Abstract: Novel compounds of the structural formula (I), and the pharmaceutically acceptable salts thereof, are inhibitors of NLRP3 and may be useful in the treatment, prevention, management, amelioration, control and suppression of diseases mediated by NLPR3. The compounds of the present invention may be useful in the treatment, prevention or management of diseases, disorders and conditions mediated by NLRP3 such as, but not limited to, gout, pseudogout, CAPS, NASH fibrosis, heart failure, idiopathic pericarditis, atopic dermatitis, inflammatory bowel disease, Alzheimer's Disease, Parkinson's Disease and traumatic brain injury.

Abstract: The present invention provides a compound of Formula I and pharmaceutical compositions comprising one or more said compounds, and methods for using said compounds for treating or preventing one or more disease states that could benefit from inhibition of plasma kallikrein, including hereditary angioedema, uveitis, posterior uveitis, wet age related macular edema, diabetic macular edema, diabetic retinopathy and retinal vein occlusion. The compounds are selective inhibitors of plasma kallikrein.

Abstract: In an example embodiment, a deep neural network is used to predict a classification for ingested job listings for a piece of information that is missing from the ingested job listings. More particularly, the deep neural network may comprise a multi-layer perceptron with a plurality of rectifier linear units (ReLUs). For a given category of information, a plurality of different information entities may be evaluated by the multi-layer perceptron against features of a job listing, producing a probability prediction of reach of those information entities for the job listing. The information entity with the highest predicted probability is identified by the multi-layer perceptron as the predicted information entity for that given category of information for the job listing.

Abstract: An evacuation slide may comprise a first side rail, a second side rail, and a sliding structure. The first side rail and the second side rail may each extend from a head end of the evacuation slide to a toe end of the evacuation slide. The sliding structure may be located between the first side rail and the second side rail. The sliding structure may comprise a drop stitch fabric.

Abstract: An evacuation slide may comprise a first side rail, a second side rail, and a sliding structure. The first side rail and the second side rail may each extend from a head end of the evacuation slide to a toe end of the evacuation slide. The sliding structure may be located between the first side rail and the second side rail. The sliding structure may comprise a drop stitch fabric.

Abstract: Techniques for optimizing content item delivery for installations or activations of a mobile application are provided. In one technique, a machine-learned model is trained based on multiple training instances that individually indicate whether an entity performed a particular action relative to a mobile application. In response to receiving a content item request from a third-party content delivery exchange, it is determined whether a client device that initiated the content item request has activated a particular application. In response to determining that the client device has not activated the particular application, multiple feature values of the content item request are identified. Based on inputting the feature values into the model, a score is generated that indicates a likelihood that an entity of the client device will perform the particular action relative to the particular application. Based on the score, a content item is transmitted over a network to the client device.

Abstract: Techniques for optimizing network-transferred multi-card content items are provided. In one technique, a first content item selection event is initiated that involves a set of content delivery campaigns that includes a content delivery campaign that includes a content item that comprises multiple cards. The content delivery campaign is selected and the content item is transmitted to a first computing device, where the multiple cards have a first card configuration. One or more events that are associated with the first computing device displaying at least one card of the plurality of cards is identified. Based on the events, a second card configuration is determined. Another content item selection event that involves the content delivery campaign is initiated and the content delivery campaign is selected. The content item is transmitted to a second computing device, where the multiple cards have the second card configuration.

Abstract: Techniques for optimizing content item delivery for installations or activations of a mobile application are provided. In one technique, a machine-learned model is trained based on multiple training instances that individually indicate whether an entity performed a particular action relative to a mobile application. In response to receiving a content item request from a third-party content delivery exchange, it is determined whether a client device that initiated the content item request has activated a particular application. In response to determining that the client device has not activated the particular application, multiple feature values of the content item request are identified. Based on inputting the feature values into the model, a score is generated that indicates a likelihood that an entity of the client device will perform the particular action relative to the particular application. Based on the score, a content item is transmitted over a network to the client device.

Abstract: Techniques for optimizing network-transferred multi-card content items are provided. In one technique, a first content item selection event is initiated that involves a set of content delivery campaigns that includes a content delivery campaign that includes a content item that comprises multiple cards. The content delivery campaign is selected and the content item is transmitted to a first computing device, where the multiple cards have a first card configuration. One or more events that are associated with the first computing device displaying at least one card of the plurality of cards is identified. Based on the events, a second card configuration is determined. Another content item selection event that involves the content delivery campaign is initiated and the content delivery campaign is selected. The content item is transmitted to a second computing device, where the multiple cards have the second card configuration.