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Biomimetics
Volume 9
Issue 6
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Biomimetics, Volume 9, Issue 6 (June 2024) – 68 articles

Cover Story (view full-size image): Hydroxyapatite (HAp) is a calcium phosphate bioceramic with the chemical formula [Ca10(PO4)6(OH)2] and is the predominant inorganic constituent of bone and dental tissues. The substitution of Ca2+ ions in the HAp structure with foreign ions has the potential to improve its properties, making it a promising candidate for various orthopedic and dental applications such as bone filling, implant coatings, tissue engineering scaffolds, graft substitutes, and more. Among the lanthanides, samarium emerges as a pivotal element due to its relative affordability, antibacterial properties, and ability to form stable Sm3+ cations with a strong affinity for bone minerals. Thus, doping HAp with Sm3+ ions could significantly enhance its biocompatibility and biological activity, showing great potential for future bone regeneration applications. View this paper
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14 pages, 5235 KiB  
Article
Continuous Optical Zoom Compound Eye Imaging Using Alvarez Lenses Actuated by Dielectric Elastomers
by Chuanxun Chen, Qun Hao, Lin Liu, Jie Cao, Zhibo Qiao and Yang Cheng
Biomimetics 2024, 9(6), 374; https://doi.org/10.3390/biomimetics9060374 - 20 Jun 2024
Viewed by 972
Abstract
The compound eye is a natural multi-aperture optical imaging system. In this paper, a continuous optical zoom compound eye imaging system based on Alvarez lenses is proposed. The main optical imaging part of the proposed system consists of a curved Alvarez lens array [...] Read more.
The compound eye is a natural multi-aperture optical imaging system. In this paper, a continuous optical zoom compound eye imaging system based on Alvarez lenses is proposed. The main optical imaging part of the proposed system consists of a curved Alvarez lens array (CALA) and two Alvarez lenses. The movement of the CALA and two Alvarez lenses perpendicular to the optical axis is realized by the actuation of the dielectric elastomers (DEs). By adjusting the focal length of the CALA and the two Alvarez lenses, the proposed system can realize continuous zoom imaging without any mechanical movement vertically to the optical axis. The experimental results show that the paraxial magnification of the target can range from ∼0.30× to ∼0.9×. The overall dimensions of the optical imaging part are 54 mm × 36 mm ×60 mm (L × W × H). The response time is 180 ms. The imaging resolution can reach up to 50 lp/mm during the optical zoom process. The proposed continuous optical zoom compound eye imaging system has potential applications in various fields, including large field of view imaging, medical diagnostics, machine vision, and distance detection. Full article
(This article belongs to the Special Issue Bionic Imaging and Optical Devices: 2nd Edition)
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35 pages, 10426 KiB  
Review
Bridging Nature and Engineering: Protein-Derived Materials for Bio-Inspired Applications
by Taufiq Nawaz, Liping Gu, Jaimie Gibbons, Zhong Hu and Ruanbao Zhou
Biomimetics 2024, 9(6), 373; https://doi.org/10.3390/biomimetics9060373 - 20 Jun 2024
Cited by 3 | Viewed by 1790
Abstract
The sophisticated, elegant protein-polymers designed by nature can serve as inspiration to redesign and biomanufacture protein-based materials using synthetic biology. Historically, petro-based polymeric materials have dominated industrial activities, consequently transforming our way of living. While this benefits humans, the fabrication and disposal of [...] Read more.
The sophisticated, elegant protein-polymers designed by nature can serve as inspiration to redesign and biomanufacture protein-based materials using synthetic biology. Historically, petro-based polymeric materials have dominated industrial activities, consequently transforming our way of living. While this benefits humans, the fabrication and disposal of these materials causes environmental sustainability challenges. Fortunately, protein-based biopolymers can compete with and potentially surpass the performance of petro-based polymers because they can be biologically produced and degraded in an environmentally friendly fashion. This paper reviews four groups of protein-based polymers, including fibrous proteins (collagen, silk fibroin, fibrillin, and keratin), elastomeric proteins (elastin, resilin, and wheat glutenin), adhesive/matrix proteins (spongin and conchiolin), and cyanophycin. We discuss the connection between protein sequence, structure, function, and biomimetic applications. Protein engineering techniques, such as directed evolution and rational design, can be used to improve the functionality of natural protein-based materials. For example, the inclusion of specific protein domains, particularly those observed in structural proteins, such as silk and collagen, enables the creation of novel biomimetic materials with exceptional mechanical properties and adaptability. This review also discusses recent advancements in the production and application of new protein-based materials through the approach of synthetic biology combined biomimetics, providing insight for future research and development of cutting-edge bio-inspired products. Protein-based polymers that utilize nature’s designs as a base, then modified by advancements at the intersection of biology and engineering, may provide mankind with more sustainable products. Full article
(This article belongs to the Special Issue Bio-Inspired Design for Structure Applications)
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24 pages, 5506 KiB  
Article
Developing a Biomimetic 3D Neointimal Layer as a Prothrombotic Substrate for a Humanized In Vitro Model of Atherothrombosis
by Jassim Echrish, Madalina-Ioana Pasca, David Cabrera, Ying Yang and Alan G. S. Harper
Biomimetics 2024, 9(6), 372; https://doi.org/10.3390/biomimetics9060372 - 20 Jun 2024
Viewed by 922
Abstract
Acute cardiovascular events result from clots caused by the rupture and erosion of atherosclerotic plaques. This paper aimed to produce a functional biomimetic hydrogel of the neointimal layer of the atherosclerotic plaque that can support thrombogenesis upon exposure to human blood. A biomimetic [...] Read more.
Acute cardiovascular events result from clots caused by the rupture and erosion of atherosclerotic plaques. This paper aimed to produce a functional biomimetic hydrogel of the neointimal layer of the atherosclerotic plaque that can support thrombogenesis upon exposure to human blood. A biomimetic hydrogel of the neointima was produced by culturing THP-1-derived foam cells within 3D collagen hydrogels in the presence or absence of atorvastatin. Prothrombin time and platelet aggregation onset were measured after exposure of the neointimal models to platelet-poor plasma and washed platelet suspensions prepared from blood of healthy, medication-free volunteers. Activity of the extrinsic coagulation pathway was measured using the fluorogenic substrate SN-17. Foam cell formation was observed following preincubation of the neointimal biomimetic hydrogels with oxidized LDL, and this was inhibited by pretreatment with atorvastatin. The neointimal biomimetic hydrogel was able to trigger platelet aggregation and blood coagulation upon exposure to human blood products. Atorvastatin pretreatment of the neointimal biomimetic layer significantly reduced its pro-aggregatory and pro-coagulant properties. In the future, this 3D neointimal biomimetic hydrogel can be incorporated as an additional layer within our current thrombus-on-a-chip model to permit the study of atherosclerosis development and the screening of anti-thrombotic drugs as an alternative to current animal models. Full article
(This article belongs to the Section Biomimetic Surfaces and Interfaces)
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22 pages, 18310 KiB  
Article
Advancing the Robotic Vision Revolution: Development and Evaluation of a Bionic Binocular System for Enhanced Robotic Vision
by Hongxin Zhang and Suan Lee
Biomimetics 2024, 9(6), 371; https://doi.org/10.3390/biomimetics9060371 - 19 Jun 2024
Cited by 2 | Viewed by 1220
Abstract
This paper describes a novel bionic eye binocular vision system designed to mimic the natural movements of the human eye. The system provides a broader field of view and enhances visual perception in complex environments. Compared with similar bionic binocular cameras, the JEWXON [...] Read more.
