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Biomimetics
Volume 8
Issue 5
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Biomimetics, Volume 8, Issue 5 (September 2023) – 66 articles

Cover Story (view full-size image): A tomography-based control system for rehab robots, focusing on dynamic modeling, is introduced in this study. The torque and hand impedance guide the rehab steps. A regression model estimates muscle state from tomography signals, adjusting patient torque in real time. Two protocol steps are key: (1) calculating specific parameters, like axis offset and inertia; (2) identifying other model elements, such as interaction torque. Tests on various participants indicate the system’s efficacy, with impedance position prediction errors below 2% and individualized force control. View this paper
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12 pages, 1364 KiB  
Article
New Glycosalen–Manganese(III) Complexes and RCA120 Hybrid Systems as Superoxide Dismutase/Catalase Mimetics
by Valeria Lanza and Graziella Vecchio
Biomimetics 2023, 8(5), 447; https://doi.org/10.3390/biomimetics8050447 - 21 Sep 2023
Cited by 1 | Viewed by 1071
Abstract
Reactive oxygen species are implicated in several human diseases, including neurodegenerative disorders, cardiovascular dysfunction, inflammation, hereditary diseases, and ageing. MnIII–salen complexes are superoxide dismutase (SOD) and catalase (CAT) mimetics, which have shown beneficial effects in various models for oxidative stress. These [...] Read more.
Reactive oxygen species are implicated in several human diseases, including neurodegenerative disorders, cardiovascular dysfunction, inflammation, hereditary diseases, and ageing. MnIII–salen complexes are superoxide dismutase (SOD) and catalase (CAT) mimetics, which have shown beneficial effects in various models for oxidative stress. These properties make them well-suited as potential therapeutic agents for oxidative stress diseases. Here, we report the synthesis of the novel glycoconjugates of salen complex, EUK-108, with glucose and galactose. We found that the complexes showed a SOD-like activity higher than EUK-108, as well as peroxidase and catalase activities. We also investigated the conjugate activities in the presence of Ricinus communis agglutinin (RCA120) lectin. The hybrid protein–galactose–EUK-108 system showed an increased SOD-like activity similar to the native SOD1. Full article
(This article belongs to the Section Biomimetic Processing and Molecular Biomimetics)
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14 pages, 1693 KiB  
Review
Recent Development and Application of “Nanozyme” Artificial Enzymes—A Review
by Sivakamavalli Jeyachandran, Ramachandran Srinivasan, Thiyagarajan Ramesh, Arumugam Parivallal, Jintae Lee and Ezhaveni Sathiyamoorthi
Biomimetics 2023, 8(5), 446; https://doi.org/10.3390/biomimetics8050446 - 21 Sep 2023
Cited by 1 | Viewed by 1944
Abstract
Nanozymes represent a category of nano-biomaterial artificial enzymes distinguished by their remarkable catalytic potency, stability, cost-effectiveness, biocompatibility, and degradability. These attributes position them as premier biomaterials with extensive applicability across medical, industrial, technological, and biological domains. Following the discovery of ferromagnetic nanoparticles with [...] Read more.
Nanozymes represent a category of nano-biomaterial artificial enzymes distinguished by their remarkable catalytic potency, stability, cost-effectiveness, biocompatibility, and degradability. These attributes position them as premier biomaterials with extensive applicability across medical, industrial, technological, and biological domains. Following the discovery of ferromagnetic nanoparticles with peroxidase-mimicking capabilities, extensive research endeavors have been dedicated to advancing nanozyme utilization. Their capacity to emulate the functions of natural enzymes has captivated researchers, prompting in-depth investigations into their attributes and potential applications. This exploration has yielded insights and innovations in various areas, including detection mechanisms, biosensing techniques, and device development. Nanozymes exhibit diverse compositions, sizes, and forms, resembling molecular entities such as proteins and tissue-based glucose. Their rapid impact on the body necessitates a comprehensive understanding of their intricate interplay. As each day witnesses the emergence of novel methodologies and technologies, the integration of nanozymes continues to surge, promising enhanced comprehension in the times ahead. This review centers on the expansive deployment and advancement of nanozyme materials, encompassing biomedical, biotechnological, and environmental contexts. Full article
(This article belongs to the Special Issue Functional Biomimetic Materials and Devices for Biomedical Applications)
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17 pages, 2096 KiB  
Article
Active Vision in Binocular Depth Estimation: A Top-Down Perspective
by Matteo Priorelli, Giovanni Pezzulo and Ivilin Peev Stoianov
Biomimetics 2023, 8(5), 445; https://doi.org/10.3390/biomimetics8050445 - 21 Sep 2023
Cited by 2 | Viewed by 1125
Abstract
Depth estimation is an ill-posed problem; objects of different shapes or dimensions, even if at different distances, may project to the same image on the retina. Our brain uses several cues for depth estimation, including monocular cues such as motion parallax and binocular [...] Read more.
Depth estimation is an ill-posed problem; objects of different shapes or dimensions, even if at different distances, may project to the same image on the retina. Our brain uses several cues for depth estimation, including monocular cues such as motion parallax and binocular cues such as diplopia. However, it remains unclear how the computations required for depth estimation are implemented in biologically plausible ways. State-of-the-art approaches to depth estimation based on deep neural networks implicitly describe the brain as a hierarchical feature detector. Instead, in this paper we propose an alternative approach that casts depth estimation as a problem of active inference. We show that depth can be inferred by inverting a hierarchical generative model that simultaneously predicts the eyes’ projections from a 2D belief over an object. Model inversion consists of a series of biologically plausible homogeneous transformations based on Predictive Coding principles. Under the plausible assumption of a nonuniform fovea resolution, depth estimation favors an active vision strategy that fixates the object with the eyes, rendering the depth belief more accurate. This strategy is not realized by first fixating on a target and then estimating the depth; instead, it combines the two processes through action–perception cycles, with a similar mechanism of the saccades during object recognition. The proposed approach requires only local (top-down and bottom-up) message passing, which can be implemented in biologically plausible neural circuits. Full article
(This article belongs to the Special Issue Bio-Inspired Neural Networks)
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16 pages, 4579 KiB  
Article
Antibacterial Calcium Phosphate Coatings for Biomedical Applications Fabricated via Micro-Arc Oxidation
by Anna I. Kozelskaya, Ksenia N. Verzunova, Igor O. Akimchenko, Johannes Frueh, Vsevolod I. Petrov, Galina B. Slepchenko, Olga V. Bakina, Marat I. Lerner, Leonid K. Brizhan, Denis V. Davydov, Artur A. Kerimov, Elena G. Cherempey, Sergey E. Krylov, Sven Rutkowski and Sergei I. Tverdokhlebov
Biomimetics 2023, 8(5), 444; https://doi.org/10.3390/biomimetics8050444 - 21 Sep 2023
Cited by 6 | Viewed by 1242
Abstract
A promising method for improving the functional properties of calcium-phosphate coatings is the incorporation of various antibacterial additives into their structure. The microbial contamination of a superficial wound is inevitable, even if the rules of asepsis and antisepsis are optimally applied. One of [...] Read more.
