Abstract: The present disclosure provides reactor systems and methods that use in-line measurement of refractive index for monitoring and controlling a catalytic reaction for hydrogen production. An outcome of the catalytic reaction (e.g., total organic carbon level) can be determined using the refractive index data measured in-line from a product stream. Advantageously, the present reactor system can include a control unit for acquiring in-line refractive index data, determining the reaction outcome, and adjusting the catalyst and/or reaction conditions according to the determined outcome, so that progress of the catalytic reaction can be controlled automatically.

Abstract: In certain embodiments, concurrency related to rehypothecated allocations may be facilitated via pre-release locking of associated positions. In some embodiments, a request to release a collateral allocation may be obtained, where the collateral allocation is associated with (i) a rehypothecated position and (ii) a cloned position on a leg downstream of the rehypothecated position, and the cloned position is derived from the rehypothecated position. Based on the release request, one or more legs related to the collateral allocation may be traversed to locate and lock one or more positions on such related legs (e.g., including the cloned position of the downstream leg). Prior to release of the rehypothecated position, the cloned position of the downstream leg may be locked based on the release request. The release of the rehypothecated position may be performed to fulfill the release request in response to the cloned position of the downstream leg being locked.

Abstract: A method for real-time data processing is described. The method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method. The method comprising allocating a real-time dataset associated with a real-time data interaction to a node in a chain of nodes, wherein each node is representative of a user in the real-time data interaction; setting a node status of the node for the real-time dataset to pending; and independently of (i) a node status of the one or more upstream nodes and (ii) a node status of the one or more downstream nodes: periodically determining, by the computer system, an availability status of the node; and in response to the availability status satisfying the criterion, setting the node status for the real-time dataset as settled.

Abstract: In certain embodiments, multi-modal-based generation of settlement instructions may be facilitated. In some embodiments, a portfolio of a live environment may be emulated in a projected environment. A target portfolio may be generated in the projected environment based on the emulated portfolio. Partial synchronization between the target portfolio of the projected environment and the portfolio of the live environment may be performed such that a first subset of changes to the portfolio of the live environment are reflected in the target portfolio of the projected environment. Subsequent to the partial synchronization, the target portfolio of the projected environment may be updated such that the update of the target portfolio accounts for the first subset of changes. Subsequent to the update of the target portfolio, settlement instructions may be generated based on differences between the target portfolio of the projected environment and the portfolio of the live environment.

Abstract: In certain embodiments, multi-modal-based generation of settlement instructions may be facilitated. In some embodiments, a portfolio of a live environment may be emulated in a projected environment. A target portfolio may be generated in the projected environment based on the emulated portfolio. Partial synchronization between the target portfolio of the projected environment and the portfolio of the live environment may be performed such that a first subset of changes to the portfolio of the live environment are reflected in the target portfolio of the projected environment. Subsequent to the partial synchronization, the target portfolio of the projected environment may be updated such that the update of the target portfolio accounts for the first subset of changes. Subsequent to the update of the target portfolio, settlement instructions may be generated based on differences between the target portfolio of the projected environment and the portfolio of the live environment.

Abstract: A self-contained, mobile Radio Frequency Identification (RFID) asset tracker and hardware assembly and method of use thereof. The mobile RFID asset tracker includes a frame mounted on locking swivel casters which provide a mobile base for mounting of an RFID antenna, RFID reader and other electrical equipment thereon. An electronics control box, which is adjustably mounted on the frame, houses the RFID reader, a custom Printed Circuit Board (PCB) control module, cellular and WIFI modems, and a power source. The electronics control box is operatively engaged via Input/Output (IO) ports and cabling to an external indicator assembly and to the external adjustably mounted RFID antenna.

Abstract: In certain embodiments, multi-modal-based generation of settlement instructions may be facilitated. In some embodiments, a portfolio of a live environment may be emulated in a projected environment. A target portfolio may be generated in the projected environment based on the emulated portfolio. Partial synchronization between the target portfolio of the projected environment and the portfolio of the live environment may be performed such that a first subset of changes to the portfolio of the live environment are reflected in the target portfolio of the projected environment. Subsequent to the partial synchronization, the target portfolio of the projected environment may be updated such that the update of the target portfolio accounts for the first subset of changes. Subsequent to the update of the target portfolio, settlement instructions may be generated based on differences between the target portfolio of the projected environment and the portfolio of the live environment.