This paper describes a novel bionic eye binocular vision system designed to mimic the natural movements of the human eye. The system provides a broader field of view and enhances visual perception in complex environments. Compared with similar bionic binocular cameras, the JEWXON BC200 bionic binocular camera developed in this study is more miniature. It consumes only 2.8 W of power, which makes it ideal for mobile robots. Combining axis and camera rotation enables more seamless panoramic image synthesis and is therefore suitable for self-rotating bionic binocular cameras. In addition, combined with the YOLO-V8 model, the camera can accurately recognize objects such as clocks and keyboards. This research provides new ideas for the development of robotic vision systems. Full article
(This article belongs to the Special Issue Bio-Inspired and Biomimetic Intelligence in Robotics)
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17 pages, 10449 KiB  
Article
Design and Control of a Tendon-Driven Robotic Finger Based on Grasping Task Analysis
by Xuanyi Zhou, Hao Fu, Baoqing Shentu, Weidong Wang, Shibo Cai and Guanjun Bao
Biomimetics 2024, 9(6), 370; https://doi.org/10.3390/biomimetics9060370 - 19 Jun 2024
Viewed by 1419
Abstract
To analyze the structural characteristics of a human hand, data collection gloves were worn for typical grasping tasks. The hand manipulation characteristics, finger end pressure, and finger joint bending angle were obtained via an experiment based on the Feix grasping spectrum. Twelve types [...] Read more.
To analyze the structural characteristics of a human hand, data collection gloves were worn for typical grasping tasks. The hand manipulation characteristics, finger end pressure, and finger joint bending angle were obtained via an experiment based on the Feix grasping spectrum. Twelve types of tendon rope transmission paths were designed under the N + 1 type tendon drive mode, and the motion performance of these 12 types of paths applied to tendon-driven fingers was evaluated based on the evaluation metric. The experiment shows that the designed tendon path (d) has a good control effect on the fluctuations of tendon tension (within 0.25 N), the tendon path (e) has the best control effect on the joint angle of the tendon-driven finger, and the tendon path (l) has the best effect on reducing the friction between the tendon and the pulley. The obtained tendon-driven finger motion performance model based on 12 types of tendon paths is a good reference value for subsequent tendon-driven finger structure design and control strategies. Full article
(This article belongs to the Special Issue Biomimetic Aspects of Human–Computer Interactions)
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19 pages, 4470 KiB  
Article
Deep Learning and Neural Architecture Search for Optimizing Binary Neural Network Image Super Resolution
by Yuanxin Su, Li-minn Ang, Kah Phooi Seng and Jeremy Smith
Biomimetics 2024, 9(6), 369; https://doi.org/10.3390/biomimetics9060369 - 18 Jun 2024
Viewed by 1024
Abstract
The evolution of super-resolution (SR) technology has seen significant advancements through the adoption of deep learning methods. However, the deployment of such models by resource-constrained devices necessitates models that not only perform efficiently, but also conserve computational resources. Binary neural networks (BNNs) offer [...] Read more.
The evolution of super-resolution (SR) technology has seen significant advancements through the adoption of deep learning methods. However, the deployment of such models by resource-constrained devices necessitates models that not only perform efficiently, but also conserve computational resources. Binary neural networks (BNNs) offer a promising solution by minimizing the data precision to binary levels, thus reducing the computational complexity and memory requirements. However, for BNNs, an effective architecture is essential due to their inherent limitations in representing information. Designing such architectures traditionally requires extensive computational resources and time. With the advancement in neural architecture search (NAS), differentiable NAS has emerged as an attractive solution for efficiently crafting network structures. In this paper, we introduce a novel and efficient binary network search method tailored for image super-resolution tasks. We adapt the search space specifically for super resolution to ensure it is optimally suited for the requirements of such tasks. Furthermore, we incorporate Libra Parameter Binarization (Libra-PB) to maximize information retention during forward propagation. Our experimental results demonstrate that the network structures generated by our method require only a third of the parameters, compared to conventional methods, and yet deliver comparable performance. Full article
(This article belongs to the Special Issue New Insights into Bio-Inspired Neural Networks)
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19 pages, 518 KiB  
Article
A City Shared Bike Dispatch Approach Based on Temporal Graph Convolutional Network and Genetic Algorithm
by Ji Ma, Shenggen Zheng, Shangjing Lin and Yonghong Cheng
Biomimetics 2024, 9(6), 368; https://doi.org/10.3390/biomimetics9060368 - 17 Jun 2024
Viewed by 866
Abstract
Public transportation scheduling aims to optimize the allocation of resources, enhance efficiency, and increase passenger satisfaction, all of which are crucial for building a sustainable urban transportation system. As a complement to public transportation, bike-sharing systems provide users with a solution for the [...] Read more.
Public transportation scheduling aims to optimize the allocation of resources, enhance efficiency, and increase passenger satisfaction, all of which are crucial for building a sustainable urban transportation system. As a complement to public transportation, bike-sharing systems provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, including peak usage periods in the morning and evening and significant demand fluctuations across different areas, optimizing shared bike dispatch can better meet user needs, reduce vehicle vacancy rates, and increase operating revenue. To address this issue, this article proposes a comprehensive decision-making approach for spatiotemporal demand prediction and bike dispatch optimization. For demand prediction, we design a T-GCN (Temporal Graph Convolutional Network)-based bike demand prediction model. In terms of dispatch optimization, we consider factors such as dispatch capacity, distance restrictions, and dispatch costs, and design an optimization solution based on genetic algorithms. Finally, we validate the approach using shared bike operating data and show that the T-GCN can effectively predict the short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution, verifying the model’s effectiveness. The shared bike dispatch approach proposed in this paper combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch. Full article
(This article belongs to the Special Issue Biomimetic Techniques for Optimization Problems in Engineering)
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14 pages, 10031 KiB  
Article
Design of Apoptotic Cell-Inspired Particles as a Blood Coagulation Test
by Liang Yue, Yasuhiro Nakagawa and Mitsuhiro Ebara
Biomimetics 2024, 9(6), 367; https://doi.org/10.3390/biomimetics9060367 - 17 Jun 2024
Viewed by 724
Abstract
The blood coagulation test is an indispensable test for monitoring the blood coagulation and fibrinolysis functions. Currently, activated partial thromboplastin time (APTT) is the most widely used approach to coagulation testing. However, APTT reagents need to be optimized due to the fact that [...] Read more.
