Abstract: Systems and methods are provided for determining a set of objects, the objects corresponding to a given case or application of a deletion/retention policy; determining at least one object in the set of objects to be scheduled for deletion, the at least one object being associated with a given state that specifies a deletion and/or retention type and schedule for the at least one object; and scheduling data corresponding to the at least one object for deletion from one or more data sources based at least in part on the deletion and/or retention type and schedule specified in the object state.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and projection datasets. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The projection datasets are indexes of the canonical dataset and/or the buffer that may have single or multiple column sort-orders and/or particular data formats. The writes to the canonical dataset, projection datasets, and buffer may be asynchronous and therefore the database system is advantageously less resource constrained.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and an edits dataset. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The edits dataset is the set of data that contains edits such as cell mutations, row appends and/or row deletions. The database system enables users to make cell or row-level edits to tables and observe those edits in analytical systems or downstream builds with minimal latency.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and projection datasets. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The projection datasets are indexes of the canonical dataset and/or the buffer that may have single or multiple column sort-orders and/or particular data formats. The writes to the canonical dataset, projection datasets, and buffer may be asynchronous and therefore the database system is advantageously less resource constrained.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and an edits dataset. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The edits dataset is the set of data that contains edits such as cell mutations, row appends and/or row deletions. The database system enables users to make cell or row-level edits to tables and observe those edits in analytical systems or downstream builds with minimal latency.

Abstract: One or more context aware processing parameters and an ambient audio stream are received. One or more sound characteristics associated with the ambient audio stream are identified using a machine learning model. One or more actions to perform are determined using the machine learning model and based on the one or more context aware processing parameters and the identified one or more sound characteristics. The one or more actions are performed.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and an edits dataset. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The edits dataset is the set of data that contains edits such as cell mutations, row appends and/or row deletions. The database system enables users to make cell or row-level edits to tables and observe those edits in analytical systems or downstream builds with minimal latency.

Abstract: A database system comprised of a decoupled compute layer and storage layer is implemented to store, build, and maintain a canonical dataset, a temporary buffer, and projection datasets. The canonical dataset is a set of batch updated data. The data is appended in chunks to the canonical dataset such that the canonical dataset becomes a historical dataset over time. The buffer is a write ahead log that contains the most recent chunks of data and provides atomicity and durability for the database system. The projection datasets are indexes of the canonical dataset and/or the buffer that may have single or multiple column sort-orders and/or particular data formats. The writes to the canonical dataset, projection datasets, and buffer may be asynchronous and therefore the database system is advantageously less resource constrained.

Abstract: Systems and methods are provided for determining a set of objects, the objects corresponding to a given case or application of a deletion/retention policy; determining at least one object in the set of objects to be scheduled for deletion, the at least one object being associated with a given state that specifies a deletion and/or retention type and schedule for the at least one object; and scheduling data corresponding to the at least one object for deletion from one or more data sources based at least in part on the deletion and/or retention type and schedule specified in the object state.

Abstract: Systems and methods are provided for determining a set of objects, the objects corresponding to a given case or application of a deletion/retention policy; determining at least one object in the set of objects to be scheduled for deletion, the at least one object being associated with a given state that specifies a deletion and/or retention type and schedule for the at least one object; and scheduling data corresponding to the at least one object for deletion from one or more data sources based at least in part on the deletion and/or retention type and schedule specified in the object state.

Abstract: One or more context aware processing parameters and an ambient audio stream are received. One or more sound characteristics associated with the ambient audio stream are identified using a machine learning model. One or more actions to perform are determined using the machine learning model and based on the one or more context aware processing parameters and the identified one or more sound characteristics. The one or more actions are performed.

Abstract: Approaches for displaying a user interface including a map based on interaction data are disclosed. A set of interaction data and can be acquired and stored in a data structure. This data can be associated with a plurality of consuming entities that may have purchased something during these interactions. A set of provisioning entities can be determined based on spending or purchasing habits of the consuming entities. Based on this set of provisioning entities, a user interface can be generated which may include various shapes similar to a heat map. These shapes can indicate an average amount spent in a particular neighborhood, among other attributes.

Abstract: Systems and methods are provided for determining a set of objects, the objects corresponding to a given case or application of a deletion/retention policy; determining at least one object in the set of objects to be scheduled for deletion, the at least one object being associated with a given state that specifies a deletion and/or retention type and schedule for the at least one object; and scheduling data corresponding to the at least one object for deletion from one or more data sources based at least in part on the deletion and/or retention type and schedule specified in the object state.

Abstract: Approaches for analyzing entity performance are disclosed. A first set of data and a second set of data can be stored in a data structure. This data can be associated with a plurality of interactions, and can be modified to include additional interactions. These interactions can involve consuming entities and provisioning entities. The modified data structure can be queried to retrieve information associated with one or more entities. After information is retrieved, it can be provided to a user.

Abstract: Approaches for analyzing entity performance are disclosed. A first set of data and a second set of data can be stored in a data structure. This data can be associated with a plurality of interactions, and can be modified to include additional interactions. These interactions can involve consuming entities and provisioning entities. The modified data structure can be queried to retrieve information associated with one or more entities. After information is retrieved, it can be provided to a user.

Abstract: One or more context aware processing parameters and an ambient audio stream are received. One or more sound characteristics associated with the ambient audio stream are identified using a machine learning model. One or more actions to perform are determined using the machine learning model and based on the one or more context aware processing parameters and the identified one or more sound characteristics. The one or more actions are performed.

Abstract: One or more context aware processing parameters and an ambient audio stream are received. One or more sound characteristics associated with the ambient audio stream are identified using a machine learning model. One or more actions to perform are determined using the machine learning model and based on the one or more context aware processing parameters and the identified one or more sound characteristics. The one or more actions are performed.

Abstract: Provided is a method of treating a proliferative disease, condition, or disorder in a subject by administering a combination of an inhibitor of p53 and MDM2 binding and an EGFR inhibitor. Various embodiments of the disclosed methods provide a synergistic anti-proliferative or anti-apoptotic effect compared to administration of one agent alone.

Abstract: Provided herein are compounds having anti-proliferative effect. Also provided are compounds that can modulate the activity of multi-domain proteins comprising a dimerization arm and interdomain tether, such as EGFR, where an untethered, extended conformation is the active state and a tethered conformation is the inactive state, resulting in an autoinhibited configuration. Also provided are methods and pharmacophores for identifying such compounds. Other aspects provide methods or therapeutic treatment for proliferative diseases, disorders, or conditions, such as those associated with EGFR.

Abstract: Provided is a method of treating a proliferative disease, condition, or disorder in a subject by administering a combination of an inhibitor of p53 and MDM2 binding and an EGFR inhibitor. Various embodiments of the disclosed methods provide a synergistic anti-proliferative or anti-apoptotic effect compared to administration of one agent alone.