Special John-Nirenberg-Campanato spaces via congruent cubes

Let p ∈ [1, ∞), q ∈ [1, ∞), α∈ R, and s be a non-negative integer. Inspired by the space JNp introduced by John and Nirenberg(1961) and the space B introduced by Bourgain et al.(2015), we introduce a special John-Nirenberg-Campanato space JN^con_(p,q,s) over Rⁿ or a given cube of R;with finite side length via congruent subcubes, which are of some amalgam features. The limit space of such spaces as p →∞ is just the Campanato space which coincides with the space BMO(the space of functions with bounded mean oscillations)when α = 0. Moreover, a vanishing subspace of this new space is introduced, and its equivalent characterization is established as well, which is a counterpart of the known characterization for the classical space VMO(the space of functions with vanishing mean oscillations) over Rⁿ or a given cube of Rⁿ with finite side length.Furthermore, some VMO-H¹-BMO-type results for this new space are also obtained, which are based on the aforementioned vanishing subspaces and the Hardy-type space defined via congruent cubes in this article. The geometrical properties of both the Euclidean space via its dyadic system and congruent cubes play a key role in the proofs of all these results.     

Quantum Watermark Algorithm Based on Maximum Pixel Difference and Tent Map

International Journal of Theoretical Physics - A new quantum watermark algorithm is presented by combining maximum pixel difference partitioning with the least significant bit substitution...     

改进遗传算法及其在钻井液设计中的运用

在深井、超深井以及地层复杂等条件下，为了避免或减少钻井事故的发生，达到优质快速钻井的目的，选择合适的钻井液体系至关重要。基于案例推理（CBR，Case-Based Reasoning）的钻井液设计中，钻井液体系由岩性、井型和井深等属性推理得出，但属性权重的分配会对推理结果产生显著的影响；遗传算法在优化属性权重时，存在收敛速度慢、收敛精度低的缺点。针对上述问题，提出一种解决CBR中属性权重分配问题的改进遗传算法。首先，对遗传算子进行改进：选择算子方面，利用指数尺度变换法优化个体选择；交叉算子方面，对算术交叉中的比例因子进行自适应调整；变异算子方面，改进个体变异方向，保持种群多样性。其次，从个体适应度和交叉个体的差异程度两方面实现交叉概率自适应调整。最后，通过对UCI数据集的对比实验，证明了改进后的遗传算法能改善全局收敛性能，提高CBR的准确率。将该算法运用到基于CBR的钻井液设计中，实验结果表明，所提方法能够优化属性权重的分配，进而提高钻井液设计的质量。     

ICP-MS法测定黔产枳椇果梗、枳椇子中22种金属元素

建立微波消解-电感耦合等离子体质谱(ICP-MS)法同时分析枳椇果梗、枳椇子中Be、Mg、Al、Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Zn、As、Sr、Mo、Ag、Cd、Sn、Sb、Ba、Tl、Pb等22种元素的含量。样品经微波消解后,利用ICP-MS测定上述22种元素,通过标准曲线计算其含量。实验结果表明,22种元素在其线性范围内线性关系良好,r值0.995;检出限为0.0007～1.0713μg/L;重复性的相对标准偏差(RSD)3%;精密度的相对标准偏差(RSD)7%;回收率为81.14%～112.91%。该方法灵敏度高,重复性好,分析速度快,适用于枳椇果梗、枳椇子中22种元素的含量测定。