Abstract: An aluminum borate whisker reinforced and toughened non-metallic matrix composite is provided, which specifically includes a non-metallic material reinforced and toughened with aluminum borate whiskers. The composite exhibits a higher bending strength and fracture toughness and a higher wear resistance. A method for preparing the composite is also provided. The method includes mixing the aluminum borate whiskers and the non-metallic material to form a mixture; and sintering the mixture by a vacuum hot press method, or molding the mixture.

Abstract: Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for payment based on wireless communication and biological features. One of the methods includes determining at least one wireless communications device is within a wireless communication range of a payment collection system. Data specifying at least one account associated with the at least one wireless communications device and data specifying a biometric feature associated with the at least one account is obtained from a payment platform. The payment collection system collects a target biometric feature of a target user. In response to determining that the target biometric feature matches the biometric feature associated with the at least one account, a target account of the target user is determined based on the at least one account, and a deduction operation is performed on the target account.

Abstract: The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

Abstract: The present invention discloses an optimization method for a screen surface dynamic load of a vibrating screen. The method includes the following steps: step 1. selecting design variables, and establishing an experimental matrix; step 2. performing a response curved surface experiment; step 3. establishing two double-objective optimization models and solving the same to obtain two groups of Pareto solution sets, wherein the solution sets respectively represent screening efficiency optimization paths of the vibrating screen under the conditions of a high screen surface dynamic load and a low screen surface dynamic load; and step 4. calculating an optimization space for a screen surface dynamic load under a high screening efficiency. According to the method of the present invention, the screen surface dynamic load can be directly reduced, and the service life of the screen surface and the whole vibrating screen is prolonged.

Abstract: Disclosed herein are methods, systems, and apparatus, including computer programs encoded on computer storage media, for payment based on wireless communication and biological features. One of the methods includes determining at least one wireless communications device is within a wireless communication range of a payment collection system. Data specifying at least one account associated with the at least one wireless communications device and data specifying a biometric feature associated with the at least one account is obtained from a payment platform. The payment collection system collects a target biometric feature of a target user. In response to determining that the target biometric feature matches the biometric feature associated with the at least one account, a target account of the target user is determined based on the at least one account, and a deduction operation is performed on the target account.