Biomimetics, Volume 8, Issue 8 (December 2023) – 64 articles

This research investigates the implementation of complex-exponential-based neurons in FPGA, which can pave the way for implementing bio-inspired spiking neural networks to compensate for the existing computational constraints in conventional artificial neural networks. The increasing use of extensive neural networks and the complexity of models in handling big data lead to higher power consumption and delays. Hence, finding solutions to reduce computational complexity is crucial for addressing power consumption challenges. The complex exponential form effectively encodes oscillating features like frequency, amplitude, and phase shift, streamlining the demanding calculations typical of conventional artificial neurons through levering the simple phase addition of complex exponential functions. The article implements such a two-neuron and a multi-neuron neural model using the Xilinx System Generator and Vivado Design Suite, employing 8-bit, 16-bit, and 32-bit fixed-point data format representations. The study evaluates the accuracy of the proposed neuron model across different FPGA implementations while also providing a detailed analysis of operating frequency, power consumption, and resource usage for the hardware implementations. BRAM-based Vivado designs outperformed Simulink regarding speed, power, and resource efficiency. Specifically, the Vivado BRAM-based approach supported up to 128 neurons, showcasing optimal LUT and FF resource utilization. Such outcomes accommodate choosing the optimal design procedure for implementing spiking neural networks on FPGAs. Full article

Smart manufacturing needs cognitive computing methods to make the relevant systems more intelligent and autonomous. In this respect, bio-inspired cognitive computing methods (i.e., biologicalization) can play a vital role. This article is written from this perspective. In particular, this article provides a general overview of the bio-inspired computing method called DNA-Based Computing (DBC), including its theory and applications. The main theme of DBC is the central dogma of molecular biology (once information of DNA/RNA has got into a protein, it cannot get out again), i.e., DNA to RNA (sequences of four types of nucleotides) and DNA/RNA to protein (sequence of twenty types of amino acids) are allowed, but not the reverse ones. Thus, DBC transfers few-element information (DNA/RAN-like) to many-element information (protein-like). This characteristic of DBC can help to solve cognitive problems (e.g., pattern recognition). DBC can take many forms; this article elucidates two main forms, denoted as DBC-1 and DBC-2. Using arbitrary numerical examples, we demonstrate that DBC-1 can solve various cognitive problems, e.g., “similarity indexing between seemingly different but inherently identical objects” and “recognizing regions of an image separated by a complex boundary.” In addition, using an arbitrary numerical example, we demonstrate that DBC-2 can solve the following cognitive problem: “pattern recognition when the relevant information is insufficient.” The remarkable thing is that smart manufacturing-based systems (e.g., digital twins and big data analytics) must solve the abovementioned problems to make the manufacturing enablers (e.g., machine tools and monitoring systems) more self-reliant and autonomous. Consequently, DBC can improve the cognitive problem-solving ability of smart manufacturing-relevant systems and enrich their biologicalization. Full article

In this paper, a new bio-inspired metaheuristic algorithm called Giant Armadillo Optimization (GAO) is introduced, which imitates the natural behavior of giant armadillo in the wild. The fundamental inspiration in the design of GAO is derived from the hunting strategy of giant armadillos in moving towards prey positions and digging termite mounds. The theory of GAO is expressed and mathematically modeled in two phases: (i) exploration based on simulating the movement of giant armadillos towards termite mounds, and (ii) exploitation based on simulating giant armadillos’ digging skills in order to prey on and rip open termite mounds. The performance of GAO in handling optimization tasks is evaluated in order to solve the CEC 2017 test suite for problem dimensions equal to 10, 30, 50, and 100. The optimization results show that GAO is able to achieve effective solutions for optimization problems by benefiting from its high abilities in exploration, exploitation, and balancing them during the search process. The quality of the results obtained from GAO is compared with the performance of twelve well-known metaheuristic algorithms. The simulation results show that GAO presents superior performance compared to competitor algorithms by providing better results for most of the benchmark functions. The statistical analysis of the Wilcoxon rank sum test confirms that GAO has a significant statistical superiority over competitor algorithms. The implementation of GAO on the CEC 2011 test suite and four engineering design problems show that the proposed approach has effective performance in dealing with real-world applications. Full article

