Biomimetics

3 pages, 181 KiB

Open AccessEditorial

Advances in Biomimetics: Combination of Various Effects at Different Scales

by Stanislav N. Gorb, Giuseppe Carbone, Thomas Speck and Andreas Taubert

Biomimetics 2023, 8(3), 329; https://doi.org/10.3390/biomimetics8030329 - 24 Jul 2023

Cited by 1 | Viewed by 1144

Biomimetics (bionics, bioinspired technology) refers to research on living systems and attempts to transfer their properties to engineering applications [...] Full article

(This article belongs to the Special Issue Advances in Biomimetics: Combination of Various Effects at Different Scales)

22 pages, 2505 KiB

Open AccessReview

A Review of Myoelectric Control for Prosthetic Hand Manipulation

by Ziming Chen, Huasong Min, Dong Wang, Ziwei Xia, Fuchun Sun and Bin Fang

Biomimetics 2023, 8(3), 328; https://doi.org/10.3390/biomimetics8030328 - 24 Jul 2023

Cited by 6 | Viewed by 6262

Abstract

Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, [...] Read more.

Myoelectric control for prosthetic hands is an important topic in the field of rehabilitation. Intuitive and intelligent myoelectric control can help amputees to regain upper limb function. However, current research efforts are primarily focused on developing rich myoelectric classifiers and biomimetic control methods, limiting prosthetic hand manipulation to simple grasping and releasing tasks, while rarely exploring complex daily tasks. In this article, we conduct a systematic review of recent achievements in two areas, namely, intention recognition research and control strategy research. Specifically, we focus on advanced methods for motion intention types, discrete motion classification, continuous motion estimation, unidirectional control, feedback control, and shared control. In addition, based on the above review, we analyze the challenges and opportunities for research directions of functionality-augmented prosthetic hands and user burden reduction, which can help overcome the limitations of current myoelectric control research and provide development prospects for future research. Full article

(This article belongs to the Special Issue Intelligent Human-Robot Interaction)

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13 pages, 3925 KiB

Open AccessArticle

Effect of the Mechanical Properties of Soft Counter-Faces on the Adhesive Capacity of Mushroom-Shaped Biomimetic Microstructures

by May Gonen and Haytam Kasem

Biomimetics 2023, 8(3), 327; https://doi.org/10.3390/biomimetics8030327 - 24 Jul 2023

Viewed by 939

Abstract

The effects of mechanical properties and contact environment conditions on the adhesiveness of the biomimetic adhesive mushroom-shaped micro-structure have been experimentally investigated. The idea is based on the adhesive micro-structures and surfaces inspired by nature after observing the abilities of some animals. Applications [...] Read more.

The effects of mechanical properties and contact environment conditions on the adhesiveness of the biomimetic adhesive mushroom-shaped micro-structure have been experimentally investigated. The idea is based on the adhesive micro-structures and surfaces inspired by nature after observing the abilities of some animals. Applications are proposed in various fields of engineering and technology. However, to enable unconventional uses of these biomimetic adhesion surfaces, such as in the biomedical field, it is necessary to adjust and optimize their tribological properties (friction, adhesion, and peeling strength) in contact with soft substrates that can simulate the mechanical features of biological tissues. Our work explores the effect of the combinations of the various parameters on the strength of adhesion. Under dry contact conditions, soft counter-faces lead to lower adhesion than hard counter-faces, whereas under wet conditions, soft counter-faces lead to higher adhesion than harder counter-faces. Full article

(This article belongs to the Special Issue Biological Attachment Systems and Biomimetics)

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15 pages, 4812 KiB

Open AccessArticle

A Novel Sensor Fusion Approach for Precise Hand Tracking in Virtual Reality-Based Human—Computer Interaction

by Yu Lei, Yi Deng, Lin Dong, Xiaohui Li, Xiangnan Li and Zhi Su

Biomimetics 2023, 8(3), 326; https://doi.org/10.3390/biomimetics8030326 - 22 Jul 2023

Cited by 1 | Viewed by 2146

Abstract

The rapidly evolving field of Virtual Reality (VR)-based Human–Computer Interaction (HCI) presents a significant demand for robust and accurate hand tracking solutions. Current technologies, predominantly based on single-sensing modalities, fall short in providing comprehensive information capture due to susceptibility to occlusions and environmental [...] Read more.

The rapidly evolving field of Virtual Reality (VR)-based Human–Computer Interaction (HCI) presents a significant demand for robust and accurate hand tracking solutions. Current technologies, predominantly based on single-sensing modalities, fall short in providing comprehensive information capture due to susceptibility to occlusions and environmental factors. In this paper, we introduce a novel sensor fusion approach combined with a Long Short-Term Memory (LSTM)-based algorithm for enhanced hand tracking in VR-based HCI. Our system employs six Leap Motion controllers, two RealSense depth cameras, and two Myo armbands to yield a multi-modal data capture. This rich data set is then processed using LSTM, ensuring the accurate real-time tracking of complex hand movements. The proposed system provides a powerful tool for intuitive and immersive interactions in VR environments. Full article

(This article belongs to the Special Issue Computer-Aided Biomimetics)

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27 pages, 13065 KiB

Open AccessArticle

Efficient and Selective Oxygenation of Cycloalkanes and Alkyl Aromatics with Oxygen through Synergistic Catalysis of Bimetallic Active Centers in Two-Dimensional Metal-Organic Frameworks Based on Metalloporphyrins

by Xin-Yan Zhou, Bo Fu, Wen-Dong Jin, Xiong Wang, Ke-Ke Wang, Mei Wang, Yuan-Bin She and Hai-Min Shen

Biomimetics 2023, 8(3), 325; https://doi.org/10.3390/biomimetics8030325 - 21 Jul 2023

Viewed by 1073

Abstract

Confined catalytic realms and synergistic catalysis sites were constructed using bimetallic active centers in two-dimensional metal-organic frameworks (MOFs) to achieve highly selective oxygenation of cycloalkanes and alkyl aromatics with oxygen towards partly oxygenated products. Every necessary characterization was carried out for all the [...] Read more.

