Molasse medium containing different concentrations of (NH4)2 SO4, (NH4)3 PO4, urea, KCI, and P2O5 were compared with the medium used for commercial production of C. utilis in a factory south of Iraq. An efficient medium, which produced 19. 16% dry wt. and 5. 78% protein, was developed. The effect of adding various concentrations of micronutrients (FeSO4, 7T20, MnSO4. 7H20, ZnSO4. 7E20) was also studied. Results showed that FeSo4. 7H20 caused a noticeable increase in both dry wt. and protein content of the yeast.

An increasing number of emerging contaminants have been detected in surface waters, sediment, soil and ground water in different locations in the world, which is a new environmental challenges need an actual concern for international scientific and legislative communities. 

   The nonprescription and huge used pharmaceuticals ibuprofen and diclofenac sodium will be focused in this study. New adsorbent developed using cheap inorganic clay material (bentonite) and organic polymer polyureaformaldehyde (PUF), the combination of these two materials gave the surface more roughness with wide active site distribution. Batch adsorption experiment performed to each pharmaceutical individually to determine the optimum separat

We studied the effect of certain environmental conditions for removing heavy metal elements from contaminated aqueous solutions (Cd, Cu, Pb, Fe, Zn, Ni, Cr) using the bacterium Bacillus subtilis to appoint the optimal conditions for removal ,The best optimum temperature range for two isolate was 30-35○C while the hydrogen number for the maximum mineral removal range was 6-7. The best primary mineral removal was 100 mg/L, while the maximum removal for all minerals was obtained after 6 hrs of Cu element time and the maximum removal efficiency was obtained after 24 hrs of Cu element. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/minute. Inoculums of 5ml/100ml which contained 1

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de