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There is a huge amount of information generated in online social networks, which is filled with a lot of rumors. The spread of a rumor often leads to the generation of a causal related rumor, and when users believe the first kind of rumor, the probability of being influenced by another causal related rumor is larger. Therefore, the influence probability will change with the process of rumor spreading. In this paper, we design the Causal Rumors Enhance Cascade ( $CREC$ ) model to describe the spreading process of causal related rumors. Then we attempt to select a set of seed users that minimizes the number of users expected to be influenced by rumors, which we call the Causal Related Rumors Controlling (CRRC) problem. The main challenges of this problem are that the influence probability is constantly changing during the spread process, so the reverse sampling technique cannot be used, and the greedy mechanism is not suitable for massive-scale datasets. For the sake of overcoming these challenges and solving the problem, we put forward the Degree Trigonometric Metrology (DTM) algorithm, which uses the property of three-directed circles in the directed network to select seed nodes. Finally, experiments on three massive-scale datasets show that our algorithm outperforms the other algorithms.

Liver cancer has become an important public health problem. In this study, bibliometrics and visual analysis were performed on the literature related to the risk factors and prevention of liver cancer, in order to understand the latest research progress of the risk factors and prevention of liver cancer. The Web of Science database was used as a retrieval platform to retrieve the published research results from 2012 to 2023. CiteSpace and VOSviewer were utilized for bibliometrics and visual analysis. A total of 2388 articles were screened according to exclusion criteria. Between 2012 and 2018, the number of articles published fluctuated. From 2018 to 2023, the number of published documents showed a steady upward trend. The 3 journals with the most publications are World Journal of Gastroenterology, PLOS ONE, and Hepatology. The United States and China are the countries with the most publications, while Harvard University, the National Institutes of Health and the University of Texas System are the 3 institutions with the most publications. Keywords such as hepatitis B virus, hepatitis C virus, alcohol, obesity, recrudescence rate, global burden are hot words in the field of liver cancer risk factors and prevention. The current research mainly focuses on the influence of environmental factors, behavioral lifestyle and biological factors on liver cancer, as well as the primary and secondary prevention of liver cancer, but there are still many undetermined factors to be explored.

In mass analysis of proteins, mass spectrometry directly measures the mass to charge ratios of ionized proteins and promises higher accuracy than that of indirect approaches measuring other physicochemical properties, provided that the charge states of detected ions are determined. Accurate mass determination of heterogeneously glycosylated proteins is often hindered by unreliable charge determination due to the insufficient resolution of signals from different charge states and inconsistency among mass profiles of ions in individual charge states. Limited charge reduction of a subpopulation of proteoforms using electron transfer/capture reactions (ETnoD/ETnoD) solves this problem by narrowing the mass distribution of examined proteoforms and preserving the mass profile of the precursor charge state in the reduced charge states. However, the limited availability of ETnoD/ETnoD function in commercial instruments limits the application of this approach. Here, utilizing a range of charge-dependent and accuracy-affecting spectral features revealed by a systematic evaluation at levels of both the ensemble and subpopulation of proteoforms based on theoretical models and experiments, we developed a limited charge reduction workflow that enables using collision-induced dissociation and higher energy collisional dissociation, two widely available reactions, as alternatives to ETnoD/ETnoD while providing adequate accuracy. Alternatively, substituting proton transfer charge reduction for ETnoD/ETnoD provides higher accuracy of mass determination. Performing mass selection in a window-sliding manner improves the accuracy and allows profiling of the whole proteoform distribution. The proposed workflow may facilitate the development of universal characterization strategies for more complex and heterogeneous protein systems.