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In this study, the spatial distribution pattern of the roads, historical samples, digital elevation data, and other available resources were incorporated into the design of a soil-sampling scheme to predict the soil organic matter (SOM) of the northern region of Zhongxiang City, Hubei Province, and simulated annealing (SA) was applied to optimize the sampling design. The sampling points determined after optimization were used to establish a multivariate linear regression model to adequately reproduce the intrinsic link between topographic factors and the SOM at 13 different sampling scales in areas nearby the existing roadways in the study area. The topographic factors included slope, plane curvature, profile curvature, topographic wetness index (TWI), stream power index (SPI), and sediment transport index (STI). A multilayer perceptron (MLP) model was also constructed. Comparison of the accuracy of the multivariate linear regression and MLP models demonstrated the feasibility of an optimized soil sampling design based on the road network. With the optimized sampling design, accurate soil-landscape information can be obtained, and its precision is greater than that of the original sampling scheme before optimization. The optimized sampling design obtained reduces sampling costs, increases sampling efficiency, and provides an effective method for obtaining the spatial distribution pattern of organic matter in soils.

The Maximum Agreement Forest (MAF) problem on two given phylogenetic trees is an important NP-hard problem in the field of computational biology. In this paper, we study the parameterized version of the MAF problem: given two unrooted (multifurcating) phylogenetic trees T 1 and T 2 with the same leaf-label set L, and a parameter k, either construct an agreement forest of at most k trees for T 1 and T 2 , or report that no such a forest exists. Whether there is a fixed-parameter tractable algorithm for this problem was posed as an open problem several times in the literature. In this paper, we resolve this open problem by presenting a parameterized algorithm of running time O(4 k n 5 ) for the problem.

The sphere decoding algorithm for signal transmitted on multiple antennas channel is considered. In this paper, the preprocessing stage is analyzed in order to seek a reduced complexity and some improvements are made to enhance the performance. The computer simulation results show that the improved algorithm by applying Pohst Enumeration with selected initial radius is more efficient than that by applying Schnorr-Euchner Enumeration. For example, the average floating-point operations in 6×6 MIMO using 64-QAM modulation reduces 71% compared with SE enumeration.

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