Abstract: There is described a vector for treating Dopamine Transporter Deficiency Syndrome, the vector comprising a promoter operably linked to a human SLC6A3 gene, wherein the promoter is selected from a human synapsin 1 promoter, a CAG promoter, a CMV promoter, a CAMKII promoter, a beta-actin promoter, and a human EF1-alpha promoter. Also described are methods and uses involving the vector for treating Dopamine Transporter Deficiency Syndrome.

Abstract: A system and method for automatic remediation of non-compliance events are provided. In embodiments, a computer-implemented method includes: accessing a compliance profile and a remediation profile, wherein the compliance profile includes compliance data regarding rules for an enterprise and the remediation profile includes remediation data regarding remediation actions to address non-compliance with one or more of the rules; generating mapped data by mapping compliance data in the compliance profile to remediation data in the remediation profile; receiving non-compliance event data from a workload node in a network; extracting information from the non-compliance event data including the workload node associated with the event and a cause of event; determining a remediation action for the event based on the information and the mapped data; and invoking automatic performance of the remediation action at the workload node based on the determined remediation action.

Abstract: A system and method for automatic remediation of non-compliance events are provided. In embodiments, a computer-implemented method includes: accessing a compliance profile and a remediation profile, wherein the compliance profile includes compliance data regarding rules for an enterprise and the remediation profile includes remediation data regarding remediation actions to address non-compliance with one or more of the rules; generating mapped data by mapping compliance data in the compliance profile to remediation data in the remediation profile; receiving non-compliance event data from a workload node in a network; extracting information from the non-compliance event data including the workload node associated with the event and a cause of event; determining a remediation action for the event based on the information and the mapped data; and invoking automatic performance of the remediation action at the workload node based on the determined remediation action.

Abstract: A hash accelerator of a cache memory may receive a query from a processor comprising the cache memory, the query to comprise an input key and an operation to be performed based on a hash table stored in the cache memory. The hash accelerator may determine whether an entry associated with the input key exists in a lock board of the hash accelerator. The hash accelerator may process the query based on whether the entry exists in the lock board.

Abstract: Methods, computer program products, and systems can include obtaining a first computing environment specific application deployment software code instance associated to a first computing environment, the first computing environment specific application deployment software code instance for deployment of a certain application on the first computing environment; parsing the first computing environment specific application deployment software code instance, wherein the parsing includes determining attributes of the first computing environment specific application deployment software code instance and generating, using the determined attributes of the first computing environment specific application deployment software code instance, a computing environment agnostic semantic tree data structure that expresses a workflow pattern for deployment of the certain application; and composing, with use of the computing environment agnostic semantic tree data structure, a second computing environment specific application d

Abstract: Inflight transactions having predictable pod failure in distributed computing environments are managed by integrating a transaction manager into pods having containers running applications in a distributed computing environment, wherein the transaction manager records a transaction log having data indicative of historical pod failure. A pod health check that is also integrated into the pods determines predictive pod failure scenarios from the data of historical pod failure in the transaction log. Pod health can be tracked using the pod health checker by matching the predictive pod failure scenarios to transaction calls. Calls may be sent to a load balancer for recovery of pod failure for transaction calling match the predictive pod failure scenarios. Pods can be configured recover for the predictive pod failure.

Abstract: Method and apparatus for predicting a transaction's outcome in a transaction processing environment are provided. A transaction request is received by a transaction processing monitor (TPM), where the transaction request comprises a plurality of tags. The TPM identifies historical prior transactions corresponding to the transaction request, and determines a plurality of historical tags associated with those historical transactions. The TPM then determines whether a predicted execution time exceeds the transaction request's timeout, and proceeds accordingly. If the predicted execution time exceeds the timeout value, the transaction is immediately returned as failed. The tags associated with a given transaction request are repeatedly updated as the request traverses the transaction processing system, and the transaction is repeatedly verified to ensure that it can still be completed successfully.

Abstract: A DNN accelerator includes a multiplication controller controlling whether to perform matrix computation based on weight values. The multiplication controller reads a weight matrix from a WRAM in the DNN accelerator and determines a row value for a row in the weight matrix. In an embodiment where the row value is one, a first switch sends a read request to the WRAM to read weights in the row and a second switch forms a data transmission path from an IRAM in the DNN accelerator to a PE in the DNN accelerator. The PE receives the weights and input data stored in the IRAM and performs MAC operations. In an embodiment where the row value is zero, the first and second switches are not triggered. No read request is sent to the WRAM and the data transmission path is not formed. The PE will not perform any MAC operations.

Abstract: Embodiments relate to an intelligent computer platform to support a chatbot platform. A semantically enriched document is subjected to natural language processing to generate a cache of tokens, and further classify the tokens, including noun and verb tokens. For each verb token, a corresponding intent is generated, and for each noun token a corresponding entity is generated. A relationship between the generated intents and entities is mapped, and a topology representing the mapped relationship is constructed. A primary verb is identified and assigned as a root node in the topology, and an arrangement of entities related to primary verb are identified and assigned as child nodes related to the root node. The constructed topology is consumed to an AI schema for implementation in the chatbot platform to support real-time communication flow.

Abstract: A system and method for automatic remediation of non-compliance events are provided. In embodiments, a computer-implemented method includes: accessing a compliance profile and a remediation profile, wherein the compliance profile includes compliance data regarding rules for an enterprise and the remediation profile includes remediation data regarding remediation actions to address non-compliance with one or more of the rules; generating mapped data by mapping compliance data in the compliance profile to remediation data in the remediation profile; receiving non-compliance event data from a workload node in a network; extracting information from the non-compliance event data including the workload node associated with the event and a cause of event; determining a remediation action for the event based on the information and the mapped data; and invoking automatic performance of the remediation action at the workload node based on the determined remediation action.

