Genome Expression Profile Analysis of the Immature Maize Embryo during Dedifferentiation

Maize is one of the most important cereal crops worldwide and one of the primary targets of genetic manipulation, which provides an excellent way to promote its production. However, the obvious difference of the dedifferentiation frequency of immature maize embryo among various genotypes indicates that its genetic transformation is dependence on genotype and immature embryo-derived undifferentiated cells. To identify important genes and metabolic pathways involved in forming of embryo-derived embryonic calli, in this study, DGE (differential gene expression) analysis was performed on stages I, II, and III of maize inbred line 18-599R and corresponding control during the process of immature embryo dedifferentiation. A total of ∼21 million cDNA tags were sequenced, and 4,849,453, 5,076,030, 4,931,339, and 5,130,573 clean tags were obtained in the libraries of the samples and the control, respectively. In comparison with the control, 251, 324 and 313 differentially expressed genes (DEGs) were identified in the three stages with more than five folds, respectively. Interestingly, it is revealed that all the DEGs are related to metabolism, cellular process, and signaling and information storage and processing functions. Particularly, the genes involved in amino acid and carbohydrate transport and metabolism, cell wall/membrane/envelope biogenesis and signal transduction mechanism have been significantly changed during the dedifferentiation. To our best knowledge, this study is the first genome-wide effort to investigate the transcriptional changes in dedifferentiation immature maize embryos and the identified DEGs can serve as a basis for further functional characterization

A Straightforward Convergence Method for ICCG Simulation of Multiloop and Time-Stepping FE Model of Synchronous Generators with Simultaneous AC and Rectified DC Connections

Now electric machines integrate with power electronics to form inseparable systems in lots of applications for high performance. For such systems, two kinds of nonlinearities, the magnetic nonlinearity of iron core and the circuit nonlinearity caused by power electronics devices, coexist at the same time, which makes simulation time-consuming. In this paper, the multiloop model combined with FE model of AC-DC synchronous generators, as one example of electric machine with power electronics system, is set up. FE method is applied for magnetic nonlinearity and variable-step variable-topology simulation method is applied for circuit nonlinearity. In order to improve the simulation speed, the incomplete Cholesky conjugate gradient (ICCG) method is used to solve the state equation. However, when power electronics device switches off, the convergence difficulty occurs. So a straightforward approach to achieve convergence of simulation is proposed. At last, the simulation results are compared with the experiments

Interferometric Phase Reconstruction Based on Probability Generative Model: Toward Efficient Analysis of High-Dimensional SAR Stacks

In order to minimize the influence of decorrelation noise on multi-temporal interferometric synthetic aperture radar (MT-InSAR) applications, a series of phase reconstruction methods have been proposed in recent years. Unfortunately, current phase reconstruction methods generally exhibit a low computational efficiency due to their high non-linearity, in particular in the case that the dimension of a SAR stack is high. In this paper, a new approach is proposed to efficiently resolve phase reconstruction problems. This approach is inspired by the theory of probabilistic principle component analysis. A complex valued probability generative model is constructed to portray a phase reconstruction process. Moreover, in order to resolve such a model, a targeted algorithm based on the idea of expectation maximization is designed and implemented. For validation purposes, the proposed approach is compared to the traditional eigenvalue decomposition-based method by using simulated data and 101 real Sentinel-1A SAR images. The experimental results demonstrate that the proposed method can accelerate the phase reconstruction process drastically, in particular when a high-dimensional SAR stack is required to be processed

An Ultrasound–Fenton Process for the Degradation of 2,4,6-Trinitrotoluene

2,4,6-Trinitrotoluene (TNT), one of the main compounds in ammunition wastewater, is harmful to the environment. In this study, the treatment efficiency of 2,4,6-TNT by different treatment processes, including ferrous ion (Fe2+), hydrogen peroxide (H2O2), Fenton, ultrasound (US) irradiation, US + Fe2+, US + H2O2 and US–Fenton process, was compared. The results showed that US–Fenton was the most effective among all methods studied. The effects of initial pH, reaction time and H2O2 to Fe2+ molar ratio were investigated. The results showed that the removal of TNT, TOC and COD was maximum at an initial pH of 3.0 and H2O2 to Fe2+ molar ratio of 10:1. TNT, TOC and COD removal was fast in the first 30 min, reaching 83%, 57% and 50%, then increased gradually to 99%, 67% and 87% until 300 min, respectively. Semi-batch mode operation increased the removal of TNT and TOC by approximately 5% and 10% at 60 min, respectively. The average carbon oxidation number (ACON) was increased from −1.7 at 30 min to a steady-state value of 0.4, indicating the mineralization of TNT. Based on GC-MS analysis, 1,3,5-trinitrobenzene, 2,4,6-trinitrobenzene acid, 3,5-dinitrobenznamine and 3,5-dinitro-p-toluidine were the major byproducts from the US–Fenton process. The TNT degradation pathway was proposed, which involved methyl group oxidation, decarboxylation, aromatic ring cleavage and hydrolysis