Abstract: An antenna and a formulation and method for making the antenna are disclosed. The antenna comprises: a first phase comprising at least one polymer; a second phase comprising at least one first component; and, optionally; and an interface between the first and second phases, wherein the interface has a concentration gradient of the at least one first component, whereby the concentration of the at least one first component decreases with distance away from the second phase towards the first phase, wherein the at least one first component comprises at least one functional component, at least one functional precursor component, or combinations thereof, and the at least one first component, in combination with the at least one polymer, has a high dielectric constant and/or a low dielectric loss tangent, wherein the antenna is a functional antenna, a functional precursor antenna, or a combination of a functional and functional precursor antenna.

Abstract: Automated vehicle repair estimation by random ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a vehicle damage object that includes a plurality of metadata objects of the damaged vehicle; fragmenting the object into fragments each including at least one of the metadata objects; providing each of the fragments to a respective artificial intelligence function; receiving a respective vehicle repair recommendation set from each of the artificial intelligence functions, wherein each of the vehicle repair recommendation sets identifies a recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; selecting a plurality of the recommended vehicle repair operations; generating a composite vehicle repair recommendation set that identifies the selected recommended vehicle repair operations; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.

Abstract: Automated vehicle repair estimation by adaptive ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from a plurality of sources, vehicle repair recommendation sets identifying recommended vehicle repair operations for damaged vehicle components; selecting, by a trained artificial intelligence function, one of the operations for each component based on a plurality of learned states; generating a composite vehicle repair recommendation set identifying the selected operation; providing the composite vehicle repair recommendation set to one or more claims management systems; and repeatedly retraining the trained artificial intelligence function by adjusting the learned states according to the vehicle damage objects received, and the corresponding composite vehicle repair recommendation generated, since the last retraining of the trained artificial intelligence function.

Abstract: Systems and methods for managing predictions for vehicle repair estimates are provided. A method includes providing one or more images of a damaged vehicle as input to a machine learning model, wherein the machine learning model has been trained with images of other damaged vehicles and corresponding vehicle operations, wherein each of the vehicle operations represents the repair or replacement of a vehicle component; receiving output of the machine learning model responsive to the input, wherein the output comprises a plurality of values each corresponding to one of a plurality of the vehicle operations; determining a confidence metric based on the values; making a comparison between the confidence metric and a confidence threshold value; and selecting the one of the plurality of the vehicle operations corresponding to the highest value as a predicted operation based on the comparison.

Abstract: An antenna and a formulation and method for making the antenna are disclosed. The antenna comprises: a first phase comprising at least one polymer; a second phase comprising at least one first component; and, optionally; and an interface between the first and second phases, wherein the interface has a concentration gradient of the at least one first component, whereby the concentration of the at least one first component decreases with distance away from the second phase towards the first phase, wherein the at least one first component comprises at least one functional component, at least one functional precursor component, or combinations thereof, and the at least one first component, in combination with the at least one polymer, has a high dielectric constant and/or a low dielectric loss tangent, wherein the antenna is a functional antenna, a functional precursor antenna, or a combination of a functional and functional precursor antenna.

Abstract: A 3D printed GRIN device, the formulation and the method for making the GRIN device are disclosed. The GRIN (graded-index) device comprises i) a first phase comprising at least one polymer; ii) a second phase comprising at least one first component; and, optionally, iii) an interface between the first phase and the second phase, wherein the interface has a concentration gradient of the at least one first component, whereby the concentration of the at least one first component decreases with distance away from the second phase towards the first phase, wherein the at least one first component comprises at least one functional component, at least one functional precursor component, or combinations thereof, and wherein the GRIN device is a functional GRIN device, a functional precursor GRIN device, or a combination of a functional and functional precursor GRIN device.

Abstract: Systems and methods for managing predictions for vehicle repair estimates are provided. A method includes providing one or more images of a damaged vehicle as input to a machine learning model, wherein the machine learning model has been trained with images of other damaged vehicles and corresponding vehicle operations, wherein each of the vehicle operations represents the repair or replacement of a vehicle component; receiving output of the machine learning model responsive to the input, wherein the output comprises a plurality of values each corresponding to one of a plurality of the vehicle operations; determining a confidence metric based on the values; making a comparison between the confidence metric and a confidence threshold value; and selecting the one of the plurality of the vehicle operations corresponding to the highest value as a predicted operation based on the comparison.

