The present study attempts to shed lights on the way "climate-related usual and disastrous events" are forecasted by Iran METEOROLOGICAL Organization and how they are covered by IRIB. This research is carried out through a "content analysis" of news items broadcast various provincial newscasts as well as Channel One newscast at 21: 00 and IRINN newscast at 13: 00 during the years of 2014, 2015 and 2016. The results of each newscast have been compared. For practical aims, as survey was conducted and the views of METEOROLOGICAL experts as well as news editors-in-chief with regard to the way weather-related news events are managed were gathered consequently. The findings indicated that the rhetoric and terminology used in almost half of the weather reports on dangerous and disastrous events were not "sensitizing and warning". About 22 percent of critical events were not forecasted in the METEOROLOGICAL Organization's announcement and 33 percent of weather reports were not consistent with the organization's forecast announcements. In 92.5 percent of weather reports, no experts and employers-at-risk were interviewed for training implications. The forecasts of 58.5 percent of dangers were reflected as usual weather events with low priority at the end of newscasts and with the same amount of time (55 percent of weather reports on usual events and 47 on critical events lasted from one to two minutes). Literature review shows that no other study has been carried out on the subject about IRIB. Therefore, the present work is a new and innovative research.

The purpose of this research was to investigate the trend of annual changes in Yazd station's METEOROLOGICAL parameters including minimum and maximum average daily temperature and average daily precipitation (1961-2005), as well as the predicted annual mean of these parameters in the three upcoming thirty years of the 2040s, 2070s and 2100s, by the SDSM model, under RCP2. 6, RCP4. 5, RCP8. 5, A2, and B2 scenarios. Accordingly, by using the coefficient of determination and the MAE, R2, RMSE indicators, we evaluated the data generated by the SDSM model in comparison with the observed data in the base period. The lowest value of R2 based on the calibration and validation of the mean values of observed and simulated SRES was obtained for precipitation (86 and 80%). In terms of the R2 evaluation index, the accuracy of the small-scaled results of the minimum and maximum average temperature values was more than that of the average precipitation; however, in terms of the MAE and RMSE evaluation indicators, the accuracy of the small-scaled results of the average precipitation was higher than that of the minimum and maximum average temperature values. Subsequently, HadCM3 large-scale climatological data was used to predict the future periods (2010-2100). The results indicated that the temperature was raised in all months and seasons and the precipitation was decreasing in most of them, thereby confirming that the climate was changing in the studied region...

Nowadays enhancement of occurrence, spread of damages and the appearance of losses which arise from the technology and knowledge products, shows necessity of the remedies beyond the classical boundaries of civil responsibility alongside the changing general thought. Accomplishment of most of these needs occur with the aid of the social remedies systems which are supported and also situated in civil remedies systems. "Social RISKS" alongside the "socialization of RISKS" are new concepts which are containing all of the damages beyond the civil responsibilities of jurisdiction and its redress ways. The terms are multifunctional and it increases their ambiguity. Exposing, surveying of various definitions, explaining the meaning of socialization of risk and its reason are the purposes of this research.

The correct selection of typical METEOROLOGICAL year is an important factor for accurate building energy simulation. In this study, the Sandia method has been applied to analyze the measured weather data of a 14-year period (1992–2005) in Tehran and to select the proper data for the typical METEOROLOGICAL year. Also, typical METEOROLOGICAL year has been generated by using the Meteonorm and Weathergenrator softwares. Then the results of the Sandia method and the two mentioned softwares have been compared with long term average measured data for main parameters in the weather data file. It was found that, the results of the Sandia method has good agreement with the long term average measured data but the created TMY data by the Weathergenrator and Meteonorm softwares have not good agreement with the long term average measured data.

Introduction: Supply of medicine as a strategic product in any health system is a top priority. Pharmaceutical companies, a major player of the drug supply chain, are subject to many RISKS. These RISKS disrupt the supply of medicine in many ways such as their quantity and quality and their delivery to the right place and customers and at the right time. Therefore risk identification in the supply process of pharmaceutical companies and mitigate them is highly recommended.Objective: In this study it is attempted to investigate pharmaceutical supply chain RISKS with perspective of manufacturing companies.Methods: Scopus, PubMed, Web of Science bibliographic databases and Google scholar scientific search engines were searched for pharmaceutical supply chain risk management studies with 6 different groups of keywords. All results found by keywords were reviewed and none-relevant articles were excluded by outcome of interests and researcher boundaries of study within 4 steps and through a systematic method.Results: Nine articles were included in the systematic review and totally 50 main RISKS based on study outcome of interest extracted which classified in 7 categories. Most of reported RISKS were related to supply and supplier issues.Organization and strategy issues, financial, logistic, political, market and regulatory issues were in next level of importance.Conclusion: It was shown that the majority of RISKS in pharmaceutical supply chain were internal RISKS due to processes, people and functions mismanagement which could be managed by suitable mitigation strategies.

Considering the increase in the world population, human needs for food and energy have been on the increase too. One of the main tasks of the heads in governments is to provide the needed energy for the people in their countries. As the fossil sources are towards their ends and they also are the source of greenhouse gas emissions causing environmental pollution, shifting to renewable sources of energy is an indispensable alternative for most countries. The sun is undoubtedly the most important source of renewable energy. To assess the accessible solar radiation in Mashhad Province from the ordinary METEOROLOGICAL data via Artificial Neural Network (ANN), a survey was conducted. Results indicated that ANN with six variable inputs of: daily mean temperature, daily relative humidity, daily sunshine duration, daily extraterrestrial radiation, number of days of the year and daily dry temperature, with two hidden layers including 37 and 18 neurons respectively, presented a good estimation of a high accuracy for solar radiation. The measured R, MAE, MSE and RMSE were recorded 0.9533, 1.4391, 4.1790, and 2.0443, respectively. Therefore, as for Mashhad, and the regions of similar climate to that of Mashhad, where there is no easy access to solar radiation data, one can use ordinary METEOROLOGICAL data, as above, to estimate the solar radiation with a high degree of acceptable accuracy.