Background. Autophagy is a catabolic process that depends on the lysosome. It is usually used to maintain cellular homeostasis, survival and development by degrading abnormal substances and dysfunctional organelles, especially when the cell is exposed to starvation or other stresses. Increasing studies have reported that autophagy is associated with various eye diseases, of which aging is one of the important factors. Objective. To summarize the functional and regulatory role of autophagy in ocular diseases with aging, and discuss the possibility of autophagy-targeted therapy in age-related diseases. Methods. PubMed searches were performed to identify relevant articles published mostly in the last 5 years. The key words were used to retrieve including “autophagy”, “aging”, “oxidative stress AND autophagy”, “dry eye AND autophagy”, “corneal disease AND autophagy”, “glaucoma AND autophagy”, “cataract AND autophagy”, “AMD AND autophagy”, “cardiovascular diseases AND autophagy”, “diabetes AND autophagy”. After being classified and assessed, the most relevant full texts in English were chosen. Results. Apart from review articles, more than two research articles for each age-related eye diseases related to autophagy were retrieved. We only included the most relevant and recent studies for summary and discussion. Conclusion. Autophagy has both protective and detrimental effects on the progress of age-related eye diseases. Different types of studies based on certain situations in vitro showed distinct results, which do not necessarily coincide with the actual situation in human bodies completely. It means the exact role and regulatory function of autophagy in ocular diseases remains largely unknown. Although autophagy as a potential therapeutic target has been proposed, many problems still need to be solved before it applies to clinical practice.
Optimum design is proven significant for improving task performances of robotic manipulators under certain constraints. However, when it is utilized for collaborative robots (Cobots), there are still many challenges such as complex smooth surface links, time-varying kinematic configurations, computational expensiveness, and nonstructural parameter optimization. Therefore, based on orthogonal design experiment (ODE) and finite element substructure method (FESM), a multi-objective optimum design method of Cobots is proposed with the structural dimensions and parameterized joint components as the optimization variables and the natural frequency, the Cartesian stiffness, and the mass of the robot as optimization objectives. Firstly, to obtain multiple global performance indexes (GPIs) of robots in real-time and efficiently, the FESM model of Cobots is established which can preserve the accuracy of the finite element method (FEM) while ensuring the computational efficiency. Then, the gray relational analysis method (GRAM) is used to construct the multi-objective optimization function which includes the global first-order natural frequency index (GFNFI), the global elastic deformation index (GEDI), and the mass of robots. The ODE is constructed, and the structural dimensions and parameterized joint components are taken as influencing factors. According to the orthogonal array (OA), the degree of gray incidence under different levels of influencing factors is solved. And the optimal combination of influencing factor levels is obtained by range analysis (RA), which is used to guide the design of Cobots. Finally, a Cobot SHIR5-I is taken as an illustrative example to perform optimum design in this paper.
A modular robot system is introduced in this paper. The requirements for configuration synthesis are analyzed and classified as hard ones, soft ones and hard-soft ones. The evaluation function is constructed based on the weighted sum of the evaluation results of the specified design requirements. A one-lever Genetic Algorithm (GA) basing on an improved hybrid coding method is presented to carry out the configuration synthesis. In addition an example is given to demonstrate the effectiveness of this method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.