Islamic Azad University

About: Islamic Azad University is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Catalysis. The organization has 83635 authors who have published 113437 publications receiving 1275049 citations. The organization is also known as: Azad University.

Developing a new correlation to estimate the thermal conductivity of MWCNT-CuO/water hybrid nanofluid via an experimental investigation

Abstract: The enhancement of thermal conductivities of water in the presence of copper oxide and multiwalled carbon nanotubes is investigated for the first time. Hybrid nanofluid is a homogenous mixture of multiwalled carbon nanotubes-CuO particles suspended in water as the base fluid. The thermal conductivity of mixture is measured by KD2 Pro instrument. All thermal conductivity measurements are repeated three times in the range of 25–50 °C. A hot water bath is used to stabilize the temperature at 25, 30, 35, 40, 45 and 50 °C during the measurements. The results show that the thermal conductivity of the nanofluid increases at more solid concentration. Furthermore, the thermal conductivity of the nanofluid increases with the temperature; however, this increase is by far more noticeable in higher solid concentrations compared with the lower ones. Moreover, it is tried to propose a new correlation for predicting the thermal conductivity of the present nanofluid at different temperatures and volume fractions. The highest enhancement percentage was observed as 30.38% for the state of T = 50 °C and φ = 0.6%. However, the enhancement percentages were achieved as 25.57–30.38 for the state of φ = 0.6% at T = 25–50 °C, respectively.

Solar energy forecasting based on hybrid neural network and improved metaheuristic algorithm

Abstract: Prediction of solar power involves the knowledge of the sun , atmosphere and other parameters, and the scattering processes and the specifications of a solar energy plant that employs the sun's energy to generate solar power . This prediction result is essential for an efficient use of the solar power plant, the management of the electricity grid, and solar energy trading. However, because of nonlinear and nonstationary behavior of solar power time series, an efficient forecasting model is needed to predict it. Accordingly, in this paper, we propose a new forecast approach based on combination of a neural network with a metaheuristic algorithm as the hybrid forecasting engine. The metaheuristic algorithm optimizes the free parameters of the neural network. This approach also includes a 2‐stage feature selection filter based on the information‐theoretic criteria of mutual information and interaction gain, which filters out the ineffective input features. To demonstrate the effectiveness of the proposed forecast approach, it is implemented on a real‐world engineering test case. Obtained results illustrate the superiority of the proposed approach in comparison with other prediction methods.

Linezolid: a review of its properties, function, and use in critical care.

Abstract: Linezolid can be considered as the first member of the class of oxazolidinone antibiotics. The compound is a synthetic antibiotic that inhibits bacterial protein synthesis through binding to rRNA. It also inhibits the creation of the initiation complex during protein synthesis which can reduce the length of the developed peptide chains, and decrease the rate of reaction of translation elongation. Linezolid has been approved for the treatment of infections caused by vancomycin-resistant Enterococcus faecium, hospital-acquired pneumonia caused by Staphylococcus aureus, complicated skin and skin structure infections (SSSIs), uncomplicated SSSIs caused by methicillin-susceptible S. aureus or Streptococcus pyogenes, and community-acquired pneumonia caused by Streptococcus pneumoniae. Analysis of high-resolution structures of linezolid has demonstrated that it binds a deep cleft of the 50S ribosomal subunit that is surrounded by 23S rRNA nucleotides. Mutation of 23S rRNA was shown to be a linezolid resistance mechanism. Besides, mutations in specific regions of ribosomal proteins uL3 and uL4 are increasingly associated with linezolid resistance. However, these proteins are located further away from the bound drug. The methicillin-resistant S. aureus and vancomycin-resistant enterococci are considered the most common Gram-positive bacteria found in intensive care units (ICUs), and linezolid, as an antimicrobial drug, is commonly utilized to treat infected ICU patients. The drug has favorable in vitro and in vivo activity against the mentioned organisms and is considered as a useful antibiotic to treat infections in the ICU.