Abstract: Methods of braiding using a braiding mechanism are described. The braiding mechanism includes a disc defining a plane and a circumferential edge, a mandrel extending from a center of the disc that is adapted to hold a plurality of filaments extending radially from the mandrel toward the circumferential edge of the disc, a plurality of catch mechanisms positioned circumferentially around the edge of the disc, a plurality of actuators adapted to move the plurality of catch mechanisms in a substantially radial direction relative to the circumferential edge of the disc, and a plurality of filaments extending radially from the mandrel towards circumferential edge of the disc. A middle portion of each filament of the plurality of filaments contacts an end of the mandrel.

Abstract: Individual four-sided shaped modules used in an assembly for underground storage of storm water and other fluid storage needs. Modules are assembled into a resultant four-sided tiling shape for maximized structural strength and material use efficiency. Internal four-sided shaped modules are assembled and encased by external four-sided shaped modules. Internal adjacent modules are in direct fluid communications with one another through a channel-less chamber. Internal four-sided shaped modules drain into four-sided shaped modules chamber where fluid is either stored or drained. Assemblies include various top and side pieces along with access ports for entry into said assembly.

Abstract: A set of vectors may be obtained. The vectors may be multi-dimensional vectors that are associated with and describe tokens from a first set of tokens from a corpus of sources. The description may be based in part on the relationship of the token to at least a portion of the remainder of the corpus. A set of sentiment scores may be obtained. The sentiment scores in the set of sentiment scores may describe a sentiment associated with a corresponding token that is described by a vector from the set of vectors. The set of vectors and the set of sentiment scores may be input into a pattern-recognizer pathway in a first neural network. A probability value of a potential future event may then be generated by the first neural network. The probability value may be based on the set of vectors and the set of sentiment scores.

Abstract: A reflection is captured of a subsonic signal reflected by a contact surface. The contact surface is contacting a simulated surface of an object projected from a midair interface (MAI) device. A difference between the subsonic signal and the reflection is converted into a measurement of a flow in the contact surface. When the measurement is in a range of measurements, a change is caused in a temperature of a volume of a medium, the simulated surface being projected in volume of the medium, where the change in the temperature causes a second change in the flow in the contact surface.

Abstract: A reflection is captured of a subsonic signal reflected by a contact surface. The contact surface is contacting a simulated surface of an object projected from a midair interface (MAI) device. A difference between the subsonic signal and the reflection is converted into a measurement of a flow in the contact surface. When the measurement is in a range of measurements, a change is caused in a temperature of a volume of a medium, the simulated surface being projected in volume of the medium, where the change in the temperature causes a second change in the flow in the contact surface.

Abstract: A set of vectors may be obtained. The vectors may be multi-dimensional vectors that are associated with and describe tokens from a first set of tokens from a corpus of sources. The description may be based in part on the relationship of the token to at least a portion of the remainder of the corpus. A set of sentiment scores may be obtained. The sentiment scores in the set of sentiment scores may describe a sentiment associated with a corresponding token that is described by a vector from the set of vectors. The set of vectors and the set of sentiment scores may be input into a pattern-recognizer pathway in a first neural network. A probability value of a potential future event may then be generated by the first neural network. The probability value may be based on the set of vectors and the set of sentiment scores.