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Although many graph-based clustering methods attempt to model the stationary diffusion state in their objectives, their performance limits to using a predefined graph. We argue that the estimation of the stationary diffusion state can be achieved by gradient descent over neural networks. We specifically design the Stationary Diffusion State Neural Estimation (SDSNE) to exploit multiview structural graph information for co-supervised learning. We explore how to design a graph neural network specially for unsupervised multiview learning and integrate multiple graphs into a unified consensus graph by a shared self-attentional module. The view-shared self-attentional module utilizes the graph structure to learn a view-consistent global graph. Meanwhile, instead of using auto-encoder in most unsupervised learning graph neural networks, SDSNE uses a co-supervised strategy with structure information to supervise the model learning. The co-supervised strategy as the loss function guides SDSNE in achieving the stationary state. With the help of the loss and the self-attentional module, we learn to obtain a graph in which nodes in each connected component fully connect by the same weight. Experiments on several multiview datasets demonstrate effectiveness of SDSNE in terms of six clustering evaluation metrics., AAAI 2022

ObjectiveIschemic heart disease (IHD) has a high prevalence and mortality rate, imposing a heavy burden on patients and society, and there is still a need to optimize treatment options for IHD patients. Cardiac shock wave therapy (CSWT) is gaining popularity as a new treatment for IHD patients. The objective of this meta-analysis is to reassess the effects of CSWT on IHD patients in light of the limited number of clinical studies included in previously published reviews, inconsistent methodological quality, and unclear outcomes.MethodsFrom database creation until September 1, 2022, 4 English databases and 3 Chinese databases were rigorously searched for any current controlled trials of CSWT for IHD. The Cochrane Risk of Bias Assessment Tool was used for methodological quality assessment. Review Manager v.5.4 software was used for meta-analysis.ResultsNineteen published controlled trials totaling 1,254 subjects were included. Results showed that CSWT could enhance left ventricular function and myocardial viability, improve cardiac function and alleviate angina pectoris symptoms. The effects of CSWT and control groups on SAQ scores and exercise time were not statistically significant.ConclusionAccording to this systematic review and meta-analysis, CSWT may be beneficial for a number of IHD clinical indications. To verify these findings, more RCT studies with bigger sample numbers and higher methodological standards are required in the future.

the purpose of the study is to improve the security of the network, and make the state of network security predicted in advance. First, the theory of neural networks is studied, and its shortcomings are analyzed by the standard Elman neural network. Second, the layers of the feedback nodes of the Elman neural network are improved according to the problems that need to be solved. Then, a network security perception system based on GA-Elman (Genetic Algorithm-Elman) neural network is proposed to train the network by global search method. Finally, the perception ability is compared and analyzed through the model. The results show that the model can accurately predict network security based on the experimental charts and corresponding evaluation indexes. The comparative experiments show that the GA-Elman neural network security perception system has a better prediction ability. Therefore, the model proposed can be used to predict the state of network security and provide early warnings for network security administrators.