Abstract: Methods and system are described for optimizing data processing in cloud-based, machine learning environments. For example, through the use of a machine learning model utilizing a self organizing map and/or the use of specific processing nodes in a computer system to perform specific tasks the methods and system may more efficiently distribute tasks through a cloud computing environment and increase overall processing speeds despite increasing amounts of data. The methods and system described herein are particularly related to collateral allocation computer systems that automate the management of numerous collateral assets. For example, as the amount of collateral assets and the complexity of given transactions grow, typical allocation systems face frequent processing delays related to collateral allocations (e.g., allocations of collateral associated with Tri-Party Repos).

Abstract: A self-contained, mobile Radio Frequency Identification (RFID) asset tracker and hardware assembly and method of use thereof. The mobile RFID asset tracker includes a frame mounted on locking swivel casters which provide a mobile base for mounting of an RFID antenna, RFID reader and other electrical equipment thereon. An electronics control box, which is adjustably mounted on the frame, houses the RFID reader, a custom Printed Circuit Board (PCB) control module, cellular and WIFI modems, and a power source. The electronics control box is operatively engaged via Input/Output (IO) ports and cabling to an external indicator assembly and to the external adjustably mounted RFID antenna.

Abstract: A method for real-time data processing is described. The method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method. The method comprising allocating a real-time dataset associated with a real-time data interaction to a node in a chain of nodes, wherein each node is representative of a user in the real-time data interaction; setting a node status of the node for the real-time dataset to pending; and independently of (i) a node status of the one or more upstream nodes and (ii) a node status of the one or more downstream nodes: periodically determining, by the computer system, an availability status of the node; and in response to the availability status satisfying the criterion, setting the node status for the real-time dataset as settled.

Abstract: A self-contained, mobile Radio Frequency Identification (RFID) asset tracker and hardware assembly and method of use thereof. The mobile RFID asset tracker includes a frame mounted on locking swivel casters which provide a mobile base for mounting of an RFID antenna, RFID reader and other electrical equipment thereon. An electronics control box, which is adjustably mounted on the frame, houses the RFID reader, a custom Printed Circuit Board (PCB) control module, cellular and WIFI modems, and a power source. The electronics control box is operatively engaged via Input/Output (IO) ports and cabling to an external indicator assembly and to the external adjustably mounted RFID antenna.

Abstract: A method for real-time data processing is described. The method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method. The method comprising allocating a real-time dataset associated with a real-time data interaction to a node in a chain of nodes, wherein each node is representative of a user in the real-time data interaction; setting a node status of the node for the real-time dataset to pending; and independently of (i) a node status of the one or more upstream nodes and (ii) a node status of the one or more downstream nodes: periodically determining, by the computer system, an availability status of the node; and in response to the availability status satisfying the criterion, setting the node status for the real-time dataset as settled.

Abstract: In certain embodiments, multi-modal-based generation of settlement instructions may be facilitated. In some embodiments, a portfolio of a live environment may be emulated in a projected environment. A target portfolio may be generated in the projected environment based on the emulated portfolio. Partial synchronization between the target portfolio of the projected environment and the portfolio of the live environment may be performed such that a first subset of changes to the portfolio of the live environment are reflected in the target portfolio of the projected environment. Subsequent to the partial synchronization, the target portfolio of the projected environment may be updated such that the update of the target portfolio accounts for the first subset of changes. Subsequent to the update of the target portfolio, settlement instructions may be generated based on differences between the target portfolio of the projected environment and the portfolio of the live environment.