Confined catalytic realms and synergistic catalysis sites were constructed using bimetallic active centers in two-dimensional metal-organic frameworks (MOFs) to achieve highly selective oxygenation of cycloalkanes and alkyl aromatics with oxygen towards partly oxygenated products. Every necessary characterization was carried out for all the two-dimensional MOFs. The selective oxygenation of cycloalkanes and alkyl aromatics with oxygen was accomplished with exceptional catalytic performance using two-dimensional MOF Co-TCPPNi as a catalyst. Employing Co-TCPPNi as a catalyst, both the conversion and selectivity were improved for all the hydrocarbons investigated. Less disordered autoxidation at mild conditions, inhibited free-radical diffusion by confined catalytic realms, and synergistic C–H bond oxygenation catalyzed by second metal center Ni employing oxygenation intermediate R–OOH as oxidant were the factors for the satisfying result of Co-TCPPNi as a catalyst. When homogeneous metalloporphyrin T(4-COOCH₃)PPCo was replaced by Co-TCPPNi, the conversion in cyclohexane oxygenation was enhanced from 4.4% to 5.6%, and the selectivity of partly oxygenated products increased from 85.4% to 92.9%. The synergistic catalytic mechanisms were studied using EPR research, and a catalysis model was obtained for the oxygenation of C–H bonds with O₂. This research offered a novel and essential reference for both the efficient and selective oxygenation of C–H bonds and other key chemical reactions involving free radicals. Full article

(This article belongs to the Special Issue The Application of Two-Dimensional Materials in Bioinspired Technologies)

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15 pages, 3781 KiB

Open AccessArticle

Drag Reduction by Fish-Scale Inspired Transverse Asymmetric Triangular Riblets: Modelling, Preliminary Experimental Analysis and Potential for Fouling Control

by Benjamin W. Hamilton, O. Remus Tutunea-Fatan and Evgueni V. Bordatchev

Biomimetics 2023, 8(3), 324; https://doi.org/10.3390/biomimetics8030324 - 21 Jul 2023

Cited by 2 | Viewed by 1390

Abstract

The natural surfaces of many plants and animals provide examples of textures and structures that remain clean despite the presence of environmental fouling contaminants. A biomimetic approach to deciphering the mechanisms used by nature will facilitate the development and application of fouling-resistant surfaces [...] Read more.

The natural surfaces of many plants and animals provide examples of textures and structures that remain clean despite the presence of environmental fouling contaminants. A biomimetic approach to deciphering the mechanisms used by nature will facilitate the development and application of fouling-resistant surfaces to a range of engineering challenges. This study investigated the mechanism underlying the drag reduction phenomenon that was shown to be responsible for fouling resistance for underwater surfaces. For this purpose, a novel fish-scale-inspired microstructure was shown to exhibit a drag reduction effect similar to that of its natural replica. The primary mechanism through which this occurs is a delayed transition to turbulence. To investigate this mechanism, a Large Eddy simulation was performed at several Reynolds numbers (Re). This analysis demonstrated a peak drag reduction performance of 6.7% at Re = 1750. The numerical data were then experimentally validated through pressure drop measurements performed by means of a custom-built micro-channel. In this case, a peak drag reduction of 4.8% was obtained at Re = 1000. These results suggest a relative agreement between the experimental and numerical data. Taken together, this study advocates that, for the analyzed conditions, drag reduction occurs at low Reynolds numbers. Nonetheless, once flow conditions become more turbulent, the decline in drag reduction performance becomes apparent. Full article

(This article belongs to the Section Biomimetic Surfaces and Interfaces)

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15 pages, 2641 KiB

Open AccessArticle

Use of Chitosan from Southern King Crab to Develop Films Functionalized with RGD Peptides for Potential Tissue Engineering Applications

by Juan Carlos Forero, Karina Carvajal, Fanny Guzmán, Cristian Acevedo, Nelson Osses and Paula Santana

Biomimetics 2023, 8(3), 323; https://doi.org/10.3390/biomimetics8030323 - 21 Jul 2023

Cited by 1 | Viewed by 1240

Abstract

Southern King Crab (SKC) represents an important fishery resource that has the potential to be a natural source of chitosan (CS) production. In tissue engineering, CS is very useful to generate biomaterials. However, CS has a lack of signaling molecules that facilitate cell–substrate [...] Read more.

Southern King Crab (SKC) represents an important fishery resource that has the potential to be a natural source of chitosan (CS) production. In tissue engineering, CS is very useful to generate biomaterials. However, CS has a lack of signaling molecules that facilitate cell–substrate interaction. Therefore, RGD (arginine–glycine–aspartic acid) peptides corresponding to the main integrin recognition site in extracellular matrix proteins have been used to improve the CS surface. The aim of this study was to evaluate in vitro cell adhesion and proliferation of CS films synthesized from SKC shell wastes functionalized with RGD peptides. The FTIR spectrum of CS isolated from SKC shells (SKC-CS) was comparable to commercial CS. Thermal properties of films showed similar endothermic peaks at 53.4 and 53.0 °C in commercial CS and SKC-CS, respectively. The purification and molecular masses of the synthesized RGD peptides were confirmed using HPLC and ESI-MS mass spectrometry, respectively. Mouse embryonic fibroblast cells showed higher adhesion on SKC-CS (1% w/v) film when it was functionalized with linear RGD peptides. In contrast, a cyclic RGD peptide showed similar adhesion to control peptide (RDG), but the highest cell proliferation was after 48 h of culture. This study shows that functionalization of SKC-CS films with linear or cyclic RGD peptides are useful to improve effects on cell adhesion or cell proliferation. Furthermore, our work contributes to knowledge of a new source of CS to synthesize constructs for tissue engineering applications. Full article

(This article belongs to the Special Issue Biomimetic Platform for Tissue Regeneration 2.0)

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24 pages, 4441 KiB

Open AccessArticle

Design of Intelligent Neuro-Supervised Networks for Brain Electrical Activity Rhythms of Parkinson’s Disease Model

by Roshana Mukhtar, Chuan-Yu Chang, Muhammad Asif Zahoor Raja and Naveed Ishtiaq Chaudhary

Biomimetics 2023, 8(3), 322; https://doi.org/10.3390/biomimetics8030322 - 21 Jul 2023

Cited by 4 | Viewed by 1072

Abstract

The objective of this paper is to present a novel design of intelligent neuro-supervised networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson’s disease illness (PDI), governed with three differential classes to represent the rhythms of brain electrical [...] Read more.

The objective of this paper is to present a novel design of intelligent neuro-supervised networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson’s disease illness (PDI), governed with three differential classes to represent the rhythms of brain electrical activity measurements at different locations in the cerebral cortex. The proposed INSNs are constructed by exploiting the knacks of multilayer structure neural networks back-propagated with the Levenberg–Marquardt (LM) and Bayesian regularization (BR) optimization approaches. The reference data for the grids of input and the target samples of INSNs were formulated with a reliable numerical solver via the Adams method for sundry scenarios of PDI models by way of variation of sensor locations in order to measure the impact of the rhythms of brain electrical activity. The designed INSNs for both backpropagation procedures were implemented on created datasets segmented arbitrarily into training, testing, and validation samples by optimization of mean squared error based fitness function. Comparison of outcomes on the basis of exhaustive simulations of proposed INSNs via both LM and BR methodologies was conducted with reference solutions of PDI models by means of learning curves on MSE, adaptive control parameters of algorithms, absolute error, histogram error plots, and regression index. The outcomes endorse the efficacy of both INSNs solvers for different scenarios in PDI models, but the accuracy of the BR-based method is relatively superior, albeit at the cost of slightly more computations. Full article

(This article belongs to the Special Issue Biomimicry for Optimization, Control, and Automation)

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24 pages, 975 KiB

Open AccessArticle

A Novel Bio-Inspired Optimization Algorithm Design for Wind Power Engineering Applications Time-Series Forecasting

by Faten Khalid Karim, Doaa Sami Khafaga, Marwa M. Eid, S. K. Towfek and Hend K. Alkahtani

Biomimetics 2023, 8(3), 321; https://doi.org/10.3390/biomimetics8030321 - 20 Jul 2023

Cited by 5 | Viewed by 2067

Abstract

Wind patterns can change due to climate change, causing more storms, hurricanes, and quiet spells. These changes can dramatically affect wind power system performance and predictability. Researchers and practitioners are creating more advanced wind power forecasting algorithms that combine more parameters and data [...] Read more.

