The aim of this study is to determine the organic and inorganic components of bile and gallstones in Iraqi patients. Forty seven patients were included in this study with mean age (53+7) years and BMI (30.82+4.18) Kg/m2. Bile was classified according to its corresponding stones into: Bile of Mixed stones and Bile of pigment stones. IR spectra were studied for both types of stones and their bile in addition to biochemical analysis for organic and inorganic components. The organic components include: (cholesterol, bilirubin, bile salts, and phospholipids), while inorganic components include salts of: (calcium, phosphorus, iron, cupper and magnesium). The results reveal to there was significant low levels (p<0.005) of bile salts and phospholipids in bile of patients with mixed stones in comparison to their levels in bile of pigment stones ( p<0.001). There is significant increase in the salts levels of calcium, phosphorus, iron, cupper, magnesium, and bilirubin, in bile of pigment stones as compared to their levels in mixed stones bile. It was concluded that most types of stones that are formed in Iraqi patients are mixed stones when cholesterol is the main component and pigment stones are more less incidence to occur when bilirubin salts form their main component and they are mostly tend to occur in hemolytic diseases such as: sickle cell anemia, thalassaemia and so on .
We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure
Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.
This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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