Biomimetics最新文献

Titanium and its alloys have been the material of choice for orthopedic implants due to their excellent physical properties as well as biocompatibility. However, titanium is not able to integrate with bone due to the mismatch of mechanical properties. Additionally, bone has a micro-nano hierarchy, which is absent on titanium's surface. A potential solution to the former is to make the surfaces porous to bring the mechanical properties closer to that of the bone, and a solution for the latter is to fabricate nanostructures. In this study, micro-porous titanium surfaces were hydrothermally treated using an alkali medium to fabricate nanostructures on the existing micro-porosity of the surface. The surface properties were evaluated using scanning electron microscopy, X-ray photoelectron spectroscopy, X-ray diffraction, and nanoindentation. The anti-bacterial properties of the surfaces were evaluated against Gram-positive and Gram-negative bacteria using fluorescence microscopy and scanning electron microscopy. Blood clotting is shown to improve the surface-to-bone integration; hence, whole blood clotting and platelet adhesion and activation were evaluated using a whole blood clotting assay, fluorescence microscopy, and scanning electron microscopy. The results indicate that nanostructured micro-porous titanium surfaces display significantly enhanced anti-bacterial properties as well as equivalent blood clotting characteristics compared to non-porous titanium surfaces.

Assisting patients with weakened hand and wrist strength during meals is essential. While various feeding devices have been developed, many do not utilize patients' residual finger functions, leading to an increase in the risk of disuse syndrome and loss of joy in life. Recently, assist-as-needed support for spoon grasping by soft hand rehabilitation devices has been studied. Moreover, in our previous study, we investigated finger motions for the required scooping angle and verified them with a dummy hand driven by soft actuators. However, eating with a spoon requires not only spoon grasping and rotating but also plunging the spoon into food and lifting it afterward. The goal of this study is to achieve self-feeding with spoons using soft actuators for individuals with partial finger disabilities. To address this, we measured scooping movements using inertial measurement units, identified feasible finger motions for spoon plunging and lifting, and verified our findings through experiments with a dummy hand driven by soft actuators. As a result, we found a way to achieve the two motions by regulating the moment applied to the spoon. These results highlight the potential of soft actuators for assisting scooping movements. This study marks an important step toward feeding assistance that leverages patients' residual finger functions.

This case report explores the innovative integration of robotic and biomechatronic technologies, including the Motore and Ultra+ devices and neuro-suits, in a 10-session rehabilitation program for a young adult with dystonic spastic tetraparesis. Notable improvements were observed in upper limb motor function, coordination, and quality of life as measured by an increase of 18 pints on the Fugl-Meyer scale and a 25% improvement in the Bartle Index. Range of motion measurements showed consistent improvements, with task execution times improving by 10 s. These findings suggest the potential of combining wearable, robotic, and biomechatronic systems to enhance neurorehabilitation. Further refinement of these technologies might support clinicians in maximizing their integration in therapeutics, despite technical issues like synchronization issues that must be overcome.

The growing reliance on mobile robots has resulted in applications where users have limited or no control over operating conditions. These applications require advanced controllers to ensure the system's performance by dynamically changing its parameters. Nowadays, online bioinspired controller tuning approaches are among the most successful and innovative tools for dealing with uncertainties and disturbances. Nevertheless, these bioinspired approaches present a main limitation in real-world applications due to the extensive computational resources required in their exhaustive search when evaluating the controller tuning of complex dynamics. This paper develops an online bioinspired controller tuning approach leveraging a surrogate modeling strategy for an omnidirectional mobile robot controller. The polynomial response surface method is incorporated as an identification stage to model the system and predict its behavior in the tuning stage of the indirect adaptive approach. The comparative analysis concerns state-of-the-art controller tuning approaches, such as online, offline robust, and offline non-robust approaches, based on bioinspired optimization. The results show that the proposal reduces its computational load by up to 62.85% while maintaining the controller performance regarding the online approach under adverse uncertainties and disturbances. The proposal also increases the controller performance by up to 93% compared to offline tuning approaches. Then, the proposal retains its competitiveness on mobile robot systems under adverse conditions, while other controller tuning approaches drop it. Furthermore, a posterior comparison against another surrogate tuning approach based on Gaussian process regression corroborates the proposal as the best online controller tuning approach by reducing the competitor's computational load by up to 91.37% while increasing its performance by 63%. Hence, the proposed controller tuning approach decreases the execution time to be applied in the evolution of the control system without deteriorating the closed-loop performance. To the best of the authors' knowledge, this is the first time that such a controller tuning strategy has been tested on an omnidirectional mobile robot.

