Abstract: A method and system determine network based access to restricted systems. The method includes receiving a request for a permission access status of a party seeking access to one of the restricted systems. A database of periodically updated lists of entities is accessed. A name of the party is extracted from the request. A determination is made whether the name does not match one of the entities. The name is decomposed into parts if the name not matching one of the entities. A determination is made whether any of the parts of the name matches one of the entities. A denial of access status is forwarded from the computer server to an external computing device if any of the parts of the name matches one of the entities.

Abstract: The present disclosure provides complexes comprising a cationic oligosaccharide and an RNA, wherein the cationic oligosaccharide comprises a plurality of cationic moieties bonded to a trehalose, a sucrose, or a gluco-n-oligosaccharide moiety, where n is 2-6, and a ratio of N/P in the complex is less than 20:1

Abstract: The present disclosure provides complexes comprising: i) a cationic oligosaccharide comprising one or more cationic moieties bonded to a trehalose, a sucrose, or a gluco-n-oligosaccharide moiety, where n is 2-6; ii) a surfactant; and iii) one or more additives selected from: a sterol, a helper lipid, an immunomodulator, and a targeting molecule; and uses thereof.

Abstract: Systems and techniques that facilitate Clifford circuit synthesis are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory that can execute the computer executable components stored in memory. The computer executable components can comprise a receiver component that receives a quantum circuit design comprising a Clifford circuit representation and one or more circuit restrictions, and a machine learning component that generates, using a machine learning model, a replacement circuit based on the one or more circuit restrictions and the Clifford circuit representation, and generates a modified quantum circuit design by replacing the Clifford circuit representation with the replacement circuit.

Abstract: An apparatus for solving time-continuous differential equations is disclosed. The apparatus includes a group of hybrid integrators interconnected to each other. Each one of the hybrid integrators includes an analog integrator, a conversion logic and multiple digital registers. The analog integrator generates an analog output, and the conversion logic along with the digital registers converts the analog output to a digital output. The analog output and the digital output are then combined to yield an integrated output. The integrated output is fed to the hybrid integrators within the group.

Abstract: An apparatus for solving time-continuous differential equations is disclosed. The apparatus includes a group of hybrid integrators interconnected to each other. Each one of the hybrid integrators includes an analog integrator, a conversion logic and multiple digital registers. The analog integrator generates an analog output, and the conversion logic along with the digital registers converts the analog output to a digital output. The analog output and the digital output are then combined to yield an integrated output. The integrated output is fed to the hybrid integrators within the group.

Abstract: The present invention is a fully connected feed forward network that includes at least one hidden layer 16. The hidden layer 16 includes nodes 20 in which the output of the node is fed back to that node as an input with a unit delay produced by a delay device 24 occurring in the feedback path 22 (local feedback). Each node within each layer also receives a delayed output (crosstalk) produced by a delay unit 36 from all the other nodes within the same layer 16. The node performs a transfer function operation based on the inputs from the previous layer and the delayed outputs. The network can be implemented as analog or digital or within a general purpose processor. Two teaching methods can be used: (1) back propagation of weight calculation that includes the local feedback and the crosstalk or (2) more preferably a feed forward gradient decent which immediately follows the output computations and which also includes the local feedback and the crosstalk.