Single-cell green microalga Nannochloropsis oceanica is potentially considered to be the bioresource for biofuel and pharmaceutical production. Urea is a kind of nutrient component for photosyn-thetic N. oceanica. Meanwhile, urea could induce to accumulate some substances such as lipid and affect its growth and physiology. However, how marine microalga N. oceanica respond and adapt to urea addition remains elusive. Here, acclimation of the metabolic reprogramming to changes in the nutrient environment was studied by high-throughput mRNA sequencing in N. oceanica under Ct vs U, there were 2104 genes displayed differential expression (including 1354 upregulation and 750 downregulation, respectively) and some pathways including carbon/nitrogen metabolism, photosynthesis, and lipid metabolism would be reprogrammed in N. oceanica. The results showed that genes related to photosynthesis in N. oceanica were significantly down-regulated, especially those related to light harvesting proteins. Interestingly, urea absorption and transport may de-pend not only on specialized transport mechanisms such as urease, but also on alternative transport channels such as the ABC transporter family, CLC protein family. In addition, urea causes specific changes in carbon and lipid metabolism. Genes associated with the Calvin cycle and carbon concentration mechanisms were significantly upregulated. In lipid metabolism, genes associated with lipases, or polyunsaturated fatty acid enzymes, are highly activated. In addition, expression is enhanced in the tricarboxylic acid cycle and folate metabolism, making important contributions to energy supply and synthesis and modification of genes or macromolecules. These phenomena indicate that N. oceanica actively and dynamically regulates the redistribution of carbon and nitrogen after urea addition., which will provide references for further research on the effects of urea on N. oceanica.

The COVID-19 pandemic has emphasized the crucial role of ventilation systems in mitigating cross-infections, especially in infectious disease hospitals. This study introduces a dual-design operation ventilation system that can operate under two sets of ventilation conditions for normal and epidemic times. A challenge is optimizing duct diameters for required airflow while maintaining hydraulic balance. We design a genetic algorithm with adaptive penalty factor, the velocity constraint and the improved crossover and mutation probability. The improved genetic algorithm is suitable for ventilation system networks, which can find a better air duct diameters combination to improve the hydraulic balance rate, and reduce the usage of air valves, resulting in efficient hydraulic balancing commissioning. Compared with the traditional genetic algorithm, it has a faster search speed and a better global search ability, which is effective for the optimal design of ventilation system networks.