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Nuclear energy plays an important role in global energy supply, especially as a key low-carbon source of power. However, safe operation is very critical in nuclear power plants (NPPs). Given the significant impact of human-caused errors on three serious nuclear accidents in history, artificial intelligence (AI) has increasingly been used in assisting operators with regard to making various decisions. In particular, data-driven AI algorithms have been used to identify the presence of accidents and their root causes. However, there is a lack of an open NPP accident dataset for measuring the performance of various algorithms, which is very challenging. This paper presents a first-of-its-kind open dataset created using PCTRAN, a pre-developed and widely used simulator for NPPs. The dataset, namely nuclear power plant accident data (NPPAD), basically covers the common types of accidents in typical pressurised water reactor NPPs, and it contains time-series data on the status or actions of various subsystems, accident types, and severity information. Moreover, the dataset incorporates other simulation data (e.g., radionuclide data) for conducting research beyond accident diagnosis. Measurement(s) nuclear power plant accident data Technology Type(s) nuclear power plant similulation Factor Type(s) accident [ABSTRACT FROM AUTHOR]

Displaying a protein on the surface of cells has been provided a very successful strategy to function research of exogenous proteins. Based on the membrane fusion characteristic of Autographa californica multiple nucleopolyhedrovirus envelope protein GP64, we amplified and cloned N-terminal signal peptide and C-terminal transmembrane domain as well as cytoplasmic tail domain of gp64 gene into vector pIZ/V5-His with multi-cloning sites to construct the cell surface expression vector pIZ/V5-gp64. To verify that the vector can be used to express proteins on the membrane of insect cells, a recombinant plasmid pIZ/V5-gp64-GFP was constructed by introducing the PCR amplified green fluorescent protein (GFP) gene and transfected into insect cell lines Sf9 and H5. The transected cells were screened with zeocin and cell cloning. PCR verification results showed that the GFP gene was successfully integrated into these cells. Green fluorescence in Sf9-GFP and H5-GFP cells was observed by using confocal laser scanning microscopy and immunofluorescence detection indicated that GFP protein was located on the cell membrane. Western blot results showed that a fusion protein GP64-GFP of about 40 kDa was expressed on the membrane of Sf9-GFP and H5-GFP cells. The expression system constructed in this paper can be used for localization and continuous expression of exogenous proteins on insect cell membrane. [ABSTRACT FROM AUTHOR]