Abstract: A set of incident records are received for a computing system. The incident records are analyzed to identify similar incident records which are then linked. Incident clusters are generated based upon the links and incident records in each cluster are ranked. A prompt is generated to an artificial intelligence (AI) model based on the ranked, related incidents and the AI model returns a response that identifies a root cause and mitigation steps corresponding to the ranked incidents.

Abstract: Implementations relate to managing multimedia content that is obtained by large language model(s) (LLM(s)) and/or generated by other generative model(s). Processor(s) of a system can: receive natural language (NL) based input that requests multimedia content, generate a response that is responsive to the NL based input, and cause the response to be rendered. In some implementations, and in generating the response, the processor(s) can process, using a LLM, LLM input to generate LLM output, and determine, based on the LLM output, at least multimedia content to be included in the response. Further, the processor(s) can evaluate the multimedia content to determine whether it should be included in the response. In response to determining that the multimedia content should not be included in the response, the processor(s) can cause the response, including alternative multimedia content or other textual content, to be rendered.

Abstract: The invention relates to activators of FXR useful in the treatment of autoimmune disorders, liver disease, intestinal disease, kidney disease, cancer, and other diseases in which FXR plays a role, having the Formula (I): wherein L1, A, X1, X2, R1, R2, and R3 are described herein.

Abstract: Apparatus for generating electro-anatomical mapping and methods used therein include a processor and a memory connected to the processor, wherein the memory contains instructions configuring the processor to receive input data, generate, using at least a machine learning model, an electro-anatomical mapping as a function of the input data, and display the electro-anatomical mapping using a user interface, wherein receiving the input data includes receiving, from an imaging device, at least a medical image and receiving, from a signal capturing device, at least an electrogram, wherein the at least a machine learning model is trained using electro-anatomical mapping training data including exemplary medical images and exemplary electrograms as input correlated to exemplary electro-anatomical mappings as output.

Abstract: Methods and systems for detecting systemwide service issues by using anomaly localization. In an example, a method includes receiving time-series monitoring data for multiple services, the time-series monitoring data including multiple dimensions and an error metric; for the monitoring data from each service, evaluating scopes within the monitoring data based on an objective function for a time-series of the error metric to identify at least one anomalous scope, each scope including at least one dimension and a value for the dimension; based on evaluating the scopes, generating a ranked list of scopes for each service based on objective function scores for the scopes; correlating the ranked lists of scopes across the multiple services to identify a cross-service anomaly; and generating an alert for the services based on the cross-service anomaly, the alert indicating at least one scope as a potential root cause for the cross-service anomaly.

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: The invention relates to non-systemic TGR5 agonist useful in the treatment of chemotherapy-induced diarrhea, diabetes, Type II diabetes, gestational diabetes, impaired fasting glucose, impaired glucose tolerance, insulin resistance, hyperglycemia, obesity, metabolic syndrome, ulcerative colitis, Crohn's disease, disorders associated with parenteral nutrition especially during short bowel syndrome, and irritable bowel syndrome (IBS), and other TGR5 associated diseases and disorders, having the Formula: where R1, R2, R2?, R3, R4, X1, X2, X3, X4, Q, and n are described herein.

Abstract: Some implementations described herein relate to a system for generating identifiers. The system receives, from a device, a request to generate a plurality of identifiers. The system determines, based on receiving the request and by performing a parameter locking operation, a compute region parameter associated and a timestamp parameter. The system generates, based on the compute region parameter and the timestamp parameter, a set of one or more identifiers of the plurality of identifiers. Respective portions of each identifier, of the set of one or more identifiers, may indicate the compute region parameter, a version parameter associated with the parameter locking operation, the timestamp parameter, a counter value parameter, and an action parameter. The system processes, using a scrambling technique, the set of one or more identifiers and provides the set of one or more identifiers to the device.

Abstract: Implementations relate to generating multi-modal response(s) through utilization of large language model(s) (LLM(s)). Processor(s) of a system can: receive natural language (NL) based input, generate a multi-modal response that is responsive to the NL based output, and cause the multi-modal response to be rendered. In some implementations, and in generating the multi-modal response, the processor(s) can process, using a LLM, LLM input (e.g., that includes at least the NL based input) to generate LLM output, and determine, based on the LLM output, textual content for inclusion in the multi-modal response and multimedia content for inclusion in the multi-modal response. In some implementations, the multimedia content can be obtained based on a multimedia content tag that is included in the LLM output and that is indicative of the multimedia content. In various implementations, the multimedia content can be interleaved between segments of the textual content.

Abstract: The invention relates to activators of FXR useful in the treatment of autoimmune disorders, liver disease, intestinal disease, kidney disease, cancer, and other diseases in which FXR plays a role, having the Formula (I): wherein L1, A, X1, X2, R1, R2, and R3 are described herein.

