Biomimetics最新文献

The performance portrait method (PPM) can be characterized as a systematized digitalized version of the trial and error method-probably the most popular and very often used method of engineering work. Its digitization required the expansion of performance measures used to evaluate the step responses of dynamic systems. Based on process modeling, PPM also contributed to the classification of models describing linear and non-linear dynamic processes so that they approximate their dynamics using the smallest possible number of numerical parameters. From most bio-inspired procedures of artificial intelligence and optimization used for the design of automatic controllers, PPM is distinguished by the possibility of repeated application of once generated performance portraits (PPs). These represent information about the process obtained by evaluating the performance of setpoint and disturbance step responses for all relevant values of the determining loop parameters organized into a grid. It can be supported by the implementation of parallel calculations with optimized decomposition in the high-performance computing (HPC) cloud. The wide applicability of PPM ranges from verification of analytically calculated optimal settings achieved by various approaches to controller design, to the analysis as well as optimal and robust setting of controllers for processes where other known control design methods fail. One such situation is illustrated by an example of predictive integrating (PrI) controller design for processes with a dominant time-delayed sensor dynamics, representing a counterpart of proportional-integrating (PI) controllers, the most frequently used solutions in practice. PrI controllers can be considered as a generalization of the disturbance-response feedback-the oldest known method for the design of dead-time compensators by Reswick. In applications with dominant dead-time and loop time constants located in the feedback (sensors), as those, e.g., met in magnetoencephalography (MEG), it makes it possible to significantly improve the control performance. PPM shows that, despite the absence of effective analytical control design methods for such situations, it is possible to obtain high-quality optimal solutions for processes that require working with uncertain models specified by interval parameters, while achieving invariance to changes in uncertain parameters.

Natural armors found in animals like fish and armadillos offer inspiration for designing protective systems that balance puncture resistance and flexibility. Although segmented armors have been used historically, modern applications are hindered by a limited understanding of their mechanics. This study addresses these challenges by presenting two novel bio-inspired scale structures with overlapping and staggered configurations, modeled after the elasmoid designs found in fish. Their shapes differ significantly from other artificial scales commonly described in the literature, which are typically flat. Instead, these scales feature a support that extends vertically from the substrate, transitioning into an inclined surface that serves as the protective component. Finite element method tests evaluated their performance in puncture resistance and flexibility. The results showed that one type of scale provided better puncture resistance, while the other type offered greater flexibility. These findings highlight how small geometric variations can significantly influence the balance between protection and flexibility. The results offer new insights into the mechanisms of natural armor and propose innovative designs for personal protective equipment, such as bulletproof vests, protective gloves, and fireproof systems. The finite element simulations employed to test the protective systems can also serve as valuable tools for the scientific community to assess and refine designs.

This study conducts a meta-analysis of over 1000 abstracts to examine the use and consistency of the terminology in biomimetics, bioinspiration, biomimicry, and bionics, focusing on how these terms impact biological study design. Despite the increasing research in these areas, the ambiguous definitions of key terms complicate study design and interdisciplinary collaboration. The primary aim of this work is to analyse how biological studies in these fields are conceptualised and evaluated, particularly concerning the inconsistent use of terminology. By identifying discrepancies in term usage, we offer refined definitions and practical examples to improve the clarity of study design and research methodologies. Our findings underscore the importance of standardised terminology for ensuring that biological research is accurately designed and executed, leading to more rigorous experimental frameworks and better alignment across disciplines. This meta-analysis reveals how clearer, more consistent terminology can enhance study design in biologically inspired research fields.

