Liquid-liquid membrane extraction technique, pertraction, using three types of solvents (methyl isobutyl ketone, n-butyl acetate, and n-amyl acetate) was used for recovery of penicillin V from simulated fermentation broth under various operating conditions of pH value (4-6) for feed and (6-8) for receiver phase, time (0-40 min), and agitation speed (300-500 rpm) in a batch laboratory unit system. The optimum conditions for extraction were at pH of 4 for feed, and 8 for receiver phase, rotation speed of 500 rpm, time of 40 min, and solvent of MIBK as membrane, where more than 98% of penicillin was extracted. 

           The plants of genus Heliotropium L. (Boraginaceae) are well-known for containing the toxic metabolites called pyrrolizidine alkaloids (PAs) in addition to the other secondary metabolites. Its spread in the Mediterranean area northwards to central and southern Europe, Asia, South Russia, Caucasia, Afghanistan, Iran, Pakistan, and India, Saudi Arabia, Turkey, and over lower Iraq, Western desert. The present study includes the preparation of various extracts from aerial parts of the Iraqi plant. Fractionation, screening the active constituent, and identification by chromatographic techniques were carried out.Heliotropium  europaeum

Three types of zeolite A were prepared from Iraqi kaoline which are 3A, 4A and 5A by ion exchange method .They were characterized by XRD and atomic absorption techniques .They were used as adsorbents to examine their applicability for H2S adsorption .The adsorption process was performed in a static form and constant volume system which constructed from stainless steel .The effect of zeolite type and temperature on the adsorption properties of H2S at -5 , 25 and 55 oC was studied .The zeolite type 5A has the highest adsorption value (79.384 µmol/g ) and the three types may be arranged in a sequence toward H2S adsorption as 5 A> 4A>3A .The amount of H2S adsorbed increased as temperature decreased from 55 to -5 for all samples. Langmuir , Fre

Retained soft tissue foreign bodies following injuries are frequently seen in the Emergency and Plastic Surgery practice. The patients with such presentations require a watchful and detailed clinical as- sessment to overcome the anticipant possibility of missing them. However, the diagnosis based on the clinical evaluation is usually challenging and needs to be supported by imaging modalities that are suboptimal and may fail in identifying some types of foreign bodies. Owing to that, serious complications such as chronic pain, infection, and delayed wound healing can be faced that necessitate a prompt intervention to halt those detrimental consequences. The classical method of removal is a surgical exploration which is not free of risks.

The genus Bacillus bacterium isolated from soil and tests their ability to produce glutamic acid, the bacteria are diagnosed by traditional methods and VITEK-2 system. And we studied the optimal conditions for production and try to improve the productivity of the isolation by manipulating the components of the production medium and of the circumstances environmental of production medium. There is 43 isolates of the 70 bacterial isolates belonging to the genus Bacillus depending on phenotypic characteristics of the colonies and microscopic characteristics and found that 13 isolated revert to species B.subtilis depending on physiological and biochemical characteristics. As well as on microscopic and biochemical tests, 13 isolates were subj

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

Conventional concretes are nearly unbendable, and just 0.1 percent of strain potential makes them incredibly brittle and stiff. This absence of bendability is a significant cause of strain failure and has been a guiding force in the production of an elegant substance, bendable concrete, also known as engineered cement composites, abbreviated as ECC. This type of concrete is capable of displaying dramatically increased flexibility. ECC is reinforced with micromechanical polymer fibers. ECC usually uses a 2 percent volume of small, disconnected fibers. Thus, bendable concrete deforms but without breaking any further than conventional concrete. This research aims to involve this type of concrete, bendable concrete, that will give solut

Conventional concretes are almost unbending, and even a small amount of strain potential leaves them brittle. This lack of bendability is a major source of strain loss, and it has been the main goal behind the development of bendable concrete, often known with engineered ce ment composites, or ECC. This form of concrete has a lot more flexibility than regular concrete. Micromechanical polymer fibers are used to strengthen ECC. In most cases, ECC uses a 2% amount of thin, separated fibers. As a result, bendable concrete deforms but unlike traditional concrete, it does not crack. This study aims to include this kind of concrete, bendable concrete, which can be used to solve concrete problems. Karasta (CK) and Tasluja (CT) Portland Lime

This study was performd on 50 urine specimens of patients with type 2 diabetes, in addition, 50 normal specimens were investigated as control group. The activity rate of maltase in patients (6.40±2.17) I.U/ml and activity rate of maltase in normal (0.44±0.20)I.U/ml. The results of the study reveal that maltase activity of type 2 diabetes patient's urine shows significant increase (P<0.01) compare to normal.