Abstract: A laminate includes the following substantially coextensive layers in the following order: (a) a non-sealable, self-supporting, thermoformable copolyester film layer having a first surface and a second surface, the second surface constituting an outermost, exposed surface of the laminate; (b) a laminating adhesive layer on the first surface of the thermoformable copolyester film layer; and (c) a self-supporting, thermoformable structural film layer having a first surface and a second surface, the first surface contacting the laminating adhesive layer.

Abstract: Methods of treating of interstitial lung disease, reducing pulmonary function decline in a subject with interstitial lung disease (ILD), and increasing forced vital capacity (FVC) in a subject suffering from ILD are provided, wherein the methods include administration of treprostinil.

Abstract: Systems and methods for determining the likelihood of a supplier accepting a certain transaction method such as a payment card. Exemplary systems can generate a machine learning predictive model to determine the likelihood of a supplier accepting a card payment.

Abstract: A gene editing system is provided that comprises a first nucleotide molecule encoding a dCas9-Ten-Eleven Translocation methylcytosine dioxygenase 1 catalytic domain (TET1CD) fusion protein; and a second nucleotide molecule encoding at least one small guide RNA (sgRNA), comprising: a scaffold region and a spacer region, wherein the spacer region hybridizes to a nucleotide sequence complementary to a target sequence adjacent to a 5?-end of a protospacer adjacent motif (PAM), and wherein the target sequence and the PAM are located within 1 kilobase (kb) of the transcriptional start site (TSS) of the CDKL5 gene. Methods of making and using the system are further described herein.

Abstract: Systems and methods of the present disclosure enable distribution modelling and forecasting for populations and sub-populations of entities by employing a processor to receive a numerical data history for a population of entities, with the numerical data history including a series of activity-related quantity indices through time and the population of entities including sub-populations. The processor determines a combination of normal distributions approximating an index distribution for the sub-population of the entities based on the series of activity-related quantity indices, where the normal distributions are centered around a respective mean quantity value of a respective sub-population. The processor uses the normal distributions to eliminate simulations by using a Bayesian model to approximate an inferred index distribution for a particular sub-population. The processor determines at least one inferred statistical value based on the inferred index distribution.

Abstract: In order to facilitate entity resolution, systems and methods include a processor receiving first records associated with one or more entities, and second records associated with the one or more entities. The processor generates candidate pairs based on a similarity between first entity data and second entity data. The processor generates features for each candidate pair based on similarity measures between the first entity record and the second entity record. The processor utilizes a scoring machine learning model to determine a match score for each candidate pair based on each feature. The processor determines clusters of candidate pairs based on the match score of each feature for each candidate pair. The processor merges records of candidate pairs of each cluster into a respective entity record. The processor determines an entity associated with each entity record and updates an entity database with the entity record.

Abstract: In order to facilitate entity resolution, systems and methods include a processor receiving first records associated with one or more entities, and second records associated with the one or more entities. The processor generates candidate pairs based on a similarity between first entity data and second entity data. The processor generates features for each candidate pair based on similarity measures between the first entity record and the second entity record. The processor utilizes a scoring machine learning model to determine a match score for each candidate pair based on each feature. The processor determines clusters of candidate pairs based on the match score of each feature for each candidate pair. The processor merges records of candidate pairs of each cluster into a respective entity record. The processor determines an entity associated with each entity record and updates an entity database with the entity record.

Abstract: In order to facilitate entity resolution, systems and methods include a processor receiving first records associated with one or more entities, and second records associated with the one or more entities. The processor generates candidate pairs based on a similarity between first entity data and second entity data. The processor generates features for each candidate pair based on similarity measures between the first entity record and the second entity record. The processor utilizes a scoring machine learning model to determine a match score for each candidate pair based on each feature. The processor determines clusters of candidate pairs based on the match score of each feature for each candidate pair. The processor merges records of candidate pairs of each cluster into a respective entity record. The processor determines an entity associated with each entity record and updates an entity database with the entity record.

Abstract: In order to facilitate entity resolution, systems and methods include a processor receiving first records associated with one or more entities, and second records associated with the one or more entities. The processor generates candidate pairs based on a similarity between first entity data and second entity data. The processor generates features for each candidate pair based on similarity measures between the first entity record and the second entity record. The processor utilizes a scoring machine learning model to determine a match score for each candidate pair based on each feature. The processor determines clusters of candidate pairs based on the match score of each feature for each candidate pair. The processor merges records of candidate pairs of each cluster into a respective entity record. The processor determines an entity associated with each entity record and updates an entity database with the entity record.

