Choices to general relativity are actual speculations that endeavor to depict the marvel of attractive energy in rivalry to Einstein's hypothesis of general relativity. There have been various efforts to build an ideal hypothesis of gravity. These endeavors can be parted into four general classifications dependent on their extension. In this article, we examine direct choices to general relativity, which don't include quantum mechanics or power unification. Different speculations which do endeavor to develop a hypothesis utilizing the standards of quantum mechanics are known as hypotheses of quantized gravity. At long last, the most driven hypotheses endeavor to both put gravity in quantum mechanical terms and bring together powers; these are called speculations of everything. None of these choices to general relativity have acquired wide acknowledgment. General relativity has withstood numerous tests, staying steady with all perceptions up until this point.

Albert Einstein introduced the hypotheses of extraordinary relativity and general relativity in distributions that either contained no proper references to past writing, or alluded uniquely to few his archetypes for principal results on which he based his speculations, most eminently to crafted by Henri Poincaré and Hendrik Lorentz for exceptional relativity, and to crafted by David Hilbert, Carl F. Gauss, Bernhard Riemann, and Ernst Mach for general relativity. Hence, claims have been advanced about the two speculations, attesting that they were defined, either completely or to a limited extent, by others before Einstein. At issue is the degree to which Einstein and different others ought to be credited for the plan of these hypotheses, in light of need contemplations.

New instructive guidelines execution focuses on the projective start of preparing in school instruction. Along these lines, thought of instructive action just as the interaction of getting prepared information ought to be deserted. Along these lines the significance of the examined issue is validated by the need to foster deliberate works associated with the presentation of between subject tasks into science instructors' educational action as arithmetic has a wide application in different sciences, however, at exercises, it is abandoned because of time limits and deficient numerical mechanical assembly school understudies have. All that said determines the objective of the paper: to characterize chances of venture based action application in incorporation of numerical and normal science disciplines and improvement of deliberate suggestions on its expansive application over the span of preparing in the subject.

Cancer has a long-time history in our human health experience. Practically, one-fifth of the disease was caused by virus infection. Thus, it is important for us to understand the virus-cancer infection mechanism. Statistically, we may perform the necessary causality regression analysis in such situation to build up the corresponding model just like my previous case in influenza-weather infection. In the present research, I will interact the systems of differential equations (Lorenz System) with my HKLam theory and figure out the recursive result that we may get. Then we may go ahead for the corresponding policy generated from the dynamic programming that can solve the Markov Decision Process. In addition, we may apply the HKLam theory to the chaotic time series and compare the model with machine learning one for a better selection while otherwise failure is explained. Finally, I will also discuss a novel mathematical method in determining the saddle point in Lorenz attractor together with the gradient descent. The aim is to find the equilibrium for the Lorenz attractor with given initial conditions. It is hope that the mathematics-statistics interaction together with the causal regression (Artificial Intelligence) model may finally help us fight against those diseases like virus-infected cancer or others.

In this article it is tried to work out on the mathematics of stochastic version of Von-Bertalanffy power law model to find an explicit solution and the MLEs of the model parameters are also worked out.Then this model is applied to the COVID infection data(First wave data) of South Korea after observing the nature of growth and some comparisons are made with stochastic Gompertz model and stochastic Logistic model in this context and the stochastic Von-Bertalanffy power law model performs better than the other two atleast here in this case. It is observed that most of the infected persons by this virus has experienced a mild to moderate respiratory problems and many of them has recovered under normal treatments, but for aged persons who were suffering from CVD (cardio vascular disease), severe respiratory problems, diabetes, cancer etc. i.e, persons with co-morbidity has faced serious trouble after getting infected(COVID positive)([13]).