Modeling directed weighted network based on event coincidence analysis and its application on spatial propagation characteristics.

The problem of synchronicity quantification, based on event occurrence time, has become the research focus in different fields. Methods of synchrony measurement provide an effective way to explore spatial propagation characteristics of extreme events. Using the synchrony measurement method of event coincidence analysis, we construct a directed weighted network and innovatively explore the direction of correlations between event sequences. Based on trigger event coincidence, the synchrony of traffic extreme events of base stations is measured. Analyzing topology characteristics of the network, we study the spatial propagation characteristics of traffic extreme events in the communication system, including the propagation area, propagation influence, and spatial aggregation. This study provides a framework of network modeling to quantify the propagation characteristics of extreme events, which is helpful for further research on the prediction of extreme events. In particular, our framework is effective for events that occurred in time aggregation. In addition, from the perspective of a directed network, we analyze differences between the precursor event coincidence and the trigger event coincidence and the impact of event aggregation on the synchrony measurement methods. The precursor event coincidence and the trigger event coincidence are consistent when identifying event synchronization, while there are differences when measuring the event synchronization extent. Our study can provide a reference for the analysis of extreme climatic events such as rainstorms, droughts, and others in the climate field.

Identifying the spatiotemporal organization of high-traffic events in a mobile communication system using event synchronization and complex networks.

In mobile communication systems, congestion is related to high-traffic events (HTEs) that occur in the coverage areas of base stations. Understanding, recognizing, and predicting these HTEs and researching their occurrence rules provides theoretical and decision-making support for preventing system congestion. Communication sectors are regarded as nodes, and if HTEs occur synchronously among sectors, then the corresponding nodes are connected. The total number of synchronous HTEs determines the edge weights. The mobile-communication spatiotemporal data are mapped to a weighted network, with the occurrence locations of HTEs as the basic elements. Network analysis provides a structure for representing the interaction of HTEs. By analyzing the topological features of the event synchronization network, the associations among the occurrence times of HTEs can be mined. We find that the event synchronization network is a small-world network, the cumulative strength distribution is exponential, and the edge weight obeys a power law. Moreover, the node clustering coefficient is negatively correlated with the node degree. A congestion coefficient based on several topological parameters is proposed, and the system congestion is visualized. The congestion coefficient contains information about the synchronous occurrence of HTEs between a sector and its neighbors and information about the synchronous occurrence of HTEs among its neighbors. For the mobile communication system considered in this study, the congestion coefficient of a large number of sectors is small and the risk of system congestion is low.

Combination of the gamma-glutamyltransferase-to-prealbumin ratio and other indicators may be a novel marker for predicting the prognosis of patients with hepatocellular carcinoma undergoing locoregional ablative therapies.

OBJECTIVE: The aim of this study was to investigate the prognostic significance of the serum γ-glutamyltransferase (γ-GT)-to-prealbumin ratio (GPR) and whether combining this ratio with other parameters can lead to an improved prognostic value for patients with hepatocellular carcinoma (HCC) undergoing transcatheter arterial chemoembolization (TACE) combined with local ablation therapy. METHODS: A total of 235 HCC patients who were treated with combined therapies were retrospectively analyzed. The demographic data and clinicopathological data were collected. A fibrinogen (Fib)-GPR score of 2 was assigned to patients with elevated Fib and GPR values, and a score of 1 or 0 was assigned to patients with one or neither of these two markers, respectively. In addition, an N-score of 2 was assigned to patients with low neutrophil and high GPR values, and a score of 1 or 0 was assigned to patients with one or neither of these two markers, respectively. The optimal cutoff values and prognostic roles of GPR and other markers were identified according to the time-dependent receiver operating characteristic (ROC) curves and Youden's index. RESULTS: Multiple tumors, high levels of α-fetoprotein (AFP) and Fib, as well as a high GPR, were found to be independent risk factors in recurrent patients, while multiple tumors, a low neutrophil count, and a high GPR were associated with reduced overall survival (OS) in patients with HCC who received combined therapies. Patients with a Fib-GPR score of 2 and N-GPR score of 2 had poor recurrence-free survival (RFS) and OS, respectively. CONCLUSIONS: Fib-GPR and N-GPR scores may be helpful in predicting both recurrence and the prognosis of HCC patients, thereby assisting in the process to make a true clinical decision and optimize therapeutic options.