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Mechanism-Based Biological Inference via Multiplex Networks, AI Agents and Cross-Species Translation
This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.
Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.
Technologies directed to polarization agnostic continuous variable quantum key distribution are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
By engineering the Serine Integrase Assisted Genome Engineering (SAGE) genetic toolkit in an industrial strain of Aspergillus niger, we have established its proof of principle for applicability in Eukaryotes.
The development of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions.
Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.
This invention addresses a key challenge in quantum communication networks by developing a controlled-NOT (CNOT) gate that operates between two degrees of freedom (DoFs) within a single photon: polarization and frequency.