Abstract: Systems, methods, and storage media for location information processing are disclosed. An example of a method comprises: obtaining transaction information from user terminals of a plurality of users using a service provided by a service provider, the transaction information comprising a plurality of pieces of location information of the user terminals; clustering, using an algorithm, the plurality of pieces of location information into a plurality of areas; determining a transaction attribute corresponding to each area in the plurality of areas, the transaction attribute comprising a number of users in a corresponding area and a number of transactions of users using the service in the corresponding area; determining, according to information entropy values of the transaction attributes, a dispersity of the service provided by the service provider according to a number of areas in the plurality of areas and a plurality of transaction attributes corresponding to the plurality of areas.

Abstract: An organic light-emitting diode (OLED) display panel and a manufacturing method thereof are provided. the OLED display panel includes: a substrate, an OLED layer and an encapsulating portion. The substrate includes a displaying region, and a non-displaying region located on an outside of the displaying region. The OLED layer is disposed in the displaying region of the substrate. The encapsulating portion is disposed above the OLED layer. The encapsulating portion includes an organic layer and at least one blocking wall surrounding the organic layer. The organic layer is located in a blocking space of the blocking wall.

Abstract: An implementation of the present specification provides a method for training a risk identification model. Because different types of unsupervised machine learning algorithms have different requirements for features, a type of a target unsupervised machine learning algorithm can be determined first, then various types of feature information are extracted from input information, and then target feature information is extracted from the feature information in a way of extracting feature information corresponding to the type of the target unsupervised machine learning algorithm. Because the target feature information adapted to the target unsupervised machine learning algorithm is extracted, a target risk identification model obtained through training by using the target feature information based on the target unsupervised machine learning algorithm has higher identification accuracy and ensures the accuracy of risk identification.

Abstract: A process is provided for upgrading a renewable feedstock. The process includes introducing the renewable feedstock into a fluid catalytic cracking (FCC) reactor unit operating under catalytic cracking conditions and comprising a circulating inventory of an equilibrium catalyst composition; removing a portion of the equilibrium catalyst inventory from the FCC reactor unit while replacing all the equilibrium catalyst removed from the unit with a spent catalyst to obtain a composite circulating catalyst within the FCC reactor unit; and contacting the composite circulating catalyst with the renewable feedstock in the FCC reactor unit under a steady state environment to provide a product stream comprising cracked products.

Abstract: Systems, methods, and storage media for location information processing are disclosed. An example of a method comprises: obtaining transaction information from user terminals of a plurality of users using a service provided by a service provider, the transaction information comprising a plurality of pieces of location information of the user terminals; clustering, using an algorithm, the plurality of pieces of location information into a plurality of areas; determining a transaction attribute corresponding to each area in the plurality of areas, the transaction attribute comprising a number of users in a corresponding area and a number of transactions of users using the service in the corresponding area; determining, according to information entropy values of the transaction attributes, a dispersity of the service provided by the service provider according to a number of areas in the plurality of areas and a plurality of transaction attributes corresponding to the plurality of areas.

Abstract: Disclosed herein is a method for making diesel, gasoline and LPG comprising coprocessing a petroleum-derived feedstock with up to 50 wt. %, relative to the total weight of the feedstocks, of a lipid-containing feedstock in the presence of a catalyst under fluidized catalyst cracking conditions. Also disclosed herein is a method for making a diesel fuel or a combined diesel and gasoline fuel by injecting up to 50 wt. %, relative to the total weight of the feedstocks, of a lipid-containing feedstock to a stripper or a riser quench downstream from a petroleum derived feedstock injection point in a fluid catalytic cracking unit.