Abstract: A plasmonic substrate includes a base, a metallic film on the base, and a semiconducting photocatalyst on the metallic film. A method for producing a plasmonic substrate includes depositing a first metal layer having a thickness ranging from 10 to 200 nm and having a first metal through a physical vapor deposition technique onto a base, depositing a second metal layer having a second metal through a physical vapor deposition technique onto the first metal layer forming a multilayered metal template, immersing the multilayered metal template into a solution having a salt or complex of the second metal for a period of time forming a metallic film, and depositing a semiconducting photocatalyst on the metallic film. A method of catalyzing hydrogen production includes immersing a plasmonic substrate in a photocatalytic solution, exposing the plasmonic substrate to light, and generating hydrogen at a surface of the semiconducting photocatalyst.

Abstract: A method for determining regression of a database query associated with a first execution plan includes receiving a first performance measure for the database query and the first execution plan; determining a presence of at least one stored performance measure for the database query in a data repository; adding the first performance measure and identifiers for the database query and the first execution plan to a synchronization list; retrieving a second performance measure associated with a second execution plan from the data repository; determining a regression of the database query by comparing the first performance measure to the second performance measure; in response to a determination that the database query is regressed, adding the first performance measure, the second performance measure, and identifiers for the database query and the first execution plan to a regression report.

Abstract: A method for presenting personalized content to a user includes receiving user data corresponding to a user having a user profile, the user data including at least one or more messages in a user mailbox and a user web browser history within a network, extracting one or more data tags from the received user data, associated at least one data tag with a message, finding information in the network that corresponds to the associated data tag, generating a notification for the user, the notification including the found information in the network, and outputting the generated notification to a user interface of a device of the user.

Abstract: A method for presenting personalized content to a user includes receiving user data corresponding to a user having a user profile, the user data including at least one or more messages in a user mailbox and a user web browser history within a network, extracting one or more data tags from the received user data, associated at least one data tag with a message, finding information in the network that corresponds to the associated data tag, generating a notification for the user, the notification including the found information in the network, and outputting the generated notification to a user interface of a device of the user.

Abstract: The example embodiments are directed toward leveraging the power of large language models (LLMs) in a messaging application. In a first embodiment, LLMs are utilized to generate message content (both original and reply). In a second embodiment, LLMs are utilized to provide enhanced semantic search functionality. In a third embodiment, LLMs are utilized to provide intelligent actions to take based on message content.

Abstract: In some implementations, the techniques described herein relate to a method including: (i) accessing, by a processor, a plurality of messages for a user, (ii) analyzing, by a large language model executed by the processor, the plurality of messages to extract a context of each message, (iii) determining, by the processor, a current context of interest to the user, (iv) identifying, by the processor, a subset of the plurality of messages that each comprises a context related to the current context of interest to the user, and (v) causing display, by the processor, of the subset of the plurality of messages in a digital message inbox.

Abstract: Disclosed are systems and methods for receiving a meeting request via an electronic account of a user; determining a conflict between the meeting request and a pre-existing meeting, extracting and comparing information associated with each meeting based on an analysis of each meeting; determining a priority associated with each meeting based on the analysis of the information of each meeting; and utilizing a machine learning model to generate an output associated with the priority of each meeting to the electronic account of the user.

Abstract: Disclosed embodiments are directed toward a computer-implemented system and method for providing an email digest in association with an interface display of an electronic inbox. The disclosed digest includes non-native inbox functionality related to a summary data structure that includes an interactive portion, whereby upon generation of electronic prompts via a large language model (LLM), the digest can leverage functionality of the LLM to determine how electronic inbox content can be rendered for display.

Abstract: In some implementations, the techniques described herein relate to a method including: (i) identifying, by a processor, an electronic message that comprises content generated by a user, (ii) predicting, by the processor, a potential action for the user by inputting the content of the electronic message into a large language model, (iii) suggesting, by the processor, the potential action to the user, (iv) receiving, by the processor, user input related to the potential action, and (v) performing, by the processor, on behalf of the user, a subsequent action conforming to the user input.

Abstract: In some implementations, the techniques described herein relate to a method including: (i) identifying, by a processor, a plurality of electronic messages addressed to a user, (ii) analyzing, by a large language model executed by the processor, the plurality of electronic messages to identify potential actions, (iii) suggesting, by the processor, to the user, a potential action identified by the large language model, (iv) receiving, by the processor, user input related to the potential action, and (v) performing, by the processor, on behalf of the user, a subsequent action conforming to the user input.

Abstract: In some implementations, the techniques described herein relate to a method including: (i) identifying, by a processor, electronic files stored in association with a user account, (ii) analyzing, by a large language model (LLM) executed by the processor, the electronic files and identifying, based on the LLM analysis, at least one file that is a candidate for deletion, (iii) compiling, by the processor, an electronic message comprising an output indicating deletion of the at least one file, (iv) causing display, by the processor, the electronic message, (v) receiving, by the processor, user input related to the at least one file, (vi) analyzing, by the LLM executed by the processor, the user input, and (vii) performing, by the processor based on the analysis of the user input via the LLM, an action on the at least one file conforming to the user input.

