Biomimetics, Volume 9, Issue 3 (March 2024) – 70 articles

About forty years after its first application, digital image correlation (DIC) has become an established method for measuring surface displacements and deformations of objects under stress. To date, DIC has been used in a variety of in vitro and in vivo studies to biomechanically characterise biological samples in order to reveal biomimetic principles. However, when surfaces of samples strongly deform or twist, they cannot be thoroughly traced. To overcome this challenge, different DIC setups have been developed to provide additional sensor perspectives and, thus, capture larger parts of an object’s surface. Herein, we discuss current solutions for this multi-perspective DIC, and we present our own approach to a 360° DIC system based on a single stereo-camera setup. Using this setup, we are able to characterise the desiccation-driven opening mechanism of two woody Hakea fruits over their entire surfaces. Both the breaking mechanism and the actuation of the two valves in predominantly dead plant material are models for smart materials. Based on these results, an evaluation of the setup for 360° DIC regarding its use in deducing biomimetic principles is given. Furthermore, we propose a way to improve and apply the method for future measurements. Full article

Hydrodynamic pressure sensors offer an auxiliary approach for ocean exploration by unmanned underwater vehicles (UUVs). However, existing hydrodynamic pressure sensors often lack the ability to monitor subtle hydrodynamic stimuli in deep-sea environments. In this study, we present the development of a deep-sea hydrodynamic pressure sensor (DSHPS) capable of operating over a wide range of water depths while maintaining exceptional hydrodynamic sensing performance. The DSHPS device was systematically optimized by considering factors such as piezoelectric polyvinylidene fluoride–trifluoroethylene/barium titanate [P(VDF-TrFE)/BTO] nanofibers, electrode configurations, sensing element dimensions, integrated circuits, and packaging strategies. The optimized DSHPS exhibited a remarkable pressure gradient response, achieving a minimum pressure difference detection capability of approximately 0.11 Pa. Additionally, the DSHPS demonstrated outstanding performance in the spatial positioning of dipole sources, which was elucidated through theoretical charge modeling and fluid–structure interaction (FSI) simulations. Furthermore, the integration of a high Young’s modulus packaging strategy inspired by fish skull morphology ensured reliable sensing capabilities of the DSHPS even at depths of 1000 m in the deep sea. The DSHPS also exhibited consistent and reproducible positioning performance for subtle hydrodynamic stimulus sources across this wide range of water depths. We envision that the development of the DSHPS not only enhances our understanding of the evolutionary aspects of deep-sea canal lateral lines but also paves the way for the advancement of artificial hydrodynamic pressure sensors. Full article

The proposed strategy for the extrusion of printable composite filaments follows the favourable association of biogenic hydroxyapatite (HA) and graphene nanoplatelets (GNP) as reinforcement materials for a poly(lactic acid) (PLA) matrix. HA particles were chosen in the <40 μm range, while GNP were selected in the micrometric range. During the melt–mixing incorporation into the PLA matrix, both reinforcement ratios were simultaneously modulated for the first time at different increments. Cylindrical composite pellets/test samples were obtained only for the mechanical and wettability behaviour evaluation. The Fourier-transformed infrared spectroscopy depicted two levels of overlapping structures due to the solid molecular bond between all materials. Scanning electron microscopy and surface wettability and mechanical evaluations vouched for the (1) uniform/homogenous dispersion/embedding of HA particles up to the highest HA/GNP ratio, (2) physical adhesion at the HA-PLA interface due to the HA particles’ porosity, (3) HA-GNP bonding, and (4) PLA-GNP synergy based on GNP complete exfoliation and dispersion into the matrix. Full article

