Abstract: Spent catalyst (500) is removed from process microchannels (310) of a Fischer-Tropsch reactor by directing a jet of air (4) from an air knife (1) through slots of a protecting member (2). The air knife is traversed across successive rows of process microchannels (310) in direction A. The spacer member (2) protects an internal microchannel architecture (315) of the process microchannels against damage by the air jet (4) which may approach or exceed sonic velocity as it is directed into the process microchannels.

Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for revising classifier predictions, wherein classification labels are tokenized according to an index of predefined classification labels. An embedding is created for each token using an embedding model. The embeddings are provided to a machine learning model that accepts a sequence of tokens as input and produces a sequence of tokens as output. Tokens are extracted from the output of the machine learning model and a classification label corresponding to each token is retrieved according to the index of predefined classification labels.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis operations using a machine learning framework that comprises a predictive event embedding machine learning model and a network-based inference machine learning model. In some embodiments, a predictive data analysis computing entity performs a sequence of L sequential network updates on an event relationship network data object for a predictive entity to generate a cross-event classification for the predictive entity.

Abstract: Spent catalyst (500) is removed from process microchannels (310) of a Fischer-Tropsch reactor by directing a jet of air (4) from an air knife (1) through slots of a protecting member (2). The air knife is traversed across successive rows of process microchannels (310) in direction A. The spacer member (2) protects an internal microchannel architecture (315) of the process microchannels against damage by the air jet (4) which may approach or exceed sonic velocity as it is directed into the process microchannels.

Abstract: There is a need for more effectively and efficiently performing predictive data analysis to determine associations between input data objects and predictive categories This need can be addressed by, for example, solutions for performing predictive data analysis to determine associations between input data objects and predictive categories that utilize at least one of accuracy scores for predictive categories, evidentiary scores for predictive categories, and predicted certification statuses for claim data objects. In one example, a method includes: for each predictive category of one or more predictive categories associated with a claim data object, determining an accuracy score and an evidentiary score; determining a predicted certification status for the claim data object based on each accuracy score for a predictive category and each evidentiary score for a predictive category; and performing prediction-based actions based on each predicted certification status.

Abstract: Systems and methods enable compression of chronological data stored within a hierarchical data storage repository by identifying related data files generated at different times, wherein the related data files comprises a first data file and a second data file, and wherein the second data file was generated chronologically after the first data file; identifying duplicative data existing in both the first data file and the second data file; deleting the duplicative data from the first data file; and generating a link between the first data file and the second data file to enable retrieval of the duplicative data during display of contents of the first data file.

Abstract: A computer-implemented method for generating a predictive output based on a predictive input includes generating a plurality of rule-based prediction scores by executing one or more prediction rules on the prediction input, wherein each prediction rule of the one or more prediction rules is associated with a rule condition and one or more predictive weights, each predictive weight of the one or more predictive weights is associated with a related prediction category of a plurality of prediction categories, and each prediction category of the plurality of prediction categories is associated with a rule-based prediction score; determining a rule-based prediction output based at least in part on the plurality of rule-based prediction scores; and providing the plurality of rule-based prediction scores and the rule-based prediction output to a machine learning engine, wherein the machine learning engine is configured to generate a machine-learning based prediction output based at least in part on the plurality of

Abstract: An active temperature differential compensation for strain gage based sensors. An array of temperature sensors can be placed at the gage locations to measure the difference in temperature that induces strain on the strain gages. The output of the temperature sensor network can be placed in series with the strain gage network to directly compensate the induced voltage caused by the temperature gradient and/or employed as the input of a mathematical algorithm that can compensate the output from the strain gage bridge to dynamically correct unwanted thermally induced strain in the strain gages.

Abstract: An active temperature differential compensation for strain gage based sensors. An array of temperature sensors can be placed at the gage locations to measure the difference in temperature that induces strain on the strain gages. The output of the temperature sensor network can be placed in series with the strain gage network to directly compensate the induced voltage caused by the temperature gradient and/or employed as the input of a mathematical algorithm that can compensate the output from the strain gage bridge to dynamically correct unwanted thermally induced strain in the strain gages.