The food web is a crucial conceptual tool for understanding the dynamics of energy transfer in an ecosystem, as well as the feeding relationships among species within a community. It also reveals species interactions and community structure. As a result, an ecological food web system with two predators competing for prey while experiencing fear was developed and studied. The properties of the solution of the system were determined, and all potential equilibrium points were identified. The dynamic behavior in their immediate surroundings was examined both locally and globally. The system’s persistence demands were calculated, and all conceivable forms of local bifurcations were investigated. With the aid of MATLAB, a numerical simu

Background: The aims of this study were to evaluate the effect of implant site preparation in low-density bone using osseodensification method in terms of implant stability changes during the osseous healing period and peri-implant bone density using CBCT. Material and methods: This prospective observational clinical study included 24 patients who received 46 dental implants that were installed in low-density bone using the osseodensification method. CBCT was used to measure the bone density pre- and postoperatively and implant stability was measured using Periotest® immediately after implant insertion and then after 6 weeks and 12 weeks postoperatively. The data were analyzed using paired t-test and the probability value <0.05 was conside

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature