Publications by authors named "Shu-de Liu"

Article Synopsis
  • Important fishery resources in China's coastal waters, including species with short life cycles and rapid growth, have seen a decline, raising concerns for their protection and utilization.
  • The study utilized three machine learning methods—random forest model, artificial neural network model, and generalized boosted regression models—to analyze the distribution of fish habitat and its relationship with environmental factors in Haizhou Bay.
  • Results indicated that factors like sea bottom temperature, seawater depth, and sea bottom salinity significantly influenced habitat distribution, with the random forest model performing best in both fitting and prediction; the fish were primarily found between coordinates 34.5°-35.8° N and 119.7°-121° E.
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We have developed a novel selection circuit based on carbon source utilization that establishes and sustains growth-production coupling over several generations in a medium with maltose as the sole carbon source. In contrast to traditional antibiotic resistance-based circuits, we first proved that coupling of cell fitness to metabolite production by our circuit was more robust with a much lower escape risk even after many rounds of selection. We then applied the selection circuit to the optimization of L-tryptophan (l-Trp) production.

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Based on the investigation data of ichthyoplankton assemblages and environmental factors in Yangtze Estuary and adjacent waters in May 1999 and 2001, the characteristics of ichthyoplankton assemblages in these areas in spring were studied by using TWINSPAN (two-way indicator species analysis) and CCA (canonical correspondence analysis). A total of 11 540 ichthyoplankton individuals were taxonomically identified, belonging to 11 orders, 18 families and 32 species, of which, Coilia mystus, Engraulis japonicus, Chaeturichthys hexanema, Allanetta bleekeri, and Trachidermis fasciatus were the dominant species. The ichthyoplankton communities were classified into three assemblages by using TWINSPAN, i.

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