Journal Description
Biomimetics
Biomimetics
is an international, peer-reviewed, open access journal on biomimicry and bionics, published monthly online by MDPI. The International Society of Bionic Engineering (ISBE) is affiliated with Biomimetics.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q1 (Engineering, Multidisciplinary) / CiteScore - Q2 (Biomedical Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.2 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
4.5 (2022);
5-Year Impact Factor:
4.1 (2022)
Latest Articles
Dynamic Analysis of the Locomotion Mechanism in Foxtail Robots: Frictional Anisotropy and Bristle Diversity
Biomimetics 2024, 9(6), 311; https://doi.org/10.3390/biomimetics9060311 - 22 May 2024
Abstract
This study investigated the locomotion mechanism of foxtail robots, focusing on the frictional anisotropy of tilted bristles under the same friction coefficient and propulsion strategy using bristle diversity. Through dynamic analysis and simulations, we confirmed the frictional anisotropy of tilted bristles and elucidated
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This study investigated the locomotion mechanism of foxtail robots, focusing on the frictional anisotropy of tilted bristles under the same friction coefficient and propulsion strategy using bristle diversity. Through dynamic analysis and simulations, we confirmed the frictional anisotropy of tilted bristles and elucidated the role of bristle diversity in generating propulsive force. The interaction between contact nonuniformity and frictional anisotropy was identified as the core principle enabling foxtail locomotion. Simulations of foxtail robots with multiple bristles demonstrated that variations in bristle length, angle, and deformation contribute to propulsive force generation and environmental adaptability. In addition, this study analyzed the influence of major design parameters on frictional anisotropy, highlighting the critical roles of body height, bristle length, stiffness, reference angle, and friction coefficient. The proposed guidelines for designing foxtail robots emphasize securing bristle nonuniformity and inducing contact nonuniformity. The simulation framework presented enables the quantitative prediction and optimization of foxtail robot performance. This research provides valuable insights into foxtail robot locomotion and lays a foundation for the development of efficient and adaptive next-generation robots for diverse environments.
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(This article belongs to the Section Locomotion and Bioinspired Robotics)
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Adaptive Gait Acquisition through Learning Dynamic Stimulus Instinct of Bipedal Robot
by
Yuanxi Zhang, Xuechao Chen, Fei Meng, Zhangguo Yu, Yidong Du, Zishun Zhou and Junyao Gao
Biomimetics 2024, 9(6), 310; https://doi.org/10.3390/biomimetics9060310 - 22 May 2024
Abstract
Standard alternating leg motions serve as the foundation for simple bipedal gaits, and the effectiveness of the fixed stimulus signal has been proved in recent studies. However, in order to address perturbations and imbalances, robots require more dynamic gaits. In this paper, we
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Standard alternating leg motions serve as the foundation for simple bipedal gaits, and the effectiveness of the fixed stimulus signal has been proved in recent studies. However, in order to address perturbations and imbalances, robots require more dynamic gaits. In this paper, we introduce dynamic stimulus signals together with a bipedal locomotion policy into reinforcement learning (RL). Through the learned stimulus frequency policy, we induce the bipedal robot to obtain both three-dimensional (3D) locomotion and an adaptive gait under disturbance without relying on an explicit and model-based gait in both the training stage and deployment. In addition, a set of specialized reward functions focusing on reliable frequency reflections is used in our framework to ensure correspondence between locomotion features and the dynamic stimulus. Moreover, we demonstrate efficient sim-to-real transfer, making a bipedal robot called BITeno achieve robust locomotion and disturbance resistance, even in extreme situations of foot sliding in the real world. In detail, under a sudden change in torso velocity of m/s in 0.65 s, the recovery time is within 1.5–2.0 s.
