Biomimetics, Volume 9, Issue 5 (May 2024) – 43 articles

Insects, renowned for their abundant and renewable biomass, stand at the forefront of biomimicry-inspired research and offer promising alternatives for chitin and chitosan production considering mounting environmental concerns and the inherent limitations of conventional sources. This comprehensive review provides a meticulous exploration of the current state of insect-derived chitin and chitosan, focusing on their sources, production methods, characterization, physical and chemical properties, and emerging biomedical applications. Abundant insect sources of chitin and chitosan, from the Lepidoptera, Coleoptera, Orthoptera, Hymenoptera, Diptera, Hemiptera, Dictyoptera, Odonata, and Ephemeroptera orders, were comprehensively summarized. A variety of characterization techniques, including spectroscopy, chromatography, and microscopy, were used to reveal their physical and chemical properties like molecular weight, degree of deacetylation, and crystallinity, laying a solid foundation for their wide application, especially for the biomimetic design process. The examination of insect-derived chitin and chitosan extends into a wide realm of biomedical applications, highlighting their unique advantages in wound healing, tissue engineering, drug delivery, and antimicrobial therapies. Their intrinsic biocompatibility and antimicrobial properties position them as promising candidates for innovative solutions in diverse medical interventions. Full article

This study presents a novel solution for ambient assisted living (AAL) applications that utilizes spiking neural networks (SNNs) and reconfigurable neuromorphic processors. As demographic shifts result in an increased need for eldercare, due to a large elderly population that favors independence, there is a pressing need for efficient solutions. Traditional deep neural networks (DNNs) are typically energy-intensive and computationally demanding. In contrast, this study turns to SNNs, which are more energy-efficient and mimic biological neural processes, offering a viable alternative to DNNs. We propose asynchronous cellular automaton-based neurons (ACANs), which stand out for their hardware-efficient design and ability to reproduce complex neural behaviors. By utilizing the remote supervised method ($ReSuMe$), this study improves spike train learning efficiency in SNNs. We apply this to movement recognition in an elderly population, using motion capture data. Our results highlight a high classification accuracy of $83.4\%$, demonstrating the approach’s efficacy in precise movement activity classification. This method’s significant advantage lies in its potential for real-time, energy-efficient processing in AAL environments. Our findings not only demonstrate SNNs’ superiority over conventional DNNs in computational efficiency but also pave the way for practical neuromorphic computing applications in eldercare. Full article

In order to reduce the toxicological impact on healthy cells and to improve the therapeutic response, many drug delivery systems have been fabricated and analysed, involving the use of different natural and synthetic materials at macro-, micro- and nanoscales. Among the natural materials which have demonstrated a huge potential for the development of effective drug delivery systems, silk fibroin has emerged for its excellent biological properties and for the possibility to be processed in a wide range of forms, which can be compliant with multiple active molecules and pharmaceutical ingredients for the treatment of various diseases. This review aims at presenting silk fibroin as an interesting biopolymer for applications in drug delivery systems, exploring the results obtained in recent works in terms of technological progress and effectiveness in vitro and in vivo. Full article

Unidirectional porous hydroxyapatite (UDPHAp) was developed as a remarkable scaffold characterized by a distinct structure with unidirectional pores oriented in the horizontal direction and connected through interposes. We evaluated the radiographic changes, clinical outcomes, and complications following UDPHAp implantation for the treatment of bone tumors. Excellent bone formation within and around the implant was observed in all patients treated with intralesional resection and UDPHAp implantation for benign bone tumors. The absorption of UDPHAp and remodeling of the bone marrow space was observed in 45% of the patients at a mean of 17 months postoperatively and was significantly more common in younger patients. Preoperative cortical thinning was completely regenerated in 84% of patients at a mean of 10 months postoperatively. No complications related to the implanted UDPHAp were observed. In a pediatric patient with bone sarcoma, when the defect after fibular resection was filled with UDPHAp implants, radiography showed complete resorption of the implant and clear formation of cortex and marrow in the resected part of the fibula. The patient could walk well without crutches and participate in sports activities. UDPHAp is a useful bone graft substitute for the treatment of benign bone tumors, and the use of this material has a low complication rate. We also review and discuss the potential of UDPHAp as a bone graft substitute in the clinical setting of orthopedic surgery. Full article

