ABSTRACT
Continuum robots are complex structures that require sophisticated modeling and control methods to achieve accurate position and motion tracking along desired trajectories. They are highly coupled, nonlinear systems with multiple degrees of freedom that pose a significant challenge for conventional approaches. In this paper, we propose a system dynamic model based on the Euler-Lagrange formulation with the assumption of piecewise constant curvature (PCC), where we accounts for the elasticity and gravity effects of the continuum robot. We also develop and apply a particle swarm optimization (PSO) algorithm to optimize the parameters of our developed controllers: an inverse dynamic proportional integral derivative (PID) controller and an inverse dynamic fuzzy logic controller (FLC), where we use the integral time of absolute error (ITAE) as the objective function for the PSO algorithm. We validate our proposed model and optimized controllers through different designed trajectories, simulated using our developed unique animated MATLAB simulation. The results show that the PSO-PID controller improves the rise time, overshoot percentage, and settling time by 16.3%, 31.1%, and 64.9%, respectively, compared to the PID controller without PSO. The PSO-FLC controller shows the best performance among all controllers, with a settling time of 0.7 s and a rise time of 0.4 s, leading to the highest level of precision in trajectory tracking. The ITAE error for the PSO-FLC controller is 11.4% and 29.9% lower than that of the PSO-PID and FLC controllers, respectively.
ABSTRACT
Risk-based approaches are used to define performance standards for water and wastewater treatment to meet health-based targets and to ensure safe and reliable water quality for desired end use. In this study, a screening level QMRA for a non-membrane based indirect potable reuse (IPR) system utilizing the sequential managed aquifer recharge technology (SMART) concept was conducted. Ambient removals of norovirus, Campylobacter and Cryptosporidium in advanced water treatment (AWT) steps were combined in a probabilistic QMRA utilizing Bayesian networks constructed in Netica. Results revealed that all pathogens complied with disease burden at the 95th percentile, and according to the assumptions taken about pathogen removal, Cryptosporidium was the pathogen with the greatest risk. Through systematic sensitivity analysis, targeted scenario analysis, and backwards inferencing, critical control points for each pathogen were determined, demonstrating the usefulness of Bayesian networks as a diagnostic tool in quantifying risk of water reuse treatment scenarios.
Subject(s)
Cryptosporidiosis , Cryptosporidium , Drinking Water , Water Purification , Animals , Bayes Theorem , Risk Assessment , WastewaterABSTRACT
BACKGROUND: Pancreatic cancer is the fourth most common cause of cancer-related deaths in the United States, with an estimated 45,750 deaths in 2019. Mortality outcomes seem to differ based on the ethnicity of the patients, with most studies focusing on the mortality and survival of Caucasians and African Americans. Little attention has been given, however, to Asian-American patients diagnosed with pancreatic adenocarcinoma (PAC). In this study, we aimed to investigate mortality rates in Asian-American patients with PAC. METHODS: The SEER 13 registries (Surveillance, Epidemiology, and End-Results) of the National Cancer Institute were used to study PAC cases during 1992-2015. The incidence and incidence-based mortality rates per 100,000 person-years, and the annual percentage changes were calculated using SEER*stat software and Joinpoint regression software. RESULTS: A total of 5814 PAC cases in Asian-American patients were identified. Most patients were older than 60 years (77.6%) and had metastatic disease (55.8%). The overall incidence of PAC among Asian-Americans was 5.740 per 100,000 person-years (95% confidence interval [CI] 5.592-5.891]. Incidence rates were highest among males and patients older than 60 years. PAC incidence rates among Asian-Americans increased by 1.503% (95%CI 1.051-1.956; P<0.001) per year over the study period. PAC incidence rates increased over the study period for all sex, age, and stage subgroups. PAC incidence-based mortality among Asian-Americans increased by 4.535% (95%CI 3.538-5.541; P<0.001) per year over the study period. CONCLUSION: The incidence of PAC in Asian-Americans, as well as incidence-based mortality rates, are on the rise, irrespective of age, sex or stage subgroup.