Full article
(This article belongs to the Special Issue Recent Advances in Robotics and Biomimetics)
Open AccessArticle
Biocompatibility and Osteogenic Activity of Samarium-Doped Hydroxyapatite—Biomimetic Nanoceramics for Bone Regeneration Applications
by
Mihaela Balas, Madalina Andreea Badea, Steluta Carmen Ciobanu, Florentina Piciu, Simona Liliana Iconaru, Anca Dinischiotu and Daniela Predoi
Biomimetics 2024, 9(6), 309; https://doi.org/10.3390/biomimetics9060309 - 22 May 2024
Abstract
In this study, we report on the development of hydroxyapatite (HAp) and samarium-doped hydroxyapatite (SmHAp) nanoparticles using a cost-effective method and their biological effects on a bone-derived cell line MC3T3-E1. The physicochemical and biological features of HAp and SmHAp nanoparticles are explored. The
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In this study, we report on the development of hydroxyapatite (HAp) and samarium-doped hydroxyapatite (SmHAp) nanoparticles using a cost-effective method and their biological effects on a bone-derived cell line MC3T3-E1. The physicochemical and biological features of HAp and SmHAp nanoparticles are explored. The X-ray diffraction (XRD) studies revealed that no additional peaks were observed after the integration of samarium (Sm) ions into the HAp structure. Valuable information regarding the molecular structure and morphological features of nanoparticles were obtained by using Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). The elemental composition obtained by using energy-dispersive X-ray spectroscopy (EDS) confirmed the presence of the HAp constituent elements, Ca, O, and P, as well as the presence and uniform distribution of Sm3+ ions. Both HAp and SmHAp nanoparticles demonstrated biocompatibility at concentrations below 25 μg/mL and 50 μg/mL, respectively, for up to 72 h of exposure. Cell membrane integrity was preserved following treatment with concentrations up to 100 μg/mL HAp and 400 μg/mL SmHAp, confirming the role of Sm3+ ions in enhancing the cytocompatibility of HAp. Furthermore, our findings reveal a positive, albeit limited, effect of SmHAp nanoparticles on the actin dynamics, osteogenesis, and cell migration compared to HAp nanoparticles. Importantly, the biological results highlight the potential role of Sm3+ ions in maintaining cellular balance by mitigating disruptions in Ca2+ homeostasis induced by HAp nanoparticles. Therefore, our study represents a significant contribution to the safety assessment of both HAp and SmHAp nanoparticles for biomedical applications focused on bone regeneration.
Full article
(This article belongs to the Special Issue Advances in Bioceramics for Bone Regeneration)
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Open AccessArticle
Synthesis of Chitosan and Ferric-Ion (Fe3+)-Doped Brushite Mineral Cancellous Bone Scaffolds
by
Lemiha Yildizbakan, Neelam Iqbal, Peter V. Giannoudis and Animesh Jha
Biomimetics 2024, 9(6), 308; https://doi.org/10.3390/biomimetics9060308 - 21 May 2024
Abstract
Biodegradable scaffolds are needed to repair bone defects. To promote the resorption of scaffolds, a large surface area is required to encourage neo-osteogenesis. Herein, we describe the synthesis and freeze-drying methodologies of ferric-ion (Fe3+) doped Dicalcium Phosphate Dihydrate mineral (DCPD), also
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Biodegradable scaffolds are needed to repair bone defects. To promote the resorption of scaffolds, a large surface area is required to encourage neo-osteogenesis. Herein, we describe the synthesis and freeze-drying methodologies of ferric-ion (Fe3+) doped Dicalcium Phosphate Dihydrate mineral (DCPD), also known as brushite, which has been known to favour the in situ condition for osteogenesis. In this investigation, the role of chitosan during the synthesis of DCPD was explored to enhance the antimicrobial, scaffold pore distribution, and mechanical properties post freeze-drying. During the synthesis of DCPD, the calcium nitrate solution was hydrolysed with a predetermined stoichiometric concentration of ammonium phosphate. During the hydrolysis reaction, 10 (mol)% iron (Fe3+) nitrate (Fe(NO3)3) was incorporated, and the DCPD minerals were precipitated (Fe3+-DCPD). Chitosan stir-mixed with Fe3+-DCPD minerals was freeze-dried to create scaffolds. The structural, microstructural, and mechanical properties of freeze-dried materials were characterized.
Full article
(This article belongs to the Special Issue Advances in Biomaterials, Biocomposites and Biopolymers)
Open AccessArticle
Enhancing the Efficiency of a Cybersecurity Operations Center Using Biomimetic Algorithms Empowered by Deep Q-Learning
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Rodrigo Olivares, Omar Salinas, Camilo Ravelo, Ricardo Soto and Broderick Crawford
Biomimetics 2024, 9(6), 307; https://doi.org/10.3390/biomimetics9060307 - 21 May 2024
Abstract
In the complex and dynamic landscape of cyber threats, organizations require sophisticated strategies for managing Cybersecurity Operations Centers and deploying Security Information and Event Management systems. Our study enhances these strategies by integrating the precision of well-known biomimetic optimization algorithms—namely Particle Swarm Optimization,
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In the complex and dynamic landscape of cyber threats, organizations require sophisticated strategies for managing Cybersecurity Operations Centers and deploying Security Information and Event Management systems. Our study enhances these strategies by integrating the precision of well-known biomimetic optimization algorithms—namely Particle Swarm Optimization, the Bat Algorithm, the Gray Wolf Optimizer, and the Orca Predator Algorithm—with the adaptability of Deep Q-Learning, a reinforcement learning technique that leverages deep neural networks to teach algorithms optimal actions through trial and error in complex environments. This hybrid methodology targets the efficient allocation and deployment of network intrusion detection sensors while balancing cost-effectiveness with essential network security imperatives. Comprehensive computational tests show that versions enhanced with Deep Q-Learning significantly outperform their native counterparts, especially in complex infrastructures. These results highlight the efficacy of integrating metaheuristics with reinforcement learning to tackle complex optimization challenges, underscoring Deep Q-Learning’s potential to boost cybersecurity measures in rapidly evolving threat environments.
