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Biomimetics
Volume 9
Issue 12
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Biomimetics, Volume 9, Issue 12 (December 2024) – 67 articles

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19 pages, 3359 KiB  
Article
MS-CLSTM: Myoelectric Manipulator Gesture Recognition Based on Multi-Scale Feature Fusion CNN-LSTM Network
by Ziyi Wang, Wenjing Huang, Zikang Qi and Shuolei Yin
Biomimetics 2024, 9(12), 784; https://doi.org/10.3390/biomimetics9120784 - 23 Dec 2024
Viewed by 763
Abstract
Surface electromyography (sEMG) signals reflect the local electrical activity of muscle fibers and the synergistic action of the overall muscle group, making them useful for gesture control of myoelectric manipulators. In recent years, deep learning methods have increasingly been applied to sEMG gesture [...] Read more.
Surface electromyography (sEMG) signals reflect the local electrical activity of muscle fibers and the synergistic action of the overall muscle group, making them useful for gesture control of myoelectric manipulators. In recent years, deep learning methods have increasingly been applied to sEMG gesture recognition due to their powerful automatic feature extraction capabilities. sEMG signals contain rich local details and global patterns, but single-scale convolutional networks are limited in their ability to capture both comprehensively, which restricts model performance. This paper proposes a deep learning model based on multi-scale feature fusion—MS-CLSTM (MS Block-ResCBAM-Bi-LSTM). The MS Block extracts local details, global patterns, and inter-channel correlations in sEMG signals using convolutional kernels of different scales. The ResCBAM, which integrates CBAM and Simple-ResNet, enhances attention to key gesture information while alleviating overfitting issues common in small-sample datasets. Experimental results demonstrate that the MS-CLSTM model achieves recognition accuracies of 86.66% and 83.27% on the Ninapro DB2 and DB4 datasets, respectively, and the accuracy can reach 89% in real-time myoelectric manipulator gesture prediction experiments. The proposed model exhibits superior performance in sEMG gesture recognition tasks, offering an effective solution for applications in prosthetic hand control, robotic control, and other human–computer interaction fields. Full article
(This article belongs to the Special Issue Human-Inspired Grasp Control in Robotics)
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11 pages, 2671 KiB  
Article
Edge Artificial Intelligence Device in Real-Time Endoscopy for Classification of Gastric Neoplasms: Development and Validation Study
by Eun Jeong Gong, Chang Seok Bang and Jae Jun Lee
Biomimetics 2024, 9(12), 783; https://doi.org/10.3390/biomimetics9120783 - 22 Dec 2024
Viewed by 588
Abstract
Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. However, this required significant computational resources. The incorporation of AI into medical devices has evolved from centralized models to decentralized edge computing devices. In this study, [...] Read more.
Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. However, this required significant computational resources. The incorporation of AI into medical devices has evolved from centralized models to decentralized edge computing devices. In this study, a deep learning endoscopic image classification model was created to automatically categorize all phases of gastric carcinogenesis using an edge computing device. Design: A total of 15,910 endoscopic images were collected retrospectively and randomly assigned to train, validation, and internal-test datasets in an 8:1:1 ratio. The major outcomes were as follows: 1. lesion classification accuracy in six categories: normal/atrophy/intestinal metaplasia/dysplasia/early/advanced gastric cancer; and 2. the prospective evaluation of classification accuracy in real-world procedures. Results: The internal-test lesion-classification accuracy was 93.8% (95% confidence interval: 93.4–94.2%); precision was 88.6%, recall was 88.3%, and F1 score was 88.4%. For the prospective performance test, the established model attained an accuracy of 93.3% (91.5–95.1%). The established model’s lesion classification inference speed was 2–3 ms on GPU and 5–6 ms on CPU. The expert endoscopists reported no delays in lesion classification or any interference from the deep learning model throughout their exams. Conclusions: We established a deep learning endoscopic image classification model to automatically classify all stages of gastric carcinogenesis using an edge computing device. Full article
(This article belongs to the Special Issue Artificial Intelligence (AI) in Biomedical Engineering)
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13 pages, 5886 KiB  
Article
The Influence of Physiological Blood Clot on Osteoblastic Cell Response to a Chitosan-Based 3D Scaffold—A Pilot Investigation
by Natacha Malu Miranda da Costa, Hilary Ignes Palma Caetano, Larissa Miranda Aguiar, Ludovica Parisi, Benedetta Ghezzi, Lisa Elviri, Leonardo Raphael Zuardi, Paulo Tambasco de Oliveira and Daniela Bazan Palioto
Biomimetics 2024, 9(12), 782; https://doi.org/10.3390/biomimetics9120782 - 21 Dec 2024
Viewed by 815
Abstract
Background: The use of ex vivo assays associated with biomaterials may allow the short-term visualization of a specific cell type response inserted in a local microenvironment. Blood is the first component to come into contact with biomaterials, providing blood clot formation, being substantial [...] Read more.
Background: The use of ex vivo assays associated with biomaterials may allow the short-term visualization of a specific cell type response inserted in a local microenvironment. Blood is the first component to come into contact with biomaterials, providing blood clot formation, being substantial in new tissue formation. Thus, this research investigated the physiological blood clot (PhC) patterns formed in 3D scaffolds (SCAs), based on chitosan and 20% beta-tricalcium phosphate and its effect on osteogenesis. Initially, SCA were inserted for 16 h in rats calvaria defects, and, after that, osteoblasts cells (OSB; UMR-106 lineage) were seeded on the substrate formed. The groups tested were SCA + OSB and SCA + PhC + OSB. Cell viability was checked by MTT and mineralized matrix formation in OSB using alizarin red (ARS). The alkaline phosphatase (ALP) and bone sialoprotein (BSP) expression in OSB was investigated by indirect immunofluorescence (IF). The OSB and PhC morphology was verified by scanning electron microscopy (SEM). Results: The SCA + PhC + OSB group showed greater cell viability (p = 0.0169). After 10 days, there was more mineralized matrix deposition (p = 0.0365) and high ALP immunostaining (p = 0.0021) in the SCA + OSB group. In contrast, BSP was more expressed in OSB seeded on SCA with PhC (p = 0.0033). Conclusions: These findings show the feasibility of using PhC in ex vivo assays. Additionally, its inclusion in the experiments resulted in a change in OSB behavior when compared to in vitro assays. This “closer to nature” environment can completely change the scenario of a study. Full article
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18 pages, 2541 KiB  
Article
Insight into the Use of Brewers’ Spent Grain as a Low-Carbon Aggregate in Building Materials
by Badreddine El Haddaji, Mohammed-Hichem Benzaama, Marc Quiertant and Yassine El Mendili
Biomimetics 2024, 9(12), 781; https://doi.org/10.3390/biomimetics9120781 - 21 Dec 2024
Viewed by 556
Abstract
This study investigates the use of Brewers’ Spent Grains (BSGs) as a sustainable biocomposite building materials, using cornstarch as a biopolymer binder. BSG aggregates are compared with hemp shives, a conventional aggregate known for its thermal properties. Starch is employed as a natural [...] Read more.
