Long memory of price-volume correlation in metal futures market based on fractal features

An empirical test on long memory between price and trading volume of China metals futures market was given with MF-DCCA method. The empirical results show that long memory feature with a certain period exists in price-volume correlation and a fittther proof was given by analyzing the source of multifractal feature. The empirical results suggest that it is of important practical significance to bring the fractal market theory and other nonlinear theory into the analysis and explanation of the behavior in metal futures market.

Exploring the relationship between fractal features and bacterial essential genes

Essential genes are indispensable for the survival of an organism in optimal conditions.Rapid and accurate identifications of new essential genes are of great theoretical and practical significance.Exploring features with predictive power is fundamental for this.Here,we calculate six fractal features from primary gene and protein sequences and then explore their relationship with gene essentiality by statistical analysis and machine learning-based methods.The models are applied to all the currently available identified genes in 27 bacteria from the database of essential genes（DEG）.It is found that the fractal features of essential genes generally differ from those of non-essential genes.The fractal features are used to ascertain the parameters of two machine learning classifiers：Na¨？ve Bayes and Random Forest.The area under the curve（AUC） of both classifiers show that each fractal feature is satisfactorily discriminative between essential genes and non-essential genes individually.And,although significant correlations exist among fractal features,gene essentiality can also be reliably predicted by various combinations of them.Thus,the fractal features analyzed in our study can be used not only to construct a good essentiality classifier alone,but also to be significant contributors for computational tools identifying essential genes.

Assessment of glaucoma using extreme learning machine and fractal feature analysis

Dear Sir,Iam Dr.Kavitha S,from the Department of Electronics and Communication Engineering,Nandha Engineering College,Erode,Tamil Nadu,India.I write to present the detection of glaucoma using extreme learning machine(ELM)and fractal feature analysis.Glaucoma is the second most frequent cause of permanent blindness in industrial

Fractal Characteristic of Soil in Typical Debris Flow-Triggering Region:A Case Study in Jiangjia Ravine of Dongchuan, Yunnan

The structural features of soil in debris flow-triggering region play an important role in the formation and evolution of debris flow. In this paper, a case study on the fractal of soil particle-size distribution （PSDFs） and pore-solid （PSFs） in Jiangjia Ravine was conducted. The results revealed that the soil in Jiangjia Ravine had significant fractal features and its PSDF and PSF had the same variation trend despite different type of soils in debris flow-triggering region： residual soil （RS） 〉 debris flow deposit （DFD）~clinosol （CL）, their fractal dimension of PSDFs are respectively between 2.62 and 2.96, 2.52 and 2.68, 2.37 and 2.52; and the fractal dimension of PSFs are respectively between 2. 75 and 2.95, 2. 57 and 2. 72, 2.59 and 2.64. The fractal dimension of soil reflected its complexity as a self-organizing system and was closely related to the evolution of soil in debris flow- triggering region.

Description of desertification evolution in Fuxin district of Liaoning province based on fractal theory

Desertification is the most serious environmental problem in the world today. Fractal feature of granularity composition was studied by using the fractal theory in view of desertification soil in Fuxin district, thereby evolution patterns of desertification was promulgated. The result shows that the self-formation degree of the developing desertification areas is higher than the relatively steady desertification areas. Evolution of desertification is beginning of forming sandy soil of framework composition, and then the sandy soil be came complex by the effect of environment, climate and anthropo-activity.

Effects of Vegetation Cover and Rainfall Intensity on Sediment-Bound Nutrient Loss,Size Composition and Volume Fractal Dimension of Sediment Particles

Vegetation and rainfall are two important factors affecting soil erosion and thus resulting in nutrient loss in the Chinese Loess Plateau.A field experiment was conducted to investigate the effects of rainfall intensities(60,100 and 140 mm h-1) and vegetation(Caragana korshinskii) coverages(0%,30% and 80%) on soil loss,nutrient loss,and the composition and volume fractal dimension of eroded sediment particles under simulated rainfall conditions.The results showed that vegetation cover,rainfall intensity and their interaction all had significant effects on sediment transport and the sedimentbound nutrient loss.Higher rainfall intensity and lower coverage led to higher sediment and nutrient losses.Positive linear relationships were observed between soil loss and nutrient loss.The treatments showed more significant effects on the enrichment ratio(ER) of nitrogen(ERN) than organic matter(EROM) and phosphorus(ERP).Compared with the original surface soil,the eroded sediment contained more fine particles.Under the same coverage,the clay content significantly decreased with increasing rainfall intensity.The ER of sediment-bound nutrients was positively correlated with that of clay,suggesting that the clay fraction was preferentially eroded and soil nutrients were mainly adsorbed onto or contained within this fraction.There were increments in the fractal dimension of the sediment particles compared to that of the original surface soil.Moreover,the fractal dimension was positively correlated with clay,silt,and sediment-bound OM,N,and P contents,whereas it was negatively correlated with sand content.This study demonstrated that fractal dimension analysis can be used to characterize differences in particle-size distribution and nutrient loss associated with soil erosion.

Insights into Pore Structure and Fractal Characteristics of the Lower Cambrian Niutitang Formation Shale on the Yangtze Platform,South China

Shales from the Lower Cambrian Niutitang Formation of Yangtze Platform have been widely investigated due to its shale gas potential.To better illustrate the pore structure and fractal characteristics of shale,a series of experiments were conducted on outcrop samples from the Lower Cambrian Niutitang Formation on Yangtze Platform,including X-ray diffraction(XRD),field-emission scanning electron microscopy(FE-SEM) and low-temperature nitrogen adsorption.Frenkel-Halsey-Hill(FHH) model was adopted to calculate the fractal dimensions.Furthermore,the relationships between fractal dimensions and pore structure parameters and mineral composition are discussed.FE-SEM observation results show that interparticle pores are most developed in shale,followed by intraparticle pores.This study identified the fractal dimensions D1(ranging from 2.558 0 to 2.710 2) and D2(ranging from 2.541 5 to 2.765 2).The pore structure of the Niutitang Formation shale is primarily controlled by quartz and clay content.Fractal dimensions are able to characterize the pore structure complexity of Niutitang Formation shale because D1 and D2 correlate well with average pore diameter and quartz content.