Abstract: A method and composition for treating drinking water for animals is disclosed. A method for treating drinking water for animals includes providing a plurality of sporulated microbes to metabolize an organic matter in the drinking water. A composition for treating animal drinking water includes a plurality of sporulated microbes.

Abstract: Systems and methods for content management wherein a client can submit requests to a first API which the forwards the requests to either an IMDB or a gateway to a distributed cluster-computing framework. Requests to the IMDB are serviced and responses from the IMDB are returned to the client. Requests that are forwarded to the gateway are first modified for the distributed cluster-computing framework, and are then parsed by the gateway and used to instantiate processors that generate corresponding requests to the distributed cluster-computing framework. Responsive data from the distributed cluster-computing framework is used to generate responses to the client requests that are forwarded to the first API which modifies them to appear as if they were generated by the IMDB. These modified responses are returned by the first API to the client.

Abstract: Cross-tabulation operation is performed within a columnar database management system. The columnar database management system receives a request to perform a cross-tabulation operation on a set of database tables. The columnar database management system determines values of cross-tabulation operation for each row of the result. The columnar database management system determines a domain for each value of the row dimension corresponding to a row combination. The columnar database management system determines an intersection set of the domains corresponding to values of the row dimensions for the row combination. The columnar database management system determines a value for the result column for the row combination as an aggregate value based on the records of the intersection set.

Abstract: Systems and methods for content management wherein a client can submit requests to a first API which the forwards the requests to either an IMDB or a gateway to a distributed cluster-computing framework. Requests to the IMDB are serviced and responses from the IMDB are returned to the client. Requests that are forwarded to the gateway are first modified for the distributed cluster-computing framework, and are then parsed by the gateway and used to instantiate processors that generate corresponding requests to the distributed cluster-computing framework. Responsive data from the distributed cluster-computing framework is used to generate responses to the client requests that are forwarded to the first API which modifies them to appear as if they were generated by the IMDB. These modified responses are returned by the first API to the client.

Abstract: Cross-tabulation operation is performed within a columnar database management system. The columnar database management system receives a request to perform a cross-tabulation operation on a set of database tables. The columnar database management system determines values of cross-tabulation operation for each row of the result. The columnar database management system determines a domain for each value of the row dimension corresponding to a row combination. The columnar database management system determines an intersection set of the domains corresponding to values of the row dimensions for the row combination. The columnar database management system determines a value for the result column for the row combination as an aggregate value based on the records of the intersection set.

Abstract: A lightweight machine learning model (MLM) microservice is hosted in a cloud computing environment suitable for large-scale data processing. A client system can utilize the MLM service to run a MLM on a dataset in the cloud computing environment. The MLM can be already developed, trained, and tested using any appropriate ML libraries on the client side or the server side. However, no data schema is required to be provided from the client side. Further, neither the MLM nor the dataset needs to be persisted on the server side. When a request to run a MLM is received by the MLM service from a client system, a data schema is inferred from a dataset provided with the MLM. The MLM is run on the dataset utilizing the inferred data schema to generate a prediction which is then returned by the MLM service to the client system.

Abstract: Venn diagrams are computed for a given plurality of input sets. The process of computing the Venn diagrams is executed on columnar database systems for efficient execution. The computation of various subsets of the Venn diagrams is performed by determining subsets of various combinations of the input sets and computing set differences of the intersection sets. The process orders the execution of various steps of computing the subsets for the Venn diagram in an order that reduces the number of times an input set is loaded. Information describing various subsets of a Venn diagram is used to render the Venn diagram for display, for example, on a client device.

Abstract: Data mining operations are performed within a columnar database management system. The columnar database management system stores input sets of data for a data mining operation. An input set of data is represented as a column of data in the columnar database management system. The columnar database management system stores instructions to perform one or more data mining operations for processing the input sets of data. The columnar database management system receives requests for performing data mining operations and performs the processing of the data mining operation within the columnar database management system. As a result, the processing of data mining operations is performed without requiring multiple data transfers between an application implementing the data mining operations and the columnar database management system.

Abstract: Venn diagrams are computed for a given plurality of input sets. The process of computing the Venn diagrams is executed on columnar database systems for efficient execution. The computation of various subsets of the Venn diagrams is performed by determining subsets of various combinations of the input sets and computing set differences of the intersection sets. The process orders the execution of various steps of computing the subsets for the Venn diagram in an order that reduces the number of times an input set is loaded. Information describing various subsets of a Venn diagram is used to render the Venn diagram for display, for example, on a client device.

Abstract: Data mining operations are performed within a columnar database management system. The columnar database management system stores input sets of data for a data mining operation. An input set of data is represented as a column of data in the columnar database management system. The columnar database management system stores instructions to perform one or more data mining operations for processing the input sets of data. The columnar database management system receives requests for performing data mining operations and performs the processing of the data mining operation within the columnar database management system. As a result, the processing of data mining operations is performed without requiring multiple data transfers between an application implementing the data mining operations and the columnar database management system.

