Foreign body in the urinary bladder causing persistent cystitis

SummaryAn unusual cause of a urinary tract infection (UTI) that presented in a woman who had previously undergone anti-incontinence sling surgery is presented here. A urinary bladder stone had formed on an eroded, nonabsorbable suture that had been used in the previous operation. Before identifying the underlying cause, the patient suffered from lower urinary tract symptoms and had undergone a prolonged course of antibiotic therapy for 3 years. Following removal of the suture, the UTI symptoms were rapidly resolved and only a short course of antibiotics was needed after the operation

HABCO: A Robust Agent on Hybrid Ant-Bee Colony Optimization

The purpose of this research is to generate a robust agent by combining bee colony optimization (BCO) and ELU-Ants for solving traveling salesman problem (TSP), called HABCO. The robust agents, called ant-bees, firstly are grouped into three types scout, follower, recruiter at each stages. Then, the bad agents are high probably discarded, while the good agents are high probably duplicated in earlier steps. This first two steps mimic BCO algorithm. However, constructing tours such as choosing nodes, and updating pheromone are built by ELU-Ants method.To evaluate the performance of the proposed algorithm, HABCO is performed on several benchmark datasets and compared to ACS and BCO. The experimental results show that HABCO achieves the better solution, either with or without 2opt

Space Net Optimization

Most metaheuristic algorithms rely on a few searched solutions to guide later searches during the convergence process for a simple reason: the limited computing resource of a computer makes it impossible to retain all the searched solutions. This also reveals that each search of most metaheuristic algorithms is just like a ballpark guess. To help address this issue, we present a novel metaheuristic algorithm called space net optimization (SNO). It is equipped with a new mechanism called space net; thus, making it possible for a metaheuristic algorithm to use most information provided by all searched solutions to depict the landscape of the solution space. With the space net, a metaheuristic algorithm is kind of like having a ``vision'' on the solution space. Simulation results show that SNO outperforms all the other metaheuristic algorithms compared in this study for a set of well-known single objective bound constrained problems in most cases.Comment: 12 pages, 6 figure