In wireless sensor networks, it is crucial to support the collected data of sensor nodes with position information. One of the promising ways to acquire the position of unknown nodes is using a mobile anchor node that traverses throughout the network, stops at determined points, and sends its position to aid in obtaining the location of other unknown nodes. The main challenge in using mobile anchor nodes lies in designing the path model with the highest localization accuracy, shortest path length, full coverage area, and minimal power consumption. In this paper, a path model named the Arrow-Curve path model is proposed for mobile node aided localization. The proposed path model can effectively localize all the static unknown sensor positions in the network field with high positioning accuracy and low power consumption while pledging full coverage area. The sensor network is implemented using MATLAB simulation and MCU node in both static unknown nodes and the mobile anchor node. The realtime environment guarantees a realistic environmental model with reliable results. The path model is implemented in realtime in indoor and outdoor environments and compared to the H-Curve path model using a trilateration technique. The results show that the suggested path model achieves better results compared to H-Curve model. The proposed path model achieves an average position error less than that of H-Curve by 10.6% in a simulation environment, 5% in an outdoor realtime environment, and 9% in an indoor realtime environment, and it decreases power consumption by 62.65% in the simulation environment, 50% in the outdoor realtime environment, and 75% in the realtime environment in indoor compared to H-Curve.
Background: Bladder cancer is a very common malignancy worldwide; its exact cause is not known, but it is believed to be multifactorial mostly caused by genetic mutations of tumor suppressor gene, proto-oncogenes and DNA repair genes including XRCC3 Thr241Met gene polymorphism. Aim of the study: Identify the link between XRCC3 (rs861539) gene polymorphism and the susceptibility to develop urothelial carcinoma of the bladder (UCB) in the Egyptian patients. Subjects and method: The presence of XRCC3 Thr241Met gene polymorphism (rs 861539) was identified by PCR-RFLP method in 50 patients with urothelial carcinoma of bladder and 50 healthy controls. Results: XRCC3 Thr 241 Met gene polymorphism CC genotype and C allele demonstrated a substantially increased susceptibility in the UCB group than the control group for the risk to develop UCB (OR 3.69, 95% CL 1.52-8.97) (P =0.003). However, while TT genotype and T allele demonstrated a substantially decreased susceptibility in the UCB group than the control group with a protective effect against UCB development (OR 0.096, 95%CL0.035-0.263) (P<0.001). UCB risk factors including sex, smoking, family history & exposure to ionizing radiation were found to be significantly associated with CC genotype and C. Regarding histopathological characteristics tumor stage and tumor size & lymph node involvement parameters were significantly associated with CC genotype and C allele. Conclusion: XRCC3 Thr241Met SNP might be associated with predisposition to UCB and might also be used as indicator of a more aggressive tumor type, which requires a more individualized surveillance.
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