In Pakistan, water pollution is a cause of numerous health issue and water stress. The aim of writing this paper is to empirically investigate the impact of industrialization, foreign direct investment, and economic growth along with energy consumption on total suspended solids in the Indus River, which is used as a proxy for water pollution. The authors employed ARDL estimation to achieve the research objective. The findings revealed that in long-run economic growth, foreign direct investment inflows and industrialization have a positive influence on water pollution in the Indus River. Still, on the other hand, due to sustainable energy production, water pollution is falling in the Indus River. At the same time, in the short-run, economic growth causes reduction in total suspended solids, whereas industrialization is still a major cause of water pollution in the Indus River.

Root finding Methods like the Bisection Method, Newton Raphson Method, Secant Method, and False Position Method have been revisited through a new approach. EACH METHOD’S user-friendly GUI computer programs have been developed on an Excel spreadsheet. A root locator graph is introduced in the spreadsheets, which helps identify the initial guess(es) required to calculate root using these methods. All real roots are now easily calculable by any of the four methods. The detailed steps to calculate roots are also shown on the spreadsheet. The spreadsheet can be made ready for the next calculation with a single click. We have developed a technique for Excel that helps accept polynomial in variable ‘x’ without directly mentioning cell location.

The notion of this research was to find the climatological parameter of a location (whose data are notavailable) with the help of climatological parameters of its neighboring locations. In this study, we supposed Hyderabad as such a location; its neighboring cities Karachi, Badin, and Nawabshah form a triangle, and Hyderabad lies within the perimeter of the triangle. The task was to find the temperature distribution of Hyderabad using the temperatures of its neighboring cities. Two different methods, Artificial Neural Networks and multiple regression analysis, have been used to find the temperature of Hyderabad by using the temperature distribution of neighboring cities, Karachi,Nawabshah, and Badin. ANN with one hidden layer of 10 neurons is used, which connect three known temperature of Karachi, Nawabshah, and Badin to the output temperature of Hyderabad. Amultiple regression analysis with three independent variables, i.e., the temperatures of Karachi,Nawabshah, and Badin, are used to find a linear equation of multiple variables for the temperature of Hyderabad.Both ANN and multiple regression analysis produce an excellent result, and it is suggested toimplement the technique where direct measurement of the climatological data system is not present.

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Conventional teaching is rapidly changing, and online and simulated software are adding up in teaching. Simulations on spreadsheets have become popular due to their ubiquitous and easily understandable. In this paper, we demonstrate three physics topics: the motion of a charged particle in a uniform magnetic field, the motion of a projectile, and the simple harmonic motion of a simple pendulum. The third example is a demonstration of an experiment on a simple pendulum to find the time period of a simple pendulum and study the amplitude’s effect on it. Students can perform the whole experiment on the spreadsheet in real-time.