Abstract: A language determination model may be applied to select a first machine learning model or a second machine learning model to analyze the input text. The first machine learning model trained to analyze text in a first language, the second machine learning model trained to analyze text in a second language, and the input text may be in a third language. The language determination model may select the first machine learning model based on the first machine learning model having a better performance analyzing text in the third language than the second machine learning model. The language determination model may be updated based on an actual performance of the first machine learning model analyzing the input text. Moreover, the first machine learning model may be subject to additional training if the actual performance of the first machine learning model analyzing the input text is below a threshold value.

Abstract: Briefly, embodiments of a system, method, and article for receiving a document from a remote device and identifying items in the document. Various operations may be performed based on one or more dependencies of the identified items. For example, additional items may be identified in the document. One or more of the identified items may be parsed. A correspondence between the identified items and a second set of items may be determined. The identified items may be validated based on a set of rules. One or more of the identified items may be transmitted to the remote device in response to the performance of the various operations.

Abstract: In some embodiments, a first output is received from a first prediction network at a second prediction network. The first prediction network generates the first output from a first input. Also, a second input is received at the second prediction network that describes the first input. The second prediction network analyzes the first output and the second input and generates a second output that classifies the first output in one of a set of classifications. The first output is output with the one of the set of classifications for the second output where the second output indicates whether the first output should be reviewed when the second output is classified in a first classification in the set of classifications or not reviewed when the second output is classified in a second classification in the set of classifications.

Abstract: The invention relates to an aqueous dental single-component primer composition as well as a kit with this primer composition and a composite. The primer composition according to the present invention is self-etching and self-undercoating. It comprises a polymerizable (meth)acrylate or (meth)acrylamide monomer with (i) at least one acidic group such as for example a phosphoric acid group and with (ii) at least one hydrophilic group such as for example a terminal hydroxy group or two polymerizable (meth)acrylate or (meth)acrylamide monomers, wherein one thereof comprises (i) at least one acidic group and one thereof comprises (ii) at least one hydrophilic group.

Abstract: Systems, methods, and computer program products are described for orchestrating communication between containers or microservices of a multi-container architecture. Data having a plurality of tasks and associated dependencies among the plurality of tasks is received. A dependency graphs is generated that correlates each dependency of the associated dependencies with a plurality of microservices. Each microservice is configured to execute a task of the plurality of tasks. Each task is distributed, based on the generated dependency graph, to a respective microservice for execution. A plurality of messages are sequentially received from the plurality of microservices. Each message includes an output of each microservice for a respective task. Output data having a combination of the output of each microservice is provided for further characterization.

Abstract: A language determination model may be applied to select a first machine learning model or a second machine learning model to analyze the input text. The first machine learning model trained to analyze text in a first language, the second machine learning model trained to analyze text in a second language, and the input text may be in a third language. The language determination model may select the first machine learning model based on the first machine learning model having a better performance analyzing text in the third language than the second machine learning model. The language determination model may be updated based on an actual performance of the first machine learning model analyzing the input text. Moreover, the first machine learning model may be subject to additional training if the actual performance of the first machine learning model analyzing the input text is below a threshold value.

Abstract: Systems, methods, and computer program products are described for orchestrating communication between containers or microservices of a multi-container architecture. Data having a plurality of tasks and associated dependencies among the plurality of tasks is received. A dependency graphs is generated that correlates each dependency of the associated dependencies with a plurality of microservices. Each microservice is configured to execute a task of the plurality of tasks. Each task is distributed, based on the generated dependency graph, to a respective microservice for execution. A plurality of messages are sequentially received from the plurality of microservices. Each message includes an output of each microservice for a respective task. Output data having a combination of the output of each microservice is provided for further characterization.

Abstract: A method clusters each character on a document into one of a plurality of clusters based on widths of at least a portion of the characters on the document and measures distances between characters on the document. A threshold for each of the plurality of clusters is calculated based on at least a portion of the distances between characters in each cluster. The method then segments characters into units using the thresholds for the plurality of clusters. A distance between two characters in the document is compared to a threshold for a cluster to classify the two characters as being part of a unit when the distance is less than the threshold and not being part of the unit when the distance is greater than the threshold. Then, the method performs a recognition process on the document using the units.

Abstract: Briefly, embodiments of a system, method, and article for receiving a document from a remote device and identifying items in the document. Various operations may be performed based on one or more dependencies of the identified items. For example, additional items may be identified in the document. One or more of the identified items may be parsed. A correspondence between the identified items and a second set of items may be determined. The identified items may be validated based on a set of rules. One or more of the identified items may be transmitted to the remote device in response to the performance of the various operations.

