Emergence of world-stock-market network

In the age of globalization, it is natural that the stock market of each country is not independent form the other markets. In this case, collective behavior could be emerged form their dependency together. This article studies the collective behavior of a set of forty influential markets in the world economy with the aim of exploring a global financial structure that could be called world-stock-market network. Towards this end, we analyze the cross-correlation matrix of the indices of these forty markets using Random Matrix Theory (RMT). We find the degree of collective behavior among the markets and the share of each market in their structural formation. This finding together with the results obtained from the same calculation on four stock markets reinforce the idea of a world financial market. Finally, we draw the dendrogram of the cross-correlation matrix to make communities in this abstract global market visible. The dendrogram, drawn by at least thirty percent of correlation, shows that the world financial market comprises three communities each of which includes stock markets with geographical proximity

Dynamics and Dislodgment from Pore Constrictions of a Trapped Nonwetting Droplet Stimulated by Seismic Waves

Seismic waves affect fluid flow and transport processes in porous media. Therefore, quantitative understanding of the role of seismic waves in subsurface hydrodynamics is important for the development of practical applications and prediction of natural phenomena. We present a theoretical fluid dynamics model to describe how low-frequency elastic waves mobilize isolated droplets trapped in pores by capillary resistance. The ability of the theoretical model to predict the critical mobilization amplitudes (Ac) and the displacement dynamics of the nonwetting droplet are validated against computational fluid dynamics (CFD) simulations. Our theory has the advantage of rapid calculation of Ac for various scenarios. Both theory and CFD simulations show that the Ac increases with increasing wave frequency. The theoretical and computational models agree well in the low-frequency range both in terms of predicting the displacement history of the droplet and its eventual dislodgment, but their results begin to diverge with increasing wave frequency since the Hagen-Poiseuille flow approximation in the model becomes invalid. Relative to a previous viscous seismic model, our model compares more favorably to experimental observations. The model is thus appropriate for predicting trapped nonwetting droplet dynamics in and dislodgement from pore constrictions by low-frequency elastic waves

Relation between clinical features and gastric emptying time in diabetic patients

BACKGROUND: Gastroparesis is characterized by delayed gastric emptying. This pathology is usually observed in patients with diabetes. One standard approach to quantitative assessment of gastric emptying is scintigraphic study. The aim of present study was to perform scintigraphic study of gastric emptying time in patient with diabetes and to find its correlation with patients' characteristics. MATERIALS AND METHODS: Gastric emptying was assessed in 19 patients with type 2 diabetes (mean age of 61.04 ± 6.09 years) and 6 healthy volunteers. Characteristics of the patients were sex, age, duration of diabetes, blood sugar and serum HbA1c level. RESULTS: Results of present study revealed that gastric emptying half time was significantly larger in patients with type 2 diabetes as compared with healthy volunteers (P-value < 0.05). While correlation of sex, age, duration of diabetes and blood sugar with gastric emptying time was not statistically significant, HbA1c level had significant effect on gastric emptying time. CONCLUSION: Results of this prospective study indicated that level of serum HbA1c is an effecting factor on gastric emptying time in patients with type 2 diabetes; however, these preliminary findings should be validated in larger and well-designed studies. Copyright © 2015 Via Medica

Analysis of the Effects of Dam Release Properties and Ambient Groundwater Flow on Surface Water‐Groundwater Exchange Over a 100‐km‐Long Reach

Hydroelectric dams often create highly dynamic downstream flows that promote surface water‐groundwater (SW‐GW) interactions including bank storage, the temporary storage of river water in the riverbank. Previous research on SW‐GW exchanges in dammed rivers has primarily been at single study sites, which has limited the understanding of how these exchanges evolve as dam releases travel downstream. This study evaluates how dam releases affect SW‐GW exchange continuously over a 100‐km distance. This is accomplished by longitudinally routing water releases through a synthetic river and modeling bed and bank fluid and solute exchange across transverse transects spaced along the reach. Peak and square dam release hydrograph shapes with three magnitudes (0.5, 1.0, and 1.5 m) were considered. The effect of four ambient groundwater flow conditions (very slightly losing, neutral, and two gaining from the perspective of the river) was evaluated for each dam release scenario. Both types of dam release shapes cause SW‐GW interaction over the entire 100‐km distance, and our results show that square type releases cause bank storage exchange well beyond this distance. Strongly gaining conditions reduce the amount of exchange and allow flushing of river‐sourced solute out of the bank after the dam pulse has passed. Both neutral and losing conditions have larger fluid and solute flux into the bank and limit the amount of solute that returns to the river. Our results support that river corridors downstream of dams have increased river‐aquifer connectivity and that this enhanced connectivity can extend at least 100 km downstream

Integrating biological knowledge into variable selection : an empirical Bayes approach with an application in cancer biology

Background: An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results: We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions: The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge

The Role of Eddies inside Pores in the Transition from Darcy to Forchheimer Flows

We studied the role of intra-pore eddies, from viscous to inertial flows, in modifying continuum-scale flow inside pores. Flow regimes spanning Reynolds Number Re ∼ 0 to 1350 are divided into three zones - one zone follows Darcy flow, and the other two zones describe non-Darcy or Forchheimer flow. During viscous flows, i.e., Re \u3c 1, stationary eddies occupy about 1/5 of the pore volume. Eddies grow when Re \u3e 1, and their growth leads to the deviation from Darcy\u27s law and the emergence of Forchheimer flow manifested as a characteristic reduction in the apparent hydraulic conductivity Ka. The reduction in Ka is due to the narrowing of the flow channel which is a consequence of the growth in eddies. The two zones of Forchheimer flow correspond to the changes in rate of reduction in Ka, which in turn are due to the changes in eddy growth rate. Since the characteristics of Forchheimer flow are specific to pore geometry, our results partly explain why a variety of Forchheimer models are expected and needed for different porous media

Theory for Dynamic Longitudinal Dispersion in Fractures and Rivers with Poiseuille Flow

We present a theory for dynamic longitudinal dispersion coefficient (D) for transport by Poiseuille flow, the foundation for models of many natural systems, such as in fractures or rivers. Our theory describes the mixing and spreading process from molecular diffusion, through anomalous transport, and until Taylor dispersion. D is a sixth order function of fracture aperture (b) or river width (W). The time (T) and length (L) scales that separate preasymptotic and asymptotic dispersive transport behavior are T = b2/(4D m), where Dm is the molecular diffusion coefficient, and L = b4 / 48μDm ∂p / ∂x, where p is pressure and μ is viscosity. In the case of some major rivers, we found that L is ∼150W. Therefore, transport has to occur over a relatively long domain or long time for the classical advection-dispersion equation to be valid

Quality improvement of liver ultrasound images using fuzzy techniques

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. © 2016 Azadeh Bayani, Leila Shahmoradi, Mostafa Langarizadeh, Amir Reza Radmard, and Ahmadreza Farzaneh Nejad