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The acceleration of digital transformation has made data a core element driving technological innovation and economic growth. However, the widespread phenomenon of data island severely hinders data circulation and collaboration across different fields and organizations, making it difficult for data supply to meet the diverse needs of users, thus creating a dilemma in matching data supply and demand. Serving as the core link in the federated ecology and an important window for external empowerment, federated services provide an innovative solution for data circulation and utilization under the principle of distributed data co-governance, thereby enabling the intelligent matching of supply and demand. Firstly, this paper delves into the pivotal role of federated services within the federated ecology, and examines the relationship between federated services and federated ecology's key components. Secondly, it presents a five-layer basic framework of federated services and discusses its core advantages. On this basis, the paper proposes the key supporting technologies for federated services, including blockchain and decentralized autonomous organizations and operations, large language models and scenario engineering, distributed computing and edge computing, as well as encryption technology and privacy computing. Finally, taking the supply-demand matching problem of data and scenarios as a case study, the paper illustrates how federated services achieve intelligent matching of demand and supply. The federated services proposed in this paper holds significant implications for constructing a smart service paradigm based on distributed data co-governance.

N80 steel and 3Cr13 steel used as tubing and hydraulic anchors are inevitably coupled in the CO2 flood oil well, which is prone to galvanic corrosion. Hence, the corrosion rate test and galvanic corrosion test of N80 steel and 3Cr13 steel under CO2 environment were carried out, for clarifying the galvanic corrosion laws of the two steels under the action of various factors including CO2 content, temperature, pressure and salinity. Results showed that the galvanic corrosion occurred at the two steels in CO2 flooding oil wells. 3Cr13 steel was the cathode, which was not affected by galvanic corrosion. In contrast, N80 steel was the anode, and its galvanic corrosion rate increased, which exhibited the same trend as the conventional corrosion, namely increasing with the increase of CO2 content, temperature, pressure and salinity. In addition, the galvanic corrosion sensitivity factor decreased with the increase of CO2 content and pressure. When the CO2 content reached 20%, the galvanic corrosion sensitivity factor was negative, which decreased first and then increased with the increase of temperature, and increased with the increase of salinity. Besides, the maximum galvanic corrosion rate was 69% higher than conventional corrosion rate.

In recent years, deep learning has made a breakthrough in the field of speech recognition, and pushes forward the wide application of speech recognition technology in people's daily lives. Further optimization of the speech recognition model needs to be supported by a larger scale calibrated data. However, the scale of the current open source audio data set is still too small, and corpus is mostly written language of news-based long texts. This paper, by talking about the popular speech recognition applications like human-computer interaction and intelligent customer service, builds and opens the largest ever Chinese Mandarin speech corpus DTZH1505 through crowdsourcing. Data set records natural speech of 6 408 speakers from 8 major Chinese dialect regions and 33 provinces, up to 1 505 hours and on various scenes like social networking, human-computer interaction, intelligent customer service and on-board commands. It can be widely used in the researches of corpus linguistics, conversation analysis, speech recognition, as well as speaker recognition. This paper implements a series benchmark speech recognition experiments, and the results show that: compared to the same scale Chinese speech corpus aishell2, the speech recognition model based on this data set has better performance. [ABSTRACT FROM AUTHOR]