Abstract: Automated mocking of computer system deployments is facilitated. A method as described herein can include associating, by a first system operatively coupled to a processor, respective properties of a first deployment of a second system on a first computing device with respective automation mapping functions; executing, by the first system, the automation mapping functions in an order defined by dependencies between respective ones of the automation mapping functions, resulting in a series of system modeling tasks and an order associated with the series of system modeling tasks; and performing, by the first system, the series of system modeling tasks in the order associated therewith, resulting in a second deployment of the second system being created on a second computing device that is distinct from the first computing device.

Abstract: A method for positioning in a wireless communication system is described. The method comprises receiving, by a second node (102), a capability-request signal from a first node (106). The second node (102) transmits a capability-response signal to the first node (106). The second node (102) transmits an assistance information to the first node (106). The second node (102) transmits the configuration of the at least one reference signal to a third node (104). The second node (102) receives a reference signal from the third node (104). The second node (102) performs measurement on the reference signal and transmits report comprising the measurement to the first node (106), where the first node (106) estimates a position of the third node (104) based on the report received from the second node (102).

Abstract: The technology disclosed relates to generating automated test plan scripts. Repository data associated with a test plan script is received. Source code and test plan solution data corresponding to the repository data are analyzed. For example, the repository data may be analyzed using natural language processing and static code analysis. In some embodiments, test steps of the test plan are performed to generate repository data. A suggestion of a reusable component for a particular test step or test validation is provided for one or more of the test steps. A selection of the suggestion of the reusable component for at least one of the test steps is received. An automated test plan script corresponding to the selection is generated.

Abstract: A method for presenting personalized content to a user includes receiving user data corresponding to a user having a user profile, the user data including at least one or more messages in a user mailbox and a user web browser history within a network, extracting one or more data tags from the received user data, associated at least one data tag with a message, finding information in the network that corresponds to the associated data tag, generating a notification for the user, the notification including the found information in the network, and outputting the generated notification to a user interface of a device of the user.

Abstract: Methods, systems, and computer-readable media are disclosed herein for proactively managing computing problems. In aspects, an execution of a script is initiated. A connection may be established via the script and the central database for identifying a network quality issue. The network quality issue may be identified more than once. Further, the network quality issue may be identified based on the network quality issue satisfying a threshold. Additionally, it may be determined that the network quality issue that satisfies the threshold is not associated with an electronic documentation based on a search in the central database. Based on determining the network quality issue is not associated with the electronic documentation, the electronic documentation may be created for the network quality issue that satisfies the threshold.

Abstract: A method for presenting personalized content to a user includes receiving user data corresponding to a user having a user profile, the user data including at least one or more messages in a user mailbox and a user web browser history within a network, extracting one or more data tags from the received user data, associated at least one data tag with a message, finding information in the network that corresponds to the associated data tag, generating a notification for the user, the notification including the found information in the network, and outputting the generated notification to a user interface of a device of the user.

Abstract: The present disclosure provides a method and system for authentication of one or more identification documents for detecting potential variations in real-time. The system receives a user data from one or more users with facilitation of one or more communication devices in real-time. The system obtains the one or more identification documents associated with the one or more users with facilitation of the one or more communication devices in one or more forms. In addition, the system authenticates each of the one or more identification documents associated with the corresponding user of the one or more users. Further, the system detects potential variations in the one or more identification documents based on heat map analysis with facilitation of one or more hardware run-algorithms. Furthermore, the system alerts one or more organizations for potential fraud based on the heat map analysis.

Abstract: Archival task processing in a data storage system is described herein. A method as described herein can include designating, by a device operatively coupled to a processor, a file stored by a primary cluster of a data storage system for archival to a remote storage system; locating, by the device, a secondary cluster of the data storage system having stored thereon a copy of the file, the secondary cluster being distinct from the primary cluster; and, in response to determining that the file stored by the primary cluster matches the copy of the file stored by the secondary cluster, causing, by the device, the secondary cluster to archive the copy of the file to the remote storage system.

Abstract: A system and method for content distribution without tracking is described. The system and method includes determining that device identifiers are not available for a first digital content channel; identifying a first cluster of users and a second cluster of users based on the determination that device identifiers are not available; providing first content and second content via the first digital content channel; monitoring user interactions on the first digital content channel to obtain a first conversion rate for users in the first cluster that receive the first content and a second conversion rate for users in the second cluster that receive the second content; computing a cross-cluster treatment effect based on the first conversion rate and the second conversion rate; computing a treatment effect for the first content based on the cross-cluster treatment effect; and providing the first content to a subsequent user based on the treatment effect.