Abstract: The invention relates to a first curable coating composition comprising a first layer comprising at least one epoxy resin and at least one hybrid nanofiller, and a second layer comprising carbon nanotubes (CNTs). This invention also relates to a second curable coating composition comprising at least one hybrid nanofiller; at least one epoxy resin; and at least one curing agent. This invention also relates to methods of making the curable coating compositions. This invention also relates to methods for coating the surface of a metallic coated substrate.

Abstract: The present disclosure provides a substance identification device and a substance identification method. The substance identification device comprises: a classifier establishing unit configured to establish a classifier based on scattering density values reconstructed for a plurality of known sample materials, wherein the classifier comprises a plurality of feature regions corresponding to a plurality of characteristic parameters for the plurality of known sample materials, respectively; and an identification unit for a material to be tested, configured to match the characteristic parameter of the material to be tested with the classifier, and to identify a type of the material to be tested by obtaining a feature region corresponding to the characteristic parameter of the material to be tested.

Abstract: Techniques described herein relate to analyzing executions of content resources within networks of execution client devices, and selecting sets of interactive content resources for execution on particular execution devices based on such analyses. Content resource execution data may be received from various execution client devices on which content resources have been executed and provided to end users. Such data may be analyzed to determine correlations between a first content executor and additional content executors based on the their respective content resource execution data, and the content resource execution data of correlated content executors may be aggregated and analyzed to select particular interactive content resources for the first content executor. Such selections may be provided to first content executor during a content execution session following an authenticated login by the first content executor.

Abstract: The present disclosure provides a substance identification device and a substance identification method. The substance identification device comprises: a classifier establishing unit configured to establish a classifier based on scattering density values reconstructed for a plurality of known sample materials, wherein the classifier comprises a plurality of feature regions corresponding to a plurality of characteristic parameters for the plurality of known sample materials, respectively; and an identification unit for a material to be tested, configured to match the characteristic parameter of the material to be tested with the classifier, and to identify a type of the material to be tested by obtaining a feature region corresponding to the characteristic parameter of the material to be tested.

Abstract: Techniques described herein relate to analyzing executions of content resources within networks of execution client devices, and selecting sets of interactive content resources for execution on particular execution devices based on such analyses. Content resource execution data may be received from various execution client devices on which content resources have been executed and provided to end users. Such data may be analyzed to determine correlations between a first content executor and additional content executors based on the their respective content resource execution data, and the content resource execution data of correlated content executors may be aggregated and analyzed to select particular interactive content resources for the first content executor. Such selections may be provided to first content executor during a content execution session following an authenticated login by the first content executor.

Abstract: Techniques described herein relate to analyzing executions of content resources within networks of execution client devices, and selecting sets of interactive content resources for execution on particular execution devices based on such analyses. Content resource execution data may be received from various execution client devices on which content resources have been executed and provided to end users. Such data may be analyzed to determine correlations between a first content executor and additional content executors based on the their respective content resource execution data, and the content resource execution data of correlated content executors may be aggregated and analyzed to select particular interactive content resources for the first content executor. Such selections may be provided to first content executor during a content execution session following an authenticated login by the first content executor.

Abstract: Techniques described herein relate to analyzing executions of content resources within networks of execution client devices, and selecting sets of interactive content resources for execution on particular execution devices based on such analyses. Content resource execution data may be received from various execution client devices on which content resources have been executed and provided to end users. Such data may be analyzed to determine correlations between a first content executor and additional content executors based on the their respective content resource execution data, and the content resource execution data of correlated content executors may be aggregated and analyzed to select particular interactive content resources for the first content executor. Such selections may be provided to first content executor during a content execution session following an authenticated login by the first content executor.