Abstract: Disclosed are quinoline and quinazoline compounds which modulate the activity of the gated ion channels. Compounds that modulate these gated ion channels are useful in the treatment of diseases and disorders related to pain, inflammation, the neurological system, the gastrointestinal system and genitourinary system. Preferred compounds include quinoline or quinazoline derivatives substituted at the 4-position via N(H), C(O) or O moieties.

Abstract: Provided herein are compounds of Formula (I): and forms thereof, including compositions thereof and uses therewith for treating spinal muscular atrophy.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.

Abstract: There is a need for solutions for efficiently and reliably perform sensor-based predictive data analysis. This need can be addressed by, for example, solutions for performing cross-sensor predictive data analysis. In one example, a method for performing cross-sensor predictive data analysis includes identifying sensor input data objects comprising one or more image data objects; determining sensor feature data objects based on the sensor input data objects; generating predictions for a target predictive entity associated with the sensor input data objects by processing the sensor feature data objects using a cross-sensor predictive inference model; and performing prediction-based actions based on the cross-sensor predictions.

Abstract: An apparatus for reconstructing a 3D object, includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain, using a first neural network, mapping function weights of a mapping function of a second neural network, based on an image feature vector corresponding to a 2D image of the 3D object, set the mapping function of the second neural network, using the obtained mapping function weights, and based on sampled points of a canonical sampling domain, obtain, using the second neural network of which the mapping function is set, 3D point coordinates and geodesic lifting coordinates of each of the sampled points in the 3D object corresponding to the 2D image, wherein the 3D point coordinates are first three dimensions of an embedding vector of a respective one of the sampled points, and the geodesic lifting coordinates are remaining dimensions of the embedding vector.

Abstract: There is a need for solutions for efficiently and reliably maintain data security policies. This need can be addressed by, for example, solutions for performing dynamic security enforcement in a data interaction platform. In one example, a method includes determining a security profile for a data object; receiving a data access request associated with the data object, wherein the data access request is associated with one or more runtime parameters associated with the data access request; determining, based at least in part on the one or more runtime parameters; determining, based at least in part on the selected security environment and the security profile, a selected access level of the plurality of access levels for the data object; and processing the data access request based at least in part on the selected access level.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: An apparatus for reconstructing a 3D object, includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain, using a first neural network, mapping function weights of a mapping function of a second neural network, based on an image feature vector corresponding to a 2D image of the 3D object, set the mapping function of the second neural network, using the obtained mapping function weights, and based on sampled points of a canonical sampling domain, obtain, using the second neural network of which the mapping function is set, 3D point coordinates and geodesic lifting coordinates of each of the sampled points in the 3D object corresponding to the 2D image, wherein the 3D point coordinates are first three dimensions of an embedding vector of a respective one of the sampled points, and the geodesic lifting coordinates are remaining dimensions of the embedding vector.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: There is a need for more effective and efficient data modeling and/or data visualization solutions. This need can be addressed by, for example, solutions for performing data modeling and/or data visualization in an effective and efficient manner. In one example, solutions for generating a data model with dynamic relational awareness are disclosed. In another example, solutions for processing data retrieval queries using data models with dynamic relational awareness are disclosed. In yet another example, solutions for generating data visualizations using data models with dynamic relational awareness are disclosed. In a further example, solutions for integrating external data objects into data models with dynamic relational awareness are disclosed.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.

Abstract: Methods, systems, apparatus, and computer program products are provided. In an example embodiment, a method is provided comprising receiving input identifying load information corresponding to a load to be inserted into a transportation plan. The transportation plan comprises a plurality of transportation schedules, each schedule comprising a plurality of transportation movements. The method further comprises identifying an available movement network comprising portions of transportation schedules having open capacity, each portion of a transportation schedule having open capacity being a potential leg of a path from the origin location to the destination location; determining potential solutions for transporting the load from the origin location to the destination location by combining one or more legs to determine a path of open capacity movements from the origin location to at least part way to the destination location; and providing one or more potential solutions for display via a user interface.