Abstract: Systems and methods for intelligently providing users with supporting information based on big-data analyses of a data set. Machine-learning algorithms may be executed using the data set to identify correlations between data objects of the data set. The correlations can be used to recommend supporting information to a user. A user interface can be provided to enable a user to initiate a process associated with an event. In response to receiving the input, the system can identify variables associated with the request. Based on these variables, the system can retrieve output data of the machine-learning algorithms to identify the supporting information for the user.

Abstract: Systems and methods for intelligently providing users with supporting information based on big-data analyses of a data set. Machine-learning algorithms may be executed using the data set to identify correlations between data objects of the data set. The correlations can be used to recommend supporting information to a user. A user interface can be provided to enable a user to initiate a process associated with an event. In response to receiving the input, the system can identify variables associated with the request. Based on these variables, the system can retrieve output data of the machine-learning algorithms to identify the supporting information for the user.

Abstract: Systems and methods for intelligently providing users with supporting information based on big-data analyses of a data set. Machine-learning algorithms may be executed using the data set to identify correlations between data objects of the data set. The correlations can be used to recommend supporting information to a user. A user interface can be provided to enable a user to initiate a process associated with an event. In response to receiving the input, the system can identify variables associated with the request. Based on these variables, the system can retrieve output data of the machine-learning algorithms to identify the supporting information for the user.

Abstract: An electrical conductor which has an electrically conducting fiber including carbon nanotubes and/or a graphene nanoribbon and a layer of insulating material coated around the electrically conducting fiber. The insulating material substantially does not penetrate the electrically conducting fiber, or penetrates the electrically conducting fiber only to a depth that leaves a continuous conductive path along a remaining part of the electrically conducting fiber.

Abstract: Disclosed is a web page display method and system. The method includes: saving for a web page display parameters corresponding to time periods, each display parameter corresponding to one time parameter; receiving a request for accessing the web page, searching for, from the display parameters saved, a display parameter of the web page corresponding to a time period to which the current time belongs; displaying the web page according to the display parameter searched. The system includes: a setting module, configured to save for a web page a display parameter corresponding to a time period; a searching module, configured to search for a display parameter of the web page corresponding to a time period to which the current time belongs when a request for accessing the web page is received; a display module, configured to display the web page according to the display parameter searched by the searching module.

Abstract: An electrical conductor comprising an electrically conducting fibre comprising carbon nanotubes and/or graphene nanoribbon and a layer of insulating material coated around the electrically conducting fibre. The insulating material substantially does not penetrate the electrically conducting fibre, or penetrates the electrically conducting fibre only to a depth that leaves a continuous conductive path along a remaining part of the electrically conducting fibre.