Sedimentary microfacies division is the basis of oil and gas exploration research. The traditional sedimentary microfacies division mainly depends on human experience, which is greatly influenced by human factor and is low in efficiency. Although deep learning has its advantage in solving complex nonlinear problems, there is no effective deep learning method to solve sedimentary microfacies division so far. Therefore, this paper proposes a deep learning method based on DMC-BiLSTM for intelligent division of well-logging—sedimentary microfacies. First, the original curve is reconstructed multi-dimensionally by trend decomposition and median filtering, and spatio-temporal correlation clustering features are extracted from the reconstructed matrix by Kmeans. Then, taking reconstructed features, original curve features and clustering features as input, the prediction types of sedimentary microfacies at current depth are obtained based on BiLSTM. Experimental results show that this method can effectively classify sedimentary microfacies with its recognition efficiency reaching 96.84%.

A series of novel sulfonylurea benzothiazoline were designed by splicing active groups and bioisosterism. A solvent-free synthetic route was developed for the sulfonylurea benzothiazoline derivatives via the cyclization and carbamylation. All the compounds were characterized by IR, 1H-NMR, 13C-NMR, HRMS. The biological activity tests indicated the compounds could protect maize against the injury caused by chlorsulfuron to some extent. The molecular docking result showed that the new compound competed with chlorosulfuron to bind with the herbicide target enzyme active site to attain detoxification.

Cadmium (Cd) is a major heavy metal pollutant and a significant cause of abiotic stress in the environment. Organisms have developed various pathways to protect themselves against Cd stress. MYB protein is a large transcription factor family in plants. Many members of the family have been found to regulate developmental processes and stress responses. However, the function and mechanism of MYB116 are far from clear. In a recent study, we found that MYB116 of Chinese cabbage enhances Cd tolerance in yeast. BrMYB116 is transiently inducible by Cd treatment in Chinese cabbage. When expressed in yeast cells, it enhances tolerance against Cd stress and reduces Cd accumulation in the cells. Further analysis shows that BrMYB116 protein enhances Cd tolerance in yeast cells by activating one target gene that encodes the facilitator of iron transport 3 (FIT3). ScFIT3 is activated through specific binding with its promoter. More importantly, the expression of ScFIT3, leads to a substantial reduction of Cd accumulation in both yeast and Chinese cabbage. This finding implies that a similar network may exist in other biological systems, which presents a promising avenue for enhancing Cd tolerance in plants and developing Cd-resistant crops.