Abstract: Intra-application messaging that is non-coupled may be facilitated through byte code injection. For example, a consumer class may be annotated with an annotation that describes data with which the function is to be called to consume data. A producer class may annotate a field/variable of an annotation to indicate that the data is generated by the producer class. At run time, a customized class loader scans each class as it is loaded for these annotations. When a consumer class is found, a byte code injector may write byte code that registers a consumer object instantiated from the consumer class to receive the data from a message router. When a producer class is found, a byte code injector may write byte code that notifies the message router that the data is available.

Abstract: Intra-application messaging that is non-coupled may be facilitated through byte code injection. For example, a consumer class may be annotated with an annotation that describes data with which the function is to be called to consume data. A producer class may annotate a field/variable of an annotation to indicate that the data is generated by the producer class. At run time, a customized class loader scans each class as it is loaded for these annotations. When a consumer class is found, a byte code injector may write byte code that registers a consumer object instantiated from the consumer class to receive the data from a message router. When a producer class is found, a byte code injector may write byte code that notifies the message router that the data is available.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: The present disclosure is directed to persisting values in a computing environment, particularly using computer programs that run on a virtual machine. An illustrative method includes first launching a computer program, preferably within the environment of a virtual machine. The method further includes loading a plurality of classes associated with the computer program into memory by way of a special class loader. This class loader scans at least one class of classes loaded into memory for at least one persistence-annotated field within that class. The special class loader further writes byte code into a class that contains the at least one persistence-annotated field. The byte code that is added to the class causes a first object that is later instantiated from the at least one class to have the persistence-annotated field.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: Materialized views are maintained for time-series databases, to enable faster analytics over large data sets and to downsample data for storage savings. These materialized views are the result of computations on existing tables, such as aggregation, approximation, sampling, filtering, statistical estimates, and more. A materialized view is created on a base table, and continuously maintained, such that as changes are made to the base table, the materialized view is correspondingly updated. The database system records metadata identifying regions of the base table that have already been materialized. Subsequently, these invalidated regions are rematerialized. Queries ensure up-to-date results by combining data from the materialized view with results calculated at query time on the base table. Invalidation records and completion thresholds are used to determine which results should use records from the materialized table and which should be computed from records from the base table.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: Materialized views are maintained for time-series databases, to enable faster analytics over large data sets and to downsample data for storage savings. These materialized views are the result of computations on existing tables, such as aggregation, approximation, sampling, filtering, statistical estimates, and more. A materialized view is created on a base table, and continuously maintained, such that as changes are made to the base table, the materialized view is correspondingly updated, either synchronously or asynchronously. The database system records metadata identifying regions of the base table that have already been materialized. Subsequently, these invalidated regions are rematerialized. Queries ensure up-to-date results by combining data from the materialized view with results calculated at query time on the base table. Invalidation records and completion thresholds are used to determine which results should use records from the materialized table and which from records from the base table.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: A database system stores both compressed and uncompressed data in a row-based database system. The database system converts a representation of data involving a set of rows of a source database table, each row comprising multiple values, into a representation involving a single row stored in a target database table, each column of the row comprising arrays of values from the set. The database system may perform type-specific compression of data when storing in the target database table. Accordingly, the database system may apply different compression schemes for different columns or sets of values obtained from the source database table and may group or order selected rows or store additional summary information to improve query performance to the target database table. The database system allows users to query data stored in compressed form. The database system combines compressed and uncompressed data at query time for efficient database analytics.

Abstract: Materialized views are maintained for time-series databases, to enable faster analytics over large data sets and to downsample data for storage savings. These materialized views are the result of computations on existing tables, such as aggregation, approximation, sampling, filtering, statistical estimates, and more. A materialized view is created on a base table, and continuously maintained, such that as changes are made to the base table, the materialized view is correspondingly updated. The database system records metadata identifying regions of the base table that have already been materialized. Subsequently, these invalidated regions are rematerialized. Queries ensure up-to-date results by combining data from the materialized view with results calculated at query time on the base table. Invalidation records and completion thresholds are used to determine which results should use records from the materialized table and which should be computed from records from the base table.

Abstract: Materialized views are maintained for time-series databases, to enable faster analytics over large data sets and to downsample data for storage savings. These materialized views are the result of computations on existing tables, such as aggregation, approximation, sampling, filtering, statistical estimates, and more. A materialized view is created on a base table, and continuously maintained, such that as changes are made to the base table, the materialized view is correspondingly updated, either synchronously or asynchronously. The database system records metadata identifying regions of the base table that have already been materialized. Subsequently, these invalidated regions are rematerialized. Queries ensure up-to-date results by combining data from the materialized view with results calculated at query time on the base table. Invalidation records and completion thresholds are used to determine which results should use records from the materialized table and which from records from the base table.

Abstract: The present disclosure is directed to persisting values in a computing environment, particularly using computer programs that run on a virtual machine. An illustrative method includes first launching a computer program, preferably within the environment of a virtual machine. The method further includes loading a plurality of classes associated with the computer program into memory by way of a special class loader. This class loader scans at least one class of classes loaded into memory for at least one persistence-annotated field within that class. The special class loader further writes byte code into a class that contains the at least one persistence-annotated field. The byte code that is added to the class causes a first object that is later instantiated from the at least one class to have the persistence-annotated field.

Abstract: The present disclosure is directed to persisting values in a computing environment, particularly using computer programs that are configured to run on a virtual machine. An illustrative method includes first launching a computer program, preferably within the environment of a virtual machine. The method further includes loading a plurality of classes associated with the computer program into memory by way of a specially configured class loader. This class loader is configured to scan at least one class of classes loaded into memory for at least one persistence-annotated field within that class. The specially configured class loader is further configured to write byte code into a class that contains the at least one persistence-annotated field. The byte code that is added to the class is configured to cause a first object that is later instantiated from the at least one class to have the persistence-annotated field.

Abstract: The present disclosure is directed to persisting values in a computing environment, particularly using computer programs that are configured to run on a virtual machine. An illustrative method includes first launching a computer program, preferably within the environment of a virtual machine. The method further includes loading a plurality of classes associated with the computer program into memory by way of a specially configured class loader. This class loader is configured to scan at least one class of classes loaded into memory for at least one persistence-annotated field within that class. The specially configured class loader is further configured to write byte code into a class that contains the at least one persistence-annotated field. The byte code that is added to the class is configured to cause a first object that is later instantiated from the at least one class to have the persistence-annotated field.

Abstract: Disclosed are advantageous methods for patterning and/or mineralizing biomaterial surfaces. The techniques described are particularly useful for generating three-dimensional or contoured bioimplant materials with patterned surfaces or patterned, mineralized surfaces. Also provided are various methods of using the mineralized and/or patterned biomaterials in tissue engineering, such as bone tissue engineering, providing more control over ongoing biological processes, such as mineralization, growth factor release, cellular attachment and tissue growth.

Abstract: A surgical instrument for applying a plurality of surgical fasteners to body tissue. The surgical instrument includes a frame having a handle at a proximal end thereof, and a support structure at a distal end thereof. The support structure adapted to support a plurality of surgical fasteners and is formed from aluminum.

Abstract: A surgical instrument for applying a plurality of surgical fasteners to body tissue. The surgical instrument includes a frame having a proximal end and a distal end, with a handle at the proximal end and a support structure at the distal end. The support structure is adapted to support cartridge containing the plurality of surgical fasteners. The instrument further includes a closure member for supporting at least a portion of the cartridge for movement from a proximal end of the support structure to a distal end of the support structure, wherein at least a portion of the closure member is made from plastic.