The severe effects of attention deficit hyperactivity disorder (ADHD) among adolescents can be prevented by timely identification and prompt therapeutic intervention. Traditional diagnostic techniques are complicated and time-consuming because they are subjective-based assessments. Machine learning (ML) techniques can automate this process and prevent the limitations of manual evaluation. However, most of the ML-based models extract few features from a single domain. Furthermore, most ML-based studies have not examined the most effective electrode placement on the skull, which affects the identification process, while others have not employed feature selection approaches to reduce the feature space dimension and consequently the complexity of the training models. This study presents an ML-based tool for automatically identifying ADHD entitled “ADHD-AID”. The present study uses several multi-resolution analysis techniques including variational mode decomposition, discrete wavelet transform, and empirical wavelet decomposition. ADHD-AID extracts thirty features from the time and time–frequency domains to identify ADHD, including nonlinear features, band-power features, entropy-based features, and statistical features. The present study also looks at the best EEG electrode placement for detecting ADHD. Additionally, it looks into the location combinations that have the most significant impact on identification accuracy. Additionally, it uses a variety of feature selection methods to choose those features that have the greatest influence on the diagnosis of ADHD, reducing the classification’s complexity and training time. The results show that ADHD-AID has provided scores for accuracy, sensitivity, specificity, F1-score, and Mathew correlation coefficients of 0.991, 0.989, 0.992, 0.989, and 0.982, respectively, in identifying ADHD with 10-fold cross-validation. Also, the area under the curve has reached 0.9958. ADHD-AID’s results are significantly higher than those of all earlier studies for the detection of ADHD in adolescents. These notable and trustworthy findings support the use of such an automated tool as a means of assistance for doctors in the prompt identification of ADHD in youngsters. Full article

Feature selection aims to select crucial features to improve classification accuracy in machine learning and data mining. In this paper, a new binary grasshopper optimization algorithm using time-varying Gaussian transfer functions (BGOA-TVG) is proposed for feature selection. Compared with the traditional S-shaped and V-shaped transfer functions, the proposed Gaussian time-varying transfer functions have the characteristics of a fast convergence speed and a strong global search capability to convert a continuous search space to a binary one. The BGOA-TVG is tested and compared to S-shaped and V-shaped binary grasshopper optimization algorithms and five state-of-the-art swarm intelligence algorithms for feature selection. The experimental results show that the BGOA-TVG has better performance in UCI, DEAP, and EPILEPSY datasets for feature selection. Full article

The Artificial Electric Field Algorithm (AEFA) stands out as a physics-inspired metaheuristic, drawing inspiration from Coulomb’s law and electrostatic force; however, while AEFA has demonstrated efficacy, it can face challenges such as convergence issues and suboptimal solutions, especially in high-dimensional problems. To overcome these challenges, this paper introduces a modified version of AEFA, named mAEFA, which leverages the capabilities of Lévy flights, simulated annealing, and the Adaptive s-best Mutation and Natural Survivor Method (NSM) mechanisms. While Lévy flights enhance exploration potential and simulated annealing improves search exploitation, the Adaptive s-best Mutation and Natural Survivor Method (NSM) mechanisms are employed to add more diversity. The integration of these mechanisms in AEFA aims to expand its search space, enhance exploration potential, avoid local optima, and achieve improved performance, robustness, and a more equitable equilibrium between local intensification and global diversification. In this study, a comprehensive assessment of mAEFA is carried out, employing a combination of quantitative and qualitative measures, on a diverse range of 29 intricate CEC’17 constraint benchmarks that exhibit different characteristics. The practical compatibility of the proposed mAEFA is evaluated on five engineering benchmark problems derived from the civil, mechanical, and industrial engineering domains. Results from the mAEFA algorithm are compared with those from seven recently introduced metaheuristic algorithms using widely adopted statistical metrics. The mAEFA algorithm outperforms the LCA algorithm in all 29 CEC’17 test functions with 100% superiority and shows better results than SAO, GOA, CHIO, PSO, GSA, and AEFA in 96.6%, 96.6%, 93.1%, 86.2%, 82.8%, and 58.6% of test cases, respectively. In three out of five engineering design problems, mAEFA outperforms all the compared algorithms, securing second place in the remaining two problems. Results across all optimization problems highlight the effectiveness and robustness of mAEFA compared to baseline metaheuristics. The suggested enhancements in AEFA have proven effective, establishing competitiveness in diverse optimization problems. Full article

Nowadays, the interaction of additive technologies and methods for designing or optimizing porous structures has yielded good results. Construction with complex microarchitectures can be created using this approach. Varying the microarchitecture leads to changes in weight and mechanical properties. However, there are problems with geometry reconstruction when dealing with complex microarchitecture. One approach is to use Voronoi cells for geometry reconstruction. In this article, an extension of the Voronoi diagram algorithm to orthotropic space for material structural design is presented. The inputs for the method include porosity, ellipticity, and ellipticity direction fields. As an example, a beam with fixed end faces and center kinematic loading was used. To estimate robust results for different numbers of clusters, 50, 75, and 100 clusters are presented. The porosity for smoothed structures ranged from 21.5% up to 22.8%. The stress–strain state was determined for the resulting structures. The stiffness for the initial and smoothed structures was the same. However, in the case of 75 and 100 clusters, local stress factors appeared in the smoothed structure. The maximum von Mises stress decreased by 20% for all smoothed structures in the area of kinematic loading and increased by 20% for all smoothed structures in the area of end faces. Full article

