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The challenge of water level control in steam generators, particularly at low power levels, has always been a critical aspect of nuclear power plant operation. To address this issue, this paper introduces an IHA controller. This controller employs a CPI controller as the primary controller for direct water level control, coupled with an agent-based controller optimized through a DRL algorithm. The agent dynamically optimizes the parameters of the CPI controller in real-time based on the system’s state, resulting in improved control performance. Firstly, a new observer information is obtained to get the accurate state of the system, and a new reward function is constructed to evaluate the status of the system and guide the agent’s learning process. Secondly, a deep ResNet with good generalization performance is used as the approximator of action value function and policy function. Then, the DDPG algorithm is used to train the agent-based controller, and an advanced controller with good performance is obtained after training. Finally, the popular UTSG model is used to verify the effectiveness of the algorithm. The results demonstrate that the proposed method achieves rise times of 73.9 s, 13.6 s, and 16.4 s at low, medium, and high power levels, respectively. Particularly, at low power levels, the IHA controller can restore the water level to its normal state within 200 s. These performances surpass those of the comparative methods, indicating that the proposed method excels not only in water level tracking but also in anti-interference capabilities. In essence, the IHA controller can autonomously learn the control strategy and reduce its reliance on the expert system, achieving true autonomous control and delivering excellent control performance.

Metamifop (MET) is a widely used herbicide. It is likely for it to enter water environment when utilized, thus potential impacts may be produced on aquatic animals. Little information is available about its effects on the endocrine system of fish to date. In the current study, female rice field eels (Monopterus albus) were exposed to different MET concentrations (0, 0.2, 0.4, 0.6, 0.8 mg L −1) for 96 h to examine the effect of MET on the hypothalamic-pituitary-gonadal (HPG) axis and sexual reversal. The results showed that high concentrations of MET exposure increased vitellogenin (VTG) levels in liver and plasma, but plasma sex hormone levels were not affected by MET exposure. MET exposure increased the expression of CYP19A1b and CYP17 that regulate sex hormone production in the brain, but the expression of genes (CYP19A1a, CYP17, FSHR, LHCGR, hsd11b2, 3β-HSD) associated with sex hormone secretion in the ovary and the estrogen receptor genes (esr1, esr2a, esr2b) in the liver were all suppressed. In addition, the expression of sex-related gene (Dmrt1) was suppressed. This study revealed for the first time that MET has estrogen-like effects and has a strong interference with the expression of HPG axis genes. MET did not show the ability to promote the sexual reversal in M. albus, on the contrary, the genes expression showed that the occurrence of male pathway was inhibited.

Polyploidy, or whole-genome duplication (WGD), often induces dramatic changes in gene expression due to “transcriptome shock. ” However, questions remain about how allopolyploidy (the merging of multiple nuclear genomes in the same nucleus) affects gene expression within and across multiple tissues and developmental stages during the initial foundation of allopolyploid plants. Here, we systematically investigated the immediate effect of allopolyploidy on gene expression variation in an artificial allopolyploidy system consisting of a constructed allotetraploid wheat (AADD genome, accession AT2) and its diploid progenitors Triticum urartu and Aegilops tauschii. We performed comprehensive RNA sequencing of 81 samples from different genotypes, tissues, and developmental stages. First, we found that intrinsic interspecific differences between the diploid parents played a major role in establishing the expression architecture of the allopolyploid. Nonetheless, allopolyploidy per se also induced dramatic and asymmetric patterns of differential gene expression between the subgenomes, and genes from the D subgenome exhibited a more drastic response. Second, analysis of homoeolog expression bias (HEB) revealed that the D subgenome exhibited significant expression bias and that de novo-generated HEB was attributed mainly to asymmetrical differential gene expression. Homoeolog-specific expression (HSE) analyses showed that the cis-only regulatory pattern was predominant in AT2, reflecting significant divergence between the parents. Co-expression network analysis revealed that homoeolog expression connectivity (HEC) was significantly correlated with sequence divergence in cis elements between subgenomes. Interestingly, allopolyploidy-induced reconstruction of network modules was also associated with different HSE patterns. Finally, a transcriptome atlas of spike development demonstrated that the phenotypic similarity of AT2 to T. urartu may be attributed to the combination of relatively stable expression of A-subgenome genes and drastic downregulation of their D-subgenome homoeologs. These findings provide a broad, multidimensional characterization of allopolyploidy-induced transcriptomic responses and suggest that allopolyploidy can have immediate and complex regulatory effects on the expression of nuclear genes.