The effects of using aqueous nanofluids containing covalently functionalized graphene nanoplatelets with triethanolamine (TEA-GNPs) as novel working fluids on the thermal performance of a flat-plate solar collector (FPSC) have been investigated. Water-based nanofluids with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% of TEA-GNPs with specific surface areas of 300, 500, and 750 m2/g were prepared. An experimental setup was designed and built and a simulation program using MATLAB was developed. Experimental tests were performed using inlet fluid temperatures of 30, 40, and 50 °C; flow rates of 0.6, 1.0, and 1.4 kg/min; and heat flux intensities of 600, 800, and 1000 W/m2. The FPSC’s efficiency increased as the flow rate and hea

The particle-hole state densities have been calculated for 232Th in
the case of incident neutron with  ,  1 Z Z T T T T and   2 Z T T .
The finite well depth, surface effect, isospin and Pauli correction are
considered in the calculation of the state densities and then the
transition rates. The isospin correction function ( ) iso f has been
examined for different exciton configurations and at different
excitation energies up to 100 MeV. The present results are indicated
that the included corrections have more affected on transition rates
behavior for        , , and    above 30MeV excitation energy

The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin