Abstract: A motor vehicle having a front end, a pair of opposing front wheel wells rearward of the front end, and an air guide duct having at least one air inlet disposed forward of the front wheel wells and facing the front end of the motor vehicle. The air guide duct also has at least one air outlet opening into at least one of the front wheel wells such that incoming air from the front end of the motor vehicle is guided into at least one of the front wheel wells.

Abstract: A device for closing an opening in a body lumen, the device having a first elongate member with a first lumen, a second elongate member distal the first elongate member, and a needle assembly slidably cooperating with the first elongate member to position a plurality of sutures within the lumen of the first elongate member. The needle assembly includes a needle base and a plurality of needle portions extending from the needle base. Slidable movement of the needle assembly in relation to the first elongate member locates the plurality of sutures selectively mounted to the needle assembly within the first lumen.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to detect malicious behavior in an industrial automation environment. In some examples, a security component monitors an integrated design application and generates feature vectors that represent operations of the integrated design application. The security component supplies the feature vectors to a machine learning engine. The security component processes a machine learning output that indicates when anomalous behavior is detected in the operations of the integrated design application. When anomalous behavior is detected in the operations of the integrated design application, the security component generates and transfers an alert that characterizes the anomalous behavior.

Abstract: A system and method for verifying a cryptographic access code is provided. If a set of cryptographic access components are quantum-aware, the system can obtain a post-quantum encryption and/or decryption algorithm from a context-specific non-critical extension in a private OID namespace, such as SABER, Kyber, Enhanced McEliece, or RLCE. If the set of cryptographic access components are quantum-aware, the system can obtain a post-quantum signature or verification algorithm from the private OID namespace. The system can validate a root of trust specified in a TAL record; confirm that a respective certificate, CRL, or TAL is specified in at least one Manifest record; confirm that a hash of the respective certificate, CRL, or TAL matches a recorded hash in a respective Manifest listing the respective certificate, CRL, or TAL; and confirm that a respective CRL or Manifest is fresh.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to detect malicious behavior in an industrial automation environment. In some examples, a security component generates feature vectors that represents inputs and outputs to a data pipeline and supplies the feature vectors to a machine learning engine. The security component processes a machine learning output that indicates when anomalous behavior is detected in the operations of the data pipeline. When anomalous behavior is detected in the operations of the data pipeline, the security component generates and transfers an alert that characterizes the anomalous behavior.

Abstract: Embodiments of the present disclosure include a system for harvesting salt, and other valued material, and generating distilled water from at least one of a produced water and salt water. The system can include a direct steam generator (DSG) configured to generate saturated steam and combustion exhaust constituents. The system can include a separation system operating after the DSG, configured to separate salt from the saturated steam and combustion exhaust constituents in at least one of brine form and solid form. The system can include an energy recovery system that includes an expansion turbine configured to recover energy from the steam and exhaust constituents.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to detect malicious behavior in an industrial automation environment. In some examples, a security component generates feature vectors that represent operations of a Programmable Logic Controller (PLC) and supplies the feature vectors to a machine learning engine. The security component processes a machine learning output that indicates when anomalous behavior is detected in the operations of the PLC. When anomalous behavior is detected in the operations of the PLC, the security component generates and transfers an alert that characterizes the anomalous behavior.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to surface machine learning systems in a design application of an industrial automation environment. In some examples, a design component generates a control program configured for implementation by a Programmable Logic Controller (PLC). The design component receives a user input that selects a program tag that represents a target variable in an industrial automation process. In response to the user selection, the design component identifies one or more machine learning models associated with the target variable and displays the one or more machine learning models. The design component receives a user input that selects one of the one or more machine learning models and responsively integrates another program tag that represents the selected machine learning model into the control program.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to train machine learning systems based on user operations in an industrial automation environment. In some examples, a Human Machine Interface (HMI) component displays a machine learning output indicating a training state of a machine learning model on a user interface and user feedback regarding the training state. A machine learning interface component weights feature vectors based on the user feedback and supplies the weighted feature vectors to the machine learning model. The machine learning interface component receives another machine learning output that indicates an updated training state for the model.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to visualize machine learning model status in an industrial automation environment. In some examples, a machine learning component receives process inputs associated with industrial devices in the industrial automated environment. The machine learning component processes the inputs to generate machine learning outputs and transfers the machine learning outputs to influence one or more functions of the industrial devices. The machine learning component reports operational data characterizing the machine learning outputs. A Human Machine Interface (HMI) component displays a visualization of the machine learning component and receives the operational data from the machine learning component.

