

作者： Xiaoxuan Zhong Yizhi Liang Xiaoyu Wang Haoying Lan Xue Bai Long Jin Bai-ou Guan Guangdong Provincial key Laboratory of Optical Fiber Sensing and Communications Institute of Photonics TechnologyJinan UniversityGuangzhou510632China

We report the development of a head-mounted photoacoustic fiberscope for cerebral imaging in a freely behaving mouse.The 4.5-gram imaging probe has a 9-µm lateral resolution and 0.2-Hz frame rate over a 1.2-mm wide area.The probe can continuously monitor cerebral oxygenation and hemodynamic responses at single-vessel resolution,showing significantly different cerebrovascular responses to external stimuli under anesthesia and in the freely moving state.For example,when subjected to high-concentration CO_(2) respiration,enhanced oxygenation to compensate for hypercapnia can be visualized due to cerebral regulation in the freely moving state.Comparative studies exhibit significantly weakened compensation capabilities in obese rodents.This new imaging modality can be used for investigating both normal and pathological cerebrovascular functions and shows great promise for studying cerebral activity,disorders and their treatments.

关键词： cerebral anesthesia moving

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A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

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Acta Pharmaceutica Sinica B 2024年第1期14卷 223-240页

作者： Lei Sun Arabella H.Wan Shijia Yan Ruonian Liu Jiarui Li Zhuolong Zhou Ruirui Wu Dongshi Chen Xianzhang Bu Jingxing ou Kai Li Xiongbin Lu Guohui Wan Zunfu ke Department of Pathology the First Affiliated HospitalSun Yat-sen UniversityGuangzhou 510080China National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation National Engineering Research Center for New Drug and Druggability(Cultivation)Guangdong Province Key Laboratory of New Drug Design and EvaluationSchool of Pharmaceutical SciencesSun Yat-sen UniversityGuangzhou 510006China Department of Medical and Molecular Genetics Indiana University School of MedicineIndianapolisIN 46202USA Department of Medicine Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCA 90033USA Department of Hepatic Surgery and Liver Transplantation Center Third Affiliated HospitalOrgan Transplantation InstituteSun Yat-sen UniversityOrgan Transplantation Research Center of Guangdong ProvinceGuangdong Province Engineering Laboratory for Transplantation MedicineGuangzhou 510630China Guangdong Provincial key Laboratory of Liver Disease Research Guangzhou 510630China Department of Ultrasound Third Affiliated HospitalSun Yat-sen UniversityGuangzhou 510630China Melvin and Bren Simon Comprehensive Cancer Center Indiana UniversityIndianapolisIN 46202USA

Lenvatinib,a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer,facing limitations due to drug resistance.Here,we applied a multidimensional,high-throughput screening platform comprising patient-derived resistant liver tumor cells(PDCs),organoids(PDOs),and xenografts(PDXs)to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings.Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment,expediting drug repurposing screens.Pharmacological screening identified romidepsin,YM155,apitolisib,NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models.Notably,romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway.A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models.Collectively,our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer,providing a feasible multidimensional platform for personalized medicine.

关键词： Lenvatinib Drug resistance High-throughput screening Drug discovery Patient-derived model Romidepsin EGFR Liver cancer

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Long-range asymmetric Cherenkov radiation

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Science China(Physics,Mechanics & Astronomy) 2024年第4期67卷 170-171页

作者： Gang Zhong Qingdong ou Macao Institute of Materials Science and Engineering(MIMSE) Faculty of Innovation EngineeringMacao University of Science and TechnologyTaipaMacao 999078China

Cherenkov radiation(CR)is gaining increasing attention as a high-output power Terahertz radiation source,and it plays a significant role in particle detectors,accelerators,and space science[1].This captivating phenomenon was first observed by Cerenkov in 1934 and was later explained theoretically by Tamm and Frank in 1937,earning them the Nobel Prize in Physics in 1958.CR occurs when charged particles move faster than the phase velocity of light in a specific medium.