Wind patterns can change due to climate change, causing more storms, hurricanes, and quiet spells. These changes can dramatically affect wind power system performance and predictability. Researchers and practitioners are creating more advanced wind power forecasting algorithms that combine more parameters and data sources. Advanced numerical weather prediction models, machine learning techniques, and real-time meteorological sensor and satellite data are used. This paper proposes a Recurrent Neural Network (RNN) forecasting model incorporating a Dynamic Fitness Al-Biruni Earth Radius (DFBER) algorithm to predict wind power data patterns. The performance of this model is compared with several other popular models, including BER, Jaya Algorithm (JAYA), Fire Hawk Optimizer (FHO), Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Particle Swarm Optimization (PSO)-based models. The evaluation is done using various metrics such as relative root mean squared error (RRMSE), Nash Sutcliffe Efficiency (NSE), mean absolute error (MAE), mean bias error (MBE), Pearson’s correlation coefficient (r), coefficient of determination (R2), and determination agreement (WI). According to the evaluation metrics and analysis presented in the study, the proposed RNN-DFBER-based model outperforms the other models considered. This suggests that the RNN model, combined with the DFBER algorithm, predicts wind power data patterns more effectively than the alternative models. To support the findings, visualizations are provided to demonstrate the effectiveness of the RNN-DFBER model. Additionally, statistical analyses, such as the ANOVA test and the Wilcoxon Signed-Rank test, are conducted to assess the significance and reliability of the results. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)

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13 pages, 3163 KiB

Open AccessArticle

STDP-Driven Rewiring in Spiking Neural Networks under Stimulus-Induced and Spontaneous Activity

by Sergey A. Lobov, Ekaterina S. Berdnikova, Alexey I. Zharinov, Dmitry P. Kurganov and Victor B. Kazantsev

Biomimetics 2023, 8(3), 320; https://doi.org/10.3390/biomimetics8030320 - 20 Jul 2023

Viewed by 1037

Abstract

Mathematical and computer simulation of learning in living neural networks have typically focused on changes in the efficiency of synaptic connections represented by synaptic weights in the models. Synaptic plasticity is believed to be the cellular basis for learning and memory. In spiking [...] Read more.

Mathematical and computer simulation of learning in living neural networks have typically focused on changes in the efficiency of synaptic connections represented by synaptic weights in the models. Synaptic plasticity is believed to be the cellular basis for learning and memory. In spiking neural networks composed of dynamical spiking units, a biologically relevant learning rule is based on the so-called spike-timing-dependent plasticity or STDP. However, experimental data suggest that synaptic plasticity is only a part of brain circuit plasticity, which also includes homeostatic and structural plasticity. A model of structural plasticity proposed in this study is based on the activity-dependent appearance and disappearance of synaptic connections. The results of the research indicate that such adaptive rewiring enables the consolidation of the effects of STDP in response to a local external stimulation of a neural network. Subsequently, a vector field approach is used to demonstrate the successive “recording” of spike paths in both functional connectome and synaptic connectome, and finally in the anatomical connectome of the network. Moreover, the findings suggest that the adaptive rewiring could stabilize network dynamics over time in the context of activity patterns’ reproducibility. A universal measure of such reproducibility introduced in this article is based on similarity between time-consequent patterns of the special vector fields characterizing both functional and anatomical connectomes. Full article

(This article belongs to the Special Issue Bio-Inspired Neural Networks)

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19 pages, 2356 KiB

Open AccessReview

Computational Fluid Dynamics Analysis in Biomimetics Applications: A Review from Aerospace Engineering Perspective

by Ernnie Illyani Basri, Adi Azriff Basri and Kamarul Arifin Ahmad

Biomimetics 2023, 8(3), 319; https://doi.org/10.3390/biomimetics8030319 - 20 Jul 2023

Cited by 4 | Viewed by 2446

Abstract

In many modern engineering fields, computational fluid dynamics (CFD) has been adopted as a methodology to solve complex problems. CFD is becoming a key component in developing updated designs and optimization through computational simulations, resulting in lower operating costs and enhanced efficiency. Even [...] Read more.

In many modern engineering fields, computational fluid dynamics (CFD) has been adopted as a methodology to solve complex problems. CFD is becoming a key component in developing updated designs and optimization through computational simulations, resulting in lower operating costs and enhanced efficiency. Even though the biomimetics application is complex in adapting nature to inspire new capabilities for exciting future technologies, the recent CFD in biomimetics is more accessible and practicable due to the availability of high-performance hardware and software with advances in computer sciences. Many simulations and experimental results have been used to study the analyses in biomimetics applications, particularly those related to aerospace engineering. There are numerous examples of biomimetic successes that involve making simple copies, such as the use of fins for swimming or the mastery of flying, which became possible only after the principles of aerodynamics were better understood. Therefore, this review discusses the essential methodology of CFD as a reliable tool for researchers in understanding the technology inspired by nature and an outlook for potential development through simulations. CFD plays a major role as decision support prior to undertaking a real commitment to execute any design inspired by nature and providing the direction to develop new capabilities of technologies. Full article

(This article belongs to the Special Issue Bio-Inspired Flight Systems and Bionic Aerodynamics 2.0)

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21 pages, 24073 KiB

Open AccessReview

Underwater Undulating Propulsion Biomimetic Robots: A Review

by Gongbo Li, Guijie Liu, Dingxin Leng, Xin Fang, Guanghao Li and Wenqian Wang

Biomimetics 2023, 8(3), 318; https://doi.org/10.3390/biomimetics8030318 - 19 Jul 2023

Cited by 9 | Viewed by 3321

Abstract

The traditional propeller-based propulsion of underwater robots is inefficient and poorly adapted to practice. By contrast, underwater biomimetic robots show better stability and maneuverability in harsh marine environments. This is particularly true of undulating propulsion biomimetic robots. This paper classifies the existing underwater [...] Read more.

