Abstract: Compostable seaweed-based thin films, and associated systems and methods are disclosed herein. In some embodiments, an exemplary seaweed-based thin film comprises a seaweed-based composition comprising agar, alginate, carrageenan, semi-refined seaweed, and/or unprocessed seaweed; an agent comprising glycerin, sorbitol, sodium lignosulphonate, potassium lignosulphonate, calcium lignosulphonate, ammonium lignosulphonate, lignosulphonate, citric acid, ascorbic acid, ethylene glycol, polyethylene glycol, polyglyceride fatty acid esters, guar gum, tributyl citrate, and/or propylene glycol; and water. The seaweed-based composition can comprise 50-90 wt % of the seaweed-based thin film, the agent can comprise no more than 40 wt % of the seaweed-based thin film, and the water can comprise 0.1-50 wt % of the seaweed-based thin film.

Abstract: A method and device for accelerating database operation, applied to a database connected with a hardware accelerator is provided, the method includes: when receiving an initial execution plan tree sent by the database that needs to be accelerated, processing the initial execution plan tree and generating a new execution plan tree and a new execution cost based on the basic operation and accelerated resource supported by the hardware accelerator; if the new execution cost of the new execution plan tree is less than the initial execution cost of the initial execution plan tree, distributing the new execution plan tree to the hardware accelerator for execution based on the organization approach and the operation approach of the hardware accelerator; the execution result returned by the hardware accelerator to complete the accelerated operation of the database operation; determining the result data after the hardware accelerator accelerates the database operation based on the execution results returned by the har

Abstract: Compostable seaweed-based compositions, and associated systems and methods are disclosed herein. In some embodiments, the seaweed-based composition comprises (i) a phycocolloid including agar, alginate, carrageenan, and/or unprocessed seaweed, (ii) a polymer comprising thermoplastic starch (TPS), polycaprolactone (PCL), polylactic acid (PLA), polyhydroxyalkanoates (PHA), polyesteramide (PEA), polybutylene adipate terephthalate (PBAT), polybutylene succinate (PBS), and/or polyvinyl alcohol (PVOH), and (iii) an additive, wherein the phycocolloid comprises no more than 90 wt % of the seaweed-based composition, the biopolymer comprises no more than 80 wt % of the seaweed-based composition, and the additive comprises no more than 50 wt % of the seaweed-based composition.

Abstract: A tiltable vehicle is configured to transform between an autonomous mode and a rideable mode by pivoting the handlebars and steering column of the vehicle about a pitch axis. In the autonomous mode, the steering column is folded back toward the chassis and a tiltable chassis of the vehicle is prevented from tilting. In the rideable mode, the steering column is unfolded and the chassis is free to tilt. In some examples, a tiltable vehicle includes features beneficial for vehicle-sharing, such as parking devices or a basket. These features may be included on any suitable vehicle and are not limited to use on transforming vehicles.

Abstract: According to some aspects, techniques are provided for building and deploying a machine learning application that do not require a user to have expert knowledge of machine learning or programming. These techniques may be executed by a system that provides a graphical user interface which allows a user to visually define a workflow for a machine learning application, without requiring the user to be an expert in machine learning. The system may automatically represent the workflow as a specification that may be used to build and deploy a machine learning application. The system may automatically execute the workflow in a series of stages while managing data flow and execution context between the stages. Such an execution process may provide flexibility in execution so that a user can build a complex machine learning application without it being necessary for the user to have detailed knowledge of how execution is managed.

Abstract: Compostable seaweed-based compositions, and associated systems and methods are disclosed herein. In some embodiments, the seaweed-based composition comprises (i) a phycocolloid including agar, alginate, carrageenan, and/or unprocessed seaweed, (ii) a polymer comprising thermoplastic starch (TPS), polycaprolactone (PCL), polylactic acid (PLA), polyhydroxyalkanoates (PHA), polyesteramide (PEA), polybutylene adipate terephthalate (PBAT), polybutylene succinate (PBS), and/or polyvinyl alcohol (PVOH), and (iii) an additive, wherein the phycocolloid comprises no more than 90 wt % of the seaweed-based composition, the biopolymer comprises no more than 80 wt % of the seaweed-based composition, and the additive comprises no more than 50 wt % of the seaweed-based composition.

Abstract: According to some aspects, techniques are provided for building and deploying a machine learning application that do not require a user to have expert knowledge of machine learning or programming. These techniques may be executed by a system that provides a graphical user interface which allows a user to visually define a workflow for a machine learning application, without requiring the user to be an expert in machine learning. The system may automatically represent the workflow as a specification that may be used to build and deploy a machine learning application. The system may automatically execute the workflow in a series of stages while managing data flow and execution context between the stages. Such an execution process may provide flexibility in execution so that a user can build a complex machine learning application without it being necessary for the user to have detailed knowledge of how execution is managed.

Abstract: A vehicle of the present disclosure may include at least one pair of opposing wheels coupled to a tiltable central chassis by a four-bar linkage or the like, such that the wheels are configured to tilt in unison with the central chassis. A steering actuator and/or a tilting actuator may be discretely controllable by an electronic controller of the vehicle. The controller may include processing logic configured to maintain alignment between a median plane of the chassis and a net force vector caused by gravity and any induced centrifugal forces. Various control algorithms may be utilized to steer the vehicle along a desired path, either autonomously or semi-autonomously.

