Biomimetics最新文献

{"title":"Using Patient-Specific 3D-Printed C1-C2 Interfacet Spacers for the Treatment of Type 1 Basilar Invagination: A Clinical Case Report.","authors":"Tim T Bui, Alexander T Yahanda, Karan Joseph, Miguel Ruiz-Cardozo, Bernardo A de Monaco, Alexander Perdomo-Pantoja, Joshua P Koleske, Sean D McEvoy, Camilo A Molina","doi":"10.3390/biomimetics10060408","DOIUrl":"10.3390/biomimetics10060408","url":null,"abstract":"<p><p><b>Background:</b> Type 1 basilar invagination (BI) is caused by a structural instability at the craniovertebral junction (CVJ) and has been historically treated with distraction and stabilization through fusion of the C1-C2 vertebrae. Recent advances in 3D printed custom implants (3DPIs) have improved the array of available options for reaching distraction and alignment goals. <b>Case Presentation:</b> We report the case of a 15-year-old male who presented with early signs of cervical myelopathy. Radiographic evaluation revealed type 1 BI with a widened atlantodental interval (ADI) of 3.7 mm and a 9 mm McRae's line violation (MLV) of the dens, resulting in severe narrowing at the CVJ and brainstem/spinal cord impingement. Of note, the patient had bilateral dysplastic C1 and C2 anatomy, thus requiring a patient-specific 3DPI to conform to this anatomy and enable sufficient distraction and fusion. Custom 3D printed C1-C2 interfacet spacers were created and implemented within 14 days to achieve sufficient distraction, osteoconduction, and stabilization of the C1-C2 joint. <b>Outcome:</b> Postoperatively, the patient remained neurologically intact with myelopathic symptom improvement before discharge on postoperative day 4. Postoperative imaging demonstrated the resolution of BI from successful C1-C2 joint distraction and confirmed intended implant placement with resolution of canal stenosis. During his 6-week follow-up, the patient remained neurologically stable with intact hardware and preserved alignment. <b>Conclusions:</b> This case is the first in the United States demonstrating the use of custom 3D printed interfacet spacers to achieve successful distraction, decompression, and stabilization of type 1 BI. These patient-specific 3DPIs were designed and created in a streamlined manner and serve as proof-of-concept of pragmatic implant design and manufacturing. Future optimization of the workflow and characterization of long-term patient outcomes should be explored for these types of 3DPI.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Domain-Separated Quantum Neural Network for Truss Structural Analysis with Mechanics-Informed Constraints.","authors":"Hyeonju Ha, Sudeok Shon, Seungjae Lee","doi":"10.3390/biomimetics10060407","DOIUrl":"10.3390/biomimetics10060407","url":null,"abstract":"<p><p>This study proposes an index-based quantum neural network (QNN) model, built upon a variational quantum circuit (VQC), as a surrogate framework for the static analysis of truss structures. Unlike coordinate-based models, the proposed QNN uses discrete member and node indices as inputs, and it adopts a separate-domain strategy that partitions the structure for parallel training. This architecture reflects the way nature organizes and optimizes complex systems, thereby enhancing both flexibility and scalability. Independent quantum circuits are assigned to each separate domain, and a mechanics-informed loss function based on the force method is formulated within a Lagrangian dual framework to embed physical constraints directly into the training process. As a result, the model achieves high prediction accuracy and fast convergence, even under complex structural conditions with relatively few parameters. Numerical experiments on 2D and 3D truss structures show that the QNN reduces the number of parameters by up to 64% compared to conventional neural networks, while achieving higher accuracy. Even within the same QNN architecture, the separate-domain approach outperforms the single-domain model with a 6.25% reduction in parameters. The proposed index-based QNN model has demonstrated practical applicability for structural analysis and shows strong potential as a quantum-based numerical analysis tool for future applications in building structure optimization and broader engineering domains.