The traditional propeller-based propulsion of underwater robots is inefficient and poorly adapted to practice. By contrast, underwater biomimetic robots show better stability and maneuverability in harsh marine environments. This is particularly true of undulating propulsion biomimetic robots. This paper classifies the existing underwater biomimetic robots and outlines their main contributions to the field. The propulsion mechanisms of underwater biomimetic undulating robots are summarized based on theoretical, numerical and experimental studies. Future perspectives on underwater biomimetic undulating robots are also presented, filling the gaps in the existing literature. Full article

(This article belongs to the Special Issue Bio-Inspired Underwater Robot)

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14 pages, 4920 KiB

Open AccessArticle

Biomimetic Design of a Tendon-Driven Myoelectric Soft Hand Exoskeleton for Upper-Limb Rehabilitation

by Rodrigo C. Silva, Bruno. G. Lourenço, Pedro H. F. Ulhoa, Eduardo A. F. Dias, Fransergio L. da Cunha, Cristiane P. Tonetto, Luis G. Villani, Claysson B. S. Vimieiro, Guilherme A. Lepski, Marina Monjardim and Rafhael M. Andrade

Biomimetics 2023, 8(3), 317; https://doi.org/10.3390/biomimetics8030317 - 19 Jul 2023

Cited by 2 | Viewed by 1917

Abstract

Degenerative diseases and injuries that compromise hand movement reduce individual autonomy and tend to cause financial and psychological problems to their family nucleus. To mitigate these limitations, over the past decade, hand exoskeletons have been designed to rehabilitate or enhance impaired hand movements. [...] Read more.

Degenerative diseases and injuries that compromise hand movement reduce individual autonomy and tend to cause financial and psychological problems to their family nucleus. To mitigate these limitations, over the past decade, hand exoskeletons have been designed to rehabilitate or enhance impaired hand movements. Although promising, these devices still have limitations, such as weight and cost. Moreover, the movements performed are not kinematically compatible with the joints, thereby reducing the achievements of the rehabilitation process. This article presents the biomimetic design of a soft hand exoskeleton actuated using artificial tendons designed to achieve low weight, volume, and cost, and to improve kinematic compatibility with the joints, comfort, and the sensitivity of the hand by allowing direct contact between the hand palm and objects. We employed two twisted string actuators and Bowden cables to move the artificial tendons and perform the grasping and opening of the hand. With this configuration, the heavy part of the system was reallocated to a test bench, allowing for a lightweight set of just 232 g attached to the arm. The system was triggered by the myoelectric signals of the biceps captured from the user’s skin to encourage the active participation of the user in the process. The device was evaluated by five healthy subjects who were asked to simulate a paralyzed hand, and manipulate different types of objects and perform grip strength. The results showed that the system was able to identify the intention of movement of the user with an accuracy of 90%, and the orthosis was able to enhance the ability of handling objects with gripping force up to 1.86 kgf. Full article

(This article belongs to the Special Issue Bionic Technology – Robotic Exoskeletons and Prostheses)

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15 pages, 5519 KiB

Open AccessArticle

Design of a Multi-Mode Mechanical Finger Based on Linkage and Tendon Fusion Transmission

by Yi Zhang, Qian Zhao, Hua Deng and Xiaolei Xu

Biomimetics 2023, 8(3), 316; https://doi.org/10.3390/biomimetics8030316 - 17 Jul 2023

Viewed by 1192

Abstract

Today, most humanoid mechanical fingers use an underactuated mechanism driven by linkages or tendons, with only a single and fixed grasping trajectory. This paper proposes a new multi-mode humanoid finger mechanism based on linkage and tendon fusion transmission, which is embedded with an [...] Read more.

Today, most humanoid mechanical fingers use an underactuated mechanism driven by linkages or tendons, with only a single and fixed grasping trajectory. This paper proposes a new multi-mode humanoid finger mechanism based on linkage and tendon fusion transmission, which is embedded with an adjustable-length tendon mechanism to achieve three types of grasping mode. The structural parameters of the mechanism are optimized according to the kinematic and static models. Furthermore, a discussion was conducted on how to set the speed ratio of the linkage driving motor and the tendon driving motor to adjust the length and tension of the tendon, in order to achieve the switching of the shape-adaptive, coupled-adaptive, and variable coupling-adaptive grasping modes. Finally, the multi-mode functionality of the proposed finger mechanism was verified through multiple grasping experiments. Full article

(This article belongs to the Special Issue Bionic Robot Hand: Dexterous Manipulation and Robust Grasping)

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13 pages, 4468 KiB

Open AccessArticle

Preservation of Mechanical and Morphological Properties of Porcine Cardiac Outflow Vessels after Decellularization and Wet Storage

by David Sergeevichev, Maria Vasiliyeva, Elena Kuznetsova and Boris Chelobanov

Biomimetics 2023, 8(3), 315; https://doi.org/10.3390/biomimetics8030315 - 17 Jul 2023

Viewed by 1154

Abstract

Widely used storage methods, including freezing or chemical modification, preserve the sterility of biological tissues but degrade the mechanical properties of materials used to make heart valve prostheses. Therefore, wet storage remains the most optimal option for biomaterials. Three biocidal solutions (an antibiotic [...] Read more.

Widely used storage methods, including freezing or chemical modification, preserve the sterility of biological tissues but degrade the mechanical properties of materials used to make heart valve prostheses. Therefore, wet storage remains the most optimal option for biomaterials. Three biocidal solutions (an antibiotic mixture, an octanediol-phenoxyethanol complex solution, and a glycerol-ethanol mixture) were studied for the storage of native and decellularized porcine aorta and pulmonary trunk. Subsequent mechanical testing and microstructural analysis showed a slight increase in the tensile strength of native and decellularized aorta in the longitudinal direction. Pulmonary trunk elongation increased 1.3–1.6 times in the longitudinal direction after decellularization only. The microstructures of the tested specimens showed no differences before and after wet storage. Thus, two months of wet storage of native and decellularized porcine aorta and pulmonary trunks does not significantly affect the strength and elastic properties of the material. The wet storage protocol using alcohol solutions of glycerol or octanediol-phenoxyethanol mixture may be intended for further fabrication of extracellular matrix for tissue-engineered biological heart valve prostheses. Full article

(This article belongs to the Special Issue The Mechanical Properties of Biomaterials)

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27 pages, 10231 KiB

Open AccessArticle

Design and Simulation of a Hierarchical Parallel Distributed Processing Model for Orientation Selection Based on Primary Visual Cortex

by Hui Wei, Jingyong Ye, Jiaqi Li and Yun Wang

Biomimetics 2023, 8(3), 314; https://doi.org/10.3390/biomimetics8030314 - 16 Jul 2023

Viewed by 1055

Abstract

The study of the human visual system not only helps to understand the mechanism of the visual system but also helps to develop visual aid systems to help the visually impaired. As the systematic study of neural signal processing mechanisms in early biological [...] Read more.

