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An M-VCUT level set-based data-driven model of microstructures and optimization of two-scale structures

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Frontiers of Mechanical Engineering 2024年第4期19卷 73-86页

作者： Minjie SHAO Tielin SHI Qi xia State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China

The optimization of two-scale structures can adapt to the different needs of materials in various regions by reasonably arranging different microstructures at the macro scale,thereby considerably improving structural ***,a multiple variable cutting(M-VCUT)level set-based data-driven model of microstructures is presented,and a method based on this model is proposed for the optimal design of two-scale *** geometry of the microstructure is described using the M-VCUT level set method,and the effective mechanical properties of microstructures are computed by the homogenization ***,a database of microstructures containing their geometric and mechanical parameters is *** two sets of parameters are adopted as input and output datasets,and a mapping relationship between the two datasets is established to build the data-driven model of *** the optimization of two-scale structures,the data-driven model is used for macroscale finite element and sensitivity *** efficiency of the analysis and optimization of two-scale structures is improved because the computational costs of invoking such a data-driven model are much smaller than those of homogenization.

关键词： two-scale structure structural optimization M-VCUT level set homogenization radial basis function data-driven

BCCLR:A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

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Computers, Materials & Continua 2024年第3期78卷 4489-4507页

作者： Yunhe Wang Yuxin xia Shuai Liu College of Information Science and Engineering Institute of Interdisciplinary StudiesHunan Normal UniversityChangsha410081China School of Educational Sciences Institute of Interdisciplinary StudiesHunan Normal UniversityChangsha410081China

In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal *** GCNs define the graph topology by physical relations of the human ***,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint *** addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar ***,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint *** using the weight relationship between the joint pairs,an adaptive model is *** also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of *** the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar *** experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.

关键词： Action recognition deep learning GCN behavior dependence context clue self-attention

Legitimate monitor by proactive guarding for counter covert communications

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Science China(Information Sciences) 2024年第8期67卷 221-237页

作者： Manlin WANG Bin xia Jiangzhou WANG School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University School of Engineering University of Kent

Covert communication has been widely investigated to avoid the transmission behavior being overheard by the warder. However, covert communication may be illegitimately utilized by unauthorized parties to evade the supervision of authorized agencies, which leads to great challenges to information security. To meet the need for authorized parties to monitor and prevent illegitimate transmission between unauthorized nodes, a novel paradigm, called legitimate monitor, is proposed for counter covert communications. In the preceding covert communication system, the covert transmission rate is the focus. Differently,the core concern of the legitimate monitor system is the outage probability of the transmission between unauthorized nodes, which should be maximized to interrupt the potential but undetectable *** achieve these goals effectively, a proactive guarding approach is proposed, where the authorized warder detects the transmission behavior and emits jamming signals to interfere with the potential transmission,simultaneously. In particular, the jamming power at the warder is optimized under cases where the instantaneous/statistical channel state information is available. Besides, the corresponding outage probability is derived to evaluate the system performance, which can also be simplified to scenarios with a passive *** results demonstrate that proactive guarding outperforms the passive one, especially when the warder is not proximal to the unauthorized transmitter. In addition, the proposed jamming power allocation scheme also outperforms other benchmark schemes.

关键词： legitimate monitor counter covert communication full-duplex technology outage probability power allocation optimization

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Differences in insomnia-related self-reported outcomes among elderly hospitalized patients

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World Journal of Psychiatry 2024年第5期14卷 686-694页

作者： xia Ding Ling-xia Qi Dong-Yun Sun Department of Gangzha General Medical Center The Affiliated Hospital of Nantong UniversityNantong 226000Jiangsu ProvinceChina Department of Anesthesiology and Surgery The Affiliated Hospital of Nantong UniversityNantong 226000Jiangsu ProvinceChina Department of Ophthalmic Surgery Room The Affiliated Hospital of Nantong UniversityNantong 226000Jiangsu ProvinceChina

Insomnia is among the most common sleep disorders *** in older adults is a social and public health *** affects the physical and mental health of elderly hospitalized patients and can aggravate or induce physical *** subjective feelings and providing reasonable and standardized care for elderly hospitalized patients with insomnia are urgent *** To explore the differences in self-reported outcomes associated with insomnia among elderly hospitalized *** One hundred patients admitted to the geriatric unit of our hospital between June 2021 and December 2021 were included in this ***-reported symptoms were assessed using the Athens Insomnia Scale(AIS),Generalized Anxiety Disorder Scale-7(GAD-7),Geriatric Depression Scale-15(GDS-15),Memorial University of Newfoundland Scale of Happiness(MUNSH),Barthel Index Evaluation(BI),Morse Fall Scale(MFS),Mini-Mental State Examination,and the Short Form 36 Health Survey Questionnaire(SF-36).Correlation coefficients were used to analyze the correlation between sleep quality and self-reported *** of insomnia was analyzed using Logistic regression *** Nineteen patients with AIS≥6 were included in the insomnia group,and the incidence of insomnia was 19%(19/100).The remaining 81 patients were assigned to the non-insomnia *** were significant differences between the two groups in the GDA-7,GDS-15,MUNSH,BI,MFS,and SF-36 items(P<0.05).Patients in the insomnia group were more likely to experience anxiety,depression,and other mental illnesses,as well as difficulties with everyday tasks and a greater risk of falling(P<0.05).Subjective well-being and quality of life were poorer in the insomnia group than in the control *** AIS scores positively correlated with the GAD-7,GDS-15,and MFS scores in elderly hospitalized patients with insomnia(P<0.05).Logistic regression analysis showed that GDS-15≥5 was an independent risk factor for ins

