Abstract: The present disclosure provides a device for determining the presence of BNP, proBNP and NT-proBNP. The devices comprise multiple capture regions configured to selectively capture BNP, proBNP and NT-proBNP by specific binding of proBNP. Alternatively or additionally, the devices may capture and label epitopes to distinguish proBNP from NT-proBNP or BNP.

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: 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: Computer-implemented methods of classifying analyte data are provided. Methods of interest include applying a regression model to determine a relationship between an initial set of analyte features and a cluster criterion, generating a sparse set from at most a portion of the initial set of the analyte features based on the relationship, generating a classification model based on the sparse set, and applying the classification model to classify the analyte data into the clusters. Systems and non-transitory computer-readable storage media configured to carry out the subject methods are also provided.

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: The disclosure relates to coated surfaces suitable for cell culture, to methods for making such surfaces, and to methods for culturing adherent cells on such surfaces. One aspect of the disclosure is a surface suitable for cell culture including an amorphous hydrogenated carbon coating. Another aspect of the disclosure is a method for making a surface suitable for cell culture including an amorphous hydrogenated carbon coating. Another aspect of the disclosure is a method for culturing adherent cells that includes incubating a surface including an amorphous hydrogenated carbon coating with adherent cells and a growth medium.

Abstract: A system derives training set factors for a customer sentiment score associated with a training set customer corresponding to training set support tickets, and a training set factor for a rate of a critical status corresponding to the training set support tickets. The system uses the training set factors to train a machine-learning model to determine a customer health score associated with the training set customer. The system derives factors for a customer sentiment score associated with a customer corresponding to support tickets, and a factor for a rate of a critical status corresponding to the support tickets. The trained machine-learning model uses the factors to determine a customer health score associated with the customer. The system enables a selection of escalating any customer account, de-escalating any customer account, escalating any support ticket, and/or de-escalating any support ticket, associated with the customer, in response to outputting the customer health score.

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.