This study investigates the use of Brewers’ Spent Grains (BSGs) as a sustainable biocomposite building materials, using cornstarch as a biopolymer binder. BSG aggregates are compared with hemp shives, a conventional aggregate known for its thermal properties. Starch is employed as a natural binder in three different formulations to further reduce the carbon footprint of the building material. Considering aggregates, the first formulation contains only BSGs, the second consists of half BSGs and half hemp shives, and the third uses only hemp shives. In addition, morphological analysis using Scanning Electron Microscopy (SEM) is conducted to examine the microstructure and porosity of the raw BSG and hemp shives. Hygrothermal properties are measured using Heat Flow Meter (HFM) and Dynamic Vapor Sorption (DVS) techniques, while mechanical properties are also assessed. Results indicate that the thermal conductivity of the BSG formulation (0.131 W/(m·K)) is double that of the hemp shives formulation (0.067 W/(m·K)), whereas the mixed BSG/hemp shives formulation exhibits a thermal conductivity of 0.106 W/(m·K). However, DVS measurements reveal better hygrothermal properties for the BSG formulation compared to the hemp shives formulation. Lastly, mechanical properties are found to be nearly equivalent across the three formulations. These findings suggest that BSG waste has potential as a viable material for use in construction. Further work on formulation optimization and durability is necessary to fully realize the potential of this waste in promoting a circular economy within the building materials industry. Full article
(This article belongs to the Special Issue Biomimetic Adaptive Buildings)
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24 pages, 7785 KiB  
Article
Adaptive Disturbance Rejection Motion Control of Direct-Drive Systems with Adjustable Damping Ratio Based on Zeta-Backstepping
by Zhongjin Zhang, Zhitai Liu, Weiyang Lin and Wei Cheng
Biomimetics 2024, 9(12), 780; https://doi.org/10.3390/biomimetics9120780 - 21 Dec 2024
Viewed by 505
Abstract
Direct-drive servo systems are extensively applied in biomimetic robotics and other bionic applications, but their performance is susceptible to uncertainties and disturbances. This paper proposes an adaptive disturbance rejection Zeta-backstepping control scheme with adjustable damping ratios to enhance system robustness and precision. An [...] Read more.
Direct-drive servo systems are extensively applied in biomimetic robotics and other bionic applications, but their performance is susceptible to uncertainties and disturbances. This paper proposes an adaptive disturbance rejection Zeta-backstepping control scheme with adjustable damping ratios to enhance system robustness and precision. An iron-core permanent magnet linear synchronous motor (PMLSM) was employed as the experimental platform for the development of a dynamic model that incorporates compensation for friction and cogging forces. To address model parameter uncertainties, an indirect parameter adaptation strategy based on a recursive least squares algorithm was introduced. It updates parameters based on the system state instead of output error, ensuring robust parameter convergence. An integral sliding mode observer (ISMO) was constructed to estimate and compensate for residual uncertainties, achieving finite-time state estimation. The proposed Zeta-backstepping controller enables adjustable damping ratios through parameterized control laws, offering flexibility in achieving desired dynamic performance. System stability and bounded tracking performance were validated via a second-order Lyapunov function analysis. Experimental results on a real PMLSM platform demonstrated that, while achieving adjustable damping ratio dynamic characteristics, there is a significant improvement in tracking accuracy and disturbance suppression. This underscores the scheme’s potential for advancing precision control in biomimetic robotics and other direct-drive system applications. Full article
(This article belongs to the Special Issue Recent Advances in Robotics and Biomimetics)
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20 pages, 3339 KiB  
Article
Trajectory Tracking Control for Robotic Manipulator Based on Soft Actor–Critic and Generative Adversarial Imitation Learning
by Jintao Hu, Fujie Wang, Xing Li, Yi Qin, Fang Guo and Ming Jiang
Biomimetics 2024, 9(12), 779; https://doi.org/10.3390/biomimetics9120779 - 21 Dec 2024
Viewed by 536
Abstract
In this paper, a deep reinforcement learning (DRL) approach based on generative adversarial imitation learning (GAIL) and long short-term memory (LSTM) is proposed to resolve tracking control problems for robotic manipulators with saturation constraints and random disturbances, without learning the dynamic and kinematic [...] Read more.
In this paper, a deep reinforcement learning (DRL) approach based on generative adversarial imitation learning (GAIL) and long short-term memory (LSTM) is proposed to resolve tracking control problems for robotic manipulators with saturation constraints and random disturbances, without learning the dynamic and kinematic model of the manipulator. Specifically, it limits the torque and joint angle to a certain range. Firstly, in order to cope with the instability problem during training and obtain a stability policy, soft actor–critic (SAC) and LSTM are combined. The changing trends of joint position over time are more comprehensively captured and understood by employing an LSTM architecture designed for robotic manipulator systems, thereby reducing instability during the training of robotic manipulators for tracking control tasks. Secondly, the obtained policy by SAC-LSTM is used as expert data for GAIL to learn a better control policy. This SAC-LSTM-GAIL (SL-GAIL) algorithm does not need to spend time exploring unknown environments and directly learns the control strategy from stable expert data. Finally, it is demonstrated by the simulation results that the end effector of the robot tracking task is effectively accomplished by the proposed SL-GAIL algorithm, and more superior stability is exhibited in a test environment with interference compared with other algorithms. Full article
(This article belongs to the Special Issue Bio-Inspired Robotics and Applications)
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16 pages, 2640 KiB  
Article
Biomimetic Linkage Mechanism Robust Control for Variable Stator Vanes in Aero-Engine
by Qinqin Sun, Zhangyang Lu, Xingyu Gui and Ye-Hwa Chen
Biomimetics 2024, 9(12), 778; https://doi.org/10.3390/biomimetics9120778 - 21 Dec 2024
Viewed by 418
Abstract
This work addresses the position tracking control design of the stator vane driven by electro-hydrostatic actuators facing uncertain aerodynamic disturbances. Rapidly changing aerodynamic conditions impose complex disturbance torques on the guide vanes. Consequently, a challenging task is to enhance control precision in complex [...] Read more.
This work addresses the position tracking control design of the stator vane driven by electro-hydrostatic actuators facing uncertain aerodynamic disturbances. Rapidly changing aerodynamic conditions impose complex disturbance torques on the guide vanes. Consequently, a challenging task is to enhance control precision in complex uncertain environments. Inspired by the principles of mammalian muscle movement, a novel robust control strategy based on the backstepping method has been proposed. Using backstepping, virtual rotational speed and virtual pressure difference force are designed, which decompose the high-order position closed-loop control problem into three lower-order parts, eliminating the need for matching conditions. Subsequently, robust controllers were designed, and stability proofs and performance analyses of the controllers were provided. This control strategy was tested through numerical hydraulic simulation. The results show that compared to other control methods, this approach significantly improves tracking accuracy and robustness. Therefore, it is believed that this method has the potential to become a new generation solution for such problems. Full article
(This article belongs to the Special Issue Bioinspired Flapping Wing Aerodynamics: Progress and Challenges)
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17 pages, 4740 KiB  
Article
Kinematics and Flow Field Analysis of Allomyrina dichotoma Flight
by Huan Shen, Kai Cao, Chao Liu, Zhiyuan Mao, Qian Li, Qingfei Han, Yi Sun, Zhikang Yang, Youzhi Xu, Shutao Wu, Jiajun Xu and Aihong Ji
Biomimetics 2024, 9(12), 777; https://doi.org/10.3390/biomimetics9120777 - 20 Dec 2024
Viewed by 388
Abstract
In recent years, bioinspired insect flight has become a prominent research area, with a particular focus on beetle-inspired aerial vehicles. Studying the unique flight mechanisms and structural characteristics of beetles has significant implications for the optimization of biomimetic flying devices. Among beetles, Allomyrina [...] Read more.
