Abstract: Aspects of the disclosure relate to prioritizing messages for server processing based on monitoring and predicting server resource utilization. A computing platform may monitor a plurality of servers (e.g., processing engines) to determine a current processing capacity and a maximum processing capacity of each processing engine. The computing platform may predict a quantity of application messages that may be received and/or processed by each processing engine at a later time. The computing platform may generate an application message prioritization framework comprising the prediction, the current processing capacity, and the maximum processing capacity of each processing engine.

Abstract: A node in a segment routing version 6 (SRv6) network includes circuitry configured to transmit and receive packets in the SRv6 network with a segment routing header (SRH) that supports one or more of a Reduced mode and a Non-reduced mode, transmit via transmitted routing updates to one or more nodes in the SRv6 network which of the one or more of the Reduced mode and the Non-reduced mode are supported by the node, and receive via received routing updates from the one or more nodes their corresponding support for the one or more of the Reduced mode and the Non-reduced mode.

Abstract: Two versions of a database can be held in two trees that have many of the same nodes. Both trees can be concurrently searched using recursive algorithms. A root node indicator indicates a root node for a tree search algorithm. The root node indicator can indicate a first root node of a first tree. A tree search algorithm can identify a record node in the first tree. Intermediate nodes between the record node and the first root node can be identified and retained nodes can be identified. A second root node and replacement intermediate nodes can be instantiated. A second tree that includes the second root node, the replacement intermediate node, and the retained nodes can be created. The root node indicator can be set to indicate the second root node after creating the second tree.

Abstract: An EtherCAT device includes a communications circuit and a wakeup circuit. The wakeup circuit is configured to determine a condition in which to send data to an EtherCAT master node. The wakeup circuit, based on such a condition, is configured to generate a wakeup packet. The communications circuit may be configured to receive an EtherCAT frame originating from the EtherCAT master node. The communications circuit may be configured to populate the EtherCAT frame with the data to be sent to the EtherCAT master node. The communications circuit may be configured to send the EtherCAT frame to the EtherCAT master device.

Abstract: Methods and system for directing traffic flows to a fast data path or a slow data path are disclosed. Parsers can produce packet header vectors (PHVs) for use in match-action units. The PHVs are also used to generate feature vectors for the traffic flows. A flow training engine produces a classification model. Feature vectors input to the classification model result in output predictions predicting if a traffic flow will be long lived or short lived. The classification models are used by network appliances to install traffic flows into fast data paths or the slow data paths based on the predictions.

Abstract: A vehicle includes: an engine assembly including a cylinder head, an engine output shaft, and a crankshaft; and an electric motor assembly transversely disposed above a crankcase of the engine assembly. The electric motor assembly includes an electric motor and an electromagnetic clutch mounted coaxially on the electric motor.

Abstract: A method for identifying documents that are similar in content to an input document includes receiving a request for identifying similar documents from among a plurality of candidate documents, retrieving document classification attributes for the input document and the candidate documents, where the document classification attributes are document level attributes.

Abstract: An EtherCAT device with a node for use in an EtherCAT network is disclosed. The EtherCAT device includes: a clock circuit; a clock input to receive an input clock signal; a clock output to send an output clock signal; and control logic. The control logic is to determine whether to operate the EtherCAT device in a clock generation mode or a clock propagation mode, wherein in the clock generation mode, the clock circuit is to drive an oscillator to generate the input clock signal; and in the clock propagation mode, the clock circuit is to receive the input clock signal from another node in the EtherCAT network. The control logic is further to control the clock circuit to output the output clock signal for a subsequent node in the EtherCAT network based upon the input clock signal.

Abstract: An EtherCAT device is disclosed. The EtherCAT device comprises a data input port to receive a signal representing data, the signal representing one of a plurality of possible logical values; and a degradation calculation circuit. The degradation calculation circuit is to read, demodulate, and convert the received signal into a digital domain representation; process the digital domain representation into slices, where the value of the received signal at a respective time is represented in a respective one of the slices; determine differences between the respective slices and reference slices; identify an intended logical value of the received signal responsive to the determined differences; determine a quantification of error at the respective time responsive to the identified logical value and the determined differences; and determine a signal quality index responsive to the determined quantification of error.

Abstract: A method for identifying documents that are similar in content to an input document includes receiving a request for identifying similar documents from among a plurality of candidate documents, retrieving document classification attributes for the input document and the candidate documents, where the document classification attributes are document level attributes.