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190723/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transition Processes in Technological Systems: Inspiration from Processes in Biological Evolution.","authors":"Martin Möller, Olga Speck, Harishankar Thekkepat, Thomas Speck","doi":"10.3390/biomimetics10060406","DOIUrl":"10.3390/biomimetics10060406","url":null,"abstract":"<p><p>With environmental challenges intensifying, a fundamental understanding and sustainable management of ongoing transition processes are crucial. Biological evolution provides valuable lessons on how to adapt and thrive under changing conditions. By studying its key principles, we identified analogies between biological evolution and technological transitions in terms of both the Multi-Level Perceptive and the path dependency model. The comparative study also revealed that, despite contrasting time scales, the generation-based and version-based developments are comparable. In addition, interesting similarities were found in the increase and decrease of variety and between fitness and consistency. The lessons learned from biology include \"Give it a try\", \"Do not close for reconstruction\", and \"Keep older versions in the innovation process\". Based on this comparison, we aim to gain insights for a better understanding of how to manage technology transitions and to derive concrete indicators for assessing and monitoring them. In doing so, we can provide action-oriented guidance for developing more sustainable technological solutions for major ongoing transitions, such as the energy transition.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190928/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical Analysis of Load Reduction in the Gliding Process Achieved by the Bionic Swan's Webbed-Foot Structures.","authors":"Fukui Gao, Xiyan Liu, Xinlin Li, Zhaolin Fan, Houcun Zhou, Wenhua Wu","doi":"10.3390/biomimetics10060405","DOIUrl":"10.3390/biomimetics10060405","url":null,"abstract":"<p><p>Webbed-foot gliding water entry is a characteristic water-landing strategy employed by swans and other large waterfowls, demonstrating exceptional low-impact loading and remarkable motion stability. These distinctive biomechanical features offer significant potential for informing the design of cross-medium vehicles' (CMVs') water-entry systems. To analyze the hydrodynamic mechanisms and flow characteristics during swan webbed-foot gliding entry, the three-dimensional bionic webbed-foot water-entry process was investigated through a computational fluid dynamics (CFD) method coupled with global motion mesh (GMM) technology, with a particular emphasis on elucidating the regulatory effects of entry parameters on dynamic performance. The results demonstrated that the gliding water-entry process can be divided into two distinct phases: stable skipping and surface gliding. During the stable skipping phase, the motion trajectory exhibits quasi-sinusoidal periodic fluctuations, accompanied by multiple water-impact events and significant load variations. In the surface-gliding phase, the kinetic energy of the bionic webbed foot progressively decreases while maintaining relatively stable load characteristics. Increasing the water-entry velocity will enhance impact loads while simultaneously increasing the skipping frequency and distance. Increasing the water-entry angle will primarily intensify the impact load magnitude while slightly reducing the skipping frequency and distance. An optimal pitch angle of 20° provides maximum glide-skip stability for the bio-inspired webbed foot, with angles exceeding 25° or below 15° leading to motion instability. This study on webbed-foot gliding entry behavior provided insights for developing novel bio-inspired entry strategies for cross-medium vehicles, while simultaneously advancing the optimization of impact-mitigation designs in gliding water-entry systems.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190444/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of EP@PDMS@F-SiO₂ Superhydrophobic Composite Coating on Titanium Alloy Substrate.","authors":"Chaoming Huang, Jinhe Qi, Jie Li, Xinchi Li, Jiawei Chen, Shuo Fu, Yanning Lu","doi":"10.3390/biomimetics10060404","DOIUrl":"10.3390/biomimetics10060404","url":null,"abstract":"<p><p>In this study, a preparation method of superhydrophobic composite coating based on a titanium alloy (Ti-6Al-4V) substrate is proposed. The micro-scale pit array structure was fabricated via laser etching technology. Utilizing the synergistic effects of epoxy resin (EP), polydimethylsiloxane (PDMS), and fluorinated nanosilica (F-SiO₂), we successfully prepared an EP@PDMS@F-SiO₂ composite coating. The effects of the contents of EP, PDMS, and F-SiO₂ on the surface wettability, mechanical stability, and UV durability were studied by optimizing the coating ratio through orthogonal experiments. The results show that the micro-nano composite structure formed by laser etching can effectively fix the coating particles and provide excellent superhydrophobicity on the surface. The coating retains high hydrophobicity after paper abrasion (1000 cm under a 200 g load), demonstrating the mechanical stability of the armor-like structure, High-content F-SiO₂ coatings exhibit greater UV durability. In addition, the coating surface has low droplet adhesion and self-cleaning capabilities for efficient contaminant removal. The research provides theoretical and technical support for the design and engineering application of a non-fluorinated, environmentally friendly superhydrophobic coating.