关键词： asymmetric faster explained

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Development of a convolutional neural network based geomechanical upscaling technique for heterogeneous geological reservoir

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2111-2125页

作者： Zhiwei Ma Xiaoyan ou Bo Zhang Earth and Environmental Sciences Division Los Alamos National LaboratoryLos AlamosUSA Civil and Environmental Engineering University of AlbertaEdmontonCanada

Geomechanical assessment using coupled reservoir-geomechanical simulation is becoming increasingly important for analyzing the potential geomechanical risks in subsurface geological developments.However,a robust and efficient geomechanical upscaling technique for heterogeneous geological reservoirs is lacking to advance the applications of three-dimensional(3D)reservoir-scale geomechanical simulation considering detailed geological heterogeneities.Here,we develop convolutional neural network(CNN)proxies that reproduce the anisotropic nonlinear geomechanical response caused by lithological heterogeneity,and compute upscaled geomechanical properties from CNN proxies.The CNN proxies are trained using a large dataset of randomly generated spatially correlated sand-shale realizations as inputs and simulation results of their macroscopic geomechanical response as outputs.The trained CNN models can provide the upscaled shear strength(R^(2)>0.949),stress-strain behavior(R^(2)>0.925),and volumetric strain changes(R^(2)>0.958)that highly agree with the numerical simulation results while saving over two orders of magnitude of computational time.This is a major advantage in computing the upscaled geomechanical properties directly from geological realizations without the need to perform local numerical simulations to obtain the geomechanical response.The proposed CNN proxybased upscaling technique has the ability to(1)bridge the gap between the fine-scale geocellular models considering geological uncertainties and computationally efficient geomechanical models used to assess the geomechanical risks of large-scale subsurface development,and(2)improve the efficiency of numerical upscaling techniques that rely on local numerical simulations,leading to significantly increased computational time for uncertainty quantification using numerous geological realizations.

关键词： Upscaling Lithological heterogeneity Convolutional neural network(CNN) Anisotropic shear strength Nonlinear stressestrain behavior

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Current therapies for osteoarthritis and prospects of CRISPR-based genome,epigenome,and RNA editing in osteoarthritis treatment

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Journal of Genetics and Genomics 2024年第2期51卷 159-183页

作者： Yuxi Chen Xiao Luo Rui Kang Kaixin Cui Jianping ou Xiya Zhang Puping Liang MOE key Laboratory of Gene Function and Regulation State Key Laboratory of BiocontrolSchool of Life SciencesSun Yat-sen UniversityGuangzhouGuangdong 510275China Center for Reproductive Medicine The Third Affiliated Hospital of Sun Yat-sen UniversitySun Yat-sen UniversityGuangzhouGuangdong 510630China

Osteoarthritis(OA)is one of the most common degenerative joint diseases worldwide,causing pain,disability,and decreased quality of life.The balance between regeneration and inflammation-induced degradation results in multiple etiologies and complex pathogenesis of OA.Currently,there is a lack of effective therapeutic strategies for OA treatment.With the development of CRISPR-based genome,epigenome,and RNA editing tools,OA treatment has been improved by targeting genetic risk factors,activating chondrogenic elements,and modulating inflammatory regulators.Supported by cell therapy and in vivo delivery vectors,genome,epigenome,and RNA editing tools may provide a promising approach for personalized OA therapy.This review summarizes CRISPR-based genome,epigenome,and RNA editing tools that can be applied to the treatment of OA and provides insights into the development of CRISPR-based therapeutics for OA treatment.Moreover,in-depth evaluations of the efficacy and safety of these tools in human OA treatment are needed.

