Abstract: This application provides a data processing method. The method is applied to a server, the server includes a first container and an Android driver (240), and a first service manager is deployed in the first container. Each container is allocated its respective private memory (2412, 2422, and 2432) and private service linked list (2411, 2421, and 2431), so as to avoid a problem in a conventional technology of data inconsistency and affected service processing caused by sharing of same memory by a plurality of containers.

Abstract: A method for measuring disaster resilience of urban public services includes the following steps: constructing a residence-service-transportation space network under normal conditions; removing, through disaster simulation, failed road segments and function nodes to construct a damaged residence-service-transportation space network; calculating a per capita accessible public service of each residential node to represent network performance; calculating a change rate of the per capita accessible public service level before and after the disaster; and drawing a relation curve between the change rate and the disaster intensity to measure the disaster resilience of the urban public services.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Disclosed by the present application is a method for producing methyl acetate by means of the carbonylation of dimethyl ether. The method comprises: passing dimethyl ether and a feed gas comprising carbon monoxide through a reactor loaded with a solid acid catalyst for reaction so as to produce methyl acetate, the molar ratio of carbon monoxide to dimethyl ether being 0.05:1-0.5:1. The described method has the advantages of a low molar ratio of carbon monoxide to dimethyl ether, a high conversion rate of carbon monoxide, a small gas circulation amount, low operation costs and so on.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: A method for directly producing methyl acetate and/or acetic acid from syngas, carried out in at least two reaction zones, including: feeding a raw material containing syngas into a first reaction zone to contact and react with a metal catalyst; allowing an obtained effluent to enter a second reaction zone directly or after the addition of carbon monoxide so as to contact and react with a solid acid catalyst; separating the obtained effluent to obtain product of acetate and/or acetic acid, and optionally returning a residual part to enter the first reaction zone and/or the second reaction zone to recycle the reaction. By the method above, the product selectivity of the product of methyl acetate or acetic acid is greater than 93%, and the quantity of methyl acetate and acetic acid may be adjusted according to processing.

Abstract: Provided are a molecular sieve catalyst, a preparation method therefor, an application thereof. The molecular sieve catalyst contains a modified Na-MOR molecular sieve, and the modification comprises: organic ammonium salt exchange, dealumination treatment, and ammonium ion exchange. The catalyst obtained by the method is used in dimethyl ether for one-step production of methyl acetate. The catalyst has high activity and stable performance, and the needs of industrial production can be satisfied.

Abstract: Provided is a method for directly preparing dimethyl ether by synthesis gas, the method comprises: the synthesis gas is passed through a reaction zone carrying a catalyst, and reacted under the reaction conditions sufficient to convert at least a portion of the raw materials to obtain the reaction effluent comprising dimethyl ether; and the dimethyl ether is separated from the reaction effluent, wherein the catalyst is zinc aluminum spinel oxide. In the present invention, only one zinc aluminum spinel oxide catalyst is used, which can make the synthesis gas to highly selectively form dimethyl ether, the catalyst has good stability and can be regenerated. The method of the present invention realizes the production of dimethyl ether in one step by the synthesis gas, and reduces the large energy consumption problem caused by step-by-step production.

Abstract: A method for directly preparing p-xylene from synthetic gas and aromatic hydrocarbon. The method includes contacting the feedstock containing synthetic gas and aromatic hydrocarbon excluding p-xylene with the catalyst in the reaction zone under reaction conditions sufficient to convert at least part of the feedstock to obtain a reaction effluent containing p-xylene; and separating p-xylene from the reaction effluent, where the catalyst includes a highly dispersed metal oxide material confined by an inert carrier, an acidic molecular sieve, and optionally at least one of graphite powder and dispersant, where in the highly dispersed metal oxide material confined by the inert carrier, the inert carrier is at least one of silicon oxide and alumina, and the content of the metal oxide in terms of metal is less than or equal to 10% by mass calculated based on the weight of the highly dispersed metal oxide material confined by the inert carrier.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.

Abstract: Provided is a method for directly preparing dimethyl ether by synthesis gas, the method comprises: the synthesis gas is passed through a reaction zone carrying a catalyst, and reacted under the reaction conditions sufficient to convert at least a portion of the raw materials to obtain the reaction effluent comprising dimethyl ether; and the dimethyl ether is separated from the reaction effluent, wherein the catalyst is zinc aluminum spinel oxide. In the present invention, only one zinc aluminum spinel oxide catalyst is used, which can make the synthesis gas to highly selectively form dimethyl ether, the catalyst has good stability and can be regenerated. The method of the present invention realizes the production of dimethyl ether in one step by the synthesis gas, and reduces the large energy consumption problem caused by step-by-step production.

Abstract: A catalyst for synthesizing aromatic hydrocarbons, a preparation method thereof and a method for synthesizing aromatic hydrocarbons by using the catalyst. The catalyst comprises acidic molecular sieve particles and zinc-aluminum composite oxide particles. The catalyst has relatively high selectivity to aromatic hydrocarbons, particularly BTX, stable performance, and a long single-pass life.