Abstract: A control system for controlling operation of a drive motor includes an input device for providing a command signal that is indicative of a desired speed and direction of rotation of the drive motor. A sensor is associated with the drive motor and adapted to provide a sensor signal indicative of current rotational speed of the drive motor. A controller receives the command signal, and determine whether the command signal is indicative of a desired zero speed to be associated with the drive motor. The controller also receives the sensor signal, and determine whether the current rotational speed of the drive motor is within a pre-defined range of difference from the desired zero speed. The controller then generates a de-rated torque command signal having a reduced gain factor, and reduce the current rotational speed of the drive motor based on the de-rated torque command signal.

Abstract: Compounds of Formula I, pharmaceutically acceptable salts thereof, tautomers thereof, pharmaceutically acceptable salts of the tautomers, or mixtures thereof are agonists of the APJ Receptor and may have use in treating cardiovascular and other conditions. Compounds of Formula (I) have the following structure: where the definitions of the variables are provided herein.

Abstract: A work machine with a mechanical brake touch-up system includes a power source that provides power to a rotational element. The work machine includes a brake that is configured with a piston to selectively engage a frictional element rotationally coupled to the rotational element, a position sensor for generating a position signal of the piston, and a control valve configured to supply hydraulic pressure to the piston to selectively apply a retarding torque to the frictional element, a speed sensor for generating a rotational speed signal. The work machine includes a touch-up controller which is configured to detect a retarding condition of the work machine based on the speed signal, and, upon detection of a retarding condition, control the position of the piston to a touch-up position between an engaged and retracted position.

Abstract: A bit cell driving mechanism is disclosed. The mechanism includes a bit cell which includes a first magnetic tunnel junction (MTJ) cell, including a pinned layer, a non-magnetic layer, a free layer having two magnetic regions separated by a laterally moveable domain wall, and a spin-hall metal layer configured to receive an electrical current therethrough which causes the DW to move laterally. The mechanism also includes a second MTJ cell coupled to the first MTJ cell as well as an interconnect driver configured to provide electrical current to the first MTJ cell during a write operation.

Abstract: A calculation circuit for calculating a transform of an input sequence may include a plurality of butterfly computation circuits configured to perform a plurality of butterfly computations and to produce a plurality of outputs during each of a plurality of computation stages, a wired routing network configured to route a first plurality of outputs of the plurality of butterfly computation circuits from a first computation stage of the plurality of computation stages as input to the plurality of butterfly computation circuits during a second computation stage of the plurality of computation stages according to a reconfigurable routing configuration, and routing control circuitry configured to modify the reconfigurable routing configuration for a third computation stage of the plurality of computation stages.

Abstract: A system includes a camera configured to generate two-dimensional (2D) image or video data of an area of a route ahead of a vehicle moving along the route, wherein wayside equipment is disposed alongside the route in the 2D image or video data. The system also includes one or more processors configured to determine a distance between reference markings in the route along a direction that is transverse to a direction of travel of the vehicle along the route. The one or more processors also are configured to determine a separation distance between the camera and the wayside equipment based on the distance between the reference markings in the route.

Abstract: Containers for transporting plants are provided that can include a base having a base recess for receiving a plant and a growing medium or soil, a lid that can attach to the base such that the lid can extend over and enclose the plant within the container, a cover for holding the plant within the base recess that can be mounted within a base opening into the base recess and abutting against the growing medium or soil, at least one light source mounted to an upper surface of the cover, and a tamper-resistant attachment mechanism for attaching the lid and the base together. Methods for enclosing and transporting plants within containers are also provided.

Abstract: Compounds of Formula I and Formula II, pharmaceutically acceptable salt thereof, stereoisomers of any of the foregoing, or mixtures thereof are agonists of the APJ Receptor and may have use in treating cardiovascular and other conditions. Compounds of Formula I and Formula II have the structures where the definitions of the variables are provided herein.

Abstract: Among other things, data is received from a sensor oriented to monitor ground transportation entities at or near an intersection of a transportation network, and a machine learning model predicts behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. A wireless communication device sends a warning about the dangerous situation to one of the ground transportation entities.

Abstract: A propulsion control system provides different levels of jerk as a function of operator inputs and actual measured operational parameters in a machine. The system includes a power source, a continuously variable transmission (CVT) coupled to an output of the power source, a plurality of input/output devices, a plurality of sensors configured to generate signals indicative of operational parameters of the machine, and a controller communicatively coupled with the power source, the CVT, the input/output devices, and the sensors. The controller includes a database stored in a memory with a plurality of jerk values mapped to different operations of the machine selected from at least one of activation of a brake by an operator for an aggressive stop, a directional shift request from an operator to select one of forward, reverse, or neutral, and a set of operating conditions of the machine indicative of a blade load shedding mode.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: A memory cell comprises channel material, insulative charge-passage material, programmable material, a control gate, and charge-blocking material between the programmable material and the control gate. The charge-blocking material comprises a non-ferroelectric insulator material and a ferroelectric insulator material comprising hafnium, zirconium, and oxygen. Other embodiments are disclosed.

Abstract: Compounds of Formula I and Formula II, pharmaceutically acceptable salt thereof, stereoisomers of any of the foregoing, I or mixtures thereof are agonists of the APJ Receptor and may have use in treating cardiovascular and other conditions. Compounds of Formula I and Formula II have the structures where the definitions of the variables are provided herein.

Abstract: Compounds of Formula I and Formula II, pharmaceutically acceptable salt thereof, stereoisomers of any of the foregoing, or mixtures thereof are agonists of the APJ Receptor and may have use in treating cardiovascular and other conditions. Compounds of Formula I and Formula II have the following structures: (I), (II) where the definitions of the variables are provided herein.

Abstract: Among other things, data is received from a sensor oriented to monitor ground transportation entities at or near an intersection of a transportation network, and a machine learning model predicts behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection. Current motion data is applied to the machine learning model to predict imminent behaviors of the ground transportation entities. An imminent dangerous situation for one or more of the ground transportation entities at or near the intersection is inferred from the predicted imminent behaviors. A wireless communication device sends a warning about the dangerous situation to one of the ground transportation entities.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: Among other things, equipment is located at an intersection of a transportation network. The equipment includes an input to receive data from a sensor oriented to monitor ground transportation entities at or near the intersection. A wireless communication device sends to a device of one of the ground transportation entities, a warning about a dangerous situation at or near the intersection, there is a processor and a storage for instructions executable by the processor to perform actions including the following. A machine learning model is stored that can predict behavior of ground transportation entities at or near the intersection at a current time. The machine learning model is based on training data about previous motion and related behavior of ground transportation entities at or near the intersection.

Abstract: An imaging system includes a digital camera configured to be disposed in a locomotive system that includes a locomotive coupled to a rail vehicle. The camera generates image data within a field of view that includes a cab of the locomotive system and a portion of a route being traveled on and/or wayside devices disposed along the route. The cab includes a space where an operator of the vehicle is located. The system also can include one or more analysis processors that examine the image data generated by the camera to identify route damage, a deteriorating condition of the route, and/or a condition of the wayside devices. The condition of the wayside devices can include damage to the wayside devices, a missing wayside device, deterioration of the wayside devices, or a change in terrain.