Many insects are able to walk vertically or upside down on both hard and soft surfaces. In beetles such as the ladybird (Coccinella septempunctata), intermolecular forces between tarsal setae on the footpads of the insects make this movement possible. In prior work, adhesion structures made from polydimethylsiloxane (PDMS) that mimic the action of the tarsal setae have been developed. It is proposed that these adhesion structures could be attached to a simplified version of the leg of a ladybird and used in practical applications. For example, the leg structures could potentially be employed in small surveillance drones to enable attachment to surfaces during flights, in order to preserve battery power. Alternatively, the structures could be used in small robotic devices to enable walking on steeply inclined surfaces. In this program of work, the morphology and movement of the leg of a ladybird were closely studied using a 3D X-ray microscope and a high-speed microscope. The positions of the tendons that facilitated movement were identified. From this knowledge, a simplified leg structure using pin-joints was designed and then fabricated using 3-D printing. The PDMS adhesion structures were then attached to the leg structure. The tendons in the actual insect leg were replicated using thread. Typical detachment forces of about 4 N indicated that the simplified leg structure was, in principle, more than capable of supporting the weight of a small device and then detach successfully. Attachment/detachment movement operations were performed using a linear actuator and controlled remotely. Therefore, proof of concept has been demonstrated for the use of such a simplified ladybird leg structure for the attachment/detachment of small robotic devices to horizontal, inclined, or vertical surfaces. Full article

Insects produce a variety of highly acrobatic maneuvers in flight owing to their ability to achieve various wing-stroke trajectories. Among them, beetles can quickly change their flight velocities and make agile turns. In this work, we report a newly discovered phasic wing-tip-folding phenomenon and its aerodynamic basis in beetles. The wings’ flapping trajectories and aerodynamic forces of the tethered flying beetles were recorded simultaneously via motion capture cameras and a force sensor, respectively. The results verified that phasic active spanwise-folding and deployment (PASFD) can exist during flapping flight. The folding of the wing-tips of beetles significantly decreased aerodynamic forces without any changes in flapping frequency. Specifically, compared with no-folding-and-deployment wings, the lift and forward thrust generated by bilateral-folding-and-deployment wings reduced by 52.2% and 63.0%, respectively. Moreover, unilateral-folding-and-deployment flapping flight was found, which produced a lateral force (8.65 mN). Therefore, a micro-flapping-wing mechanism with PASFD was then designed, fabricated, and tested in a motion capture and force measurement system to validate its phasic folding functions and aerodynamic performance under different operating frequencies. The results successfully demonstrated a significant decrease in flight forces. This work provides valuable insights for the development of flapping-wing micro-air-vehicles with high maneuverability. Full article

The popular immediate dentin sealing (IDS) technique is used to improve the bond strength of indirect restorations. This systematic review assessed whether bond strength is affected by the type of aging conditions, bonding agents, flowable resin composites, impression materials, temporary materials, and/or resin cement used within the IDS procedure. A comprehensive database search of PubMed, Embase, Scopus, Ovid Medline, Web of Sciences, Cochrane Library, Dentistry & Oral Sciences Source, and ProQuest was carried out up to 30 January 2024 without publication year or language limitations. Only in vitro full-texts regarding the effect of IDS on bond strength were included, and the quality of their methods was assessed via a Risk of Bias (RoB) test. In total, 1023 pertinent studies were initially found, and 60 articles were selected for review after screening for the title, abstract, and full texts. IDS application improves the bond strength of indirect restorations to dentin and reduces the negative effects of temporary materials on the bond durability of final indirect restorations. Filled dentin bonding agents or combinations with flowable resin composite are preferred to protect the IDS layer from conditioning procedures. Full article