Treatment of bone defects resulting after tumor surgeries, accidents, or non-unions is an actual problem linked to morbidity and the necessity of a second surgery and often requires a critical healthcare cost. Although the surgical technique has changed in a modern way, the treatment outcome is still influenced by patient age, localization of the bone defect, associated comorbidities, the surgeon approach, and systemic disorders. Three-dimensional magnesium-based scaffolds are considered an important step because they can have precise bone defect geometry, high porosity grade, anatomical pore shape, and mechanical properties close to the human bone. In addition, magnesium has been proven in in vitro and in vivo studies to influence bone regeneration and new blood vessel formation positively. In this review paper, we describe the magnesium alloy’s effect on bone regenerative processes, starting with a short description of magnesium’s role in the bone healing process, host immune response modulation, and finishing with the primary biological mechanism of magnesium ions in angiogenesis and osteogenesis by presenting a detailed analysis based on a literature review. A strategy that must be followed when a patient-adapted scaffold dedicated to bone tissue engineering is proposed and the main fabrication technologies are combined, in some cases with artificial intelligence for Mg alloy scaffolds, are presented with examples. We emphasized the microstructure, mechanical properties, corrosion behavior, and biocompatibility of each study and made a basis for the researchers who want to start to apply the regenerative potential of magnesium-based scaffolds in clinical practice. Challenges, future directions, and special potential clinical applications such as osteosarcoma and persistent infection treatment are present at the end of our review paper. Full article

Poly-ε-caprolactone (PCL) has been widely used in additive manufacturing for the construction of scaffolds for bone tissue engineering. However, its use is limited by its lack of bioactivity and inability to induce cell adhesion, hence limiting bone tissue regeneration. Biomimicry is strongly influenced by the dynamics of cell–substrate interaction. Thus, characterizing scaffolds at the cell scale could help to better understand the relationship between surface mechanics and biological response. We conducted atomic force microscopy-based nanoindentation on 3D-printed PCL fibers of ~300 µm thickness and mapped the near-surface Young’s modulus at loading forces below 50 nN. In this non-disruptive regime, force mapping did not show clear patterns in the spatial distribution of moduli or a relationship with the topographic asperities within a given region. Remarkably, we found that the average modulus increased linearly with the logarithm of the strain rate. Finally, a dependence of the moduli on the history of nanoindentation was demonstrated on locations of repeated nanoindentations, likely due to creep phenomena capable of hindering viscoelasticity. Our findings can contribute to the rational design of scaffolds for bone regeneration that are capable of inducing cell adhesion and proliferation. The methodologies described are potentially applicable to various tissue-engineered biopolymers. Full article

Achieving omnidirectional walking for bipedal robots is considered one of the most challenging tasks in robotics technology. Reinforcement learning (RL) methods have proved effective in bipedal walking tasks. However, most existing methods use state machines to switch between multiple policies and achieve omnidirectional gait, which results in shaking during the policy switching process for bipedal robots. To achieve a seamless transition between omnidirectional gait and transient motion for full-size bipedal robots, we propose a novel multi-agent RL method. Firstly, a multi-agent RL algorithm based on the actor–critic framework is designed, and policy entropy is introduced to improve exploration efficiency. By learning agents with parallel initial state distributions, we minimize reliance on gait planner effectiveness in the Robot Operating System (ROS). Additionally, we design a novel heterogeneous policy experience replay mechanism based on Euclidean distance. Secondly, considering the periodicity of bipedal robot walking, we develop a new periodic gait function. Including periodic objectives in the policy can accelerate the convergence speed of training periodic gait functions. Finally, to enhance the robustness of the policy, we construct a novel curriculum learning method by discretizing Gaussian distribution and incorporate it into the robot’s training task. Our method is validated in a simulation environment, and the results show that our method can achieve multiple gaits through a policy network and achieve smooth transitions between different gaits. Full article

In the realm of computational problem-solving, the search for efficient algorithms tailored for real-world engineering challenges and software requirement prioritization is relentless. This paper introduces the Multi-Learning-Based Reptile Search Algorithm (MLBRSA), a novel approach that synergistically integrates Q-learning, competitive learning, and adaptive learning techniques. The essence of multi-learning lies in harnessing the strengths of these individual learning paradigms to foster a more robust and versatile search mechanism. Q-learning brings the advantage of reinforcement learning, enabling the algorithm to make informed decisions based on past experiences. On the other hand, competitive learning introduces an element of competition, ensuring that the best solutions are continually evolving and adapting. Lastly, adaptive learning ensures the algorithm remains flexible, adjusting the traditional Reptile Search Algorithm (RSA) parameters. The application of the MLBRSA to numerical benchmarks and a few real-world engineering problems demonstrates its ability to find optimal solutions in complex problem spaces. Furthermore, when applied to the complicated task of software requirement prioritization, MLBRSA showcases its capability to rank requirements effectively, ensuring that critical software functionalities are addressed promptly. Based on the results obtained, the MLBRSA stands as evidence of the potential of multi-learning, offering a promising solution to engineering and software-centric challenges. Its adaptability, competitiveness, and experience-driven approach make it a valuable tool for researchers and practitioners. Full article