Abstract: The present invention may include a method for automatic correction and migration of a plurality of bulk data. The method may identify sources, where the sources include the plurality of bulk data. The method may identify a subset of the bulk data, where the subset represents one or more records selected from the plurality of bulk data. The method may upload the subset to an enterprise application. The method may determine an error list from the enterprise application based on the uploaded subset. The method may roll back the subset from the enterprise application and based on the determined error list, the method may match one or more rules to a one or more errors in the error list.

Abstract: Embodiments relate to an intelligent computer platform to support a chatbot platform. A semantically enriched document is subjected to natural language processing to generate a cache of tokens, and further classify the tokens, including noun and verb tokens. For each verb token, a corresponding intent is generated, and for each noun token a corresponding entity is generated. A relationship between the generated intents and entities is mapped, and a topology representing the mapped relationship is constructed. A primary verb is identified and assigned as a root node in the topology, and an arrangement of entities related to primary verb are identified and assigned as child nodes related to the root node. The constructed topology is consumed to an AI schema for implementation in the chatbot platform to support real-time communication flow.

Abstract: A method and associated systems improve access time of a federated repository that represents a set of individual data repositories as a virtualized aggregated repository. An analyzer module counts the number of entries in each individual repository that are associated with each possible value of a selected concordance parameter. The analyzer stores these counts in a Concordance Frequency Table. When the federated-repository manager receives a data-access request, the analyzer associates the requested data element with a corresponding value of the concordance parameter. The analyzer then uses information stored in the Table to select an optimal sequence in which the federated-repository manager should search the repositories for the requested data. This optimal sequence orders the repositories such that the first repositories to be searched will be those that contain the greatest number of entries associated with the concordance-parameter value of the requested data.

Abstract: A client facility is provided for establishing a subscription to a streaming service provider, without loss of events. The establishing includes generating, by the client, a subscription request to the streaming service provider of events. The generating includes determining, based on an event offset maintained by the client, identifying data of a most-recently received event from the streaming service provider for a topic of the subscription. The identifying data of the most-recently received event from the streaming service provider for the topic is used in customizing the subscription request with a topic configuration which requests the streaming service provider to resume streaming events from the most-recently received event identified in the event offset for the topic. Therefore, an interrupted streaming subscription may be reestablished without loss of events.

Abstract: A cloud-management system intercepts API calls from a client application. Based on the expected amount of cloud resources required to service the API call, and given the terms of the client's billing plan, the system estimates the cost to service the call. The system embeds this cost into its response to the API call and the client application, or an IDE hosting the application, keeps a running total of API-related costs incurred by the application. The system can also run in an emulation mode, estimating the application's API resource-consumption costs without actually consuming cloud resources. In this mode, the system replaces each GET and PUT call in the intercepted API call with an equivalent HEAD call that does not consume resources. The system still, however, predicts the actual cost of the original API call by returning the cost of each original GET and PUT.

Abstract: Method and apparatus for predicting a transaction's outcome in a transaction processing environment are provided. A transaction request is received by a transaction processing monitor (TPM), where the transaction request comprises a plurality of tags. The TPM identifies historical prior transactions corresponding to the transaction request, and determines a plurality of historical tags associated with those historical transactions. The TPM then determines whether a predicted execution time exceeds the transaction request's timeout, and proceeds accordingly. If the predicted execution time exceeds the timeout value, the transaction is immediately returned as failed. The tags associated with a given transaction request are repeatedly updated as the request traverses the transaction processing system, and the transaction is repeatedly verified to ensure that it can still be completed successfully.

Abstract: The present invention may include a method for automatic correction and migration of a plurality of bulk data. The method may identify sources, where the sources include the plurality of bulk data. The method may identify a subset of the bulk data, where the subset represents one or more records selected from the plurality of bulk data. The method may upload the subset to an enterprise application. The method may determine an error list from the enterprise application based on the uploaded subset. The method may roll back the subset from the enterprise application and based on the determined error list, the method may match one or more rules to a one or more errors in the error list.

Abstract: Aspects migrate an unstructured document to a specific document type definition Darwin Information Typing architecture wherein processors are configured to calculate a verb to noun ratio of an unstructured document by dividing a of plurality verbs of the unstructured document by a plurality of nouns of the unstructured document, assign a first weight to the unstructured document based on the calculated verb to noun ratio, and migrate the unstructured document to a specific document type definition Darwin Information Typing Architecture based on the first weight.

Abstract: Systems, methods, and computer program products to perform an operation comprising receiving a request from a first application to receive business events from a second application, deploying a first connector selected according to a set of parameters specified in the request, receiving, by the first connector from the second application, a first unit of event data of a first format, and converting the first unit of event data to a second format specified in the request.

Abstract: Method and apparatus for predicting a transaction's outcome in a transaction processing environment are provided. A transaction request is received by a transaction processing monitor (TPM), where the transaction request comprises a plurality of tags. The TPM identifies historical prior transactions corresponding to the transaction request, and determines a plurality of historical tags associated with those historical transactions. The TPM then determines whether a predicted execution time exceeds the transaction request's timeout, and proceeds accordingly. If the predicted execution time exceeds the timeout value, the transaction is immediately returned as failed. The tags associated with a given transaction request are repeatedly updated as the request traverses the transaction processing system, and the transaction is repeatedly verified to ensure that it can still be completed successfully.