Abstract: A probabilistic digital signal processor is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and/or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates using a physical model on data from a mechanical system or a medical meter or instrument, such as an electrocardiogram. Output of the physical model yields an enhanced output of the original data, an output to a second physical parameter not output by the medical meter, or a prediction, such as an arrhythmia warning.

Abstract: A one-step process for the lysis of microalgae cell walls and separation of the cellular lipids for use in biofuel production by utilizing a hydrophilic ionic liquid, 1-butyl-3-methylimidazolium. The hydrophilic ionic liquid both lyses the microalgae cell walls and forms two immiscible layers, one of which consists of the lipid contents of the lysed cells. After mixture of the hydrophilic ionic liquid with a suspension of microalgae cells, gravity causes a hydrophobic lipid phase to move to a top phase where it is removed from the mixture and purified. The hydrophilic ionic liquid is recycled to lyse new microalgae suspensions.

Abstract: The invention relates to use of an active ionic liquid to dissolve algae cell walls. The ionic liquid is used to, in an energy efficient manner, dissolve and/or lyse an algae cell walls, which releases algae constituents used in the creation of energy, fuel, and/or cosmetic components. The ionic liquids include ionic salts having multiple charge centers, low, very low, and ultra low melting point ionic liquids, and combinations of ionic liquids. An algae treatment system is described, which processes wet algae in a lysing reactor, separates out algae constituent products, and optionally recovers the ionic liquid in an energy efficient manner.

Abstract: A probabilistic digital signal processor is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and/or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates using a physical model on data from a mechanical system or a medical meter or instrument, such as an electrocardiogram. Output of the physical model yields an enhanced output of the original data, an output to a second physical parameter not output by the medical meter, or a prediction, such as an arrhythmia warning.

Abstract: A probabilistic digital signal processor using data from multiple instruments is described. In one example, an analyzer is configured to: receive discrete first and second input data, related to a first and second sub-system of the system, from a first and second instrument, respectively. A system processor is used to fuse the first and second input data into fused data. The system processor optionally includes: (1) a probabilistic processor configured to convert the fused data into at least two probability distribution functions and (2) a dynamic state-space model, the dynamic state-space model including at least one probabilistic model configured to operate on the at least two probability distribution functions. The system processor iteratively circulates the at least two probability distribution functions in the dynamic state-space model in synchronization with receipt of updated input data, processes the probability distribution functions, and generates an output related to the state of the system.

Abstract: A probabilistic digital signal processor using data from multiple instruments is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and/or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data from multiple instruments with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates on fused data using a physical model, where the data originates from a mechanical system or a medical meter or instrument, such as an electrocardiogram or pulse oximeter to generate new parameter information and/or enhanced parameter information.

Abstract: A probabilistic digital signal processor using data from multiple instruments is described. In one example, a digital signal processor is integrated into a biomedical device. The processor is configured to: use a dynamic state-space model configured with a physiological model of a body system to provide a prior probability distribution function; receive sensor data input from at least two data sources; and iteratively use a probabilistic updater to integrate the sensor data as a fused data set and generate a posterior probability distribution function using all of: (1) the fused data set; (2) an application of Bayesian probability; and (3) the prior probability distribution function. The processor further generates an output of a biomedical state using the posterior probability function.

Abstract: A one-step process for the lysis of microalgae cell walls and separation of the cellular lipids for use in biofuel production by utilizing a hydrophilic ionic liquid, 1-butyl-3-methylimidazolium. The hydrophilic ionic liquid both lyses the microalgae cell walls and forms two immiscible layers, one of which consists of the lipid contents of the lysed cells. After mixture of the hydrophilic ionic liquid with a suspension of microalgae cells, gravity causes a hydrophobic lipid phase to move to a top phase where it is removed from the mixture and purified. The hydrophilic ionic liquid is recycled to lyse new microalgae suspensions.

Abstract: The invention relates to use of an active ionic liquid to dissolve algae cell walls. The ionic liquid is used to, in an energy efficient manner, dissolve and/or lyse an algae cell walls, which releases algae constituents used in the creation of energy, fuel, and/or cosmetic components. The ionic liquids include ionic salts having multiple charge centers, low, very low, and ultra low melting point ionic liquids, and combinations of ionic liquids.An algae treatment system is described, which processes wet algae in a lysing reactor, separates out algae constituent products, and optionally recovers the ionic liquid in an energy efficient manner.