The blood coagulation test is an indispensable test for monitoring the blood coagulation and fibrinolysis functions. Currently, activated partial thromboplastin time (APTT) is the most widely used approach to coagulation testing. However, APTT reagents need to be optimized due to the fact that they are unstable, highly variable, and cannot be easily controlled. In this study, we created apoptotic cell-inspired methacryloyloxyethyl phosphorylserine (MPS) particles for blood coagulation as an alternative to conventional APTT reagents. Particle size could be controlled by changing the concentration of the polymer. The blood coagulation ability of particles was stable at different environmental temperatures. Moreover, the procoagulant activity could be enhanced by increasing the concentration to 0.06 mg/mL and reducing the size of the particles to around 900 nm. Fibrin clotted by particles showed no significant difference from that formed by APTT regent Actin FSL. We propose that MPS particles are a potential alternative to Actin FS for the application of blood coagulation tests. Full article
(This article belongs to the Section Biomimetics of Materials and Structures)
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13 pages, 19662 KiB  
Article
Three-Dimensional Bioprinted Skin Microrelief and Its Role in Skin Aging
by Wenxuan Sun, Bo Wang, Tianhao Yang, Ruixue Yin, Feifei Wang, Hongbo Zhang and Wenjun Zhang
Biomimetics 2024, 9(6), 366; https://doi.org/10.3390/biomimetics9060366 - 17 Jun 2024
Cited by 1 | Viewed by 1101
Abstract
Skin aging is a complex physiological process, in which cells and the extracellular matrix (ECM) interreact, which leads to a change in the mechanical properties of skin, which in turn affects the cell secretion and ECM deposition. The natural skin microrelief that exists [...] Read more.
Skin aging is a complex physiological process, in which cells and the extracellular matrix (ECM) interreact, which leads to a change in the mechanical properties of skin, which in turn affects the cell secretion and ECM deposition. The natural skin microrelief that exists from birth has rarely been taken into account when evaluating skin aging, apart from the common knowledge that microreliefs might serve as the starting point or initialize micro-wrinkles. In fact, microrelief itself also changes with aging. Does the microrelief have other, better uses? In this paper, owing to the fast-developing 3D printing technology, skin wrinkles with microrelief of different age groups were successfully manufactured using the Digital light processing (DLP) technology. The mechanical properties of skin samples with and without microrelief were tested. It was found that microrelief has a big impact on the elastic modulus of skin samples. In order to explore the role of microrelief in skin aging, the wrinkle formation was numerically analyzed. The microrelief models of different age groups were created using the modified Voronoi algorithm for the first time, which offers fast and flexible mesh formation. We found that skin microrelief plays an important role in regulating the modulus of the epidermis, which is the dominant factor in wrinkle formation. The wrinkle length and depth were also analyzed numerically for the first time, owing to the additional dimension offered by microrelief. The results showed that wrinkles are mainly caused by the modulus change of the epidermis in the aging process, and compared with the dermis, the hypodermis is irrelevant to wrinkling. Hereby, we developed a hypothesis that microrelief makes the skin adaptive to the mechanical property changes from aging by adjusting its shape and size. The native-like skin samples with microrelief might shed a light on the mechanism of wrinkling and also help with understanding the complex physiological processes associated with human skin. Full article
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8 pages, 745 KiB  
Article
Effect of Zeolite Incorporation on the Ion Release Properties of Silver-Reinforced Glass Ionomer Cement
by Jessica Tan, Jessica Hao, David Vann, Krešimir Pavelić and Fusun Ozer
Biomimetics 2024, 9(6), 365; https://doi.org/10.3390/biomimetics9060365 - 17 Jun 2024
Viewed by 810
Abstract
Background: Zeolite can release antimicrobial silver ions in a targeted and controlled manner for an extended time, selectively inhibiting the growth of pathogenic oral bacteria when added to dental materials. The objective of this study was to investigate the effect of the addition [...] Read more.
Background: Zeolite can release antimicrobial silver ions in a targeted and controlled manner for an extended time, selectively inhibiting the growth of pathogenic oral bacteria when added to dental materials. The objective of this study was to investigate the effect of the addition of zeolite to silver-reinforced glass ionomer cement on the release of silver ions over time. Methods: Five concentrations of silver–zeolite (0%, 0.5%, 1%, 2%, 4% wt) were incorporated into silver-reinforced GIC in the form of 10 mm × 2 mm circular disks (n = 5). The disks were incubated in deionized water at 37 °C and ion release from the samples was measured at 1, 2, 7, and 30 days after immersion by inductively coupled atomic emission spectroscopy. Results: Incorporating silver–zeolite increased silver ion release from silver-reinforced GIC disks compared to the control disks (p < 0.05), while incorporating zeolite alone had no effect. Higher concentrations of added silver–zeolite resulted in increased silver ion release. Sustained silver ion release was observed for up to 30 days. Conclusion: Adding silver–zeolite to silver-reinforced GIC may enhance its extended antibacterial effect in the oral cavity. Full article
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31 pages, 8993 KiB  
Article
A Novel Multi-Scaled Deep Convolutional Structure for Punctilious Human Gait Authentication
by Reem N. Yousef, Mohamed Maher Ata, Amr E. Eldin Rashed, Mahmoud Badawy, Mostafa A. Elhosseini and Waleed M. Bahgat
Biomimetics 2024, 9(6), 364; https://doi.org/10.3390/biomimetics9060364 - 16 Jun 2024
Viewed by 967
Abstract
The need for non-interactive human recognition systems to ensure safe isolation between users and biometric equipment has been exposed by the COVID-19 pandemic. This study introduces a novel Multi-Scaled Deep Convolutional Structure for Punctilious Human Gait Authentication (MSDCS-PHGA). The proposed MSDCS-PHGA involves segmenting, [...] Read more.
