^210Pbex depth distribution in soil and calibration models for assessment of soil erosion rates from ^210Pbex measurements

Throughout the past decade, the potential for using nuclear weapon-produced 137Cs ( half-life 30.2 a) fallout to quantify soil erosion rates on both cultivated and uncul- tivated lands for medium-term timescales (≈ 40 a) has been successfully demonstrated in a wide range of envi- ronments in different regions of the world[1—6]. Because in difficulties of distinguishing Chernobyl-derived compo- nent from total 137Cs input in many parts of Europe, and in measuring low activity samples of…     

Research progress in nonlinear analysis of heart electric activities

1INTRODUCTION THE WORLD IS NONLINEAR,AND THE HUMAN LIFE ACTIVITY IS ALSO NONLINEAR.FROM THE VIEWPOINT OF SYSTEM,HUMAN BEINGS(OR THE OTHER HIGHER ANIMAL)ARE THE MOST COM-PLEX SYSTEM IN THE NATURE.FOR SUCH A PHYSIOLOGICAL SYS-TEM WITH THE UTTERMOST COMPLEXI…     

小型化体外冲击波碎石机

本文介绍了一种新型的使用B型超声波检测仪定位的小型化体外冲击波碎石机。利用该机成功地进行了正规的动物实验,对184例泌尿系结石病人进行了治疗,成功率为97％,它可与大型碎石机相媲美,并且该机成本低,操作方便,受到了医生和病人的欢迎。     

Soil Erosion Spatial Distribution Character of Sloping Field in the Sichuan Hilly Basin： Taking a Cultivated Slope in Neijiang as Example

0IntroductionNeijiang City locates in the south of The SichuanHilly Basin.The Sichuan Hilly Basin is underlainby horizontally bedded Mesozoic mudstones,siltstonesand sandstones.Purple soils developed on these rapidlyweathering rocks are widely distributed across the basin.According to second state soil erosion surveys based onremote sensing,the soil erosion rates in local area aretypicallyinthe range of3000-5000t·km-2·a-1[1,2].Inthe Sichuan Hilly Basin,one sloping field may is com-pose…     

Nonlinearity degree of short-term heart rate variability signal

A nonlinear autoregressive (NAR) model is built to model the heartbeat interval time series and the optimum model degree is proposed to be taken to evaluate the nonlinearity degree of heart rate variability (HRV). A group of healthy persons are studied and the results indicate that this method can effectively get nonlinear information from short (6—7 min) heartbeat series and consequently reflect the degree of heart rate variability, which supplies convenience in clinical application. Finally, a comparison with the traditional time domain method shows that the NAR model method can reflect the complexity of the whole signal and lessen the influence of noise and instability, in the signal.     

Interleaving distribution of multifractal strength of 16-channel EEG signals

Muitifractai characteristics of 16-channel human electroencephalogram (EEG) signals under eye-closed rest are analyzed for the first time. The result shows that the EEGs from the different sites on the scalp have different muitifractai characteristics and the muitifractai strength value △α exhibits a kind of interleaving and left-right opposite distribution on scalp. This distribution rule is consistent with the localization of function and the iateralization theory in physiology. So △α can become an effective parameter to describe the brain potential character. And such a △α stable distribution rule on sites of the scalp means a classic cerebral cortex active state.     

Growth of decagonal quasicrystal phase in laser resolidified Al72Ni12Co16

An ultra-high temperature gradient directional solidification process produced by a widened laser beam was adopted to achieve the directionally solidified microstructure of the stable decagonal quasicrystal phase in Al72Ni12Co16 alloy. X-ray, SEM, TEM and optical microscopy techniques were used to investigate the microstructures and identify the phase. The directionally solidified decagonal quasicrystal showed the facet morphology and grew in lateral growth mode. The unusual periodic and quasiperiodic atomic structures of the decagonal quasicrystal and the epitaxial growth in the melt pool were considered to be the key factors influencing the growth morphology. The experimental results were consistent with the Toner's theoretical atomistic growth model.     

多岩性信息融合在砂泥岩孔隙度预测中的应用

储层孔隙度是表征储油物性、建立各类地质模型的重要参数。支持向量回归机(SVR)凭借良好的非线性回归能力,在孔隙度预测中开始广泛应用。由于不同岩性的储层孔隙类型不同,孔隙度结构也存在较大差异,导致该方法的实际应用效果仍不理想。针对上述问题,在孔隙度预测模型中考虑了岩性信息,将样本岩性转化为一种与岩性变化相关性好的属性值,以此构造一种新的预测模型。使用网格粗选和网格精选相结合的方法,优选模型参数。网格粗选确定最优解的近似范围,网格精选可以在局部区间搜索到最优解。结果表明:利用优选参数建立的预测模型,在实际资料预测结果中,加入岩性信息可以提高储层孔隙度的预测精度,该方法可行。