A promising method for improving the functional properties of calcium-phosphate coatings is the incorporation of various antibacterial additives into their structure. The microbial contamination of a superficial wound is inevitable, even if the rules of asepsis and antisepsis are optimally applied. One of the main problems is that bacteria often become resistant to antibiotics over time. However, this does not apply to certain elements, chemical compounds and drugs with antimicrobial properties. In this study, the fabrication and properties of zinc-containing calcium-phosphate coatings that were formed via micro-arc oxidation from three different electrolyte solutions are investigated. The first electrolyte is based on calcium oxide, the second on hydroxyapatite and the third on calcium acetate. By adding zinc oxide to the three electrolyte solutions, antibacterial properties of the coatings are achieved. Although the same amount of zinc oxide has been added to each electrolyte solution, the zinc concentration in the coatings obtained vary greatly. Furthermore, this study investigates the morphology, structure and chemical composition of the coatings. The antibacterial properties of the zinc-containing coatings were tested toward three strains of bacteria—Staphylococcus aureus, methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa. Coatings of calcium acetate and zinc oxide contained the highest amount of zinc and displayed the highest zinc release. Moreover, coatings containing hydroxyapatite and zinc oxide show the highest antibacterial activity toward Pseudomonas aeruginosa, and coatings containing calcium acetate and zinc oxide show the highest antibacterial activities toward Staphylococcus aureus and methicillin-resistant Staphylococcus aureus. Full article
(This article belongs to the Special Issue Functional Biomimetic Materials and Devices for Biomedical Applications)
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12 pages, 2048 KiB  
Article
Inchworm-like Soft Robot with Multi-Responsive Bilayer Films
by Xufeng Wang, Wei Pu, Ruichen Zhang and Fanan Wei
Biomimetics 2023, 8(5), 443; https://doi.org/10.3390/biomimetics8050443 - 21 Sep 2023
Cited by 1 | Viewed by 1158
Abstract
As an important branch of robotics, soft robots have the advantages of strong flexibility, a simple structure, and high safety. These characteristics enable soft robots to be widely used in various fields such as biomedicine, military reconnaissance, and micro space exploration. However, contemporary [...] Read more.
As an important branch of robotics, soft robots have the advantages of strong flexibility, a simple structure, and high safety. These characteristics enable soft robots to be widely used in various fields such as biomedicine, military reconnaissance, and micro space exploration. However, contemporary soft crawling robots still face problems such as the single drive mode and complex external equipment. In this study, we propose an innovative design of an inchworm-like soft crawling robot utilizing the synergistic interaction of electricity and moisture for its hybrid dual-drive locomotion. The legs of the soft robot are mainly made of GO-CNT/PE composite film, which can convert its own volume expansion into a corresponding bending motion after being stimulated by electricity or moisture. Unlike other drive methods, it requires less power and precision from external devices. The combination of the two driving methods greatly improves the environmental adaptability of the soft robot, and we developed visible light as the driving method on the basis of the dual drive. Finally, we also verified the robot’s excellent load capacity, climbing ability, and optical drive effect, which laid the foundation for the application of soft robots in the future. Full article
(This article belongs to the Special Issue Advance in Bio-Inspired Micro-Robotics)
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23 pages, 1238 KiB  
Review
Artificial Intelligence in Regenerative Medicine: Applications and Implications
by Hamed Nosrati and Masoud Nosrati
Biomimetics 2023, 8(5), 442; https://doi.org/10.3390/biomimetics8050442 - 20 Sep 2023
Cited by 9 | Viewed by 5598
Abstract
The field of regenerative medicine is constantly advancing and aims to repair, regenerate, or substitute impaired or unhealthy tissues and organs using cutting-edge approaches such as stem cell-based therapies, gene therapy, and tissue engineering. Nevertheless, incorporating artificial intelligence (AI) technologies has opened new [...] Read more.
The field of regenerative medicine is constantly advancing and aims to repair, regenerate, or substitute impaired or unhealthy tissues and organs using cutting-edge approaches such as stem cell-based therapies, gene therapy, and tissue engineering. Nevertheless, incorporating artificial intelligence (AI) technologies has opened new doors for research in this field. AI refers to the ability of machines to perform tasks that typically require human intelligence in ways such as learning the patterns in the data and applying that to the new data without being explicitly programmed. AI has the potential to improve and accelerate various aspects of regenerative medicine research and development, particularly, although not exclusively, when complex patterns are involved. This review paper provides an overview of AI in the context of regenerative medicine, discusses its potential applications with a focus on personalized medicine, and highlights the challenges and opportunities in this field. Full article
(This article belongs to the Section Bioinspired Sensorics, Information Processing and Control)
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37 pages, 6731 KiB  
Article
An Enhanced Hunger Games Search Optimization with Application to Constrained Engineering Optimization Problems
by Yaoyao Lin, Ali Asghar Heidari, Shuihua Wang, Huiling Chen and Yudong Zhang
Biomimetics 2023, 8(5), 441; https://doi.org/10.3390/biomimetics8050441 - 20 Sep 2023
Cited by 1 | Viewed by 1440
Abstract
The Hunger Games Search (HGS) is an innovative optimizer that operates without relying on gradients and utilizes a population-based approach. It draws inspiration from the collaborative foraging activities observed in social animals in their natural habitats. However, despite its notable strengths, HGS is [...] Read more.
The Hunger Games Search (HGS) is an innovative optimizer that operates without relying on gradients and utilizes a population-based approach. It draws inspiration from the collaborative foraging activities observed in social animals in their natural habitats. However, despite its notable strengths, HGS is subject to limitations, including inadequate diversity, premature convergence, and susceptibility to local optima. To overcome these challenges, this study introduces two adjusted strategies to enhance the original HGS algorithm. The first adaptive strategy combines the Logarithmic Spiral (LS) technique with Opposition-based Learning (OBL), resulting in the LS-OBL approach. This strategy plays a pivotal role in reducing the search space and maintaining population diversity within HGS, effectively augmenting the algorithm’s exploration capabilities. The second adaptive strategy, the dynamic Rosenbrock Method (RM), contributes to HGS by adjusting the search direction and step size. This adjustment enables HGS to escape from suboptimal solutions and enhances its convergence accuracy. Combined, these two strategies form the improved algorithm proposed in this study, referred to as RLHGS. To assess the efficacy of the introduced strategies, specific experiments are designed to evaluate the impact of LS-OBL and RM on enhancing HGS performance. The experimental results unequivocally demonstrate that integrating these two strategies significantly enhances the capabilities of HGS. Furthermore, RLHGS is compared against eight state-of-the-art algorithms using 23 well-established benchmark functions and the CEC2020 test suite. The experimental results consistently indicate that RLHGS outperforms the other algorithms, securing the top rank in both test suites. This compelling evidence substantiates the superior functionality and performance of RLHGS compared to its counterparts. Moreover, RLHGS is applied to address four constrained real-world engineering optimization problems. The final results underscore the effectiveness of RLHGS in tackling such problems, further supporting its value as an efficient optimization method. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)
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14 pages, 2677 KiB  
Article
Using Footpad Sculpturing to Enhance the Maneuverability and Speed of a Robotic Marangoni Surfer
by Samuel Bechard, Mitchel L. Timm, Hassan Masoud and Jonathan P. Rothstein
Biomimetics 2023, 8(5), 440; https://doi.org/10.3390/biomimetics8050440 - 20 Sep 2023
Viewed by 939
Abstract
From insects to arachnids to bacteria, the surfaces of lakes and ponds are teaming with life. Many modes of locomotion are employed by these organisms to navigate along the air–water interface, including the use of lipid-laden excretions that can locally change the surface [...] Read more.
From insects to arachnids to bacteria, the surfaces of lakes and ponds are teaming with life. Many modes of locomotion are employed by these organisms to navigate along the air–water interface, including the use of lipid-laden excretions that can locally change the surface tension of the water and induce a Marangoni flow. In this paper, we improved the speed and maneuverability of a miniature remote-controlled robot that mimics insect locomotion using an onboard tank of isopropyl alcohol and a series of servomotors to control both the rate and location of alcohol release to both propel and steer the robot across the water. Here, we studied the effect of a series of design changes to the foam rubber footpads, which float the robot and are integral in efficiently converting the alcohol-induced surface tension gradients into propulsive forces and effective maneuvering. Two designs were studied: a two-footpad design and a single-footpad design. In the case of two footpads, the gap between the two footpads was varied to investigate its impact on straight-line speed, propulsion efficiency, and maneuverability. An optimal design was found with a small but finite gap between the two pads of 7.5 mm. In the second design, a single footpad without a central gap was studied. This footpad had a rectangular cut-out in the rear to capture the alcohol. Footpads with wider and shallower cut-outs were found to optimize efficiency. This observation was reinforced by the predictions of a simple theoretical mechanical model. Overall, the optimized single-footpad robot outperformed the two-footpad robot, producing a 30% improvement in speed and a 400% improvement in maneuverability. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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23 pages, 16445 KiB  
Article
Characterization of Morphologically Distinct Components in the Tarsal Secretion of Medauroidea extradentata (Phasmatodea) Using Cryo-Scanning Electron Microscopy
by Julian Thomas, Stanislav N. Gorb and Thies H. Büscher
Biomimetics 2023, 8(5), 439; https://doi.org/10.3390/biomimetics8050439 - 20 Sep 2023
Viewed by 1131
Abstract
Attachment to the substrate is an important phenomenon that determines the survival of many organisms. Most insects utilize wet adhesion to support attachment, which is characterized by fluids that are secreted into the interface between the tarsus and the substrates. Previous research has [...] Read more.
Attachment to the substrate is an important phenomenon that determines the survival of many organisms. Most insects utilize wet adhesion to support attachment, which is characterized by fluids that are secreted into the interface between the tarsus and the substrates. Previous research has investigated the composition and function of tarsal secretions of different insect groups, showing that the secretions are likely viscous emulsions that contribute to attachment by generating capillary and viscous adhesion, leveling surface roughness and providing self-cleaning of the adhesive systems. Details of the structural organization of these secretions are, however, largely unknown. Here, we analyzed footprints originating from the arolium and euplantulae of the stick insect Medauroidea extradentata using cryo-scanning electron microscopy (cryo-SEM) and white light interferometry (WLI). The secretion was investigated with cryo-SEM, revealing four morphologically distinguishable components. The 3D WLI measurements of the droplet shapes and volumes over time revealed distinctly different evaporation rates for different types of droplets. Our results indicate that the subfunctionalization of the tarsal secretion is facilitated by morphologically distinct components, which are likely a result of different proportions of components within the emulsion. Understanding these components and their functions may aid in gaining insights for developing adaptive and multifunctional biomimetic adhesive systems. Full article
(This article belongs to the Special Issue Biological Attachment Systems and Biomimetics)
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19 pages, 4568 KiB  
Article
An Automatic-Segmentation- and Hyper-Parameter-Optimization-Based Artificial Rabbits Algorithm for Leaf Disease Classification
by Ihtiram Raza Khan, M. Siva Sangari, Piyush Kumar Shukla, Aliya Aleryani, Omar Alqahtani, Areej Alasiry and M. Turki-Hadj Alouane
Biomimetics 2023, 8(5), 438; https://doi.org/10.3390/biomimetics8050438 - 19 Sep 2023
Cited by 1 | Viewed by 1102
Abstract
In recent years, disease attacks have posed continuous threats to agriculture and caused substantial losses in the economy. Thus, early detection and classification could minimize the spread of disease and help to improve yield. Meanwhile, deep learning has emerged as the significant approach [...] Read more.
In recent years, disease attacks have posed continuous threats to agriculture and caused substantial losses in the economy. Thus, early detection and classification could minimize the spread of disease and help to improve yield. Meanwhile, deep learning has emerged as the significant approach to detecting and classifying images. The classification performed using the deep learning approach mainly relies on large datasets to prevent overfitting problems. The Automatic Segmentation and Hyper Parameter Optimization Artificial Rabbits Algorithm (AS-HPOARA) is developed to overcome the above-stated issues. It aims to improve plant leaf disease classification. The Plant Village dataset is used to assess the proposed AS-HPOARA approach. Z-score normalization is performed to normalize the images using the dataset’s mean and standard deviation. Three augmentation techniques are used in this work to balance the training images: rotation, scaling, and translation. Before classification, image augmentation reduces overfitting problems and improves the classification accuracy. Modified UNet employs a more significant number of fully connected layers to better represent deeply buried characteristics; it is considered for segmentation. To convert the images from one domain to another in a paired manner, the classification is performed by HPO-based ARA, where the training data get increased and the statistical bias is eliminated to improve the classification accuracy. The model complexity is minimized by tuning the hyperparameters that reduce the overfitting issue. Accuracy, precision, recall, and F1 score are utilized to analyze AS-HPOARA’s performance. Compared to the existing CGAN-DenseNet121 and RAHC_GAN, the reported results show that the accuracy of AS-HPOARA for ten classes is high at 99.7%. Full article
(This article belongs to the Special Issue Biomimicry for Optimization, Control, and Automation)
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17 pages, 3215 KiB  
Article
Design and Dynamic Control: A Free-Flying Space Robot Inspired by Water Striders
by Huayang Sai, Chengkai Xia, Zhenbang Xu and Hang Li
Biomimetics 2023, 8(5), 437; https://doi.org/10.3390/biomimetics8050437 - 19 Sep 2023
Viewed by 877
Abstract
This work designed a free-flying space robot (FFSR) that simulates the on-orbit assembly of large space telescopes, drawing inspiration from the flexible movement of water striders on water surfaces. Initially, we developed the system structure of the robot, including the corresponding air-floating ground [...] Read more.
This work designed a free-flying space robot (FFSR) that simulates the on-orbit assembly of large space telescopes, drawing inspiration from the flexible movement of water striders on water surfaces. Initially, we developed the system structure of the robot, including the corresponding air-floating ground simulation system. This system enables floating movement of the robot in a gravity-free environment through the utilization of planar air bearings. Subsequently, we established the kinematics and dynamics models for the FFSR. Following that, we propose a novel adaptive boundary layer fuzzy sliding mode control (ABLFSMC) method to achieve trajectory tracking control of the FFSR. The virtual angle and angular velocity are formulated to serve as references for the angle and angular velocity in the body coordinate system. Furthermore, a fuzzy logic system is employed to minimize the chattering effect of the sliding mode control. The global stability of the proposed controller is guaranteed through the Lyapunov stability theory. Finally, we validate the effectiveness of the proposed control method as well as the high trajectory tracking accuracy of the developed FFSR through simulation and experimental results, respectively. Overall, our findings present a crucial experimental platform and development opportunity for the ground-based validation of technologies concerning the on-orbit assembly of large space telescopes. Full article
(This article belongs to the Special Issue Biomimetic Design for Space Applications)
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20 pages, 8675 KiB  
Article
Perceiving like a Bat: Hierarchical 3D Geometric–Semantic Scene Understanding Inspired by a Biomimetic Mechanism
by Chi Zhang, Zhong Yang, Bayang Xue, Haoze Zhuo, Luwei Liao, Xin Yang and Zekun Zhu
Biomimetics 2023, 8(5), 436; https://doi.org/10.3390/biomimetics8050436 - 19 Sep 2023
Viewed by 1338
Abstract
Geometric–semantic scene understanding is a spatial intelligence capability that is essential for robots to perceive and navigate the world. However, understanding a natural scene remains challenging for robots because of restricted sensors and time-varying situations. In contrast, humans and animals are able to [...] Read more.
Geometric–semantic scene understanding is a spatial intelligence capability that is essential for robots to perceive and navigate the world. However, understanding a natural scene remains challenging for robots because of restricted sensors and time-varying situations. In contrast, humans and animals are able to form a complex neuromorphic concept of the scene they move in. This neuromorphic concept captures geometric and semantic aspects of the scenario and reconstructs the scene at multiple levels of abstraction. This article seeks to reduce the gap between robot and animal perception by proposing an ingenious scene-understanding approach that seamlessly captures geometric and semantic aspects in an unexplored environment. We proposed two types of biologically inspired environment perception methods, i.e., a set of elaborate biomimetic sensors and a brain-inspired parsing algorithm related to scene understanding, that enable robots to perceive their surroundings like bats. Our evaluations show that the proposed scene-understanding system achieves competitive performance in image semantic segmentation and volumetric–semantic scene reconstruction. Moreover, to verify the practicability of our proposed scene-understanding method, we also conducted real-world geometric–semantic scene reconstruction in an indoor environment with our self-developed drone. Full article
(This article belongs to the Special Issue Biologically Inspired Vision and Image Processing)
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17 pages, 4373 KiB  
Review
Advances in Ghost Imaging of Moving Targets: A Review
by Moudan Shi, Jie Cao, Huan Cui, Chang Zhou and Tianhua Zhao
Biomimetics 2023, 8(5), 435; https://doi.org/10.3390/biomimetics8050435 - 19 Sep 2023
Cited by 3 | Viewed by 1599
Abstract
Ghost imaging is a novel imaging technique that utilizes the intensity correlation property of an optical field to retrieve information of the scene being measured. Due to the advantages of simple structure, high detection efficiency, etc., ghost imaging exhibits broad application prospects in [...] Read more.
Ghost imaging is a novel imaging technique that utilizes the intensity correlation property of an optical field to retrieve information of the scene being measured. Due to the advantages of simple structure, high detection efficiency, etc., ghost imaging exhibits broad application prospects in the fields of space remote sensing, optical encryption transmission, medical imaging, and so on. At present, ghost imaging is gradually developing toward practicality, in which ghost imaging of moving targets is becoming a much-needed breakthrough link. At this stage, we can improve the imaging speed and improve the imaging quality to seek a more optimized ghost imaging scheme for moving targets. Based on the principle of moving target ghost imaging, this review summarizes and compares the existing methods for ghost imaging of moving targets. It also discusses the research direction and the technical challenges at the current stage to provide references for further promotion of the instantiation of ghost imaging applications. Full article
(This article belongs to the Special Issue Bionic Imaging and Optical Devices)
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26 pages, 1231 KiB  
Article
Adaptive PI Controller Based on a Reinforcement Learning Algorithm for Speed Control of a DC Motor
by Ulbio Alejandro-Sanjines, Anthony Maisincho-Jivaja, Victor Asanza, Leandro L. Lorente-Leyva and Diego H. Peluffo-Ordóñez
Biomimetics 2023, 8(5), 434; https://doi.org/10.3390/biomimetics8050434 - 19 Sep 2023
Cited by 1 | Viewed by 2337
Abstract
Automated industrial processes require a controller to obtain an output signal similar to the reference indicated by the user. There are controllers such as PIDs, which are efficient if the system does not change its initial conditions. However, if this is not the [...] Read more.
Automated industrial processes require a controller to obtain an output signal similar to the reference indicated by the user. There are controllers such as PIDs, which are efficient if the system does not change its initial conditions. However, if this is not the case, the controller must be retuned, affecting production times. In this work, an adaptive PID controller is developed for a DC motor speed plant using an artificial intelligence algorithm based on reinforcement learning. This algorithm uses an actor–critic agent, where its objective is to optimize the actor’s policy and train a critic for rewards. This will generate the appropriate gains without the need to know the system. The Deep Deterministic Policy Gradient with Twin Delayed (DDPG TD3) was used, with a network composed of 300 neurons for the agent’s learning. Finally, the performance of the obtained controller is compared with a classical control one using a cost function. Full article
(This article belongs to the Special Issue Bionic Artificial Neural Networks and Artificial Intelligence)
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20 pages, 37838 KiB  
Article
Research on Self-Stiffness Adjustment of Growth-Controllable Continuum Robot (GCCR) Based on Elastic Force Transmission
by Mingyuan Wang, Jianjun Yuan, Sheng Bao, Liang Du and Shugen Ma
Biomimetics 2023, 8(5), 433; https://doi.org/10.3390/biomimetics8050433 - 18 Sep 2023
Cited by 2 | Viewed by 1047
Abstract
Continuum robots have good adaptability in unstructured and complex environments. However, affected by their inherent nature of flexibility and slender structure, there are challenges in high-precision motion and load. Thus, stiffness adjustment for continuum robots has consistently attracted the attention of researchers. In [...] Read more.
Continuum robots have good adaptability in unstructured and complex environments. However, affected by their inherent nature of flexibility and slender structure, there are challenges in high-precision motion and load. Thus, stiffness adjustment for continuum robots has consistently attracted the attention of researchers. In this paper, a stiffness adjustment mechanism (SAM) is proposed and built in a growth-controllable continuum robot (GCCR) to improve the motion accuracy in variable scale motion. The self-stiffness adjustment is realized by antagonism through cable force transmission during the length change of the continuum robot. With a simple structure, the mechanism has a scarce impact on the weight and mass distribution of the robot and required no independent actuators for stiffness adjustment. Following this, a static model considering gravity and end load is established. The presented theoretical static model is applicable to predict the shape deformations of robots under different loads. The experimental validations showed that the maximum error ratio is within 5.65%. The stiffness of the robot can be enhanced by nearly 79.6%. Full article
(This article belongs to the Special Issue Design and Control of a Bio-Inspired Robot)
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12 pages, 1955 KiB  
Article
Enhanced Synaptic Behaviors in Chitosan Electrolyte-Based Electric-Double-Layer Transistors with Poly-Si Nanowire Channel Structures
by Dong-Hee Lee, Hwi-Su Kim, Ki-Woong Park, Hamin Park and Won-Ju Cho
Biomimetics 2023, 8(5), 432; https://doi.org/10.3390/biomimetics8050432 - 18 Sep 2023
Viewed by 1090
Abstract
In this study, we enhance the synaptic behavior of artificial synaptic transistors by utilizing nanowire (NW)-type polysilicon channel structures. The high surface-to-volume ratio of the NW channels enables efficient modulation of the channel conductance, which is interpreted as the synaptic weight. As a [...] Read more.
In this study, we enhance the synaptic behavior of artificial synaptic transistors by utilizing nanowire (NW)-type polysilicon channel structures. The high surface-to-volume ratio of the NW channels enables efficient modulation of the channel conductance, which is interpreted as the synaptic weight. As a result, NW-type synaptic transistors exhibit a larger hysteresis window compared to film-type synaptic transistors, even within the same gate voltage sweeping range. Moreover, NW-type synaptic transistors demonstrate superior short-term facilitation and long-term memory transition compared with film-type ones, as evidenced by the measured paired-pulse facilitation and excitatory post-synaptic current characteristics at varying frequencies and pulse numbers. Additionally, we observed gradual potentiation/depression characteristics, making these artificial synapses applicable to artificial neural networks. Furthermore, the NW-type synaptic transistors exhibit improved Modified National Institute of Standards and Technology pattern recognition rate of 91.2%. In conclusion, NW structure channels are expected to be a promising technology for next-generation artificial intelligence (AI) semiconductors, and the integration of NW structure channels has significant potential to advance AI semiconductor technology. Full article
(This article belongs to the Special Issue Bionic Engineering for Boosting Multidisciplinary Integration 2023)
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13 pages, 6103 KiB  
Article
Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm
by Xin Li, Mingyang Li, Moduo Yu and Qinqin Fan
Biomimetics 2023, 8(5), 431; https://doi.org/10.3390/biomimetics8050431 - 18 Sep 2023
Viewed by 1025
Abstract
Distribution network reconfiguration involves altering the topology structure of distribution networks by adjusting the switch states, which plays an important role in the smart grid since it can effectively isolate faults, reduce the power loss, and improve the system stability. However, the fault [...] Read more.
Distribution network reconfiguration involves altering the topology structure of distribution networks by adjusting the switch states, which plays an important role in the smart grid since it can effectively isolate faults, reduce the power loss, and improve the system stability. However, the fault reconfiguration of the distribution network is often regarded as a single-objective or multi-objective optimization problem, and its multimodality is often ignored in existing studies. Therefore, the obtained solutions may be unsuitable or infeasible when the environment changes. To improve the availability and robustness of the solutions, an improved discrete multimodal multi-objective particle swarm optimization (IDMMPSO) algorithm is proposed to solve the fault reconfiguration problem of the distribution network. To demonstrate the performance of the proposed IDMMPSO algorithm, the IEEE33-bus distribution system is used in the experiment. Moreover, the proposed algorithm is compared with other competitors. Experimental results show that the proposed algorithm can provide different equivalent solutions for decision-makers in solving the fault reconfiguration problem of the distribution network. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)
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23 pages, 12088 KiB  
Article
Design and Experiment of a Biomimetic Duckbill-like Vibration Chain for Physical Weed Control during the Rice Tillering Stage
by Longyu Fang, Xiwen Luo, Zaiman Wang, Wenwu Yang, Hui Li, Shiyu Song, Haoyang Xie, Jianhao Hu, Weiman Chen and Qinghai Liu
Biomimetics 2023, 8(5), 430; https://doi.org/10.3390/biomimetics8050430 - 18 Sep 2023
Viewed by 1149
Abstract
The widespread use of chemical herbicides has jeopardized concerns about food safety and ecological consequences. To address these issues and reduce reliance on chemical herbicides, a physical weed control device was developed for the tillering stage in paddy fields. This device features a [...] Read more.
The widespread use of chemical herbicides has jeopardized concerns about food safety and ecological consequences. To address these issues and reduce reliance on chemical herbicides, a physical weed control device was developed for the tillering stage in paddy fields. This device features a biomimetic duckbill-like vibration chain that effectively controls weed outbreaks. The chain penetrates the soft surface soil of the paddy field under gravity and rapidly stirs the soil through vibration, leading to the detachment of the weed roots anchored in the surface layer. Simultaneously, the device avoids mechanical damage to rice seedlings rooted in deeper soil. This study aimed to investigate the effects of chain structural parameters (the number of chain rows, vibration amplitude, and length of chains) and operational parameters (vibration frequency and working velocity) on weed control efficiency and rice seedling damage. Through a central composite regression field test, the optimal device structure and operational parameters were determined. The optimization results demonstrated that a vibration amplitude of 78.8 mm, a chain length of 93.47 cm, and 3.4 rows of chains, along with a vibration frequency and working velocity ranging from 0.5 to 1.25 m/s, achieved an optimal weeding effect. Under the optimal parameter combination, field test results demonstrated that approximately 80% of the weeds in the field were effectively cleared. This indicates that the design of the biomimetic duckbill-like vibration chain weeding device exhibits a relatively superior weeding performance, offering a practical solution for the management of weeds in rice fields. Full article
(This article belongs to the Special Issue Biomimetics in Agri-Food: From Preliminary Design to Field Applications)
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11 pages, 2117 KiB  
Article
A Bionic Venus Flytrap Soft Microrobot Driven by Multiphysics for Intelligent Transportation
by Xiaowen Wang, Yingnan Gao, Xiaoyang Ma, Weiqiang Li and Wenguang Yang
Biomimetics 2023, 8(5), 429; https://doi.org/10.3390/biomimetics8050429 - 17 Sep 2023
Cited by 1 | Viewed by 1152
Abstract
With the continuous integration of material science and bionic technology, as well as increasing requirements for the operation of robots in complex environments, researchers continue to develop bionic intelligent microrobots, the development of which will cause a great revolution in daily life and [...] Read more.
With the continuous integration of material science and bionic technology, as well as increasing requirements for the operation of robots in complex environments, researchers continue to develop bionic intelligent microrobots, the development of which will cause a great revolution in daily life and productivity. In this study, we propose a bionic flower based on the PNIPAM–PEGDA bilayer structure. PNIPAM is temperature-responsive and solvent-responsive, thus acting as an active layer, while PEGDA does not change significantly in response to a change in temperature and solvent, thus acting as a rigid layer. The bilayer flower is closed in cold water and gradually opens under laser illumination. In addition, the flower gradually opens after injecting ethanol into the water. When the volume of ethanol exceeds the volume of water, the flower opens completely. In addition, we propose a bionic Venus flytrap soft microrobot with a bilayer structure. The robot is temperature-responsive and can reversibly transform from a 2D sheet to a 3D tubular structure. It is normally in a closed state in both cold (T < 32 °C) and hot water (T > 32 °C), and can be used to load and transport objects to the target position (magnetic field strength < 1 T). Full article
(This article belongs to the Special Issue Advance in Bio-Inspired Micro-Robotics)
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26 pages, 2272 KiB  
Article
An Improved Harris Hawks Optimization Algorithm and Its Application in Grid Map Path Planning
by Lin Huang, Qiang Fu and Nan Tong
Biomimetics 2023, 8(5), 428; https://doi.org/10.3390/biomimetics8050428 - 15 Sep 2023
Cited by 2 | Viewed by 1162
Abstract
Aimed at the problems of the Harris Hawks Optimization (HHO) algorithm, including the non-origin symmetric interval update position out-of-bounds rate, low search efficiency, slow convergence speed, and low precision, an Improved Harris Hawks Optimization (IHHO) algorithm is proposed. In this algorithm, a circle [...] Read more.
Aimed at the problems of the Harris Hawks Optimization (HHO) algorithm, including the non-origin symmetric interval update position out-of-bounds rate, low search efficiency, slow convergence speed, and low precision, an Improved Harris Hawks Optimization (IHHO) algorithm is proposed. In this algorithm, a circle map was added to replace the pseudo-random initial population, and the population boundary number was reduced to improve the efficiency of the location update. By introducing a random-oriented strategy, the information exchange between populations was increased and the out-of-bounds position update was reduced. At the same time, the improved sine-trend search strategy was introduced to improve the search performance and reduce the out-of-bound rate. Then, a nonlinear jump strength combining escape energy and jump strength was proposed to improve the convergence accuracy of the algorithm. Finally, the simulation experiment was carried out on the test function and the path planning application of a 2D grid map. The results show that the Improved Harris Hawks Optimization algorithm is more competitive in solving accuracy, convergence speed, and non-origin symmetric interval search efficiency, and verifies the feasibility and effectiveness of the Improved Harris Hawks Optimization in the path planning of a grid map. Full article
(This article belongs to the Special Issue Nature-Inspired Computer Algorithms: 2nd Edition)
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23 pages, 47149 KiB  
Article
A Navigation Path Search and Optimization Method for Mobile Robots Based on the Rat Brain’s Cognitive Mechanism
by Yishen Liao, Naigong Yu and Jinhan Yan
Biomimetics 2023, 8(5), 427; https://doi.org/10.3390/biomimetics8050427 - 14 Sep 2023
Viewed by 1051
Abstract
Rats possess exceptional navigational abilities, allowing them to adaptively adjust their navigation paths based on the environmental structure. This remarkable ability is attributed to the interactions and regulatory mechanisms among various spatial cells within the rat’s brain. Based on these, this paper proposes [...] Read more.
Rats possess exceptional navigational abilities, allowing them to adaptively adjust their navigation paths based on the environmental structure. This remarkable ability is attributed to the interactions and regulatory mechanisms among various spatial cells within the rat’s brain. Based on these, this paper proposes a navigation path search and optimization method for mobile robots based on the rat brain’s cognitive mechanism. The aim is to enhance the navigation efficiency of mobile robots. The mechanism of this method is based on developing a navigation habit. Firstly, the robot explores the environment to search for the navigation goal. Then, with the assistance of boundary vector cells, the greedy strategy is used to guide the robot in generating a locally optimal path. Once the navigation path is generated, a dynamic self-organizing model based on the hippocampal CA1 place cells is constructed to further optimize the navigation path. To validate the effectiveness of the method, this paper designs several 2D simulation experiments and 3D robot simulation experiments, and compares the proposed method with various algorithms. The experimental results demonstrate that the proposed method not only surpasses other algorithms in terms of path planning efficiency but also yields the shortest navigation path. Moreover, the method exhibits good adaptability to dynamic navigation tasks. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)
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20 pages, 4463 KiB  
Article
MPPT of PEM Fuel Cell Using PI-PD Controller Based on Golden Jackal Optimization Algorithm
by Ahmed M. Agwa, Tarek I. Alanazi, Habib Kraiem, Ezzeddine Touti, Abdulaziz Alanazi and Dhari K. Alanazi
Biomimetics 2023, 8(5), 426; https://doi.org/10.3390/biomimetics8050426 - 14 Sep 2023
Cited by 5 | Viewed by 1255
Abstract
Subversive environmental impacts and limited amounts of conventional forms of energy necessitate the utilization of renewable energies (REs). Unfortunately, REs such as solar and wind energies are intermittent, so they should be stored in other forms to be used during their absence. One [...] Read more.
Subversive environmental impacts and limited amounts of conventional forms of energy necessitate the utilization of renewable energies (REs). Unfortunately, REs such as solar and wind energies are intermittent, so they should be stored in other forms to be used during their absence. One of the finest storage techniques for REs is based on hydrogen generation via an electrolyzer during abundance, then electricity generation by fuel cell (FC) during their absence. With reference to the advantages of the proton exchange membrane fuel cell (PEM-FC), this is preferred over other kinds of FCs. The output power of the PEM-FC is not constant, since it depends on hydrogen pressure, cell temperature, and electric load. Therefore, a maximum power point tracking (MPPT) system should be utilized with PEM-FC. The techniques previously utilized have some disadvantages, such as slowness of response and largeness of each oscillation, overshoot and undershoot, so this article addresses an innovative MPPT for PEM-FC using a consecutive controller made up of proportional-integral (PI) and proportional-derivative (PD) controllers whose gains are tuned via the golden jackal optimization algorithm (GJOA). Simulation results when applying the GJOA-PI-PD controller for MPPT of PEM-FC reveal its advantages over other approaches according to quickness of response, smallness of oscillations, and tininess of overshoot and undershoot. The overshoot resulting using the GJOA-PI-PD controller for MPPT of PEM-FC is smaller than that of perturb and observe, GJOA-PID, and GJOA-FOPID controllers by 98.26%, 86.30%, and 89.07%, respectively. Additionally, the fitness function resulting when using the GJOA-PI-PD controller for MPPT of PEM-FC is smaller than that of the aforementioned approaches by 93.95%, 87.17%, and 87.97%, respectively. Full article
(This article belongs to the Special Issue Biomimicry for Optimization, Control, and Automation)
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13 pages, 2409 KiB  
Article
Lightweight Soft Robotic Glove with Whole-Hand Finger Motion Tracking for Hand Rehabilitation in Virtual Reality
by Fengguan Li, Jiahong Chen, Zhitao Zhou, Jiefeng Xie, Zishu Gao, Yuxiang Xiao, Pei Dai, Chanchan Xu, Xiaojie Wang and Yitong Zhou
Biomimetics 2023, 8(5), 425; https://doi.org/10.3390/biomimetics8050425 - 14 Sep 2023
Cited by 2 | Viewed by 1721
Abstract
Soft robotic gloves have attracted significant interest in hand rehabilitation in the past decade. However, current solutions are still heavy and lack finger-state monitoring and versatile treatment options. To address this, we present a lightweight soft robotic glove actuated by twisted string actuators [...] Read more.
Soft robotic gloves have attracted significant interest in hand rehabilitation in the past decade. However, current solutions are still heavy and lack finger-state monitoring and versatile treatment options. To address this, we present a lightweight soft robotic glove actuated by twisted string actuators (TSA) that provides whole-hand finger motion tracking. We have developed a virtual reality environment for hand rehabilitation training, allowing users to interact with various virtual objects. Fifteen small inertial measurement units are placed on the glove to predict finger joint angles and track whole-hand finger motion. We performed TSA experiments to identify design and control rules, by understanding how their response varies with input load and voltages. Grasping experiments were conducted to determine the grasping force and range of motion. Finally, we showcase an application of the rehabilitation glove in a Unity-based VR interface, which can actuate the operator’s fingers to grasp different virtual objects. Full article
(This article belongs to the Special Issue Advanced Service Robots: Exoskeleton Robots)
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16 pages, 2793 KiB  
Article
Dynamic System Stability Modeling Approach with Sparrow-Inspired Meta-Heuristic Optimization Algorithm
by Tianqi Xia, Mingming Zhang and Shaohong Wang
Biomimetics 2023, 8(5), 424; https://doi.org/10.3390/biomimetics8050424 - 13 Sep 2023
Viewed by 891
Abstract
Aiming at the accurate prediction of the inception of instability in a compressor, a dynamic system stability model is proposed based on a sparrow-inspired meta-heuristic optimization algorithm in this article. To achieve this goal, a spatial mode is employed for flow field feature [...] Read more.
Aiming at the accurate prediction of the inception of instability in a compressor, a dynamic system stability model is proposed based on a sparrow-inspired meta-heuristic optimization algorithm in this article. To achieve this goal, a spatial mode is employed for flow field feature extraction and modeling object acquisition. The nonlinear characteristic presented in the system is addressed using fuzzy entropy as the identification strategy to provide a basis for instability determination. Using Sparrow Search Algorithm (SSA) optimization, a Radial Basis Function Neural Network (RBFNN) is achieved for the performance prediction of system status. A Logistic SSA solution is first established to seek the optimal parameters of the RBFNN to enhance prediction accuracy and stability. On the basis of the RBFNN-LSSA hybrid model, the stall inception is detected about 35.8 revolutions in advance using fuzzy entropy identification. To further improve the multi-step network model, a Tent SSA is introduced to promote the accuracy and robustness of the model. A wider range of potential solutions within the TSSA are explored by incorporating the Tent mapping function. The TSSA-based optimization method proves a suitable adaptation for complex nonlinear dynamic modeling. And this method demonstrates superior performance, achieving 42 revolutions of advance warning with multi-step prediction. This RBFNN-TSSA model represents a novel and promising approach to the application of system modeling. These findings contribute to enhancing the abnormal warning capability of dynamic systems in compressors. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)
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23 pages, 4424 KiB  
Article
Enantioselective Biomimetic Structures Inspired by Oxi-Dase-Type Metalloenzymes, Utilizing Polynuclear Compounds Containing Copper (II) and Manganese (II) Ions as Building Blocks
by Didier Gómez, Jorge Acosta, Horacio López-Sandoval, Ricardo A. Torres-Palma and Yenny Ávila-Torres
Biomimetics 2023, 8(5), 423; https://doi.org/10.3390/biomimetics8050423 - 13 Sep 2023
Viewed by 1146
Abstract
This study focuses on developing and evaluating two novel enantioselective biomimetic models for the active centers of oxidases (ascorbate oxidase and catalase). These models aim to serve as alternatives to enzymes, which often have limited action and a delicate nature. For the ascorbate [...] Read more.
This study focuses on developing and evaluating two novel enantioselective biomimetic models for the active centers of oxidases (ascorbate oxidase and catalase). These models aim to serve as alternatives to enzymes, which often have limited action and a delicate nature. For the ascorbate oxidase (AO) model (compound 1), two enantiomers, S,S(+)cpse and R,R(−)cpse, were combined in a crystalline structure, resulting in a racemic compound. The analysis of their magnetic properties and electrochemical behavior revealed electronic transfer between six metal centers. Compound 1 effectively catalyzed the oxidation of ascorbic to dehydroascorbic acid, showing a 45.5% yield for the racemic form. This was notably higher than the enantiopure compounds synthesized previously and tested in the current report, which exhibited yields of 32% and 28% for the S,S(+)cpse and R,R(-)cpse enantiomers, respectively. This outcome highlights the influence of electronic interactions between metal ions in the racemic compound compared to pure enantiomers. On the other hand, for the catalase model (compound 2), both the compound and its enantiomer displayed polymeric properties and dimeric behavior in the solid and solution states, respectively. Compound 2 proved to be effective in catalyzing the oxidation of hydrogen peroxide to oxygen with a yield of 64.7%. In contrast, its enantiomer (with R,R(-)cpse) achieved only a 27% yield. This further validates the functional nature of the prepared biomimetic models for oxidases. This research underscores the importance of understanding and designing biomimetic models of metalloenzyme active centers for both biological and industrial applications. These models show promising potential as viable alternatives to natural enzymes in various processes. Full article
(This article belongs to the Section Biomimetics of Materials and Structures)
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16 pages, 6506 KiB  
Article
Artificial Neural Network Model with Astrocyte-Driven Short-Term Memory
by Ilya A. Zimin, Victor B. Kazantsev and Sergey V. Stasenko
Biomimetics 2023, 8(5), 422; https://doi.org/10.3390/biomimetics8050422 - 12 Sep 2023
Cited by 1 | Viewed by 1391
Abstract
In this study, we introduce an innovative hybrid artificial neural network model incorporating astrocyte-driven short-term memory. The model combines a convolutional neural network with dynamic models of short-term synaptic plasticity and astrocytic modulation of synaptic transmission. The model’s performance was evaluated using simulated [...] Read more.
In this study, we introduce an innovative hybrid artificial neural network model incorporating astrocyte-driven short-term memory. The model combines a convolutional neural network with dynamic models of short-term synaptic plasticity and astrocytic modulation of synaptic transmission. The model’s performance was evaluated using simulated data from visual change detection experiments conducted on mice. Comparisons were made between the proposed model, a recurrent neural network simulating short-term memory based on sustained neural activity, and a feedforward neural network with short-term synaptic depression (STPNet) trained to achieve the same performance level as the mice. The results revealed that incorporating astrocytic modulation of synaptic transmission enhanced the model’s performance. Full article
(This article belongs to the Special Issue Neuromorphic Engineering: Biomimicry from the Brain)
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15 pages, 6513 KiB  
Article
3D-Printed Tumor-on-a-Chip Model for Investigating the Effect of Matrix Stiffness on Glioblastoma Tumor Invasion
by Meitham Amereh, Amir Seyfoori, Briana Dallinger, Mostafa Azimzadeh, Evan Stefanek and Mohsen Akbari
Biomimetics 2023, 8(5), 421; https://doi.org/10.3390/biomimetics8050421 - 11 Sep 2023
Viewed by 1507
Abstract
Glioblastoma multiform (GBM) tumor progression has been recognized to be correlated with extracellular matrix (ECM) stiffness. Dynamic variation of tumor ECM is primarily regulated by a family of enzymes which induce remodeling and degradation. In this paper, we investigated the effect of matrix [...] Read more.