The study of the human visual system not only helps to understand the mechanism of the visual system but also helps to develop visual aid systems to help the visually impaired. As the systematic study of neural signal processing mechanisms in early biological vision continues, the hierarchical structure of the visual system is gradually being dissected, bringing the possibility of building brain-like computational models from a bionic perspective. In this paper, we follow the objective facts of neurobiology and propose a parallel distributed processing computational model of primary visual cortex orientation selection with reference to the complex process of visual signal processing and transmission between the retina to the primary visual cortex, the hierarchical receptive field structure between cells in each layer, and the very fine-grained parallel distributed characteristics of cortical visual computation, which allow for high speed and efficiency. We approach the design from a brain-like chip perspective, map our network model on the field programmable gate array (FPGA), and perform simulation experiments. The results verify the possibility of implementing our proposed model with programmable devices, which can be applied to small wearable devices with low power consumption and low latency. Full article

(This article belongs to the Section Locomotion and Bioinspired Robotics)

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21 pages, 1783 KiB

Open AccessArticle

Diagnosis of Monkeypox Disease Using Transfer Learning and Binary Advanced Dipper Throated Optimization Algorithm

by Amal H. Alharbi, S. K. Towfek, Abdelaziz A. Abdelhamid, Abdelhameed Ibrahim, Marwa M. Eid, Doaa Sami Khafaga, Nima Khodadadi, Laith Abualigah and Mohamed Saber

Biomimetics 2023, 8(3), 313; https://doi.org/10.3390/biomimetics8030313 - 16 Jul 2023

Cited by 10 | Viewed by 1547

Abstract

The virus that causes monkeypox has been observed in Africa for several years, and it has been linked to the development of skin lesions. Public panic and anxiety have resulted from the deadly repercussions of virus infections following the COVID-19 pandemic. Rapid detection [...] Read more.

The virus that causes monkeypox has been observed in Africa for several years, and it has been linked to the development of skin lesions. Public panic and anxiety have resulted from the deadly repercussions of virus infections following the COVID-19 pandemic. Rapid detection approaches are crucial since COVID-19 has reached a pandemic level. This study’s overarching goal is to use metaheuristic optimization to boost the performance of feature selection and classification methods to identify skin lesions as indicators of monkeypox in the event of a pandemic. Deep learning and transfer learning approaches are used to extract the necessary features. The GoogLeNet network is the deep learning framework used for feature extraction. In addition, a binary implementation of the dipper throated optimization (DTO) algorithm is used for feature selection. The decision tree classifier is then used to label the selected set of features. The decision tree classifier is optimized using the continuous version of the DTO algorithm to improve the classification accuracy. Various evaluation methods are used to compare and contrast the proposed approach and the other competing methods using the following metrics: accuracy, sensitivity, specificity, p-Value, N-Value, and F1-score. Through feature selection and a decision tree classifier, the following results are achieved using the proposed approach; F1-score of 0.92, sensitivity of 0.95, specificity of 0.61, p-Value of 0.89, and N-Value of 0.79. The overall accuracy of the proposed methodology after optimizing the parameters of the decision tree classifier is 94.35%. Furthermore, the analysis of variation (ANOVA) and Wilcoxon signed rank test have been applied to the results to investigate the statistical distinction between the proposed methodology and the alternatives. This comparison verified the uniqueness and importance of the proposed approach to Monkeypox case detection. Full article

(This article belongs to the Special Issue Nature-Inspired Computer Algorithms)

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16 pages, 2054 KiB

Open AccessArticle

Deep Learning Combinatorial Models for Intelligent Supply Chain Demand Forecasting

by Xiaoya Ma, Mengxiu Li, Jin Tong and Xiaying Feng

Biomimetics 2023, 8(3), 312; https://doi.org/10.3390/biomimetics8030312 - 15 Jul 2023

Cited by 3 | Viewed by 1683

Abstract

Low-carbon and environmentally friendly living boosted the market demand for new energy vehicles and promoted the development of the new energy vehicle industry. Accurate demand forecasting can provide an important decision-making basis for new energy vehicle enterprises, which is beneficial to the development [...] Read more.

Low-carbon and environmentally friendly living boosted the market demand for new energy vehicles and promoted the development of the new energy vehicle industry. Accurate demand forecasting can provide an important decision-making basis for new energy vehicle enterprises, which is beneficial to the development of new energy vehicles. From the perspective of an intelligent supply chain, this study explored the demand forecasting of new energy vehicles, and proposed an innovative SARIMA-LSTM-BP combination model for prediction modeling. The data showed that the RMSE, MSE, and MAE values of the SARIMA-LSTM-BP combination model were 2.757, 7.603, and, 1.912, respectively, all of which are lower values than those of the single models. This study therefore, indicated that, compared with traditional econometric forecasting models and deep learning forecasting models, such as the random forest, support vector regression (SVR), long short-term memory (LSTM), and back propagation neural network (BP) models, the SARIMA-LSTM-BP combination model performed outstandingly with higher accuracy and better forecasting performance. Full article

(This article belongs to the Special Issue Biomimicry for Optimization, Control, and Automation)

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19 pages, 12296 KiB

Open AccessArticle

A Comparative and Collaborative Study of the Hydrodynamics of Two Swimming Modes Applicable to Dolphins

by Dan Xia, Zhihan Li, Ming Lei, Han Yan and Zilong Zhou

Biomimetics 2023, 8(3), 311; https://doi.org/10.3390/biomimetics8030311 - 14 Jul 2023

Cited by 3 | Viewed by 1170

Abstract

This paper presents a hydrodynamics study that examines the comparison and collaboration of two swimming modes relevant to the universality of dolphins. This study utilizes a three-dimensional virtual swimmer model resembling a dolphin, which comprises a body and/or caudal fin (BCF) module, as [...] Read more.

This paper presents a hydrodynamics study that examines the comparison and collaboration of two swimming modes relevant to the universality of dolphins. This study utilizes a three-dimensional virtual swimmer model resembling a dolphin, which comprises a body and/or caudal fin (BCF) module, as well as a medium and/or paired fin (MPF) module, each equipped with predetermined kinematics. The manipulation of the dolphin to simulate various swimming modes is achieved through the application of overlapping grids in conjunction with the parallel hole cutting technique. The findings demonstrate that the swimming velocity and thrust attained through the single BCF mode consistently surpass those achieved through the single MPF mode and collaborative mode. Interestingly, the involvement of the MPF mode does not necessarily contribute to performance enhancement. Nevertheless, it is encouraging to note that adjusting the phase difference between the two modes can partially mitigate the limitations associated with the MPF mode. To further investigate the potential advantages of dual-mode collaboration, we conducted experiments by increasing the MPF frequency while keeping the BCF frequency constant, thus introducing the concept of frequency ratio (β). In comparison to the single BCF mode, the collaborative mode with a high β exhibits superior swimming velocity and thrust. Although its efficiency experiences a slight decrease, it tends to stabilize. The corresponding flow structure indirectly verifies the favorable impact of collaboration. Full article

(This article belongs to the Special Issue Bio-Inspired Underwater Robot)

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19 pages, 3415 KiB

Open AccessArticle

Binary Sand Cat Swarm Optimization Algorithm for Wrapper Feature Selection on Biological Data

by Amir Seyyedabbasi

Biomimetics 2023, 8(3), 310; https://doi.org/10.3390/biomimetics8030310 - 14 Jul 2023

Cited by 13 | Viewed by 1544

Abstract

In large datasets, irrelevant, redundant, and noisy attributes are often present. These attributes can have a negative impact on the classification model accuracy. Therefore, feature selection is an effective pre-processing step intended to enhance the classification performance by choosing a small number of [...] Read more.

