Abstract: The disclosed exemplary embodiments include computer-implemented systems, apparatuses, and processes that, among other things, generate and provision digital tokens based on dynamically obtained contextual data. For example, an apparatus may receive first information that characterizes an exchange of data initiated by a first application program executed by the apparatus, and may generate and transmit a signal to a computing system through a programmatic interface associated with a second application program executed by the apparatus. In some instances, the first signal may include the first information and data that instructs the computing system to obtain a digital token representative of a data type available for use in the data exchange. The apparatus may also receive a second signal that includes the digital token and based on the digital token, perform operations that present second information characterizing the available data type on an interface.

Abstract: A night vision system, a microchannel plate (MCP), and a planetary deposition system and methodology are provided for selectively depositing an electrode contact metal on one side of MCP channel openings. MCPs can be secured to a face of a platter that rotates about its central platter axis. The rotating platter can be tilted on a fixture surrounding an evaporative source of contact metal. A mask with a variable size mask opening is arranged between the rotating platter and the evaporative source. While the mask orbits around the evaporative source with the rotating platter, the mask does not rotate along its own axis as does the rotating platter. Depending on the opening of the non-rotating mask, and the tilt angle of the rotating platter, the respective circumferential distance around and the depth into the shaded first side of the channel opening is controlled.

Abstract: A night vision system, a microchannel plate (MCP), and a planetary deposition system and methodology are provided for selectively depositing an electrode contact metal on one side of MCP channel openings. One or more MCPs can be releasably secured to a face of a platter that rotates about its central platter axis. The rotating platter can be tilted on a rotating ring fixture surrounding an evaporative source of contact metal. Therefore, the rotating platter further rotates so that it orbits around the evaporative source of contact metal. A mask with a variable size mask opening is arranged between the rotating platter and the evaporative source. While the mask orbits around the evaporative source with the rotating platter, the mask does not rotate along its own axis as does the rotating platter.

Abstract: A night vision system, a microchannel plate (MCP), and a planetary deposition system and methodology are provided for selectively depositing an electrode contact metal on one side of MCP channel openings. One or more MCPs can be releasably secured to a face of a platter that rotates about its central platter axis. The rotating platter can be tilted on a rotating ring fixture surrounding an evaporative source of contact metal. Therefore, the rotating platter further rotates so that it orbits around the evaporative source of contact metal. A mask with a variable size mask opening is arranged between the rotating platter and the evaporative source. While the mask orbits around the evaporative source with the rotating platter, the mask does not rotate along its own axis as does the rotating platter.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: A suction cup can include a body and a skirt connected to a periphery of the body. The body can include an engagement surface with an aperture. A friction material can be positioned on the engagement surface for engagement with a container. A channel can extend along the engagement surface between the aperture and a periphery of the body.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: A learner engagement engine provides a unique way to track and measure a learner's engagement across a plurality of different learning resources. In preferred embodiments, the learning engagement engine measures learner's engagement activities at the most detailed level (such as at a paragraph level, instead of a chapter or book level). This allows the learner engagement engine to easily aggregate learner activities, even when a course structure or context are changed during the course.

Abstract: This disclosure provides multimeric binding molecules that bind to SARS-CoV-2. This disclosure also provides compositions comprising the multimeric binding molecules, polynucleotides that encode the multimeric binding molecules, and host cells that can produce the binding molecules. Further this disclosure provides methods of using the multimeric binding molecules, including methods for treating and preventing coronavirus disease 2019 (COVID-19).

Abstract: A mobile vehicle mounted dry filtration system to support a grinder system used for removal of markings, creating rumble strips, or the like. Blowers create a vacuum for drawing debris and dust from the grinder system into a debris bin. Large debris is removed from the vacuum draw and remains in the bin for later disposal. Small particles and dust are drawn into parallel positioned filter cyclones that have a cyclonic separation followed by flexible and inexpensive bag filters. The flexible filters are cleaned using vibrating diaphragms mounted on the top of the filter cyclones subject to a reverse air flow by the blowers using slide valves. A polishing tank containing water receives the exhaust from the filter cyclones for removal of airborne particles and sound suppression.

Abstract: A system including a computer server implementing a learning resource configured to monitor a user interaction with the learning resource, and encode, based on the user interactions, a user event. The system includes a computer server implementing an event processor. The event processor is configured to receive, from the computer server, the user event, parse the user event to determine the identifications of the user generating the user event, the assessment item, and the learning resource, and the indication of whether the user event is associated with a correct answer or an incorrect answer, and store, in an analytics storage database, a data record including the identification of the user generating the user event, the assessment item, the learning resource, and the indication of whether the user event is associated with a correct answer or an incorrect answer.

Abstract: A computer controlled laser based profiling system for accurate equipment positioning. In one embodiment the profiler is used in combination with a vehicle automated guidance system for guiding a vehicle and equipment secured to a vehicle for removing of road markings. The computer controlled profiler detects the position of one or more grinding, grooving, rumbling heads in the X, Y and Z position. A controller and one or more actuators are manipulated in response to ground markings visible in the field of the laser.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: A grinder truck with a computer controlled profiler in combination with a vehicle automated guidance system for guiding a vehicle and equipment secured to a vehicle for removing of road markings. The computer controlled profiler detects the position of one or more grinding, grooving, rumbling heads in the X, Y and Z position. A controller and one or more actuators are manipulated in response to ground markings visible in a camera field. A remote controller allows an operator to control grinder heads individually, and allows for precise adjustment based upon an operator's visual inspection.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: A system for enterprise performance management includes an enterprise performance management server, including a processor, a non-transitory memory, an input/output, an account aggregation manager, an account planning manager, an activity id correlation table, and activity id connectivity table with an account calculation procedure, a planning account overview table; an enterprise performance management device; an inventory procurement system; and a plurality of enterprise resource planning/accounting systems with general ledgers, such that the system creates an aggregated chart of activity accounts, each activity account comprising an activity id and associated aggregated planned cost, aggregated actual cost, and aggregated forecasted quantity, which aggregates general ledger accounts. The aggregated forecasted quantity can be used for centralized purchasing via the inventory procurement system.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

Abstract: Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.