The need for non-interactive human recognition systems to ensure safe isolation between users and biometric equipment has been exposed by the COVID-19 pandemic. This study introduces a novel Multi-Scaled Deep Convolutional Structure for Punctilious Human Gait Authentication (MSDCS-PHGA). The proposed MSDCS-PHGA involves segmenting, preprocessing, and resizing silhouette images into three scales. Gait features are extracted from these multi-scale images using custom convolutional layers and fused to form an integrated feature set. This multi-scaled deep convolutional approach demonstrates its efficacy in gait recognition by significantly enhancing accuracy. The proposed convolutional neural network (CNN) architecture is assessed using three benchmark datasets: CASIA, OU-ISIR, and OU-MVLP. Moreover, the proposed model is evaluated against other pre-trained models using key performance metrics such as precision, accuracy, sensitivity, specificity, and training time. The results indicate that the proposed deep CNN model outperforms existing models focused on human gait. Notably, it achieves an accuracy of approximately 99.9% for both the CASIA and OU-ISIR datasets and 99.8% for the OU-MVLP dataset while maintaining a minimal training time of around 3 min. Full article
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16 pages, 4495 KiB  
Article
Preliminary Analysis of Hydrodynamic Drag Reduction and Fouling Resistance of Surfaces Inspired by the Mollusk Shell, Dosinia juvenilis
by Benjamin W. Hamilton, O. Remus Tutunea-Fatan and Evgueni V. Bordatchev
Biomimetics 2024, 9(6), 363; https://doi.org/10.3390/biomimetics9060363 - 15 Jun 2024
Viewed by 768
Abstract
Many species of plants and animals show an ability to resist fouling with surface topographies tailored to their environments. The mollusk species Dosinia juvenilis has demonstrated the ability to resist the accumulation of fouling on its outer surface. Understanding the functional mechanism employed [...] Read more.
Many species of plants and animals show an ability to resist fouling with surface topographies tailored to their environments. The mollusk species Dosinia juvenilis has demonstrated the ability to resist the accumulation of fouling on its outer surface. Understanding the functional mechanism employed by nature represents a significant opportunity for the persistent challenges of many industrial and consumer applications. Using a biomimetic approach, this study investigates the underlying hydrodynamic mechanisms of fouling resistance through Large Eddy simulations of a turbulent boundary layer above a novel ribletted surface topography bio-inspired by the Dosinia juvenilis. The results indicate a maximum drag reduction of 6.8% relative to a flat surface. The flow statistics near the surface are analogous to those observed for other ribletted surfaces in that the appropriately sized riblets effectively reduce the spanwise and wall-normal velocity fluctuations near the surface. This study supports the understanding that nature employs ribletted surfaces toward multiple functionalities including the considered drag reduction and fouling resistance. Full article
(This article belongs to the Section Biomimetic Surfaces and Interfaces)
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42 pages, 1857 KiB  
Review
Review of the Brain’s Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM)
by Luis Irastorza-Valera, Edgar Soria-Gómez, José María Benitez, Francisco J. Montáns and Luis Saucedo-Mora
Biomimetics 2024, 9(6), 362; https://doi.org/10.3390/biomimetics9060362 - 14 Jun 2024
Viewed by 1475
Abstract
The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic [...] Read more.
The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections—the connectome—both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain. Full article
(This article belongs to the Special Issue Biomimetic Approaches in Healthcare—Innovations Inspired by Nature)
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44 pages, 18289 KiB  
Article
An Improved Multi-Strategy Crayfish Optimization Algorithm for Solving Numerical Optimization Problems
by Ruitong Wang, Shuishan Zhang and Guangyu Zou
Biomimetics 2024, 9(6), 361; https://doi.org/10.3390/biomimetics9060361 - 14 Jun 2024
Cited by 2 | Viewed by 1280
Abstract
The crayfish optimization algorithm (COA), proposed in 2023, is a metaheuristic optimization algorithm that is based on crayfish’s summer escape behavior, competitive behavior, and foraging behavior. COA has a good optimization performance, but it still suffers from the problems of slow convergence speed [...] Read more.
The crayfish optimization algorithm (COA), proposed in 2023, is a metaheuristic optimization algorithm that is based on crayfish’s summer escape behavior, competitive behavior, and foraging behavior. COA has a good optimization performance, but it still suffers from the problems of slow convergence speed and sensitivity to the local optimum. To solve these problems, an improved multi-strategy crayfish optimization algorithm for solving numerical optimization problems, called IMCOA, is proposed to address the shortcomings of the original crayfish optimization algorithm for each behavioral strategy. Aiming at the imbalance between local exploitation and global exploration in the summer heat avoidance and competition phases, this paper proposes a cave candidacy strategy and a fitness–distance balanced competition strategy, respectively, so that these two behaviors can better coordinate the global and local optimization capabilities and escape from falling into the local optimum prematurely. The directly foraging formula is modified during the foraging phase. The food covariance learning strategy is utilized to enhance the population diversity and improve the convergence accuracy and convergence speed. Finally, the introduction of an optimal non-monopoly search strategy to perturb the optimal solution for updates improves the algorithm’s ability to obtain a global best solution. We evaluated the effectiveness of IMCOA using the CEC2017 and CEC2022 test suites and compared it with eight algorithms. Experiments were conducted using different dimensions of CEC2017 and CEC2022 by performing numerical analyses, convergence analyses, stability analyses, Wilcoxon rank–sum tests and Friedman tests. Experiments on the CEC2017 and CEC2022 test suites show that IMCOA can strike a good balance between exploration and exploitation and outperforms the traditional COA and other optimization algorithms in terms of its convergence speed, optimization accuracy, and ability to avoid premature convergence. Statistical analysis shows that there is a significant difference between the performance of the IMCOA algorithm and other algorithms. Additionally, three engineering design optimization problems confirm the practicality of IMCOA and its potential to solve real-world problems. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)
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14 pages, 662 KiB  
Article
Gender-Driven English Speech Emotion Recognition with Genetic Algorithm
by Liya Yue, Pei Hu and Jiulong Zhu
Biomimetics 2024, 9(6), 360; https://doi.org/10.3390/biomimetics9060360 - 14 Jun 2024
Cited by 1 | Viewed by 1111
Abstract
Speech emotion recognition based on gender holds great importance for achieving more accurate, personalized, and empathetic interactions in technology, healthcare, psychology, and social sciences. In this paper, we present a novel gender–emotion model. First, gender and emotion features were extracted from voice signals [...] Read more.