The development of soft robotics owes much to the field of biomimetics, where soft actuators predominantly mimic the movement found in nature. In contrast to their rigid counterparts, soft robots offer superior safety and human–machine interaction comfort, particularly in medical applications. However, when it comes to the hand rehabilitation exoskeletons, the soft devices have been limited by size and material constraints, unable to provide sufficient tensile strength for patients with high muscle tension. In this paper, we drew inspiration from the muscle structure found in the tail of dragonflies and designed a novel central tendon-based bellows actuator. The experimental results demonstrated that the central tendon-based bellows actuator significantly outperforms conventional pneumatic bellows actuators in terms of mechanical output. The tensile strength of the central tendon-based bellows actuator exceeded that of pneumatic actuators more than tenfold, while adding only 2 g to the wearable weight. This finding suggests that the central tendon-based bellows actuator is exceptionally well-suited for applications demanding substantial pulling force, such as in the field of exoskeleton robotics. With tensile strength exceeding that of pneumatic bellows actuators, this biomimetic design opens new avenues for safer and more effective human–machine interaction, revolutionizing various sectors from healthcare to industrial automation. Full article

Various processes designed for the humification (HF) of animal husbandry wastes, primarily bird droppings, reduce their volumes, solve environmental problems, and make it possible to obtain products with artificially formed humic substances (HSs) as analogues of natural HSs, usually extracted from fossil sources (coal and peat). This review studies the main characteristics of various biological and physicochemical methods of the HF of animal wastes (composting, anaerobic digestion, pyrolysis, hydrothermal carbonation, acid or alkaline hydrolysis, and subcritical water extraction). A comparative analysis of the HF rates and HS yields in these processes, the characteristics of the resulting artificial HSs (humification index, polymerization index, degree of aromaticity, etc.) was carried out. The main factors (additives, process conditions, waste pretreatment, etc.) that can increase the efficiency of HF and affect the properties of HSs are highlighted. Based on the results of chemical composition analysis, the main trends and preferences with regard to the use of HF products as complex biomimetics are discussed. Full article

Silk has been consistently popular throughout human history due to its enigmatic properties. Today, it continues to be widely utilized as a polymer, having first been introduced to the textile industry. Furthermore, the health sector has also integrated silk. The Bombyx mori silk fibroin (SF) holds the record for being the most sustainable, functional, biocompatible, and easily produced type among all available SF sources. SF is a biopolymer approved by the FDA due to its high biocompatibility. It is versatile and can be used in various fields, as it is non-toxic and has no allergenic effects. Additionally, it enhances cell adhesion, adaptation, and proliferation. The use of SF has increased due to the rapid advancement in tissue engineering. This review comprises an introduction to SF and an assessment of the relevant literature using various methods and techniques to enhance the tissue engineering of SF-based hydrogels. Consequently, the function of SF in skin tissue engineering, wound repair, bone tissue engineering, cartilage tissue engineering, and drug delivery systems is therefore analysed. The potential future applications of this functional biopolymer for biomedical engineering are also explored. Full article

Soft continuum robots, inspired by the adaptability and agility of natural soft-bodied organisms like octopuses and elephant trunks, present a frontier in robotics research. However, exploiting their full potential necessitates precise modeling and control for specific motion and manipulation tasks. This study introduces an innovative approach using Deep Convolutional Neural Networks (CNN) for the inverse quasi-static modeling of these robots within the Absolute Nodal Coordinate Formulation (ANCF) framework. The ANCF effectively represents the complex non-linear behavior of soft continuum robots, while the CNN-based models are optimized for computational efficiency and precision. This combination is crucial for addressing the complex inverse statics problems associated with ANCF-modeled robots. Extensive numerical experiments were conducted to assess the performance of these Deep CNN-based models, demonstrating their suitability for real-time simulation and control in statics modeling. Additionally, this study includes a detailed cross-validation experiment to identify the most effective model architecture, taking into account factors such as the number of layers, activation functions, and unit configurations. The results highlight the significant benefits of integrating Deep CNN with ANCF models, paving the way for advanced statics modeling in soft continuum robotics. Full article

