Abstract: A method and formulation for fluids, such as drinking water, containing plant phytochemicals are disclosed. Some plants can survive in water without a root system, and the formulation includes fluid, such as water, with one or more of the plants maintained in the fluid. Cold storage resulted in enhanced production and excretion of phytochemicals from the plants into the fluid, including bacosides and bacopasides. These phytochemicals have been shown to exhibit antioxidant properties, promote memory and provide additional health benefits, as well as replace bottled water or other fluids as a means to ensure proper hydration. The fluids are useful for enhancing alertness.

Abstract: A method and formulation for fluids, such as drinking water, containing plant phytochemicals are disclosed. Some plants can survive in water without a root system, and the formulation includes fluid, such as water, with one or more of the plants maintained in the fluid. Cold storage resulted in enhanced production and excretion of phytochemicals from the plants into the fluid, including bacosides and bacopasides. These phytochemicals have been shown to exhibit antioxidant properties, promote memory and provide additional health benefits, as well as replace bottled water or other fluids as a means to ensure proper hydration. The fluids are useful for enhancing alertness.

Abstract: The present invention relates to a method for generating hypotheses automatically from graphical models built directly from data. The method of the present invention links three key scientific concepts to enable hypothesis generation from data driven hypothesis-models: including the use of information theory based measures to identify informative feature subsets within the data; the automatic generation of graphical models from the informative data subsets identified from step one; and the application of optimization methods to graphical models to enable hypothesis generation. The integration of these three concepts can enable scalable approaches to hypothesis generation from large, complex data environments. The use of graphical models as the model representation can allow prior knowledge to be effectively integrated into the modeling environment.

Abstract: The present invention relates to a method for generating hypotheses automatically from graphical models built directly from data. The method of the present invention links three key scientific concepts to enable hypothesis generation from data driven hypothesis-models: including the use of information theory based measures to identify informative feature subsets within the data; the automatic generation of graphical models from the informative data subsets identified from step one; and the application of optimization methods to graphical models to enable hypothesis generation. The integration of these three concepts can enable scalable approaches to hypothesis generation from large, complex data environments. The use of graphical models as the model representation can allow prior knowledge to be effectively integrated into the modeling environment.