Full article
(This article belongs to the Special Issue Computer-Aided Biomimetics: 2nd Edition)
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Open AccessReview
Advancement in Cancer Vasculogenesis Modeling through 3D Bioprinting Technology
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Arvind Kumar Shukla, Sik Yoon, Sae-Ock Oh, Dongjun Lee, Minjun Ahn and Byoung Soo Kim
Biomimetics 2024, 9(5), 306; https://doi.org/10.3390/biomimetics9050306 - 20 May 2024
Abstract
Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional
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Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional (3D) bioprinting technology present promising solutions to these challenges. This review provides an overview of cancer vasculogenesis and underscores the importance of precise modeling. It juxtaposes traditional techniques with 3D bioprinting technologies, elucidating the advantages of the latter in developing cancer vasculogenesis models. Furthermore, it explores applications in pathological investigations, preclinical medication screening for personalized treatment and cancer diagnostics, and envisages future prospects for 3D bioprinted cancer vasculogenesis models. Despite notable advancements, current 3D bioprinting techniques for cancer vasculogenesis modeling have several limitations. Nonetheless, by overcoming these challenges and with technological advances, 3D bioprinting exhibits immense potential for revolutionizing the understanding of cancer vasculogenesis and augmenting treatment modalities.
Full article
(This article belongs to the Special Issue Biomimetic 3D/4D Printing)
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Open AccessCase Report
Biomechanical Multipurpose Miniscrew Strategy for Simultaneous Distalization in Class II Patients—The BiGa System
by
Gabriele Di Carlo, Guglielmo Biondi, Ivan Gazzola and Matteo Saccucci
Biomimetics 2024, 9(5), 305; https://doi.org/10.3390/biomimetics9050305 - 20 May 2024
Abstract
An efficient treatment plan using a temporary anchorage device should be built following the principle of reducing the number of tads to obtain a multiple biomechanical advantage. The following case report concerns the Biga system, a strategy that supports orthodontists during class II
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An efficient treatment plan using a temporary anchorage device should be built following the principle of reducing the number of tads to obtain a multiple biomechanical advantage. The following case report concerns the Biga system, a strategy that supports orthodontists during class II corrections and vertical control through treatment. A 12-year-old girl with a high angle of skeletal class II was selected. A novel biomechanical strategy was effectively applied using two tads on the upper arch to obtain sequential distalization of the upper teeth and to correct the lower arch spee curve using third-class elastics. Eventually, on the same tads, a double cantilever was applied to control the overbite and intrusion during incisors’ retraction. The Biga system is an easy biomechanical strategy that ensures the three-dimensional control of treatment mechanics in class II patients.
Full article
(This article belongs to the Special Issue Dentistry and Craniofacial District: The Role of Biomimetics—Second Edition)
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Survival Prediction of Patients after Heart Attack and Breast Cancer Surgery with a Hybrid Model Built with Particle Swarm Optimization, Stacked AutoEncoders, and the Softmax Classifier
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Mehmet Akif Bülbül and Mehmet Fatih Işık
Biomimetics 2024, 9(5), 304; https://doi.org/10.3390/biomimetics9050304 - 19 May 2024
Abstract
The prediction of patient survival is crucial for guiding the treatment process in healthcare. Healthcare professionals rely on analyzing patients’ clinical characteristics and findings to determine treatment plans, making accurate predictions essential for efficient resource utilization and optimal patient support during recovery. In
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The prediction of patient survival is crucial for guiding the treatment process in healthcare. Healthcare professionals rely on analyzing patients’ clinical characteristics and findings to determine treatment plans, making accurate predictions essential for efficient resource utilization and optimal patient support during recovery. In this study, a hybrid architecture combining Stacked AutoEncoders, Particle Swarm Optimization, and the Softmax Classifier was developed for predicting patient survival. The architecture was evaluated using the Haberman’s Survival dataset and the Echocardiogram dataset from UCI. The results were compared with several Machine Learning methods, including Decision Trees, K-Nearest Neighbors, Support Vector Machines, Neural Networks, Gradient Boosting, and Gradient Bagging applied to the same datasets. The findings indicate that the proposed architecture outperforms other Machine Learning methods in predicting patient survival for both datasets and surpasses the results reported in the literature for the Haberman’s Survival dataset. In the light of the findings obtained, the models obtained with the proposed architecture can be used as a decision support system in determining patient care and applied methods.