In recent years, bioinspired insect flight has become a prominent research area, with a particular focus on beetle-inspired aerial vehicles. Studying the unique flight mechanisms and structural characteristics of beetles has significant implications for the optimization of biomimetic flying devices. Among beetles, Allomyrina dichotoma (rhinoceros beetle) exhibits a distinct wing deployment–flight–retraction sequence, whereby the interaction between the hindwings and protective elytra contributes to lift generation and maintenance. This study investigates A. dichotoma’s wing deployment, flight, and retraction behaviors through motion analysis, uncovering the critical role of the elytra in wing folding. We capture the kinematic parameters throughout the entire flight process and develop an accurate kinematic model of A. dichotoma flight. Using smoke visualization, we analyze the flow field generated during flight, revealing the formation of enhanced leading-edge vortices and attached vortices during both upstroke and downstroke phases. These findings uncover the high-lift mechanism underlying A. dichotoma’s flight dynamics, offering valuable insights for optimizing beetle-inspired micro aerial vehicles. Full article
(This article belongs to the Special Issue Bio-Inspired Fluid Flows and Fluid Mechanics)
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17 pages, 11720 KiB  
Article
A Worm-like Soft Robot Based on Adhesion-Controlled Electrohydraulic Actuators
by Yangzhuo Wu, Zhe Sun, Yu Xiang and Jieliang Zhao
Biomimetics 2024, 9(12), 776; https://doi.org/10.3390/biomimetics9120776 - 20 Dec 2024
Viewed by 647
Abstract
Worms are organisms characterized by simple structures, low energy consumption, and stable movement. Inspired by these characteristics, worm-like soft robots demonstrate exceptional adaptability to unstructured environments, attracting considerable interest in the field of biomimetic engineering. The primary challenge currently involves improving the motion [...] Read more.
Worms are organisms characterized by simple structures, low energy consumption, and stable movement. Inspired by these characteristics, worm-like soft robots demonstrate exceptional adaptability to unstructured environments, attracting considerable interest in the field of biomimetic engineering. The primary challenge currently involves improving the motion performance of worm-like robots from the perspectives of actuation and anchoring. In this study, a single segment worm-like soft robot driven by electrohydraulic actuators is proposed. The robot consists of a soft actuation module and two symmetrical anchoring modules. The actuation modules enable multi-degree-of-freedom motion of the robot using symmetric dual-electrode electrohydraulic actuators, while the anchoring modules provide active friction control through bistable electrohydraulic actuators. A hierarchical microstructure design is used for the biomimetic adhesive surface, enabling rapid, reversible, and stable attachment to and detachment from different surfaces, thereby improving the robot’s surface anchoring performance. Experimental results show that the designed robot can perform peristaltic and bending motions similar to a worm. It achieves rapid bidirectional propulsion on both dry and wet surfaces, with a maximum speed of 10.36 mm/s (over 6 velocity/length ratio (min−1)). Full article
(This article belongs to the Special Issue Sustainable Soft Robotics: Innovations and Advances in Soft Manipulators and Grippers)
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24 pages, 8881 KiB  
Article
Research on Multimodal Control Method for Prosthetic Hands Based on Visuo-Tactile and Arm Motion Measurement
by Jianwei Cui and Bingyan Yan
Biomimetics 2024, 9(12), 775; https://doi.org/10.3390/biomimetics9120775 - 19 Dec 2024
Viewed by 592
Abstract
The realization of hand function reengineering using a manipulator is a research hotspot in the field of robotics. In this paper, we propose a multimodal perception and control method for a robotic hand to assist the disabled. The movement of the human hand [...] Read more.
The realization of hand function reengineering using a manipulator is a research hotspot in the field of robotics. In this paper, we propose a multimodal perception and control method for a robotic hand to assist the disabled. The movement of the human hand can be divided into two parts: the coordination of the posture of the fingers, and the coordination of the timing of grasping and releasing objects. Therefore, we first used a pinhole camera to construct a visual device suitable for finger mounting, and preclassified the shape of the object based on YOLOv8; then, a filtering process using multi-frame synthesized point cloud data from miniature 2D Lidar, and DBSCAN algorithm clustering objects and the DTW algorithm, was proposed to further identify the cross-sectional shape and size of the grasped part of the object and realize control of the robot’s grasping gesture; finally, a multimodal perception and control method for prosthetic hands was proposed. To control the grasping attitude, a fusion algorithm based on information of upper limb motion state, hand position, and lesser toe haptics was proposed to realize control of the robotic grasping process with a human in the ring. The device designed in this paper does not contact the human skin, does not produce discomfort, and the completion rate of the grasping process experiment reached 91.63%, which indicates that the proposed control method has feasibility and applicability. Full article
(This article belongs to the Special Issue Bionic Technology—Robotic Exoskeletons and Prostheses: 2nd Edition)
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18 pages, 3461 KiB  
Article
Dynamic Structure-Aware Modulation Network for Underwater Image Super-Resolution
by Li Wang, Ke Li, Chengang Dong, Keyong Shen and Yang Mu
Biomimetics 2024, 9(12), 774; https://doi.org/10.3390/biomimetics9120774 - 19 Dec 2024
Viewed by 546
Abstract
Image super-resolution (SR) is a formidable challenge due to the intricacies of the underwater environment such as light absorption, scattering, and color distortion. Plenty of deep learning methods have provided a substantial performance boost for SR. Nevertheless, these methods are not only computationally [...] Read more.
Image super-resolution (SR) is a formidable challenge due to the intricacies of the underwater environment such as light absorption, scattering, and color distortion. Plenty of deep learning methods have provided a substantial performance boost for SR. Nevertheless, these methods are not only computationally expensive but also often lack flexibility in adapting to severely degraded image statistics. To counteract these issues, we propose a dynamic structure-aware modulation network (DSMN) for efficient and accurate underwater SR. A Mixed Transformer incorporated a structure-aware Transformer block and multi-head Transformer block, which could comprehensively utilize local structural attributes and global features to enhance the details of underwater image restoration. Then, we devised a dynamic information modulation module (DIMM), which adaptively modulated the output of the Mixed Transformer with appropriate weights based on input statistics to highlight important information. Further, a hybrid-attention fusion module (HAFM) adopted spatial and channel interaction to aggregate more delicate features, facilitating high-quality underwater image reconstruction. Extensive experiments on benchmark datasets revealed that our proposed DSMN surpasses the most renowned SR methods regarding quantitative and qualitative metrics, along with less computational effort. Full article
(This article belongs to the Special Issue Exploration of Computer Vision and Pattern Recognition)
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21 pages, 12168 KiB  
Article
An Octopus-Inspired Soft Pneumatic Robotic Arm
by Emmanouil Papadakis, Dimitris P. Tsakiris and Michael Sfakiotakis
Biomimetics 2024, 9(12), 773; https://doi.org/10.3390/biomimetics9120773 - 19 Dec 2024
Viewed by 726
Abstract
This paper addresses the design, development, control, and experimental evaluation of a soft robot arm whose actuation is inspired by the muscular structure of the octopus arm, one of the most agile biological manipulators. The robot arm is made of soft silicone and [...] Read more.