Abstract: Automated vehicle repair estimation by random ensembling of multiple artificial intelligence functions is provided. A method comprises receiving a vehicle damage object that includes a plurality of metadata objects of the damaged vehicle; fragmenting the object into fragments each including at least one of the metadata objects; providing each of the fragments to a respective artificial intelligence function; receiving a respective vehicle repair recommendation set from each of the artificial intelligence functions, wherein each of the vehicle repair recommendation sets identifies a recommended vehicle repair operation of a plurality of the vehicle repair operations for the damaged vehicle; selecting a plurality of the recommended vehicle repair operations; generating a composite vehicle repair recommendation set that identifies the selected recommended vehicle repair operations; and providing the composite vehicle repair recommendation set to one or more vehicle repair insurance claims management systems.

Abstract: Automated vehicle repair estimation by adaptive ensembling of multiple artificial intelligence functions is provided. A method comprises receiving, from a plurality of sources, vehicle repair recommendation sets identifying recommended vehicle repair operations for damaged vehicle components; selecting, by a trained artificial intelligence function, one of the operations for each component based on a plurality of learned states; generating a composite vehicle repair recommendation set identifying the selected operation; providing the composite vehicle repair recommendation set to one or more claims management systems; and repeatedly retraining the trained artificial intelligence function by adjusting the learned states according to the vehicle damage objects received, and the corresponding composite vehicle repair recommendation generated, since the last retraining of the trained artificial intelligence function.

Abstract: A method, non-transitory computer readable medium, and an apparatus for automated estimation of repair data includes applying a first generated artificial intelligence model on a received vehicle damage image associated with an electronic claim to identify damaged component(s) on a vehicle without using any metadata. A heat map analysis is performed on the received actual vehicle damage image to identify a damage severity value associated with at least one of the identified damaged component(s). A second generated artificial intelligence model is applied on the received actual vehicle damage image and the damage severity value associated with the identified damaged component(s) to determine repair data and a repair-or-replace designation. The determined repair data and the determined repair-or-replace designation for at least one of the identified one or more damaged components is provided in response to the received actual vehicle damage image associated with the electronic claim.

Abstract: Apparatus and method of exposing a chemical, biological or biochemical sample to radiation. A sample in liquid or vapour phase is segmented and conveyed along a sample path. At least one generator or source for generating electromagnetic radiation is directed at the sample and at least one of reflected, emitted and transmitted radiation is measured at least one point along the sample path. In one embodiment, the sample is a luminescent culture produced by a continuous culture system.

Abstract: Apparatus and method of exposing a chemical, biological or biochemical sample to radiation. A sample in liquid or vapour phase is segmented and conveyed along a sample path. At least one generator or source for generating electromagnetic radiation is directed at the sample and at least one of reflected, emitted and transmitted radiation is measured at at least one point along the sample path. In one embodiment, the sample is a luminescent culture produced by a continuous culture system.

Abstract: A track system includes an accelerator track section having a ferrous metal accelerator rod which attracts a magnetized spinning top and imparts a linear acceleration to the top. Additional coaster and turn track sections provide a selected glide path for the freely moving top. Alternate embodiments of the accelerator track sections include the incorporation of a guide channel, a "T" shaped accelerator strip, a planar accelerator strip, and a dual sided accelerator strip.

Abstract: Terminating apparatus for a flat conductor cable including a plurality of generally coplanar individual conductors. The terminating apparatus includes a generally rectangular insulation housing having an array of longitudinally extending apertures with mutually parallel and coplanar axes. A box contact assembly is positioned within each housing aperture and includes a contact tail for simultaneously providing a secure structural and electrical connection to an associated one of the plurality of individual conductors and a contact nose for providing a releasable electrical connection to another associated one of a plurality of mating conductors. Each box contact assembly is fashioned with a resilient locking lance which operates in cooperation with a recess fashioned within one wall of each aperture within the insulation housing to releasably maintain the conductor cable within the insulation housing.