Full article
(This article belongs to the Special Issue Biomimetic Approaches in Healthcare—Innovations Inspired by Nature)
Open AccessArticle
Development of a New Aggregation Method to Remove Nanoplastics from the Ocean: Proof of Concept Using Mussel Exposure Tests
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Antonio Cid-Samamed, Catarina S. E. Nunes, Cristina Lomas Martínez and Mário S. Diniz
Biomimetics 2024, 9(5), 303; https://doi.org/10.3390/biomimetics9050303 - 18 May 2024
Abstract
The overproduction and mismanagement of plastics has led to the accumulation of these materials in the environment, particularly in the marine ecosystem. Once in the environment, plastics break down and can acquire microscopic or even nanoscopic sizes. Given their sizes, microplastics (MPs) and
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The overproduction and mismanagement of plastics has led to the accumulation of these materials in the environment, particularly in the marine ecosystem. Once in the environment, plastics break down and can acquire microscopic or even nanoscopic sizes. Given their sizes, microplastics (MPs) and nanoplastics (NPs) are hard to detect and remove from the aquatic environment, eventually interacting with marine organisms. This research mainly aimed to achieve the aggregation of micro- and nanoplastics (MNPs) to ease their removal from the marine environment. To this end, the size and stability of polystyrene (PS) MNPs were measured in synthetic seawater with the different components of the technology (ionic liquid and chitosan). The MPs were purchased in their plain form, while the NPs displayed amines on their surface (PS NP-NH2). The results showed that this technology promoted a significant aggregation of the PS NP-NH2, whereas, for the PS MPs, no conclusive results were found, indicating that the surface charge plays an essential role in the MNP aggregation process. Moreover, to investigate the toxicological potential of MNPs, a mussel species (M. galloprovincialis) was exposed to different concentrations of MPs and NPs, separately, with and without the technology. In this context, mussels were sampled after 7, 14, and 21 days of exposure, and the gills and digestive glands were collected for analysis of oxidative stress biomarkers and histological observations. In general, the results indicate that MNPs trigger the production of reactive oxygen species (ROS) in mussels and induce oxidative stress, making gills the most affected organ. Yet, when the technology was applied in moderate concentrations, NPs showed adverse effects in mussels. The histological analysis showed no evidence of MNPs in the gill’s tissues.
Full article
(This article belongs to the Special Issue Biomimetics in Agri-Food: From Preliminary Design to Field Applications)
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Open AccessFeature PaperArticle
Whale Optimization for Cloud–Edge-Offloading Decision-Making for Smart Grid Services
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Gabriel Ioan Arcas, Tudor Cioara and Ionut Anghel
Biomimetics 2024, 9(5), 302; https://doi.org/10.3390/biomimetics9050302 - 18 May 2024
Abstract
As IoT metering devices become increasingly prevalent, the smart energy grid encounters challenges associated with the transmission of large volumes of data affecting the latency of control services and the secure delivery of energy. Offloading computational work towards the edge is a viable
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As IoT metering devices become increasingly prevalent, the smart energy grid encounters challenges associated with the transmission of large volumes of data affecting the latency of control services and the secure delivery of energy. Offloading computational work towards the edge is a viable option; however, effectively coordinating service execution on edge nodes presents significant challenges due to the vast search space making it difficult to identify optimal decisions within a limited timeframe. In this research paper, we utilize the whale optimization algorithm to decide and select the optimal edge nodes for executing services’ computational tasks. We employ a directed acyclic graph to model dependencies among computational nodes, data network links, smart grid energy assets, and energy network organization, thereby facilitating more efficient navigation within the decision space to identify the optimal solution. The offloading decision variables are represented as a binary vector, which is evaluated using a fitness function considering round-trip time and the correlation between edge-task computational resources. To effectively explore offloading strategies and prevent convergence to suboptimal solutions, we adapt the feedback mechanisms, an inertia weight coefficient, and a nonlinear convergence factor. The evaluation results are promising, demonstrating that the proposed solution can effectively consider both energy and data network constraints while enduring faster decision-making for optimization, with notable improvements in response time and a low average execution time of approximately 0.03 s per iteration. Additionally, on complex computational infrastructures modeled, our solution shows strong features in terms of diversity, fitness evolution, and execution time.
