Abstract: Generating, using a computer, a digital twin model or simulation for organ transplant or organ repairs where organ data of an organ for a patient is received at a computer. Organ parts are identified based on organ data, and the organ parts include a retained portion of the organ and a replacement portion of the organ. A digital model is generated as a digital twin simulations of the organ parts based on the received organ data. Parameters for the organ parts is determined, which include dimensions of the retained portion of the organ and dimensions of the replacement portion of the organ.

Abstract: Aspects of the present disclosure relate generally to reminder systems and, more particularly, to a contextual item discovery and pattern inculcated reminder mechanism and methods of use. A computer-implemented method includes: determining, by a computing device, an event in which a user will participate; associating, by the computing device, one or more items with the event; determining a location of the one or more items associated with the event including that the user does not possess any combination of the one or more items; and providing an alert to the user that the any of the one or more items associated with the event is not in the possession of the user.

Abstract: The present invention relates to an in vitro method for production of heterodimeric proteins.

Abstract: The present invention relates to an in vitro method for production of heterodimeric proteins.

Abstract: Provided are techniques for detecting contamination propagation and performing decontamination. In response to receiving a request to detect contaminants and perform decontamination, an entity is identified. Whether there are contaminants on the entity is detected using any combination of sensor data, one or more images, and one or more contamination propagation patterns. In response to determining that there are no contaminants, the entity is allowed to pass through an entry point. In response to determining that there are contaminants, one or more decontamination techniques are identified, decontamination of the entity is performed, using the one or more decontamination techniques, and, in response to determining that the decontamination has been successful, the entity is allowed to pass through the entry point.

Abstract: Provided herein are methods for purifying an anti-?4?7 integrin antibody, such as vedolizumab, from a liquid solution, e.g., from a mammalian cell culture clarified harvest. The invention relates, inter alia, to purification methods for controlling the amount of product-related substances and/or process-related impurities present in purified preparations of an anti-?4?7 integrin antibody, or antigen-binding fragment thereof, e.g., vedolizumab. Compositions comprising an anti-?4?7 antibody, and uses thereof to treat a disorder, are also provided.

Abstract: A method, system, and computer program product for virtual reality simulation-based device configuration are provided. The method generates a virtual reality environment for a simulated activity. Interactions of a user are monitored within the virtual reality environment. Based on the interactions of the user, one or more simulated devices used are identified during the simulated activity. The method determines a set of device characteristics for the one or more simulated devices. A set of simulated configurations are determined for the one or more simulated devices based on the set of device characteristics. The method matches a set of configurations for one or more physical devices to the set of simulated configurations for the one or more simulated devices.

Abstract: A tool for providing context-based copy and paste commands. The tool monitors a plurality of user activities across one or more user devices for a plurality of copied content items and associated contextual data. The tool generates a list of the plurality of copied content items and the associated contextual data. Responsive to a determination that a user issued a paste command, the tool calculates a relevancy score for each of the plurality of copied content items in the list. The tool determines at least one of the plurality of copied content items to fulfill the paste command based, at least in part, on the relevancy score for each of the plurality of copied content items. The tool presents the at least one of the plurality of copied content items to a user to select for the paste command.

Abstract: Method and apparatus for using machine learning to monitor biometric data to provide intelligent alerts are provided. At a first moment in time, first biometric data for a plurality of users are received from a plurality of sensor devices. A group metric is generated by processing the first biometric data using at least one trained machine learning model, and it is determined that the group metric does not satisfy one or more predefined criteria. At a second moment in time, second biometric data for the plurality of users is received from the plurality of sensor devices, and an updated group metric is generated by processing the second biometric data using the at least one trained machine learning model. Upon determining that the updated group metric satisfies the one or more predefined criteria, an indication is provided that the one or more predefined criteria have been satisfied.

Abstract: The present invention relates to an in vitro method for production of heterodimeric proteins.

Abstract: The present invention relates to an in vitro method for production of heterodimeric proteins.

Abstract: Disclosed aspects relate to using a database driver to manage application resiliency with respect to a shared pool of configurable computing resources. A transaction request having a set of command data may be received. An updated set of global property data for the database driver may be detected. The updated set of global property data for the database driver may be captured in a memory device coupled with the database driver. An operational member asset of the shared pool of configurable computing resources may be determined to process the transaction request. The transaction request may be connected with the operational member asset of the shared pool of configurable computing resources. The set of command data for the transaction request may be transmitted to the operational member of the shared pool of configurable computing resources.

