Effect of compression modalities for recovery on wrestlers’ biomarkers in one day tournament

The aim of the study was to investigate the effect of different compression modalities as to recovery enhancement on some biomarkers in wrestlers. Serum creatinine, lactic acid and glucose level were tested in elite wrestlers before a match-up, 3 minutes post-match up and 19 minutes after applying recovery compression model. The results showed insignificant differences between pre-post 3-minutes tests among research groups due to sample equality, 3-minutes and 19-minutes post match up tests showed efficacy of compression technique in enhancing recovery in sake of 160/20 mmHg compression modality with enhancement percentage of 16.614% for serum creatinine, 43.214% for lactic acid and 22.505% for glucose level. The compression band with 160/20 mmHg exceeds recovery after match-up

Helical and rotating plasma structures in the solar atmosphere

Aims. We model helical or rotating signatures in the solar atmosphere to further understand the efficiency of the equilibrium conditions, for example magnetic twist, rotation, plasma-β, and viscous effects on the life of solar helical structures. Methods. Solar rotating structures, such as tornadoes, spirals, and whirls are modelled by considering a rotating and twisted magnetic cylinder residing in an environment with a straight magnetic field. A macroscopic approach proves adequate for working on the phase speed and damping of waves in solar atmospheric structures; as such, the magnetohydrodynamic theory is implemented. In this way the second order thin flux tube approximation is used for obtaining expressions for the frequency, deceleration, and damping of torsional waves in solar plasma structures in the presence of equilibrium rotation, magnetic twist, viscosity, and gravity. Results. The dependency of the dissipation effects regarding the torsional wave in the linear regime is highlighted. The dispersion relation for axisymmetric oscillations propagating along a rotating and twisted solar cylindrical plasma structure in the presence of plasma viscosity and gravity is obtained. In this way we present explicit expressions for the oscillation and damping of torsional waves. The explicit expressions shed light on the influence of the equilibrium and environmental conditions on the speed deceleration, frequency, and damping of the torsional wave that exists in various layers of the solar atmosphere. The dispersion of the torsional wave is highly controlled by the combined effects of the rotation and the plasma-β, where when both are zero, the magnetic twist becomes significant only when the plasma resistivity comes into play. Regarding damping, the dominant actor for coronal conditions is the magnetic twist. However, since the damping time is highly dependent on the plasma-β, for photospheric conditions, the rotation becomes very significant. The damping of torsional waves is inversely proportional to the elevation of the rotating structure. This means that if the torsional wave survives through the photosphere and chromosphere, the chance for it to extend through the corona and solar wind is very high by gradually dissipating energy, which gives more opportunity for it to be observed

A new model based on gene expression programming to estimate air flow in a single rock joint

This paper is aimed to introduce and validate a gene expression programming (GEP) model to estimate the rate of air flow in triaxial conditions at various confining pressures incorporating cell pressure, air inlet pressure and air outlet pressure. To achieve the aim of this study, a series of laboratory experiments were designed and carried out and then a database comprising 47 datasets was prepared to develop new predictive models. A gene expression programming (GEP) model for prediction of air flow was proposed using the prepared datasets. In this regard, a series of sensitivity analyses were performed to choose the best GEP model. For comparison purposes, multiple regression (MR) analysis was also employed for air flow estimation. Several performance indices, i.e., coefficient of determination (CoD), mean absolute error (MAE), root mean square error (RMSE) and variance account for (VAF) were considered and calculated to evaluate the performance prediction of the developed models. Considering both training and testing datasets, the developed GEP model can provide higher performance prediction of rate of air flow in comparison to the MR model

Several non-linear models in estimating air-overpressure resulting from mine blasting

This research presents several non-linear models including empirical, artificial neural network (ANN), fuzzy system and adaptive neuro-fuzzy inference system (ANFIS) to estimate air-overpressure (AOp) resulting from mine blasting. For this purpose, Miduk copper mine, Iran was investigated and results of 77 blasting works were recorded to be utilized for AOp prediction. In the modeling procedure of this study, results of distance from the blast-face and maximum charge per delay were considered as predictors. After constructing the non-linear models, several performance prediction indices, i.e. root mean squared error (RMSE), variance account for (VAF), and coefficient of determination (R2) and total ranking method are examined to choose the best predictive models and evaluation of the obtained results. It is obtained that the ANFIS model is superior to other utilized techniques in terms of R2, RMSE, VAF and ranking herein. As an example, RMSE values of 5.628, 3.937, 3.619 and 2.329 were obtained for testing datasets of empirical, ANN, fuzzy and ANFIS models, respectively, which indicate higher performance capacity of the ANFIS technique to estimate AOp compared to other implemented methods