Speech emotion recognition based on gender holds great importance for achieving more accurate, personalized, and empathetic interactions in technology, healthcare, psychology, and social sciences. In this paper, we present a novel gender–emotion model. First, gender and emotion features were extracted from voice signals to lay the foundation for our recognition model. Second, a genetic algorithm (GA) processed high-dimensional features, and the Fisher score was used for evaluation. Third, features were ranked by their importance, and the GA was improved through novel crossover and mutation methods based on feature importance, to improve the recognition accuracy. Finally, the proposed algorithm was compared with state-of-the-art algorithms on four common English datasets using support vector machines (SVM), and it demonstrated superior performance in accuracy, precision, recall, F1-score, the number of selected features, and running time. The proposed algorithm faced challenges in distinguishing between neutral, sad, and fearful emotions, due to subtle vocal differences, overlapping pitch and tone variability, and similar prosodic features. Notably, the primary features for gender-based differentiation mainly involved mel frequency cepstral coefficients (MFCC) and log MFCC. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)
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19 pages, 7512 KiB  
Article
Innovative Design of a 3D Printed Esophageal Stent Inspired by Nature: Mitigating Migration Challenges in Palliative Esophageal Cancer Therapy
by Thomas Profitiliotis, Savvas Koltsakidis, Konstantinos Tsongas and Dimitrios Tzetzis
Biomimetics 2024, 9(6), 359; https://doi.org/10.3390/biomimetics9060359 - 14 Jun 2024
Viewed by 1386
Abstract
Esophageal cancer is a complex and challenging tumor to treat, with esophageal stenting being used as a palliative measure to improve the quality of life of patients. Self-expandable metal stents (SEMS), self-expandable plastic stents (SEPS), and biodegradable stents are the most commonly used [...] Read more.
Esophageal cancer is a complex and challenging tumor to treat, with esophageal stenting being used as a palliative measure to improve the quality of life of patients. Self-expandable metal stents (SEMS), self-expandable plastic stents (SEPS), and biodegradable stents are the most commonly used types of stents. However, complications can arise, such as migration, bleeding, and perforation. To address issues of migration, this study developed a novel 3D printed bioinspired esophageal stent utilizing a highly flexible and ductile TPU material. The stent was designed to be self-expanding and tubular with flared ends to provide secure anchorage at both the proximal and distal ends of the structure. Suction cups were strategically placed around the shaft of the stent to prevent migration. The stent was evaluated through compression–recovery, self-expansion, and anti-migration tests to evaluate its recovery properties, self-expansion ability, and anchoring ability, respectively. The results indicated that the novel stent was able to recover its shape, expand, keep the esophagus open, and resist migration, demonstrating its potential for further research and clinical applications. Finite element analysis (FEA) was leveraged to analyze the stent’s mechanical behavior, providing insights into its structural integrity, self-expansion capability, and resistance against migration. These results, supported by FEA, highlight the potential of this innovative stent for further research and its eventual application in preclinical settings. Full article
(This article belongs to the Special Issue Biomimetic Approaches in Healthcare—Innovations Inspired by Nature)
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38 pages, 45161 KiB  
Review
Biomimetic Design of Soil-Engaging Components: A Review
by Zihe Xu, Hongyan Qi, Peng Gao, Shuo Wang, Xuanting Liu and Yunhai Ma
Biomimetics 2024, 9(6), 358; https://doi.org/10.3390/biomimetics9060358 - 14 Jun 2024
Cited by 1 | Viewed by 1840
Abstract
Soil-engaging components play a critical role in agricultural production and engineering construction. However, the soil-engaging components directly interacting with the soil often suffer from the problems of high resistance, adhesion, and wear, which significantly reduce the efficiency and quality of soil operations. A [...] Read more.
Soil-engaging components play a critical role in agricultural production and engineering construction. However, the soil-engaging components directly interacting with the soil often suffer from the problems of high resistance, adhesion, and wear, which significantly reduce the efficiency and quality of soil operations. A large number of featured studies on the design of soil-engaging components have been carried out while applying the principles of bionics extensively, and significant research results have been achieved. This review conducts a comprehensive literature survey on the application of biomimetics in the design of soil-engaging components. The focus is on performance optimization in regard to the following three aspects: draught reduction, anti-adhesion, and wear resistance. The mechanisms of various biomimetic soil-engaging components are systematically explained. Based on the literature analysis and biomimetic research, future trends in the development of biomimetic soil-engaging components are discussed from both the mechanism and application perspectives. This research is expected to provide new insights and inspiration for addressing related scientific and engineering challenges. Full article
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15 pages, 4583 KiB  
Article
Simultaneous Electrochemical Detection of Dopamine and Tryptophan Using 3D Goethite–Spongin Composites
by Sedigheh Falahi, Anita Kubiak, Alona Voronkina, Hermann Ehrlich, Yvonne Joseph and Parvaneh Rahimi
Biomimetics 2024, 9(6), 357; https://doi.org/10.3390/biomimetics9060357 - 14 Jun 2024
Viewed by 1218
Abstract
In this study, a facile approach for simultaneous determination of dopamine (DA) and tryptophan (TRP) using a 3D goethite–spongin-modified carbon paste electrode is reported. The prepared electrode exhibited excellent electrochemical catalytic activity towards DA and TRP oxidation. The electrochemical sensing of the modified [...] Read more.
In this study, a facile approach for simultaneous determination of dopamine (DA) and tryptophan (TRP) using a 3D goethite–spongin-modified carbon paste electrode is reported. The prepared electrode exhibited excellent electrochemical catalytic activity towards DA and TRP oxidation. The electrochemical sensing of the modified electrode was investigated using cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy. Through differential pulse voltammetry analysis, two well-separated oxidation peaks were observed at 28 and 77 mV, corresponding to the oxidation of DA and TRP at the working electrode, with a large peak separation of up to 490 mV. DA and TRP were determined both individually and simultaneously in their dualistic mixture. As a result, the anodic peak currents and the concentrations of DA and TRP were found to exhibit linearity within the ranges of 4–246 μM for DA and 2 to 150 μM for TRP. The detection limits (S/N = 3) as low as 1.9 μM and 0.37 μM were achieved for DA and TRP, respectively. The proposed sensor was successfully applied to the simultaneous determination of DA and TRP in human urine samples with satisfactory recoveries (101% to 116%). Full article
(This article belongs to the Special Issue Bio-Inspired Design for Structural and Sustainable Applications)
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22 pages, 2337 KiB  
Article
Exploitation of Bio-Inspired Classifiers for Performance Enhancement in Liver Cirrhosis Detection from Ultrasonic Images
by Karthikamani Ramamoorthy and Harikumar Rajaguru
Biomimetics 2024, 9(6), 356; https://doi.org/10.3390/biomimetics9060356 - 14 Jun 2024
Cited by 1 | Viewed by 852
Abstract
In the current scenario, liver abnormalities are one of the most serious public health concerns. Cirrhosis of the liver is one of the foremost causes of demise from liver diseases. To accurately predict the status of liver cirrhosis, physicians frequently use automated computer-aided [...] Read more.