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bionic Energy-Efficient Inverse Kinematics Method Based on Neural Networks for the Legs of Hydraulic Legged Robots.","authors":"Jinbo She, Xiang Feng, Bao Xu, Linyang Chen, Yuan Wang, Ning Liu, Wenpeng Zou, Guoliang Ma, Bin Yu, Kaixian Ba","doi":"10.3390/biomimetics10060403","DOIUrl":"10.3390/biomimetics10060403","url":null,"abstract":"<p><p>Hydraulic legged robots, with advantages such as high load capacity and power density, have become a strategic driving force in advancing intelligent mobile platform technologies. However, their high energy consumption significantly limits long-duration endurance and efficient operational performance. In this paper, inspired by the excellent autonomous energy-efficient consciousness of mammals endowed by natural evolution, a bionic energy-efficient inverse kinematics method based on neural networks (EIKNN) is proposed for the energy-efficient motion planning of hydraulic legged robots with redundant degrees of freedom (RDOFs). Firstly, the dynamic programming (DP) algorithm is used to solve the optimal joint configuration with minimum energy loss as the goal, and the training data set is generated. Subsequently, the inverse kinematic model of the leg with minimum energy loss is learned based on neural network (NN) simulation of the autonomous energy-efficient consciousness endowed to mammals by natural evolution. Finally, extensive comparative experiments validate the effectiveness and superiority of the proposed method. This method not only significantly reduces energy dissipation in hydraulic legged robots but also lays a crucial foundation for advancing hydraulic legged robot technology toward high efficiency, environmental sustainability, and long-term developmental viability.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bio-Signal-Guided Robot Adaptive Stiffness Learning via Human-Teleoperated Demonstrations.","authors":"Wei Xia, Zhiwei Liao, Zongxin Lu, Ligang Yao","doi":"10.3390/biomimetics10060399","DOIUrl":"10.3390/biomimetics10060399","url":null,"abstract":"<p><p>Robot learning from human demonstration pioneers an effective mapping paradigm for endowing robots with human-like operational capabilities. This paper proposes a bio-signal-guided robot adaptive stiffness learning framework grounded in the conclusion that muscle activation of the human arm is positively correlated with the endpoint stiffness. First, we propose a human-teleoperated demonstration platform enabling real-time modulation of robot end-effector stiffness by human tutors during operational tasks. Second, we develop a dual-stage probabilistic modeling architecture employing the Gaussian mixture model and Gaussian mixture regression to model the temporal-motion correlation and the motion-sEMG relationship, successively. Third, a real-world experiment was conducted to validate the effectiveness of the proposed skill transfer framework, demonstrating that the robot achieves online adaptation of Cartesian impedance characteristics in contact-rich tasks. This paper provides a simple and intuitive way to plan the Cartesian impedance parameters, transcending the classical method that requires complex human arm endpoint stiffness identification before human demonstration or compensation for the difference in human-robot operational effects after human demonstration.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191027/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Feature Facial Complexion Classification Algorithms Based on CNN.","authors":"Xiyuan Cao, Delong Zhang, Chunyang Jin, Zhidong Zhang, Chenyang Xue","doi":"10.3390/biomimetics10060402","DOIUrl":"10.3390/biomimetics10060402","url":null,"abstract":"<p><p>Variations in facial complexion serve as a telltale sign of underlying health conditions. Precisely categorizing facial complexions poses a significant challenge due to the subtle distinctions in facial features. Three multi-feature facial complexion classification algorithms leveraging convolutional neural networks (CNNs) are proposed. They fuse, splice, or independently train the features extracted from distinct facial regions of interest (ROI), respectively. Innovative frameworks of the three algorithms can more effectively exploit facial features, improving the utilization