Abstract: An electrochemical assembly, comprising: a plurality of electrochemical cells arranged to form an electrochemical stack having a first end and a second end; a first endcap disposed at the first end of the electrochemical stack, and a second endcap disposed at the second end of the electrochemical stack, and at least one of the endcaps being arranged to provide a fluidic connection to the electrochemical stack; wherein the first and second endcaps are secured to the electrochemical stack by a fibre-reinforced casing that extends around at least a portion of the electrochemical stack and at least a portion of each endcap such that a fluidic seal is formed between the electrochemical stack and each endcap.

Abstract: Extending access to a data model includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

Abstract: A method for the automatic generation of a data model from an SQL statement includes receiving a single SQL statement in a user interface to a data analytics application, parsing the single SQL statement and extracting from the SQL statement different table references. The method also includes, for each one of the table references, directing a selection of all fields available in a corresponding table and storing the available fields in a collection of fields implicated by each table referenced by the table references. Finally, the method includes generating a data model with the fields in the collection of fields and displaying a view of the data model in a user interface of the data analytics application.

Abstract: Data content governance for presentation layer synchronization for a version controlled underlying data model includes defining a data model for underlying data in a database, specifying a presentation layer for the defined data model and identifying selected elements of the data model necessary to meet data requirements of the specified presentation layer. Then, the identified selected elements of the data model are serialized and both the specified presentation layer and the serialized elements are versioned in respect to the specified presentation layer. Thereafter, when the data model becomes modified, the specified presentation layer is modified to accommodate the modified data model. In response to the modification, a different selection of elements of the data model necessary to meet data requirements of the modified presentation layer are re-identified and serialized, with the modified presentation layer and the serialized re-identified different selection of elements becoming re-versioned.

Abstract: Extending access to a data model includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

Abstract: Extending access to a data model in a data analytics computer data processing system includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

Abstract: A method for the automatic generation of a data model from an SQL statement includes receiving a single SQL statement in a user interface to a data analytics application, parsing the single SQL statement and extracting from the SQL statement different table references. The method also includes, for each one of the table references, directing a selection of all fields available in a corresponding table and storing the available fields in a collection of fields implicated by each table referenced by the table references. Finally, the method includes generating a data model with the fields in the collection of fields and displaying a view of the data model in a user interface of the data analytics application.

Abstract: A method for the automatic generation of a data model from an SQL statement includes receiving a single SQL statement in a user interface to a data analytics application, parsing the single SQL statement and extracting from the SQL statement different table references. The method also includes, for each one of the table references, directing a selection of all fields available in a corresponding table and storing the available fields in a collection of fields implicated by each table referenced by the table references. Finally, the method includes generating a data model with the fields in the collection of fields and displaying a view of the data model in a user interface of the data analytics application.

Abstract: A method for the automatic generation of a data model from an SQL statement includes receiving a single SQL statement in a user interface to a data analytics application, parsing the single SQL statement and extracting from the SQL statement different table references. The method also includes, for each one of the table references, directing a selection of all fields available in a corresponding table and storing the available fields in a collection of fields implicated by each table referenced by the table references, finally, the method includes generating a data model with the fields in the collection of fields and displaying a view of the data model in a user interface of the data analytics application.

Abstract: Extending access to a data model in a data analytics computer data processing system includes loading into a programmatically isolated process address space of a computer, an instance of an extension framework computer program and executing in the framework, computer program logic configured to establish a communicative channel between the isolated process address space and a data analytics computer data processing system executing in a separate process address space. Thereafter, within the framework a directive may be received to access a data model managed in the data analytics computer data processing system. In response, a function may be selected in respect to an API to the data analytics computer data processing system corresponding to the received directive. Finally, the selected API function may be invoked over the communicative channel and a result derived from the data model may be received in the framework from over the communicative channel in response to the selected API function.

Abstract: Data content governance for presentation layer synchronization for a version controlled underlying data model includes defining a data model for underlying data in a database, specifying a presentation layer for the defined data model and identifying selected elements of the data model necessary to meet data requirements of the specified presentation layer. Then, the identified selected elements of the data model are serialized and both the specified presentation layer and the serialized elements are versioned in respect to the specified presentation layer. Thereafter, when the data model becomes modified, the specified presentation layer is modified to accommodate the modified data model. In response to the modification, a different selection of elements of the data model necessary to meet data requirements of the modified presentation layer are re-identified and serialized, with the modified presentation layer and the serialized re-identified different selection of elements becoming re-versioned.

Abstract: A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are stored in association with the user profile.

Abstract: A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Abstract: A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Abstract: A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Abstract: A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Abstract: A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Abstract: A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are stored in association with the user profile.

Abstract: A personal content stream comprising a plurality of videos is generated for a user. The user selects topics used in the generation of a personal content stream. The plurality of user selected topics is expanded to include topics related to one or more of the user selected topics. Each of the topics in the expanded plurality of topics includes a topic weight. Videos are selected that are related to one or more of the expanded plurality of topics to generate a plurality of stream videos. Additional videos are selected and added to the plurality of stream videos as the user watches videos. The topic weights are adjusted during video playback based on feedback from the user.

Abstract: A system and method for developing a user's profile based on the user's interaction with content items. A module on the client rendering the content items or the service including the content items tracks the user's interactions with the content items and transmits the tracked data to a user analysis module. The user analysis module determines the topics associated with the interacted upon content items. The user analysis module then selects the topics for the user's profiles based on the received tracked data and the associated topics. The selected topics are stored in association with the user profile.