Glioblastoma multiform (GBM) tumor progression has been recognized to be correlated with extracellular matrix (ECM) stiffness. Dynamic variation of tumor ECM is primarily regulated by a family of enzymes which induce remodeling and degradation. In this paper, we investigated the effect of matrix stiffness on the invasion pattern of human glioblastoma tumoroids. A 3D-printed tumor-on-a-chip platform was utilized to culture human glioblastoma tumoroids with the capability of evaluating the effect of stiffness on tumor progression. To induce variations in the stiffness of the collagen matrix, different concentrations of collagenase were added, thereby creating an inhomogeneous collagen concentration. To better understand the mechanisms involved in GBM invasion, an in silico hybrid mathematical model was used to predict the evolution of a tumor in an inhomogeneous environment, providing the ability to study multiple dynamic interacting variables. The model consists of a continuum reaction–diffusion model for the growth of tumoroids and a discrete model to capture the migration of single cells into the surrounding tissue. Results revealed that tumoroids exhibit two distinct patterns of invasion in response to the concentration of collagenase, namely ring-type and finger-type patterns. Moreover, higher concentrations of collagenase resulted in greater invasion lengths, confirming the strong dependency of tumor behavior on the stiffness of the surrounding matrix. The agreement between the experimental results and the model’s predictions demonstrates the advantages of this approach in investigating the impact of various extracellular matrix characteristics on tumor growth and invasion. Full article
(This article belongs to the Special Issue Organ-on-a-Chip Platforms for Drug Delivery Systems)
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18 pages, 2667 KiB  
Article
Development of a New Control System for a Rehabilitation Robot Using Electrical Impedance Tomography and Artificial Intelligence
by Alireza Abbasimoshaei, Adithya Kumar Chinnakkonda Ravi and Thorsten Alexander Kern
Biomimetics 2023, 8(5), 420; https://doi.org/10.3390/biomimetics8050420 - 11 Sep 2023
Cited by 8 | Viewed by 1289
Abstract
In this study, we present a tomography-based control system for a rehabilitation robot using a novel approach to assess advancement and a dynamic model of the system. In this model, the torque generated by the robot and the impedance of the patient’s hand [...] Read more.
In this study, we present a tomography-based control system for a rehabilitation robot using a novel approach to assess advancement and a dynamic model of the system. In this model, the torque generated by the robot and the impedance of the patient’s hand are used to determine each step of the rehabilitation. In the proposed control architecture, a regression model is developed and implemented based on the extraction of tomography signals to estimate the muscles state. During the rehabilitation session, the torque applied by the patient is adjusted according to this estimation. The first step of this protocol is to calculate the subject-specific parameters. These include the axis offset, inertia parameters, passive damping and stiffness. The second step involves identifying the other elements of the model, such as the torque resulting from interaction. In this case, the robot will calculate the torque generated by the patient. The developed robot-based solution and the suggested protocol were tested on different participants and showed promising results. First, the prediction of the impedance–position relationship was evaluated, and the prediction was below 2% error. Then, different participants with different impedances were tested, and the results showed that the control system controlled the force and position for each participant individually. Full article
(This article belongs to the Special Issue Intelligent Human-Robot Interaction)
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18 pages, 6444 KiB  
Article
Preparation and Characterization of Nano-Silver-Loaded Antibacterial Membrane via Coaxial Electrospinning
by Qingxi Hu, Zhenwei Huang, Haiguang Zhang and Murugan Ramalingam
Biomimetics 2023, 8(5), 419; https://doi.org/10.3390/biomimetics8050419 - 11 Sep 2023
Cited by 1 | Viewed by 1110
Abstract
The coaxial electrospinning process has been widely used in the biomedical field, and its process parameters affect product quality seriously. In this paper, the influence of key process parameters of coaxial electrostatic spinning (solution concentration, electrospinning voltage, acceptance distance and liquid supply velocity) [...] Read more.
The coaxial electrospinning process has been widely used in the biomedical field, and its process parameters affect product quality seriously. In this paper, the influence of key process parameters of coaxial electrostatic spinning (solution concentration, electrospinning voltage, acceptance distance and liquid supply velocity) on the preparation of a membrane with Chitosan, Polyethylene oxide and nano-silver as the core layer and Polycaprolactone as the shell layer was studied. The optimal combination of key process parameters was obtained by using an orthogonal test, scanning electron microscope, transmission electron microscope and macro-characterization diagram. The results showed that the coaxial electrospun membrane had good mechanical properties (tensile strength is about 2.945 Mpa), hydrophilicity (the water contact angle is about 72.28°) and non-cytotoxicity, which was conducive to cell adhesion and proliferation. The coaxial electrospun membrane with nano-silver has an obvious inhibitory effect on Escherichia coli and Staphylococcus aureus. In summary, the coaxial electrospun membrane that we produced is expected to be used in clinical medicine, such as vascular stent membranes and bionic blood vessels. Full article
(This article belongs to the Special Issue Biomaterials for Cardiovascular Repairs and Cardiovascular Biomechanics)
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22 pages, 7978 KiB  
Article
Otsu Multi-Threshold Image Segmentation Based on Adaptive Double-Mutation Differential Evolution
by Yanmin Guo, Yu Wang, Kai Meng and Zongna Zhu
Biomimetics 2023, 8(5), 418; https://doi.org/10.3390/biomimetics8050418 - 08 Sep 2023
Cited by 3 | Viewed by 1249
Abstract
A quick and effective way of segmenting images is the Otsu threshold method. However, the complexity of time grows exponentially as the number of thresolds rises. The aim of this study is to address the issues with the standard threshold image segmentation method’s [...] Read more.
A quick and effective way of segmenting images is the Otsu threshold method. However, the complexity of time grows exponentially as the number of thresolds rises. The aim of this study is to address the issues with the standard threshold image segmentation method’s low segmentation effect and high time complexity. The two mutations differential evolution based on adaptive control parameters is presented, and the twofold mutation approach and adaptive control parameter search mechanism are used. Superior double-mutation differential evolution views Otsu threshold picture segmentation as an optimization issue, uses the maximum interclass variance technique as the objective function, determines the ideal threshold, and then implements multi-threshold image segmentation. The experimental findings demonstrate the robustness of the enhanced double-mutation differential evolution with adaptive control parameters. Compared to other benchmark algorithms, our algorithm excels in both image segmentation accuracy and time complexity, offering superior performance. Full article
(This article belongs to the Special Issue Biomimetic and Bioinspired Computer Vision and Image Processing)
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