关键词： Osteoarthritis Genome editing Epigenone editing RNA editing

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Ultrathin two-dimensional medium-entropy oxide as a highly efficient and stable electrocatalyst for oxygen evolution reaction

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Nano Research 2024年第4期17卷 2555-2562页

作者： Guangyuan Yan Tianlu Wang Biwei Zhao Wenjing Gao Tong Wu Liming ou School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China

Medium-entropy oxides(MEOs)with broad compositional tunability and entropy-driven structural stability,are receiving booming attention as a promising candidate for oxygen evolution reaction(OER)electrocatalysts.Meanwhile,ultrathin two-dimensional(2D)nanostructure offers extremely large specific surface area and is therefore considered to be an ideal catalyst structure.However,it remains a grant challenge to synthesize ultrathin 2D MEOs due to distinct nucleation and growth kinetics of constituent multimetallic elements in 2D anisotropic systems.In this work,an ultrathin 2D MEO(MnFeCoNi)O was successfully synthesized by a facile and low-temperature ionic layer epitaxy method.Benefiting from multi-metal synergistic effects within ultrathin 2D nanostructure,this 2D MEO(MnFeCoNi)O revealed excellent OER electrocatalytic performance with a quite low overpotential of 117 mV at 10 mA·cm^(-2) and an impressive stability for 120 h continuous operation with only 6.9%decay.Especially,the extremely high mass activity(5584.3 A·g^(-1))was three orders of magnitude higher than benchmark RuO_(2)(3.4 A·g^(-1))at the same overpotential of 117 mV.This work opens up a new avenue for developing highly efficient and stable electrocatalysts by creating 2D nanostructured MEOs.

关键词： medium-entropy oxide two-dimensional nanomaterials ionic layer epitaxy oxygen evolution reaction electrocatalysis

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Alleviating the anisotropic microstructural change and boosting the lithium ions diffusion by grain orientation regulation for Ni-rich cathode materials

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Journal of Energy Chemistry 2024年第1期88卷 213-222,I0005页

作者： Xinyou He Shilin Su Bao Zhang Zhiming Xiao Zibo Zhang Xing ou Engineering Research Center of the Ministry of Education for Advanced Battery Materials School of Metallurgy and EnvironmentCentral South UniversityChangsha 410083HunanChina Zhejiang Power New Energy Co.Ltd Zhuji 311899ZhejiangChina

Generally,layered Ni-rich cathode materials exhibit the morphology of polycrystalline secondary sphere composed of numerous primary particles.While the arrangement of primary particles plays a very important role in the properties of Ni-rich cathodes.The disordered particle arrangement is harmful to the cyclic performance and structural stability,yet the fundamental understanding of disordered structure on the structural degradation behavior is unclarified.Herein,we have designed three kinds of LiNi_(0.83)Co_(0.06)Mn_(0.11)O_(2) cathode materials with different primary particle orientations by regulating the precursor coprecipitation process.Combining finite element simulation and in-situ characterization,the Li^(+)transport and structure evolution behaviors of different materials are unraveled.Specifically,the smooth Li^(+)diffusion minimizes the reaction heterogeneity,homogenizes the phase transition within grains,and mitigates the anisotropic microstructural change,thereby modulating the crack evolution behavior.Meanwhile,the optimized structure evolution ensures radial tight junctions of the primary particles,enabling enhanced Li^(+)diffusion during dynamic processes.Closed-loop bidirectional enhancement mechanism becomes critical for grain orientation regulation to stabilize the cyclic performance.This precursor engineering with particle orientation regulation provides the useful guidance for the structural design and feature enhancement of Ni-rich layered cathodes.

关键词： Ni-rich cathode Grain orientation regulation Anisotropic microstructural change Precursor engineering Li~+-ions diffusion

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A Video Captioning Method by Semantic Topic-Guided Generation

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Computers, Materials & Continua 2024年第1期78卷 1071-1093页

作者： ou Ye Xinli Wei Zhenhua Yu Yan Fu Ying Yang College of Computer Science and Technology Xi’an University of Science and TechnologyXi’an710054China