The gut microbiota is a complex and dynamic ecosystem that plays a fundamental role in human health by regulating immunity, metabolism, and the gut-brain axis. Beyond its critical physiological functions, it has emerged as a rich source of inspiration for biomimetic innovations in healthcare and biotechnology. This review explores the transformative potential of microbiota-based biomimetics, focusing on key biological mechanisms such as resilience, self-regulation, and quorum sensing. These mechanisms have inspired the development of innovative applications, including personalized probiotics, synbiotics, artificial microbiomes, bioinspired biosensors, and bioremediation systems. Such technologies aim to emulate and optimize the intricate functions of microbial ecosystems, addressing challenges in healthcare and environmental sustainability. The integration of advanced technologies, such as artificial intelligence, bioengineering, and multi-omics approaches, has further accelerated the potential of microbiota biomimetics. These tools enable the development of precision therapies tailored to individual microbiota profiles, enhance the efficacy of diagnostic systems, and facilitate the design of environmentally sustainable solutions, such as waste-to-energy systems and bioremediation platforms. Emerging areas of innovation, including gut-on-chip models and synthetic biology, offer unprecedented opportunities for studying and applying microbiota principles in controlled environments. Despite these advancements, challenges remain. The replication of microbial complexity in artificial environments, ethical concerns regarding genetically engineered microorganisms, and equitable access to advanced therapies are critical hurdles that must be addressed. This review underscores the importance of interdisciplinary collaboration and public awareness in overcoming these barriers and ensuring the responsible development of microbiota-based solutions. By leveraging the principles of microbial ecosystems, microbiota biomimetics represents a promising frontier in healthcare and sustainability. This approach has the potential to revolutionize therapeutic strategies, redefine diagnostic tools, and address global challenges, paving the way for a more personalized, efficient, and sustainable future in medicine and biotechnology.

The mechanical properties of materials for spinal fixation can significantly affect spinal surgical outcomes. Traditional materials such as titanium exhibit high stiffness, which can lead to stress shielding and adjacent segment degeneration. This study investigates the biomechanical performance of titanium and PEEK (polyetheretherketone) in spinal fixation using finite element analysis, through the evaluation of the Shielding Strength Factor (SSF). Methods: A three-dimensional finite element analysis (FEA) model of an L4/L5 functional spinal unit was developed to simulate the mechanical behavior of three fixation systems: titanium screws and rods (model A), titanium screws with PEEK rods (model B), and PEEK screws and rods (model C). The analysis evaluated stress distribution and load transfer under physiological conditions, in comparison with the intact spine (baseline model). Results: The analysis showed that titanium fixation systems resulted in higher stress shielding effects, with a significant difference in stress distribution compared to PEEK. The maximum stress recorded in the neutral position was 24.145 MPa for PEEK, indicating better biomechanical compatibility. Conclusions: The results suggest that PEEK may be an attractive alternative to titanium for spinal fixation, promoting more healthy load transfer and minimizing the risk of stress shielding complications.

Soft arms, characterized by their compliance and adaptability, have gained significant attention in applications ranging from industrial automation to biomedical fields. Modeling these systems presents unique challenges due to their high degrees of freedom, nonlinear behavior, and complex material properties. This review provides a comprehensive overview of three primary modeling approaches: numerical methods, analytical techniques, and data-driven models. Numerical methods, including finite element analysis and multi-body dynamics, offer precise but computationally expensive solutions for simulating soft arm behaviors. Analytical models, rooted in continuum mechanics and simplified assumptions, provide insights into the fundamental principles while balancing computational efficiency. Data-driven approaches, leveraging machine learning and artificial intelligence, open new avenues for adaptive and real-time modeling by bypassing explicit physical formulations. The strengths, limitations, and application scenarios of each approach are systematically analyzed, and future directions for integrating these methodologies are discussed. This review aims to guide researchers in selecting and developing effective modeling strategies for advancing the field of soft robotic arm design and control.

