A Faster and More Accurate Iterative Threshold Algorithm for Signal Reconstruction in Compressed Sensing.

Fast iterative soft threshold algorithm (FISTA) is one of the algorithms for the reconstruction part of compressed sensing (CS). However, FISTA cannot meet the increasing demands for accuracy and efficiency in the signal reconstruction. Thus, an improved algorithm (FIPITA, fast iterative parametric improved threshold algorithm) based on mended threshold function, restart adjustment mechanism and parameter adjustment is proposed. The three parameters used to generate the gradient in the FISTA are carefully selected by assessing the impact of them on the performance of the algorithm. The developed threshold function is used to replace the soft threshold function to reduce the reconstruction error and a restart mechanism is added at the end of each iteration to speed up the algorithm. The simulation experiment is carried out on one-dimensional signal and the FISTA, RadaFISTA and RestartFISTA are used as the comparison objects, with the result that in one case, for example, the residual rate of FIPITA is about 6.35% lower than those three and the number of iterations required to achieve the minimum error is also about 102 less than that of FISTA.

[QTL mapping for contents of main carotenes and lycopene in carrot (Daucus carota L.)].

An F2 population derived from two carrot inbred lines, P50006 and HCM A.C. with high carotene accumulation, was developed and used to map and analyze quantitative trait locus (QTL) associated with the accumulation of alpha and beta-carotene, total carotene and lycopene. Broad-sense heritabilities of these traits were 0.75, 0.50, 0.31, and 0.93, respectively. A genetic map with 91 SRAP (Sequence-related amplified polymorphism) markers was developed, which spanned 502.9 cM in 9 linkage groups with a mean marker interval of 5.5 cM. Mixed-model-based composite interval mapping was performed to analyze QTL and epistasis effects. One major QTL each for beta-carotene, total carotene and lycopene accumulation were detected which can explain 12.79%, 12.87%, and 14.61% of total phenotypic variations, respectively. Additive genetic variance was primarily responsible for genetic variability in all three major QTL. In addition, a pair of epistasis QTL for beta-carotene and lycopene accumulation was detected, which were able to explain 15.1% and 6.5% of total phenotypic variation, respectively. The dominant x additive and dominant x dominant interaction variance were primary epistasis effect for beta-carotene and lycopene. These SRAP markers linked to QTL could be used in selection or QTL pyramiding for high carotene and lycopene content in carrot breeding.