Abstract: The present invention is directed to compounds and compositions comprising thereof. Further, methods of use such as for the treatment and prevention of a disorder associated with binding of IGF2BP1 to an RNA in a subject in need thereof are also provided.

Abstract: A system and method processes images of insurance cards to extract information. The images of the insurance cards are processed using OCR to identify characters on the insurance cards. Combinations of characters on each insurance card are identified as tokens, and their relative spatial orientation is determined. Deep learning architectures are utilized to generate a fully connected neural network with a node for each token on each card. The neural network is utilized to extract entities from each insurance card, such as a valid member ID.

Abstract: The present disclosure relates to leveraging explainable machine learning methods and feature importance mechanisms as a mechanism for gene discovery and furthermore leveraging the outputs of the gene discovery to recommend ideal gene expression profiles and the requisite genome edits that are conducive to a desired phenotype. Particularly, aspects of the present disclosure are directed to obtaining gene expression profiles for a set of genes measured in a tissue sample of a plant, inputting the gene expression profiles into a prediction model constructed for a task of predicting a phenotype as output data, generating, using the prediction model, the prediction of the phenotype for the plant, analyzing, by an explainable artificial intelligence system, decisions made by the prediction model to predict the phenotype, and identifying a set of candidate gene targets for the phenotype as having a largest contribution or influence on the prediction based on the analyzing.

Abstract: A video annotation interface includes a video pane configured to display a video, a video timeline bar including a video play-head indicating a current point of the video which is being played, a segment timeline bar including initial and final handles configured to define a segment of the video for playing, and a plurality of color-coded comment markers displayed in connection with the video timeline bar. Each of the comment markers is associated with a frame or segment of the video and corresponds to one or more annotations for that frame or segment made by one of a plurality of users. Each of the users can make annotations and view annotations made by other users. The annotations can include annotations corresponding to a plurality of modalities, including text, drawing, video, and audio modalities.

Abstract: A video annotation interface includes a video pane configured to display a video, a video timeline bar including a video play-head indicating a current point of the video which is being played, a segment timeline bar including initial and final handles configured to define a segment of the video for playing, and a plurality of color-coded comment markers displayed in connection with the video timeline bar. Each of the comment markers is associated with a frame or segment of the video and corresponds to one or more annotations for that frame or segment made by one of a plurality of users. Each of the users can make annotations and view annotations made by other users. The annotations can include annotations corresponding to a plurality of modalities, including text, drawing, video, and audio modalities.

Abstract: A video annotation interface includes a video pane configured to display a video, a video timeline bar including a video play-head indicating a current point of the video which is being played, a segment timeline bar including initial and final handles configured to define a segment of the video for playing, and a plurality of color-coded comment markers displayed in connection with the video timeline bar. Each of the comment markers is associated with a frame or segment of the video and corresponds to one or more annotations for that frame or segment made by one of a plurality of users. Each of the users can make annotations and view annotations made by other users. The annotations can include annotations corresponding to a plurality of modalities, including text, drawing, video, and audio modalities.

Abstract: A video annotation interface includes a video pane configured to display a video, a video timeline bar including a video play-head indicating a current point of the video which is being played, a segment timeline bar including initial and final handles configured to define a segment of the video for playing, and a plurality of color-coded comment markers displayed in connection with the video timeline bar. Each of the comment markers is associated with a frame or segment of the video and corresponds to one or more annotations for that frame or segment made by one of a plurality of users. Each of the users can make annotations and view annotations made by other users. The annotations can include annotations corresponding to a plurality of modalities, including text, drawing, video, and audio modalities.

Abstract: A video annotation interface includes a video pane configured to display a video, a video timeline bar including a video play-head indicating a current point of the video which is being played, a segment timeline bar including initial and final handles configured to define a segment of the video for playing, and a plurality of color-coded comment markers displayed in connection with the video timeline bar. Each of the comment markers is associated with a frame or segment of the video and corresponds to one or more annotations for that frame or segment made by one of a plurality of users. Each of the users can make annotations and view annotations made by other users. The annotations can include annotations corresponding to a plurality of modalities, including text, drawing, video, and audio modalities.