An aerodynamic/hydrodynamic investigation of water cross-over is performed for a bionic unmanned aquatic–aerial amphibious vehicle (bionic UAAV). According to flying fish features and UAAV flight requirements of water cross-over, the bionic conceptual design of crossing over water is described and planned in multiple stages and modes of motion. A solution procedure for the numerical simulation method, based on a modified SST turbulence model and the VOF model, is expressed, and a verification study is presented using a typical case. Longitudinal–lateral numerical simulation analysis investigates the cruise performance underwater and in the air. The numerical simulation and principal experiment verification are conducted for crossing over water and water surface acceleration. The results indicate that the bionic UAAV has an excellent aerodynamic/hydrodynamic performance and variant configuration to adapt to water cross-over. The bionic UAAV has good water and air navigation stability, and the cruise flying lift–drag ratio is greater than 15 at a low Reynolds number. Its pitching moment has the phenomenon of a “water mound” forming and breaking at the water cross-over process. The present method and the bionic variant configuration provide a feasible water cross-over design and analysis strategy for bionic UAAVs. Full article

This study presents the design and evaluation of a prototype snake-like robot that possesses an actuation system based on shape memory alloys (SMAs). The device is constructed based on a modular structure of links connected by two degrees of freedom links utilizing Cardan joints, where each degree of freedom is actuated by an agonist–antagonist mechanism using the SMA spring-shaped actuators to generate motion, which can be easily replaced once they reach a degradation point. The methodology for programming the spring shape into the SMA material is described in this work, as well as the instrumentation required for the monitoring and control of the actuators. A simplified design is presented to describe the way in which the motion is performed and the technical difficulties faced in manufacturing. Based on this information, the way in which the design is adapted to generate a feasible robotic system is described, and a mathematical model for the robot is developed to implement an independent joint controller. The feasibility of the implementation of the SMA actuators regarding the motion of the links is verified for the case of a joint, and the change in the shape of the snake robot is verified through the implementation of a set of tracking references based on a central pattern generator. The generated tracking results confirm the feasibility of the proposed mechanism in terms of performing snake gaits, as well as highlighting some of the drawbacks that should be considered in further studies. Full article

This study explores the efficacy of metaheuristic-based feature selection in improving machine learning performance for diagnosing sarcopenia. Extraction and utilization of features significantly impacting diagnosis efficacy emerge as a critical facet when applying machine learning for sarcopenia diagnosis. Using data from the 8th Korean Longitudinal Study on Aging (KLoSA), this study examines harmony search (HS) and the genetic algorithm (GA) for feature selection. Evaluation of the resulting feature set involves a decision tree, a random forest, a support vector machine, and naïve bayes algorithms. As a result, the HS-derived feature set trained with a support vector machine yielded an accuracy of 0.785 and a weighted F1 score of 0.782, which outperformed traditional methods. These findings underscore the competitive edge of metaheuristic-based selection, demonstrating its potential in advancing sarcopenia diagnosis. This study advocates for further exploration of metaheuristic-based feature selection’s pivotal role in future sarcopenia research. Full article

Clinical indications for the newly released Ti-Zr (Roxolid^®) alloy mini-implants (MDIs) aimed for overdenture (OD) retention in subjects with narrow alveolar ridges are not fully defined. The aim of this study was to analyze peri-implant and posterior edentulous area microstrains utilizing models of the mandible mimicking a “real” mouth situation with two (splinted with a bar or as single units) or four unsplinted Ti-Zr MDIs. The models were virtually designed from a cone beam computed tomography (CBCT) scan of a convenient patient and printed. The artificial mucosa was two millimeters thick. After MDI insertion, the strain gauges were bonded on the oral and vestibular peri-implant sites, and on distal edentulous areas under a denture. After attaching the ODs to MDIs, the ODs were loaded using a metal plate positioned on the first artificial molars (posterior loadings) bilaterally and unilaterally with 50, 100, and 150 N forces, respectively. During anterior loadings, the plate was positioned on the denture’s incisors and loaded with 50 and 100 N forces. Each loading was repeated 15 times. The means with standard deviations, and the significance of the differences (two- and three-factor MANOVA) were calculated. Variations in the MDI number, location, and splinting status elicited different microstrains. Higher loading forces elicited higher microstrains. Unilateral loadings elicited higher microstrains than bilateral and anterior loadings, especially on the loading side. Peri-implant microstrains were lower in the four-MDI single-unit model than in both two-MDI models (unsplinted and splinted). Posterior implants showed higher peri-implant microstrains than anterior in the four-MDI model. The splinting of the two-MDI did not have a significant effect on peri-implant microstrains but elicited lower microstrains in the posterior edentulous area. The strains did not exceed the bone reparatory mechanisms, although precaution and additional study should be addressed when two Ti-Zr MDIs support mandibular ODs. Full article