With advancements in technology, digital humans are becoming increasingly sophisticated, with their application scope widening to include interactions with real people. However, research on expressions that facilitate natural engagement in interactions between real people and digital humans is scarce. With this study, we aimed to examine the differences in user engagement as measured by subjective evaluations, eye tracking, and electroencephalogram (EEG) responses relative to different gaze expressions in various conversational contexts. Conversational situations were categorized as face-to-face, face-to-video, and digital human interactions, with gaze expressions segmented into eye contact and gaze avoidance. Story stimuli incorporating twelve sentences verified to elicit positive and negative emotional responses were employed in the experiments after validation. A total of 45 participants (31 females and 14 males) underwent stimulation through positive and negative stories while exhibiting eye contact or gaze avoidance under each of the three conversational conditions. Engagement was assessed using subjective evaluation metrics in conjunction with measures of the subjects’ gaze and brainwave activity. The findings revealed engagement disparities between the face-to-face and digital-human conversation conditions. Notably, only positive stimuli elicited variations in engagement based on gaze expression across different conversation conditions. Gaze analysis corroborated the engagement differences, aligning with prior research on social sensitivity, but only in response to positive stimuli. This research departs from traditional studies of un-natural interactions with digital humans, focusing instead on interactions with digital humans designed to mimic the appearance of real humans. This study demonstrates the potential for gaze expression to induce engagement, regardless of the human or digital nature of the conversational dyads. Full article

A living lab is a valuable method for designing tangible and intangible service elements, ensuring a comprehensive user experience. Developing a digital companion service, which users may be unfamiliar with, requires observing user behavior in real-world environments and analyzing living and behavioral patterns. A living lab starts with understanding user characteristics and behaviors. Living lab methods have an impact on the accuracy and precision of service design. The number of seniors in South Korea is rapidly increasing, leading to a rise in social issues like solitary deaths and suicide. Addressing these problems has led to a growing demand for companion robots. To design effective companion services, understanding seniors’ living environments and their cognitive and behavioral traits is essential. This opinion piece, based on a national R&D project, presents the development of a digital companion for seniors. It offers insights, providing a comprehensive overview of living lab-based service interaction design and proposing methodologies about living lab environment construction and experimentation and considerations when designing robot interaction functions and appearance. The living lab environment includes real living spaces, laboratories, virtual reality settings, and senior welfare centers. Using the research findings, we created service scenarios, analyzed senior language characteristics, and developed the concept and facial expressions of the digital companion. To successfully introduce a novel service, it is crucial to analyze users’ real-life behavior and adjust the service accordingly. Full article

Combined Heat and Power Units Economic Dispatch (CHPUED) is a challenging non-convex optimization challenge in the power system that aims at decreasing the production cost by scheduling the heat and power generation outputs to dedicated units. In this article, a Kepler optimization algorithm (KOA) is designed and employed to handle the CHPUED issue under valve points impacts in large-scale systems. The proposed KOA is used to forecast the position and motion of planets at any given time based on Kepler’s principles of planetary motion. The large 48-unit, 96-unit, and 192-unit systems are considered in this study to manifest the superiority of the developed KOA, which reduces the fuel costs to 116,650.0870 USD/h, 234,285.2584 USD/h, and 487,145.2000 USD/h, respectively. Moreover, the dwarf mongoose optimization algorithm (DMOA), the energy valley optimizer (EVO), gray wolf optimization (GWO), and particle swarm optimization (PSO) are studied in this article in a comparative manner with the KOA when considering the 192-unit test system. For this large-scale system, the presented KOA successfully achieves improvements of 19.43%, 17.49%, 39.19%, and 62.83% compared to the DMOA, the EVO, GWO, and PSO, respectively. Furthermore, a feasibility study is conducted for the 192-unit test system, which demonstrates the superiority and robustness of the proposed KOA in obtaining all operating points between the boundaries without any violations. Full article

High-rise buildings often use mechanical systems to assist ventilation to maintain the stability of their internal environments, and the energy consumption of mechanical ventilation poses a great challenge to urban environments and energy systems. The ventilation system of termite mounds with a combination of internal main and attached chambers is one of the classic examples of nature’s bionic approach to maintaining a stable internal ventilation environment for large-volume structures. In this study, based on the inspiration of the internal ventilation chamber structure of bionic termite mounds, we constructed seven high-rise building chamber ventilation models based on the chamber structure of termite mounds with main chambers, main chambers plus single-attached chambers (three types), and main chambers plus double-attached chambers (three types) under natural ventilation conditions, aiming at obtaining the optimal low-energy and high-efficiency chamber ventilation model for bionic termite mounds in high-rise buildings. (1) The wind speed and wind pressure of the high-rise building with the addition of the bionic termite mound chamber structure is higher than that of the traditional chamber-free high-rise building in the sample floors, the maximal difference of the wind speed between the two models is 0.05 m/s, and the maximal difference of the wind speed of the single building is 0.14 m/s, with the maximal difference of the wind speed of the single building being 0.14 m/s; and the natural ventilation environment can be satisfied by a high-rise building with a chamber. (2) After increasing the single-attached chamber structure of the bionic termite mound, the difference in wind speed of different floors is 0.15 m/s, which is 0.10 m/s higher than that of the high-rise building model with the main chamber only. (3) Under the bionic termite mound chamber high-rise building double-attached chamber model, the maximum difference in wind speed of each floor sampling point can reach 0.19 m/s, while the wind pressure cloud map shows a stable wind environment system. (4) Two attached chambers are added at A and B of the high-rise building to form the a4 model of the chamber of the high-rise building with a double-chamber bionic termite mound. According to the results, it can be seen that the model of the nine floor sampling points of the maximum wind speed difference has six places for the highest value, and the single building wind speed difference for the minimum value of 0.10 m/s. The study aims to optimize the connectivity and ventilation performance of high-rise buildings under natural ventilation conditions and to promote the green and sustainable design of high-rise buildings. Full article