Full article
(This article belongs to the Special Issue Biomimetics and Bioinspired Artificial Intelligence Applications)
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Pectoral Fin Propulsion Performance Analysis of Robotic Fish with Multiple Degrees of Freedom Based on Burst-and-Coast Swimming Behavior Stroke Ratio
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Zonggang Li, Bin Li, Haoyu Li and Guangqing Xia
Biomimetics 2024, 9(5), 301; https://doi.org/10.3390/biomimetics9050301 - 18 May 2024
Abstract
The pectoral fin propulsion of a bionic robotic fish always consists of two phases: propulsion and recovery. The robotic fish moves in a burst-and-coast swimming manner. This study aims to analyze a pair of bionic robotic fish with rigid pectoral fin propulsion with
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The pectoral fin propulsion of a bionic robotic fish always consists of two phases: propulsion and recovery. The robotic fish moves in a burst-and-coast swimming manner. This study aims to analyze a pair of bionic robotic fish with rigid pectoral fin propulsion with three degrees of freedom and optimize the elliptical propulsion curve with the minimum recovery stroke resistance using computational fluid dynamics methods. Then, the time allocated to the propulsion and recovery phases is investigated to maximize the propulsion performance of the bionic robotic fish. The numerical simulation results show that when the time ratio of the propulsion and recovery phases is 0.5:1, the resistance during the movement of the robotic fish is effectively reduced, and the drag-reducing effect is pronounced. According to a further analysis of pressure clouds and vortex structures, the pressure difference between the upstream and downstream fins of the pectoral fin varies with different stroke ratios. The increase in recovery phase time helps to prevent premature damage to the vortex ring structure generated during the propulsion process and improves propulsion efficiency.
Full article
(This article belongs to the Special Issue Bio-Inspired Underwater Robots: 2nd Edition)
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Open AccessArticle
Modeling the Electrical Activity of the Heart via Transfer Functions and Genetic Algorithms
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Omar Rodríguez-Abreo, Mayra Cruz-Fernandez, Carlos Fuentes-Silva, Mario A. Quiroz-Juárez and José L. Aragón
Biomimetics 2024, 9(5), 300; https://doi.org/10.3390/biomimetics9050300 - 18 May 2024
Abstract
Although healthcare and medical technology have advanced significantly over the past few decades, heart disease continues to be a major cause of mortality globally. Electrocardiography (ECG) is one of the most widely used tools for the detection of heart diseases. This study presents
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Although healthcare and medical technology have advanced significantly over the past few decades, heart disease continues to be a major cause of mortality globally. Electrocardiography (ECG) is one of the most widely used tools for the detection of heart diseases. This study presents a mathematical model based on transfer functions that allows for the exploration and optimization of heart dynamics in Laplace space using a genetic algorithm (GA). The transfer function parameters were fine-tuned using the GA, with clinical ECG records serving as reference signals. The proposed model, which is based on polynomials and delays, approximates a real ECG with a root-mean-square error of 4.7% and an value of . The model achieves the periodic nature of an ECG signal by using a single periodic impulse input. Its simplicity makes it possible to adjust waveform parameters with a predetermined understanding of their effects, which can be used to generate both arrhythmic patterns and healthy signals. This is a notable advantage over other models that are burdened by a large number of differential equations and many parameters.