Abstract: Multiple sets of data are obtained from different sources. Each data set is represented using a different format having a different syntax and organized in a multi-level nested data structure. Each data set is reformatted into a standardized table format using a depth-first recursive algorithm without relying on the syntax schema of the original format of the data set. Various operations are performed on the tables corresponding to the data sets, including but not limited to joining multiple tables, grouping selected rows of a table, ranking rows of a table, adding or deleting fields from selected rows of a table, etc. Optionally, inferred namespace and text normalization are utilized for selected table operations. One or more templates are provided for converting the data set of a table to a format that may be presented to a user.

Abstract: Multiple sets of data are obtained from different sources. Each data set is represented using a different format having a different syntax and organized in a multi-level nested data structure. Each data set is reformatted into a standardized table format using a depth-first recursive algorithm without relying on the syntax schema of the original format of the data set. Various operations are performed on the tables corresponding to the data sets, including but not limited to joining multiple tables, grouping selected rows of a table, ranking rows of a table, adding or deleting fields from selected rows of a table, etc. Optionally, inferred namespace and text normalization are utilized for selected table operations. One or more templates are provided for converting the data set of a table to a format that may be presented to a user.

Abstract: An improved system and method for ranking search results using social information is provided. A social information ranking engine may be provided to rerank a list of URLs of web pages in search results from a search engine using social information. To do so, the search query may be applied to a social information domain and a second list of references to web pages may be obtained as search results. A dimensional vector of users with the plurality of terms may be constructed using search results from social information domain, and a similarity measure may be computed between the references to web pages obtained from search results by the search engine and the references to web pages obtained from search results by the social information ranking engine. The score from the similarity measure may then be used to rerank the list of references to web pages.

Abstract: A system and method is provided that permits a conventional search function to use information from a social bookmarking system to provide search results, as the results from social bookmarking systems are generally very relevant. According to one example, a blended search result is determined using results from a conventional search engine and results found by a social bookmarking system. In one example, these results are blended and presented to a user within a single interface. In another example, search results and results from a social bookmarking system are normalized so that they can be combined within the same interface. Generally, a method is provided for blending search results from two or more different corpora having different search engines.

Abstract: An improved system and method for ranking search results using social information is provided. A social information ranking engine may be provided to rerank a list of URLs of web pages in search results from a search engine using social information. To do so, the search query may be applied to a social information domain and a second list of references to web pages may be obtained as search results. A dimensional vector of users with the plurality of terms may be constructed using search results from social information domain, and a similarity measure may be computed between the references to web pages obtained from search results by the search engine and the references to web pages obtained from search results by the social information ranking engine. The score from the similarity measure may then be used to rerank the list of references to web pages.

Abstract: Multiple sets of data are obtained from different sources. Each data set is represented using a different format having a different syntax and organized in a multi-level nested data structure. Each data set is reformatted into a standardized table format using a depth-first recursive algorithm without relying on the syntax schema of the original format of the data set. Various operations are performed on the tables corresponding to the data sets, including but not limited to joining multiple tables, grouping selected rows of a table, ranking rows of a table, adding or deleting fields from selected rows of a table, etc. Optionally, inferred namespace and text normalization are utilized for selected table operations. One or more templates are provided for converting the data set of a table to a format that may be presented to a user.

Abstract: Multiple sets of data are obtained from different sources. Each data set is represented using a different format having a different syntax and organized in a multi-level nested data structure. Each data set is reformatted into a standardized table format using a depth-first recursive algorithm without relying on the syntax schema of the original format of the data set. Various operations are performed on the tables corresponding to the data sets, including but not limited to joining multiple tables, grouping selected rows of a table, ranking rows of a table, adding or deleting fields from selected rows of a table, etc. Optionally, inferred namespace and text normalization are utilized for selected table operations. One or more templates are provided for converting the data set of a table to a format that may be presented to a user.