Using Blockchain Technology and Sharing Culture to Promote Sustainable Forest Management in Tribal Communities.

Forest protection is crucial to ensuring the balance between human beings and ecology. This study explores the key role played by communities that originally lived in forest-protected areas in implementing the traditional management of forests. The unified management mode previously used by the state power can no longer meet the demands of modern times; hence, multiple types of management systems should be implemented to enable adaption to the original ecology of forest areas. A multimodal management mode should be adopted to restore the original ecology of forest areas. The adoption of this management system can restore a forest to its original state (i.e., the state that existed prior to the entry of state power). The forest has been in a state of ecological balance involving numerous species since ancient times. However, in the modern field of science, the passive restoration of a community's self-governance ability could be unsustainable and unstable. To improve this situation, blockchain technology can first be used to improve the community management of a forest, such that the capabilities of the original local community can be improved; second, tourism promotion benefits both the community and the forest. When a community in a forest develops the tourism industry with the support of blockchain technology, the information and resources of all parties can be widely connected with the larger world, and this considerably increases success rates; finally, the traditional spiritual culture of a community, such as the culture of sharing, should be promoted. In addition to the skillful utilization of technology, culture can improve the traditional forest management ability of tribal communities who live in native forest areas in terms of their personality traits. Overall, we conclude that: against the evolution history of the over one hundred years, the adoption of new technology for forest management is inherently a creative innovation for the tribal community's entrepreneurial development.

Using a Random Forest Model to Study the Impact of Local Government-Led Urbanization on Urban Sustainable Development.

Urbanization has accelerated China's economic growth, but it has also brought many sustainability issues. This paper selected a random forest model to study the impact of local government-led urbanization on urban sustainable development. Urbanization affected urban sustainable development through government revenue expansion, land resources mismatch, and industrial structure adjustment. The results showed that the adjustment of industrial structure has the greatest impact on urban sustainable development, and the importance of the average output of industrial enterprises confirms it. Government revenue expansion and land resources mismatch are more important to the sustainable development of representative urban agglomerations. The goodness of fit of the random forest model is better than the multiple linear regression (MLR) model and the extreme gradient boosting (XGBoost) model. The generalization ability of the model is improved with the optimization of variables. The main contribution of this paper is that we have established a complete information dynamic game model on government revenue expansion, land resource mismatch, industrial structure adjustment, and urban sustainable development. And the random forest model is used to study the relationship between the above variables.

Genetically-modified R-ω-transaminase: purification and self-assembly facilitating interaction with substrate droplets.

OBJECTIVES: An easy-to-operate method of using R-ω-transaminase has been developed by fusing it to an elastin-like polypeptide and forming a complex with D-amino acid oxidase. RESULTS: R-ω-Transaminase (R-ω-TA) was fused to an elastin-like polypeptide (ELP) through genetic engineering of the enzyme. The enzyme was purified through reversible phase transition. For the single-enzyme system, in the reaction media, ELP-R-ω-TA self-assembled and formed enzyme clusters of micrometer size, and the substrate, (R)-1-phenylethylamine, also formed droplets of micrometer size. Intimate contact of the enzyme clusters and the substrate droplets provided a microenvironment of high substrate concentration close to the enzyme, facilitating the diffusion of substrate molecules into the active sites. For the two-enzyme system, ELP-R-ω-TA and ELP-fusion D-amino acid oxidase assembled to form two-enzyme complexes, forming clusters with a size much larger size than that of single enzymes. The efficiency of the combined enzymes for producing the product was 99.6 %. CONCLUSIONS: The two-enzyme complexes significantly improved the catalytic efficiency. Potentially, the two enzymes forming complex clusters can facilitate the immobilization of the two enzymes together through non covalent methods by entrapping in porous supports.