The new compounds synthesized by sequence reactions starting from a reaction of 4-hydroxybenzaldehyde with 1,5-dibromo pentane to produce dialdehyde)I( .Then compound )I( reacted with different aromatic amines to give schiff bases )IIIV(,thereafter added acetyl chloride to schiff bases to yield N-acyl derivatives)VVII(.While1,3-diazetine derivatives)VIII-X( were synthesized from the reaction of N-acyl derivatives with sodium azide.The reaction of thiourea with N-acyl compounds led to formation of thiourea derivatives (XI-XIII).Finally, the pyrimidine compounds )XIV-XVI( were synthesized by ring closure reaction of compounds(XIXIII) with diethyl malonate.The synthesized compounds were characterized by measurements of melting points,FTIR,1H-N

The main factors that make it possible to get the corrosion of reinforcing steel in concrete are chloride ions and the absorption of carbon dioxide from the environment, and each of them works with a mechanism which destroys the stable immunity of rebar in the concrete. In this work the effect of carbon dioxide content in the artificial concrete solution on the corrosion behavior of carbon steel reinforcing bar (CSRB) was studied, potentiostatically using CO₂ stream gas at 6 level of concentrations;  0.03 to 2.0  weight percent, and the effect of rising electrolyte temperature was also followed  in the range 20 to 50^ᴼ C. Tafel plots and cyclic polarization procedures were obeyed to investigate the c

This study presents an investigation about the effect of fire flame on the punching shear strength of hybrid fiber reinforced concrete flat plates. The main considered parameters are the fiber type (steel or glass) and the burning steady-state temperatures (500 and 600°C). A total of 9 half-scale flat plate specimens of dimensions 1500mm×1500mm×100mm and 1.5% fiber volume fraction were cast and divided into 3 groups. Each group consisted of 3 specimens that were identical to those in the other groups. The specimens of the second and the third groups were subjected to fire flame influence for 1 hour and steady-state temperature of 500 and 600°C respectively. Regarding the cooling process, water sprinkling was applied directly aft

High-rise structures are a significant indication in contemporary urban improvement, mainly in areas characterized by accelerated urban growth and dense population. This type of building should be designed to withstand severe load conditions. Therefore, using composite structural elements in such structures is required for stronger and durable elements. This paper introduces a finite element analysis model for Concrete Filled Stainless Steel Tubular Columns (CFSST) of (100x100) mm cross-section and (1250) mm length to inspect the impact of concrete compressive strength on the response of (CFSST). The generated model was first evaluated through a comprehensive comparison with experimental research. Then, after the model was used to s

The ratio of draft tube to reactor diameters is of decisive importance for the operation behavior of air lift loop reactors. The influence of draft tube geometry was investigated with respect to oxygen mass transfer and mixing time. The diameter ratio was varied between 0.33 and 0.80. The measurements were performed in two loop reactors with liquid capacities of 11.775 and 26.49 liters using aqueous with solutions of different coalescence behavior. The results show that there is no single diameter ratio which would produce most favorable conditions for the two process parameters. With respect to the more important requirements of aerobic cultures, i.e high oxygen mass transfer and efficient mixing, a diameter ratio between 0.5 and 0.6 is

In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

Steady natural and mixed convection flow in a square vented enclosure filled with water-saturated aluminum metal foam is numerically investigated. The left vertical wall is kept at constant temperature and the remaining walls are thermally insulated. Forced convection is imposed by providing an inlet at cavity bottom surface, and a vent at the top surface. Natural convection takes place due to the temperature difference inside the enclosure. Darcy-Brinkman-Forchheimer model for fluid flow and the two-equation of the local thermal non-equilibrium model for heat flow was adopted to describe the flow characteristics within the porous cavity. Numerical results are obtained for a wide range of width of the inlet as a fraction

Iron is one of the abundant elements on earth that is an essential element for humans and may be a troublesome element in water supplies.  In this research an AAN model was developed to predict iron concentrations in the location of Al- Wahda water treatment plant in Baghdad city by water quality assessment of iron concentrations at seven WTPs up stream Tigris River. SPSS software was used to build the ANN model. The input data were iron concentrations in the raw water for the period 2004-2011. The results indicated the best model predicted Iron concentrations at Al-Wahda WTP with a coefficient of determination 0.9142. The model used one hidden layer with two nodes and the testing error was 0.834. The ANN model coul

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad