This study carried out in animal field in the Department of animal production /Faculty of Agriculture /University of Baghdad, Al Gadria Campus. 80 Japanese quail divided into four parameters used in this study. These quails are treated with boron (B) in the diets (boric acid 16% B) with concentration 0, 50, 75, 100 mg /kg. diets for 120 hours. the following characteristics are examined: changes in the rate of body weight (BL), concentrate of hemoglobin (Hb), hematocrit (PCV%), and the ratio of heterophile to Lymphocyte (H/L ratio). The results indicated that the high levels of B led to a Significant decrease in BL and significantly increased in hematocrit PCV% with significant decrease in Hb, and increasing in the H/L ratio. The anatomy of birds showed that there are gross lesions in each of the liver and kidneys. The current study concludes that the use of B in high concentrations in the fodder of quails led to the toxic effects that lead to the physiological deterioration of birds but it was not fatal
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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