Abstract: A valve is provided for a sheath, catheter, or other tubular device that includes a first face, a second face opposite the first face and an axis extending between the first and second faces. A first slit extends substantially parallel to the axis from the first face towards the second face to a first intermediate location within the valve body, a second slit extends substantially parallel to the axis from the second face towards the first face to a second intermediate location within the valve body, and a bore extends along the axis between the first intermediate location and the second intermediate location.

Abstract: A communication system, includes a trailer bridge disposed on a cargo trailer, the trailer bridge comprising a power line transceiver for communicating with a tractor module when the trailer and a tractor having the tractor module are electrically connected; and a locator module for communicating with the trailer bridge, the locator module comprising a mobile or cellular transceiver for communicating with a mobile or cellular communications network external to the trailer. The locator module is to communicate making of the electrical connection between the trailer and tractor to a remote datacenter of an owner/operator of the trailer in response to a signal from the trailer bridge indicating that the electrical connection has been made.

Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system uses a machine learning system to rank the property listings returned by the search. The machine learning system uses objective functions to determine parameters for each property listing and assign a ranking based on the parameters. A first objective function generates a parameter indicating an extent to which a property listing matches preferences of the guest, and is based on data about the guest's interactions with the reservation system. A second objective function generates another parameter indicating an extent to which the search request matches the preferences of the host associate with the property listing, and is based on data about the host's responses to reservation requests.

Abstract: A user is associated with initial search requests, and results that comprise attribute types indicative of a common relationship with other results. Each result has an attribute parameter for each attribute type. Search interaction data. Search interaction data comprises attribute parameter data and user interaction data for the search results. A machine learning algorithm is trained to analyze the search interaction data to recognize common relationships, and used to detect a common relationship between the respective attribute parameters for one of the attribute types for which the user interest data indicates interest. When a subsequent search request is received from the user, a user interest characteristic is computed for each result, based on similarity between the attribute preference data detected using the machine learning algorithm and the attribute parameter for the attribute type. The search results are presented to the user, sorted according to user interest characteristic.

Abstract: A valve is provided for a sheath, catheter, or other tubular device that includes a first face, a second face opposite the first face and an axis extending between the first and second faces. A first slit extends substantially parallel to the axis from the first face towards the second face to a first intermediate location within the valve body, a second slit extends substantially parallel to the axis from the second face towards the first face to a second intermediate location within the valve body, and a bore extends along the axis between the first intermediate location and the second intermediate location.

Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system also tracks interactions of the guest with the returned property listings in order to determine which of the property listings are of interest to the guest, and the system may determine one or more guest preference parameters indicative of the guest's preferences based on such interactions. Thereafter, when the guest submits another search request, the system sorts the search results based on the guest preference parameters so that the property listings deemed more likely to be of interest to the guest are ranked higher (e.g., listed first), thereby helping the guest to more quickly find property listings of interest within the search results.

Abstract: In one example in accordance with the present disclosure, a method for identifying an available cargo vehicle is described. According to the method, a time when a cargo tractor is scheduled to be available is determined as well as a location where the cargo tractor is scheduled to be available. Characteristics of a cargo trailer coupled to the cargo tractor are determined and an available number of hours left to drive for a driver associated with the cargo tractor are also determined. Time information, location information, cargo trailer characteristic information, and driver availability information for multiple cargo vehicles is aggregated in a database.

Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system uses a machine learning system to rank the property listings returned by the search. The machine learning system uses objective functions to determine parameters for each property listing and assign a ranking based on the parameters. A first objective function generates a parameter indicating an extent to which a property listing matches preferences of the guest, and is based on data about the guest's interactions with the reservation system. A second objective function generates another parameter indicating an extent to which the search request matches the preferences of the host associate with the property listing, and is based on data about the host's responses to reservation requests.

Abstract: An online reservation system is configured to receive requests from a guest for searching property listings and to return property listings that satisfy the search criteria of the requests. The online reservation system also tracks interactions of the guest with the returned property listings in order to determine which of the property listings are of interest to the guest, and the system may determine one or more guest preference parameters indicative of the guest's preferences based on such interactions. Thereafter, when the guest submits another search request, the system sorts the search results based on the guest preference parameters so that the property listings deemed more likely to be of interest to the guest are ranked higher (e.g., listed first), thereby helping the guest to more quickly find property listings of interest within the search results.