Biomineralization peptides are versatile tools for generating nanostructures since they can make specific interactions with various inorganic metals, which can lead to the formation of intricate nanostructures. Previously, we examined the influence that multivalency has on inorganic structures formed by p53 tetramer-based biomineralization peptides and noted a connection between the geometry of the peptide and its ability to regulate nanostructure formation. To investigate the role of multivalency in nanostructure formation by biomineralization peptides more thoroughly, silver biomineralization peptides were engineered by linking them to additional self-assembling molecules based on coiled-coil peptides and multistranded DNA oligomers. Under mild reducing conditions at room temperature, these engineered biomineralization peptides self-assembled and formed silver nanostructures. The trimeric forms of the biomineralization peptides were the most efficient in forming a hexagonal disk nanostructure, with both the coiled-coil peptide and DNA-based multimeric forms. Together, the results suggest that the spatial arrangement of biomineralization peptides plays a more important role in regulating nanostructure formation than their valency. Full article

In the realm of industrial robotics, there is a growing challenge in simplifying human–robot collaboration (HRC), particularly in complex settings. The demand for more intuitive teleoperation systems is on the rise. However, optimizing robot control interfaces and streamlining teleoperation remains a formidable task due to the need for operators to possess specialized knowledge and the limitations of traditional methods regarding operational space and time constraints. This study addresses these issues by introducing a virtual reality (VR) HRC system with five-dimensional capabilities. Key advantages of our approach include: (1) real-time observation of robot work, whereby operators can seamlessly monitor the robot’s real-time work environment and motion during teleoperation; (2) leveraging VR device capabilities, whereby the strengths of VR devices are harnessed to simplify robot motion control, significantly reducing the learning time for operators; and (3) adaptability across platforms and environments: our system effortlessly adapts to various platforms and working conditions, ensuring versatility across different terminals and scenarios. This system represents a significant advancement in addressing the challenges of HRC, offering improved teleoperation, simplified control, and enhanced accessibility, particularly for operators with limited prior exposure to robot operation. It elevates the overall HRC experience in complex scenarios. Full article

Research on the efficiency and quality issues faced in aircraft assembly was conducted in this article. A new method of human–machine collaborative riveting was proposed, which combined the flexibility of manual collaboration with the precise control of automatic riveting. The research works include: (1) a theoretical model of pneumatic hammer riveting was established to clarify the principle and parameters of riveting process. (2) A smart bucking bar was designed to support the data collection and extraction of manual collaborative riveting process. (3) An automatic riveting experimental platform was designed to test the automatic riveting process incorporating the extracted manual riveting process parameters, and further an optimization strategy was proposed for the automatic riveting process. (4) A human–machine collaborative riveting experimental platform was developed to conduct the verification work. Through the theoretical analysis, experimental research, system scheme design, and process parameters optimization, the application and verification of human–machine collaborative assembly technology have been achieved. This technology is expected to be comprehensively promoted in the field of aircraft manufacturing, and for breaking through the current difficulties of low production efficiency and poor assembly quality control. Full article

