Topological and topological-electronic correlations in amorphous silicon

In this paper, we study several structural models of amorphous silicon, and discuss structural and electronic features common to all. We note spatial correlations between short bonds, and similar correlations between long bonds. Such effects persist under a first principles relaxation of the system and at finite temperature. Next we explore the nature of the band tail states and find the states to possess a filamentary structure. We detail correlations between local geometry and the band tails.Comment: 7 pages, 11 figures, submitted to Journal of Crystalline Solid

Fine mapping and candidate gene analysis of proportion of four-seed pods by soybean CSSLs

Soybean yield, as one of the most important and consistent breeding goals, can be greatly affected by the proportion of four-seed pods (PoFSP). In this study, QTL mapping was performed by PoFSP data and BLUE (Best Linear Unbiased Estimator) value of the chromosome segment substitution line population (CSSLs) constructed previously by the laboratory from 2016 to 2018, and phenotype-based bulked segregant analysis (BSA) was performed using the plant lines with PoFSP extreme phenotype. Totally, 5 ICIM QTLs were repeatedly detected, and 6 BSA QTLs were identified in CSSLs. For QTL (qPoFSP13-1) repeated in ICIM and BSA results, the secondary segregation populations were constructed for fine mapping and the interval was reduced to 100Kb. The mapping results showed that the QTL had an additive effect of gain from wild parents. A total of 14 genes were annotated in the delimited interval by fine mapping. Sequence analysis showed that all 14 genes had genetic variation in promoter region or CDS region. The qRT−PCR results showed that a total of 5 candidate genes were differentially expressed between the plant lines having antagonistic extreme phenotype (High PoFSP > 35.92%, low PoFSP< 17.56%). The results of haplotype analysis showed that all five genes had two or more major haplotypes in the resource population. Significant analysis of phenotypic differences between major haplotypes showed all five candidate genes had haplotype differences. And the genotypes of the major haplotypes with relatively high PoFSP of each gene were similar to those of wild soybean. The results of this study were of great significance to the study of candidate genes affecting soybean PoFSP, and provided a basis for the study of molecular marker-assisted selection (MAS) breeding and four-seed pods domestication

Simulation of steel corrosion and iron yield in LFR with lead coolant

Liquid lead is the main coolant of the fourth generation of advanced nuclear energy system — lead cooled fast reactor (LFR), due to its good neutron economy, high heat transfer performance, stable chemical properties, constant low melting point, high boiling point, etc. Although there are many advantages, the corrosion of metal materials in liquid lead is one of the decisive factors restricting the development of lead cooled fast reactor. In this study, an engineering model for simulating the oxide film growth in liquid lead coolant is established, and the time-dependence of steel flux is analyzed based on the experimental data in the literature. The effects of circuit temperature, hydraulic diameter of section simulated, coolant velocity and steel types on the steel corrosion were investigated. The results showed that the oxide film formed on the steels is of micron grade and the diffusion yield of iron produced in pure lead coolant is of kilogram grade after ten years’ corrosion. The temperature and the coolant velocity have significant effects on the steel corrosion while the effect of hydraulic diameter is mild. Also, the steel types affect the growth of oxide film. The findings provide basic data for the evaluation of radioactive corrosion products of LFR

Adaptive Magnetic Anomaly Detection Method with Ensemble Empirical Mode Decomposition and Minimum Entropy Feature

Due to the fast attenuation of the magnetic field along with the distance, the magnetic anomaly generated by the remote magnetic target is usually buried in the magnetic noise. In order to improve the performance of magnetic anomaly detection (MAD) with low SNR, we propose an adaptive method of MAD with ensemble empirical mode decomposition (EEMD) and minimum entropy (ME) feature. The magnetic data is decomposed into the multiple intrinsic modal functions (IMFs) with different scales by EEMD. According to a defined criterion, the magnetic noise and magnetic signal are reconstructed based on IMFs, respectively. Entropy feature of reconstructed magnetic signal is extracted based on the probability density function (PDF) of the noise which is updated by the reconstructed magnetic noise. Compared to the traditional minimum entropy method, the entropy feature extracted by the proposed method is more obvious. The magnetic anomaly is detected whenever the entropy feature drops below the threshold. Thus, it is effective for revealing the weak magnetic anomaly by the proposed method. The measured magnetic noise is used to validate the performance of the proposed method. The results show that the detection probability of the proposed method is higher with low input SNR

