Abstract: A user equipment (UE) or other device performs service discovery of edge computing resources in a cellular network system and dynamic offloading of UE application tasks to discovered edge computing resources. As part of the discovery process, the device (e.g., the UE) may request edge server site capability information. When performing dynamic offloading, the UE may obtain (collect and/or receive) information regarding channel conditions, cellular network parameters or application requirements and dynamically determine whether a task of the application executing on the UE should be offloaded to an edge server or executed locally on the UE. In making decisions between offloaded or local execution, the UE may use a utility function that takes into account factors such as relative differences in application latency, energy consumption and offloading cost.

Abstract: A method of providing a custom visual marking on a earing device includes: providing a hearing device comprising a behind-the-ear (BTE) component, an in-the-ear (ITE) component, and a connector having a proximal end connected to the ITE component and a distal end connected to the BTE component, the connector comprising a flexible member extending between the proximal and distal ends; arranging the BTE component behind the ear of the user, and arranging the ITE component in the ear canal of the user so that the connector has a covered portion inserted in the ear canal and an exposed portion outside the ear canal; and providing a visual marking on the connector, wherein the visual marking distinguishes the covered portion from the exposed portion. Further disclosed is a connector and a hearing device.

Abstract: An exemplary system according to the present disclosure comprises a computing device that in operation, causes the system to receive financial product or financial portfolio data, map the financial product to a risk factor, execute a risk factor simulation process involving the risk factor, generate product profit and loss values for the financial product or portfolio profit and loss values for the financial portfolio based on the risk factor simulation process, and determine an initial margin for the financial product. The risk factor simulation process can be a filtered historical simulation process.

Abstract: An asparagine-linked glycan (N-glycan) detection reagent is provided that utilizes Fbs variants engineered from mouse Fbs proteins, wherein the Fbs variants bind specifically to N-glycosylated peptides and proteins and not to non-glycosylated peptides and proteins, including wherein the Fbs variants bind to N-glycosylated peptides and proteins and not to corresponding non-glycosylated versions of the same peptides and proteins. Compositions and methods for developing and using N-glycosylation-specific analytical, diagnostic, and therapeutic tools are provided.

Abstract: An exemplary system according to the present disclosure comprises a computing device that in operation, causes the system to receive financial product or financial portfolio data, map the financial product to a risk factor, execute a risk factor simulation process involving the risk factor, generate product profit and loss values for the financial product or portfolio profit and loss values for the financial portfolio based on the risk factor simulation process, and determine an initial margin for the financial product. The risk factor simulation process can be a filtered historical simulation process.

Abstract: An exemplary system according to the present disclosure comprises a computing device that in operation, causes the system to receive financial product or financial portfolio data, map the financial product to a risk factor, execute a risk factor simulation process involving the risk factor, generate product profit and loss values for the financial product or portfolio profit and loss values for the financial portfolio based on the risk factor simulation process, and determine an initial margin for the financial product. The risk factor simulation process can be a filtered historical simulation process.

Abstract: Techniques are disclosed for executing a data processing pipeline. The techniques may include receiving a job at a data pipeline queue, setting up one or more distributed processing environments, and allocating the job to one of the distributed processing environments. The techniques may further include receiving the allocated job at a job queue within the distributed processing environment, increasing a priority level of the job, and executing the job within the distributed processing environment. The techniques can further include providing a retry pipeline at the data processing pipeline, and re-executing the job at a stage following a failure of at least one of its components. The techniques may decrement the retry budget as the job is re-executed.

Abstract: Embodiments are disclosed for performing automation services. Automation services are, in embodiments, applications, processes, or systems capable of converting an initial file into a converted file having a different file type from the initial file. In embodiments, a requestor generates a conversion request message. The conversion request message may contain information about the desired conversion, options to be performed during the conversion, and an initial file that is to be converted. The initial file may be represented by a data stream that is part of the request message. The request message is sent to a file converter that performs the desired request on the data stream to create a converted file.