SAPO-11 is synthesized from silicoaluminophosphate in the presence of di-n-propylamine as a template. The results show that the sample obtained has good crystallinity, 396m²/g BET surface area, and 0.35 cm³/g pore volume. The hydroisomerization activity of (0.25)Pt (1)Zr (0.5)W/SAPO-11 catalyst was determined using n-decane and base oil. All hydroisomerization experiments of n-decane were achieved at a fixed bed plug flow reactor at a temperature range of 200-275°C and  LHSV 0.5-2h^-1.  The results show that the n-decane conversion increases with increasing temperature and decreasing LHSV, the maximum conversion of 66.7 % was achieved at temperature 275°C and LHSV of 0.5 h^-1

The technology of subsurface soil water retention (SWRT) uses a polyethylene ‎trough that is fixed under the root zone of the plant. It is a modern technology to increase the values of water ‎use efficiency, plant productivity and saving irrigation water by applying as little irrigation water ‎as possible. This study work aims at improving the crop yield and water use efficiency of a cucumber plant with less applied irrigation water by installing membrane trough below the soil surface. The field experiment was conducted in the Hawr Rajab District of ‎Baghdad Governorate in Winter 2018 for testing various trickle irrigation ‎systems. Two agricultural ‎treatment plots were utilized in a greenhouse for the compa

This research is devoted to investigating the thermal buckling analysis behaviour of laminated composite plates subjected to uniform and non-uniform temperature fields by applying an analytical model based on a refined plate theory (RPT) with five unknown independent variables. The theory accounts for the parabolic distribution of the transverse shear strains through the plate thickness and satisfies the zero-traction boundary condition on the surface without using shear correction factors; hence a shear correction factor is not required. The governing differential equations and associated boundary conditions are derived by using the virtual work principle and solved via Navier-type analytical procedure to obtain critica

Abstract Objective: To identify correlation of elevated LDH & CRP levels with the outcomes of COVID-19. Methodology: The cross-sectional retrospective study consisted of 200 COVID-19 patients who presented at a private clinical in Baghdad, Iraq. It was carried out from February 2021 to February 2022. Data included age, gender and clinical presentation. Blood samples were taken for high sensitivity CRP and LDH in the serum. Results: Out of 200 patients, 50 were critical and 150 severe according to clinical features. LDH and CRP showed a significant increase (p=0.000) in critical patients. This group involved admission to the respiratory intensive care unit requiring mechanical ventilation than in patients with severe COVID-19 (760.5±6.3 vs.

Herein, the interfacial polymerization method has been used for the synthesis of PPy/NaVO3 composites with different compositions of NaVO3 (10 %, 20 %, 30 %, 40 % and 50 %) as an efficient electrode material for supercapacitors. The successful formation and composition of the as-prepared composites (PV1-PV5) were confirmed by FTIR, XRD, EDX, and SEM analysis. The electrochemical properties were investigated by cyclic voltammetry (CV), galvanometric charge–discharge measurement (GCD), and electrochemical impedance spectroscopy (EIS) in 0.5 M H2SO4 electrolyte. As compared to other, the PV4 composite exhibit excellent specific capacitance of 391 F g−1 at a current density of 0.75 A/g with good cycling stability of ∼59 % after 1000 cycle

Tirzepatide is a revolutionary and promising medication with a high impact in the treatment of Obesity and T2DM with their complications. Its efficacy was proven through different trials in achieving favorable weight loss and a significant reduction in glycemic index. It also treated a large diversity of related co-morbidities, including fatty liver, cardiovascular disease, dyslipidemia, and more. Tirzepatide is well tolerated, has a good safety profile, and is highly reliable and suitable for use in a population.

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

This research investigates the adsorption isotherm and adsorption kinetics of nitrogen from air using packed bed of Li-LSX zeolite to get medical oxygen. Experiments were carried out to estimate the produced oxygen purity under different operating conditions: input pressure of 0.5 – 2.5 bar, feed flow rate of air of 2 – 10 L.min^-1 and packing height of 9-16 cm. The adsorption isotherm was studied at the best conditions of input pressure of 2.5 bar, the height of packing 16 cm, and flow rate 6 Lmin^-1 at ambient temperature, at these conditions   the highest purity of oxygen by this system 73.15 vol % of outlet gas was produced. Langmuir isotherm was the best models representing the experimental data., and the m

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the