Wearable mechatronics for powered orthoses, exoskeletons and prostheses require improved soft actuation systems acting as ‘artificial muscles’ that are capable of large strains, high stresses, fast response and self-sensing and that show electrically safe operation, low specific weight and large compliance. Among the diversity of soft actuation technologies under investigation, pneumatic devices have been the focus, during the last couple of decades, of renewed interest as an intrinsically soft artificial muscle technology, due to technological advances stimulated by applications in soft robotics. As of today, quite a few solutions are available to endow a pneumatic soft device with linear actuation and self-sensing ability, while also easily achieving these features with off-the-shelf materials and low-cost fabrication processes. Here, we describe a simple process to make self-sensing pneumatic actuators, which may be used as ‘inverse artificial muscles’, as, upon pressurisation, they elongate instead of contracting. They are made of an elastomeric tube surrounded by a plastic coil, which constrains radial expansions. As a novelty relative to the state of the art, the self-sensing ability was obtained with a piezoresistive stretch sensor shaped as a conductive elastomeric body along the tube’s central axis. Moreover, we detail, also by means of video clips, a step-by-step manufacturing process, which uses off-the-shelf materials and simple procedures, so as to facilitate reproducibility. Full article

In complex and dynamic environments, traditional pursuit–evasion studies may face challenges in offering effective solutions to sudden environmental changes. In this paper, a bio-inspired neural network (BINN) is proposed that approximates a pursuit–evasion game from a neurodynamic perspective instead of formulating the problem as a differential game. The BINN is topologically organized to represent the environment with only local connections. The dynamics of neural activity, characterized by the neurodynamic shunting model, enable the generation of real-time evasive trajectories with moving or sudden-change obstacles. Several simulation and experimental results indicate that the proposed approach is effective and efficient in complex and dynamic environments. Full article

We propose a new nature- and neuro-science-inspired algorithm for spatiotemporal learning and prediction based on sequential recall and vector symbolic architecture. A key novelty is the learning of spatial and temporal patterns as decoupled concepts where the temporal pattern sequences are constructed using the learned spatial patterns as an alphabet of elements. The decoupling, motivated by cognitive neuroscience research, provides the flexibility for fast and adaptive learning with dynamic changes to data and concept drift and as such is better suited for real-time learning and prediction. The algorithm further addresses several key computational requirements for predicting the next occurrences based on real-life spatiotemporal data, which have been found to be challenging with current state-of-the-art algorithms. Firstly, spatial and temporal patterns are detected using unsupervised learning from unlabeled data streams in changing environments; secondly, vector symbolic architecture (VSA) is used to manage variable-length sequences; and thirdly, hyper dimensional (HD) computing-based associative memory is used to facilitate the continuous prediction of the next occurrences in sequential patterns. The algorithm has been empirically evaluated using two benchmark and three time-series datasets to demonstrate its advantages compared to the state-of-the-art in spatiotemporal unsupervised sequence learning where the proposed ST-SOM algorithm is able to achieve 45% error reduction compared to HTM algorithm. Full article

The metastable vaterite polymorph of calcium carbonate (CaCO₃) holds significant practical importance, particularly in regenerative medicine, drug delivery, and various personal care products. Controlling the size and morphology of vaterite particles is crucial for biomedical applications. This study explored the synergistic effect of ultrasonic (US) irradiation and acidic amino acids on CaCO₃ synthesis, specifically the size, dispersity, and crystallographic phase of curved-edge vaterite with chiral toroids (chiral-curved vaterite). We employed 40 kHz US irradiation and introduced L- or D-aspartic acid as an additive for the formation of spheroidal chiral-curved vaterite in an aqueous solution of CaCl₂ and Na₂CO₃ at 20 ± 1 °C. Chiral-curved vaterites precipitated through mechanical stirring (without US irradiation) exhibited a particle size of approximately 15 μm, whereas those formed under US irradiation were approximately 6 μm in size and retained their chiral topoid morphology. When a fluorescent dye was used for the analysis of loading efficiency, the size-reduced vaterites with chiral morphology, produced through US irradiation, exhibited a larger loading efficiency than the vaterites produced without US irradiation. These results hold significant value for the preparation of biomimetic chiral-curved CaCO₃, specifically size-reduced vaterites, as versatile biomaterials for material filling, drug delivery, and bone regeneration. Full article