Full article
(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2024)
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Open AccessCase Report
Anterior Esthetic Restorations with the Stratified Stamp Technique: A Case Report
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Camillo D’Arcangelo, Matteo Buonvivere and Francesco De Angelis
Biomimetics 2024, 9(5), 299; https://doi.org/10.3390/biomimetics9050299 - 18 May 2024
Abstract
Anterior teeth restoration represents a challenge for dentists, who often rely on the dental technician’s wax-up. The proposed Stratified Stamp Technique (SST) allows for clinically reproducing the wax-up in a quick and easy way. A patient with fractures and discoloration on the upper
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Anterior teeth restoration represents a challenge for dentists, who often rely on the dental technician’s wax-up. The proposed Stratified Stamp Technique (SST) allows for clinically reproducing the wax-up in a quick and easy way. A patient with fractures and discoloration on the upper central incisors was treated with resin-based composite direct restorations. Using SST, a 1 mm thick thermoformed polyethylene-terephthalate-glycol (PETG) template, based on the technician’s wax-up, was produced. Enamel Selective Area Reduction (SAR) was performed to guarantee adequate space for the restorations, and the fracture margins were rounded and finished. Traditional layering procedures according to the five color dimensions of teeth were performed, except for the final labial layer, which was realized with warm composite loaded inside the template and polymerized through it, in order to ensure accurate tooth morphology reproduction. SST offers a reliable method for transferring technician’s wax-up morphology to direct composite restorations in anterior teeth. Compared with other methods, SST allows for better isolation with a rubber dam and permits traditional layering with multiple composite shades, thus leading to satisfactory esthetic outcomes.
Full article
(This article belongs to the Special Issue Dentistry and Craniofacial District: The Role of Biomimetics—Second Edition)
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Open AccessArticle
Solving Engineering Optimization Problems Based on Multi-Strategy Particle Swarm Optimization Hybrid Dandelion Optimization Algorithm
by
Wenjie Tang, Li Cao, Yaodan Chen, Binhe Chen and Yinggao Yue
Biomimetics 2024, 9(5), 298; https://doi.org/10.3390/biomimetics9050298 - 17 May 2024
Abstract
In recent years, swarm intelligence optimization methods have been increasingly applied in many fields such as mechanical design, microgrid scheduling, drone technology, neural network training, and multi-objective optimization. In this paper, a multi-strategy particle swarm optimization hybrid dandelion optimization algorithm (PSODO) is proposed,
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In recent years, swarm intelligence optimization methods have been increasingly applied in many fields such as mechanical design, microgrid scheduling, drone technology, neural network training, and multi-objective optimization. In this paper, a multi-strategy particle swarm optimization hybrid dandelion optimization algorithm (PSODO) is proposed, which is based on the problems of slow optimization speed and being easily susceptible to falling into local extremum in the optimization ability of the dandelion optimization algorithm. This hybrid algorithm makes the whole algorithm more diverse by introducing the strong global search ability of particle swarm optimization and the unique individual update rules of the dandelion algorithm (i.e., rising, falling and landing). The ascending and descending stages of dandelion also help to introduce more changes and explorations into the search space, thus better balancing the global and local search. The experimental results show that compared with other algorithms, the proposed PSODO algorithm greatly improves the global optimal value search ability, convergence speed and optimization speed. The effectiveness and feasibility of the PSODO algorithm are verified by solving 22 benchmark functions and three engineering design problems with different complexities in CEC 2005 and comparing it with other optimization algorithms.
Full article
(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications: 2nd Edition)
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Open AccessReview
Update on Chitin and Chitosan from Insects: Sources, Production, Characterization, and Biomedical Applications
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Zhenying Mei, Pavel Kuzhir and Guilhem Godeau
Biomimetics 2024, 9(5), 297; https://doi.org/10.3390/biomimetics9050297 - 15 May 2024
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Insects, renowned for their abundant and renewable biomass, stand at the forefront of biomimicry-inspired research and offer promising alternatives for chitin and chitosan production considering mounting environmental concerns and the inherent limitations of conventional sources. This comprehensive review provides a meticulous exploration of
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Insects, renowned for their abundant and renewable biomass, stand at the forefront of biomimicry-inspired research and offer promising alternatives for chitin and chitosan production considering mounting environmental concerns and the inherent limitations of conventional sources. This comprehensive review provides a meticulous exploration of the current state of insect-derived chitin and chitosan, focusing on their sources, production methods, characterization, physical and chemical properties, and emerging biomedical applications. Abundant insect sources of chitin and chitosan, from the Lepidoptera, Coleoptera, Orthoptera, Hymenoptera, Diptera, Hemiptera, Dictyoptera, Odonata, and Ephemeroptera orders, were comprehensively summarized. A variety of characterization techniques, including spectroscopy, chromatography, and microscopy, were used to reveal their physical and chemical properties like molecular weight, degree of deacetylation, and crystallinity, laying a solid foundation for their wide application, especially for the biomimetic design process. The examination of insect-derived chitin and chitosan extends into a wide realm of biomedical applications, highlighting their unique advantages in wound healing, tissue engineering, drug delivery, and antimicrobial therapies. Their intrinsic biocompatibility and antimicrobial properties position them as promising candidates for innovative solutions in diverse medical interventions.
