G. Feng | Geology Reports

USGS2011

Effect of anaesthetics MS-222 and clove oil on blood biochemical parameters of juvenile Siberian sturgeon (Acipenser baerii)

The effects of MS-222 and clove oil on blood biochemical parameters of juvenile Siberian sturgeon (Acipenser baerii) were studied. MS-222 caused higher glucose (GLU) concentrations in anaesthetic test groups than for the control group. Triglyceride (TGL) concentrations of fish in the 140 and 160mgL-1 groups were also significantly higher than those of other groups. Alanine aminotransferase (ALT) activity in the 140mgL-1 group was significantly higher than the level in 80, 100 and 120mgL-1 groups. Aspartate aminotransferase (AST) activity in the 140mgL-1 group was significantly higher than those in the 100 and 120mgL-1 groups. Levels of total protein (TP), cholesterol (CHOL) and alkaline phosphatase (ALP) in anaesthetic test groups were not significantly influenced by MS-222. Clove oil did not have significant effects on levels of GLU, TP, CHOL, ALT and ALP. TGL concentration of fish exposed to 180mgL-1 clove oil was significantly higher than those of the rest anaesthetic groups. AST activities of fish exposed to 120, 150 and 180mgL-1 were significantly higher than those of 60 and 90mgL-1. Overall, TGL and AST could be potentially used as indicators of anaesthetic stress for juvenile Siberian sturgeon. Based on blood biochemical parameters, the appropriate anaesthetic concentrations of MS-222 and clove oil were 80-120mgL-1 and 60-90mgL-1, respectively. Clove oil was a promising alternative to MS-222. ?? 2011 Blackwell Verlag, Berlin.

Journal of Applied Ichthyology↗

USGS2006

Nonlinear inversion of potential-field data using a hybrid-encoding genetic algorithm

Using a genetic algorithm to solve an inverse problem of complex nonlinear geophysical equations is advantageous because it does not require computer gradients of models or "good" initial models. The multi-point search of a genetic algorithm makes it easier to find the globally optimal solution while avoiding falling into a local extremum. As is the case in other optimization approaches, the search efficiency for a genetic algorithm is vital in finding desired solutions successfully in a multi-dimensional model space. A binary-encoding genetic algorithm is hardly ever used to resolve an optimization problem such as a simple geophysical inversion with only three unknowns. The encoding mechanism, genetic operators, and population size of the genetic algorithm greatly affect search processes in the evolution. It is clear that improved operators and proper population size promote the convergence. Nevertheless, not all genetic operations perform perfectly while searching under either a uniform binary or a decimal encoding system. With the binary encoding mechanism, the crossover scheme may produce more new individuals than with the decimal encoding. On the other hand, the mutation scheme in a decimal encoding system will create new genes larger in scope than those in the binary encoding. This paper discusses approaches of exploiting the search potential of genetic operations in the two encoding systems and presents an approach with a hybrid-encoding mechanism, multi-point crossover, and dynamic population size for geophysical inversion. We present a method that is based on the routine in which the mutation operation is conducted in the decimal code and multi-point crossover operation in the binary code. The mix-encoding algorithm is called the hybrid-encoding genetic algorithm (HEGA). HEGA provides better genes with a higher probability by a mutation operator and improves genetic algorithms in resolving complicated geophysical inverse problems. Another significant result is that final solution is determined by the average model derived from multiple trials instead of one computation due to the randomness in a genetic algorithm procedure. These advantages were demonstrated by synthetic and real-world examples of inversion of potential-field data. ?? 2005 Elsevier Ltd. All rights reserved.

Computers & Geosciences↗