Abstract: A device for closing an opening in a body lumen, the device having a first elongate member with a first lumen, a second elongate member distal the first elongate member, and a needle assembly slidably cooperating with the first elongate member to position a plurality of sutures within the lumen of the first elongate member. The needle assembly includes a needle base and a plurality of needle portions extending from the needle base. Slidable movement of the needle assembly in relation to the first elongate member locates the plurality of sutures selectively mounted to the needle assembly within the first lumen.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to train machine learning systems to perform autonomous control in an industrial automation environment. In some examples, a data aggregation component receives operational data from Original Equipment Manufacturer (OEM) devices, identifies a device type for the operational data, and transfers the operational data for the device type to a machine learning interface component. The operational data characterizes the operations of the OEM devices. The interface component receives the operational data for the device type and generates feature vectors based on the operational data configured for ingestion by a machine learning model. The interface component transfers the feature vectors to a machine learning model.

Abstract: Modulated light therapy devices for treatment of dermatological disorders of the scalp are provided. An exemplary device includes a flexible printed circuit board (FPCB) supporting at least one light emitting device having an emitter height. The FPCB includes multiple interconnected panels and bending regions defined in and between at least some of the interconnected panels as to allow the FPCB to be configured in a concave shape to cover at least a portion of a cranial vertex of the patient. At least one light-transmissive layer proximate to the FPCB is configured to transmit (e.g., incoherent) light emissions generated by at least one light emitting device. At least one standoff is configured to be arranged between the FPCB and the scalp of the patient, wherein the at least one standoff includes a standoff height that exceeds the emitter height.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to surface data pipelines in an industrial automation environment. In some examples, a design component generates a control program configured for implementation by a programmable logic controller to control an industrial process. The design component adds program tags to the control program and implements the control program through the programmable logic controller. The design component establishes data pipelines that correspond to the program tags in the control program between data sources associated with the program tags and a machine learning system that consumes process data generated by the data sources. A pipeline management component generates a pipeline suggestion that indicates individual ones of the data pipelines and their corresponding program tags.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods to optimize a target variable in an industrial automation environment. In some examples, a design application generates a control program configured and selects a program tag that represents a target variable in an industrial process. A processing application identifies a set of available program tags that represent independent variables in the industrial process and determines correlations between ones of the independent variables and the target variable. The processing application selects available program tags that represent independent variables correlated with the target variable and generates a recommendation that indicates the selected available program tags. The design application modifies the control program using the selected available program tags to optimize the target variable.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods for training a machine learning model for implementation in the environment. In some embodiments, an application receives a data set that comprises a control program configured for implementation by a Programmable Logic Controller (PLC). The application processes the data set and calculates derivative values based on the data set. The design application identifies types for individual ones of the feature vectors and ranks the feature vectors based on their types. The design application weights the feature vectors based on their ranks. The design application generates feature vectors that comprise the derivative values and supplies the weighted feature vectors to the machine learning model for training. The application receives a machine learning training output generated by processing the weighted feature vectors.

Abstract: Various embodiments of the present technology generally relate to industrial automation environments. More specifically, embodiments include systems and methods for applying machine learning techniques to industrial control code to detect errors, perform optimizations, and generate predictions. In some embodiments, a design application in an industrial automation environment generates a functional block diagram configured for implementation by a programmable logic controller. The design application generates feature vectors that represent the functional block diagram configured for ingestion by a machine learning model. The design application supplies the feature vectors to the machine learning model. The design application receives a machine learning output that comprises the recommendation feedback generated by the machine learning model and responsively modifies the functional block diagram based on the recommendation feedback.

Abstract: Modulated light therapy devices for treatment of dermatological disorders of the scalp are provided. An exemplary device includes a flexible printed circuit board (FPCB) supporting at least one light emitting device having an emitter height. The FPCB includes multiple interconnected panels and bending regions defined in and between at least some of the interconnected panels as to allow the FPCB to be configured in a concave shape to cover at least a portion of a cranial vertex of the patient. At least one light-transmissive layer proximate to the FPCB is configured to transmit (e.g., incoherent) light emissions generated by at least one light emitting device. At least one standoff is configured to be arranged between the FPCB and the scalp of the patient, wherein the at least one standoff includes a standoff height that exceeds the emitter height.

Abstract: The present disclosure describes devices, systems, and methods for intravascularly delivering an implantable device to a targeted anatomical site such as the mitral annulus. A delivery system includes a delivery member coupled to a handle assembly and extending distally from the handle assembly. A delivery catheter is concentrically positioned within an outer member and configured to advance the intravascular device relative to the outer member. The delivery catheter includes a distal can structure configured to house at least a portion of the intravascular device in a compressed, pre-deployed position.

Abstract: A method of closing a patent foramen ovale (PFO) including a septum primum and septum secundum is implemented using a suture device including an operational shaft housing an anchor assembly, a needle assembly, and a suture. The method includes advancing an end of the operational shaft to a proximal side of the PFO, positioning a distal portion of the end of the operational shaft on a distal side of the PFO, and actuating the anchor assembly to deploy the anchor assembly on the distal side of the PFO. The method also includes actuating the needle assembly on the proximal side of the PFO to deploy the needle assembly through the PFO and the anchor assembly, thereby deploying the suture through the PFO. The method further includes retracting the anchor assembly into the operational shaft, and withdrawing the distal portion of the operational shaft from the PFO, leaving the deployed suture.