The world is embroiled in a pandemic of a new coronavirus at the end of 2019 and early in 2020, with such a large scale that it has severely involved the political, economic, and social systems in most countries around the world. The scale of the crisis is so widespread that many experts believe that the post-corona world will be substantially different from the pre-corona world. In the face of this massive epidemic, how people perceive risk and how to risk is communicated, plays a central role in deciding and choosing people's behavior. Fighting with this emerging phenomenon requires mobilizing all the possibilities of society and helping all people in the field of empathy and altruism. In this article, we briefly review aspects of the important concept of risk perception and communication in this pervasive crisis.

In this paper, a private telephone communication network of an electrical energy distribution company has been studied analytically and through discrete event system simulation. Considering the pitfalls and difficulties associated with the analytical approach in designing such a network and the power and performance of a simulation methodology in this regard, a simulation model was developed using GPSS/H simulation language. After data collection and analysis, model development and validation, initial transient study and design of experimental phases, the model was applied to determine the operating performance of the current system, as well as to evaluate the performance of any newly designed network before the installation and implementation of the new equipment.

Transportation networks are essential infrastructures of the present societies and are progressively growing in importance. Therefore, the network should develop in accordance with the society's needs. Transportation network expansion is a costly process and often is not returnable. Usually, there are not enough resources to satisfy the hole future demand; therefore, available resources must be utilized in an efficient manner. It has been shown that classic transportation planning approach and decision theory should be revised and a more flexible planning approach must be taken to deal with the uncertainties and the internal or external changes. The concept of flexibility has been used in many scientific disciplines including transportation planning. Most of the studies of network flexibility have focused on the concept of capacity flexibility. network flexibility can be considered as an effective factor in network reliability. A network should be flexible enough to be considered as a reliable one. In this study, a model of transportation network design has been developed based on increasing the flexibility, especially increasing the survivability of the network facing daily variations including daily crashes or rush-hour blockings. network survivability is the ratio of the demand that will be answered after the occurrence of a failure in a network. Improving the properties of a network will affect the flow pattern all around the network. In most studies, utility theory has been used to model user answer to realize the model to a greater degree. It has been shown that utility theory faces basic shortcomings and regret theory has been introduced as an alternative way to handle the users' behavior. In this study, a stochastic user equilibrium has been developed based on regret theory to model the user reply to the network expansion. Results show that the network improves based on the survivability model, which has better performance when a link is blocked.

To Adequately design density and distribution of rain- gauges in rainfall networks of each region, is an effective step toward success of water projects, regional programming and proper use of information. In this research, the locations of new rain- gauges in rainfall network of Gav-khuni basin have been determined using transinformation entropy concept based on annual rainfall data of stations (1356-1385).Sequential and genetic algorithms have been used in order to seleet the proper rain- gauges sites. Two objectives of maximizing the minimum transinformation entropy and maximizing the mean of transinformation entropy have been defined for each algorithm. Then the performances of different models have been compared. The results imply on the better performance and relative supremacy of genetic algorithm, with maximizing the minimum entropy (maximum supremacy is +1.31, +1.34 and +0.12% in zone 1, 2 and 3, respectively) and maximizing the mean entropy (maximum supremacy is +0.35, +0.21 and +0.02% in zone 1, 2 and 3 respectively) objectives to sequential algorithm.