Abstract: A method of forming a glass sheet comprises: (a) forming a ribbon of glass from molten glass with a pair of forming rollers; (b) reducing horizontal temperature variability of the ribbon of glass to be 10° C. or less across 80 percent of an entire width of the ribbon of glass before the ribbon of glass cools to a glass transition temperature; (c) controlling a cooling rate of the ribbon of glass while the ribbon of glass moves vertically downward within a setting zone such that the ribbon of glass has a first average cooling rate before the ribbon of glass cools to the glass transition temperature and a second average cooling rate after the ribbon of glass cools to the glass transition temperature, the first average cooling rate being less than the second average cooling rate; and (d) separating a glass sheet from the ribbon of glass.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: Disclosed herein are systems and methods for managing exceptions to orders collected by autonomous vehicles. The exemplary systems may be configured to receive an indication of an exception that at least one item for an order cannot be collected with a first autonomous vehicle carrying a container associated with the order and determine a reconfigured path for the first vehicle responsive to receiving the indication of the exception. The reconfigured path may include a stop at a storage location configured to store containers associated with the exception. The systems may be configured to receive an indication that the container was removed from the first vehicle and deposited at the storage location, transmit an instruction to a second autonomous vehicle to collect the at least one item for the order, and receive an indication that the at least one item has been matched with the container deposited at the storage location.

Abstract: A system of maintaining the form of a pocket square comprises an insert, a pocket square sleeve, and a holder. The insert comprises a semi-rigid or rigid material. The pocket square sleeve comprises fabric sewn along a lengthwise seam to form a sleeve and a second seam substantially perpendicular to the lengthwise seam forming a cavity configured to receive the insert. The holder comprises an elongate member and a fastening element, the elongate member configured to be folded to cause engagement of the fastening element. The insert is disposed in the cavity of the pocket square sleeve and the combined insert and pocket square sleeve is disposed in the holder with the fastening element engaged.

Abstract: A processor coupled to memory is configured to receive image data based on an image captured by a camera of a vehicle. The image data is used as a basis of an input to a trained machine learning model trained to predict a three-dimensional trajectory of a machine learning feature. The three-dimensional trajectory of the machine learning feature is provided for automatically controlling the vehicle.

Abstract: Disclosed herein are systems and methods for managing exceptions to orders collected by autonomous vehicles. The exemplary systems may be configured to receive an indication of an exception that at least one item for an order cannot be collected with a first autonomous vehicle carrying a container associated with the order and determine a reconfigured path for the first vehicle responsive to receiving the indication of the exception. The reconfigured path may include a stop at a storage location configured to store containers associated with the exception. The systems may be configured to receive an indication that the container was removed from the first vehicle and deposited at the storage location, transmit an instruction to a second autonomous vehicle to collect the at least one item for the order, and receive an indication that the at least one item has been matched with the container deposited at the storage location.

Abstract: A leading edge structure for providing an aerodynamic surface of an aircraft is disclosed having a skin structure, the skin structure providing an outer aerodynamic surface and an inner surface, both surfaces extending in a chordwise and spanwise direction of the structure, and a plurality of structural members, each structural member being connected to the inner surface of the skin structure and extending in the chordwise direction along the inner surface, wherein the structural members are integrally formed with the inner surface of the skin structure. The disclosure is also related to an aircraft wing, aircraft tailplane, wing box structure, wing or wing structure and an aircraft including the leading edge structure.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: A processor coupled to memory is configured to receive image data based on an image captured by a camera of a vehicle. The image data is used as a basis of an input to a trained machine learning model trained to predict a three-dimensional trajectory of a machine learning feature. The three-dimensional trajectory of the machine learning feature is provided for automatically controlling the vehicle.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: A replacement heart valve device is disclosed. In some embodiments, the device includes a frame coupled to one or more leaflets that are moveable between open and closed configurations. In some embodiments, the frame comprises at least two frame sections that join at a pair of commissural posts. In some embodiments, the device may be geometrically accommodating to adapt to different vasculature shapes and sizes and/or to be able to change size while implanted within a growing patient.

Abstract: A replacement heart valve device is disclosed. In some embodiments, the device includes a frame coupled to one or more leaflets that are moveable between open and closed configurations. In some embodiments, the frame comprises at least two frame sections that join at a pair of commissural posts. In some embodiments, the device may be geometrically accommodating to adapt to different vasculature shapes and sizes and/or to be able to change size while implanted within a growing patient.

Abstract: A replacement heart valve device is disclosed. In some embodiments, the device includes a frame coupled to one or more leaflets that are moveable between open and closed configurations. In some embodiments, the frame comprises at least two frame sections that join at a pair of commissural posts. In some embodiments, the device may be geometrically accommodating to adapt to different vasculature shapes and sizes and/or to be able to change size while implanted within a growing patient.

Abstract: A processor coupled to memory is configured to receive image data based on an image captured by a camera of a vehicle. The image data is used as a basis of an input to a trained machine learning model trained to predict a three-dimensional trajectory of a machine learning feature. The three-dimensional trajectory of the machine learning feature is provided for automatically controlling the vehicle.

Abstract: Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.

Abstract: A surgical fastener having a first part and a second part, each of the first and second parts comprising a clamping bar and a centrally-positioned perpendicular bracing bar extending therefrom, the clamping bar and bracing bar together defining a “T”-shape, wherein the surgical fastener further comprises at least one bracing element connecting the bracing bar of each of the first and second parts.

Abstract: A leading edge structure for providing an aerodynamic surface of an aircraft is disclosed having a skin structure, the skin structure providing an outer aerodynamic surface and an inner surface, both surfaces extending in a chordwise and spanwise direction of the structure, and a plurality of structural members, each structural member being connected to the inner surface of the skin structure and extending in the chordwise direction along the inner surface, wherein the structural members are integrally formed with the inner surface of the skin structure. The disclosure is also related to an aircraft wing, aircraft tailplane, wing box structure, wing or wing structure and an aircraft including the leading edge structure.

Abstract: A system of maintaining the form of a pocket square comprises an insert, a pocket square sleeve, and a holder. The insert comprises a semi-rigid or rigid material. The pocket square sleeve comprises fabric sewn along a lengthwise seam to form a sleeve and a second seam substantially perpendicular to the lengthwise seam forming a cavity configured to receive the insert. The holder comprises an elongate member and a fastening element, the elongate member configured to be folded to cause engagement of the fastening element. The insert is disposed in the cavity of the pocket square sleeve and the combined insert and pocket square sleeve is disposed in the holder with the fastening element engaged.

Abstract: Apparatus for Minimal Invasive Surgery (MIS) comprising a master device, a slave device, a detector for detecting a parameter of, or associated with the slave device, and a shape locking system for locking the shape of the master device in response to a parameter detected by the detector.