Abstract: In some implementations, a server device can generate configuration data for an application based on user engagement segments associated with a user of the application. For example, a server device can receive information identifying user engagement segments associated with a particular user. When the server device receives a request for configuration data for the application that identifies the particular user, the server device can obtain the engagement segment identifiers associated with the particular user. The server device can use the engagement segment identifiers to obtain segment configuration data for each engagement segment identifier, combine the segment configuration data into a combined configuration, and send the combined configuration to the application on the user device. The application can then determine what content to present and how to present the content on the user device based on the combined configuration data.

Abstract: A source stochastic signal is deconstructed into its intrinsic components using a decomposition process. The intrinsic components are transformed, and a set of machine learning models are defined and trained to operate with individual ones of the transformed components. The source stochastic signal is thus empirically broken down into underlying components which are then used as learning datasets for the set of machine learning models to predict target components. The target components are then individually predicted and combined to reconstruct a predicted target stochastic signal. The source stochastic signal and the target stochastic signals can be biological signals having a related or common origin, such as photoplethysmogram signals and arterial blood pressure waveforms.

Abstract: In some implementations, a server device can generate configuration data for an application based on user engagement segments associated with a user of the application. For example, a server device can receive information identifying user engagement segments associated with a particular user. When the server device receives a request for configuration data for the application that identifies the particular user, the server device can obtain the engagement segment identifiers associated with the particular user. The server device can use the engagement segment identifiers to obtain segment configuration data for each engagement segment identifier, combine the segment configuration data into a combined configuration, and send the combined configuration to the application on the user device. The application can then determine what content to present and how to present the content on the user device based on the combined configuration data.

Abstract: In some implementations, a user device can generate configuration data for an application on the user device using multilevel configuration data. For example, an application on the user device can obtain application level configuration data from a server device. The application level configuration data can be generated based on user engagement segments associated with the user of the user device, for example. The application can obtain publisher level configuration data generated by a content publisher. In response to requesting a content item, the application can receive content level configuration data. The application can combine the application level configuration data, the publisher level configuration data, and/or the content level configuration data to generate dynamic configuration data. The dynamic configuration data can be used by the application to determine, among other things, what content to present to the user of the application on the user device.

Abstract: Systems and methods are provided for managing and rewarding sharing of user data via a computing device with a requesting device. A privacy risk score is received for the requesting device characterizing a degree of cyber risk for sharing data. Initial privacy settings are received for the user via a GUI in response to the privacy risk score characterizing the user data allowable for sharing. A reward incentive is then automatically determined based on the privacy risk and the initial privacy settings for sharing additional user data with the requesting device beyond that identified by the initial privacy settings. Then, in response to an override from the GUI overriding the initial privacy settings to accept the reward incentive and thereby allow sharing of the additional user data beyond the initial range: updated privacy settings are determined and the sharing of the user data is limited to the updated privacy settings.

Abstract: In some implementations, a server device can segment users based on user engagement with an application on a user device. For example, server device can receive user event data from many user devices indicating user activities with respect to the application and/or content presented by the application. The server device can generate user engagement segments based on the received user event data. The server device can generate predictive models for each user engagement segment based on the received user event data. The server device can determine which particular user engagement segments a particular user is associated with based on user event data associated with the particular user and/or the predictions generated by the predictive models. The application on the user device associated with the particular user can then be configured according to the user engagement segments associated with the particular user.

Abstract: In some implementations, a user device can generate configuration data for an application on the user device using multilevel configuration data. For example, an application on the user device can obtain application level configuration data from a server device. The application level configuration data can be generated based on user engagement segments associated with the user of the user device, for example. The application can obtain publisher level configuration data generated by a content publisher. In response to requesting a content item, the application can receive content level configuration data. The application can combine the application level configuration data, the publisher level configuration data, and/or the content level configuration data to generate dynamic configuration data. The dynamic configuration data can be used by the application to determine, among other things, what content to present to the user of the application on the user device.

Abstract: In some implementations, a server device can generate configuration data for an application based on user engagement segments associated with a user of the application. For example, a server device can receive information identifying user engagement segments associated with a particular user. When the server device receives a request for configuration data for the application that identifies the particular user, the server device can obtain the engagement segment identifiers associated with the particular user. The server device can use the engagement segment identifiers to obtain segment configuration data for each engagement segment identifier, combine the segment configuration data into a combined configuration, and send the combined configuration to the application on the user device. The application can then determine what content to present and how to present the content on the user device based on the combined configuration data.

Abstract: In some implementations, a server device can segment users based on user engagement with an application on a user device. For example, server device can receive user event data from many user devices indicating user activities with respect to the application and/or content presented by the application. The server device can generate user engagement segments based on the received user event data. The server device can generate predictive models for each user engagement segment based on the received user event data. The server device can determine which particular user engagement segments a particular user is associated with based on user event data associated with the particular user and/or the predictions generated by the predictive models. The application on the user device associated with the particular user can then be configured according to the user engagement segments associated with the particular user.

Abstract: Provided herein are novel, stilbene like compounds of the general formula (I), their derivatives, analogs, tautomeric forms, stereoisomers, polymorphs, hydrates, metabolites, prodrugs, solvates, pharmaceutically acceptable salts and compositions thereof. These compounds can inhibit HDACs and are useful as a therapeutic or ameliorating agent for diseases that are involved in cellular growth such as malignant tumors, autoimmune diseases, skin diseases, infections, inflammation, etc.

Abstract: Provided herein are novel, stilbene like compounds of the general formula (I), their derivatives, analogs, tautomeric forms, stereoisomers, polymorphs, hydrates, metabolites, prodrugs, solvates, pharmaceutically acceptable salts and compositions thereof. These compounds can inhibit HDACs and are useful as a therapeutic or ameliorating agent for diseases that are involved in cellular growth such as WO 2009/047615 A2 malignant tumors, autoimmune diseases, skin diseases, infections, inflammation, etc.

Abstract: A computer implemented method for updating one or a combination of the system software, operating systems, device configuration, application software and firmware of electronic devices via geographically located local communication points likely to be proximate to the electronic device being updated. The communication points are connected to local servers which communicate stored update packages to the electronic device which are pre-provided by the device manufacturers, or customize update packages to the device subsequent to a query response as to the state of software, firmware, and configuration of the device to be updated.

Abstract: A pedestrian navigation and spatial relation device including a position finder, a spatial relationship sensor, an input mechanism, and an output mechanism. The position finder can be configured to determine a geographic position of the device based upon received wireless signals. The spatial relationship sensor can provide data used to detect a position of at least one obstacle relative to the device. The input mechanism can specify a destination location. The output mechanism can present device output to a user. The device output can include sensory indicators for at least one of guiding a pedestrian to the destination location and warning a pedestrian about the detected obstacles.