Activity evaluation of metal oxide catalysts with different crystal structures has been an important prerequisite for industrial applications. This work systematically elucidates the structure-activity relationship of α-, β-, γ- and δ-MnO 2 catalysts toward the selective oxidation of benzyl...

Chitosan and its water-soluble derivatives have been widely used in biomaterials, but their disadvantages have hindered their widespread application. In this study, butyryl chitosan, a liposoluble chitosan derivative, was prepared by introducing butyryl groups into chitosan molecules through an...

In this paper, we propose a general methodology to characterize (i.e. develop the recursive equation systems for) the dynamic stochastic general equilibrium asset pricing problems (DSGE) with arbitrary numbers of agents and financial assets in a Lucas economy and propose a convergent numerical...

In this paper, we combine the theory of stochastic process and techniques of machine learning with the regression analysis, first proposed by Longstaff and Schwartz 2001 and apply the new methodologies on financial derivatives pricing. Rigorous convergence proofs are provided for some of the...

In this paper, we propose a general framework of optimal investment and a collection of trading ideas, which combine probability and statistical theory with, potentially, machine learning techniques. The trading ideas are easy to implement and their validity is justified by full mathematical...

In this paper, we introduce a clustering method to approximate the solution to a general Backward Stochastic Differential Equation with Jumps (BSDEJ). We show the convergence of the sequence of approximate solutions to the true one. The method is implemented for an application in finance....

In this paper, we provide insights on the prediction of asset returns via novel machine learning methodologies. Machine learning clustering-enhanced classification and regression techniques to predict future asset return movements are proposed and compared. Numerical experiments show good...

In this paper, we document a novel machine learning based bottom-up approach for static and dynamic portfolio optimization on, potentially, a large number of assets. The methodology overcomes many major difficulties arising in current optimization schemes. For example, we no longer need to...

Since the formation of intermetallic compounds at the copper-side interface for the duration of the copper/aluminum brazing process leads to a reduction in the mechanical properties of the brazing joint, and the diffusion and reaction process between the molten filler metal and the base material...