Abstract: Methods and apparatus to assign demographic information to panelists are disclosed.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. An example disclosed apparatus disclosed herein includes a database proprietor identifier (DPID) extractor to extract a panelist database proprietor identifier from a cookie, the panelist database proprietor identifier associated with credentials used by a panelist to access a website.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. An example disclosed apparatus disclosed herein includes a database proprietor identifier (DPID) extractor to extract a panelist database proprietor identifier from a cookie, the panelist database proprietor identifier associated with credentials used by a panelist to access a website.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. An example disclosed method includes generating decoy database proprietor identifiers to protect privacies of members of panelist households corresponding to panelist database proprietor identifiers, the decoy database proprietor identifiers to be determined based on a probability density function so that a quantity of the decoy database proprietor identifiers is less than would be used if the decoy database proprietor identifiers were selected by a random selection process. The example method also includes querying a server at a database proprietor using the panelist database proprietor identifiers and the decoy database proprietor identifiers, to obtain demographic information and assigning, by executing an instruction with a processor, the panelist database proprietor identifiers to panelists in the panelist households based on the demographic information obtained from the server at the database proprietor.

Abstract: Data processing can be managed in a distributed computing environment (DCE). In one example, the DCE can receive a sequence of computing operations to be consecutively executed in the DCE. For each computing operation in the sequence, the DCE can receive input data for the computing operation, partition the input data into subsets, and determine whether the computing operation is linear or non-linear. The DCE can then apply different processing techniques to the subsets depending on whether the computing operation is linear or non-linear.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. An example disclosed method includes generating decoy database proprietor identifiers to protect privacies of members of panelist households corresponding to panelist database proprietor identifiers, the decoy database proprietor identifiers to be determined based on a probability density function so that a quantity of the decoy database proprietor identifiers is less than would be used if the decoy database proprietor identifiers were selected by a random selection process. The example method also includes querying a server at a database proprietor using the panelist database proprietor identifiers and the decoy database proprietor identifiers, to obtain demographic information and assigning, by executing an instruction with a processor, the panelist database proprietor identifiers to panelists in the panelist households based on the demographic information obtained from the server at the database proprietor.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. Example disclosed apparatus include a decoy generator to generate decoy database proprietor identifiers to protect privacies of members of panelist households corresponding to panelist database proprietor identifiers, the decoy database proprietor identifiers to be determined by the decoy generator based on a probability density function so that a quantity of the decoy database proprietor identifiers is less than would be used if the decoy database proprietor identifiers were selected by a random selection process. The example apparatus also includes a query handler to query, via a network, a server at a database proprietor using the panelist database proprietor identifiers and the decoy database proprietor identifiers, to obtain demographic information.

Abstract: A compressed data structure is disclosed for storing collected data and delivering ad-hoc data analysis. The compressed data structure can reduce hardware requirements, such as data storage requirements, and decrease processing requirements during ad-hoc data analysis. Raw data can be pre-aggregated to a base level of aggregation (base cell level) that is determined by the unique combination of attributes available for aggregation. Rather than storing the raw data, the entire distribution is stored at the base cell level along with a selection of pre-computed statistics of the raw data. At the time of ad-hoc analysis, pre-computed results based on the raw data can be retrieved or computed from the pre-computed statistics, or analysis of higher-level data can be computed on-demand based on the pre-aggregated base level data.

Abstract: The present application generally compositions comprising a synthetic delivery RNA comprising a first sequence from a viral genome and/or a second sequence from a viral genome and wherein the synthetic delivery RNA further comprises a nucleic acid sequence encoding a gene. The application further relates to methods of using the composition for delivering a nucleic acid to a nucleus of a cell disclosed herein. The application further relates to methods of treating, inhibiting, or ameliorating a disease in a subject including administering to the subject a cell disclosed herein.

Abstract: A compressed data structure is disclosed for storing collected data and delivering ad-hoc data analysis. The compressed data structure can reduce hardware requirements, such as data storage requirements, and decrease processing requirements during ad-hoc data analysis. Raw data can be pre-aggregated to a base level of aggregation (base cell level) that is determined by the unique combination of attributes available for aggregation. Rather than storing the raw data, the entire distribution is stored at the base cell level along with a selection of pre-computed statistics of the raw data. At the time of ad-hoc analysis, pre-computed results based on the raw data can be retrieved or computed from the pre-computed statistics, or analysis of higher-level data can be computed on-demand based on the pre-aggregated base level data.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. Example disclosed apparatus include a decoy generator to generate decoy database proprietor identifiers to protect privacies of members of panelist households corresponding to panelist database proprietor identifiers, the decoy database proprietor identifiers to be determined by the decoy generator based on a probability density function so that a quantity of the decoy database proprietor identifiers is less than would be used if the decoy database proprietor identifiers were selected by a random selection process. The example apparatus also includes a query handler to query, via a network, a server at a database proprietor using the panelist database proprietor identifiers and the decoy database proprietor identifiers, to obtain demographic information.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. Example disclosed methods include generating decoy database proprietor identifiers based on probability density functions. The example method also include querying a database proprietor using panelist database proprietor identifiers and the decoy database proprietor identifiers to obtain demographic information associated with the panelist database proprietor identifiers. The example method also include assigning the panelist database proprietor identifiers to panelists based on the demographic information obtained from the database proprietor.

