Background: The reproduction number (R 0 ) is vital in epidemiology to estimate the number of infected people and trace close contacts. R 0 values vary depending on social activity and type of gathering events that induce infection transmissibility and its pathophysiology dependence. Objectives: In this study, we estimated the probable outbreak size of COVID-19 clusters mathematically using a simple model that can predict the number of COVID-19 cases as a function of time. Methods: We proposed a mathematical model to estimate the R 0 of COVID-19 in an outbreak occurring in both local and international clusters in light of published data. Different types of clusters (religious, wedding, and industrial activity) were selected based on reported events in different countries between February and April 2020. Results: The highest R 0 values were found in wedding party events (5), followed by religious gathering events (2.5), while the lowest value was found in the industrial cluster (2). In return, this will enable us to assess the trend of coronavirus spread by comparing the model results and observed patterns. Conclusions: This study provides predictive COVID-19 transmission patterns in different cluster types based on different R 0 values. This model offers a contact-tracing task with the predicted number of cases, to decision-makers; this would help them in epidemiological investigations by knowing when to stop.

No abstract

No abstract

In this paper, an energy end-use model of the Jordanian SMEs industries is presented. The industrial sector in Jordan consumes about 23% of the country's total energy. To establish the end-use model, a survey covering 150 facilities of different types of industries was conducted. The results show that the main electricity enduse consumers are electrical motors with a share of 55% of the total electricity consumption. On the other hand, fossil fuel is mainly used for hot water and steam generation with diesel fuel as a dominant fuel. The results of the study can be considered as an insight into the energy usage pattern of the Jordanian industrial sector for the policy maker. Furthermore, the results could provide important guidelines and insights for future research and development allocations and energy projects.

Several locally available materials were tested for hydrogen storage. This study was conducted theoretically using suitable software. The materials tested were Sweileh |San, Zeolite, Nickel, Magnesium and Lanthanium. It was found that using the locally available Sweileh sand alone did not give promising results. Pure Magnesium showed the best results followed with Nickle then lanthanium. On mixture basis, adding Magnesium to local Sweileh sand improved its storage ability more than adding other materials like Ni or La.