Abstract: A close-end fuel cell and an anode bipolar plate thereof are provided. The anode bipolar plate includes an airtight conductive frame and a conductive porous substrate disposed within the airtight conductive frame. In the airtight conductive frame, an edge of a first side has a fuel inlet, and an edge of a second side has a fuel outlet. The conductive porous substrate has at least one flow channel, where a first end of the flow channel communicates with the fuel inlet, a second end of the flow channel communicates with the fuel outlet. The flow channel is provided with a blocking part near the fuel inlet to divide the flow channel into two areas.

Abstract: A control method of a driving mechanism is provided, including: the driving mechanism provides a first electrical signal from a control assembly to the driving mechanism to move the movable portion into an initial position relative to the fixed portion, wherein the control assembly includes a control unit and a position sensing unit; the status signal of an inertia sensing unit is read; the control unit sends the status signal to the control unit to calculate a target position; the control unit provides a second electrical signal to the driving assembly according to the target position for driving the driving assembly; a position signal is sent from the position sensing unit to the control unit; the control unit provides a third electric signal to the driving assembly to drive the driving assembly according the position signal.

Abstract: A method for predicting clinical severity of a neurological disorder includes steps of: a) identifying, according to a magnetic resonance imaging (MRI) image of a brain, brain image regions each of which contains a respective portion of diffusion index values of a diffusion index, which results from image processing performed on the MRI image; b) for one of the brain image regions, calculating a characteristic parameter based on the respective portion of the diffusion index values; and c) calculating a severity score that represents the clinical severity of the neurological disorder of the brain based on the characteristic parameter of the one of the brain image regions via a prediction model associated with the neurological disorder.

Abstract: A vehicle control apparatus includes a host vehicle position recognizer, a moving object recognizer, a map database, an influence recognizer configured to recognize an influence of a moving object around the host vehicle traveling along a target path of the host vehicle, and a vehicle controller configured to decelerate the host vehicle to avoid collision with the moving object based on the influence. Map information includes area information regarding a plurality of areas on the map for specifying the moving object that is a target of recognizing the influence. When the host vehicle position satisfies predetermined host vehicle position conditions set in advance for each area, the influence recognizer recognizes the influence of the moving object present in the area where the host vehicle position satisfies the host vehicle position conditions, based on the host vehicle position, the area information, and the recognition result from the moving object recognizer.