Rotating cylinder electrode (RCE) is used . in weight loss technique , the salinity is 200000 p.p.m, temperatures are (30,5060,7080Co) . the velocity of (RCE) are (500,1500,3000 r.p.m). the water cut (30% , 50%). The corrosion rate of carbon steel increase with increasing rotating cylinder velocity. In single phase flow, an increase im rotational velocity from 500 to 1500 r.p.m, the corrosion rate increase from 6.88258 mm/y to 10.11563 mm/y respectively.

   In multiphase flow, an increase in (RCE) from 500 to 1500 r.p.m leads to increase in corrosion rate from 0.786153 to 0.910327 mm/y respectively. Increasing brine concentration leads to increase in corrosion rate at water cut 30%.

The apoptotic activity of methionine γ- lyase from Pseudomonas putida on cancer cell lines was indicated by measuring the concentration of cytochrome c in the supernatants of cell lines. The result revealed high concentration of cytochrome c in the supernatants of cancer cell lines (RD, AMGM and AMN3) respectively while the concentration of anti-apoptotic protein (Bcl-2) was very low.

his analysis aims to establish Riemann-Liouville derivation andintegral operators regarding the recently suggested seven-parameter Mittag-Leffler function then investigates the corresponding special cases. In addition,certain notable results associated with those new operators have been dis-cussed

Studies in Iraq that concerned identification of free-living Protozoa (sarcodina) are scarce; so the current study deals with these protozoan communities inhabiting the Tigris River in Baghdad City. Sampling collection stations have been selected at each of AL-Gheraiˈat and AL-Adhamiyah area adjacent to the river. Monthly intervals sampling with three samples were collected from each station from June to September 2020. Total of 23 sarcodina taxa were listed, out of them 5 taxa were new record to the Tigris River in Baghdad: Difflugia urceolata Carter, 1864 (Arcellinida, Difflugiidae), Heleopera perapetricola Leidy, 1879 (Arcellinida, Heleoperidae), Rhaphidiophrys pallida F.E. Schulze, 1874 (Centrohelida, Raphidiophridae), Saccamoeba sp

The plant Papaver rhoeas ,which belongs to family Papaveraceae and known as common poppy is wildly grown in Iraq .It was used in traditional medicine in wide range of diseases including inflammation, diarrhea, sleep disorders, treatment of cough, analgesia, and also to reduce the withdrawal signs of opioid addiction.

The project provide the first comprehensive research done in Iraq to study the phytochemical and the methods of extraction and separation of alkaloids from Papaver rhoeas wildly grown in Iraq .The plant was harvested in April 2019 from Zurbatiya is an Iraqi town located at the northeast of Waist province in Iraq.The collected plant was washed thoroughly, dries under shade, and grounding in a mechani

         Certain cyclic amine derivatives of metronidazole via acetate spacer were prepared. Cyclic amines used are piperidine and piperazine to improve the physicochemical properties and reduce some of metronidazole side effects. This is believed to be done by modification of its structural features to get prodrugs with improved properties over that of metronidazole. The present work includes esterification of metronidazole with choroacetic acid, N-alkylation of the cyclic amines by the halogenated ester and characterization of their structures by spectral(UV and IR) and elemental(CHN)analysis.The melting points, degree of solubilities and partition coefficients were also determined. Both metronid

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur