Abstract: The present disclosure provides a pixel circuit with pulse width compensation, and the pixel circuit includes a pulse width modulation circuit and a pulse amplitude modulation circuit, and the pulse amplitude modulation circuit is electrically connected to the pulse width modulation circuit. The pulse width modulation circuit includes a P-type pulse width compensation transistor and a first P-type control transistor, and the first P-type control transistor is electrically connected to the P-type pulse width compensation transistor. The pulse amplitude modulation circuit includes a second P-type control transistor, a first capacitor, a P-type driving transistor and a light-emitting element. The second P-type control transistor is electrically connected to the first P-type control transistor. The first capacitor is electrically connected to the second P-type control transistor.

Abstract: An automatic material changing and welding system for stamping materials includes a welding transfer sliding table and a welding platform. The automatic material changing device further includes a feeding system. The feeding system includes a double-head uncoiling machine, an automatic feeding machine and a flattening machine. The automatic material changing device is used for automatic feeding for a stamping machine. The system triggers a material changing signal through a sensor to control and integrate the welding transfer sliding table and the welding platform to act to execute a welding procedure, so that the stamping materials are in welding connection with new and old coiled materials through a welding connection plate to realize continuous production operation of an automated stamping production line.

Abstract: In an embodiment, a system, includes: a first pressurized load port interfaced with a workstation body; a second pressurized load port interfaced with the workstation body; the workstation body maintained at a set pressure level, wherein the workstation body comprises an internal material handling system configured to move a semiconductor workpiece within the workstation body between the first and second pressurized load ports at the set pressure level; a first modular tool interfaced with the first pressurized load port, wherein the first modular tool is configured to process the semiconductor workpiece; and a second modular tool interfaced with the second pressurized load port, wherein the second modular tool is configured to inspect the semiconductor workpiece processed by the first modular tool.

Abstract: The present disclosure provides a scan driving circuit, which includes a pull-up output charging circuit, a pull-down discharge circuit, a pre-charge circuit, an anti-noise start-up circuit and an anti-noise pull-down discharge circuit. The pull-up output charging circuit is electrically connected to an output terminal, and the pull-down discharge circuit is electrically connected to the output terminal. The pre-charge circuit is electrically connected to the pull-up output charging circuit and the pull-down discharge circuit through a driving node. The anti-noise start-up circuit is electrically connected to the pre-charge circuit. The anti-noise pull-down discharge circuit is electrically connected to the anti-noise start-up circuit, and the anti-noise pull-down discharge circuit is electrically connected to the driving node.

Abstract: The present disclosure provides a scan driving circuit, which includes a pull-up output charging circuit, a pull-down discharge circuit, a pre-charge circuit, an anti-noise start-up circuit and an anti-noise pull-down discharge circuit. The pull-up output charging circuit is electrically connected to an output terminal, and the pull-down discharge circuit is electrically connected to the output terminal. The pre-charge circuit is electrically connected to the pull-up output charging circuit and the pull-down discharge circuit through a driving node. The anti-noise start-up circuit is electrically connected to the pre-charge circuit. The anti-noise pull-down discharge circuit is electrically connected to the anti-noise start-up circuit, and the anti-noise pull-down discharge circuit is electrically connected to the driving node.

Abstract: A semiconductor device structure, along with methods of forming such, are described. The semiconductor device structure includes a first dielectric feature extending along a first direction, the first dielectric feature comprising a first dielectric layer having a first sidewall and a second sidewall opposing the first sidewall, a first semiconductor layer disposed adjacent the first sidewall, the first semiconductor layer extending along a second direction perpendicular to the first direction, a second dielectric feature extending along the first direction, the second dielectric feature disposed adjacent the first semiconductor layer, and a first gate electrode layer surrounding at least three surfaces of the first semiconductor layer, and a portion of the first gate electrode layer is exposed to a first air gap.

Abstract: A blood pressure detection device manufactured by a semiconductor process includes a substrate, a microelectromechanical element, a gas-pressure-sensing element, a driving-chip element, an encapsulation layer and a valve layer. The substrate includes inlet apertures. The microelectromechanical element and the gas-pressure-sensing element are stacked and integrally formed on the substrate. The encapsulation layer is encapsulated and positioned on the substrate. A flowing-channel space is formed above the microelectromechanical element and the gas-pressure-sensing element. The encapsulation layer includes an outlet aperture in communication with an airbag. The driving-chip element controls the microelectromechanical element, the gas-pressure-sensing element and valve units to transport gas.

Abstract: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.

Abstract: A method for electrolysis of water and a method for preparing a catalyst for electrolysis of water are provided. The method for electrolysis of water includes using a high entropy alloy as a catalyst. Further, the method for preparing a catalyst for electrolysis of water includes the steps of placing a substrate in an aqueous electrolyte containing a high entropy alloy precursor and performing an electroplating process on the substrate to form a high entropy alloy catalyst on the substrate.

Abstract: A method for electrolysis of water and a method for preparing a catalyst for electrolysis of water are provided. The method for electrolysis of water includes using a high entropy alloy as a catalyst. Further, the method for preparing a catalyst for electrolysis of water includes the steps of placing a substrate in an aqueous electrolyte containing a high entropy alloy precursor and performing an electroplating process on the substrate to form a high entropy alloy catalyst on the substrate.