In large datasets, irrelevant, redundant, and noisy attributes are often present. These attributes can have a negative impact on the classification model accuracy. Therefore, feature selection is an effective pre-processing step intended to enhance the classification performance by choosing a small number of relevant or significant features. It is important to note that due to the NP-hard characteristics of feature selection, the search agent can become trapped in the local optima, which is extremely costly in terms of time and complexity. To solve these problems, an efficient and effective global search method is needed. Sand cat swarm optimization (SCSO) is a newly introduced metaheuristic algorithm that solves global optimization algorithms. Nevertheless, the SCSO algorithm is recommended for continuous problems. bSCSO is a binary version of the SCSO algorithm proposed here for the analysis and solution of discrete problems such as wrapper feature selection in biological data. It was evaluated on ten well-known biological datasets to determine the effectiveness of the bSCSO algorithm. Moreover, the proposed algorithm was compared to four recent binary optimization algorithms to determine which algorithm had better efficiency. A number of findings demonstrated the superiority of the proposed approach both in terms of high prediction accuracy and small feature sizes. Full article

(This article belongs to the Special Issue Nature-Inspired Computer Algorithms)

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15 pages, 3724 KiB

Open AccessArticle

Detection and Dispersion Analysis of Water Globules in Oil Samples Using Artificial Intelligence Algorithms

by Alexey N. Beskopylny, Anton Chepurnenko, Besarion Meskhi, Sergey A. Stel’makh, Evgenii M. Shcherban’, Irina Razveeva, Alexey Kozhakin, Kirill Zavolokin and Andrei A. Krasnov

Biomimetics 2023, 8(3), 309; https://doi.org/10.3390/biomimetics8030309 - 13 Jul 2023

Cited by 1 | Viewed by 1251

Abstract

Fluid particle detection technology is of great importance in the oil and gas industry for improving oil-refining techniques and in evaluating the quality of refining equipment. The article discusses the process of creating a computer vision algorithm that allows the user to detect [...] Read more.

Fluid particle detection technology is of great importance in the oil and gas industry for improving oil-refining techniques and in evaluating the quality of refining equipment. The article discusses the process of creating a computer vision algorithm that allows the user to detect water globules in oil samples and analyze their sizes. The process of developing an algorithm based on the convolutional neural network (CNN) YOLOv4 is presented. For this study, our own empirical base was proposed, which comprised microphotographs of samples of raw materials and water–oil emulsions taken at various points and in different operating modes of an oil refinery. The number of images for training the neural network algorithm was increased by applying the authors’ augmentation algorithm. The developed program makes it possible to detect particles in a fluid medium with the level of accuracy required by a researcher, which can be controlled at the stage of training the CNN. Based on the results of processing the output data from the algorithm, a dispersion analysis of localized water globules was carried out, supplemented with a frequency diagram describing the ratio of the size and number of particles found. The evaluation of the quality of the results of the work of the intelligent algorithm in comparison with the manual method on the verification microphotographs and the comparison of two empirical distributions allow us to conclude that the model based on the CNN can be verified and accepted for use in the search for particles in a fluid medium. The accuracy of the model was AP@50 = 89% and AP@75 = 78%. Full article

(This article belongs to the Special Issue Neuromorphic Engineering: Biomimicry from the Brain)

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17 pages, 17261 KiB

Open AccessArticle

Biomimetics Design of Tooth Root Zone at Cylindrical Gears Profile

by Ivana Atanasovska, Dejan Momcilovic, Tatjana Lazovic, Aleksandar Marinkovic and Natasa Soldat

Biomimetics 2023, 8(3), 308; https://doi.org/10.3390/biomimetics8030308 - 12 Jul 2023

Viewed by 1651

Abstract

During the last few decades, the requirements for modern machine elements in terms of size reduction, increasing the energy efficiency, and a higher load capacity of standard and non-standard gears have been very prevalent issues. Within these demands, the main goals are the [...] Read more.

During the last few decades, the requirements for modern machine elements in terms of size reduction, increasing the energy efficiency, and a higher load capacity of standard and non-standard gears have been very prevalent issues. Within these demands, the main goals are the optimization of the gears’ tooth profiles, as well as the investigation of new tooth profile designs. The presented design idea is based on the optimal solutions inspired by nature. Special attention is paid to the new design of the tooth root zones of spur gears in order to decrease the stress concentration values and increase the tooth root fatigue resistance. The finite element method is used for stress and strain state calculations, and the particular gear pair is modeled and optimized for these purposes. For tooth root strength analysis, the estimations are based on the theory of critical distances and the stress gradients obtained through finite element analysis. The obtained stress gradients have shown important improvements in the stress distribution in the transition zone optimized by biomimetics. An analysis of the material variation influence is also performed. Based on the investigations of a particular gear pair, a significant stress reduction of about 7% for steel gears and about 10.3% for cast iron gears is obtained for tooth roots optimized by bio-inspired design. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)

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16 pages, 10752 KiB

Open AccessArticle

An AAM-Based Identification Method for Ear Acupoint Area

by Qingfeng Li, Yuhan Chen, Yijie Pang, Lei Kou, Dongxin Lu and Wende Ke

Biomimetics 2023, 8(3), 307; https://doi.org/10.3390/biomimetics8030307 - 12 Jul 2023

Viewed by 1126

Abstract

Ear image segmentation and identification is for the “observation” of TCM (traditional Chinese medicine), because disease diagnoses and treatment are achieved through the massaging of or pressing on some corresponding ear acupoints. With the image processing of ear image positioning and regional segmentation, [...] Read more.

