By targeting a very specific type of algorithm that would be constructed from the use of differentials defined in a very unique algebraic configuration, this has succeeding in exposing what appears to be a complete unified theory of analytical integration in Calculus. The unique mathematical properties of this algorithm could be exploited much further for establishing the basic fundamental building blocks of what is known today as the theory of everything. Under such a unified theory of integration, the analytical solutions of all fundamental PDEs of Physics and Engineering may now be potentially resolved in their complete original form thereby avoiding the uncertainty of having to apply various types of transformation processes just for reducing the PDEs to more integrable type.

The classical definition of the theory of everything according to many physicists is a hypothetical single, coherent theoretical framework of physics that fully explains and links together all physical aspects of the universe. We ask ourselves "how can such a grandiose physical theory for explaining everything about this universe be possible without the application of an equivalent grandiose mathematical theory that would explain everything about the complete integration of all differential equations (DEs) ". Since DEs are universal and not linked to any specific area of the Physical Sciences there is no evidence to support that Modern Physics is the only subject by which a complete theory of everything may be entirely constructed from. Instead, it is only by consolidating the general analytical solutions of all PDEs describing a unique physical system such as the Maxwell equations, the Einstein Field equations and the Navier-Stokes equations all in terms of fundamental theorems that would lead to the construction of some gigantic theory capable of explaining everything about our physical universe. This of course can only be possible under a complete unified theory of analytical integration such as the one that will be presenting in this talk.

Biography

Mike Mikalajunas has a degree in Mechanical Engineering with a specialization in fluid mechanics. He has taken part in a number of research projects with various other faculty members that would include a long term flight simulation project in conjunction with Canadian Aviation Electronics (CAE) and also some extensive research and development work related to mechanical vibrations. There were also a number of specialized computer projects he had been involved in with a computer science department that would include some development work for the software program AUTO (continuation and bifurcation problems in ordinary differential equations).

Back in the mid 80's the PC hardware and software industry was in the process of becoming more and more evolved for the health care industry. Mike Mikalajunas along with Dr. Robert Carbone has founded a software company specifically for providing much greater software accessibility of the PC to various large manufacturing corporations.

Because of his extensive software involvement with this consulting company, he has been assigned to maintain and support the company's leading statistical software within Boehringer Ingelheim pharmaceutical division and at Novartis Animal Health division which is now owned by Elanco a division of Eli Lilly. Under a special software license agreement he would be responsible for running the sales forecasting and assumption reporting software on a monthly basis for all international division of both Boehringer Ingelheim and Novartis in order to meet each of their own total manufacturing process requirements.

The growing popularity of the unique approach to integration by the proposed method of differentials has resulted into a number of independent requests for giving many such presentations to various other leading universities in both Canada and in the US. The same type of presentations were also given in the past to various major conferences as far away as in New Zealand involving pure and applied mathematics as well as in computational physics and engineering.