Abstract: Sequences of hierarchical records are aggregated and summarized. A capture log that includes a plurality of operations of a workload is received. A first data structure that models transaction types as sequences of nodes is created. The nodes identify operations in the workload. A present operation and a transaction identifier are read from the capture log. The transaction identifier is dissociated from a first node that identifies a prior operation. The transaction identifier is associated with a second node that identifies the present operation. In a second data structure that associates nodes with transaction identifiers, the first node is dissociated from the transaction identifier and the second node is associated with the transaction identifier. A summary of the workload is generated based, at least in part, on the first and second data structures. The summary includes signatures of transaction types and counts of instances of the transaction types.

Abstract: Sequences of hierarchical records are aggregated and summarized. A capture log that includes a plurality of operations of a workload is received. A first data structure that models transaction types as sequences of nodes is created. The nodes identify operations in the workload. A present operation and a transaction identifier are read from the capture log. The transaction identifier is dissociated from a first node that identifies a prior operation. The transaction identifier is associated with a second node that identifies the present operation. In a second data structure that associates nodes with transaction identifiers, the first node is dissociated from the transaction identifier and the second node is associated with the transaction identifier. A summary of the workload is generated based, at least in part, on the first and second data structures. The summary includes signatures of transaction types and counts of instances of the transaction types.

Abstract: Sequences of hierarchical records are aggregated and summarized. A capture log that includes a plurality of operations of a workload is received. A first data structure that models transaction types as sequences of nodes is created. The nodes identify operations in the workload. A present operation and a transaction identifier are read from the capture log. The transaction identifier is dissociated from a first node that identifies a prior operation. The transaction identifier is associated with a second node that identifies the present operation. In a second data structure that associates nodes with transaction identifiers, the first node is dissociated from the transaction identifier and the second node is associated with the transaction identifier. A summary of the workload is generated based, at least in part, on the first and second data structures. The summary includes signatures of transaction types and counts of instances of the transaction types.

Abstract: Sequences of hierarchical records are aggregated and summarized. A capture log that includes a plurality of operations of a workload is received. A first data structure that models transaction types as sequences of nodes is created. The nodes identify operations in the workload. A present operation and a transaction identifier are read from the capture log. The transaction identifier is dissociated from a first node that identifies a prior operation. The transaction identifier is associated with a second node that identifies the present operation. In a second data structure that associates nodes with transaction identifiers, the first node is dissociated from the transaction identifier and the second node is associated with the transaction identifier. A summary of the workload is generated based, at least in part, on the first and second data structures. The summary includes signatures of transaction types and counts of instances of the transaction types.

Abstract: Database operation records are sequentially read from two or more log files. If the transaction identifier is new and the record is not an end-of-transaction record, an open transactions list entry is created. If the transaction identifier is new and the record is an end-of-transaction record, a transaction type list entry is created or updated. If the transaction identifier is not new and is not an end-of-transaction record, an open transactions list entry is updated. If the transaction identifier is not new and the record is an end-of-transaction record, a transaction type list entry is created or updated. When all log file records are read, analytical comparison between the information associated with two or more of the log files in data fields in the transaction type list entries is performed.

Abstract: Identifying matching transactions between two log files. First and second log files contain operation records of transactions in a transaction workload. The first and second log files are split into first and second corresponding partition files, based on distinct sequences of operation record types beginning operation records of the transactions in each of the log files. A record location in a first partition file, and a window of sequential record locations in a corresponding second partition file at a defined offset relative to the record location in the first file are advanced one record location at a time. If each operation record of a complete transaction at a record location in a first file has a matching record in the associated window of record locations in a second file, the corresponding transactions match.

Abstract: Identifying matching transactions between two log files. First and second log files contain operation records of transactions in a transaction workload. The first and second log files are split into first and second corresponding partition files, based on distinct sequences of operation record types beginning operation records of the transactions in each of the log files. A record location in a first partition file, and a window of sequential record locations in a corresponding second partition file at a defined offset relative to the record location in the first file are advanced one record location at a time. If each operation record of a complete transaction at a record location in a first file has a matching record in the associated window of record locations in a second file, the corresponding transactions match.

Abstract: Database operation records are sequentially read from two or more log files. If the transaction identifier is new and the record is not an end-of-transaction record, an open transactions list entry is created. If the transaction identifier is new and the record is an end-of-transaction record, a transaction type list entry is created or updated. If the transaction identifier is not new and is not an end-of-transaction record, an open transactions list entry is updated. If the transaction identifier is not new and the record is an end-of-transaction record, a transaction type list entry is created or updated. When all log file records are read, analytical comparison between the information associated with two or more of the log files in data fields in the transaction type list entries is performed.