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https://www.selleckchem.com/products/atezolizumab.html More than 99% of NH4+-N and 81% - 85% of total nitrogen were stably removed, with anammox bacteria contributing to more than 96% of total nitrogen removal. Anammox bacteria were efficiently enriched to the highest level among the key nitrogen-converting microbial groups, both in terms of abundance (8.17%) and nitrogen-conversion capacity, while ammonium oxidizing bacteria were well controlled to provide sufficient ammonium-oxidizing capacity. Nitrite oxidizing bacteria were maintained stable (relative abundance of 1.08%-1.88%) and their activity was effectively suppressed. This study provided a novel technology, SPAN, to precisely control oxygen input in PN-A system, and proved that SPAN was effective and reliable in achieving long-term high-efficiency nitrogen removal.River algal blooms have become a challenging environmental problem worldwide due to strong interference of human activities and megaprojects (e.g., big dams and large-scale water transfer projects). Previous studies on algal blooms were mainly focused on relatively static water bodies (i.e., lakes and reservoirs), but less on the large rivers. As the largest tributary of the Yangtze River of China and the main freshwater source of the South-to-North Water Diversion Project (SNWDP), the Han River has experienced frequent algal blooms in recent decades. Here we investigated the algal blooms during a decade (2003-2014) in the Han River by two gradient boosting machine (GBM) models with k-fold cross validation, which used explanatory variables from current 10-day (GBMc model) or previous 10-day period (GBMp model). Our results advocate the use of GBMp due to its higher accuracy (median Kappa = 0.9) and practical predictability (using antecedent observations) compared to GBMc. We also revealed that the algal blooms in the Han River were significantly modulated by antecedent water levels in the Han River and the Yangtze River and water level variation i

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