In the video captioning methods based on an encoder-decoder,limited visual features are extracted by an encoder,and a natural sentence of the video content is generated using a decoder.However,this kind ofmethod is dependent on a single video input source and few visual labels,and there is a problem with semantic alignment between video contents and generated natural sentences,which are not suitable for accurately comprehending and describing the video contents.To address this issue,this paper proposes a video captioning method by semantic topic-guided generation.First,a 3D convolutional neural network is utilized to extract the spatiotemporal features of videos during the encoding.Then,the semantic topics of video data are extracted using the visual labels retrieved from similar video data.In the decoding,a decoder is constructed by combining a novel Enhance-TopK sampling algorithm with a Generative Pre-trained Transformer-2 deep neural network,which decreases the influence of“deviation”in the semantic mapping process between videos and texts by jointly decoding a baseline and semantic topics of video contents.During this process,the designed Enhance-TopK sampling algorithm can alleviate a long-tail problem by dynamically adjusting the probability distribution of the predicted words.Finally,the experiments are conducted on two publicly used Microsoft Research Video Description andMicrosoft Research-Video to Text datasets.The experimental results demonstrate that the proposed method outperforms several state-of-art approaches.Specifically,the performance indicators Bilingual Evaluation Understudy,Metric for Evaluation of Translation with Explicit Ordering,Recall Oriented Understudy for Gisting Evaluation-longest common subsequence,and Consensus-based Image Description Evaluation of the proposed method are improved by 1.2%,0.1%,0.3%,and 2.4% on the Microsoft Research Video Description dataset,and 0.1%,1.0%,0.1%,and 2.8% on the Microsoft Research-Video to Text dataset,respectively,compared with the existing video c

关键词： Video captioning encoder-decoder semantic topic jointly decoding Enhance-TopK sampling

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scRNA-seq reveals that origin recognition complex subunit 6 regulates mouse spermatogonial cell proliferation and apoptosis via activation of Wnt/β-catenin signaling

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Asian Journal of Andrology 2024年第1期26卷 46-56页

作者： Shi-Wei Liu Jia-Qiang Luo Liang-Yu Zhao Ning-Jing ou Chao-Yang Yu-Xiang Zhang Hao-Wei Bai Hong-Fang Sun Jian-Xiong Zhang Chen-Cheng Yao peng Li Ru-Hui Tian Zheng Li Zi-Jue Zhu Department of Andrology Center for Men's HealthUrologic Medical CenterShanghai General HospitalShanghai Jiao Tong University School of MedicineShanghai 200080China State key Lab of Reproductive Medicine Nanjing Medical UniversityNanjing 211166China Shanghai key Lab of Reproductive Medicine Shanghai Jiao Tong University School of MedicineShanghai 200080China Department of Urology Guangdong Provincial Key Laboratory of Biomedical ImagingThe Fifth Affiliated HospitalSun Yat-sen UniversityZhuhai 519000China Department of Urology First Affiliated Hospital of Nanjing Medical UniversityNanjing 210029China

The regulation of spermatogonial proliferation and apoptosis is of great significance for maintaining spermatogenesis.The single-cell RNA sequencing(scRNA-seq)analysis of the testis was performed to identify genes upregulated in spermatogonia.Using scRNAseq analysis,we identified the spermatogonia upregulated gene origin recognition complex subunit 6(Orc6),which is involved in DNA replication and cell cycle regulation;its protein expression in the human and mouse testis was detected by western blot and immunofluorescence.To explore the potential function of Orc6 in spermatogonia,the C18-4 cell line was transfected with control or Orc6 siRNA.Subsequently,5-ethynyl-2-deoxyuridine(EdU)and terminal deoxynucleotidyl transferase dUTP nick end labeling(TUNEL)assays,flow cytometry,and western blot were used to evaluate its effects on proliferation and apoptosis.It was revealed that ORC6 could promote proliferation and inhibit apoptosis of C18-4 cells.Bulk RNA sequencing and bioinformatics analysis indicated that Orc6 was involved in the activation of wingless/integrated(Wnt)/β-catenin signaling.Western blot revealed that the expression ofβ-catenin protein and its phosphorylation(Ser675)were significantly decreased when silencing the expression of ORC6.our findings indicated that Orc6 was upregulated in spermatogonia,whereby it regulated proliferation and apoptosis by activating Wnt/β-catenin signaling.

关键词： cell proliferation ORCG scRNA-seq analysis spermatogonia Wnt/β-catenin signaling

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