Dependency distance: A new perspective on syntactic patterns in natural languages

Dependency distance, measured by the linear distance between two syntactically related words in a sentence, is generally held as an important index of memory burden and an indicator of syntactic difficulty. Since this constraint of memory is common for all human beings, there may well be a universal preference for dependency distance minimization (DDM) for the sake of reducing memory burden. This human-driven language universal is supported by big data analyses of various corpora that consistently report shorter overall dependency distance in natural languages than in artificial random languages and long-tailed distributions featuring a majority of short dependencies and a minority of long ones. Human languages, as complex systems, seem to have evolved to come up with diverse syntactic patterns under the universal pressure for dependency distance minimization. However, there always exist a small number of long-distance dependencies in natural languages, which may reflect some other biological or functional constraints. Language system may adapt itself to these sporadic long-distance dependencies. It is these universal constraints that have shaped such a rich diversity of syntactic patterns in human languages.     

基于纯方位的浅海距离特征量解算分析

目标辐射噪声的LOFAR图中的干涉条纹包含了目标的运动参数和环境信息。当LOFAR图中的干涉条纹模糊或缺失时,其中的目标距离信息将无法提取。对于匀速直线运动的声源目标,仅利用方位信息,通过构造距离特征量和目标方位的关系模型,给出了一种浅海估计距离特征量的补充方法。浅海数值仿真和实验验证表明了该方法的可行性和有效性。     

Efficient algorithms for three‐dimensional axial and planar random assignment problems

Beautiful formulas are known for the expected cost of random two‐dimensional assignment problems, but in higher dimensions even the scaling is not known. In three dimensions and above, the problem has natural “Axial” and “Planar” versions, both of which are NP‐hard. For 3‐dimensional Axial random assignment instances of size n, the cost scales as Ω(1/ n), and a main result of the present paper is a linear‐time algorithm that, with high probability, finds a solution of cost O(n^–1+o(1)). For 3‐dimensional Planar assignment, the lower bound is Ω(n), and we give a new efficient matching‐based algorithm that with high probability returns a solution with cost O(n log n). © 2013 Wiley Periodicals, Inc. Random Struct. Alg., 46, 160–196, 2015     

三维多面体网格上扩散方程的保正格式

 针对三维任意(星形)多面体网格, 本文构造了扩散方程的一种单元中心型非线性有限体积格式, 证明了该格式具有保正性. 在该格式设计中, 除引入网格中心量外, 还引入网格节点量和网格面中心量作为中间未知量, 它们将用网格中心未知量线性组合表示, 使得格式仅有网格中心未知量作为基本未知量. 在节点量计算中, 利用网格面上的调和平均点, 设计了一种适用于三维多面体网格的局部显式加权方法. 该格式适用于求解非平面的网格表面和间断扩散系数的问题. 数值例子验证了它对光滑解具有二阶精度和保正性.     

聚3-己基噻吩：非富勒烯太阳能电池中的量子效率损失和电压损失

聚3-己基噻吩(P3HT)以其合成工艺简单、成本低廉的优势,成为有机光伏领域中最具吸引力的电子给体材料之一。然而,目前P3HT: 非富勒烯太阳能电池的光伏性能仍然较差。在本工作中,我们证明了与P3HT: 富勒烯太阳能电池相比,较快的电荷转移态的非辐射衰减速率(K_nr)是导致P3HT: 非富勒烯太阳能电池中较低的量子效率和较高的电压损失的原因。然后,我们研究了基于非富勒烯受体ZY-4Cl的太阳能电池的工作机理。研究结果表明与P3HT: 非富勒烯体系相比,P3HT: ZY-4Cl中K_nr的降低改善了器件的量子效率,同时降低了电压损失。K_nr降低的原因可以部分归因于电荷转移态能量的增加。此外,给体分子和受体分子之间的距离(DA间距)的增大也是K_nr减少的重要原因。因此,我们得出结论：为了提高P3HT太阳能电池的性能,需进一步降低器件的K_nr,这可通过增加活性层中的DA间距来实现。     

双分散颗粒体系在临界堵塞态的结构特征

堵塞行为是颗粒体系中一种常见的现象,其力学性质与堆积结构的关联非常复杂.本文采用离散元法研究了由两种不同半径颗粒组成的二维双分散无摩擦球形颗粒体系在临界堵塞态所呈现的结构特征,讨论了大小颗粒粒径比与大颗粒百分比对临界堵塞态的影响.数值模拟结果表明,当粒径比小于1.4时,临界平均接触数与大颗粒百分比关系不大,当粒径比大于1.4时随着大颗粒百分比的增大临界平均接触数先减小再增大.而临界体积分数在粒径比小于1.8时随着大颗粒百分比的增加先减小后增大,大于1.8时又基本不随大颗粒百分比而变化.大颗粒百分比在接近0或1时,系统近似为单分散体系,临界平均接触数与体积分数基本不随半径比的增大而变化;在接近0.5时,临界平均接触数随着半径比的增大逐渐减小,而临界体积分数则是先减小后增大.文中对大-小颗粒这一接触类型的百分比也进行了探讨,其值随着大颗粒百分比的增大呈二次函数的变化趋势,粒径比对这一变化趋势只有较小的影响.     

基于飞秒激光模间拍频法的大尺寸测距方法

本文基于飞秒激光模间拍频法实现多波长相位式绝对距离测量, 通过改变光频梳重复频率合成波长扩大测距量程, 并采用监测臂和双快门切换系统补偿和消除由电路产生的相位差单向漂移和大幅抖动. 实验中以20倍重复频率的拍频进行测量, 在30 min内相位测量的标准偏差为0.022°; 与双频激光干涉仪比对1125 mm行程内位移测量结果, 测距精度优于50 μm; 实验验证了合成波长方法扩大量程方案的可行性, 获得的测距重复性优于3 μm, 该系统理论上可扩展量程至7.5 km.     

Localization microscopy (SPDM) facilitates high precision control of lithographically produced nanostructures

Nanoscale resolution in material sciences is usually restricted to scanning electron beam microscopes. Here we present a procedure that allows single molecule resolution of the sample surface with visible light. Highlighting the performance we used electron beam lithography to generate highly regular nanostructures consisting of interconnected cubes. The samples were labeled with Alexa 647 dyes. The spatial organization of the dyes on nanostructured surfaces was localized with single molecule resolution using localization microscopy. This succeeded also in an absolute spatial calibration of the localization method applied (spectral precision distance microscopy/SPDM). The findings will contribute to the field of product control for industrial applications and long-term fluorescence imaging.