Face recognition technology, despite its widespread use in various applications, still faces challenges related to occlusions, pose variations, and expression changes. Three-dimensional face recognition with depth information, particularly using point cloud-based networks, has shown effectiveness in overcoming these challenges. However, due to the limited extent of extensive 3D facial data and the non-rigid nature of facial structures, extracting distinct facial representations directly from point clouds remains challenging. To address this, our research proposes two key approaches. Firstly, we introduce a learning framework guided by a small amount of real face data based on morphable models with Gaussian processes. This system uses a novel method for generating large-scale virtual face scans, addressing the scarcity of 3D data. Secondly, we present a dual-branch network that directly extracts non-rigid facial features from point clouds, using kernel point convolution (KPConv) as its foundation. A local neighborhood adaptive feature learning module is introduced and employs context sampling technology, hierarchically downsampling feature-sensitive points critical for deep transfer and aggregation of discriminative facial features, to enhance the extraction of discriminative facial features. Notably, our training strategy combines large-scale face scanning data with 967 real face data from the FRGC v2.0 subset, demonstrating the effectiveness of guiding with a small amount of real face data. Experiments on the FRGC v2.0 dataset and the Bosphorus dataset demonstrate the effectiveness and potential of our method.

This paper investigates the integration of thermo-responsive materials into bio-inspired structures, combining biomimicry and adaptive technologies in architecture. A problem-based biomimetic approach and a morphological analogy with the plate-type snowflake-known for its lightness, transparency, and crystalline organisation-were adopted to develop the geometry of an architectural pavilion. This research highlights glass as a main constructive material, analysing the potential of thermochromic film and the hydrogel technique, both inserted in the context of thermo-responsiveness. In this regard, the focus is on adaptations to temperature changes, exploring how these materials can alter their properties in response to solar incidence, offering solutions for energy efficiency, thermal regulation, and environmental adaptation. The pavilion demonstrates that this integration is feasible, and this is supported by an interdisciplinary approach that combines materials science, bio-inspired design, and practical experimentation. It also highlights biomimicry's fundamental role as a tool for guiding the development of innovative architectural geometries, while thermo-responsive materials expand the possibilities for creating structures that are adaptable to temperature variations and solar exposure. The conclusion points to the applicability and relevance of this combination, highlighting the transformative potential of thermo-responsive materials in architectural projects, especially in the development of lightweight, transparent, and environmentally responsive structures.

Juvenile mantises can jump towards targets by rapidly extending their middle and hind legs. Here, we investigate how mantises can perform jumps from smooth surfaces such as those found on many plants. Stagmomantis theophila mantises possess two distinct types of attachment pads on each foot: three small proximal euplantulae ("heel pads") with microscopic cuticular ridges and one smooth large distal pair of euplantulae ("toe pad"). Microscopy showed that the surface contact of heel pads is strongly load-dependent; at low normal forces, they make only partial surface contact due to the ridges, but at higher loads they switch to larger areas in full contact. By analysing the kinematics of 64 jumps of 23 third-instar nymphs from glass surfaces and the foot contact areas of their accelerating legs, we show that heel and toe pads fulfil distinct roles. During the acceleration phase of jumps, the contact area of the hind legs' heel pads tripled, while that of the toe pad decreased strongly, and the toe pad sometimes detached completely before take-off. Although the middle legs also contribute to the jump, they showed a less consistent pattern; the contact areas of their heel and toe pads remained largely unchanged during acceleration. Our findings show that jumping mantises accelerate mainly by pushing with their hind legs and produce grip on smooth surfaces primarily with the heel pads on their proximal tarsus.

This study evaluated the internal and marginal accuracy (trueness and precision) of zirconia laminate veneers fabricated using the DLP printing and milling method, employing 3D analysis software program. The maxillary central incisor tooth of a typodont model was prepared by a dentist and scanned using a desktop scanner. An anatomical zirconia laminate was designed using computer-aided design (CAD) software and saved in a standard tessellation language (STL) format. Thirty zirconia laminates were manufactured using a milling machine (MLL group) and a DLP printer (PTL group). All the specimens were scanned, and their internal and marginal areas were edited accordingly. The root-mean-square value was used to assess the accuracy of the internal and marginal areas of the zirconia laminates. Statistical significance was evaluated using the Mann-Whitney U test. Statistically significant differences were found in RMS values for both groups in the internal and marginal areas (p < 0.001 and p = 0.034, respectively). The MLL and PTL groups differed significantly in terms of precision (p = 0.017), but not at the margin (p = 0.361). DLP-printed zirconia laminates demonstrated stable and consistent performance, making the technique a reliable option for producing esthetic prostheses.