Abstract: A method includes determining a current situation to be present in a process controlled by an industrial process control and automation system (IPCS) that includes at least one process controller coupled to input output (I/O) modules coupled to field devices including sensors and actuators that are coupled to processing equipment. Responsive to the current situation, displaying a plurality of suggested actions each including at least one step in a selectable panel in a human machine interface (HMI) associated with an operator computing system for an operator that is coupled to the process controller. Responsive to the displaying, the operator selects in the selectable panel at least one of the plurality of suggested actions (selected action). The selecting of the selected action results in the IPCS automatically implementing at least in part the step(s) associated with the selected action.

Abstract: This disclosure relates to antibodies and antigen binding fragments that specifically bind Ebola virus particles. In certain embodiments, the antibodies and fragments are capable of treating or preventing an Ebola viral infection. In certain embodiments, the antibodies and antigen binding fragments are also contemplated for diagnostic methods and compositions related thereto.

Abstract: This disclosure relates to antibodies and antigen binding fragments that specifically bind Ebola virus particles. In certain embodiments, the antibodies and fragments are capable of treating or preventing an Ebola viral infection. In certain embodiments, the antibodies and antigen binding fragments are also contemplated for diagnostic methods and compositions related thereto.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: Systems and methods are disclosed configured to train an autoencoder. A data training set is generated comprising images of different faces. A first autoencoder configuration is generated, comprising a first encoder, and a first decoder. The first autoencoder configuration is trained using dataset images, wherein weights associated with the first encoder and weights associated with the first decoder are modified. A second autoencoder configuration is generated comprising the first encoder and a second decoder. The second decoder is trained using images of a first target face. First encoder weights are substantially maintained, and weights associated with the second decoder are modified. An autoencoder comprising the trained first encoder and the trained second decoder generates an output using a source image of a first face having a facial expression, where the facial expression of the first face from the source image is applied to the first specific target face.

Abstract: Aspects of the present disclosure provide systems, methods, apparatus, and computer-readable storage media that support local and cloud-based tax determination operations. In some examples, a transaction system may execute a local tax engine to enable localized tax calculation services in a lightweight footprint while still achieving one or more benefits of a cloud-based system (e.g., technical support and automatic updates of software and tax content). As a result, some aspects of the present disclosure may enable a “full power” tax engine that is local to a transactional system, such as an edge device, while also enabling the tax engine to automatically sync back to a cloud-based system, such as to receive one or more of a configuration update, a software release, a software update, or updated tax content. Further, the transaction system may transmit results of tax calculations to the cloud-based system, such as for reporting, compliance, or both.

Abstract: Systems and methods are disclosed configured to train an autoencoder. A data training set is generated comprising images of different faces. A first autoencoder configuration is generated, comprising a first encoder, and a first decoder. The first autoencoder configuration is trained using dataset images, wherein weights associated with the first encoder and weights associated with the first decoder are modified. A second autoencoder configuration is generated comprising the first encoder and a second decoder. The second decoder is trained using a plurality of images of a first target face. First encoder weights are substantially maintained, and weights associated with the second decoder are modified. An autoencoder comprising the trained first encoder and the trained second decoder is used to generate an output using a source image of a first face having a facial expression, where the facial expression of the first face from the source image is applied to the first specific target face.

Abstract: A method includes determining a current situation to be present in a process controlled by an industrial process control and automation system (IPCS) that includes at least one process controller coupled to input output (I/O) modules coupled to field devices including sensors and actuators that are coupled to processing equipment. Responsive to the current situation, displaying a plurality of suggested actions each including at least one step in a selectable panel in a human machine interface (HMI) associated with an operator computing system for an operator that is coupled to the process controller. Responsive to the displaying, the operator selects in the selectable panel at least one of the plurality of suggested actions (selected action). The selecting of the selected action results in the IPCS automatically implementing at least in part the step(s) associated with the selected action.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: This disclosure relates to antibodies and antigen binding fragments that specifically bind Ebola virus particles. In certain embodiments, the antibodies and fragments are capable of treating or preventing an Ebola viral infection. In certain embodiments, the antibodies and antigen binding fragments are also contemplated for diagnostic methods and compositions related thereto.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: A method includes creating, in a secure platform, multiple securely-partitioned system sandboxes under control of at least one user associated with an industrial process control and automation system. Different system sandboxes are associated with different third parties who are not owners or operators of the industrial process control and automation system. The method also includes receiving content from the third parties in the system sandboxes. The method further includes receiving from the at least one user a selective activation of at least some of the content in the system sandboxes in order to place the at least some of the content into use by the industrial process control and automation system. The content could include equipment configurations for equipment associated with the industrial process control and automation system, and the equipment configurations could include control strategies and visualizations for the equipment.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: Systems and methods are disclosed configured to train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a face exhibiting a plurality of facial expressions and transitions between facial expressions is generated and accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles and using different lighting. An autoencoder is trained using source images that include the face with different facial expressions captured at different angles with different lighting, and using destination images that include a destination face.

Abstract: Systems and methods are disclosed configured to pre-train an autoencoder using images that include faces, wherein the autoencoder comprises an input layer, an encoder configured to output a latent image from a corresponding input image, and a decoder configured to attempt to reconstruct the input image from the latent image. An image sequence of a CGI sculpted and textured face exhibiting a plurality of facial expressions and transitions between facial expressions is accessed. Images of the plurality of facial expressions and transitions between facial expressions are captured from a plurality of different angles. The pre-trained autoencoder is trained using source images that include a CGI face with different facial expressions captured at different angles, and using destination images that include a real face. The trained autoencoder is used to generate an output where the real face in the destination images is swapped with the CGI face, while preserving expressions of the real face.

Abstract: A method includes creating, in a secure platform, multiple securely-partitioned system sandboxes under control of at least one user associated with an industrial process control and automation system. Different system sandboxes are associated with different third parties who are not owners or operators of the industrial process control and automation system. The method also includes receiving content from the third parties in the system sandboxes. The method further includes receiving from the at least one user a selective activation of at least some of the content in the system sandboxes in order to place the at least some of the content into use by the industrial process control and automation system. The content could include equipment configurations for equipment associated with the industrial process control and automation system, and the equipment configurations could include control strategies and visualizations for the equipment.

Abstract: The present invention is directed to the welding of a trailing sheet tail on a roll of sheet material to an underlying layer of the sheet material on the roll to form a finished roll product ready for packaging. A device for effecting the welding comprises a thermally conductive, heat sealing disk mounted for rotation about an axis, and a heating element for heating an inner portion of the disk so as to cause thermal conduction through an outer portion of the disk towards an outer peripheral surface thereof. The heat sealing disk is mounted for engagement with the outer surface of the trailing sheet tail to weld this tail to the underlying layer of sheet material on the roll.