In the current scenario, liver abnormalities are one of the most serious public health concerns. Cirrhosis of the liver is one of the foremost causes of demise from liver diseases. To accurately predict the status of liver cirrhosis, physicians frequently use automated computer-aided approaches. In this paper, through clustering techniques like fuzzy c-means (FCM), possibilistic fuzzy c-means (PFCM), and possibilistic c means (PCM) and sample entropy features are extracted from normal and cirrhotic liver ultrasonic images. The extracted features are classified as normal and cirrhotic through the Gaussian mixture model (GMM), Softmax discriminant classifier (SDC), harmonic search algorithm (HSA), SVM (linear), SVM (RBF), SVM (polynomial), artificial algae optimization (AAO), and hybrid classifier artificial algae optimization (AAO) with Gaussian mixture mode (GMM). The classifiers’ performances are compared based on accuracy, F1 Score, MCC, F measure, error rate, and Jaccard metric (JM). The hybrid classifier AAO–GMM, with the PFCM feature, outperforms the other classifiers and attained an accuracy of 99.03% with an MCC of 0.90. Full article
(This article belongs to the Section Bioinspired Sensorics, Information Processing and Control)
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18 pages, 1165 KiB  
Article
Exploiting Signal Propagation Delays to Match Task Memory Requirements in Reservoir Computing
by Stefan Iacob and Joni Dambre
Biomimetics 2024, 9(6), 355; https://doi.org/10.3390/biomimetics9060355 - 14 Jun 2024
Viewed by 761
Abstract
Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying axon properties. Recently, this feature was implemented in echo state [...] Read more.
Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying axon properties. Recently, this feature was implemented in echo state networks (ESNs), a type of RNN, by assigning spatial locations to neurons and introducing distance-dependent inter-neuron delays. These delays were shown to significantly improve ESN task performance. However, thus far, it is still unclear why distance-based delay networks (DDNs) perform better than ESNs. In this paper, we show that by optimizing inter-node delays, the memory capacity of the network matches the memory requirements of the task. As such, networks concentrate their memory capabilities to the points in the past which contain the most information for the task at hand. Moreover, we show that DDNs have a greater total linear memory capacity, with the same amount of non-linear processing power. Full article
(This article belongs to the Special Issue Bioinspired Algorithms)
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20 pages, 6470 KiB  
Article
Bionic 3D Path Planning for Plant Protection UAVs Based on Swarm Intelligence Algorithms and Krill Swarm Behavior
by Nuo Xu, Haochen Zhu and Jiyu Sun
Biomimetics 2024, 9(6), 353; https://doi.org/10.3390/biomimetics9060353 - 13 Jun 2024
Cited by 1 | Viewed by 895
Abstract
The protection of plants in mountainous and hilly areas differs from that in plain areas due to the complex terrain, which divides the work plot into many narrow plots. When designing the path planning method for plant protection UAVs, it is important to [...] Read more.
The protection of plants in mountainous and hilly areas differs from that in plain areas due to the complex terrain, which divides the work plot into many narrow plots. When designing the path planning method for plant protection UAVs, it is important to consider the generality in different working environments. To address issues such as poor path optimization, long operation time, and excessive iterations required by traditional swarm intelligence algorithms, this paper proposes a bionic three-dimensional path planning algorithm for plant protection UAVs. This algorithm aims to plan safe and optimal flight paths between work plots obstructed by multiple obstacle areas. Inspired by krill group behavior and based on group intelligence algorithm theory, the bionic three-dimensional path planning algorithm consists of three states: “foraging behavior”, “avoiding enemy behavior”, and “cruising behavior”. The current position information of the UAV in the working environment is used to switch between these states, and the optimal path is found after several iterations, which realizes the adaptive global and local convergence of the track planning, and improves the convergence speed and accuracy of the algorithm. The optimal flight path is obtained by smoothing using a third-order B-spline curve. Three sets of comparative simulation experiments are designed to verify the performance of this proposed algorithm. The results show that the bionic swarm intelligence algorithm based on krill swarm behavior reduces the path length by 1.1~17.5%, the operation time by 27.56~75.15%, the path energy consumption by 13.91~27.35%, and the number of iterations by 46~75% compared with the existing algorithms. The proposed algorithm can shorten the distance of the planned path more effectively, improve the real-time performance, and reduce the energy consumption. Full article
(This article belongs to the Special Issue Biomechanics and Biomimetics for Insect-Inspired MAVs)
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21 pages, 5145 KiB  
Article
Effect of Trough Incidence Angle on the Aerodynamic Characteristics of a Biomimetic Leading-Edge Protuberanced (LEP) Wing at Various Turbulence Intensities
by Shanmugam Arunvinthan, Ponnusamy Gouri, Saravanan Divysha, RK Devadharshini and Rajan Nithya Sree
Biomimetics 2024, 9(6), 354; https://doi.org/10.3390/biomimetics9060354 - 12 Jun 2024
Viewed by 950
Abstract
A series of wind tunnel tests were performed to investigate the effect of turbulent inflows on the aerodynamic characteristics of variously modified trough incident leading-edge-protuberanced (LEP) wing configurations at various turbulence intensities. A self-developed passive grid made of parallel arrays of round bars [...] Read more.
A series of wind tunnel tests were performed to investigate the effect of turbulent inflows on the aerodynamic characteristics of variously modified trough incident leading-edge-protuberanced (LEP) wing configurations at various turbulence intensities. A self-developed passive grid made of parallel arrays of round bars was placed at different locations of the wind tunnel to generate desired turbulence intensity. The aerodynamic forces acting over the trough incidence LEP wing configuration where obtained from surface pressure measurements made over the wing at different turbulence intensities using an MPS4264 Scanivalve simultaneous pressure scanner corresponding to a sampling frequency of 700 Hz. All the test models were tested at a wide range of angles of attack ranging between 0°≤α≤90° at turbulence intensities varying between 5.90% ≤ TI ≤ 10.54%. Results revealed that the time-averaged mean coefficient of lift (CL) increased with the increase in the turbulence intensity associated with smooth stall characteristics rendering the modified LEP test models advantageous. Furthermore, based on the surface pressure coefficients, the underlying dynamics behind the stall delay tendency were discussed. Additionally, attempts were made to statistically quantify the aerodynamic forces using standard deviation at both the pre-stall and the post-stall angles. Full article
(This article belongs to the Special Issue Bio-Inspired Fluid Flows and Fluid Mechanics)
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22 pages, 8603 KiB  
Article
Novel Methods for Personalized Gait Assistance: Three-Dimensional Trajectory Prediction Based on Regression and LSTM Models
by Pablo Romero-Sorozábal, Gabriel Delgado-Oleas, Annemarie F. Laudanski, Álvaro Gutiérrez and Eduardo Rocon
Biomimetics 2024, 9(6), 352; https://doi.org/10.3390/biomimetics9060352 - 12 Jun 2024
Cited by 1 | Viewed by 1234
Abstract
Enhancing human–robot interaction has been a primary focus in robotic gait assistance, with a thorough understanding of human motion being crucial for personalizing gait assistance. Traditional gait trajectory references from Clinical Gait Analysis (CGA) face limitations due to their inability to account for [...] Read more.
