The impact of competing time delays in coupled stochastic systems

We study the impact of competing time delays in coupled stochastic synchronization and coordination problems. We consider two types of delays: transmission delays between interacting elements and processing, cognitive, or execution delays at each element. We establish the scaling theory for the phase boundary of synchronization and for the steady-state fluctuations in the synchronizable regime. Further, we provide the asymptotic behavior near the boundary of the synchronizable regime. Our results also imply the potential for optimization and trade-offs in synchronization problems with time delays.     

Self-organized critical model for protein folding

The major factor that drives a protein toward collapse and folding is the hydrophobic effect. At the folding process a hydrophobic core is shielded by the solvent-accessible surface area of the protein. We study the fractal behavior of 5526 protein structures present in the Brookhaven Protein Data Bank. Power laws of protein mass, volume and solvent-accessible surface area are measured independently. The present findings indicate that self-organized criticality is an alternative explanation for the protein folding. Also we note that the protein packing is an independent and constant value because the self-similar behavior of the volumes and protein masses have the same fractal dimension. This power law guarantees that a protein is a complex system. From the analyzed data, q-Gaussian distributions seem to fit well this class of systems.     

Scaling characteristics of ocean wave height time series

Fluctuations in the significant wave height can be quantified by using scaling statistics. In this paper, the scaling properties of the significant wave height were explored by using a large data set of hourly series from 25 monitoring stations located off the west coast of the US. Detrended fluctuation analysis (DFA) was used to investigate the scaling properties of the series. DFA is a robust technique that can be used to detect long-range correlations in nonstationary time series. The significant wave height data was analyzed by using scales from hourly to monthly. It was found that a common scaling behavior can be observed for all stations. A breakpoint in the scaling region around 4-5 days was apparent. Spectral analysis confirms this result. This breakpoint divided the scaling region into two distinct parts. The first part was for finer scales (up to 4 days) which exhibited Brown noise characteristics, while the second one showed 1/f noise behavior at coarser scales (5 days to 1 month). The first order and the second order DFA (DFA1 and DFA2) were used to check the effect of seasonality. It was found that there were no differences between DFA1 and DFA2 results, indicating that there is no effect of trends in the wave height time series. The resulting scaling coefficients range from 0.696 to 0.890 indicating that the wave height exhibits long-term persistence. There were no coherent spatial variations in the scaling coefficients.     

Scaling of Prosocial Behavior in Cities

Previous research has examined how various behaviors scale in cities in relation to their population sizes. Behavior related to innovation and productivity has been found to increase per capita as the size of the city increases, a phenomenon known as superlinear scaling. Criminal behavior has also been found to scale superlinearly. Here we examine a variety of prosocial behaviors (e.g., voting and organ donation), which also would be presumed to be categorized into a single class of scaling with population. We find that, unlike productivity and innovation, prosocial behaviors do not scale in a unified manner. We argue how this might be due to the nature of interactions that are distinct for different prosocial behaviors.     

Non-neural BOLD variability in block and event-related paradigms

Block and event-related stimulus designs are typically used in fMRI studies depending on the importance of detection power or estimation efficiency. The extent of vascular contribution to variability in block and event-related fMRI-BOLD response is not known. With scaling, the extent of vascular variability in the fMRI-BOLD response during block and event-related design tasks was investigated. Blood oxygen level-dependent (BOLD) contrast data from healthy volunteers performing a block design motor task and an event-related memory task requiring performance of a motor response were analyzed from the regions of interest (ROIs) surrounding the primary and supplementary motor cortices. Average BOLD signal change was significantly larger during the block design compared to the event-related design. In each subject, BOLD signal change across voxels in the ROIs had higher variation during the block design task compared to the event-related design task. Scaling using the resting state fluctuation of amplitude (RSFA) and breath-hold (BH), which minimizes BOLD variation due to vascular origins, reduced the within-subject BOLD variability in every subject during both tasks but significantly reduced BOLD variability across subjects only during the block design task. The strong non-neural source of intra- and intersubject variability of BOLD response during the block design compared to event-related task indicates that study designs optimizing for statistical power through enhancement of the BOLD contrast (for, e.g., block design) can be affected by enhancement of non-neural sources of BOLD variability.     

HL-1装置等离子体特性的初步研究

HL-1装置在环向磁场2.3T下运行,获得135kA平衡稳定等离子体,平顶时间160ms。实验表明,环向磁场杂散分量约为纵场的万分之一,导体壳和平衡场基本上能保证等离子体的平衡。观察到的电子温度约500eV,平均电子密度2.8×10~(13)cm~(-3),能量约束时间10ms,有效电荷数小于3,最低稳定运行安全因子2.5,最长放电持续时间1040ms。在对MHD稳定性进行观察的基础上,确定了稳定运行区域;极限密度服从Murakami定标律。     

氢同位素球形靶丸在其相应高能离子轰击下的消融

本文采用跨音速中性气体屏蔽模型,得到了氢同位素球形靶丸在其相应高能离子轰击下的消融率G_(is)及其定标律,s可为氢或氘。计算表明,当离子与电子的未扰态能量E_(0s)/E_(0e)~2≥1.5时,G_(is)/G_(es)≥20％,G_(es)为靶丸在等离子体电子轰击下的消融率。因此,当聚变实验有中性粒子束注入加热时,需考虑高能离子轰击对靶丸消融的影响。这也为此情况下靶丸消融强化提供了一种解释。     

非对称相异性矩阵的一种非度量多维尺度变换

本文将Okada ＆ Imaizumi等的模型加以推广,提出了一种用于处理非对称相异性矩阵的非度量多维尺度变换新方法.在模型中,我们假定每个研究对象可以表示为Minkowski度量空间中的一个点和一个超球面,超球面的半径揭示了相应研究对象的非对称性.文中我们给出了一种计算点坐标及球半径的算法.该算法使用了代数方法,比原来的方法收敛速度快,节省计算时间.最后给出了一个数值例子.