miRNAs regulate protein abundance and control diverse aspects of cellular processes and biological functions in metabolic diseases, such as obesity and diabetes. Lethal-7(Let-7) miRNAs specifically target genes associated with diabetes and have a role in the regulation of peripheral glucose metabolism. The present study aimed to describe the gene expressions of the let-7a gene with the development of diabetes in Iraq and the difference in the expression of this gene in patients with diabetes and healthy individuals. The association between age and gender with the development of diabetes was studied in this study and the results were compared with those of healthy individuals in the group of control. Based on the obtained results, there was a lack in the mean of gene expression level (ΔCt) in patients, compared to controls. Moreover, the gene expression folding (2-ΔΔCt) of the let-7a reflects significant differences in terms of gene expression between groups of patients and controls, and the level of let-7a expression was reported to be 12.97 in patients with diabetes. On the other hand, significant difference was observed in terms of age and gender between diabetic patients and controls. The findings suggest that diabetes can affect individuals in all age groups and occur regardless of gender in both males and females. Based on the obtained results in this study, the gene expression level of miRNA let-7a was lower in diabetic patients compared to healthy individuals in the group of control. This also reflects differences in the gene expression fold (2-ΔΔCt) of gene let-7a between both groups of patients and controls. Keywords: Gene expression, Diabetes, Micrornalet-7a
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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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Bipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv
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Al-Naymi, N.A.Sh., H.A.S. AL-Nuaimi and M.R. Nashaat. 2022. Toxicity Stress of the Durah Power Plant Ash and its Effect on the Alga Chlorococcum humicola (Naeg) Rabenhorst 1868. Arab Journal of Plant Protection, 40(2): 188-192. https://doi.org/10.22268/AJPP-040.2.188192 This study illustrates the acute toxic effect of ash released from Durah power plant (DPP) on the biology of the phytoplankton species Chlorococcum humicola in Iraq. The results showed that the median lethal concentration for killing 50% of the Alga population (LC50) was 0.15 and 0.13 ppt (parts per thousand) for 24 and 48 hours exposure to crude ash concentrations, respectively. In contrast, no LC50 value was recorded for 72 and 96 hrs after exposure. The reduction
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Karst aquifers in semi-arid regions are vital yet exceptionally vulnerable lifelines. This study investigates how tectonic, geomorphological, and climatic factors control the dynamics of karst springs in the El Menzel Causse (Middle Atlas, Morocco). Using an integrated approach that combines field investigations, remote sensing, and quantitative hydro-climatic analysis, we identify the mechanisms driving the system’s severe decline. Results indicated that the structural architecture of the major fault systems in the North Middle Atlas Fault (NMAF) and the Median Middle Atlas Fault (MMAF), governs the spatial distribution of more than 50 springs, which occur preferentially within highly permeable fault damage zones. However, the aquifer is
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