This research aims to enhance the surface quality, mechanical properties, and biocompatibility of PEEK (polyether–ether–ketone) biomimetic dental implants through laser polishing. The objective is to improve osseointegration and implant durability by reducing surface roughness, increasing hydrophilicity, and enhancing mechanical strength. The methodology involved fabricating PEEK implants via FDM and applying laser polishing. The significant findings showed a 66.7% reduction in surface roughness, Ra reduced from 2.4 µm to 0.8 µm, and a 25.3% improvement in hydrophilicity, water contact angle decreased from 87° to 65°. Mechanical tests revealed a 6.3% increase in tensile strength (96 MPa to 102 MPa) and a 50% improvement in fatigue resistance (100,000 to 150,000 cycles). The strength analysis result showed a 10% increase in stiffness storage modulus from 1400 MPa to 1500 MPa. Error analysis showed a standard deviation of ±3% across all tests. In conclusion, laser polishing significantly improves the surface, mechanical, and biological performance of PEEK implants, making it a promising approach for advancing biomimetic dental implant technology.

Grasp planning is crucial for robots to perform precision grasping tasks, where determining the grasp points significantly impacts the performance of the robotic hand. Currently, the majority of grasp planning methods based on analytic approaches solve the problem by transforming it into a nonlinear constrained planning problem. This method often requires performing convex hull computations, which tend to have high computational complexity. This paper proposes a new algorithm for calculating multi-finger force-closure grasps of three-dimensional objects based on humanoid multi-fingered hands. Firstly, sufficient conditions for the multi-finger force-closure grasps of three-dimensional objects are derived from a point contact model with friction. These three-dimensional force-closure conditions are then transformed into two-dimensional plane conditions, leading to a simple algorithm for multi-finger force-closure determination. This method is purely based on geometric analysis, resulting in low computational demands and enabling the rapid assessment of force-closure grasps, which are beneficial for real-time applications. Finally, the algorithm is validated through two case studies, demonstrating its feasibility and effectiveness.

The nutcracker optimizer algorithm (NOA) is a metaheuristic method proposed in recent years. This algorithm simulates the behavior of nutcrackers searching and storing food in nature to solve the optimization problem. However, the traditional NOA struggles to balance global exploration and local exploitation effectively, making it prone to getting trapped in local optima when solving complex problems. To address these shortcomings, this study proposes a reinforcement learning-based bi-population nutcracker optimizer algorithm called RLNOA. In the RLNOA, a bi-population mechanism is introduced to better balance global and local optimization capabilities. At the beginning of each iteration, the raw population is divided into an exploration sub-population and an exploitation sub-population based on the fitness value of each individual. The exploration sub-population is composed of individuals with poor fitness values. An improved foraging strategy based on random opposition-based learning is designed as the update method for the exploration sub-population to enhance diversity. Meanwhile, Q-learning serves as an adaptive selector for exploitation strategies, enabling optimal adjustment of the exploitation sub-population’s behavior across various problems. The performance of the RLNOA is evaluated using the CEC-2014, CEC-2017, and CEC-2020 benchmark function sets, and it is compared against nine state-of-the-art metaheuristic algorithms. Experimental results demonstrate the superior performance of the proposed algorithm.

As engineering demands for structural energy absorption intensify, triply periodic minimal surface (TPMS) structures, known for their light weight and exceptional energy absorption, are increasingly valued in aerospace, automotive, and shipping engineering. In this study, the energy absorption performance of three typical TPMS structures was evaluated (i.e., Gyroid, Diamond, and IWP) using quasi-static compression tests at various load-bearing angles. The results showed that while there is little influence of load-bearing angles on the energy absorption performance of Gyroid structures, its energy absorption is the least of the three structures. In contrast, Diamond structures have notable fluctuation in energy absorption at certain angles. Moreover, IWP (I-graph and Wrapped Package-graph) structures, though highly angle-sensitive, achieve the highest energy absorption. Further analysis of deformation behaviors revealed that structures dominated by bending deformation are stable under multi-directional loads but less efficient in energy absorption. Conversely, structures exhibiting mainly tensile deformation, despite their load direction sensitivity, perform best in energy absorption. By integrating bending and tensile deformations, energy absorption was enhanced through a multi-stage platform response. The data and conclusions revealed in the present study can provide valuable insights for future applications of TPMS structures.

An efficient treatment plan using a temporary anchorage device should be built following the principle of reducing the number of tads to obtain a multiple biomechanical advantage. The following case report concerns the Biga system, a strategy that supports orthodontists during class II corrections and vertical control through treatment. A 12-year-old girl with a high angle of skeletal class II was selected. A novel biomechanical strategy was effectively applied using two tads on the upper arch to obtain sequential distalization of the upper teeth and to correct the lower arch spee curve using third-class elastics. Eventually, on the same tads, a double cantilever was applied to control the overbite and intrusion during incisors' retraction. The Biga system is an easy biomechanical strategy that ensures the three-dimensional control of treatment mechanics in class II patients.