Ear image segmentation and identification is for the “observation” of TCM (traditional Chinese medicine), because disease diagnoses and treatment are achieved through the massaging of or pressing on some corresponding ear acupoints. With the image processing of ear image positioning and regional segmentation, the diagnosis and treatment of intelligent traditional Chinese medicine ear acupoints is improved. In order to popularize ear acupoint therapy, image processing technology has been adopted to detect the ear acupoint areas and help to gradually replace well-trained, experienced doctors. Due to the small area of the ear and the numerous ear acupoints, it is difficult to locate these acupoints based on traditional image recognition methods. An AAM (active appearance model)-based method for ear acupoint segmentation was proposed. The segmentation was illustrated as 91 feature points of a human ear image. In this process, the recognition effects of the ear acupoints, including the helix, antihelix, cymba conchae, cavum conchae, fossae helicis, fossae triangularis auriculae, tragus, antitragus, and earlobe, were divided precisely. Besides these, specially appointed acupoints or acupoint areas could be prominent in ear images. This method made it possible to partition and recognize the ear’s acupoints through computer image processing, and maybe own the same abilities as experienced doctors for observation. The method was proved to be effective and accurate in experiments and can be used for the intelligent diagnosis of diseases. Full article

(This article belongs to the Special Issue Biomimetic and Bioinspired Computer Vision and Image Processing)

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23 pages, 4049 KiB

Open AccessArticle

Towards an Optimal KELM Using the PSO-BOA Optimization Strategy with Applications in Data Classification

by Yinggao Yue, Li Cao, Haishao Chen, Yaodan Chen and Zhonggen Su

Biomimetics 2023, 8(3), 306; https://doi.org/10.3390/biomimetics8030306 - 12 Jul 2023

Cited by 5 | Viewed by 988

Abstract

The features of the kernel extreme learning machine—efficient processing, improved performance, and less human parameter setting—have allowed it to be effectively used to batch multi-label classification tasks. These classic classification algorithms must at present contend with accuracy and space–time issues as a result [...] Read more.

The features of the kernel extreme learning machine—efficient processing, improved performance, and less human parameter setting—have allowed it to be effectively used to batch multi-label classification tasks. These classic classification algorithms must at present contend with accuracy and space–time issues as a result of the vast and quick, multi-label, and concept drift features of the developing data streams in the practical application sector. The KELM training procedure still has a difficulty in that it has to be repeated numerous times independently in order to maximize the model’s generalization performance or the number of nodes in the hidden layer. In this paper, a kernel extreme learning machine multi-label data classification method based on the butterfly algorithm optimized by particle swarm optimization is proposed. The proposed algorithm, which fully accounts for the optimization of the model generalization ability and the number of hidden layer nodes, can train multiple KELM hidden layer networks at once while maintaining the algorithm’s current time complexity and avoiding a significant number of repeated calculations. The simulation results demonstrate that, in comparison to the PSO-KELM, BBA-KELM, and BOA-KELM algorithms, the PSOBOA-KELM algorithm proposed in this paper can more effectively search the kernel extreme learning machine parameters and more effectively balance the global and local performance, resulting in a KELM prediction model with a higher prediction accuracy. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)

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33 pages, 23533 KiB

Open AccessArticle

Reptile Search Algorithm Considering Different Flight Heights to Solve Engineering Optimization Design Problems

by Liguo Yao, Guanghui Li, Panliang Yuan, Jun Yang, Dongbin Tian and Taihua Zhang

Biomimetics 2023, 8(3), 305; https://doi.org/10.3390/biomimetics8030305 - 11 Jul 2023

Cited by 2 | Viewed by 1402

Abstract

The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitations of natural laws, it is [...] Read more.

The reptile search algorithm is an effective optimization method based on the natural laws of the biological world. By restoring and simulating the hunting process of reptiles, good optimization results can be achieved. However, due to the limitations of natural laws, it is easy to fall into local optima during the exploration phase. Inspired by the different search fields of biological organisms with varying flight heights, this paper proposes a reptile search algorithm considering different flight heights. In the exploration phase, introducing the different flight altitude abilities of two animals, the northern goshawk and the African vulture, enables reptiles to have better search horizons, improve their global search ability, and reduce the probability of falling into local optima during the exploration phase. A novel dynamic factor (DF) is proposed in the exploitation phase to improve the algorithm’s convergence speed and optimization accuracy. To verify the effectiveness of the proposed algorithm, the test results were compared with ten state-of-the-art (SOTA) algorithms on thirty-three famous test functions. The experimental results show that the proposed algorithm has good performance. In addition, the proposed algorithm and ten SOTA algorithms were applied to three micromachine practical engineering problems, and the experimental results show that the proposed algorithm has good problem-solving ability. Full article

(This article belongs to the Special Issue Bio-Inspired Optimization Algorithms and Designs for Engineering Applications)

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15 pages, 2235 KiB

Open AccessArticle

Biomimetics for Sustainable Developments—A Literature Overview of Trends

by Anne-Sophie Jatsch, Shoshanah Jacobs, Kirsten Wommer and Kristina Wanieck

Biomimetics 2023, 8(3), 304; https://doi.org/10.3390/biomimetics8030304 - 11 Jul 2023

Cited by 1 | Viewed by 2032

Abstract

Biomimetics holds the promise to contribute to sustainability in several ways. However, it remains unclear how the two broad concepts and research fields are connected. This article presents a literature overview on biomimetic sustainable developments and research. It is shown that there is [...] Read more.

Biomimetics holds the promise to contribute to sustainability in several ways. However, it remains unclear how the two broad concepts and research fields are connected. This article presents a literature overview on biomimetic sustainable developments and research. It is shown that there is an increasing trend in publications dealing with various topics and that the research takes place worldwide. The biological models studied in biomimetic sustainable developments are mostly sub-elements of biological systems on a molecular level and lead to eco-friendly, resource and energy-efficient applications. This article indicates that biomimetics is further integrating sustainability to contribute to real problems in this context. Full article

(This article belongs to the Section Biomimetic Design, Constructions and Devices)

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24 pages, 46546 KiB

Open AccessEditor’s ChoiceArticle

Biomimetics in Botanical Gardens—Educational Trails and Guided Tours

by Olga Speck and Thomas Speck

Biomimetics 2023, 8(3), 303; https://doi.org/10.3390/biomimetics8030303 - 11 Jul 2023

Viewed by 1883

Abstract

The first botanical gardens in Europe were established for the study of medicinal, poisonous, and herbal plants by students of medicine or pharmacy at universities. As the natural sciences became increasingly important in the 19th Century, botanical gardens additionally took on the role [...] Read more.