Abstract: An apparatus includes a processor and a storage storing instructions causing the processor to receive representation metadata indicating features of representation data to be generated from a plurality of representation portions, receive a command to generate at least one row of the representation data, determine a subset of data blocks of a data blob required to generate the at least one row, and a subset of node devices that store the subset of data blocks, for each node device of the subset of node devices, derive a node block map identifying at least one data item of a data block for generating a representation portion, transmit the node block maps to the subset of node devices; and transmit a command to the subset of node devices to each generate at least one row of one of the plurality of representation portions.

Abstract: An apparatus includes a processor and storage storing instructions causing the processor to store, at a node device of a grid of node devices, a data block of a data blob, receive data blob metadata indicative of an organization of data items within the data blob, receive a command to generate, from the data block, at least one row of a representation portion of a plurality of representation portions from which a 2D representation of the data blob is to be generated, use the data blob metadata and a node block map indicative of which data items of the data block are required to generate the representation portion to derive one or more transforms to be performed with the data block to generate the at least one row of the representation portion, and perform the one or more transforms with the data block to generate the at least one row.

Abstract: An apparatus includes a processor and a storage storing instructions causing the processor to determine whether an analysis routine is multi-threaded and calls a library function of a non-threadsafe library, and if so, causes the processor to: instantiate an analysis process for executing the analysis routine on multiple threads; instantiate an instance of the library for execution within a isolated library process; instantiate another instance of the library for execution within another isolated library process; retrieve library metadata providing a function prototype of the library function; employ the function prototype to generate an instance of a bridge routine to enable a call from the analysis routine on a first thread to the library function; employ the function prototype to generate another instance of the bridge routine to enable a call from the analysis routine on a second thread to the library function; and begin execution of the analysis routine.

Abstract: An apparatus includes a processor and storage storing instructions causing the processor to store, at a node device of a grid of node devices, a data block of a data blob, receive data blob metadata indicative of an organization of data items within the data blob, receive a command to generate, from the data block, at least one row of a representation portion of a plurality of representation portions from which a 2D representation of the data blob is to be generated, use the data blob metadata and a node block map indicative of which data items of the data block are required to generate the representation portion to derive one or more transforms to be performed with the data block to generate the at least one row of the representation portion, and perform the one or more transforms with the data block to generate the at least one row.

Abstract: An apparatus includes a processor and a storage storing instructions causing the processor to receive representation metadata indicating features of representation data to be generated from a plurality of representation portions, receive a command to generate at least one row of the representation data, determine a subset of data blocks of a data blob required to generate the at least one row, and a subset of node devices that store the subset of data blocks, for each node device of the subset of node devices, derive a node block map identifying at least one data item of a data block for generating a representation portion, transmit the node block maps to the subset of node devices; and transmit a command to the subset of node devices to each generate at least one row of one of the plurality of representation portions.

Abstract: An apparatus includes a processor and a storage storing instructions causing the processor to determine whether an analysis routine is multi-threaded and calls a library function of a non-threadsafe library, and if so, causes the processor to: instantiate an analysis process for executing the analysis routine on multiple threads; instantiate an instance of the library for execution within a isolated library process; instantiate another instance of the library for execution within another isolated library process; retrieve library metadata providing a function prototype of the library function; employ the function prototype to generate an instance of a bridge routine to enable a call from the analysis routine on a first thread to the library function; employ the function prototype to generate another instance of the bridge routine to enable a call from the analysis routine on a second thread to the library function; and begin execution of the analysis routine.

Abstract: Methods and apparatus to assign demographic information to panelists are disclosed. Example disclosed methods include generating decoy database proprietor identifiers based on probability density functions. The example method also include querying a database proprietor using panelist database proprietor identifiers and the decoy database proprietor identifiers to obtain demographic information associated with the panelist database proprietor identifiers. The example method also include assigning the panelist database proprietor identifiers to panelists based on the demographic information obtained from the database proprietor.