Yixuan Ma,1 Wen Zhang,1,2 Peipei Han,3 Masahiro Kohzuki,1 Qi Guo3 1Department of Internal Medicine and Rehabilitation Science, Tohoku University Graduate School of Medicine, Tohoku University, Sendai, Japan; 2Department of Rehabilitation and Sports Medicine, Tianjin Medical University, Tianjin, People’s Republic of China; 3Department of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences, Shanghai, People’s Republic of ChinaCorrespondence: Masahiro KohzukiDepartment of Internal Medicine and Rehabilitation Science, Tohoku University Graduate School of Medicine, Tohoku University, 1– 1 Seiryou-Cho, Aoba-Ku, Sendai 980– 8574, JapanEmail makohzuki@gmail.comQi GuoDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences, No. 279 Zhouzhu Road, Pudong New Area, Shanghai 201318, People’s Republic of ChinaTel/ Fax +86-22-8333-6977Email guoqijp@gmail.comObjective: The aims of this study were to investigate the association between osteosarcopenic obesity (OSO) and physical performance in Chinese elderly communities.Methods: Our study population is comprised of residents of the Township Central Hospital in the suburban of Tianjin, China. Participants (n=303; percent body fat (PBF): ≥ 25% for men and ≥ 32% for women) were assessed using the direct segmental multi-frequency bioelectrical impedance analysis (BIA) for body composition. Sarcopenia was defined as the lower 20th percentile of appendicular skeletal muscle mass/height2 (ASMI). A quantitative ultrasound scan of each participants’ calcaneus with a T score≤− 1.0 was used to identify the prevalence of osteopenia/osteoporosis (OP). We divided people into four groups: obesity only (O), osteopenic obesity (OO), sarcopenic obesity (SO), and osteosarcopenic obesity (OSO). We assessed the physical performance by grip strength, 4-m walk test (WS) and timed up and go test (TUGT).Results: A total of 303 participants had completed data (89 men, 214 women; mean age of 68.8± 6.0 years). The prevalence of OSO was 10.2% (men: 15.70%, women: 7.9%). After multiple adjustments, WS was significantly declined in OSO group when compared with the O group in men (mean value 95% CI was 0.84 (0.69, 0.99)) and women (mean value 95% CI was 0.93 (0.84, 1.02)). TUGT was significantly poorer in men (mean value 95% CI was 13.3 (10.6, 15.9)) and women (mean value 95% CI was 12.4 (11.2, 13.7)) with OSO when compared with the O group. Furthermore, the OSO group in women also had a significantly poorer TUGT compared with the OO group. The result of grip strength decreased significantly in women SO and OSO groups when compared with the O group (mean value 95% CI was 16.4 (14.5, 18.2) and 16.1 (13.9, 18.3)). But the results of grip strength in men showed no significant differences in any of the group.Conclusion: In Chinese community-dwelling elderly, slower WS and lower balance function were associated with OSO in men and women. Lower grip strength was associated with SO and OSO in women.Keywords: elder, osteosarcopenic obesity, physical performance

The existing energy flow analysis of power system has been formed a complete framework of modeling and quantitative analysis, which does not explicitly account for information characteristics of communication, protection and control. There are almost no remarkable achievements for analyzing the coupling and associated behaviors of energy flow and information flow in a cyber physical power system (CPPS), for lacking the information model suited for power system application. The modeling idea and computing methods of fluid information were developed, in which the graph, matrix and network calculus theory were composited and power flow calculation of the electric system were used for reference. As an example, the upper bound delay and traffic distribution of protection based on a substation communication network were calculated using the proposed method. The computing results and experimental ones from a network analyzer are very consistent, which suggests the validity of the proposed information flow calculation method.

Aiming at the transient stability disturbed trajectory prediction, a real-time prediction method of transient stability disturbed trajectory based on selfremembering gray Verhulst model is proposed. At the same time, considering the typical dynamic characteristics of the transient stability disturbed trajectory and its strong nonlinearity and stochastic volatility, a gray Verhulst model with self-remembering is constructed. Based on this mathematical prediction model, a real-time prediction scheme based on adaptive model parameters is proposed. The scheme adopts equal-dimensional innovation and rolling prediction method, which can make full use of WAMS real-time measurement data and continuously update the sample data to improve prediction performance. Model parameter adaptability. Finally, the rapidity and effectiveness of the transient instability identification based on the predicted trajectory are simulated and verified in the New England 10-machine 39-bus system. The results show that the method can effectively improve the rapidity of transient instability identification, which can be used for subsequent emergency. Control to get more time.

This paper presents an efficient computational method for time series clustering and application concerning research funding of universities directly under Minster of Education of People Republic of China. Presented approach was based on extraction of trend features with Haar wavelet decomposition from time series data and their use in feature-based agglomerative hierarchical clustering of monthly measured research funding income data. This method could be implemented for users who desire to manage research funding of all universities.

RNA viruses are a major human health threat. The life cycles of many highly pathogenic RNA viruses like influenza A virus (IAV) and Lassa virus depends on host mRNA, because viral polymerases cleave 5'-m7G-capped host transcripts to prime viral mRNA synthesis ("cap-snatching"). We hypothesized that start codons within cap-snatched host transcripts could generate chimeric human-viral mRNAs with coding potential. We report the existence of this mechanism of gene origination, which we named "start-snatching." Depending on the reading frame, start-snatching allows the translation of host and viral "untranslated regions" (UTRs) to create N-terminally extended viral proteins or entirely novel polypeptides by genetic overprinting. We show that both types of chimeric proteins are made in IAV-infected cells, generate T cell responses, and contribute to virulence. Our results indicate that during infection with IAV, and likely a multitude of other human, animal and plant viruses, a host-dependent mechanism allows the genesis of hybrid genes.