This paper addresses the design, development, control, and experimental evaluation of a soft robot arm whose actuation is inspired by the muscular structure of the octopus arm, one of the most agile biological manipulators. The robot arm is made of soft silicone and thus possesses enhanced compliance, which is beneficial in a variety of applications where the arm may come into contact with delicate features of its environment. The arm is composed of three elongated segments arranged in series, each one of which contains several pneumatically actuated chambers embedded in its silicone body, which may induce various types of deformations of the segment. By combining the segment deformations, and by imitating the antagonistic muscle group functionality of the octopus, the robot arm can bend in various directions, increase or decrease its length, as well as twist around its central axis. This is one of the few octopus-inspired soft robotic arms where twisting is replicated in its motion characteristics, thus greatly expanding the arm’s potential applications. We present the design process and the development steps of the soft arm, where the molding of two-part silicone of low hardness in 3d-printed molds is employed. In addition, we present the control methodology and the experimental evaluation of both a standalone segment and the entire three-segment arm. This experimental evaluation involves model-free closed-loop control schemes, exploiting visual feedback from a pair of external cameras in order to reconstruct in real time the shape of the soft arm and the pose of its tip. Full article
(This article belongs to the Special Issue Bio-Inspired Soft Robotics: Design, Fabrication and Applications)
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16 pages, 4067 KiB  
Article
Neural Network-Based Shape Analysis and Control of Continuum Objects
by Yuqiao Dai, Shilin Zhang, Wei Cheng and Peng Li
Biomimetics 2024, 9(12), 772; https://doi.org/10.3390/biomimetics9120772 - 18 Dec 2024
Viewed by 444
Abstract
Soft robots are gaining increasing attention in current robotics research due to their continuum structure. However, accurately recognizing and reproducing the shape of such continuum robots remains a challenge. In this paper, we propose a novel approach that combines contour extraction with camera [...] Read more.
Soft robots are gaining increasing attention in current robotics research due to their continuum structure. However, accurately recognizing and reproducing the shape of such continuum robots remains a challenge. In this paper, we propose a novel approach that combines contour extraction with camera reconstruction to obtain shape features. Neural networks are employed to model the relationship between motor inputs and the resulting shape output. A simulation environment is established to verify the shape estimation and shape control of the flexible continuum. The outcomes demonstrate that this approach effectively predicts and reproduces the shape of flexible continuum robots, providing a promising solution for continuum shape control. Full article
(This article belongs to the Special Issue Bio-Inspired Soft Robotics: Design, Fabrication and Applications)
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16 pages, 1907 KiB  
Review
Dehydrated Human Amnion–Chorion Membrane as a Bioactive Scaffold for Dental Pulp Tissue Regeneration
by Sahng G. Kim
Biomimetics 2024, 9(12), 771; https://doi.org/10.3390/biomimetics9120771 - 18 Dec 2024
Viewed by 680
Abstract
The dehydrated human amnion–chorion membranes (dHACMs) derived from the human placenta have emerged as a promising biomaterial for dental pulp regeneration owing to their unique biological and structural properties. The purpose of this review is to explore the potentials of dHACMs in dental [...] Read more.
The dehydrated human amnion–chorion membranes (dHACMs) derived from the human placenta have emerged as a promising biomaterial for dental pulp regeneration owing to their unique biological and structural properties. The purpose of this review is to explore the potentials of dHACMs in dental pulp tissue engineering, focusing on their ability to promote cellular proliferation, differentiation, angiogenesis, and neurogenesis. dHACMs are rich in extracellular matrix proteins and growth factors such as TGF-β1, FGF2, and VEGF. They also exhibit significant anti-inflammatory and antimicrobial properties, creating an optimal environment for dental pulp regeneration. The applications of dHACMs in regenerative endodontic procedures are discussed, highlighting their ability to support the formation of dentin and well-vascularized pulp-like tissue. This review demonstrates that dHACMs hold significant potential for enhancing the success of pulp regeneration and offer a biologically based approach to preserve tooth vitality and improve tooth survival. Future research is expected to focus on conducting long-term clinical studies to establish their efficacy and safety. Full article
(This article belongs to the Special Issue Dentistry and Craniofacial District: The Role of Biomimetics—Second Edition)
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11 pages, 2125 KiB  
Review
A Comprehensive Review of Treatment Plans for Marginal Enamel Fractures in Anterior Teeth
by Riccardo Favero, Alessandro Scattolin, Martina Barone, Giampaolo Drago, Rim Bourgi, Vincenzo Tosco, Riccardo Monterubbianesi and Angelo Putignano
Biomimetics 2024, 9(12), 770; https://doi.org/10.3390/biomimetics9120770 - 18 Dec 2024
Viewed by 499
Abstract
Marginal enamel fractures (MEF) are a common clinical concern in dentistry, particularly in anterior teeth. These fractures occur at the enamel margins and their etiopathogenesis involves a complex interplay of mechanical, chemical, and biological factors. The ongoing research focuses on an overview of [...] Read more.
Marginal enamel fractures (MEF) are a common clinical concern in dentistry, particularly in anterior teeth. These fractures occur at the enamel margins and their etiopathogenesis involves a complex interplay of mechanical, chemical, and biological factors. The ongoing research focuses on an overview of MEF to improve the knowledge about this condition. Understanding the multifaceted nature of MEF is crucial for devising effective preventive and therapeutic strategies in contemporary restorative dentistry. Indeed, mechanical stresses, such as occlusal forces and parafunctional habits are primary contributors for MEF. Additionally, it can happen at the enamel-restoration interface due to expansion and contraction of restorative materials. Chemical degradation, including acid erosion and the breakdown of adhesive bonds, further exacerbates the vulnerability of enamel. Biological factors, such as enamel composition and the presence of micro-cracks also play a role in the development of MEF. Clinical management of MEF involves subtractive or additive techniques, repairing or replacing the compromised tooth structure using techniques to ensure the integration with the natural enamel. Full article
(This article belongs to the Special Issue Biomimetic Bonded Restorations for Dental Applications)
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24 pages, 6055 KiB  
Article
Analyzing the Impact of Responding to Joint Attention on the User Perception of the Robot in Human-Robot Interaction
by Jesús García-Martínez, Juan José Gamboa-Montero, José Carlos Castillo and Álvaro Castro-González
Biomimetics 2024, 9(12), 769; https://doi.org/10.3390/biomimetics9120769 - 18 Dec 2024
Viewed by 724
Abstract
The concept of joint attention holds significant importance in human interaction and is pivotal in establishing rapport, understanding, and effective communication. Within social robotics, enhancing user perception of the robot and promoting a sense of natural interaction with robots becomes a central element. [...] Read more.
