Abstract: A preparation method of a highland barley tea includes stir-frying highland barley; after immersing the same in water, performing extraction at a temperature of 95±1° C., and filtering the extracted product to obtain a highland barley tea.

Abstract: A preparation method of a highland barley tea includes stir-frying highland barley; after immersing the same in water, performing extraction at a temperature of 95±1° C., and filtering the extracted product to obtain a highland barley tea.

Abstract: Systems and methods for accelerating computer network policy searching are provided. According to one embodiment, a packet is received by a policy search engine (PSE) of a packet processing device. A set of candidate policies are identified from among multiple policies of the packet processing device by screening the multiple policies by a speculation unit of the PSE based on metadata associated with the received packet. Finally, a matching policy for the received packet is identified by a policy search processor (PSP) of the PSE by executing policy-search-specific instructions and general purpose instructions.

Abstract: Systems and methods for accelerating computer network policy searching are provided. According to one embodiment, a packet is received by a policy search engine (PSE) of a packet processing device. A set of candidate policies are identified from among multiple policies of the packet processing device by screening the multiple policies by a speculation unit of the PSE based on metadata associated with the received packet. Finally, a matching policy for the received packet is identified by a policy search processor (PSP) of the PSE by executing policy-search-specific instructions and general purpose instructions.

Abstract: In an example embodiment, a method of calculating end-of-life (EOL) predictions for a physical asset is provided. A state-space model for the physical asset is obtained, the state-space model being a physics-based model describing a state of the physical asset at a particular time given measurements or observations for the physical asset. Then a current state of the physical asset is inferred. Then a long-term prediction is derived for the physical asset based on the inferred current state of the physical asset and the state-space model for the physical asset. Then an EOL probability distribution function is generated for the physical asset based on the long-term prediction, the EOL probability distribution function describing a range of estimates of EOL for the physical asset and their corresponding confidence intervals.

Abstract: In an example embodiment, a method of calculating end-of-life (EOL) predictions for a physical asset is provided. A state-space model for the physical asset is obtained, the state-space model being a physics-based model describing a state of the physical asset at a particular time given measurements or observations for the physical asset. Then a current state of the physical asset is inferred. Then a long-term prediction is derived for the physical asset based on the inferred current state of the physical asset and the state-space model for the physical asset. Then an EOL probability distribution function is generated for the physical asset based on the long-term prediction, the EOL probability distribution function describing a range of estimates of EOL for the physical asset and their corresponding confidence intervals.