Enhancing human–robot interaction has been a primary focus in robotic gait assistance, with a thorough understanding of human motion being crucial for personalizing gait assistance. Traditional gait trajectory references from Clinical Gait Analysis (CGA) face limitations due to their inability to account for individual variability. Recent advancements in gait pattern generators, integrating regression models and Artificial Neural Network (ANN) techniques, have aimed at providing more personalized and dynamically adaptable solutions. This article introduces a novel approach that expands regression and ANN applications beyond mere angular estimations to include three-dimensional spatial predictions. Unlike previous methods, our approach provides comprehensive spatial trajectories for hip, knee and ankle tailored to individual kinematics, significantly enhancing end-effector rehabilitation robotic devices. Our models achieve state-of-the-art accuracy: overall RMSE of 13.40 mm and a correlation coefficient of 0.92 for the regression model, and RMSE of 12.57 mm and a correlation of 0.99 for the Long Short-Term Memory (LSTM) model. These advancements underscore the potential of these models to offer more personalized gait trajectory assistance, improving human–robot interactions. Full article
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27 pages, 9023 KiB  
Article
Application of Improved Sparrow Search Algorithm to Path Planning of Mobile Robots
by Yong Xu, Bicong Sang and Yi Zhang
Biomimetics 2024, 9(6), 351; https://doi.org/10.3390/biomimetics9060351 - 11 Jun 2024
Cited by 2 | Viewed by 1055
Abstract
Path planning is an important research direction in the field of robotics; however, with the advancement of modern science and technology, the study of efficient, stable, and safe path-planning technology has become a realistic need in the field of robotics research. This paper [...] Read more.
Path planning is an important research direction in the field of robotics; however, with the advancement of modern science and technology, the study of efficient, stable, and safe path-planning technology has become a realistic need in the field of robotics research. This paper introduces an improved sparrow search algorithm (ISSA) with a fusion strategy to further improve the ability to solve challenging tasks. First, the sparrow population is initialized using circle chaotic mapping to enhance diversity. Second, the location update formula of the northern goshawk is used in the exploration phase to replace the sparrow search algorithm’s location update formula in the security situation. This improves the discoverer model’s search breadth in the solution space and optimizes the problem-solving efficiency. Third, the algorithm adopts the Lévy flight strategy to improve the global optimization ability, so that the sparrow jumps out of the local optimum in the later stage of iteration. Finally, the adaptive T-distribution mutation strategy enhances the local exploration ability in late iterations, thus improving the sparrow search algorithm’s convergence speed. This was applied to the CEC2021 function set and compared with other standard intelligent optimization algorithms to test its performance. In addition, the ISSA was implemented in the path-planning problem of mobile robots. The comparative study shows that the proposed algorithm is superior to the SSA in terms of path length, running time, path optimality, and stability. The results show that the proposed method is more effective, robust, and feasible in mobile robot path planning. Full article
(This article belongs to the Section Development of Biomimetic Methodology)
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22 pages, 753 KiB  
Article
Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models
by Yinglong Dang, Xiaoguang Gao and Zidong Wang
Biomimetics 2024, 9(6), 350; https://doi.org/10.3390/biomimetics9060350 - 10 Jun 2024
Cited by 1 | Viewed by 941
Abstract
Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning. However, a single meta-heuristic algorithm requires specific domain knowledge and [...] Read more.
Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning. However, a single meta-heuristic algorithm requires specific domain knowledge and empirical parameter tuning and cannot guarantee good performance in all cases. Hyper-heuristics provide an alternative methodology to meta-heuristics, enabling multiple heuristic algorithms to be combined and optimized to achieve better generalization ability. In this paper, we propose a multi-population choice function hyper-heuristic to discover the causal relationships encoded in a DAG. This algorithm provides a reasonable solution for combining structural priors or possible expert knowledge with swarm intelligence. Under a linear structural equation model (SEM), we first identify the partial v-structures through partial correlation analysis as the structural priors of the next nature-inspired swarm intelligence approach. Then, through partial correlation analysis, we can limit the search space. Experimental results demonstrate the effectiveness of the proposed methods compared to the earlier state-of-the-art methods on six standard networks. Full article
(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2024)
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23 pages, 14384 KiB  
Article
Enhancing Icephobic Coatings: Exploring the Potential of Dopamine-Modified Epoxy Resin Inspired by Mussel Catechol Groups
by Mohammad Sadegh Koochaki, Gelareh Momen, Serge Lavoie and Reza Jafari
Biomimetics 2024, 9(6), 349; https://doi.org/10.3390/biomimetics9060349 - 8 Jun 2024
Viewed by 1035
Abstract
A nature-inspired approach was employed through the development of dopamine-modified epoxy coating for anti-icing applications. The strong affinity of dopamine’s catechol groups for hydrogen bonding with water molecules at the ice/coating interface was utilized to induce an aqueous quasi-liquid layer (QLL) on the [...] Read more.
A nature-inspired approach was employed through the development of dopamine-modified epoxy coating for anti-icing applications. The strong affinity of dopamine’s catechol groups for hydrogen bonding with water molecules at the ice/coating interface was utilized to induce an aqueous quasi-liquid layer (QLL) on the surface of the icephobic coatings, thereby reducing their ice adhesion strength. Epoxy resin modification was studied by attenuated total reflectance infrared spectroscopy (ATR-FTIR) and nuclear magnetic resonance spectroscopy (NMR). The surface and mechanical properties of the prepared coatings were studied by different characterization techniques. Low-temperature ATR-FTIR was employed to study the presence of QLL on the coating’s surface. Moreover, the freezing delay time and temperature of water droplets on the coatings were evaluated along with push-off and centrifuge ice adhesion strength to evaluate their icephobic properties. The surface of dopamine-modified epoxy coating presented enhanced hydrophilicity and QLL formation, addressed as the main reason for its remarkable icephobicity. The results demonstrated the potential of dopamine-modified epoxy resin as an effective binder for icephobic coatings, offering notable ice nucleation delay time (1316 s) and temperature (−19.7 °C), reduced ice adhesion strength (less than 40 kPa), and an ice adhesion reduction factor of 7.2 compared to the unmodified coating. Full article
(This article belongs to the Special Issue Bionic Engineering for Boosting Multidisciplinary Integration)
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17 pages, 481 KiB  
Review
The Applicability of Nanostructured Materials in Regenerating Soft and Bone Tissue in the Oral Cavity—A Review
by Giorgiana Corina Muresan, Sanda Boca, Ondine Lucaciu and Mihaela Hedesiu
Biomimetics 2024, 9(6), 348; https://doi.org/10.3390/biomimetics9060348 - 8 Jun 2024
Cited by 1 | Viewed by 1241
Abstract
Background and Objectives: Two of the most exciting new technologies are biotechnology and nanotechnology. The science of nanostructures, or nanotechnology, is concerned with the development, testing, and use of structures and molecules with nanoscale dimensions ranging from 1 to 100 nm. The development [...] Read more.
