Abstract: Provided are systems and methods for automatically detecting a change in screen content and generating a hint message in response. As another example, the system may auto-capture the detected change in the screen content instead of or in addition to the hint message. In one example, a method may include capturing user interface metadata of content being displayed by a client-side of the software application, activating a recorder that is configured to record events transmitted between the client-side and a server-side of the software application, receiving updated user interface metadata based on a user interaction on the client-side of the software application, determining that user interface content has changed based on a comparison of the captured user interface metadata to the updated user interface metadata, and displaying a hint message via the user interface of the client-side of the software application.

Abstract: Techniques are disclosed relating to memory controllers and rate-limited traffic. In some embodiments, an apparatus includes memory controller circuitry configured to satisfy different quality-of-service parameters for multiple different classes of request traffic. The apparatus may also include multiple agents configured to send requests to the memory controller circuitry, where the agents operate according to a rate limit for a first class of traffic. The apparatus may include cache circuitry. In some embodiments, based on an allocation in the cache circuitry for a read operation of the first class that causes an eviction from the cache circuitry, the control circuitry is configured to perform a write operation of evicted data: as the first class of traffic and without counting the write operation toward the rate limit for the first class of traffic. In contrast, the control circuitry may count other write operations of the first class of traffic toward the rate limit.

Abstract: Systems and methods of automated network optimization of large-scale distribution networks are disclosed. A network optimization request is received and an in-memory initial state target network is obtained. A plurality of in-memory intermediate target networks are generated by adding at least one candidate node to the in-memory initial state target network. A distorted incremental gain for each intermediate target network is calculated and one of the intermediate target networks in the plurality of in-memory intermediate target networks having a highest distorted increment gain is identified as an optimal iteration target network. The optimal iteration target network is stored.

Abstract: According to an aspect of the present invention, there is provided a [1,2,4]triazolo[3,4-b]benzothiazole scaffold, which can be used to inhibit efficiently human PARP enzymes. The compounds disclosed bind to the nicotinamide pocket of the enzyme and compete with the natural substrate, NAD*. The present compounds are new types of nicotinamide mimics with wide use as new therapeutics especially against cancer.

Abstract: This disclosure describes techniques and mechanisms for enabling an end point to have concurrent access to multiple private groups within a network. For instance, the private groups may correspond to user defined network (UDN) groups. The techniques described herein include mapping identifiers (e.g., device identifiers, flowlabels, application identifiers, UDN group identifiers, etc.). The techniques enable a user device to access a first UDN group using a first application on the user device and a second UDN group using a second application on the user device, such that a user does not have to leave the first UDN group in order to participate in the second UDN group. Moreover, the assignment of a user device to one or more UDN groups is policy driven and the infrastructure ensures that only the relevant data traffic is forwarded to the group members within a particular UDN group.

Abstract: A memory control circuit coupled to multiple memory ranks may receive read and write requests for a different ranks of the multiple memory ranks. The memory control may allocate write requests to different slots based on the write requests target memory rank, and may adjust the number of slots available for a given memory rank during a write turn to improve write efficiency. The memory control circuit may also determine a number of ranks switches within a read turn based on whether a particular quality-of-service requirement associated with the read requests is being satisfied.

Abstract: Systems and methods for performing a medical imaging analysis task using a machine learning based model (e.g., a foundational model) are provided. One or more input medical images are received. One or more modality-specific expert subnetworks of the machine learning based model are selected for performing a first processing of the one or more input medical images. The first processing of the one or more input medical images is performed for performing a medical imaging analysis task using the one or more selected modality-specific expert subnetworks. Results of the first processing are merged into one or more sets of merged results. One or more cross-modality expert subnetworks of the machine learning based model are selected for performing a second processing of the one or more sets of merged results. The second processing of the one or more sets of merged results is performed for performing the medical imaging analysis task using the one or more selected cross-modality expert subnetworks.

Abstract: Systems and methods for allocating optimal supply chain resources based on order data are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, an allocation request associated with an order; determining a customer node associated with the order, wherein the customer node is in a supply chain network; determining, based on the order and the customer node, a sub-network of the supply chain network; determining, based on cost information associated with the sub-network, at least one path from at least one source node to the customer node in the sub-network; generating supply chain allocation data for the order based on the at least one path; and transmitting the supply chain allocation data to the computing device.

Abstract: A method of issuing one or more commands for a management appliance of a software-defined data center (SDDC) to perform an operation, includes the steps of: retrieving the operation to be performed by the management appliance; transmitting a request to the management appliance for a first token, wherein the first token is associated with permissions for issuing commands to the management appliance, and wherein the request for the first token includes a second token that is associated with the initiator of the operation and that has a longer time-to-live period than the first token has; and upon receiving the first token from the management appliance, transmitting the first token and a command to the management appliance, wherein the command is for the management appliance to execute at least one task of the operation.

Abstract: An example method for encrypting clusters during deployment may include retrieving, from a blueprint, resource information required to deploy a cluster including a host computing system and a virtual cluster manager node to manage the host computing system. The resource information may include host information and disk information required to deploy the virtual cluster manager node, and encryption information associated with a key provider. Based on the host information and the disk information, a clustered datastore may be created on the host computing system. Further, the virtual cluster manager node may be deployed on the clustered datastore. Based on the encryption information associated with the key provider, the virtual cluster manager node and associated disks may be encrypted. Upon encrypting the virtual cluster manager node, a cluster may be created and the host computing system may be added to the cluster.

