Abstract: The present disclosure relates to a closed loop aptamer development system that leverages in vitro experiments and in silico computation and artificial intelligence-based techniques to iteratively improve a process for identifying binders that can bind a molecular target. Particularly, aspects of the present disclosure are directed to obtaining, using an experimental assay, experimental data for a set of aptamers. The experimental data includes multiple pairs of data, each pair of data having: (i) an aptamer sequence for an aptamer from a set of aptamers, and (ii) a measurement for the characteristic of the aptamer with respect to a given target. A reward model is fine-tuned, using the experimental data, to predict a function-approximation metric for the characteristic of each aptamer in the set of aptamers. A decoder model is fine-tuned for generating novel aptamer sequences based on the function-approximation metric generated by the reward model for the novel aptamer sequences.

Abstract: A system and method for making engagement offers. A processor monitors a navigation path of a user navigating a website. The processor makes an offer for engagement with the user on a first web page reached by the user upon following the navigation path. The processor monitors a reaction of the user to the offer for engagement, and updates tag data associated with a second web page encountered by the user while traversing the navigation path. The tag data is updated based on the reaction of the user to the offer for engagement.

Abstract: Systems and methods are shown for routing task objects to multiple agents that involve analyzing content of each task object in an input buffer to determine a classification relevant to the content of the task object that is added to task object metadata, which is placed in a second buffer. Objects in the second buffer are analyzed and the classification in the object metadata used to search workforce management data representing agent characteristics to identify agents who match the classification. A routing strategy is applied to the object to select an agent and the object is routed to the agent's workbin. Another aspect involves organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data, and presenting remaining objects based on order of priority, or re-arranging objects between workbins based on recent status info.

Abstract: A system and method for proactively making knowledge offers. A processor is configured to gather information on interactions by a user with resources provided by an enterprise having a customer contact center. The processor anticipates need of the user based on the gathered information, and generates a query based on the anticipated need. Prior to the user expressly requesting knowledge relating to a particular topic, the processor proactively identifies and suggests the knowledge to the user based on the generated query. The processor receives feedback relating to the suggested knowledge and outputs based on the feedback, a relevance score for the suggested knowledge.

Abstract: Systems and methods are shown for routing task objects to multiple agents that involve analyzing content of each task object in an input buffer to determine a classification relevant to the content of the task object that is added to task object metadata, which is placed in a second buffer. Objects in the second buffer are analyzed and the classification in the object metadata used to search workforce management data representing agent characteristics to identify agents who match the classification. A routing strategy is applied to the object to select an agent and the object is routed to the agent's workbin. Another aspect involves organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data, and presenting remaining objects based on order of priority, or re-arranging objects between workbins based on recent status info.

Abstract: Systems and methods are shown for routing task objects to multiple agents that involve analyzing content of each task object in an input buffer to determine a classification relevant to the content of the task object that is added to task object metadata, which is placed in a second buffer. Objects in the second buffer are analyzed and the classification in the object metadata used to search workforce management data representing agent characteristics to identify agents who match the classification. A routing strategy is applied to the object to select an agent and the object is routed to the agent's workbin. Another aspect involves organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data and presenting remaining objects based on order of priority, or re-arranging objects between workbins based on recent status info.

Abstract: Systems and methods are shown for organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data, and presenting remaining objects to an agent based on order of priority or workflow strategy.

Abstract: Systems and methods are shown for routing task objects to multiple agents that involve analyzing content of each task object in an input buffer to determine a classification relevant to the content of the task object that is added to task object metadata, which is placed in a second buffer. Objects in the second buffer are analyzed and the classification in the object metadata used to search workforce management data representing agent characteristics to identify agents who match the classification. A routing strategy is applied to the object to select an agent and the object is routed to the agent's workbin. Another aspect involves organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data and presenting remaining objects based on order of priority, or re-arranging objects between workbins based on recent status info.

Abstract: Systems and methods are shown for organizing workbin tasks objects by priority, according to recent system conditions excluding objects that cannot presently be processed based on a workflow strategy or status data, and presenting remaining objects to an agent based on order of priority or workflow strategy.

Abstract: A system and method for making engagement offers. A processor monitors a navigation path of a user navigating a website. The processor makes an offer for engagement with the user on a first web page reached by the user upon following the navigation path. The processor monitors a reaction of the user to the offer for engagement, and updates tag data associated with a second web page encountered by the user while traversing the navigation path. The tag data is updated based on the reaction of the user to the offer for engagement.

Abstract: An integrated circuit device for use in forming a communication interface for an enterprise server including a system controller, at least one CPU, a system bus communicatively interconnecting the controller and the CPU, a system memory, a first optical interface for facilitating data transport between the device and SONET based networks, and a second optical interface for facilitating data transport between the device and ethernet/Fibre Channel based networks.

Abstract: A method for scheduling a flag generating instruction and a subsequent instruction. The subsequent instruction has a data dependency on the flag generating instruction. The flag generating instruction is translated into first and second instructions. The subsequent instruction is translated into at least a third instruction. The first instruction, when executed, generates a result and intermediate flag generation data. The second instruction, when executed, generates a plurality of flags. The first instruction is scheduled to execute before the second and third instructions. The second instruction is scheduled to execute before the third instruction if the third instruction has a data dependency on the second instruction, otherwise the third instruction may be scheduled to execute before the second instruction.

Abstract: A microprocessor capable of renaming a numeric register and a segment register includes a plurality of general registers and a data dependency unit. The data dependency unit is configured to receive instructions to be executed, wherein the instructions include accessing the numeric register and accessing the segment register. The data dependency unit renames the numeric register as one of the plurality of general registers for each of the instructions accessing said numeric register, renames the segment register as one of the plurality of general registers for each of the instructions accessing the segment register, and generates a dependency vector for each of the instructions. The microprocessor may include a scheduler configured to receive the instructions and dependency vector and schedule the instructions for execution based on the dependency vector, and an execution engine adapted to receive the instructions from the scheduler and execute the instructions.