Background and Objectives: Two of the most exciting new technologies are biotechnology and nanotechnology. The science of nanostructures, or nanotechnology, is concerned with the development, testing, and use of structures and molecules with nanoscale dimensions ranging from 1 to 100 nm. The development of materials and tools with high specificity that interact directly at the subcellular level is what makes nanotechnology valuable in the medical sciences. At the cellular or tissue level, this might be converted into focused clinical applications with the greatest possible therapeutic benefits and the fewest possible side effects. The purpose of the present study was to review the literature and explore the applicability of the nanostructured materials in the process of the regeneration of the soft and hard tissues of the oral cavity. Materials and Methods: An electronic search of articles was conducted in several databases, such as PubMed, Embase, and Web of Science, to conduct this study, and the 183 articles that were discovered were chosen and examined, and only 22 articles met the inclusion criteria in this review. Results: The findings of this study demonstrate that using nanoparticles can improve the mechanical properties, biocompatibility, and osteoinductivity of biomaterials. Conclusions: Most recently, breakthroughs in tissue engineering and nanotechnology have led to significant advancements in the design and production of bone graft substitutes and hold tremendous promise for the treatment of bone abnormalities. The creation of intelligent nanostructured materials is essential for various applications and therapies, as it allows for the precise and long-term delivery of medication, which yields better results. Full article
(This article belongs to the Special Issue Biomaterials in Bone Regeneration: Challenges to Guarantee Appropriate Biological Features: 2nd Edition)
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19 pages, 4310 KiB  
Review
Biological Surface Layer Formation on Bioceramic Particles for Protein Adsorption
by Reo Kimura, Daichi Noda, Zizhen Liu, Wanyu Shi, Ryota Akutsu and Motohiro Tagaya
Biomimetics 2024, 9(6), 347; https://doi.org/10.3390/biomimetics9060347 - 8 Jun 2024
Cited by 1 | Viewed by 908
Abstract
In the biomedical fields of bone regenerative therapy, the immobilization of proteins on the bioceramic particles to maintain their highly ordered structures is significantly important. In this review, we comprehensively discussed the importance of the specific surface layer, which can be called “non-apatitic [...] Read more.
In the biomedical fields of bone regenerative therapy, the immobilization of proteins on the bioceramic particles to maintain their highly ordered structures is significantly important. In this review, we comprehensively discussed the importance of the specific surface layer, which can be called “non-apatitic layer”, affecting the immobilization of proteins on particles such as hydroxyapatite and amorphous silica. It was suggested that the water molecules and ions contained in the non-apatitic layer can determine and control the protein immobilization states. In amorphous silica particles, the direct interactions between proteins and silanol groups make it difficult to immobilize the proteins and maintain their highly ordered structures. Thus, the importance of the formation of a surface layer consisting of water molecules and ions (i.e., a non-apatitic layer) on the particle surfaces for immobilizing proteins and maintaining their highly ordered structures was suggested and described. In particular, chlorine-containing amorphous silica particles were also described, which can effectively form the surface layer of protein immobilization carriers. The design of the bio-interactive and bio-compatible surfaces for protein immobilization while maintaining the highly ordered structures will improve cell adhesion and tissue formation, thereby contributing to the construction of social infrastructures to support super-aged society. Full article
(This article belongs to the Special Issue Biomaterials in Bone Regeneration: Challenges to Guarantee Appropriate Biological Features: 2nd Edition)
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19 pages, 1961 KiB  
Article
Biped Robots Control in Gusty Environments with Adaptive Exploration Based DDPG
by Yilin Zhang, Huimin Sun, Honglin Sun, Yuan Huang and Kenji Hashimoto
Biomimetics 2024, 9(6), 346; https://doi.org/10.3390/biomimetics9060346 - 8 Jun 2024
Cited by 1 | Viewed by 1347
Abstract
As technology rapidly evolves, the application of bipedal robots in various environments has widely expanded. These robots, compared to their wheeled counterparts, exhibit a greater degree of freedom and a higher complexity in control, making the challenge of maintaining balance and stability under [...] Read more.
As technology rapidly evolves, the application of bipedal robots in various environments has widely expanded. These robots, compared to their wheeled counterparts, exhibit a greater degree of freedom and a higher complexity in control, making the challenge of maintaining balance and stability under changing wind speeds particularly intricate. Overcoming this challenge is critical as it enables bipedal robots to sustain more stable gaits during outdoor tasks, thereby increasing safety and enhancing operational efficiency in outdoor settings. To transcend the constraints of existing methodologies, this research introduces an adaptive bio-inspired exploration framework for bipedal robots facing wind disturbances, which is based on the Deep Deterministic Policy Gradient (DDPG) approach. This framework allows the robots to perceive their bodily states through wind force inputs and adaptively modify their exploration coefficients. Additionally, to address the convergence challenges posed by sparse rewards, this study incorporates Hindsight Experience Replay (HER) and a reward-reshaping strategy to provide safer and more effective training guidance for the agents. Simulation outcomes reveal that robots utilizing this advanced method can more swiftly explore behaviors that contribute to stability in complex conditions, and demonstrate improvements in training speed and walking distance over traditional DDPG algorithms. Full article
(This article belongs to the Special Issue Design and Control of a Bio-Inspired Robot: 2nd Edition)
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20 pages, 7586 KiB  
Article
Kinematic Modeling and Experimental Study of a Rope-Driven Bionic Fish
by Bo Zhang, Yongchen Huang, Zhuo Wang and Hongwen Ma
Biomimetics 2024, 9(6), 345; https://doi.org/10.3390/biomimetics9060345 - 7 Jun 2024
Viewed by 1043
Abstract
This paper presents a biomimetic fish robot featuring a flexible spine driven by cables, which integrates the cable-driven mechanism with a flexible spine. The drive system separates the body and tail fin drives for control, offering enhanced flexibility and ease in achieving phase [...] Read more.
This paper presents a biomimetic fish robot featuring a flexible spine driven by cables, which integrates the cable-driven mechanism with a flexible spine. The drive system separates the body and tail fin drives for control, offering enhanced flexibility and ease in achieving phase difference control between the body and tail fin movements compared to the conventional servo motor cascaded structure. A prototype of the biomimetic fish robot was developed, accompanied by the establishment of a kinematic model. Based on this model, a control method for the biomimetic fish is proposed. Additionally, we introduce the concept of prestress to establish a numerical model for the biomimetic fish. Using multi-physical field simulation software, we simulate the two-dimensional autonomous swimming process of the biomimetic fish under different flapping frequencies and solve for its swimming characteristics as well as hydrodynamic properties. Both the simulation and experimental results validate the accuracy of our kinematic model. Full article
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