Abstract: A tiltable vehicle has a pair of front wheels coupled to a tiltable chassis by a tilt linkage, such that the pair of front wheels and the chassis are configured to tilt in unison with respect to a roll axis of the chassis. The tilt linkage includes a four-bar linkage having a pair of upper bar segments coupled to the chassis at spaced-apart respective inboard joints. In some examples, the inboard joints of the upper bar segments are each disposed outboard of a central chassis joint of a lower bar of the tilt linkage. An orientation sensor is configured to detect directional information regarding a net force vector applied to the chassis, and a tilt actuator operatively coupled to the chassis and configured to selectively tilt the chassis. A controller is configured to selectively control the tilt actuator based on the directional information from the orientation sensor.

Abstract: According to some aspects, techniques are provided for building and deploying a machine learning application that do not require a user to have expert knowledge of machine learning or programming. These techniques may be executed by a system that provides a graphical user interface which allows a user to visually define a workflow for a machine learning application, without requiring the user to be an expert in machine learning. The system may automatically represent the workflow as a specification that may be used to build and deploy a machine learning application. The system may automatically execute the workflow in a series of stages while managing data flow and execution context between the stages. Such an execution process may provide flexibility in execution so that a user can build a complex machine learning application without it being necessary for the user to have detailed knowledge of how execution is managed.

Abstract: An autonomous tilting three-wheeled vehicle comprises a pair of front wheels coupled to a tiltable chassis by a mechanical linkage, such that the pair of wheels and the chassis are configured to tilt in unison with respect to a roll axis of the chassis. An electronic controller of the autonomous vehicle controls a tilt actuator to selectively tilt the chassis. Optionally, a steering actuator is coupled to the front wheels and controlled by the electronic controller to selectively steer the wheels. A sensor configured to measure orientation-dependent information may be coupled to the chassis by a gimbal configured to compensate for vehicle tilt. In some examples, the autonomous vehicle comprises an autonomous delivery robot.

Abstract: There is provided herein a motion-based evaluation of reaction time that utilizes motion detection hardware of a mobile device to determine auditory and visual stimulated reaction time. In an embodiment, the subject holds a mobile computing device equipped with built-in triaxis accelerometer and gyroscope with both hands at arms length away from the face. A visual or auditory stimulus is then presented on screen via a software application that also records the response time for the individual to initiate a movement of the device. A simple reaction time test could include the movement of the device in any direction that exceeded a threshold of movement beyond what would be expected from static holding. An embodiment of a choice reaction time test would provide for specific directional movements as it related to an instructed stimulus.

Abstract: A tiltable vehicle is configured to transform between an autonomous mode and a rideable mode by pivoting the handlebars and steering column of the vehicle about a pitch axis. In the autonomous mode, the steering column is folded back toward the chassis and a tiltable chassis of the vehicle is prevented from tilting. In the rideable mode, the steering column is unfolded and the chassis is free to tilt. In some examples, a tiltable vehicle includes features beneficial for vehicle-sharing, such as parking devices or a basket. These features may be included on any suitable vehicle and are not limited to use on transforming vehicles.

Abstract: A tiltable vehicle has a pair of front wheels coupled to a tiltable chassis by a tilt linkage, such that the pair of front wheels and the chassis are configured to tilt in unison with respect to a roll axis of the chassis. The tilt linkage includes a four-bar linkage having a pair of upper bar segments coupled to the chassis at spaced-apart respective inboard joints. In some examples, the inboard joints of the upper bar segments are each disposed outboard of a central chassis joint of a lower bar of the tilt linkage. An orientation sensor is configured to detect directional information regarding a net force vector applied to the chassis, and a tilt actuator operatively coupled to the chassis and configured to selectively tilt the chassis. A controller is configured to selectively control the tilt actuator based on the directional information from the orientation sensor.

Abstract: A vehicle of the present disclosure may include at least one pair of opposing wheels coupled to a tiltable central chassis by a four-bar linkage or the like, such that the wheels are configured to tilt in unison with the central chassis. A steering actuator and/or a tilting actuator may be discretely controllable by an electronic controller of the vehicle. The controller may include processing logic configured to maintain alignment between a median plane of the chassis and a net force vector caused by gravity and any induced centrifugal forces. Various control algorithms may be utilized to steer the vehicle along a desired path, either autonomously or semi-autonomously.

Abstract: According to some aspects, techniques are provided for building and deploying a machine learning application that do not require a user to have expert knowledge of machine learning or programming. These techniques may be executed by a system that provides a graphical user interface which allows a user to visually define a workflow for a machine learning application, without requiring the user to be an expert in machine learning. The system may automatically represent the workflow as a specification that may be used to build and deploy a machine learning application. The system may automatically execute the workflow in a series of stages while managing data flow and execution context between the stages. Such an execution process may provide flexibility in execution so that a user can build a complex machine learning application without it being necessary for the user to have detailed knowledge of how execution is managed.

Abstract: According to some aspects, techniques are provided for building and deploying a machine learning application that do not require a user to have expert knowledge of machine learning or programming. These techniques may be executed by a system that provides a graphical user interface which allows a user to visually define a workflow for a machine learning application, without requiring the user to be an expert in machine learning. The system may automatically represent the workflow as a specification that may be used to build and deploy a machine learning application. The system may automatically execute the workflow in a series of stages while managing data flow and execution context between the stages. Such an execution process may provide flexibility in execution so that a user can build a complex machine learning application without it being necessary for the user to have detailed knowledge of how execution is managed.