B3LYP/6-31G, DFT method was applied to hypothetical study the design of six carbon nanotube materials based on [8]circulene, through the use of cyclic polymerization of two and three molecules of [8]circulene. Optimized structures of [8]circulene have saddle-shaped. Design of six carbon nanotubes reactions were done by thermodynamically calculating (Δ S, Δ G and Δ H) and the stability of these hypothetical nanotubes depending on the value of HOMO energy level. Nanotubes obtained have the most efficient gap energy, making them potentially useful for solar cell applications.

Celery (Apium graveolens L. ; family : Apiaceae) was often used as a spice in daily food. However, this plant contains many antioxidant compounds useful for attenuating neurodegenerative disorders including Parkinson's disease. Planting celery in the form of microgreens harvested 15 days was expected to increase the content of bioactive compounds. In the current study, we intended to evaluate the neuromodulatory potential of methanol extract of celery microgreens on fruit flies (Drosophila melanogaster Meigen : family Drosophilidae ; ordo : Diptera) which were exposed to paraquat. Neuroprotective capacity was assessed by survival rate, locomotor performance, lipid peroxidation and dopamine content after being treated wi

Lead selenide PbSe thin films of different thicknesses (300, 500, and 700 nm) were deposited under vacuum using thermal evaporation method on glass substrates. X-ray diffraction measurements showed that increasing of thickness lead to well crystallize the prepared samples, such that the crystallite size increases while the dislocation density decreases with thickness increasing. A.C conductivity, dielectric constants, and loss tangent are studied as function to thickness, frequency (10kHz-10MHz) and temperatures (293K-493K). The conductivity measurements confirm confirmed that hopping is the mechanism responsible for the conduction process. Increasing of thickness decreases the thermal activation energy estimated from Arhinus equation is

        In this study the design and installation of evaporative air cooler was carried out using completely outdoor air (fresh air) according to two stage evaporative cooling principle. The laboratory equipment was installed by designing and manufacturing a cross flow plate heat exchanger, where aluminum plates used for this purpose with dimensions (50 × 30 × 40 cm). The surfaces of heat exchanger were covered by sawdust from wetted channels side, to increase the percentage of wetting these surfaces and hence improve the performance and efficiency of air cooler.

        An experimental study was carried out to estimate the performance of cooling system, where som

The weather of Iraq has longer summer season compared with other countries. The ambient temperature during this season reaches over 50 ^OC which makes the evaporative cooling system suitable for this climate. In present work, the two-stage evaporative cooling system is studied. The first stage is indirect evaporative cooling (IEC) represented by two heat exchangers with the groundwater flow rate (5 L/min). The second stage is direct evaporative cooling (DEC) which represents three pads with groundwater flow rates of (4.5 L/min). The experimental work was conducted in July, August, September, and October in Baghdad. Results showed that overall evaporative efficiency of the system (two coils with three pads each

Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

Prediction of the structural response of reinforced concrete to the time-dependent, creep and shrinkage, volume changes is complex. Creep is usually determined by measuring the change, with time, in the strain of specimens subjected to a constant stress and stored under appropriate conditions. This paper brings into view the development of creep strain for four self-compacting concrete mixes: A40, AL40, B60 and BL60 (where 40 and 60 represent the compressive strength level at 28 days and L indicates to Portlandlimestone cement). Specimens were put under sustained load and exposed to controlled conditions in a creep chamber (ASTM C512). The test results showed that normal strength Portland-limestone mixes have yielded lower ultimate c

Construction projects are complicated in nature and require many considerations in contractor selection. One of the complicated interactions is that between performance with the project size, and contractor financial status, and size of projects contracted. At the prequalification stage, the financial ‎requirements restrict the ‎contractors to meet minimum limits in financial criteria such as net worth, working capital and ‎annual turnover, etc. In construction projects, however, there are cases when contractors meet these requirements but show low performance in practice. The model used in the study predicts the performance by training of a neural network. The data used in the study are 72 of the most recent roadw