Shandong Computer Science Center (National Supercomputer Center in Jinan)

Shandong University

China University of Petroleum

Yanling Zhao

Wei Zhang

Lu Wang

Huiling Shi

Meng Sun

Xinchang Zhang

Zhaomin Li

Teng Lu

Yajie Xu

Zhengxiao Xu

Tong Zhang

Jianwei Zhang

Qinyuan Ma

Fanyu Meng

Zhixin Ma

Xiuzhen Gao

Shaoju Tang

Faqiang Dang

Yiran He

Yanmiao Yin

The present disclosure relates to the technical field of biotechnology, in particular to carbonyl reductase mutant and its application. Specifically, the present disclosure provides a carbonyl reductase mutant for catalyzing the preparation of (R)-8-chloro-6-hydroxyoctanoic acid ethyl ester from 8-chloro-6-oxooctanoic acid ethyl ester. The mutant protein is a non natural protein and undergoes mutations in three core amino acids related to enzyme catalytic activity in the initial carbonyl reductase. The advantageous effect of the present disclosure is that the carbonyl reductase mutant provided by the present disclosure has the characteristic of efficiently catalyzing the preparation of the precursor substance (R)-8-chloro-6-hydroxyoctanoic acid from 8-chloro-6-oxooctanoic acid ethyl ester, and can efficiently catalyze the oxidation-reduction reaction of 8-chloro-6-oxooctanoic acid, with a product space-time yield of 99.9 g·L−1·h−1 or more.

Carbonyl reductase mutant and its application

The resource allocation method and apparatus are based on edge computing. The method includes: decomposing all application systems in a server into a plurality of meta-service units according to the coupling degree between different service modules in the application systems, and obtaining the quality of experience (QoE) index parameter value of each meta-service unit; clustering the plurality of meta-service units by using a clustering algorithm based on the QoE index parameter value of each meta-service unit; and allocating resources to each cluster according to the QoE index parameter values of all meta-service units in each cluster, so that all meta-service units in each cluster share the allocated resources. According to the invention, the resource allocation is more reasonable, the QoE value of a user is increased, and the resource use is more effective.

Resource allocation method and apparatus based on edge computing

The data caching method and a storage medium includes acquiring, by receiving the request of caching service data sent by the UE, the network status data between an SBS corresponding to UE and the UE, the network status data between an MBS corresponding to the SBS and the UE, and the network status data between the UE and a data source of the service data. According to the types of the three pieces of network status data and the service data, three corresponding QoE values are acquired, and whether the cache is configured for the UE is determined according to the three QoE values. The quantification of the three QoE values is realized, and whether the cache is configured for the UE is determined according to the quantized QoE values, thereby achieving the effect of improving the quality of user experience.

Data caching method and storage medium

The invention relates to the recovery of heavy oil reservoirs, and more particularly to a supported catalyst-assisted microwave method for exploiting a heavy oil reservoir. The method includes: (1) injecting a slug of a supported catalyst fluid into the heavy oil reservoir; (2) placing a microwave generator in the heavy oil reservoir to perform volumetric heating on an oil layer containing the supported catalyst fluid; and (3) turning off the microwave generator and injecting water into the heavy oil reservoir for subsequent displacement, where a water injection rate is 3 m/d or less.

Supported catalyst-assisted microwave method for exploiting heavy oil reservoir

Growing community of inventors

Shandong, China

Yanling Zhao