The concept of joint attention holds significant importance in human interaction and is pivotal in establishing rapport, understanding, and effective communication. Within social robotics, enhancing user perception of the robot and promoting a sense of natural interaction with robots becomes a central element. In this sense, emulating human-centric qualities in social robots, such as joint attention, defined as the ability of two or more individuals to focus on a common event simultaneously, can increase their acceptability. This study analyses the impact on user perception of a responsive joint attention system integrated into a social robot within an interactive scenario. The experimental setup involves playing against the robot in the “Odds and Evens” game under two conditions: whether the joint attention system is active or inactive. Additionally, auditory and visual distractors are employed to simulate real-world distractions, aiming to test the system’s ability to capture and follow user attention effectively. To assess the influence of the joint attention system, participants completed the Robotic Social Attributes Scale (RoSAS) after each interaction. The results showed a significant improvement in user perception of the robot’s competence and warmth when the joint attention system was active. Full article
(This article belongs to the Special Issue Intelligent Human–Robot Interaction: 3rd Edition)
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13 pages, 5286 KiB  
Article
Eye-Inspired Single-Pixel Imaging with Lateral Inhibition and Variable Resolution for Special Unmanned Vehicle Applications in Tunnel Inspection
by Bin Han, Quanchao Zhao, Moudan Shi, Kexin Wang, Yunan Shen, Jie Cao and Qun Hao
Biomimetics 2024, 9(12), 768; https://doi.org/10.3390/biomimetics9120768 - 18 Dec 2024
Viewed by 598
Abstract
This study presents a cutting-edge imaging technique for special unmanned vehicles (UAVs) designed to enhance tunnel inspection capabilities. This technique integrates ghost imaging inspired by the human visual system with lateral inhibition and variable resolution to improve environmental perception in challenging conditions, such [...] Read more.
This study presents a cutting-edge imaging technique for special unmanned vehicles (UAVs) designed to enhance tunnel inspection capabilities. This technique integrates ghost imaging inspired by the human visual system with lateral inhibition and variable resolution to improve environmental perception in challenging conditions, such as poor lighting and dust. By emulating the high-resolution foveal vision of the human eye, this method significantly enhances the efficiency and quality of image reconstruction for fine targets within the region of interest (ROI). This method utilizes non-uniform speckle patterns coupled with lateral inhibition to augment optical nonlinearity, leading to superior image quality and contrast. Lateral inhibition effectively suppresses background noise, thereby improving the imaging efficiency and substantially increasing the signal-to-noise ratio (SNR) in noisy environments. Extensive indoor experiments and field tests in actual tunnel settings validated the performance of this method. Variable-resolution sampling reduced the number of samples required by 50%, enhancing the reconstruction efficiency without compromising image quality. Field tests demonstrated the system’s ability to successfully image fine targets, such as cables, under dim and dusty conditions, achieving SNRs from 13.5 dB at 10% sampling to 27.7 dB at full sampling. The results underscore the potential of this technique for enhancing environmental perception in special unmanned vehicles, especially in GPS-denied environments with poor lighting and dust. Full article
(This article belongs to the Special Issue Advanced Biologically Inspired Vision and Its Application)
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16 pages, 4966 KiB  
Article
Polyetheretherketone Double Functionalization with Bioactive Peptides Improves Human Osteoblast Response
by Leonardo Cassari, Cristian Balducci, Grazia M. L. Messina, Giovanna Iucci, Chiara Battocchio, Federica Bertelà, Giovanni Lucchetta, Trevor Coward, Lucy Di Silvio, Giovanni Marletta, Annj Zamuner, Paola Brun and Monica Dettin
Biomimetics 2024, 9(12), 767; https://doi.org/10.3390/biomimetics9120767 - 17 Dec 2024
Viewed by 622
Abstract
In recent years, the demand for orthopedic implants has surged due to increased life expectancy, necessitating the need for materials that better mimic the biomechanical properties of human bone. Traditional metal implants, despite their mechanical superiority and biocompatibility, often face challenges such as [...] Read more.
In recent years, the demand for orthopedic implants has surged due to increased life expectancy, necessitating the need for materials that better mimic the biomechanical properties of human bone. Traditional metal implants, despite their mechanical superiority and biocompatibility, often face challenges such as mismatched elastic modulus and ion release, leading to complications and implant failures. Polyetheretherketone (PEEK), a semi-crystalline polymer with an aromatic backbone, presents a promising alternative due to its adjustable elastic modulus and compatibility with bone tissue. This study explores the functionalization of sandblasted 3D-printed PEEK disks with the bioactive peptides Aoa-GBMP1α and Aoa-EAK to enhance human osteoblast response. Aoa-GBMP1α reproduces 48–69 trait of Bone Morphogenetic Protein 2 (BMP-2), whereas Aoa-EAK is a self-assembling peptide mimicking extracellular matrix (ECM) fibrous structure. Superficial characterization included X-ray photoelectron spectroscopy (XPS), white light interferometer analysis, static water contact angle (S-WCA), and force spectroscopy (AFM-FS). Biological assays demonstrated a significant increase in human osteoblast (HOB) proliferation, calcium deposition, and expression of osteogenic genes (RUNX2, SPP1, and VTN) on functionalized PEEK compared to non-functionalized controls. The findings suggest that dual peptide-functionalized PEEK holds significant potential for advancing orthopedic implant technology. Full article
(This article belongs to the Special Issue Biomimetic Strategies to Enhance Bone Tissue Healing, Remodeling and Regeneration)
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22 pages, 45649 KiB  
Article
A Whole-Body Coordinated Motion Control Method for Highly Redundant Degrees of Freedom Mobile Humanoid Robots
by Hao Niu, Xin Zhao, Hongzhe Jin and Xiuli Zhang
Biomimetics 2024, 9(12), 766; https://doi.org/10.3390/biomimetics9120766 - 16 Dec 2024
Viewed by 683
Abstract
Humanoid robots are becoming a global research focus. Due to the limitations of bipedal walking technology, mobile humanoid robots equipped with a wheeled chassis and dual arms have emerged as the most suitable configuration for performing complex tasks in factory or home environments. [...] Read more.
Humanoid robots are becoming a global research focus. Due to the limitations of bipedal walking technology, mobile humanoid robots equipped with a wheeled chassis and dual arms have emerged as the most suitable configuration for performing complex tasks in factory or home environments. To address the high redundancy issue arising from the wheeled chassis and dual-arm design of mobile humanoid robots, this study proposes a whole-body coordinated motion control algorithm based on arm potential energy optimization. By constructing a gravity potential energy model for the arms and a virtual torsional spring elastic potential energy model with the shoulder-wrist line as the rotation axis, we establish an optimization index function for the arms. A neural network with variable stiffness is introduced to fit the virtual torsional spring, representing the stiffness variation trend of the human arm. Additionally, a posture mapping method is employed to map the human arm potential energy model to the robot, enabling realistic humanoid movements. Combining task-space and joint-space planning algorithms, we designed experiments for single-arm manipulation, independent object retrieval, and dual-arm carrying in a simulation of a 23-degree-of-freedom mobile humanoid robot. The results validate the effectiveness of this approach, demonstrating smooth motion, the ability to maintain a low potential energy state, and conformity to the operational characteristics of the human arm. Full article
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44 pages, 17816 KiB  
Article
An Improved Spider Wasp Optimizer for UAV Three-Dimensional Path Planning
by Haijun Liang, Wenhai Hu, Lifei Wang, Ke Gong, Yuxi Qian and Longchao Li
Biomimetics 2024, 9(12), 765; https://doi.org/10.3390/biomimetics9120765 - 16 Dec 2024
Viewed by 578
Abstract
This paper proposes an Improved Spider Wasp Optimizer (ISWO) to address inaccuracies in calculating the population (N) during iterations of the SWO algorithm. By innovating the population iteration formula and integrating the advantages of Differential Evolution and the Crayfish Optimization Algorithm, [...] Read more.
