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Nanocellulose is characterised by favourable biocompatibility, degradability, nanostructure effect, high modulus and high tensile strength and has been widely applied in various fields. The current research in the field of new nanocellulose materials mainly focuses on the hydrogel, aerogel and the tissue engineering scaffold. All of these are three-dimensional (3D) porous materials, but conventional manufacturing technology fails to realise precise control. Therefore, the method of preparing structural materials using 3D printing and adopting the nanocellulose as the 3D printing material has been proposed. Then, how to realise 3D printing of nanocellulose is the problem that should be solved.

By adding the photosensitive component polyethyleneglycol diacrylate (PEGDA) in the aqueous dispersion system of nanocellulose, the nanocellulose was endowed with photosensitivity. Then, nanocellulose/PEGDA hydrogels were prepared by the additive manufacturing of nanocellulose through light curing.

The results showed that the nanocellulose/PEGDA hydrogels had a uniform shape and a controllable structure. The nanocellulose supported the scaffold structure in the hydrogels. Prepared with 1.8 per cent nanocellulose through 40 s of light curing, the nanocellulose/PEGDA hydrogels had a maximum compression modulus of 0.91 MPa. The equilibrium swelling ratio of the nanocellulose/PEGDA hydrogel prepared with 1.8 per cent nanocellulose was 13.56, which increased by 44 per cent compared with that of the PEGDA hydrogel without nanocellulose.

The paper proposed a method for rapidly prototyping the nanocellulose with expected properties, which provided a theoretical basis and technological reference for the 3D additive manufacturing of nanocellulose 3D structure materials with a controlled accurate architecture.

This paper intends to construct a new adaptive grey seasonal model (AGSM) to promote the application of the grey forecasting model in quarterly GDP.

Firstly, this paper constructs a new accumulation operation that embodies the new information priority by using a hyperparameter. Then, a new AGSM is constructed by using a new grey action quantity, nonlinear Bernoulli operator, discretization operation, moving average trend elimination method and the proposed new accumulation operation. Subsequently, the marine predators algorithm is used to quickly obtain the hyperparameters used to build the AGSM. Finally, comparative analysis experiments and ablation experiments based on China's quarterly GDP confirm the validity of the proposed model.

AGSM can be degraded to some classical grey prediction models by replacing its own structural parameters. The proposed accumulation operation satisfies the new information priority rule. In the comparative analysis experiments, AGSM shows better prediction performance than other competitive algorithms, and the proposed accumulation operation is also better than the existing accumulation operations. Ablation experiments show that each component in the AGSM is effective in enhancing the predictive performance of the model.

A new AGSM with new information priority accumulation operation is proposed.