Furfural is a toxic aromatic aldehyde that can cause a severe environmental problem especially the wastewater drown from petroleum refinery units. In the present work, a useless by-product from local furniture manufacturing industry; sawdust was used as raw material for the preparation of activated carbon which is chemically activated with phosphoric acid. The effect of adsorption variables which include initial pH of solution (2-9), agitation speed (50-250) rpm, agitation time (15-120) min, initial concentration of furfural (50-250) ppm, and amount of adsorbent material (0.5-2.5) g for the three adsorbents used (prepared activated carbon, commercial activated carbon and raw sawdust) were investigated in a batch process

This study included isolation of some active materials from Curcuma longa such as tannins, saponins and volatile oils with percentage of 59%, 31%, and 9% respectively. Also the study included the determination of minerals in Curcuma longa such as " Na, Ca and K" using Flame photometer. The concentrations of these minerals were (14 ppm),(10 ppm) and )76 ppm) respectively. The anti-bacterial activity study was performed for the active materials isolated from Curcuma longa against two genus of pathogenic bacteria, Escherichia Coli and Staphylococcus aurous by using agar-well diffusion method. It appeared from this study that all of the extraction have inhibitory effect on bacteria was used. The inhibition zone diameter varies with

     Water treatment plants play an important role in the purification and distribution of safe drinking water to the public. The present study focused on the performance assessment of the Al-Rasheed water treatment plant [ARWTP]. The main objectives of the assessment were to determine the efficiency of various plant units as well as the quality of inlet water from the Tigris River. Results obtained from the collected data indicated the presence of high concentrations of soluble nitrate and phosphate ions in the filtered water. The removal efficiency of alkalinity, EC, total hardness, SO₄, Cl, NO₃ and PO₄ were found to be (+11.05%), (-0.67%), (-29.33%), (-2.64%), (-6.25%), (-32.13%), and (0%) respecti

In order to evaluate the effect of seed size, plant growth regulators and some chemical materials on seed vigour and seedling growth of rice (Oryza sativa L.) an experiment was conducted in 2015 at Laboratories of Agriculture and Marshes College, University of Thi-Qar. Factorial experiment in CRD was used with four replications in two factors. The first factor included three seed sizes (4.6-5.1, 5.2-5.7 and 5.8-6.3 mm). The second factor was seeds soaking treatments (KNO3 6 gl-1, CaCl2 20 gl-1, salicylic acid 20 mg l-1, cytokinin 40 mg l-1, gibberllic acid 400 mg l-1, ascorbic acid 40 mg l-1 and seeds soaked in distilled water). The results showed that the largest seed size influenced significantly and gave the higher averages of germinatio

Trace Elements (Cd, Pb, Cu, Zn, Ni) level were examined in hair of donors from industrial areas, cities and village, and in permanent contact with a polluted workplace environment in lattakia. Hair sample were analyzed for their contents of the trace elements by inductivity coupled plasma- mass spectrometer (ICP- MS). It was found that the contents of (Cd, Pb, Cu, Zn, Ni) in the hair were significantly higher in the industrial areas and cities, while in the village had the lower concentration of elements. Correlation coefficients between the levels of the elements in hair found in this study showed that hair is a good indicator of Environmental Pollution.

Feature selection algorithms play a big role in machine learning applications. There are several feature selection strategies based on metaheuristic algorithms. In this paper a feature selection strategy based on Modified Artificial Immune System (MAIS) has been proposed. The proposed algorithm exploits the advantages of Artificial Immune System AIS to increase the performance and randomization of features. The experimental results based on NSL-KDD dataset, have showed increasing in performance of accuracy compared with other feature selection algorithms (best first search, correlation and information gain).