COVID-19 trends across borders: Identifying correlations among countries.

Objectives: To enhance the accuracy of forecasting future coronavirus disease 2019 (COVID-19) cases and trends by identifying and analyzing correlations between the daily case counts of different countries reported between January 2020 and January 2023, to uncover significant links in COVID-19 patterns between nations, allowing for real-time, precise predictions of disease spread based on observed trends in correlated countries.

Methods: Daily COVID-19 cases for each country were tracked between January 2020 and January 2023 to identify correlations between nations. Current case data were obtained from reliable sources, such as Johns Hopkins University and the World Health Organization.

Predicting COVID-19 future trends for different European countries using Pearson correlation.

The ability to accurately forecast the number of COVID-19 cases and future case trends would certainly assist governments and various organisations in strategising and preparing for the newly infected cases well in advance. Many predictions have failed to foresee future COVID-19 cases due to the lack of reliable data; however, such data are now widely available for predicting future trends in COVID-19 after more than one and a half years of the pandemic. Also, various countries are closely monitoring other countries that are experiencing a surge in COVID-19 cases in the expectation of similar scenarios, but this does not always produce correct results, as no research has identified specific correlations between different countries in terms of COVID-19 cases.

The Significance of Occupants' Interaction with Their Environment on Reducing Cooling Loads and Dermatological Distresses in East Mediterranean Climates.

Global endeavors to respond to the problems caused by climate change and are leading to higher temperatures inside homes, which can cause skin conditions (such as eczema), lethargy, and poor concentration; disturbed sleep and fatigue are also rising. The energy performance of buildings is influenced by interactions and associations of numerous different variables, such as the envelope specifications as well as the design, technologies, apparatuses, and occupant behaviours. This paper introduces simple and sustainable strategies that are not dependent on expensive or sophisticated technologies, as they rely only on the actions practiced by the building's occupants (movable window shading, and nighttime natural ventilation) instead of completely relying on high-cost mechanical cooling systems in buildings located in the main Eastern Mediterranean climates represented in the country of Jordan.

Factorial analysis of diesel engine performance using different types of biofuels.

In this study, several bio-source-fuels like fresh and waste vegetable oil and waste animal fat were tested at different injector pressures (120, 140, 190, 210 bar) in a direct-injection, naturally aspirated, single-cylinder diesel engine with a design injection pressure of 190 bar. Using 2k factorial analysis, the effect of injection pressure (Pi) and fuel type on three engine parameters, namely, combustion efficiency (etac), mass fuel consumption (mf), and engine speed (N) was examined. It was found that Pi and fuel type significantly affected both etac and mf while they had a slight effect on engine speed.