In light of pressing global health concerns, the significance of indoor air quality in densely populated structures has been emphasized. This research introduces the Mimosa kinetic façade, an innovative design inspired by the adaptive responsiveness of the Mimosa plant to environmental stimuli. Traditional static architectural façades often hinder natural ventilation, leading to diminished air quality with potential health and cognitive repercussions. The Mimosa kinetic façade addresses these challenges by enhancing effective airflow and facilitating the removal of airborne contaminants. This study evaluates the façade’s impact on quality of life and its aesthetic contribution to architectural beauty, utilizing the biomimicry design spiral for a nature-inspired approach. Computational simulations and physical tests were conducted to assess the ventilation capacities of various façade systems, with a particular focus on settings in Bangkok, Thailand. The study revealed that kinetic façades, especially certain patterns, provided superior ventilation compared to static ones. Some patterns prioritized ventilation, while others optimized human comfort during extended stays. Notably, the most effective patterns of the kinetic façade inspired by the Mimosa demonstrated a high air velocity reaching up to 12 m/s, in contrast to the peak of 2.50 m/s in single-sided façades (traditional façades). This highlights the kinetic façade’s potential to rapidly expel airborne particles from indoor spaces, outperforming traditional façades. The findings underscore the potential of specific kinetic façade patterns in enhancing indoor air quality and human comfort, indicating a promising future for kinetic façades in architectural design. This study aims to achieve an optimal balance between indoor air quality and human comfort, although challenges remain in perfecting this equilibrium. Full article

Decapod crustaceans have tooth-like white denticles that are present only on the pinching side of the claws. In the mud crab, Scylla serrata, a huge denticle exists on the movable finger of the dominant claw. This is mainly used to crush the shells of the crab’s staple food. The local mechanical properties, hardness (H_IT) and elastic modulus (E_r), of the peak and valley areas of the largest denticle were examined via a nanoindentation test. The microstructure and elemental composition were characterized using a scanning electron microscope and energy-dispersive X-ray spectroscopy. The striation patterns originating from a twisted plywood structure parallel to the surface were visible over the entire denticle. Most of the largest denticle was occupied by a hard area without phosphorus, and there was a soft layer corresponding to the endocuticle with phosphorus in the innermost part. The H_IT of the denticle valley was about 40% lower than that of the denticle peak, and the thickness of the soft endocuticle of the denticle valley was five times thicker than that of the denticle peak. The H_IT–E_r map showed that the abrasion resistance of the denticle surface was vastly superior and was in the top class among organisms. The claw denticles were designed with the necessary characteristics in the necessary places, as related to the ecology of the mud crab. Full article

The fuel pump serves as the central component of the aircraft fuel system, necessitating real-time data acquisition for monitoring purposes. As the number of sensors increases, there is a substantial rise in data volume, leading to a simultaneous increase in computational processing for traditional Prognostics and Health Management methods while computational efficiency decreases. In response to this challenge, a novel health monitoring approach for aircraft fuel pumps is proposed based on the collaborative utilization of cloud-edge resources. This approach enables efficient cooperation among the sensor side, edge side, and cloud side to achieve timely fault warnings and accurate fault classification for fuel pumps. Within this method, anomaly judgment tasks are allocated to the edge side, and an anomaly judgment method that integrates the 3σ threshold and “3/5 strategy” is devised. Additionally, a fault diagnosis algorithm, founded on a convolutional auto-encoder, is formulated in the cloud to discern various fault types and severities. Comparative results demonstrate that, in contrast to long short-term memory networks, convolutional neural networks, extreme learning machines, and support vector machines, the proposed method yields improvements in accuracy of 4.35%, 6.40%, 17.65%, and 19.35%, respectively. Consequently, it is evident that the proposed method exhibits notable efficacy in the condition monitoring of aircraft fuel pumps. Full article

The attachment performances of mechanical feet are significant in improving the trafficability and mobility of robots on the extreme ground. In the future, frozen-ground robots can be used to replace human soldiers in scouting and deep space exploration. In this study, the influence factors on the attachment function of the bionic feet were analyzed. Soft frozen soil and tight frozen soil close to natural frozen soil were prepared, and the friction between ungula and frozen soil ground was simulated together with the plantar pressures of reindeer under trotting. The major attachment parts were the ungula cusp, outer edges, and ungula capsules, and the stress on the ungula was mainly 4.56–24.72 MPa. According to the microstructures of plantar fur and ungula, the corresponding ratio of the rib width and length was 0.65:1, and the corresponding ratio of the rib width and distance was 3:1. In addition, the scales of the plantar fur were very tightly arranged and had large ripples. Based on typical curves, an ungula capsule-curved surface, and a nonsmooth plantar fur surface, four types of bionic feet and the corresponding ordinary multidamboard foot were designed. On the frozen soil, the bionic foot with ribs and an ungula capsule showed the best attachment performance. Compared with the multidamboard foot, the dynamic coefficient of friction of the bionic foot with ribs and ungula capsules increased by 11.43–31.75%. The attachment mechanism of the bionic feet is as follows: under the action of pressure, the fine patterns of the bionic convex-crown generate friction with the nonsmooth structure of the frozen soil surface, which improves the attachment performance. Full article

