Abstract: A system and method adaptively control a heterogeneous system of systems. A graph convolutional network (GCN) that receive a time series of graphs representing topology of an observed environment at a time moment and state of a system. Embedded features are generated having local information for each graph node. Embedded features are divided into embedded states grouped according to a defined grouping, such as node type. Each of several reinforcement learning algorithms are assigned to a unique group and include an adaptive control policy in which a control action is learned for a given embedded state. Reward information is received from the environment with a local reward related to performance specific to the unique group and a global reward related to performance of the whole graph responsive to the control action. Parameters of the GCN and adaptive control policy are updated using state information, control action information, and reward information.

Abstract: Techniques for generating full-spatial resolution, full spectral resolution image(s) from a 3D spectral-data cube for any spectral value within a given spectral range are provided without requiring the acquisition of all full-spatial resolution, full spectral resolution data by an instrument. The 3D spectral-data cube is generated from a limited number of full-spatial resolution, sparse spectral resolution data and a sparse-spatial resolution, full-spectral resolution data of the same area of the sample. The use of the 3D spectral-data cube reduces the data acquisition time.

Abstract: Machine learning approach can combine mass spectral imaging (MSI) techniques, one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The machine learning approach can perform transformations on the spectral image data of the two MSI techniques to reduce dimensionality, and using a correlation technique, find relationships between the transformed spectral image data. The determined relationships can be used to generate MSI spectra of desired resolution.

Abstract: A composite filament for use in additive manufacturing such as fused filament fabrication is described along with methods of its construction and use. The composite filament includes a single continuous filament (e.g., a continuous carbon roving) and a polymer (e.g., a high glass transition polymer) in intimate contact. The composite filament is formed through immersion of the continuous filament in a solution of the polymer. The composite filament can be combined with an additional formation material in an additive manufacturing process.

Abstract: Techniques for generating full-spatial resolution, full spectral resolution image(s) from a 3D spectral-data cube for any spectral value within a given spectral range are provided without requiring the acquisition of all full-spatial resolution, full spectral resolution data by an instrument. The 3D spectral-data cube is generated from a limited number of full-spatial resolution, sparse spectral resolution data and a sparse-spatial resolution, full-spectral resolution data of the same area of the sample. The use of the 3D spectral-data cube reduces the data acquisition time.

Abstract: Provided is an orthopedic implant comprising a surface with a coating on the surface wherein the coating comprises a copolymer defined by Formula I: Aw-Bx-Cy-Dz wherein: A comprises an epoxy group; B comprises a hydrophobic group; C is an optional cross-linker; D of Formula I comprises a hydrophilic group; w is at least 0.1 to no more than 0.9 with the proviso that at least one of x or z is not zero; x is up to 0.9; y is up to 0.3; and z is up to 0.9.

Abstract: A composite filament for use in additive manufacturing such as fused filament fabrication is described along with methods of its construction and use. The composite filament includes a single continuous filament (e.g., a continuous carbon roving) and a polymer (e.g., a high glass transition polymer) in intimate contact. The composite filament is formed through immersion of the continuous filament in a solution of the polymer. The composite filament can be combined with an additional formation material in an additive manufacturing process.