The purpose of this study was to evaluate the repair process in rat calvaria filled with synthetic biphasic bioceramics (Plenum® Osshp-70:30, HA:βTCP) or autogenous bone, covered with a polydioxanone membrane (PDO). A total of 48 rats were divided into two groups (n = 24): particulate autogenous bone + Plenum® Guide (AUTOPT+PG) or Plenum® Osshp + Plenum® Guide (PO+PG). A defect was created in the calvaria, filled with the grafts, and covered with a PDO membrane, and euthanasia took place at 7, 30, and 60 days. Micro-CT showed no statistical difference between the groups, but there was an increase in bone volume (56.26%), the number of trabeculae (2.76 mm), and intersection surface (26.76 mm2) and a decrease in total porosity (43.79%) in the PO+PG group, as well as higher values for the daily mineral apposition rate (7.16 µm/day). Histometric analysis presented material replacement and increased bone formation at 30 days compared to 7 days in both groups. Immunostaining showed a similar pattern between the groups, with an increase in proteins related to bone remodeling and formation. In conclusion, Plenum® Osshp + Plenum® Guide showed similar and sometimes superior results when compared to autogenous bone, making it a competent option as a bone substitute.

Previous studies on the clap-fling mechanism have predominantly focused on the initial downward and forward phases of flight in miniature insects, either during hovering or forward flight. However, this study presents the first comprehensive kinematic data of Coccinella septempunctata during climbing flight. It reveals, for the first time, that a clap-and-fling mechanism occurs during the initial upward and backward phase of the hind wings' motion. This discovery addresses the previously limited understanding of the clap-and-fling mechanism by demonstrating that, during the clap motion, the leading edges of beetle's wings come into proximity to form a figure-eight shape before rotating around their trailing edge to open into a "V" shape. By employing numerical solutions to solve Navier-Stokes (N-S) equations, we simulated both single hind wings' and double hind wings' aerodynamic conditions. Our findings demonstrate that this fling mechanism not only significantly enhances the lift coefficient by approximately 9.65% but also reduces the drag coefficient by about 1.7%, indicating an extension of the applicability range of this clap-and-fling mechanism beyond minute insect flight. Consequently, these insights into insect flight mechanics deepen our understanding of their biological characteristics and inspire advancements in robotics and biomimetics.

The sand cat swarm optimization algorithm (SCSO) is a novel metaheuristic algorithm that has been proposed in recent years. The algorithm optimizes the search ability of individuals by mimicking the hunting behavior of sand cat groups in nature, thereby achieving robust optimization performance. It is characterized by few control parameters and simple operation. However, due to the lack of population diversity, SCSO is less efficient in solving complex problems and is prone to fall into local optimization. To address these shortcomings and refine the algorithm's efficacy, an improved multi-strategy sand cat optimization algorithm (IMSCSO) is proposed in this paper. In IMSCSO, a roulette fitness-distance balancing strategy is used to select codes to replace random agents in the exploration phase and enhance the convergence performance of the algorithm. To bolster population diversity, a novel population perturbation strategy is introduced, aiming to facilitate the algorithm's escape from local optima. Finally, a best-worst perturbation strategy is developed. The approach not only maintains diversity throughout the optimization process but also enhances the algorithm's exploitation capabilities. To evaluate the performance of the proposed IMSCSO, we conducted experiments in the CEC 2017 test suite and compared IMSCSO with seven other algorithms. The results show that the IMSCSO proposed in this paper has better optimization performance.

The study of bio-inspired structures and their reproduction has always fascinated humans. The advent of soft robotics, thanks to soft materials, has enabled considerable progress in this field. Over the years, polyps, worms, cockroaches, jellyfish, and multiple anthropomorphic structures such as hands or limbs have been reproduced. These structures have often been used for gripping and handling delicate objects or those with complex unknown a priori shapes. Several studies have also been conducted on grippers inspired by the seahorse tail. In this paper, a novel biomimetic soft pneumatic actuator inspired by the tail of the seahorse Hippocampus reidi is presented. The actuator has been developed to make a leg to sustain a multi-legged robot. The prototyping of the actuator was possible by combining a 3D-printed reinforcement in thermoplastic polyurethane, mimicking the skeletal apparatus, within a silicone rubber structure, replicating the functions of the external epithelial tissue. The latter has an internal channel for pneumatic actuation that acts as the inner muscle. The study on the anatomy and kinematic behaviour of the seahorse tail suggested the mechanical design of the actuator. Through a test campaign, the actuator prototype was characterized by isotonic tests with an external null load, isometric tests, and activation/deactivation times. Specifically, the full actuator distension of 154.5 mm occurs at 1.8 bar, exerting a maximum force of 11.9 N, with an activation and deactivation time of 74.9 and 94.5 ms, respectively.

Soft robotics is closely related to embodied intelligence in the joint exploration of the means to achieve more natural and effective robotic behaviors via physical forms and intelligent interactions. Embodied intelligence emphasizes that intelligence is affected by the synergy of the brain, body, and environment, focusing on the interaction between agents and the environment. Under this framework, the design and control strategies of soft robotics depend on their physical forms and material properties, as well as algorithms and data processing, which enable them to interact with the environment in a natural and adaptable manner. At present, embodied intelligence has comprehensively integrated related research results on the evolution, learning, perception, decision making in the field of intelligent algorithms, as well as on the behaviors and controls in the field of robotics. From this perspective, the relevant branches of the embodied intelligence in the context of soft robotics were studied, covering the computation of embodied morphology; the evolution of embodied AI; and the perception, control, and decision making of soft robotics. Moreover, on this basis, important research progress was summarized, and related scientific problems were discussed. This study can provide a reference for the research of embodied intelligence in the context of soft robotics.