Abstract: Exemplary systems and methods for calendaring are provided. Exemplary systems include a natural language receiving component configured to receive a natural language entry corresponding to a future status, a calendar generation engine configured to create a calendar entry based on the natural language entry, a social network database configured for accessing and querying by the calendar generation engine, a privacy component configured to receive a privacy setting indicating a person who is approved to view the calendar entry, and a display module configured to display the calendar entry on a calendar. Exemplary methods include receiving a natural language entry corresponding to a future status, creating a calendar entry, and displaying the calendar entry.

Abstract: A social networking service presents information about the social network using multiple feeds in a user interface and provides mechanisms for filtering the content. A content feed includes the most recent content generated by the user's connections, and a highlights feed displays content based on importance and relevance. A user may add content to the social networking service through a composer interface. A user may also filter either or both of the content feed and the highlights feed using a filtering interface, which allows selective filtering of the feeds using one or more different types of filters, including as filtering by the source of the content, friends or networks, and/or content type.

Abstract: In one embodiment, a method includes receiving an indication of a first location of a first user from a mobile-client system of a first user, generating one or more search queries based on the location of the first user, executing one or more of the search queries, and sending a plurality of search results corresponding to the executed search queries to the mobile-client system.

Abstract: Exemplary systems and methods for calendaring are provided. Exemplary systems include a natural language receiving component configured to receive a natural language entry corresponding to a future status, a calendar generation engine configured to create a calendar entry based on the natural language entry, a social network database configured for accessing and querying by the calendar generation engine, a privacy component configured to receive a privacy setting indicating a person who is approved to view the calendar entry, and a display module configured to display the calendar entry on a calendar. Exemplary methods include receiving a natural language entry corresponding to a future status, creating a calendar entry, and displaying the calendar entry.

Abstract: Exemplary systems and methods for calendaring are provided. Exemplary systems include a natural language receiving component configured to receive a natural language entry corresponding to a future status, a calendar generation engine configured to create a calendar entry based on the natural language entry, a social network database configured for accessing and querying by the calendar generation engine, a privacy component configured to receive a privacy setting indicating a person who is approved to view the calendar entry, and a display module configured to display the calendar entry on a calendar. Exemplary methods include receiving a natural language entry corresponding to a future status, creating a calendar entry, and displaying the calendar entry.

Abstract: An external system (e.g., a website) is associated with an event and includes an interface that allows users to interact with streams of content associated with a social networking system. The interface allows a user to provide posts about the event via the interface, where the posts are displayed in the interface and also in a social networking interface on social networking system in connection with the user and other users associated with that user. The user can view, via the interface on the external system, posts from all users that are provided via the interface (e.g., everyone watching the event), thereby increasing the likelihood that the posts are relevant to the event. The user can also view, via the interface, posts from users associated with the user via the social networking system (e.g., friends of the user), regardless of where those are posted.

Abstract: In one embodiment, a method includes receiving an indication of a first location of a first user from a mobile-client system of a first user, generating one or more search queries based on the location of the first user, executing one or more of the search queries, and sending a plurality of search results corresponding to the executed search queries to the mobile-client system.

Abstract: Exemplary systems and methods for calendaring are provided. Exemplary systems include a natural language receiving component configured to receive a natural language entry corresponding to a future status, a calendar generation engine configured to create a calendar entry based on the natural language entry, a social network database configured for accessing and querying by the calendar generation engine, a privacy component configured to receive a privacy setting indicating a person who is approved to view the calendar entry, and a display module configured to display the calendar entry on a calendar. Exemplary methods include receiving a natural language entry corresponding to a future status, creating a calendar entry, and displaying the calendar entry.

Abstract: In one embodiment, a method includes receiving an indication of a location of a mobile-client system of a user, determining an intent of the user based on the location of the user, generating one or more suggested queries based on the determined intent of the user; and transmitting a notification to the mobile-client system of the user that includes one or more of the suggested queries.

Abstract: A social networking service presents information about the social network using multiple feeds in a user interface and provides mechanisms for filtering the content. A content feed includes the most recent content generated by the user's connections, and a highlights feed displays content based on importance and relevance. A user may add content to the social networking service through a composer interface. A user may also filter either or both of the content feed and the highlights feed using a filtering interface, which allows selective filtering of the feeds using one or more different types of filters, including as filtering by the source of the content, friends or networks, and/or content type.

Abstract: A social networking service presents information about the social network using multiple feeds in a user interface and provides mechanisms for filtering the content. A content feed includes the most recent content generated by the user's connections, and a highlights feed displays content based on importance and relevance. A user may add content to the social networking service through a composer interface. A user may also filter either or both of the content feed and the highlights feed using a filtering interface, which allows selective filtering of the feeds using one or more different types of filters, including as filtering by the source of the content, friends or networks, and/or content type.