Optimization is a topic that has always been discussed in all different fields of science. One of the most effective techniques for solving such problems is optimization algorithms. In this paper, a new optimizer called Multi-Leader optimizer (MLO) is developed in which multiple leaders guide members of the population towards the optimal answer. MLO is mathematically modelled based on the process of advancing members of the population and following the leaders. MLO performance in optimization is examined on twenty-three standard objective functions. The results of this optimization are compared with the results of the other eight existing optimization algorithms including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Teaching-Learning-Based Optimization (TLBO), Gray Wolf Optimizer (GWO), Grasshopper Optimization Algorithm (GOA), Emperor Penguin Optimizer (EPO), Shell Game Optimization (SGO), and Hide Objects Game Optimization (HOGO). Based on the analysis of the simulation results on unimodal test functions to evaluate exploitation ability and multimodal test functions in order to evaluate exploration ability, it has been determined that MLO has a higher ability to solve optimization problems than existing optimization algorithms.

The 2021 sales volume in the market of service robots is attractive. Expert reports from the International Federation of Robotics confirm 27 billion USD in total market share. Moreover, the number of new startups with the denomination of service robots nowadays constitutes 29% of the total amount of robotic companies recorded in the United States. Those data, among other similar figures, remark the need for formal development in the service robots area, including knowledge transfer and literature reviews. Furthermore, the COVID-19 spread accelerated business units and some research groups to invest time and effort into the field of service robotics. Therefore, this research work intends to contribute to the formalization of service robots as an area of robotics, presenting a systematic review of scientific literature. First, a definition of service robots according to fundamental ontology is provided, followed by a detailed review covering technological applications; state-of-the-art, commercial technology; and application cases indexed on the consulted databases.

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Herein, we reviewed polymeric constructs of polyhydroxyalkanoates (PHAs) at large and poly‐3‐hydroxybutyrate (P3HB), in particular, for drug delivery and tissue engineering applications. Polymeric constructs that can efficiently respond to numerous variations in their surroundings have gained notable attention from different industrial sectors such as biomedical, clinical, pharmaceutical, and cosmeceutical. Among them, considerable importance is given to their drug delivery and tissue engineering applications. PHAs with peculiar reference to P3HB are gaining prominence attention as candidate materials with such requisite potentialities. The unique structural and functional characteristics of PHAs and P3HB are of supreme interest and being used to engineer novel constructs for efficient drug delivery and tissue regeneration purposes. So far, an array of methodological approaches, such as in vitro, in vivo, and ex vivo techniques have been exploited though using different materials with different geometries for a said purpose. However, a low‐level production majorly limits their proper exploitation. Various physiochemical characteristics and production strategies have been introduced in this review. The data have been summarized on PHAs production by several microorganisms aiming to cover the scope of the last 10 years. The present review highlights the recent applications of PHAs and P3HB‐based constructs, such as micro/nanoparticles, biocomposite, nanofibers, and hydrogels as novel drug carries for regenerative medicine and tissue engineering. In summary, drug delivery and tissue engineering potentialities of PHAs and P3HB‐based constructs are discussed with suitable examples and envisioned directions of future developments.