Abstract: A method clusters each character on a document into one of a plurality of clusters based on widths of at least a portion of the characters on the document and measures distances between characters on the document. A threshold for each of the plurality of clusters is calculated based on at least a portion of the distances between characters in each cluster. The method then segments characters into units using the thresholds for the plurality of clusters. A distance between two characters in the document is compared to a threshold for a cluster to classify the two characters as being part of a unit when the distance is less than the threshold and not being part of the unit when the distance is greater than the threshold. Then, the method performs a recognition process on the document using the units.

Abstract: In some embodiments, a first output is received from a first prediction network at a second prediction network. The first prediction network generates the first output from a first input. Also, a second input is received at the second prediction network that describes the first input. The second prediction network analyzes the first output and the second input and generates a second output that classifies the first output in one of a set of classifications. The first output is output with the one of the set of classifications for the second output where the second output indicates whether the first output should be reviewed when the second output is classified in a first classification in the set of classifications or not reviewed when the second output is classified in a second classification in the set of classifications.

Abstract: The present disclosure involves systems, software, and computer implemented methods for using microservices to analyze a data source. One example method includes: providing, in a data access layer, a set of multiple independent microservices for analyzing data provided by a data providing system, including a browsing service that enables selection of a data source included in the data providing system, a model service that enables viewing and modifying a model of the data source, and a result set service that enables retrieval of data from the data source; executing, in response to a first request, the browsing service, including providing a description of a selected data source; executing, in response to a second request, the model service, including providing a model description; and executing, in response to a third request, the result set service, including asynchronously providing data corresponding to the model description.

Abstract: A business intelligence (BI) computing system obtains a plurality of relational data records from a data source that has an associated hierarchy description. The BI computing system, using the hierarchy description, next builds a hierarchical structure of the plurality of data records. Subsequently, the BI computing system, using the hierarchical structure, initiates at least one hierarchical workflow operation to allow a user to display, analyze, and navigate the plurality of data records on a BI client. Related apparatus, systems, techniques and articles are also described.

Abstract: Data is exported by at least one remote computing system to a client computing device that includes a state description characterizing a navigation state of a business intelligence (BI) application executing on the client computing device that interacts with the at least one remote computing system having at least one associated data source. Thereafter, the at least one remote computing system adjusts a query view state to retrieve a data set corresponding to the current navigation state. Next, metadata of a query and its objects are retrieved and exported that correspond to the adjusted query view state to the client computing device. Further, a data set from the at least one associated data source to the client computing device is retrieved and exported that uses the adjusted query view state.

Abstract: Various embodiments of systems and methods for converting reports between disparate report formats are described herein. In one aspect, a first report in a markup data schema is received. On another aspect, a second report in a banded report schema, comprising one or more bands, is created. The second report is created as a blank report. First report formatting settings of the first report are converted to second report formatting setting of the second report. Report content and report content layout from the first report are converted to the second report.

Abstract: Various embodiments of systems and methods for converting reports between disparate report formats are described herein. In one aspect, a first report in a markup data schema is received. On another aspect, a second report in a banded report schema, comprising one or more bands, is created. The second report is created as a blank report. First report formatting settings of the first report are converted to second report formatting setting of the second report. Report content and report content layout from the first report are converted to the second report.

Abstract: The invention is concerned with determining the three-dimensional structure of biological macromolecules such as proteins. In particular, it is concerned with methods for rapidly determining protein structure by NMR, by providing methods for simplifying NMR spectra using labeled proteins prepared from specifically isotopically labeled amino acids having at least two isotopes of 13C, 15N and 2H in the backbone, and methods for making these labeled proteins, e.g., by cultivation of a microbial culture containing said labeled amino acids.

Abstract: This invention is concerned with determining the three-dimensional structure of biological macromolecules such as proteins. In particular, it is concerned with methods for rapidly determining protein structure by NMR, by providing methods for simplifying NMR spectra using labeled proteins prepared from specifically isotopically labeled amino acids having at least two isotopes of 13C, 15N and 2H in the backbone, and methods for making these labeled proteins, e.g., by cultivation of a microbial culture containing said labeled amino acids.

Abstract: This invention is concerned with determining the three-dimensional structure of biological macromolecules such as proteins. In particular, it is concerned with methods for rapidly determining protein structure by NMR, by providing methods for simplifying NMR spectra using labeled proteins prepared from specifically isotopically labeled amino acids having at least two isotopes of 13C, 15N and 2H in the backbone, and methods for making these labeled proteins, e.g., by cultivation of a microbial culture containing said labeled amino acids.

Abstract: Peptidic molecules suitable for three dimensional NMR structure determination are provided which have been substituted with .sup.13 C and/or .sup.15 N in the backbone and/or at the .alpha.-carbon with .sup.2 H but not otherwise in the sidechains of the amino acid residues. One or more amino acids, amino acid species or substantially all of the amino acid residues of the molecule may be so substituted. A method of making the substituted peptidic molecules substituted in this manner is provided.