Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a machine-learned yield model. In particular, the machine-learned yield model can be trained or otherwise configured to receive and process feature data descriptive of objects perceived by the autonomous vehicle and/or the surrounding environment and, in response to receipt of the feature data, provide yield decisions for the autonomous vehicle relative to the objects. For example, a yield decision for a first object can describe a yield behavior for the autonomous vehicle relative to the first object (e.g., yield to the first object or do not yield to the first object). Example objects include traffic signals, additional vehicles, or other objects. The motion of the autonomous vehicle can be controlled in accordance with the yield decisions provided by the machine-learned yield model.

Abstract: The disclosure provides, e.g., compositions, systems, and methods for targeting, editing, modifying, or manipulating a host cell's genome at one or more locations in a DNA sequence in a cell, tissue, or subject. Gene modifying systems for treating cystic fibrosis, e.g., in subjects having a mutation resulting in F508del, are described.

Abstract: The disclosure provides, e.g., compositions, systems, and methods for targeting, editing, modifying, or manipulating a host cell's genome at one or more locations in a DNA sequence in a cell, tissue, or subject. Gene modifying systems for treating phenylketonuria (PKU) are described.

Abstract: The disclosure provides, e.g., compositions, systems, and methods for targeting, editing, modifying, or manipulating a host cell's genome at one or more locations in a DNA sequence in a cell, tissue, or subject. Gene modifying systems for treating alpha-1 antitrypsin deficiency (AATD) are described.

Abstract: A security device made up of a security film (130) having (i) an array of image elements (103); (ii) an array of focusing elements (106); and (iii) at least one anti-viscid agent (115), is provided. The array of focusing elements and the array of image elements are disposed relative to each other such that a synthetic image is projected by the security film when at least a portion of the array of image elements are viewed through at least a portion of the array of focusing elements. The anti-viscid agent is coupled with the array of focusing elements.

Abstract: A method of operating a laundry treating appliance for treating laundry according to a treating cycle of operation. The laundry treating appliance comprises a treating chamber for receiving the laundry that is selectively accessible through a door movable between opened and closed positions. The method comprises determining at the end of a laundry treating cycle whether the door has been opened and subsequently reclosed and reducing humidity in the treating chamber after the determination that the door has been reclosed.

Abstract: A method of operating a laundry treating appliance for treating laundry according to a treating cycle of operation. The laundry treating appliance comprises a treating chamber for receiving the laundry that is selectively accessible through a door movable between opened and closed positions. The method comprises determining at the end of a laundry treating cycle whether the door has been opened and subsequently reclosed and reducing humidity in the treating chamber after the determination that the door has been reclosed.

Abstract: An on-demand transportation management system can collect vehicle fleet utilization data corresponding to human-driven vehicles (HDVs) and autonomous vehicles (AVs) operating within a given region in connection with an on-demand transportation service. The on-demand transportation management system can then establish a set of selection priorities for respective areas of the given region based on the vehicle fleet utilization data, each selection priority indicating whether a respective area of the given region is to favor HDVs or AVs for servicing transport requests.

Abstract: A laundry treating appliance includes a treating chamber and a drying circuit fluidly coupled to the treating chamber and supplying process air. A heating assembly for the laundry treating appliance is in thermal interaction with the supplied process air. The heating assembly includes a housing defining an air inlet and an air outlet, an air flow path extending through the housing from the air inlet to the air outlet, and a heat exchange plate disposed within the housing. A first heating element is positioned within the housing and spaced from a first side of the heat exchange plate. A set of fins can also extend from at least the first side of the heat exchange plate.

Abstract: Systems and methods for autonomous vehicle motion planning are provided. Sensor data describing an environment of an autonomous vehicle and an initial travel path for the autonomous vehicle through the environment can be obtained. A number of trajectories for the autonomous vehicle are generated based on the sensor data and the initial travel path. The trajectories can be evaluated by generating a number of costs for each trajectory. The costs can include a safety cost and a total cost. Each cost is generated by a cost function created in accordance with a number of relational propositions defining desired relationships between the number of costs. A subset of trajectories can be determined from the trajectories based on the safety cost and an optimal trajectory can be determined from the subset of trajectories based on the total cost. The autonomous vehicle can control its motion in accordance with the optimal trajectory.

Abstract: The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a machine-learned yield model. In particular, the machine-learned yield model can be trained or otherwise configured to receive and process feature data descriptive of objects perceived by the autonomous vehicle and/or the surrounding environment and, in response to receipt of the feature data, provide yield decisions for the autonomous vehicle relative to the objects. For example, a yield decision for a first object can describe a yield behavior for the autonomous vehicle relative to the first object (e.g., yield to the first object or do not yield to the first object). Example objects include traffic signals, additional vehicles, or other objects. The motion of the autonomous vehicle can be controlled in accordance with the yield decisions provided by the machine-learned yield model.