The back support exoskeletons have garnered significant attention to alleviate musculoskeletal injuries, prevalent in industrial settings. In this paper, we propose AeBS, a quasi-passive back-support exoskeleton developed to provide variable assistive torque across the entire range of hip joint motion, for tasks with frequent load changes. AeBS can adjust the assistive torque levels while minimizing energy for the torque variation without constraining the range of motion of the hip joint. To match the requisite assistance levels for back support, a compact variable gravity compensation module with reinforced elastic elements is applied to AeBS. Additionally, we devised a bio-inspired hip joint mechanism that mimics the configuration of the human hip axis to ensure the free body motion of the wearer, significantly affecting assistive torque transmission and wearing comfort. Benchtop testing showed that AeBS has a variable assistive torque range of 5.81 Nm (ranging from 1.23 to 7.04 Nm) across a targeted hip flexion range of 135°. Furthermore, a questionnaire survey revealed that the bio-inspired hip joint mechanism effectively facilitates the transmission of the intended assistive torque while enhancing wearer comfort. Full article

The finger workspace is crucial for performing various grasping tasks. Thus, various soft rehabilitation gloves have been developed to assist individuals with paralyzed hands in activities of daily living (ADLs) or rehabilitation training. However, most soft robotic glove designs are insufficient to assist with various hand postures because most of them use an underactuated mechanism for design simplicity. Therefore, this paper presents a methodology for optimizing the design of a high-degree-of-freedom soft robotic glove while not increasing the design complexity. We defined the required functional workspace of the index finger based on ten frequently used grasping postures in ADLs. The design optimization was achieved by simulating the proposed finger–robot model to obtain a comparable workspace to the functional workspace. In particular, the moment arm length for extension was optimized to facilitate the grasping of large objects (precision disk and power sphere), whereas a torque-amplifying routing design was implemented to aid the grasping of small objects (lateral pinch and thumb–two-finger pinch). The effectiveness of the optimized design was validated through testing with a stroke survivor and comparing the assistive workspace. The observed workspace demonstrated that the optimized glove design could assist with nine out of the ten targeted grasping posture functional workspaces. Furthermore, the assessment of the grasping speed and force highlighted the glove’s usability for various rehabilitation activities. We also present and discuss a generalized methodology to optimize the design parameters of a soft robotic glove that uses an underactuated mechanism to assist the targeted workspace. Overall, the proposed design optimization methodology serves as a tool for developing advanced hand rehabilitation robots, as it offers insight regarding the importance of routing optimization in terms of the workspace. Full article

Biological fish exhibit a remarkably broad-spectrum visual perception capability. Inspired by the eye arrangement of biological fish, we design a fish-like binocular vision system, thereby endowing underwater bionic robots with an exceptionally broad visual perception capacity. Firstly, based on the design principles of binocular visual field overlap and tangency to streamlined shapes, a fish-like vision system is developed for underwater robots, enabling wide-field underwater perception without a waterproof cover. Secondly, addressing the significant distortion and parallax of the vision system, a visual field stitching algorithm is proposed to merge the binocular fields of view and obtain a complete perception image. Thirdly, an orientation alignment method is proposed that draws scales for yaw and pitch angles in the stitched images to provide a reference for the orientation of objects of interest within the field of view. Finally, underwater experiments evaluate the perception capabilities of the fish-like vision system, confirming the effectiveness of the visual field stitching algorithm and the orientation alignment method. The results show that the constructed vision system, when used underwater, achieves a horizontal field of view of 306.56°. The conducted work advances the visual perception capabilities of underwater robots and presents a novel approach to and insight for fish-inspired visual systems. Full article

Malignant tumors have become one of the serious public health problems in human safety and health, among which the chest and abdomen diseases account for the largest proportion. Early diagnosis and treatment can effectively improve the survival rate of patients. However, respiratory motion in the chest and abdomen can lead to uncertainty in the shape, volume, and location of the tumor, making treatment of the chest and abdomen difficult. Therefore, compensation for respiratory motion is very important in clinical treatment. The purpose of this review was to discuss the research and development of respiratory movement monitoring and prediction in thoracic and abdominal surgery, as well as introduce the current research status. The integration of modern respiratory motion compensation technology with advanced sensor detection technology, medical-image-guided therapy, and artificial intelligence technology is discussed and analyzed. The future research direction of intraoperative thoracic and abdominal respiratory motion compensation should be non-invasive, non-contact, use a low dose, and involve intelligent development. The complexity of the surgical environment, the constraints on the accuracy of existing image guidance devices, and the latency of data transmission are all present technical challenges. Full article