To balance the diversity and stringency of Pareto solutions in multi-objective optimization, this paper introduces a multi-objective White Shark Optimization algorithm (MONSWSO) tailored for multi-objective optimization. MONSWSO integrates non-dominated sorting and crowding distance into the White Shark Optimization framework to select the optimal solution within the population. The uniformity of the initial population is enhanced through a chaotic reverse initialization learning strategy. The adaptive updating of individual positions is facilitated by an elite-guided forgetting mechanism, which incorporates escape energy and eddy aggregation behavior inspired by marine organisms to improve exploration in key areas. To evaluate the effectiveness of MONSWSO, it is benchmarked against five state-of-the-art multi-objective algorithms using four metrics: inverse generation distance, spatial homogeneity, spatial distribution, and hypervolume on 27 typical problems, including 23 multi-objective functions and 4 multi-objective project examples. Furthermore, the practical application of MONSWSO is demonstrated through an example of optimizing the design of subway tunnel foundation pits. The comprehensive results reveal that MONSWSO outperforms the comparison algorithms, achieving impressive and satisfactory outcomes.

This research aims to enhance the performance of unmanned aerial vehicles (UAVs) by investigating the impact of twisting wingtip (TWT) on UAVs' wing aeroelastic and structural behavior using MATLAB and ANSYS simulations. The study focuses on a simplified twisting wingtip design and its aeroelastic effect. This study includes both static and dynamic aeroelastic phenomena. Previous research has primarily focused on only flutter speed while neglecting divergence speed and lift-effectiveness in design results. Numerical and experimental validation underscores the model's fidelity and its practical applicability. The TWT is designed to exhibit a predominant torsional mode using a guide mode preference technique. The design results reveal that the twist morphing wing improves structural and aeroelastic performance due to its unique twisting deformation capabilities. Furthermore, this research contributes fundamental insights into a specific twist morphing wing concept, highlighting its potential to enhance UAV performance through twisting wingtip technologies. The torsional mode can be predetermined using the guide mode preference technique. Notably, the divergence speed analysis confirms that the twisting shaft position should not exceed the aerodynamic center, which is located at 0.2103 of the chord length. This serves as the theoretical foundation for the TWT design in this study. The adjustment of the TWT's twisting angle is confirmed to provide optimal divergence speed improvement within a range of 0% to 27.7%. Additionally, the relative aeroelastic efficiencies indicate that the highest lift effectiveness is 0.68% at a twisting angle of 30°, following an exponential relationship, which can be further extended to aircraft control laws. However, the relative efficiency of flutter speed is not significantly improved by the TWT, showing only a marginal improvement of 0% to 1.84% when twisting up and down, in accordance with previous research findings.

Biologically inspired product design (BIPD) inherently encompasses the concept of sustainability. It acquires inspiration from natural organisms, and the references in aspects such as form, structure, and function typically contribute to efficient resource utilization and environmentally friendly coexistence. However, past studies have mainly evaluated from the perspective of designers and researchers, which is relatively subjective. It is difficult to meet the real needs of industry and market. At the same time, the method of establishing indicators is not scientific enough, and the importance of indicators is not ranked. This research integrates the concept of sustainable design into the BIPD evaluation system, comprehensively considering the evaluation indices of different stakeholders such as sustainable designers, industrial designers, and users and decision-makers of design companies. By employing the analytic hierarchy process, a complete and systematic evaluation index model is constructed. This model can comprehensively and accurately screen and evaluate design proposals during the conceptual design stage of BIPD. Through this approach, it effectively averts resource waste caused by incorrect decisions in the production process, optimizes resource allocation, meets user requirements and vigorously promotes the sustainable development of BIPD throughout its entire life cycle.