Abstract: In certain embodiments, multi-modal-based generation of settlement instructions may be facilitated. In some embodiments, a portfolio of a live environment may be emulated in a projected environment. A target portfolio may be generated in the projected environment based on the emulated portfolio. Partial synchronization between the target portfolio of the projected environment and the portfolio of the live environment may be performed such that a first subset of changes to the portfolio of the live environment are reflected in the target portfolio of the projected environment. Subsequent to the partial synchronization, the target portfolio of the projected environment may be updated such that the update of the target portfolio accounts for the first subset of changes. Subsequent to the update of the target portfolio, settlement instructions may be generated based on differences between the target portfolio of the projected environment and the portfolio of the live environment.

Abstract: A method for real-time data processing is described. The method being implemented on a computer system having one or more physical processors programmed with computer program instructions which, when executed, perform the method. The method comprising allocating a real-time dataset associated with a real-time data interaction to a node in a chain of nodes, wherein each node is representative of a user in the real-time data interaction; setting a node status of the node for the real-time dataset to pending; and independently of (i) a node status of the one or more upstream nodes and (ii) a node status of the one or more downstream nodes: periodically determining, by the computer system, an availability status of the node; and in response to the availability status satisfying the criterion, setting the node status for the real-time dataset as settled.

Abstract: A self-contained, mobile Radio Frequency Identification (RFID) asset tracker and hardware assembly and method of use thereof. The mobile RFID asset tracker includes a frame mounted on locking swivel casters which provide a mobile base for mounting of an RFID antenna, RFID reader and other electrical equipment thereon. An electronics control box, which is adjustably mounted on the frame, houses the RFID reader, a custom Printed Circuit Board (PCB) control module, cellular and WIFI modems, and a power source. The electronics control box is operatively engaged via Input/Output (IO) ports and cabling to an external indicator assembly and to the external adjustably mounted RFID antenna.

Abstract: In certain embodiments, transaction-subset-assignment of computer processing nodes may be facilitated to perform collateral allocation. In some embodiments, a query may be performed to obtain a set of transactions. Computer processing nodes may be selected from a set of available nodes for performing collateral allocations. Collateral allocation rules associated with a lender may be obtained, and each of the computer processing nodes may be caused to perform collateral allocations for one subset of the transaction set in accordance with the collateral allocation rules by assigning transactions of the transaction set respectively to the computer processing nodes such that the computer processing nodes collectively perform collateral allocations for the transaction set.

Abstract: Methods and system are described for optimizing data processing in cloud-based, machine learning environments. For example, through the use of a machine learning model utilizing a self organizing map and/or the use of specific processing nodes in a computer system to perform specific tasks the methods and system may more efficiently distribute tasks through a cloud computing environment and increase overall processing speeds despite increasing amounts of data. The methods and system described herein are particularly related to collateral allocation computer systems that automate the management of numerous collateral assets. For example, as the amount of collateral assets and the complexity of given transactions grow, typical allocation systems face frequent processing delays related to collateral allocations (e.g., allocations of collateral associated with Tri-Party Repos).

Abstract: Methods and system are described for optimizing data processing in cloud-based, machine learning environments. For example, through the use of a machine learning model utilizing a self organizing map and/or the use of specific processing nodes in a computer system to perform specific tasks the methods and system may more efficiently distribute tasks through a cloud computing environment and increase overall processing speeds despite increasing amounts of data. The methods and system described herein are particularly related to collateral allocation computer systems that automate the management of numerous collateral assets. For example, as the amount of collateral assets and the complexity of given transactions grow, typical allocation systems face frequent processing delays related to collateral allocations (e.g., allocations of collateral associated with Tri-Party Repos).

Abstract: In certain embodiments, transaction-subset-assignment of computer processing nodes may be facilitated to perform collateral allocation. In some embodiments, a query may be performed to obtain a set of transactions. Computer processing nodes may be selected from a set of available nodes for performing collateral allocations. Collateral allocation rules associated with a lender may be obtained, and each of the computer processing nodes may be caused to perform collateral allocations for one subset of the transaction set in accordance with the collateral allocation rules by assigning transactions of the transaction set respectively to the computer processing nodes such that the computer processing nodes collectively perform collateral allocations for the transaction set.