Ceramic biocomposites based on bioactive tricalcium phosphate doped with metal ions are a strategy for obtaining good biomimetics for human bone composition. Manufacturing with PMMA porogen also induces bone-like porosity morphology. The poor strength of tricalcium phosphate can be overcomed by designing ceramic composites reinforced with tetragonal and cubic zirconia. In this work, five different bioceramic composites were manufactured without and with induced porosity and their physical, mechanical, microstructural, and biological properties were studied. With the addition of tetragonal and cubic zirconia, an improvement in strength of 22% and 55%, respectively, was obtained, corresponding to up to 20.7 MPa. PMMA was suitable for adding porosity, up to 30%, with interconnectivity while an excellent hOB cellular viability was achieved for all biocomposites. Full article

The robustness of superhydrophobic objects conflicts with both the inevitable introduction of fragile micro/nanoscale surfaces and three-dimensional (3D) complex structures. The popular metal 3D printing technology can manufacture robust metal 3D complex components, but the hydrophily and mass surface defects restrict its diverse application. Herein, we proposed a strategy that takes the inherent ridges and grooves’ surface defects from laser powder bed fusion additive manufacturing (LPBF-AM), a metal 3D printing process, as storage spaces for hydrophobic silica (HS) nanoparticles to obtain superhydrophobic capacity and superior robustness. The HS nanoparticles stored in the grooves among the laser-melted tracks serve as the hydrophobic guests, while the ridges’ metal network provides the mechanical strength, leading to robust superhydrophobic objects with desired 3D structures. Moreover, HS nanoparticles coated on the LPBF-AM-printed surface can inhibit corrosion behavior caused by surface defects. It was found that LPBF-AM-printed objects with HS nanoparticles retained superior hydrophobicity after 150 abrasion cycles (~12.5 KPa) or 50 cycles (~37.5 KPa). Furthermore, LPBF-AM-printed ships with superhydrophobic coating maintained great water repellency even after 10,000 cycles of seawater swashing, preventing dynamic corrosion upon surfaces. Our proposed strategy, therefore, provides a low-cost, highly efficient, and robust superhydrophobic coating, which is applicable to metal 3D architectures toward corrosion-resistant requirements. Full article

A large number of experimental studies have demonstrated that globular proteins can be absorbed from the solution by both polycationic and polyanionic brushes when the net charge of protein globules is of the same or of the opposite sign with respect to that of brush-forming polyelectrolyte chains. Here, we overview the results of experimental studies on interactions between globular proteins and polycationic or polyanionic brushes, and present a self-consistent field theoretical model that allows us to account for the asymmetry of interactions of protein-like nanocolloid particles comprising weak (pH-sensitive) cationic and anionic groups with a positively or negatively charged polyelectrolyte brush. The position-dependent insertion free energy and the net charge of the particle are calculated. The theoretical model predicts that if the numbers of cationic and anionic ionizable groups of the protein are approximately equal, then the interaction patterns for both cationic and anionic brushes at equal offset on the “wrong side” from the isoelectric point (IEP), i.e., when the particle and the brush charge are of the same sign, are similar. An essential asymmetry in interactions of particles with polycationic and polyanionic brushes is predicted when fractions of cationic and anionic groups differ significantly. That is, at a pH above IEP, the anionic brush better absorbs negatively charged particles with a larger fraction of ionizable cationic groups and vice versa. Full article

Soft robots are compliant, impact resistant, and relatively safe in comparison to hard robots. However, the development of untethered soft robots is still a major challenge because soft legs cannot effectively support the power and control systems. Most untethered soft robots apply a crawling or walking gait, which limits their locomotion speed and mobility. This paper presents an untethered soft robot that can move with a bioinspired dynamic trotting gait. The robot is driven by inflatable soft legs designed on the basis of the pre-charged pneumatic (PCP) actuation principle. Experimental results demonstrate that the developed robot can trot stably with the fastest speed of 23 cm/s (0.97 body length per second) and can trot over different terrains (slope, step, rough terrain, and natural terrains). The robotic dog can hold up to a 5.5 kg load in the static state and can carry up to 1.5 kg in the trotting state. Without any rigid components inside the legs, the developed robotic dog exhibits resistance to large impacts, i.e., after withstanding a 73 kg adult (46 times its body mass), the robotic dog can stand up and continue its trotting gait. This innovative robotic system has great potential in equipment inspection, field exploration, and disaster rescue. Full article

