Numerical Simulation of Large-Scale Internal Seiche in Lake Inawashiro

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Identifying exogenous and endogenous activity in social media

The occurrence of new events in a system is typically driven by external causes and by previous events taking place inside the system. This is a general statement, applying to a range of situations including, more recently, to the activity of users in Online social networks (OSNs). Here we develop a method for extracting from a series of posting times the relative contributions of exogenous, e.g. news media, and endogenous, e.g. information cascade. The method is based on the fitting of a generalized linear model (GLM) equipped with a self-excitation mechanism. We test the method with synthetic data generated by a nonlinear Hawkes process, and apply it to a real time series of tweets with a given hashtag. In the empirical dataset, the estimated contributions of exogenous and endogenous volumes are close to the amounts of original tweets and retweets respectively. We conclude by discussing the possible applications of the method, for instance in online marketing.Comment: 5 figure

Clinical Utility of 4C Mortality Scores among Japanese COVID-19 Patients: A Multicenter Study

Background: We analyzed data from COVID-19 patients in Japan to assess the utility of the 4C mortality score as compared with conventional scorings. Methods: In this multicenter study, COVID-19 patients hospitalized between March 2020 and June 2021, over 16 years old, were recruited. The superiority for correctly predicting mortality and severity by applying the receiver operating characteristic (ROC) curve was compared. A Cox regression model was used to compare the length of hospitalization for each risk group of 4C mortality score. Results: Among 206 patients, 21 patients died. The area under the curve (AUC) (95% confidential interval (CI)) of the ROC curve for mortality and severity, respectively, of 4C mortality scores (0.84 (95% CI 0.76-0.92) and 0.85 (95% CI 0.80-0.91)) were higher than those of qSOFA (0.66 (95% CI 0.53-0.78) and 0.67 (95% CI 0.59-0.75)), SOFA (0.70 (95% CI 0.55-0.84) and 0.81 (95% CI 0.74-0.89)), A-DROP (0.78 (95% CI 0.69-0.88) and 0.81 (95% CI 0.74-0.88)), and CURB-65 (0.82 (95% CI 0.74-0.90) and 0.82 (95% CI 0.76-0.88)). For length of hospitalization among survivors, the intermediate- and high- or very high-risk groups had significantly lower hazard ratios, i.e., 0.48 (95% CI 0.30-0.76)) and 0.23 (95% CI 0.13-0.43) for discharge. Conclusions: The 4C mortality score is better for estimating mortality and severity in COVID-19 Japanese patients than other scoring systems