This review will present the latest research related to the production and application of spider silk and silk-based materials in reconstructive and regenerative medicine and tissue engineering, with a focus on musculoskeletal tissues, and including skin regeneration and tissue repair of bone and cartilage, ligaments, muscle tissue, peripheral nerves, and artificial blood vessels. Natural spider silk synthesis is reviewed, and the further recombinant production of spider silk proteins. Research insights into possible spider silk structures, like fibers (1D), coatings (2D), and 3D constructs, including porous structures, hydrogels, and organ-on-chip designs, have been reviewed considering a design of bioactive materials for smart medical implants and drug delivery systems. Silk is one of the toughest natural materials, with high strain at failure and mechanical strength. Novel biomaterials with silk fibroin can mimic the tissue structure and promote regeneration and new tissue growth. Silk proteins are important in designing tissue-on-chip or organ-on-chip technologies and micro devices for the precise engineering of artificial tissues and organs, disease modeling, and the further selection of adequate medical treatments. Recent research indicates that silk (films, hydrogels, capsules, or liposomes coated with silk proteins) has the potential to provide controlled drug release at the target destination. However, even with clear advantages, there are still challenges that need further research, including clinical trials. Full article

The frog-inspired jumping robot is an interesting topic in the field of biomechanics and bionics. However, due to the frog’s explosive movement and large range of joint motion, it is very difficult to make their structure completely bionic. To obtain the optimal jumping motion model, the musculoskeletal structure, jumping movement mechanism, and characteristics of frogs are first systematically analyzed, and the corresponding structural and kinematic parameters are obtained. Based on biological characteristics, a model of the articular bone structure is created, which can fully describe the features of frog movement. According to the various factors affecting the frog’s jumping movement, mass and constraints are added, and the complex biological joint structure is simplified into four different jumping structure models. The jumping ground reaction force, velocity, and displacement of the center of mass, joint torque, and other motion information of these four models are obtained through ADAMS simulation to reveal the jumping movement mechanism and the influencing factors of frogs. Finally, various motion features are analyzed and compared to determine the optimal structural model of the comprehensive index, which provides a theoretical basis for the design of the frog-inspired jumping robot. Full article

In this paper, we explore a nonlinear interactive network system comprising nodalized flapping-wing micro air vehicles (FMAVs) to address the distributed $H_{\infty }$ state estimation problem associated with FMAVs. We enhance the model by introducing an information fusion function, leading to an information-fusionized estimator model. This model ensures both estimation accuracy and the completeness of FMAV topological information within a unified framework. To facilitate the analysis, each FMAV’s received signal is individually sampled using independent and time-varying samplers. Transforming the received signals into equivalent bounded time-varying delays through the input delay method yields a more manageable and analyzable time-varying nonlinear network error system. Subsequently, we construct a Lyapunov–Krasovskii functional (LKF) and integrate it with the refined Wirtinger and relaxed integral inequalities to derive design conditions for the FMAVs’ distributed $H_{\infty }$ state estimator, minimizing conservatism. Finally, we validate the effectiveness and superiority of the designed estimator through simulations. Full article

Knee osteoarthritis (OA), also known as degenerative arthritis, is a disease characterized by irreversible changes in the cartilage and bones comprising the joints, resulting in pain, impaired function, and deformity. Furthermore, independent of natural aging, the rate of change in joint cartilage has increased in recent years, which is mainly attributed to environmental factors. The rising incidence of knee-related disorders emphasizes the importance of analyzing the morphology and kinematics of knee structure. This study introduces a knee measurement system designed to replicate the motions of knee using 3D-printing technology, providing insights into knee mechanics with OA level. The research explores the stages of OA using the Kellgren–Lawrence (KL) grade scale, highlighting the variations in the force applied to the knee bone according to movement. The developed knee-simulation system, utilizing the four-bar-link theory, presents a novel approach to studying OA levels 0 to 4. As OA progresses, the cartilage deteriorates, affecting the movement of OA. The OA-based knee measurement system that incorporates soft tissues and skeletons can assist in developing a personalized diagnostic approach for knee disease. This will also help to enhance surgical effectiveness by facilitating the creation of personalized prosthetic joints for individual patients and offering a customized surgical simulation. Full article