Abstract: Systems and methods for performing a medical analysis task using a trained machine learning based task network are provided. Input medical data is received. A medical analysis task is performed using a trained machine learning based task network based on the input medical data. Results of the medical analysis task are output. The trained machine learning based task network is trained by: receiving unannotated training medical data; generating weakly-supervised labels for the unannotated training medical data using one or more trained machine learning based supervised learning networks; training the machine learning based task network for performing the medical analysis task based on 1) the unannotated training medical data, 2) self-supervised labels for the unannotated training medical data learned via self-supervised learning, and 3) the generated weakly-supervised labels for the unannotated training medical data; and outputting the trained machine learning based task network.

Abstract: Methods, apparatus, and processor-readable storage media for detecting task-related patterns using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining data associated with at least one task and related to one or more task performance-related metrics; detecting one or more patterns indicative of one or more task performance issues by processing at least a portion of the obtained data using one or more artificial intelligence techniques; generating, using the one or more artificial intelligence techniques, at least one recommendation in response to at least one of the one or more detected patterns; and performing one or more automated actions based at least in part on the at least one recommendation.

Abstract: A method for switching between a first lens and a second lens in an electronic device includes displaying, by the electronic device, a first frame showing a field of view (FOV) of the first lens; detecting, by the electronic device, an event that causes the electronic device to transition from displaying the first frame to displaying a second frame showing a FOV of the second lens; generating, by the electronic device and based on the detecting the event, at least one intermediate frame for transitioning from the first frame to the second frame; and switching, by the electronic device and based on the detecting the event, from the first lens to the second lens and displaying the second frame, wherein the at least one intermediate frame is displayed after the displaying the first frame and before the displaying the second frame while the switching is performed.

Abstract: Techniques that include a network that is configured in the first mode of a reactive mode to respond to a client attempting to access an endpoint of the network by providing information to be sent to a map server and by checking whether at least an IP address associated with the client corresponds to a registration produced for the client by a wireless controller. Further, the network is configured in a second mode of a proactive mode to determine based on a count maintained by a wireless controller of a number of client IP addresses whether to allow access or not to allow access to one or more clients to the network.

Abstract: A client device identifier for dual-Wi-Fi connections may be provided. First, it may be determined that a client device has associated over a first link having a first Media Access Control (MAC) address. Next, from the client device over the first link, a first management frame may be received that identifies a MAC address of a second link associated with the client device. Then, based on information in the first management frame, it may be determined that the first link and the second link are associated with the client device.

Abstract: Systems and methods for performing one or more medical imaging analysis tasks are provided. A sequence of medical images is received. One or more patches are extracted from each image of the sequence of medical images. Spatio-temporal features are extracted from the one or more extracted patches using a machine learning based encoder network. One or more medical imaging analysis tasks are performed based on the extracted spatio-temporal features. Results of the one or more medical imaging analysis tasks are output. The machine learning based encoder network is trained by receiving a sequence of training medical images. Patches of a first set of images of the sequence of training medical images are masked according to a first masking strategy. Patches of a second set of images of the sequence of training medical images are masked according to a second masking strategy.

Abstract: A memory control circuit coupled to multiple memory ranks may receive read and write requests for a different ranks of the multiple memory ranks. The memory control may allocate write requests to different slots based on the write requests target memory rank, and may adjust the number of slots available for a given memory rank during a write turn to improve write efficiency. The memory control circuit may also determine a number of ranks switches within a read turn based on whether a particular quality-of-service requirement associated with the read requests is being satisfied.

Abstract: Certain aspects of the present disclosure provide techniques for automatically detecting and classifying tumor regions in a tissue slide. The method generally includes obtaining a digitized tissue slide from a tissue slide database and determining, based on output from a tissue classification module, a type of tissue of shown in the digitized tissue slide. The method further includes determining, based on output from a tumor classification model for the type of tissue, a region of interest (ROI) of the digitized tissue slide and generating a classified slide showing the ROI of the digitized tissue slide and an estimated diameter of the ROI. The method further includes displaying on an image display unit, the classified slide and user interface (UI) elements enabling a pathologist to enter input related to the classified slide.

Abstract: The present invention discloses an N-substituted bicyclic heteroaromatic compound of formula (I), wherein, R, R1, R2, R4, W1, W2, A and Het are as defined in the detailed description. The present invention further discloses methods for preparation of compounds of formula (I) and use of the compounds of formula (I) as a pest control agent.

Abstract: Techniques for analyzing traffic originating from a host device in a wireless network to identify one or more virtual machines (VMs) running on the host device and connected to the network via the host device in bridge mode. When a VM is created in bridge mode behind a host device, the traffic originated by the VM will have the source Media Access Layer (MAC) address of the host device. According to techniques described herein, devices and/or components associated with the network may profile the traffic to identify an address of the VM, such as by analyzing dynamic host configuration protocol (DHCP) packets to determine the Internet Protocol (IP) address of the VM. Once the IP address and the MAC address of the VM is known, the components and/or devices may apply security policies to the VM that may be different than security policies applied to the host device.