Abstract: An apparatus may comprise a memory communicatively coupled to a processor. The memory may be configured to store a start script configured to enable execution of one or more middleware instances and multiple start-up files configured to indicate any middleware instances to be executed by an admin server or one or more managed servers. The processor may be configured to trigger initiation of the start script, determine whether the start-up files comprise a middleware instance, ping the admin server in response to determining that the start-up files comprise the middleware instance, and determine that the admin server is running. Further, the processor is configured to ping the managed server associated with databases associated with a managed server, determine that the databases are running, and trigger a start of the middleware instance at the admin server or at the managed server.

Abstract: An apparatus may comprise a memory communicatively coupled to a processor. The memory may be configured to store an installer script configured to install multiple middleware scripts in an admin server, and one or more installed middleware instances. The processor may be configured to trigger initiation of the installer script, install the middleware scripts over a predefined time period, determine whether the one or more installed middleware instances comprises an installed middleware instance, and determine whether an operation performed by the admin server is associated with the installed middleware instance in response to determining that the one or more installed middleware instances comprises the installed middleware instance. Further, the processor may be configured to generate a middleware flag indicating that the installed middleware instance is active, and generate multiple start-up files comprising a middleware instance corresponding to the installed middleware instance.

Abstract: A device is configured to detect a communication error between a first network device and a second network device. The device is further configured to identify a first node in a computer network map corresponding with the first network device and to identify node properties for the first node. Error correction instructions in the node properties for the first node include an address for rerouting data traffic to a third network device. The device is further configured to apply the error correction instructions where applying the error correction instructions suspends data traffic to the second network device and reroutes data traffic to the third network device.

Abstract: Systems, methods, and computer program products are provided for monitoring network processing using node analysis. The method includes receiving node operation information relating to a node command from one or more nodes. The one or more nodes are grouped into a cluster. The method also includes determining one or more node characteristics based on the node operation information. The method further includes comparing the node characteristic(s) of the node command to expected node characteristic(s). The method still further includes determining a node outage likelihood. The node outage likelihood indicates the likelihood the given node will experience a node outage. The method also includes determining a cluster node operation plan. The cluster node operation plan is configured to determine the nodes of the cluster that must be in operation in an event of the node outage of the given node.

Abstract: The invention relates to non-systemic TGR5 agonist useful in the treatment of chemotherapy-induced diarrhea, diabetes, Type II diabetes, gestational diabetes, impaired fasting glucose, impaired glucose tolerance, insulin resistance, hyperglycemia, obesity, metabolic syndrome, ulcerative colitis, Crohn's disease, disorders associated with parenteral nutrition especially during short bowel syndrome, and irritable bowel syndrome (IBS), and other TGR5 associated diseases and disorders, having the Formula: where R1, R2, R2?, R3, R4, X1, X2, X3, X4, Q, and n are described herein.

Abstract: One or more computer processors route one or more packets within an application that comprises a plurality of pods distributed in a multi-cloud environment. The one or more computer processors deploy one or more created proxies as one or more sidecar containers for each pod in the plurality of pods, wherein the sidecar containers run with an application container. The one or more computer processors apply a set of routing rules to each pod in the plurality of pods, wherein all traffic is routed between the one or more created proxies based on the set of routing rules.

Abstract: Embodiments of the invention are directed to a computer system that includes a memory electronically coupled to a processor system. The processor system is operable to perform processor system operations that include accessing a graph model representation of a computer network. The graph model is used to implement a resiliency-problem identification analysis that identifies a set of resiliency problems in the graph model. The graph model is used to apply a resiliency-problem solution analysis to a resiliency problem in the set of resiliency problems to generate a set of resiliency-problem solutions. Each resiliency-problem solution in the set of resiliency-problem solutions is ranked.

Abstract: An improved heterostructure for an optoelectronic device is provided. The heterostructure includes an active region, an electron blocking layer, and a p-type contact layer. The heterostructure can include a p-type interlayer located between the electron blocking layer and the p-type contact layer. In an embodiment, the electron blocking layer can have a region of graded transition. The p-type interlayer can also include a region of graded transition.

Abstract: An apparatus includes a cable having two ends and at least two object markers coupled to the cable configured to enable augmented reality (AR) detection of each end of the cable among a plurality of cables. A computer-implemented method using augmented reality (AR) technology includes selecting a cable of interest and identifying an object marker positioned toward a first end of the cable of interest. The method also includes storing the object marker, scanning a plurality of cables, and identifying a second end of the cable of interest based an instance of the object marker positioned toward the second end of the cable of interest. A computer program product for detecting ends of cables using augmented reality (AR) technology includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a computer to cause the computer to perform the foregoing method.

Abstract: A device is configured to detect a communication error between a first network device and a second network device. The device is further configured to identify a first node in a computer network map corresponding with the first network device and to identify node properties for the first node. Error correction instructions in the node properties for the first node include an address for rerouting data traffic to a third network device. The device is further configured to apply the error correction instructions where applying the error correction instructions suspends data traffic to the second network device and reroutes data traffic to the third network device.