The interaction between the plant lipid transfer protein Pru p 3 and phytosphingosine was assessed using an atomic force microscope. Phytosphingosine was covalently immobilized on DeepTip^TM probes and Pru p 3 on MicroDeck^TM functionalized substrates. Single-molecular interaction events between both molecules were retrieved and classified and the distribution for each one of the identified types was calculated. A success rate of over 70% was found by comparing the number of specific Pru p 3-phytosphingosine interaction events with the total number of recorded curves. The analysis of the distribution established among the various types of curves was further pursued to distinguish between those curves that can mainly be used for assessing the recognition between phytosphingosine (sensor molecule) and Pru p 3 (target molecule) in the context of affinity atomic force microscopy, and those that entail details of the interaction and might be employed in the context of force spectroscopy. The successful application of these functionalized probes and substrates to the characterization of the low-intensity hydrophobic interaction characteristic of this system is a clear indication of the potential of exploiting this approach with an extremely wide range of different biological molecules of interest. The possibility of characterizing molecular assembly events with single-molecule resolution offers an advantageous procedure to plough into the field of molecular biomimetics. Full article

In this work, we compare the basketball scoring performance of two imaginary (simulated) mechanical robots in conditions of erroneous information-processing circuits: Machine, whose moves are controlled by a conventional digital computer and Man, controlled by a random pulse computer composed of biologically-inspired circuits which execute basic arithmetic operations. This is the first comparative study of robustness of the digital and the random pulse computing paradigms, with respect to the error rate of the information-processing circuits ($p_{err}$), for a mechanical robot. In spite of the fact that Man’s computer consists of only about 100 logic gates while Machine’s requires about 3500 gates, Man achieves a significantly higher scoring probability for $p_{err}$ in the range from 0.01% all the way to 10%, while at lower $p_{err}$, both converge to the perfect score. Furthermore, Man’s hits make up a smooth Gaussian distribution with a vanishing probability of making large misses even at the highest $p_{err}$, while Machine is prone to spectacular misses already at $p_{err}$ as low as 1 part-per-million. These findings indicate that the biologically inspired computation requires less hardware for the same task, and ensures higher robustness and better behaving operation than digital computation, which are characteristics of importance for the survivability of living beings. Full article

Odor-guided navigation is fundamental to the survival and reproductive success of many flying insects. Despite its biological importance, the mechanics of how insects sense and interpret odor plumes in the presence of complex flow fields remain poorly understood. This study employs numerical simulations to investigate the influence of turbulence, wingbeat-induced flow, and Schmidt number on the structure and perception of odor plumes by flying insects. Using an in-house computational fluid dynamics solver based on the immersed-boundary method, we solve the three-dimensional Navier–Stokes equations to model the flow field. The solver is coupled with the equations of motion for passive flapping wings to emulate wingbeat-induced flow. The odor landscape is then determined by solving the odor advection–diffusion equation. By employing a synthetic isotropic turbulence generator, we introduce turbulence into the flow field to examine its impact on odor plume structures. Our findings reveal that both turbulence and wingbeat-induced flow substantially affect odor plume characteristics. Turbulence introduces fluctuations and perturbations in the plume, while wingbeat-induced flow draws the odorant closer to the insect’s antennae. Moreover, we demonstrate that the Schmidt number, which affects odorant diffusivity, plays a significant role in odor detectability. Specifically, at high Schmidt numbers, larger fluctuations in odor sensitivity are observed, which may be exploited by insects to differentiate between various odorant volatiles emanating from the same source. This study provides new insights into the complex interplay between fluid dynamics and sensory biology and behavior, enhancing our understanding of how flying insects successfully navigate using olfactory cues in turbulent environments. Full article

This study utilized the mallard’s foot as the subject, examining the bone distribution via computed tomography (CT) and analyzing pertinent parameters of the tarsometatarsal bones. Additionally, gross anatomy methods were employed to elucidate the characteristics of the toes and webbing bio-structures and their material composition. Biologically, the mallard’s foot comprises tarsometatarsal bones and 10 phalanges, enveloped by fascia, tendons, and skin. Vernier calipers were used to measure the bones, followed by statistical analysis to acquire structural data. Tendons, originating in proximal muscles and terminating in distal bones beneath the fascia, facilitate force transmission and systematic movement of each segment’s bones. Regarding material composition, the skin layer serves both encapsulation and wrapping functions. Fat pads, located on the metatarsal side of metatarsophalangeal joints and each phalanx, function as cushioning shock absorbers. The correlation between the force applied to the tarsometatarsal bones and the webbing opening angle was explored using a texture analyzer. A simplified model describing the driving force behind the webbing opening angle was introduced. Furthermore, we designed a bionic foot, contributing a foundational reference for anti-sinking bionic foot development. Full article