The first botanical gardens in Europe were established for the study of medicinal, poisonous, and herbal plants by students of medicine or pharmacy at universities. As the natural sciences became increasingly important in the 19th Century, botanical gardens additionally took on the role of public educational institutions. Since then, learning from living nature with the aim of developing technical applications, namely biomimetics, has played a special role in botanical gardens. Sir Joseph Paxton designed rainwater drainage channels in the roof of the Crystal Palace for the London World’s Fair in 1881, having been inspired by the South American giant water lily (Victoria amazonica). The development of the Lotus-Effect^® at the Botanical Garden Bonn was inspired by the self-cleaning leaf surfaces of the sacred lotus (Nelumbo nucifera). At the Botanic Garden Freiburg, a self-sealing foam coating for pneumatic systems was developed based on the self-sealing of the liana stems of the genus Aristolochia. Currently, botanical gardens are both research institutions and places of lifelong learning. Numerous botanical gardens provide biomimetics trails with information panels at each station for self-study and guided biomimetics tours with simple experiments to demonstrate the functional principles transferred from the biological model to the technical application. We present eight information panels suitable for setting up education about biomimetics and simple experiments to support guided garden tours about biomimetics. Full article

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14 pages, 2695 KiB

Open AccessArticle

New N-Methylimidazole-Functionalized Chitosan Derivatives: Hemocompatibility and Antibacterial Properties

by Natalia Drozd, Alexey Lunkov, Balzhima Shagdarova, Alla Il’ina and Valery Varlamov

Biomimetics 2023, 8(3), 302; https://doi.org/10.3390/biomimetics8030302 - 11 Jul 2023

Cited by 2 | Viewed by 1147

Abstract

Novel imidazole derivatives of the low molecular weight chitosan N-(2-hydroxypropyl)-1H-1,2,3-triazol-4-yl)methyl)-1-methyl-1H-imidazol-3-ium chitosan chloride (NMIC) were synthesized using copper-catalyzed azide–alkyne cycloaddition (CuAAC). The degrees of substitution (DSs) for the new derivatives were 18–76%. All chitosan derivatives (2000 µg/mL) were completely soluble in water. The antimicrobial [...] Read more.

Novel imidazole derivatives of the low molecular weight chitosan N-(2-hydroxypropyl)-1H-1,2,3-triazol-4-yl)methyl)-1-methyl-1H-imidazol-3-ium chitosan chloride (NMIC) were synthesized using copper-catalyzed azide–alkyne cycloaddition (CuAAC). The degrees of substitution (DSs) for the new derivatives were 18–76%. All chitosan derivatives (2000 µg/mL) were completely soluble in water. The antimicrobial activity of the new compounds against E. coli and S. epidermidis was studied. The effect of chitosan derivatives on blood and its components was studied. NMIC samples (DS 34–76%) at a concentration <10 μg/mL had no effect on blood and plasma coagulation. Chitosan derivatives (DS 18–76%) at concentrations of ≥83 μg/mL in blood and ≥116.3 μg/mL in plasma resulted in a prolongation of the clotting time of blood and plasma, positively related to the DS. At concentrations up to 9.1 μg/mL, NMIC did not independently provoke platelet aggregation. The degree of erythrocyte hemolysis upon contact with NMIC samples (2.5–2500 μg/mL) was below 4%. The inhibition of blood/plasma coagulation indicates the promising use of the studied samples to modify the surface of medical materials in order to achieve thromboresistance. Full article

(This article belongs to the Special Issue Blood-Compatible Materials: Preparation, Modification and Functionalization)

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18 pages, 11568 KiB

Open AccessArticle

Multi-Criterion Sampling Matting Algorithm via Gaussian Process

by Yuan Yang, Hongshan Gou, Mian Tan, Fujian Feng, Yihui Liang, Yi Xiang, Lin Wang and Han Huang

Biomimetics 2023, 8(3), 301; https://doi.org/10.3390/biomimetics8030301 - 10 Jul 2023

Cited by 2 | Viewed by 1130

Abstract

Natural image matting is an essential technique for image processing that enables various applications, such as image synthesis, video editing, and target tracking. However, the existing image matting methods may fail to produce satisfactory results when computing resources are limited. Sampling-based methods can [...] Read more.

Natural image matting is an essential technique for image processing that enables various applications, such as image synthesis, video editing, and target tracking. However, the existing image matting methods may fail to produce satisfactory results when computing resources are limited. Sampling-based methods can reduce the dimensionality of the decision space and, therefore, reduce computational resources by employing different sampling strategies. While these approaches reduce computational consumption, they may miss an optimal pixel pair when the number of available high-quality pixel pairs is limited. To address this shortcoming, we propose a novel multi-criterion sampling strategy that avoids missing high-quality pixel pairs by incorporating multi-range pixel pair sampling and a high-quality sample selection method. This strategy is employed to develop a multi-criterion matting algorithm via Gaussian process, which searches for the optimal pixel pair by using the Gaussian process fitting model instead of solving the original pixel pair objective function. The experimental results demonstrate that our proposed algorithm outperformed other methods, even with 1% computing resources, and achieved alpha matte results comparable to those yielded by the state-of-the-art optimization algorithms. Full article

(This article belongs to the Special Issue Nature-Inspired Computer Algorithms)

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13 pages, 2143 KiB

Open AccessArticle

Silica-Containing Biomimetic Composites Based on Sea Urchin Skeleton and Polycalcium Organyl Silsesquioxane

by Nikolay P. Shapkin, Irina G. Khalchenko, Anatoliy L. Drozdov, Aleksander N. Fedorets, Igor Yu Buravlev, Anna A. Andrasyuk, Natalya V. Maslova, Kirill A. Pervakov and Evgeniy K. Papynov

Biomimetics 2023, 8(3), 300; https://doi.org/10.3390/biomimetics8030300 - 09 Jul 2023

Cited by 2 | Viewed by 1317

Abstract

The paper presents an original approach to the synthesis of polycalciumorganyl silsesquioxanes through the reaction of polyorganyl silsesquioxanes [RSiO_1.5]_n (where R is an ethyl and phenyl radical) with sea urchin skeleton under the conditions of mechanochemical activation. The [...] Read more.

The paper presents an original approach to the synthesis of polycalciumorganyl silsesquioxanes through the reaction of polyorganyl silsesquioxanes [RSiO_1.5]_n (where R is an ethyl and phenyl radical) with sea urchin skeleton under the conditions of mechanochemical activation. The novelty and practical significance of the present study lies in the use of an available natural raw source as a source of calcium ions to initiate the reaction of calcium silicate formation and create a matrix for the formation of a porous inorganic composite framework. The thermal stability of the introduced silicates, i.e., the ability to maintain a porous structure at high temperatures, is key to the production of an ordered porous material. The reaction scheme was proposed to be based on the interaction of calcium carbonate with the siloxane bond. FTIR, XRD, GPC, and TGA were used to study the composition and structure of the obtained materials. The cross-sectional area of the polymer chain and the volumes of the coherent scattering regions of the polymers obtained were calculated from the XRD data. To prepare the composites, the sea urchin skeleton was further modified with polycalciumorganyl silsesquioxanes in a toluene solution. To remove the sea urchin skeleton, the obtained biomimetic composites were treated with hydrochloric acid. The results of the morphological and surface composition studies are reported. The method proposed in the paper could be of fundamental importance for the possibility of obtaining structured porous composite materials for a wide range of practical applications, including for the purpose of creating a composite that may be a promising carrier for targeted delivery of chemotherapy agents. Full article

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Biomimetics, Volume 8, Issue 3 (July 2023) – 62 articles

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