Restoring strength, function, and mobility following an illness, accident, or surgery is the primary goal of upper arm rehabilitation. Exoskeletons offer adaptable support, enhancing patient engagement and accelerating recovery. This work proposes an adjustable, wearable robotic exoskeleton powered by electromyography (EMG) data for upper arm rehabilitation. Three activation levels-low, medium, and high-were applied to the EMG data to forecast the Pulse Width Modulation (PWM) based on the range of motion (ROM) angle. Conventional machine learning (ML) models, including K-Nearest Neighbor Regression (K-NNR), Support Vector Regression (SVR), and Random Forest Regression (RFR), were compared with neural network approaches, including Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTM) to determine the best ML model for the ROM angle prediction. The LSTM model emerged as the best predictor with a high accuracy of 0.96. The system achieved 0.89 accuracy in exoskeleton control and 0.85 accuracy in signal categorization. Additionally, the proposed exoskeleton demonstrated a 0.97 performance in ROM correction compared to conventional methods (p = 0.097). These findings highlight the potential of EMG-based, LSTM-enabled exoskeleton systems to deliver accurate and adaptive upper arm rehabilitation, particularly for senior citizens, by providing personalized and effective support.

Biomolecular adsorption has great significance in medical, environmental, and technological processes. Understanding adsorption equilibrium and binding kinetics is essential for advanced process implementation. This requires identifying intrinsic determinants that predict optimal adsorption properties at bio-hybrid interfaces. Solid-binding peptides (SBPs) have targetable intrinsic properties involving peptide-peptide and peptide-solid interactions, which result in high-affinity material-selective binding. Atomic force microscopy investigations confirmed this complex interplay of multi-step peptide assemblies in a cooperative modus. Yet, most studies report adsorption properties of SBPs using non-cooperative or single-step adsorption models. Using non-cooperative kinetic models for predicting cooperative self-assembly behavior creates an oversimplified view of peptide adsorption, restricting implementing SBPs beyond their current use. To address these limitations and provide insight into surface-level events during self-assembly, a novel method, the Frequency Response Cooperativity model, was developed. This model iteratively fits adsorption data through spectral analysis of several time-dependent kinetic parameters. The model, applied to a widely used gold-binding peptide data obtained using a quartz crystal microbalance with dissipation, verified multi-step assembly. Peak deconvolution of spectral plots revealed distinct differences in the size and distribution of the kinetic rates present during adsorption across the concentrations. This approach provides new fundamental insights into the intricate dynamics of self-assembly of biomolecules on surfaces.

Background: This case report outlines the clinical workflows for immediate implant placement for both maxillary central incisors and ceramic laminate veneers for the remaining teeth in the smile zone.

Methods: The patient's chief complaint was to improve her smile and address periapical infections with purulent exudate at the apex of her central incisors. Clinical and CBCT evaluations determined that the maxillary central incisors were non-restorable, while the lateral incisors and canines showed signs of incisal wear. Atraumatic extractions were performed for the central incisors, and immediate implants were placed with a 3D-printed surgical guide in conjunction with an autogenous soft tissue grafting procedure. Once the soft tissue between the central incisors was contoured with provisional implant restorations, minimally invasive veneer preparations were performed for porcelain laminate veneers. Final restorations were bonded under dental dam isolation.

Results: Single immediate implants for maxillary central incisors can be successfully paired with ceramic laminate veneers on adjacent teeth in the smile zone to replace non-restorable teeth in the esthetic zone.

Conclusions: Atraumatic tooth extraction, 3D implant planning with grafting procedures, and minimally invasive ceramic veneers can help in meeting patients' esthetic and functional expectations. Total isolation using a dental dam maximizes the bonding performance of ceramic restorations.