This article contains the results of identifying the potential of coniferous trees to act as bioinspiration for the structural design of columns in single-story warehouses subjected to high wind velocity and severe seismic action. This study starts by analyzing the biomechanics of coniferous trees, continues with an abstraction of the relevant features, and ends with the transfer of a design methodology for long reinforced and prestressed concrete columns. To verify the applicability and validity of the mathematical relationships extracted from the bibliographic study to characterize the biomechanics of coniferous trees, a study site is conducted for Norway spruce trees felled by the wind in the Bilbor area. The design methodology for long reinforced and prestressed concrete columns bioinspired by the Norway spruce trees is experimentally validated using two case studies. The first case study deals with the effect of centric prestressing on long concrete columns, and the second on the influence of the walnut shell powder on the adhesion of the reinforcement in concrete. The case studies presented aim to transfer some characteristics from trees to reinforced concrete to improve the performance of long columns under horizontal forces. The results obtained indicate a good approximation of the trees’ structural behavior for this site and for ones investigated by other researchers in different forests. Full article

Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion and control strategies. Expanding upon our prior research in electric–pneumatic actuation (EPA), we present the mechanical and electrical designs of the latest developments in the EPA robot series. These include EPA Jumper, a human-sized segmented monoped robot, and its extension EPA Walker, a human-sized bipedal robot. Both replicate the human weight and inertia distributions, featuring co-actuation through electrical motors and pneumatic artificial muscles. These low-cost modular platforms, with considerations for degrees of freedom and redundant actuation, (1) provide opportunities to study different locomotor subfunctions—stance, swing, and balance; (2) help investigate the role of actuation schemes in tasks such as hopping and walking; and (3) allow testing hypotheses regarding biological locomotors in real-world physical test benches. Full article

Chronic total occlusion (CTO) is one of the most severe and sophisticated vascular stenosis because of complete blockage, greater operation difficulty, and lower procedural success rate. This study proposes a hydraulic-driven soft robot imitating the earthworm’s locomotion to assist doctors or operators in actively opening thrombi in coronary or peripheral artery vessels. Firstly, a three-actuator bionic soft robot is developed based on earthworms’ physiological structure. The soft robot’s locomotion gait inspired by the earthworm’s mechanism is designed. Secondly, the influence of structure parameters on actuator deformation, stress, and strain is explored, which can help us determine the soft actuators’ optimal structure parameters. Thirdly, the relationship between hydraulic pressure and actuator deformation is investigated by performing finite element analysis using the bidirectional fluid–structure interaction (FSI) method. The kinematic models of the soft actuators are established to provide a valuable reference for the soft actuators’ motion control. Full article

Proteins in the crowded environment of human cells have often been studied regarding nonspecific interactions, misfolding, and aggregation, which may cause cellular malfunction and disease. Specifically, proteins with high abundance are more susceptible to these issues due to the law of mass action. Therefore, the surfaces of highly abundant cytoplasmic (HAC) proteins directly exposed to the environment can exhibit specific physicochemical, structural, and geometrical characteristics that reduce nonspecific interactions and adapt to the environment. However, the quantitative relationships between the overall surface descriptors still need clarification. Here, we used machine learning to identify HAC proteins using hydrophobicity, charge, roughness, secondary structures, and B-factor from the protein surfaces and quantified the contribution of each descriptor. First, several supervised learning algorithms were compared to solve binary classification problems for the surfaces of HAC and extracellular proteins. Then, logistic regression was used for the feature importance analysis of descriptors considering model performance (80.2% accuracy and 87.6% AUC) and interpretability. The HAC proteins showed positive correlations with negatively and positively charged areas but negative correlations with hydrophobicity, the B-factor, the proportion of beta structures, roughness, and the proportion of disordered regions. Finally, the details of each descriptor could be explained concerning adaptative surface strategies of HAC proteins to regulate nonspecific interactions, protein folding, flexibility, stability, and adsorption. This study presented a novel approach using various surface descriptors to identify HAC proteins and provided quantitative design rules for the surfaces well-suited to human cellular crowded environments. Full article