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Open AccessArticle
A Biologically Inspired Movement Recognition System with Spiking Neural Networks for Ambient Assisted Living Applications
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Athanasios Passias, Karolos-Alexandros Tsakalos, Ioannis Kansizoglou, Archontissa Maria Kanavaki, Athanasios Gkrekidis, Dimitrios Menychtas, Nikolaos Aggelousis, Maria Michalopoulou, Antonios Gasteratos and Georgios Ch. Sirakoulis
Biomimetics 2024, 9(5), 296; https://doi.org/10.3390/biomimetics9050296 - 15 May 2024
Abstract
This study presents a novel solution for ambient assisted living (AAL) applications that utilizes spiking neural networks (SNNs) and reconfigurable neuromorphic processors. As demographic shifts result in an increased need for eldercare, due to a large elderly population that favors independence, there is
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This study presents a novel solution for ambient assisted living (AAL) applications that utilizes spiking neural networks (SNNs) and reconfigurable neuromorphic processors. As demographic shifts result in an increased need for eldercare, due to a large elderly population that favors independence, there is a pressing need for efficient solutions. Traditional deep neural networks (DNNs) are typically energy-intensive and computationally demanding. In contrast, this study turns to SNNs, which are more energy-efficient and mimic biological neural processes, offering a viable alternative to DNNs. We propose asynchronous cellular automaton-based neurons (ACANs), which stand out for their hardware-efficient design and ability to reproduce complex neural behaviors. By utilizing the remote supervised method ( ), this study improves spike train learning efficiency in SNNs. We apply this to movement recognition in an elderly population, using motion capture data. Our results highlight a high classification accuracy of , demonstrating the approach’s efficacy in precise movement activity classification. This method’s significant advantage lies in its potential for real-time, energy-efficient processing in AAL environments. Our findings not only demonstrate SNNs’ superiority over conventional DNNs in computational efficiency but also pave the way for practical neuromorphic computing applications in eldercare.
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(This article belongs to the Special Issue Biologically Inspired Vision and Image Processing)
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Open AccessReview
The Emerging Role of Silk Fibroin for the Development of Novel Drug Delivery Systems
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Mauro Pollini and Federica Paladini
Biomimetics 2024, 9(5), 295; https://doi.org/10.3390/biomimetics9050295 - 15 May 2024
Abstract
In order to reduce the toxicological impact on healthy cells and to improve the therapeutic response, many drug delivery systems have been fabricated and analysed, involving the use of different natural and synthetic materials at macro-, micro- and nanoscales. Among the natural materials
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In order to reduce the toxicological impact on healthy cells and to improve the therapeutic response, many drug delivery systems have been fabricated and analysed, involving the use of different natural and synthetic materials at macro-, micro- and nanoscales. Among the natural materials which have demonstrated a huge potential for the development of effective drug delivery systems, silk fibroin has emerged for its excellent biological properties and for the possibility to be processed in a wide range of forms, which can be compliant with multiple active molecules and pharmaceutical ingredients for the treatment of various diseases. This review aims at presenting silk fibroin as an interesting biopolymer for applications in drug delivery systems, exploring the results obtained in recent works in terms of technological progress and effectiveness in vitro and in vivo.
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(This article belongs to the Special Issue Silk-Based Bioinspired Materials: Design and Applications)
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Clinical Application of Unidirectional Porous Hydroxyapatite to Bone Tumor Surgery and Other Orthopedic Surgery
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Toshiyuki Kunisada, Eiji Nakata, Tomohiro Fujiwara, Toshiaki Hata, Kohei Sato, Haruyoshi Katayama, Ayana Kondo and Toshifumi Ozaki
Biomimetics 2024, 9(5), 294; https://doi.org/10.3390/biomimetics9050294 - 15 May 2024
Abstract
Unidirectional porous hydroxyapatite (UDPHAp) was developed as a remarkable scaffold characterized by a distinct structure with unidirectional pores oriented in the horizontal direction and connected through interposes. We evaluated the radiographic changes, clinical outcomes, and complications following UDPHAp implantation for the treatment of
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Unidirectional porous hydroxyapatite (UDPHAp) was developed as a remarkable scaffold characterized by a distinct structure with unidirectional pores oriented in the horizontal direction and connected through interposes. We evaluated the radiographic changes, clinical outcomes, and complications following UDPHAp implantation for the treatment of bone tumors. Excellent bone formation within and around the implant was observed in all patients treated with intralesional resection and UDPHAp implantation for benign bone tumors. The absorption of UDPHAp and remodeling of the bone marrow space was observed in 45% of the patients at a mean of 17 months postoperatively and was significantly more common in younger patients. Preoperative cortical thinning was completely regenerated in 84% of patients at a mean of 10 months postoperatively. No complications related to the implanted UDPHAp were observed. In a pediatric patient with bone sarcoma, when the defect after fibular resection was filled with UDPHAp implants, radiography showed complete resorption of the implant and clear formation of cortex and marrow in the resected part of the fibula. The patient could walk well without crutches and participate in sports activities. UDPHAp is a useful bone graft substitute for the treatment of benign bone tumors, and the use of this material has a low complication rate. We also review and discuss the potential of UDPHAp as a bone graft substitute in the clinical setting of orthopedic surgery.
