Sociocultural Space: On the ProЬlem ofExplanation and Understanding

The socio-cultural orientation of modernization processes changes the emphasis in the social development of mankind, emphasizes the need to determine the place and role of man in the world. The transformation of the socio-cultural space under the pressure of globalization dictates the need to understand the structure and functions that determine the vectors of development of the world community, changing the accents of evolution. Structurally, the socio-cultural space integrates the social and cultural potential of activities, including !оса! communities. It functionally ensures the reproduction of culture and sociality, sets the permissiЬle limits of reform, guaranteeing the preservation of socio-cultural integrity, implementing the functions of socialization, regulation, information, feedback.

Spread Mechanism and Control Strategies of Rumor Propagation Model Considering Rumor Refutation and Information Feedback in Emergency Management

The rumor-free equilibrium state and rumor-endemic equilibrium state are two symmetric descriptions of the status of a system. The constant spreading of rumors would affect the smooth operation of emergency management procedures and cause unnecessary social and economic loss. To reduce the negative effect of rumor propagation, in this paper, we introduce a compartmental model of rumor propagation, which considers the rumor refutation of public and information feedback. By deriving mean-field equations that describe the dynamics of the model, we use analytical and numerical solutions of these equations to investigate the threshold and dynamics of the model in both the closed system and open system. The results imply that the initial equilibrium point is not stable and there exists a rumor-free equilibrium point; in the open system, there exists a threshold beyond which rumors can spread; the stability of the initial equilibrium point is related to the threshold R0 = (φ*α)/μ, and there exists a rumor-endemic equilibrium point. The development process of rumor propagation can be divided into four stages: latent period, progressive period, intense period, and recession period. Under the influence of population, rumor spreading can exceed the threshold readily because the migration rate μ is usually less than the proportion of ignorants without critical ability φ, and the rumor spreading process in an open system presents a fluctuating development, the rumor would not disappear in this autonomous system. Based on the analysis, we propose some measures, such as providing open and efficient information queries and exchange platforms, etc.

Sequential Shortest Path Interdiction with Incomplete Information and Limited Feedback

We study sequential shortest path interdiction, where in each period an interdictor with incomplete knowledge of the arc costs blocks at most [Formula: see text] arcs, and an evader with complete knowledge about the costs traverses a shortest path between two fixed nodes in the interdicted network. In each period, the interdictor, who aims at maximizing the evader’s cumulative cost over a finite time horizon, and whose initial knowledge is limited to valid lower and upper bounds on the costs, observes only the total cost of the path traversed by the evader, but not the path itself. This limited information feedback is then used by the interdictor to refine knowledge of the network’s costs, which should lead to better decisions. Different interdiction decisions lead to different responses by the evader and thus to different feedback. Focusing on minimizing the number of periods it takes a policy to recover a full information interdiction decision (that taken by an interdictor with complete knowledge about costs), we show that a class of greedy interdiction policies requires, in the worst case, an exponential number of periods to converge. Nonetheless, we show that under less stringent modes of feedback, convergence in polynomial time is possible. In particular, we consider different versions of imperfect randomized feedback that allow establishing polynomial expected convergence bounds. Finally, we also discuss a generalization of our approach for the case of a strategic evader, who does not necessarily follow a shortest path in each period.

How Does Risk-Information Communication Affect the Rebound of Online Public Opinion of Public Emergencies in China?

The rebound of online public opinion is an important driving force in inducing a secondary crisis in the case of public emergencies. Effective risk-information communication is an important means to manage online public opinion regarding emergencies. This paper employs fuzzy-set qualitative comparative analysis to discover which conditions are combined and may result in the rebound of online public opinion. Five conditions were selected: the type of public emergency, messengers, message attributes, audience, and information feedback. The study used a sample of 25 major public emergencies that occurred between 2015 and 2020 in China. The type of public emergency, audience, and information feedback emerged as critical influencing factors. Message attributes promote the rebound of online public opinion regarding public health emergencies, while messengers play a traction role in the rebound of online public opinion on other types of public emergencies. This study extends risk-information communication theory from the perspective of the type of emergency, explores the causes of rebounded online public opinion regarding public emergencies, and provides policies and suggestions for risk-information communication and online public-opinion governance during emergencies.

A Glider Simulation Model Based on Optimized Support Vector Regression for Efficient Coordinated Observation

Multi-gliders have been widely deployed as an array in nowadays ocean observation for fine and long-term ocean research, especially in deep-sea exploration. However, the strong, variable ocean currents and the delayed information feedback of gliders are remaining huge challenges for the deployment of glider arrays which may cause that the observed data cannot meet the study needs and bring a prohibitive cost. In this paper, we develop a Glider Simulation Model (GSM) based on the support vector regression with the particle swarm optimization (PSO)-SVR algorithm to integrate the information feedback from gliders and ocean current data for rapid modeling to effectively predict the gliders’ trajectories. Based on the real-time predictive information of the trajectories, each glider can select future movement strategies. We utilize the in-suit datasets obtained by sea-wing gliders in ocean observation to train and test the simulation model. The results show that GSM has an effective and stable performance. The information obtained from the modeling approaches can be utilized for the optimization of the deployment of the glider arrays.