Abstract: Systems and methods for content management wherein a client can submit requests to a first API which the forwards the requests to either an IMDB or a gateway to a distributed cluster-computing framework. Requests to the IMDB are serviced and responses from the IMDB are returned to the client. Requests that are forwarded to the gateway are first modified for the distributed cluster-computing framework, and are then parsed by the gateway and used to instantiate processors that generate corresponding requests to the distributed cluster-computing framework. Responsive data from the distributed cluster-computing framework is used to generate responses to the client requests that are forwarded to the first API which modifies them to appear as if they were generated by the IMDB. These modified responses are returned by the first API to the client.

Abstract: The present disclosure relates generally to an apparatus and methods for microorganism isolation, characterization and identification based on oxygen, pressure, culture media gradients and metabolites. In each embodiment, the apparatus of the disclosure is particularly useful for the purpose of novel isolation of never before cultured species of microorganisms and their by-products.

Abstract: Cross-tabulation operation is performed within a columnar database management system. The columnar database management system receives a request to perform a cross-tabulation operation on a set of database tables. The columnar database management system determines values of cross-tabulation operation for each row of the result. The columnar database management system determines a domain for each value of the row dimension corresponding to a row combination. The columnar database management system determines an intersection set of the domains corresponding to values of the row dimensions for the row combination. The columnar database management system determines a value for the result column for the row combination as an aggregate value based on the records of the intersection set.

Abstract: Cross-tabulation operation is performed within a columnar database management system. The columnar database management system receives a request to perform a cross-tabulation operation on a set of database tables. The columnar database management system determines values of cross-tabulation operation for each row of the result. The columnar database management system determines a domain for each value of the row dimension corresponding to a row combination. The columnar database management system determines an intersection set of the domains corresponding to values of the row dimensions for the row combination. The columnar database management system determines a value for the result column for the row combination as an aggregate value based on the records of the intersection set.

Abstract: A primary piston of a tandem master cylinder includes: a body provided with a skirt, having in the rear thereof a cavity for the plunger and the push rod connected to the brake pedal and in the front a cavity defining the primary chamber. The piston is made of a plastic material and at least one magnet is built into the body of the piston.

Abstract: Data mining operations are performed within a columnar database management system. The columnar database management system stores input sets of data for a data mining operation. An input set of data is represented as a column of data in the columnar database management system. The columnar database management system stores instructions to perform one or more data mining operations for processing the input sets of data. The columnar database management system receives requests for performing data mining operations and performs the processing of the data mining operation within the columnar database management system. As a result, the processing of data mining operations is performed without requiring multiple data transfers between an application implementing the data mining operations and the columnar database management system.

Abstract: Data mining operations are performed within a columnar database management system. The columnar database management system stores input sets of data for a data mining operation. An input set of data is represented as a column of data in the columnar database management system. The columnar database management system stores instructions to perform one or more data mining operations for processing the input sets of data. The columnar database management system receives requests for performing data mining operations and performs the processing of the data mining operation within the columnar database management system. As a result, the processing of data mining operations is performed without requiring multiple data transfers between an application implementing the data mining operations and the columnar database management system.

Abstract: Venn diagrams are computed for a given plurality of input sets. The process of computing the Venn diagrams is executed on columnar database systems for efficient execution. The computation of various subsets of the Venn diagrams is performed by determining subsets of various combinations of the input sets and computing set differences of the intersection sets. The process orders the execution of various steps of computing the subsets for the Venn diagram in an order that reduces the number of times an input set is loaded. Information describing various subsets of a Venn diagram is used to render the Venn diagram for display, for example, on a client device.

Abstract: Venn diagrams are computed for a given plurality of input sets. The process of computing the Venn diagrams is executed on columnar database systems for efficient execution. The computation of various subsets of the Venn diagrams is performed by determining subsets of various combinations of the input sets and computing set differences of the intersection sets. The process orders the execution of various steps of computing the subsets for the Venn diagram in an order that reduces the number of times an input set is loaded. Information describing various subsets of a Venn diagram is used to render the Venn diagram for display, for example, on a client device.

Abstract: Cross-tabulation operation is performed within a columnar database management system. The columnar database management system receives a request to perform a cross-tabulation operation on a set of database tables. The columnar database management system determines values of cross-tabulation operation for each row of the result. The columnar database management system determines a domain for each value of the row dimension corresponding to a row combination. The columnar database management system determines an intersection set of the domains corresponding to values of the row dimensions for the row combination. The columnar database management system determines a value for the result column for the row combination as an aggregate value based on the records of the intersection set.