Abstract: The present disclosure includes systems and/or methods for receiving historical trading data associated with previously executed trade transactions for a financial instrument by a plurality of candidate invitee users. Trading intentions are received from the candidate invitee users and a score representative of a likelihood of successfully trading the financial instrument is modelled for each candidate invitee user based on inputting into a machine learning model the trading intentions and the historical trading data of each candidate invitee user.

Abstract: Computer-implemented methods and computer systems for an electronic transaction platform that enables the buying and/or selling of securities by users. The methods and systems relate to controlling communication of information during an electronic communication session for trading a financial instrument between an initiating user and one or more invitee users with the assistance of a dealer user or other intermediate entity. When a dealer with whom the initiating user has a relationship does not have a relationship with invitee users that may desire to trade for the security, a second dealer can be included in the electronic communication session, where the second dealer has a relationship with such invitee users. Various levels of participation are available for each user and correspond to what information each user is provided during the electronic communication session.

Abstract: Content is managed and provided to users over a communications link using a differencing engine. The differencing engine is configured to selectively cause content to be refreshed in a cache. Specifically, the differencing engine is configured to detect whether a more recent version of a data item is available, and if so, delete a current version of the data item from the cache and retrieve and store in the cache the more recent version of the data item. Content is selected for refresh based upon a set of one or more selection criteria. The selection criteria may include, for example, the source of content, the size of content, the age of content, the type of content and users to which the content is being provided.

Abstract: Systems, machine readable storage, and methods for solving a respiratory tract model of radiation dosage. Steps include selecting input parameters associated with a respiratory tract model, computing a probability density function for the input parameters, and solving the respiratory tract model using the computed probability density functions.

Abstract: Content is managed and provided to users over a communications link using a differencing engine. The differencing engine is configured to selectively cause content to be refreshed in a cache. Specifically, the differencing engine is configured to detect whether a more recent version of a data item is available, and if so, delete a current version of the data item from the cache and retrieve and store in the cache the more recent version of the data item. Content is selected for refresh based upon a set of one or more selection criteria. The selection criteria may include, for example, the source of content, the size of content, the age of content, the type of content and users to which the content is being provided.