A Wavelet-Driven Subspace Basis Learning Network for High-Resolution Synthetic Aperture Radar Image Classification

The feature learning strategy of convolutional neural networks learns the deep spatial features from high-resolution (HR) synthetic aperture radar (SAR) images while ignoring the speckle noise based on the SAR imaging mechanism. In the feature learning module, the noise reduction by feature-adaptive projection guided by a powerful embedded wavelet feature reconstruction mechanism can effectively learn the deep feature statistics. In this article, we present a wavelet-driven subspace basis learning network (WDSBLN), following an encoder–decoder architecture, for the HR SAR image classification. The powerful wavelet module, including wavelet decomposition and reconstruction, is employed for keeping the structures of learned features well under speckle noise. Specifically, a compact second-order feature enhancement mechanism is designed for improving the contour and edge information of low-frequency components in the feature decomposition stage, and a local feature attention module based on the point-wise convolutional layer is adopted to aggregate the contextual information of the local channel and reserves detail information in the high-frequency components. Then, the reconstructed feature map is employed as a guided standard in the subspace basis learning (SBL) module. The SBL module, including basis generation (generating the subspace basis vectors) and subspace projection (transforming deep feature maps into a signal subspace), maintains the local structure of HR SAR image patches and acquires the robust feature statistics. We conduct evaluations on three real HR SAR image classification datasets, achieving superior performances as compared to other related networks

A review of the retention mechanisms of redox-sensitive radionuclides in multi-barrier systems

International audienc

Effect of pH on Aqueous Se(IV) Reduction by Pyrite

International audienceInteraction of aqueous Se(IV) with pyrite was investigated using persistently stirred batch reactors under O2-free (<1 ppm) conditions at pH ranging from 4.5 to 6.6. Thermodynamic calculations, an increase in pH during the experiments, and spectroscopic observation indicate that the reduction of aqueous Se(IV) by pyrite is dominated by the following reaction: FeS2 + 3.5HSeO3− + 1.5H+ = 2SO42− + Fe2+ + 3.5Se(0) + 2.5H2O. The released Fe(II) was partitioned between the bulk solution and pyrite surface at pH ≈ 4.5 and 4.8, with the Fe2+ density at pyrite-solution interface about 4 orders of magnitude higher than that in the bulk solution, while iron oxyhydroxide precipitated at pH ≈ 6.6, resulting in the decrease of dissolved iron. In the Se(IV) concentration range of the experiments, aqueous Se(IV) reduction rate follows the pseudofirst order which is in the form of ln mSe(IV) = −k′t + ln mSe(IV)0, where k′ is apparent rate constant combining the rate constant k and pyrite surface area to mass of solution ratio (A/M). And the aqueous Se(IV) reduction rate constant for a standard system (k) with 1 m2 pyrite surface area per 1 kg solution was obtained to be 1.65 × 10−4 h−1, 3.28 × 10−4 h−1, and 4.76 × 10−4 h−1 at pH around 4.5, 4.8, and 5.1, respectively. The positive correlation between reaction rate and pH disagrees with the theories that protons are consumed when HSeO3− is reduced to Se0, and negative charge density on pyrite surface increases as pH increases. Thus, a ferrous iron mediated electron transfer mechanism is proposed to operate during the reduction of aqueous Se(IV) by pyrite. pH and iron concentration affect significantly on Se(IV) reaction rate and reaction product