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(This article belongs to the Special Issue Advances in Bioceramics for Bone Regeneration)
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Open AccessArticle
Enhancing Energy Harvesting Efficiency of Flapping Wings with Leading-Edge Magnus Effect Cylinder
by
Huaqiang Zhang, Bing Zhu and Weidong Chen
Biomimetics 2024, 9(5), 293; https://doi.org/10.3390/biomimetics9050293 - 13 May 2024
Abstract
According to the Magnus principle, a rotating cylinder experiences a lateral force perpendicular to the incoming flow direction. This phenomenon can be harnessed to boost the lift of an airfoil by positioning a rotating cylinder at the leading edge. In this study, we
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According to the Magnus principle, a rotating cylinder experiences a lateral force perpendicular to the incoming flow direction. This phenomenon can be harnessed to boost the lift of an airfoil by positioning a rotating cylinder at the leading edge. In this study, we simulate flapping-wing motion using the sliding mesh technique in a heaving coordinate system to investigate the energy harvesting capabilities of Magnus effect flapping wings (MEFWs) featuring a leading-edge rotating cylinder. Through analysis of the flow field vortex structure and pressure distribution, we explore how control parameters such as gap width, rotational speed ratio, and phase difference of the leading-edge rotating cylinder impact the energy harvesting characteristics of the flapping wing. The results demonstrate that MEFWs effectively mitigate the formation of leading-edge vortices during wing motion. Consequently, this enhances both lift generation and energy harvesting capability. MEFWs with smaller gap widths are less prone to induce the detachment of leading-edge vortices during motion, ensuring a higher peak lift force and an increase in the energy harvesting efficiency. Moreover, higher rotational speed ratios and phase differences, synchronized with wing motion, can prevent leading-edge vortex generation during wing motion. All three control parameters contribute to enhancing the energy harvesting capability of MEFWs within a certain range. At the examined Reynolds number, the optimal parameter values are determined to be = 0.0005, R = 3, and = 0°.
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(This article belongs to the Special Issue Bio-Inspired Flapping Wing Aerodynamics for Propulsion and Power Generation)
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Intelligent Learning-Based Methods for Determining the Ideal Team Size in Agile Practices
by
Rodrigo Olivares, Rene Noel, Sebastián M. Guzmán, Diego Miranda and Roberto Munoz
Biomimetics 2024, 9(5), 292; https://doi.org/10.3390/biomimetics9050292 - 13 May 2024
Abstract
One of the significant challenges in scaling agile software development is organizing software development teams to ensure effective communication among members while equipping them with the capabilities to deliver business value independently. A formal approach to address this challenge involves modeling it as
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One of the significant challenges in scaling agile software development is organizing software development teams to ensure effective communication among members while equipping them with the capabilities to deliver business value independently. A formal approach to address this challenge involves modeling it as an optimization problem: given a professional staff, how can they be organized to optimize the number of communication channels, considering both intra-team and inter-team channels? In this article, we propose applying a set of bio-inspired algorithms to solve this problem. We introduce an enhancement that incorporates ensemble learning into the resolution process to achieve nearly optimal results. Ensemble learning integrates multiple machine-learning strategies with diverse characteristics to boost optimizer performance. Furthermore, the studied metaheuristics offer an excellent opportunity to explore their linear convergence, contingent on the exploration and exploitation phases. The results produce more precise definitions for team sizes, aligning with industry standards. Our approach demonstrates superior performance compared to the traditional versions of these algorithms.
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(This article belongs to the Special Issue Nature-Inspired Metaheuristic Optimization Algorithms 2024)
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