rate of feature information and classification performance. We trained and validated the three algorithms on the dataset consisting of 721 facial images that we had collected and preprocessed. The comprehensive evaluation reveals that multi-feature fusion and splicing classification algorithms achieve accuracies of 95.98% and 93.76%, respectively. The optimal approach combining multi-feature CNN with machine learning algorithms attains a remarkable accuracy of 97.78%. Additionally, these experiments proved that the multidomain combination was crucial, and the arrangement of ROI features, including the nose, forehead, philtrum, and right and left cheek, was the optimal choice for classification. Furthermore, we employed the EfficientNet model for training on the face image as a whole, which achieves a classification accuracy of 89.37%. The difference in accuracy underscores the superiority and efficacy of multi-feature classification algorithms. The employment of multi-feature fusion algorithms in facial complexion classification holds substantial advantages, ushering in fresh research directions in the field of facial complexion classification and deep learning.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12190456/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Structural Design and Optimization of a Novel Independently Driven Bionic Ornithopter.","authors":"Mouhui Dai, Ruien Wu, Mingxuan Ye, Kai Gao, Bin Chen, Xinwang Tao, Zhijie Fan","doi":"10.3390/biomimetics10060401","DOIUrl":"10.3390/biomimetics10060401","url":null,"abstract":"<p><p>To address the limitations of traditional single-motor bionic ornithopters in terms of environmental adaptability and lift capacity, this study proposes a dual-motor independently driven system utilizing a cross-shaft single-gear crank mechanism to achieve adjustable flap speed and wing frequency, thereby enabling asymmetric flapping for enhanced environmental adaptability. The design integrates a two-stage reduction gear group to optimize torque transmission and an S1223 high-lift airfoil to improve aerodynamic efficiency. Multiphysics simulations combining computational fluid dynamics (CFD) and finite element analysis (FEA) demonstrate that, under flapping frequencies of 1-3.45 Hz and wind speeds of 1.2-3 m/s, the optimized model achieves 50% and 60% improvements in lift and thrust coefficients, respectively, compared to the baseline. Concurrently, peak stress in critical components (e.g., cam disks and wing rods) is reduced by 37% to 41 MPa, with significantly improved stress uniformity. These results validate the dual-motor system's capability to dynamically adapt to turbulent airflow through the precise control of wing kinematics, offering innovative solutions for applications such as aerial inspection and precision agriculture.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards Self-Assembling 3D-Printed Shapes Through Βiomimetic Μechanical Interlocking.","authors":"Tino Marte, Savvas Koltsakidis, Thomas Profitiliotis, Emmanouil Tzimtzimis, Dimitrios Tzetzis","doi":"10.3390/biomimetics10060400","DOIUrl":"10.3390/biomimetics10060400","url":null,"abstract":"<p><p>While early studies on macroscopic self-assembly peaked in the late 20th century, recent research continues to explore and expand the field's potential through innovative materials and external control strategies. To harness this potential, a unit cell was designed and 3D-printed that could form a face-centered cubic lattice and stabilize it through a biomimetic mechanism for mechanical interlocking. The wing coupling structures of the brown marmorated stink bug were examined under a scanning electron microscope to be used as a source of bio-inspiration for the interlocking mechanism. A total of 20 unit cells were studied in five different self-assembly processes and in different compression scenarios. A maximum average of 34% of unit cells remained stable, and 20% were mechanically interlocked after self-assembly tests. The compression tests performed on a single unit cell revealed that the cell can withstand forces up to 1000 N without any plastic deformation. Pyramid configurations from 5-unit cells were manually assembled and assessed in compression tests. They showed an average compression force of 294 N. As the first study focused on self-assembly through mechanical interlocking, further studies that change the unit cell production and self-assembly processes are expected to improve upon these results.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 6","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12191241/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144483007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}