Abstract: An illustrative method includes providing, by an orchestrator implemented on top of a plurality of clusters, a client-facing interface; receiving, by the orchestrator by way of the client-facing interface, a request to deploy a containerized application; selecting, by the orchestrator and based on the request, a cluster from the plurality of clusters; and deploying, by the orchestrator, the containerized application to the selected cluster.

Abstract: A system for characterizing a specimen is disclosed. In one embodiment, the system includes a characterization sub-system configured to acquire one or more images a specimen, and a controller communicatively coupled to the characterization sub-system. The controller may be configured to: receive from the characterization sub-system one or more training images of one or more defects of a training specimen; generate one or more augmented images of the one or more defects of the training specimen; generate a machine learning classifier based on the one or more augmented images of the one or more defects of the training specimen; receive from the characterization sub-system one or more target images of one or more target features of a target specimen; and determine one or more defects of the one or more target features with the machine learning classifier.

Abstract: Generally discussed herein are systems, apparatuses, and methods for providing information regarding a product that is unique to a geographical region. In one or more embodiments a method may include determining a location of a user, receiving information indicative of one or more products unique to a particular geographical region corresponding to the determined location of the user, wherein each of the one or more products are offered for sale in the particular region by one or more merchants, and providing information about at least one of the products and about a merchant, from the one or more merchants, offering that product for sale in the geographical region.

Abstract: In some embodiments, storage operation routing in a container system may include receiving, by a container storage system executing on a node within a container system, a storage operation configured to be performed with respect to a storage resource; determining whether the storage resource is locally accessible at the node; and routing the storage operation based on the determining of whether the storage resource is locally accessible at the node. For example, the routing may be performed such that when the storage resource is not locally accessible at the node, the routing is by way of both a kernel space and a user space of the node, and when the storage resource is locally accessible at the node, the routing is contained within the kernel space of the node. Corresponding methods and systems are also disclosed.

Abstract: In some embodiments, storage path routing in a container system includes: determining, within the container system, a storage operation directed to a storage resource; determining one or more conditions associated with a plurality of network paths to the storage resource, where the plurality of network paths includes a first network path through a storage area network and a second network path through a container system communication network; and routing, based on the one or more conditions, the storage operation to the storage resource using the first network path.

Abstract: A method includes providing a computer system, the computer system including at least a processor and a memory, the memory including at least an operating system, executing a process in the memory, the process including providing a recurrent circuit model, and converting the recurrent circuit model into a recurrent neural network that can be fit with gradient descent.

Abstract: An illustrative distributed storage system detects a request to resize an online volume that provides persistent storage for a containerized application running in a container system, wherein the online volume is backed by a virtual block device created in device namespace using a device mapper virtualization of data blocks of one or more storage devices. The distributed storage system performs, in response to the request, a resize process to resize the online volume. The resizing of the online volume includes resizing the virtual block device. In some examples, a file system implemented on the virtual block device is also resized while the online volume is online. The storage system may manage inflight IOs over the virtual block device and the online volume such that the resize process is performed without error.

Abstract: Two versions of a database can be held in two trees that have many of the same nodes. Both trees can be concurrently searched using recursive algorithms. A root node indicator indicates a root node for a tree search algorithm. The root node indicator can indicate a first root node of a first tree. A tree search algorithm can identify a record node in the first tree. Intermediate nodes between the record node and the first root node can be identified and retained nodes can be identified. A second root node and replacement intermediate nodes can be instantiated. A second tree that includes the second root node, the replacement intermediate node, and the retained nodes can be created. The root node indicator can be set to indicate the second root node after creating the second tree.

Abstract: A calendar application server, a computer-readable storage medium, and corresponding methods for third-party resource management within the context of a calendar application are described herein. The computer-readable storage medium includes computer-executable instructions that, when executed one or more processors, cause the processor(s) to associate a third-party resource with an event within a calendar application in response to a user command received via an event UI functionality provided by the calendar application, to connect with the third-party resource via an API corresponding to the third-party resource in response to another user command received via the event UI functionality (where the API is provided within the context of the calendar application), to generate third-party resource data for the event in response to user interaction with the third-party resource via the API, and to reconcile the third-party resource data with event data within the calendar application.

Abstract: Methods and systems for determining information for a specimen are provided. One system includes a computer subsystem and one or more components executed by the computer subsystem. The one or more components include a deep learning model configured for denoising an image of a specimen generated by an imaging subsystem. The computer subsystem is configured for determining information for the specimen from the denoised image.