This paper proposes an Improved Spider Wasp Optimizer (ISWO) to address inaccuracies in calculating the population (N) during iterations of the SWO algorithm. By innovating the population iteration formula and integrating the advantages of Differential Evolution and the Crayfish Optimization Algorithm, along with introducing an opposition-based learning strategy, ISWO accelerates convergence. The adaptive parameters trade-off probability (TR) and crossover probability (Cr) are dynamically updated to balance the exploration and exploitation phases. In each generation, ISWO optimizes individual positions using Lévy flights, DE’s mutation, and crossover operations, and COA’s adaptive update mechanisms. The OBL strategy is applied every 10 generations to enhance population diversity. As the iterations progress, the population size gradually decreases, ultimately yielding the optimal solution and recording the convergence process. The algorithm’s performance is tested using the 2017 test set, modeling a mountainous environment with a Gaussian function model. Under constraint conditions, the objective function is updated to establish a mathematical model for UAV flight. The minimal cost for obstacle-avoiding flight within the specified airspace is obtained using the fitness function, and the flight path is smoothed through cubic spline interpolation. Overall, ISWO generates high-quality, smooth paths with fewer iterations, overcoming premature convergence and the insufficient local search capabilities of traditional genetic algorithms, adapting to complex terrains, and providing an efficient and reliable solution. Full article
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17 pages, 2166 KiB  
Article
Color Masking Ability of Guided Enamel Regeneration with a Novel Self-Assembling Peptide and Resin Infiltration on Artificial Enamel Lesions Under Various Challenges: An In Vitro Spectrophotometric Analysis
by Nassreen Albar, Syed Nahid Basheer, Mohammed M. Al Moaleem, Sana Ageel, Rehab Abbas, Rafaa Hakami, Arwa Daghrery, Mohammed Sawady, Syed Wali Peeran, Thilla Sekar Vinothkumar and Bassam Zidane
Biomimetics 2024, 9(12), 764; https://doi.org/10.3390/biomimetics9120764 - 16 Dec 2024
Viewed by 530
Abstract
The color masking ability of resin infiltration (RI) and curodont repair fluoride plus–self-assembling peptide (CRFP-SAP) was investigated under various simulated oral challenging conditions. Sixty-four extracted caries-free human canines were randomly divided into two groups: Group 1 (RI) and Group 2 (CRFP-SAP). The baseline [...] Read more.
The color masking ability of resin infiltration (RI) and curodont repair fluoride plus–self-assembling peptide (CRFP-SAP) was investigated under various simulated oral challenging conditions. Sixty-four extracted caries-free human canines were randomly divided into two groups: Group 1 (RI) and Group 2 (CRFP-SAP). The baseline color values of samples were recorded using a spectrophotometer (VITA Easyshade® Advance 4.0 VITA Zahnfabrik, Bad Sackingen, Germany). The samples were stored in a demineralization solution for 4 days to induce artificial enamel lesions (AELs). The AELs of Groups I and II were treated with RI (Icon, DMG, Hamburg, Germany) and CRFP-SAP (vVARDIS, Zug, Switzerland), respectively, followed by color measurements. Each group was subjected to challenges such as remineralization, pH cycling, staining, and thermocycling, followed by color measurements. The difference between the mean ∆E (color difference value) of sound enamel and both treatment groups was less than 3.7 1-week post treatment. Meanwhile, the difference between the mean ∆E of RI-treated samples and all kinds of challenges was more than 3.7, while for the CRFP-SAP-treated samples, it was less than 3.7 for all kinds of challenges, except for the thermocycling, for which the mean ∆E difference was 4.3. RI and CRFP-SAP treatments were effective in masking the discoloration caused by AELs. However, the color was not stable for RI-treated samples, whereas it was stable for CRFP-SAP-treated samples under all challenges, except for thermocycling. Full article
(This article belongs to the Special Issue Functional Biomimetic Materials and Devices for Biomedical Applications: 4th Edition)
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16 pages, 5803 KiB  
Article
3D-Printed Self-Assembling Helical Models for Exploring Viral Capsid Structures
by Donald Plante, Keegan Unzen and John R. Jungck
Biomimetics 2024, 9(12), 763; https://doi.org/10.3390/biomimetics9120763 - 16 Dec 2024
Viewed by 837
Abstract
This work presents a novel application of additive manufacturing in the design of self-assembling helical viral capsids using 3D-printed components. Expanding on prior work with 3D-printed self-assembling spherical capsids, we developed helical models that integrate geometric parameters and magnetic interactions to mimic key [...] Read more.
This work presents a novel application of additive manufacturing in the design of self-assembling helical viral capsids using 3D-printed components. Expanding on prior work with 3D-printed self-assembling spherical capsids, we developed helical models that integrate geometric parameters and magnetic interactions to mimic key features of the assembly process of helical viral capsids. Using dual-helix phyllotactic patterns and simplified electrostatic simulations, these models consistently self-assemble into a cylinder, providing unique insights into the structural organization and stability of helical capsids. This accessible 3D-printed approach demonstrates the potential of additive manufacturing for research in mesoscale self-assembling models and in the education of complex biological assembly processes, promoting hands-on exploration of viral architecture and self-assembly mechanisms. Full article
(This article belongs to the Special Issue Biomimetic Nanotechnology Vol. 4: Advances in Biomimetic Nanotechnology)
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13 pages, 3729 KiB  
Article
Quasi-Static Mechanical Biomimetics Evaluation of Car Crash Dummy Skin
by Yurun Li, Zhixin Liu, Cuiru Sun, Xiaoya Zheng, Guorui Du, Xiaoshuang Wang, Songchen Wang and Weidong Liu
Biomimetics 2024, 9(12), 762; https://doi.org/10.3390/biomimetics9120762 - 15 Dec 2024
Viewed by 673
Abstract
Accurate replication of soft tissue properties is essential for the development of car crash test dummy skin to ensure the precision of biomechanical injury data. However, the intricacy of multi-layer soft tissue poses challenges in standardizing the development and testing of dummy skin [...] Read more.