关键词： Elderly hospitalized patients Insomnia Self-reported outcomes Symptoms Subjective feelings Correlation

A dynamical neural network approach for distributionally robust chance-constrained Markov decision process

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Science China Mathematics 2024年第6期67卷 1395-1418页

作者： Tian xia Jia Liu Zhiping Chen School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’an710049China

In this paper,we study the distributionally robust joint chance-constrained Markov decision *** the logarithmic transformation technique,we derive its deterministic reformulation with bi-convex terms under the moment-based uncertainty *** cope with the non-convexity and improve the robustness of the solution,we propose a dynamical neural network approach to solve the reformulated optimization *** results on a machine replacement problem demonstrate the efficiency of the proposed dynamical neural network approach when compared with the sequential convex approximation approach.

关键词： Markov decision process chance constraints distributionally robust optimization moment-based ambiguity set dynamical neural network

维普期刊数据库

Interface engineering via molecules/ions/groups for electrocatalytic water splitting

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Nano Research 2024年第9期17卷 7864-7879页

作者： Defang Ding Youwen Liu Fan xia Engineering Research Center of Nano-Geomaterials of Ministry of Education Faculty of Materials Science and ChemistryChina University of GeosciencesWuhan 430074China State Key Laboratory of Materials Processing and Die&Mould Technology and School of Materials Science and Engineering Huazhong University of Science and Technology WuhanHubei 430074China

The electrochemical water splitting to produce hydrogen converts electric energy into clean hydrogen energy,which is a groundbreaking concept of energy *** achieve high efficiency,numerous strategies have been developed to enhance the performance of *** these,interface engineering with molecules/ions/groups,serves as a versatile approach for optimizing the performance of electrocatalysts in water *** the basis of numerous achievements in high-performance electrocatalysts engineered through molecules/ions/groups at interface,a comprehensive understanding of these advancements is crucial for guiding future ***,after providing a concise overview of the background,the interface engineering via molecules/ions/groups for electrocatalytic water splitting is demonstrated from three ***,the engineering of electronic state of electrocatalysts by molecules/ions/groups at interface to reduce the Gibbs free energy of the corresponding ***,the modification of local microenvironment surrounding electrocatalysts via molecules/ions/groups at interface to enhance the transfer of reactants and ***,the protection of electrocatalysts with molecule/ion/group fences improves their durability,including protecting active sites from leaching and defending them against harmful *** fundamental principles of these three aspects are outlined for each,along with pertinent ***,several research directions and challenges are proposed.

关键词： electrocatalyst water splitting interface engineering molecules/ions/groups

Interleukins in Epilepsy:Friend or Foe

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Neuroscience Bulletin 2024年第5期40卷 635-657页

作者： Yuan Dong xia Zhang Ying Wang Neuropsychiatry Research Institute The Affiliated Hospital of Qingdao UniversityQingdao UniversityQingdao266000China Program in Cellular and Molecular Medicine Boston Children’s HospitalBostonMA02115USA

Epilepsy is a chronic neurological disorder with recurrent unprovoked seizures,affecting~65 million *** in patients with epilepsy and animal models suggests a contribution of neuroinflammation to epileptogenesis and the development of ***(ILs),as one of the major contributors to neuroinflammation,are intensively studied for their association and modulatory effects on ictogenesis and *** are commonly divided into pro-and anti-inflammatory cytokines and therefore are expected to be pathogenic or neuroprotective in ***,both protective and destructive effects have been reported for many *** may be due to the complex nature of ILs,and also possibly due to the different disease courses that those ILs are involved *** this review,we summarize the contributions of different ILs in those processes and provide a current overview of recent research advances,as well as preclinical and clinical studies targeting ILs in the treatment of epilepsy.

关键词： Epilepsy Interleukins Neuroinflammation

Towards imbalanced motion:part-decoupling network for video portrait segmentation

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Science China(Information Sciences) 2024年第7期67卷 197-210页

作者： Tianshu YU Changqun xia Jia LI State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang University Peng Cheng Laboratory

Video portrait segmentation(VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, the simplicity of existing VPS datasets leads to a limitation on extensive research of the task. In this work, we propose a new intricate large-scale multi-scene video portrait segmentation dataset MVPS consisting of 101 video clips in 7 scenario categories,in which 10843 sampled frames are finely annotated at the pixel level. The dataset has diverse scenes and complicated background environments, which is the most complex dataset in VPS to our best *** the observation of a large number of videos with portraits during dataset construction, we find that due to the joint structure of the human body, the motion of portraits is part-associated, which leads to the different parts being relatively independent in motion. That is, the motion of different parts of the portraits is imbalanced. Towards this imbalance, an intuitive and reasonable idea is that different motion states in portraits can be better exploited by decoupling the portraits into parts. To achieve this, we propose a part-decoupling network(PDNet) for VPS. Specifically, an inter-frame part-discriminated attention(IPDA)module is proposed which unsupervisedly segments portrait into parts and utilizes different attentiveness on discriminative features specified to each different part. In this way, appropriate attention can be imposed on portrait parts with imbalanced motion to extract part-discriminated correlations, so that the portraits can be segmented more accurately. Experimental results demonstrate that our method achieves leading performance with the comparison to state-of-the-art methods.

关键词： video portrait segmentation imbalanced motion unsupervised part decoupling motion correlation inter-frame attention

Path signature-based XAI-enabled network time series classification

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Science China(Information Sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng xia Department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network