Detection of DNA methylation changes during seed germination in rapeseed （Brassica napus）

DNA methylation is a common yet important modi- fication of DNA in eukaryotic organisms. DNA methy- lation, especially methylation of cytosine (m5C), have both epigenetic and mutagenic effects on various cellu- lar activities such as differential gene exp…     

Microstructure evolution and nucleation mechanism of Inconel 601H alloy welds by vibration-assisted GTAW

Nickel-based alloys exhibit excellent high-temperature strength and oxidation resistance; however, because of coarse grains and severe segregation in their welding joints, these alloys exhibit increased susceptibility to hot cracking. In this paper, to improve the hot-cracking resistance and mechanical properties of nickel-based alloy welded joints, sodium thiosulfate was used to simulate crystallization, enabling the nucleation mechanism under mechanical vibration to be investigated. On the basis of the results, the grain refinement mechanism during the gas tungsten arc welding (GTAW) of Inconel 601H alloy under various vibration modes and parameters was investigated. Compared with the GTAW process, the low-frequency mechanical vibration processes resulted in substantial grain refinement effects in the welds; thus, a higher hardness distribution was also achieved under the vibration conditions. In addition, the γ' phase exhibited a dispersed distribution and segregation was improved in the welded joints with vibration assistance. The results demonstrated that the generation of free crystals caused by vibration in the nucleation stage was the main mechanism of grain refinement. Also, fine equiaxed grains and a dispersed γ' phase were found to improve the grain-boundary strength and reduce the segregation, contributing to preventing the initiation of welding hot cracking in nickel-based alloys.     

基于FCM-ELM-BBPS的预测控制参数整定

模型预测控制设计参数选择显著影响被控系统性能，目前基于专家经验的主流参数整定方法会出现控制器鲁棒性差、计算成本高等缺点.为了解决上述问题，提出一种基于模糊C均值-极限学习机-裸骨粒子群（Fuzzy C-means-Extreme Learning Machine-Bare Bones Particle Swarm， FCM-ELM-BBPS）的参数整定算法.通过模糊C均值算法（Fuzzy C-means， FCM）聚类进行数据预处理，将被控系统复杂数据根据自身特征进行聚类，以降低神经网络的训练误差，提高预测精度；针对每一类特征数据，利用极限学习机（Extreme Learning Machine， ELM）建立预测控制参数与性能指标的映射关系模型，并进一步获得参数整定规则；采用裸骨粒子群（Bare Bones Particle Swarm， BBPS）优化算法进行预测控制参数整定，通过采用高斯分布来更新粒子位置，加快目标函数的收敛速度，从而有效地减少参数寻优时间；分别进行仿真和水箱系统实验验证，证明了提出算法的有效性.实验结果表明，本文提出的算法与现有方法相比，更具有优越性，其中整定时间减少了34.84%，同时在调整时间等时域性能指标上提升了43.98%.     

Porous bismuth nanocrystals with advanced sodium ion storage property

Bismuth-based materials are ideal electrodes for sodium-ion batteries(SIBs) due to their high capacity and low cost. However, conventional solid bismuth materials still suffer from severe volume expansion during the reaction process, which hinders its application. Herein, single-crystal bismuth nanospheres with diameters in the range of200–400 nm were successfully prepared with the Na–Bi alloying mechanism studied using in-situ XRD, which confirms a stepwise process of Bi→NaBi→Na3Bi with large v...     

Design and implementation of instruction-driven and data-driven self-reconfigurable cell array

The reconfigurable chip, which integrates the advantages of high performance, high flexibility,high parallelism, low power consumption, and low cost, has achieved rapid development and wide application. Generally, the control part and the computing part of algorithm is accelerated based on different reconfigurable architectures, but it is difficult to obtain overall performance improvement.For improving efficiency of reconfigurable structure both for the control part and the computing part,a hyb...     

一种基于极值特征值之差的全盲多天线频谱感知算法

提出了一种新的基于接收信号取样协方差矩阵（SCM）极值特征值之差的多天线频谱感知算法BDDEE，其以SCM的最大最小特征值之差与接收信号平均能量之比作为感知判决量，在检测过程中摆脱了对噪声方差的依赖，且无须使用主用户信号及无线传输信道等相关参数.在此基础上，基于有限维Wishart随机矩阵有序特征值分布的相关结果，从理论上提出了一种精确的虚警概率和判决门限的分析和计算方法；更进一步，考虑到次级用户计算和存储资源的限制，利用高维Wishart随机矩阵中极值特征值的分布理论，通过融合最大和最小特征值极限分布所对应的判决门限，提出了一种低计算复杂度的判决门限计算方法.综合考虑检测性能和虚警性能指标来看，新算法比经典的CAV、MME和DMME算法具有更优的感知性能，在样本数目有限的条件下能获得更加稳健的检测结果，数值仿真结果证明了所提BDDEE算法的有效性.