Accurate replication of soft tissue properties is essential for the development of car crash test dummy skin to ensure the precision of biomechanical injury data. However, the intricacy of multi-layer soft tissue poses challenges in standardizing the development and testing of dummy skin materials to emulate soft tissue properties. This study presents a comprehensive testing and analysis of the compressive mechanical properties of both single and multi-layered soft tissues and car crash dummy skin materials, aiming to enhance the biofidelity of dummy skin. We presented one-term Ogden hyperelastic models and generalized Maxwell viscoelastic models for single-layer and multi-layer soft tissues, as well as dummy skin materials. The comparative analysis results indicate that the existing dummy skin material fails to fully consider the strain-rate-dependent characteristic of soft tissue. Furthermore, dummy skin materials exhibited ~3 times shorter relaxation times and ~2–3 times lower stress decay rates compared to soft tissues, suggesting a less viscous nature. This study provides an accurate representation of the mechanics of soft tissue and dummy skin under quasi-static compressive loading. The findings are instrumental for the development of novel bionic skin materials or structures to more precisely replicate the biomechanical properties of soft tissues, thereby enhancing the accuracy and reliability of car crash test dummies. Full article
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24 pages, 9053 KiB  
Article
An Ensemble Deep Learning Approach for EEG-Based Emotion Recognition Using Multi-Class CSP
by Behzad Yousefipour, Vahid Rajabpour, Hamidreza Abdoljabbari, Sobhan Sheykhivand and Sebelan Danishvar
Biomimetics 2024, 9(12), 761; https://doi.org/10.3390/biomimetics9120761 - 14 Dec 2024
Viewed by 907
Abstract
In recent years, significant advancements have been made in the field of brain–computer interfaces (BCIs), particularly in the area of emotion recognition using EEG signals. The majority of earlier research in this field has missed the spatial–temporal characteristics of EEG signals, which are [...] Read more.
In recent years, significant advancements have been made in the field of brain–computer interfaces (BCIs), particularly in the area of emotion recognition using EEG signals. The majority of earlier research in this field has missed the spatial–temporal characteristics of EEG signals, which are critical for accurate emotion recognition. In this study, a novel approach is presented for classifying emotions into three categories, positive, negative, and neutral, using a custom-collected dataset. The dataset used in this study was specifically collected for this purpose from 16 participants, comprising EEG recordings corresponding to the three emotional states induced by musical stimuli. A multi-class Common Spatial Pattern (MCCSP) technique was employed for the processing stage of the EEG signals. These processed signals were then fed into an ensemble model comprising three autoencoders with Convolutional Neural Network (CNN) layers. A classification accuracy of 99.44 ± 0.39% for the three emotional classes was achieved by the proposed method. This performance surpasses previous studies, demonstrating the effectiveness of the approach. The high accuracy indicates that the method could be a promising candidate for future BCI applications, providing a reliable means of emotion detection. Full article
(This article belongs to the Special Issue Advances in Brain–Computer Interfaces)
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20 pages, 2833 KiB  
Article
An Advanced Whale Optimization Algorithm for Grayscale Image Enhancement
by Yibo Han, Pei Hu, Zihan Su, Lu Liu and John Panneerselvam
Biomimetics 2024, 9(12), 760; https://doi.org/10.3390/biomimetics9120760 - 14 Dec 2024
Viewed by 524
Abstract
Image enhancement is an important step in image processing to improve contrast and information quality. Intelligent enhancement algorithms are gaining popularity due to the limitations of traditional methods. This paper utilizes a transformation function to enhance the global and local information of grayscale [...] Read more.
Image enhancement is an important step in image processing to improve contrast and information quality. Intelligent enhancement algorithms are gaining popularity due to the limitations of traditional methods. This paper utilizes a transformation function to enhance the global and local information of grayscale images, but the parameters of this function can produce significant changes in the processed images. To address this, the whale optimization algorithm (WOA) is employed for parameter optimization. New equations are incorporated into WOA to improve its global optimization capability, and exemplars and advanced spiral updates improve the convergence of the algorithm. Its performance is validated on four different types of images. The algorithm not only outperforms comparison algorithms in the objective function but also excels in other image enhancement metrics, including peak signal-to-noise ratio (PSNR), feature similarity index (FSIM), structural similarity index (SSIM), and patch-based contrast quality index (PCQI). It is superior to the comparison algorithms in 11, 6, 11, 13, and 7 images in these metrics, respectively. The results demonstrate that the algorithm is suitable for image enhancement both subjectively and statistically. Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)
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17 pages, 8621 KiB  
Article
The Protection of RC Columns by Bio-Inspired Honeycomb Column Thin-Walled Structure (BHTS) Under Impact Load
by Shijie Wang, Hongxiang Xia, Yuncui Zong, Jianjun Liang and Ripeng Zhu
Biomimetics 2024, 9(12), 759; https://doi.org/10.3390/biomimetics9120759 - 13 Dec 2024
Viewed by 689
Abstract
The bio-inspired honeycomb column thin-walled structure (BHTS) is inspired by the biological structure of beetle elytra and designed as a lightweight buffer interlayer to prevent damage to the reinforced concrete bridge pier (RCBP) under the overload impact from vehicle impact. According to the [...] Read more.
The bio-inspired honeycomb column thin-walled structure (BHTS) is inspired by the biological structure of beetle elytra and designed as a lightweight buffer interlayer to prevent damage to the reinforced concrete bridge pier (RCBP) under the overload impact from vehicle impact. According to the prototype structure of the pier, a batch of scale models with a scaling factor of 1:10 was produced. The BHTS buffer interlayer was installed on the reinforced concrete (RC) column specimen to carry out the steel ball impact test. Then, the modified numerical model was subjected to the low-energy input impact test of the steel ball without energy loss during the falling process at the equivalent height of 1.0–3.5 m, and the dynamic response characteristics of the RC column were analyzed. By comparing the impact force and impact duration, maximum displacement, and residual displacement in the impact model, the BHTS buffer interlayer’s protective effect on RC columns under lower energy lateral impact was evaluated. Later, a high-energy input lateral impact test of a steel ball falling at an equivalent height of 20.0 m was carried out. According to the material damage, dynamic response, and energy absorption characteristics in the impact model, the failure process of the RC columns was analyzed. The results showed that BHTS absorbed 82.33% of the impact kinetic energy and reduced 77.27% of the impact force, 86.51% of the inertia force, and 64.86% of the base shear force under the failure mode of a 20 m impact condition. It can transform the shear failure of the RC column into bending failure and play an effective protective role for the RC column. This study can provide useful references for collision prevention design in practical engineering. Full article
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14 pages, 6225 KiB  
Article
The Contribution of the Limbus and Collagen Fibrils to Corneal Biomechanical Properties: Estimation of the Low-Strain In Vivo Elastic Modulus and Tissue Strain
by Frederick H. Silver, Tanmay Deshmukh, Dominick Benedetto, Mickael Asfaw, Olivia Doyle, Nicholas Kozachuk and Kamryn Li
Biomimetics 2024, 9(12), 758; https://doi.org/10.3390/biomimetics9120758 - 13 Dec 2024
Viewed by 767
Abstract
We have compared the biomechanical properties of human and porcine corneas using vibrational optical coherence tomography (VOCT). The elastic modulus of the cornea has been previously reported in the literature to vary from about several kPa to more than several GPa based on [...] Read more.
