The desert areas of the playas are important due to the diversity of geomorphological landforms and the great potential for geo-tourism development. These areas can be provided using statistical and quantitative models to determine the areas with a higher geomorphological diversity value to land planners for the sustainable development. This research was conducted to evaluate the geomorphodiversity in Mesileh playas in Namak Lake and Hoz-e- Sultan region. The geomorphological landforms in this area were extracted using satellite images and field studies, Fragstats software and the eight quantitative indicators of the landscape METRICS include Patch Richness Density, Relative Patch Richness, Simpsons Evenness Index, Index Shannon Evenness, Shannons Diversity Index, Simpson's Diversity Index, Modified Simpson's Diversity Index, Modified Sahanon Evenness Index were exerted to evaluate the richness of geomorphological units in Masileh playas. The results indicate that the geomorphological units of alluvial fans, salt flats, salt mud flats and dunes, respectively, have the highest value among the landscape METRICS. In addition, from the point of view of the landscape METRICS, the northwest regions of Kashan and Abuzeydabad have the most incredible variety of geomorphology. This research showed that geomorphological units could be used as a suitable indicator in evaluating the diversity of the landscape, especially in flat areas with morphometric and geological diversity.

The purpose of this study was to design educational content of Green Chemistry METRICS for undergraduate chemistry students. Based on the purpose of the research, it was an applied-development type, and in terms of collecting and analyzing the data; a descriptive-analytical type is used. The statistical sample was a collection of books, articles, journals, and dissertations related to green chemistry which were selected and analyzed up to getting theoretical saturation. By reviewing related literature and investigating various sources on how to design the educational contents of the chemistry green, and also by directions of the field experts, during several revers phases of core coding, chapters were determined, then, according to the designated chapters, objectives were written for each topic in the target-content table. The results of this study showed that for the design of the content of training green chemistry measurements, two categories of mass measurements and environmental measurements can often be quantitatively evaluated in the twelve principles of green chemistry. In these two categories, there are various methods for assessing the greenness of a reaction (organic reaction synthesis) were identified, including atomic economy, reaction mass efficiency, material recovery parameter, environmental factor, process mass intensity, and effective mass efficiency are presented in a conceptual framework.

Wide Area Measurement System (WAMS) may be considered as the most important application in smart transmission grids. State Estimation has been considered as the kernel of WAMS since such a package extracts creditable states from the raw and noisey data. Indeed, WAMS creates data flow in order to achieve reliable and efficient energy flow. More data flow benefits the system operation but at the same time increases the cyber RISK of the system. This study aims to assess the cyber RISK of elements of WAMS. To do this, cyber dependency is modeled as the dependency graph and then such a graph is examined by two centrality METRICS (i. e. eigenvector and betweenness centralities). Two classes of nodes (i. e. State and Intermediate nodes) are detected in WAMS and simulation results show that the aforementioned centrality METRICS are able to assess such classes of nodes and the proposed method has the ability of designing resilient WAMS.

In recent years the main models for measuring Market RISK is Value-At-RISK models. Market RISK is the RISK that the portfolio investment value or asset value of financial institution will decrease due to some factors Such as: changes of asset prices, interest rate, market Volatility or market liquidity.In the following Research, We are trying to evaluate the efficiency of RISK METRICS model of J.P Morgan corporation And GARCH Type model for VAR estimation via index volatilities.For this purpose, we use TSE index data between 1382-1386 years in order to design and test model efficiency. This is done using a 1382-1384 TSE index data to estimate parameters of model and real data of 1385 and 1386 for credit viability of these models. Kupiec Likelihood Ratio (LR) that Calculate failure probability show us: it does not have a meaning difference between RISK METRICS and GARCH type models for market RISK estimation in 95% and 99% confidence levels. Both of these models are efficient to estimate market RISK (VAR).

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.