Abstract: A method of operating a laundry treating appliance having a tub, a rotatable drum at least partially defining a treating chamber, and a treating chemistry dispenser comprising multiple treating chemistry cups configured to dispense treating chemistry to the treating chamber. The method comprises performing a first wash cycle and dispensing a first dose of treating chemistry from one of the treating chemistry cups, receiving at a controller a user selection of an activation of a performance enhancement selector, and upon activation of the performance enhancement selector, activating a second wash cycle comprising dispensing a second dose of treating chemistry from another of treating chemistry cups.

Abstract: Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a computer-implemented method includes obtaining data associated with an object within a surrounding environment of an autonomous vehicle. The data associated with the object is indicative of a predicted motion trajectory of the object. The method includes determining a vehicle action sequence based at least in part on the predicted motion trajectory of the object. The vehicle action sequence is indicative of a plurality of vehicle actions for the autonomous vehicle at a plurality of respective time steps associated with the predicted motion trajectory. The method includes determining a motion plan for the autonomous vehicle based at least in part on the vehicle action sequence. The method includes causing the autonomous vehicle to initiate motion control in accordance with at least a portion of the motion plan.

Abstract: Generally, the present disclosure is directed to systems and methods for streaming processing within one or more systems of an autonomy computing system. When an update for a particular object or region of interest is received by a given system, the system can control transmission of data associated with the update as well as a determination of other aspects by the given system. For example, the system can determine based on a received update for a particular aspect and a priority classification and/or interaction classification determined for that aspect whether data associated with the update should be transmitted to a subsequent system before waiting for other updates to arrive.

Abstract: A method of operating a laundry treating appliance having a tub, a rotatable drum at least partially defining a treating chamber, and a treating chemistry dispenser comprising multiple treating chemistry cups configured to dispense treating chemistry to the treating chamber. The method comprises performing a first wash cycle and dispensing a first dose of treating chemistry from one of the treating chemistry cups, receiving at a controller a user selection of an activation of a performance enhancement selector, and upon activation of the performance enhancement selector, activating a second wash cycle comprising dispensing a second dose of treating chemistry from another of treating chemistry cups.

Abstract: A laundry treating appliance having a rotatable basket that defines a treating chamber, a tub for mounting the rotatable basket, a drive assembly mounted to the tub for rotating the basket and a drive motor mounted to the tub for driving the drive assembly. The tub has a lower region comprising a central cavity and a second cavity. The drive assembly is nested in the central cavity and the drive motor is nested in the second cavity for reducing the vertical stack of tub and the motor.

Abstract: Generally, the present disclosure is directed to systems and methods for streaming processing within one or more systems of an autonomy computing system. When an update for a particular object or region of interest is received by a given system, the system can control transmission of data associated with the update as well as a determination of other aspects by the given system. For example, the system can determine based on a received update for a particular aspect and a priority classification and/or interaction classification determined for that aspect whether data associated with the update should be transmitted to a subsequent system before waiting for other updates to arrive.

Abstract: Generally, the present disclosure is directed to systems and methods that include or otherwise leverage an iterative solver as part of optimizing a motion plan for an autonomous vehicle (AV). In particular, a scenario generator within a motion planning system can include a warm start generator configured to determine an initial trajectory that respects the dynamics of the autonomous vehicle and that closely tracks a speed profile determined by a constraint solver and one or more nominal paths determined by a route selector. A decision validator can analyze speed profiles and nominal paths to identify potential inconsistencies and validate a decision before optimization and execution. An initial trajectory can be further optimized by an iterative solver to determine an optimized trajectory for execution as a motion plan for the autonomous vehicle.

Abstract: The present disclosure is directed to analyzing motion plans of autonomous vehicles. In particular, the methods, devices, and systems of the present disclosure can: receive data indicating a motion plan, of an autonomous vehicle through an environment, based at least in part on multiple different constraints of the environment; and determine, for each constraint of the multiple different constraints, a measure of an influence of the constraint on the motion plan.

Abstract: Method of determining a laundry load size in a laundry treating appliance comprising a rotatable drum at least partially defining a treating chamber for receiving laundry for treatment in accordance with a treating cycle of operation, an imaging device, and a controller having a processor, the method includes generating an image, detecting markings in the generated image, and determining, by the controller, a load size based thereon.