We have compared the biomechanical properties of human and porcine corneas using vibrational optical coherence tomography (VOCT). The elastic modulus of the cornea has been previously reported in the literature to vary from about several kPa to more than several GPa based on the results of different techniques. In addition, the formation of corneal cones near the central cornea in keratoconus has been observed in the clinic. Measurements of the resonant frequency and morphology of human and porcine corneas were used to evaluate the role of the limbus in corneal stabilization, the effect of Bowman’s layer, and the effect of collagen content on the low-strain corneal biomechanics. The results of these studies indicate that limbus stability plays an important anatomic role in preventing folding, corneal slippage, and cone formation. Machine learning studies of both human and porcine corneas indicate that Bowman’s membrane, like that of the collagen fibrils found in the anterior corneal stroma, contributes to the 110–120 Hz resonant frequency peak. Finite element and SOLIDWORKS models of normal and keratoconus corneas suggest that the deformation of the cornea is the highest at the central zone and is higher in keratoconus corneas compared to normal controls. VOCT results suggest that although collagen fibril slippage occurs first at the limbus, cone formation in keratoconus occurs centrally/paracentrally, where stress concentration and deformation due to intraocular forces are the highest. Cone formation occurs at the points of maximum curvature. Results of these studies indicate the elastic modulus of cornea fibrillar collagen dictates the corneal elastic modulus at low strains. These results suggest that tension in the cornea at the limbus results in deformation into the low modulus region of the J-shaped stress–strain curve, resulting in an in vivo strain of less than about 10%. We propose that tension in the cornea provides a baseline force that regulates corneal epithelial regeneration as well as corneal lamellae composition and matrix turnover. Full article
(This article belongs to the Special Issue Dynamical Response of Biological System and Biomaterial 2024)
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26 pages, 2478 KiB  
Article
Enhanced Nutcracker Optimization Algorithm with Hyperbolic Sine–Cosine Improvement for UAV Path Planning
by Shuhao Jiang, Shengliang Cui, Haoran Song, Yizi Lu and Yong Zhang
Biomimetics 2024, 9(12), 757; https://doi.org/10.3390/biomimetics9120757 - 12 Dec 2024
Viewed by 565
Abstract
Three-dimensional (3D) path planning is a crucial technology for ensuring the efficient and safe flight of UAVs in complex environments. Traditional path planning algorithms often find it challenging to navigate complex obstacle environments, making it challenging to quickly identify the optimal path. To [...] Read more.
Three-dimensional (3D) path planning is a crucial technology for ensuring the efficient and safe flight of UAVs in complex environments. Traditional path planning algorithms often find it challenging to navigate complex obstacle environments, making it challenging to quickly identify the optimal path. To address these challenges, this paper introduces a Nutcracker Optimizer integrated with Hyperbolic Sine–Cosine (ISCHNOA). First, the exploitation process of the sinh cosh optimizer is incorporated into the foraging strategy to enhance the efficiency of nutcracker in locating high-quality food sources within the search area. Secondly, a nonlinear function is designed to improve the algorithm’s convergence speed. Finally, a sinh cosh optimizer that incorporates historical positions and dynamic factors is introduced to enhance the influence of the optimal position on the search process, thereby improving the accuracy of the nutcracker in retrieving stored food. In this paper, the performance of the ISCHNOA algorithm is tested using 14 classical benchmark test functions as well as the CEC2014 and CEC2020 suites and applied to UAV path planning models. The experimental results demonstrate that the ISCHNOA algorithm outperforms the other algorithms across the three test suites, with the total cost of the planned UAV paths being lower. Full article
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18 pages, 4484 KiB  
Article
One-Step Fabrication Process of Silica–Titania Superhydrophobic UV-Blocking Thin Coatings onto Polymeric Films
by Sharon Hayne, Naftali Kanovsky and Shlomo Margel
Biomimetics 2024, 9(12), 756; https://doi.org/10.3390/biomimetics9120756 - 12 Dec 2024
Viewed by 665
Abstract
Developing a durable multifunctional superhydrophobic coating on polymeric films that can be industrially scalable is a challenge in the field of surface engineering. This article presents a novel method for a scalable technology using a simple single-step fabrication of a superhydrophobic coating on [...] Read more.
Developing a durable multifunctional superhydrophobic coating on polymeric films that can be industrially scalable is a challenge in the field of surface engineering. This article presents a novel method for a scalable technology using a simple single-step fabrication of a superhydrophobic coating on polymeric films that exhibits excellent water-repelling and UV-blocking properties, along with impressive wear resistance and chemical robustness. A mixture of titanium precursors, tetraethylorthosilicate (TEOS), hydrophobic silanes and silica nano/micro-particles is polymerized directly on a corona-treated polymeric film which reacts with the surface via siloxane chemistry. The mixture is then spread on polymeric films using a Mayer rod, which eliminates the need for expensive equipment or multistep processes. The incorporation of silica nanoparticles along with titanium precursor and TEOS results in the formation of a silica–titania network around the silica nanoparticles. This chemically binds them to the activated surface, forming a unique dual-scale surface morphology depending on the size of the silica nanoparticles used in the coating mixture. The coated films were shown to be superhydrophobic with a high water contact angle of over 180° and a rolling angle of 0°. This is due to the combination of dual-scale micro/nano roughness with fluorinated hydrocarbons that lowered the surface free energy. The coatings exhibited excellent chemical and mechanical durability, as well as UV-blocking capabilities. The results show that the coatings remain superhydrophobic even after a sandpaper abrasion test under a pressure of 2.5 kPa for a distance of 30 m. Full article
(This article belongs to the Special Issue Superhydrophobic Surfaces: Challenges, Solutions and Applications)
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19 pages, 954 KiB  
Article
Memory–Non-Linearity Trade-Off in Distance-Based Delay Networks
by Stefan Iacob and Joni Dambre
Biomimetics 2024, 9(12), 755; https://doi.org/10.3390/biomimetics9120755 - 11 Dec 2024
Viewed by 735
Abstract
The performance of echo state networks (ESNs) in temporal pattern learning tasks depends both on their memory capacity (MC) and their non-linear processing. It has been shown that linear memory capacity is maximized when ESN neurons have linear activation, and that a trade-off [...] Read more.
The performance of echo state networks (ESNs) in temporal pattern learning tasks depends both on their memory capacity (MC) and their non-linear processing. It has been shown that linear memory capacity is maximized when ESN neurons have linear activation, and that a trade-off between non-linearity and linear memory capacity is required for temporal pattern learning tasks. The more recent distance-based delay networks (DDNs) have shown improved memory capacity over ESNs in several benchmark temporal pattern learning tasks. However, it has not thus far been studied whether this increased memory capacity comes at the cost of reduced non-linear processing. In this paper, we advance the hypothesis that DDNs in fact achieve a better trade-off between linear MC and non-linearity than ESNs, by showing that DDNs can have strong non-linearity with large memory spans. We tested this hypothesis using the NARMA-30 task and the bitwise delayed XOR task, two commonly used reservoir benchmark tasks that require a high degree of both non-linearity and memory. Full article
(This article belongs to the Special Issue Biomimetics and Bioinspired Artificial Intelligence Applications: 2nd Edition)
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