Miniaturized volume holographic optical data storage and correlation system with a storage density of 10 Gb／cm^3

The general idea of holographic optical data storage (HODS) is briefly introduced. Based on the recent advances of HODS, the key techniques and the challenges of HODS are discussed. Some new techniques are proposed to improve the system. A miniaturized volume holographic data storage and correlation system is presented. It can achieve a density of 10 Gb/cm^3 and a fast correlation recognition rate of more than 2000 images per second. It shows the attracting potential advantages over other conventional storage methods in the information storage as well as information processing.     

基于遗传算法-深度神经网络的分布式光纤监测工作面矿压预测

煤层开采过程中的工作面矿压分析与预测,对煤矿顶板管理与安全生产具有重要意义。然而,工作面开采引起的围岩移动和变形影响着矿压预测的准确度。为了提高工作面来压位置预测的精度,以分布式光纤监测采动覆岩变形的频移数据为基础,引入门控循环神经网络(gated recurrent neural networks, GRU),建立了遗传算法(genetic algorithm, GA)-GRU-反向传播(back propagation, BP)的工作面来压位置预测模型。将光纤频移值的统计特征融合工作面推进距离等因素作为特征向量,并采用GA对GRU及BP网络的超参数寻优。实验结果表明：预测模型的决定系数为98.7%,平均绝对误差为1.224 cm,均方根误差为1.769 cm,预测的准确性高,为工作面矿压预测提供了新的方法。     

瞬态热传导问题的一阶对称SPH方法模拟

为提高传统光滑粒子动力学(smoothed particle hydrodynamics, SPH)方法模拟瞬态热传导问题的精度和稳定性,本文提出了一种一阶对称光滑粒子动力学(first order symmetric SPH, FO-SSPH)方法.该方法将具有二阶热传导方程分解成两个一阶偏微分方程,然后基于梯度离散和Taylor级数展开思想,对一阶核梯度形式进行修正,并将得到的局部矩阵对称化.数值结果表明:与传统SPH方法相比,FO-SSPH方法精度高、数值稳定性好; 该方法能较准确地直接施加混合边值 关键词： 瞬态热传导 光滑粒子动力学 非线性     

Mass spectrometry imaging for biomedical applications

The development of technologies for mass spectrometry imaging is of substantial research interest. Mass spectrometry is potentially capable of providing highly specific information about the distribution of compounds in tissues, with high sensitivity. The in-situ analysis needed for tissue imaging requires MS to be performed under conditions different from the traditional ones, typically with intensive sample preparation and optimized for pharmaceutical applications. In this paper we critically review the current status of MS imaging with different methods of sample ionization and discuss the 3D and quantitative imaging capabilities which need further development, the importance of the multi-modal imaging, and the balance between the pursuit of high-resolution imaging and the practical application of MS imaging in biomedicine.     

Synthesis and relaxivity of polyamide paramagnetic metal complexes for magnetic resonance imaging

A new class of paramagnetic macromolecular magnetic resonance imaging contrast agents has been developed. Eight new polyamide ligands were synthesized by copolymerization of ethylenediaminetetraacetic acid dianhydride or diethylenetriaminepentaacetic acid dianhydride and diamine monomers. Their gadolinium(III), manganese(II) and iron(III) complexes were also synthesized. All polyamide ligands and metal complexes were characterized by ¹H nuclear magnetic resonance, infrared spectra and elemental analyses. Relaxivity studies showed that the polyamide paramagnetic metal complexes had obviously higher relaxation effectiveness as compared to corresponding simple monomeric paramagnetic metal complexes.     

Discovery of Novel Non-Oxime Reactivators Showing In Vivo Antidotal Efficiency for Sarin Poisoned Mice

A family of novel efficient non-oxime compounds exhibited promising reactivation efficacy for VX and sarin inhibited human acetylcholinesterase was discovered. It was found that aromatic groups coupled to Mannich phenols and the introduction of imidazole to the ortho position of phenols would dramatically enhance reactivation efficiency. Moreover, the in vivo experiment was conducted, and the results demonstrated that Mannich phenol L10R1 (30 mg/kg, ip) could afford 100% 48 h survival for mice of 2*LD₅₀ sarin exposure, which is promising for the development of non-oxime reactivators with central efficiency.     

Friction-induced vibration considering multiple types of nonlinearities

Nonlinear Dynamics - The friction-induced vibration of a novel 5-DoF (degree-of-freedom) mass-on-oscillating-belt model considering multiple types of nonlinearities is studied. The first type of...     

Nanostructures for Electrocatalytic CO2 Reduction

One of the most effective ways to cope with the problems of global warming and the energy shortage crisis is to develop renewable and clean energy sources. To achieve a carbon-neutral energy cycle, advanced carbon sequestration technologies are urgently needed, but because CO₂ is a thermodynamically stable molecule with the highest carbon valence state of +4, this process faces many challenges. In recent years, electrochemical CO₂ reduction has become a promising approach to fix and convert CO₂ into high-value-added fuels and chemical feedstock. However, the large-scale commercial use of electrochemical CO₂ reduction systems is hindered by poor electrocatalyst activity, large overpotential, low energy conversion efficiency, and product selectivity in reducing CO₂. Therefore, there is an urgent need to rationally design highly efficient, stable, and scalable electrocatalysts to alleviate these problems. This minireview also aims to classify heterogeneous nanostructured electrocatalysts for the CO₂ reduction reaction (CDRR).     

Spin gapless armchair graphene nanoribbons under magnetic field and uniaxial strain

Using Green＇s function method, we investigate the spin transport properties of armchair graphene nanoribbons （AG- NRs） under magnetic field and uniaxial strain. Our results show that it is very difficult to transform narrow AGNRs directly from semiconductor to spin gapless semiconductors （SGS） by applying magnetic fields. However, as a uniaxial strain is exerted on the nanoribbons, the AGNRs can transform to SGS by a small magnetic field. The combination mode be- tween magnetic field and uniaxial strain displays a nonmonotonic arch-pattern relationship. In addition, we find that the combination mode is associated with the widths of nanoribbons, which exhibits group behaviors.