Abstract: A multiple layer cytometric test card includes a waste channel to receive biological waste from an area of the test card utilized for testing biological samples, a first waste storage compartment in a waste layer of the card having a top and a bottom in relation to an operating vertical orientation of the test card, and a capillary positioned along a vertical length of the first waste storage compartment, the capillary being open to the waste compartment along the vertical length of the waste compartment, wherein the waste channel is coupled to the capillary channel proximate the top of the waste storage compartment.

Abstract: One embodiment of the application provides a method and system for selecting a template characterizing a power plant from a template base, the template base including a plurality of templates and creating a power plant model of the power plant using the first template, the power plant model including a plurality of modules arranged in a hierarchical tree array having at least one tree branch, wherein each of the plurality of modules includes a plurality of attributes of the power plant that are arranged to be accessed by a data access layer using a tag name which includes names of ancestor modules in the tree branch. Additionally, the method and system also provides for mapping the plurality of attributes to specific applications of the power plant using the data access layer and configuring the power plant with the plurality of attributes using the data access layer.

Abstract: In an embodiment, a system and method provide a constraint on a genetic algorithm, and further provide dynamic programming capability to the genetic algorithm. The system and method then allocate load demand over a finite number of time intervals among a number of power generating units as a function of the constraint on the genetic algorithm and the dynamic programming capability of the genetic algorithm.

Abstract: In an embodiment, a system and method provide a constraint on a genetic algorithm, and further provide dynamic programming capability to the genetic algorithm. The system and method then allocate load demand over a finite number of time intervals among a number of power generating units as a function of the constraint on the genetic algorithm and the dynamic programming capability of the genetic algorithm.