According to the Magnus principle, a rotating cylinder experiences a lateral force perpendicular to the incoming flow direction. This phenomenon can be harnessed to boost the lift of an airfoil by positioning a rotating cylinder at the leading edge. In this study, we simulate flapping-wing motion using the sliding mesh technique in a heaving coordinate system to investigate the energy harvesting capabilities of Magnus effect flapping wings (MEFWs) featuring a leading-edge rotating cylinder. Through analysis of the flow field vortex structure and pressure distribution, we explore how control parameters such as gap width, rotational speed ratio, and phase difference of the leading-edge rotating cylinder impact the energy harvesting characteristics of the flapping wing. The results demonstrate that MEFWs effectively mitigate the formation of leading-edge vortices during wing motion. Consequently, this enhances both lift generation and energy harvesting capability. MEFWs with smaller gap widths are less prone to induce the detachment of leading-edge vortices during motion, ensuring a higher peak lift force and an increase in the energy harvesting efficiency. Moreover, higher rotational speed ratios and phase differences, synchronized with wing motion, can prevent leading-edge vortex generation during wing motion. All three control parameters contribute to enhancing the energy harvesting capability of MEFWs within a certain range. At the examined Reynolds number, the optimal parameter values are determined to be $a^{\ast }$ = 0.0005, R = 3, and ${\varphi }_0$ = 0°. Full article

One of the significant challenges in scaling agile software development is organizing software development teams to ensure effective communication among members while equipping them with the capabilities to deliver business value independently. A formal approach to address this challenge involves modeling it as an optimization problem: given a professional staff, how can they be organized to optimize the number of communication channels, considering both intra-team and inter-team channels? In this article, we propose applying a set of bio-inspired algorithms to solve this problem. We introduce an enhancement that incorporates ensemble learning into the resolution process to achieve nearly optimal results. Ensemble learning integrates multiple machine-learning strategies with diverse characteristics to boost optimizer performance. Furthermore, the studied metaheuristics offer an excellent opportunity to explore their linear convergence, contingent on the exploration and exploitation phases. The results produce more precise definitions for team sizes, aligning with industry standards. Our approach demonstrates superior performance compared to the traditional versions of these algorithms. Full article

The dung beetle optimization (DBO) algorithm, a swarm intelligence-based metaheuristic, is renowned for its robust optimization capability and fast convergence speed. However, it also suffers from low population diversity, susceptibility to local optima solutions, and unsatisfactory convergence speed when facing complex optimization problems. In response, this paper proposes the multi-strategy improved dung beetle optimization algorithm (MDBO). The core improvements include using Latin hypercube sampling for better population initialization and the introduction of a novel differential variation strategy, termed “Mean Differential Variation”, to enhance the algorithm’s ability to evade local optima. Moreover, a strategy combining lens imaging reverse learning and dimension-by-dimension optimization was proposed and applied to the current optimal solution. Through comprehensive performance testing on standard benchmark functions from CEC2017 and CEC2020, MDBO demonstrates superior performance in terms of optimization accuracy, stability, and convergence speed compared with other classical metaheuristic optimization algorithms. Additionally, the efficacy of MDBO in addressing complex real-world engineering problems is validated through three representative engineering application scenarios namely extension/compression spring design problems, reducer design problems, and welded beam design problems. Full article

This paper explores if plants are capable of responding to human movement by changes in their electrical signals. Toward that goal, we conducted a series of experiments, where humans over a period of 6 months were performing different types of eurythmic gestures in the proximity of garden plants, namely salad, basil, and tomatoes. To measure plant perception, we used the plant SpikerBox, which is a device that measures changes in the voltage differentials of plants between roots and leaves. Using machine learning, we found that the voltage differentials over time of the plant predict if (a) eurythmy has been performed, and (b) which kind of eurythmy gestures has been performed. We also find that the signals are different based on the species of the plant. In other words, the perception of a salad, tomato, or basil might differ just as perception of different species of animals differ. This opens new ways of studying plant ecosystems while also paving the way to use plants as biosensors for analyzing human movement. Full article

Placental trophoblast invasion is critical for establishing the maternal–fetal interface, yet the mechanisms driving trophoblast-induced maternal arterial remodeling remain elusive. To address this gap, we developed a three-dimensional microfluidic placenta-on-chip model that mimics early pregnancy placentation in a hypoxic environment. By studying human umbilical vein endothelial cells (HUVECs) under oxygen-deprived conditions upon trophoblast invasion, we observed significant HUVEC artery remodeling, suggesting the critical role of hypoxia in placentation. In particular, we found that trophoblasts secrete matrix metalloproteinase (MMP) proteins under hypoxic conditions, which contribute to arterial remodeling by the degradation of extracellular matrix components. This MMP-mediated remodeling is critical for facilitating trophoblast invasion and proper establishment of the maternal–fetal interface. In addition, our platform allows real-time monitoring of HUVEC vessel contraction during trophoblast interaction, providing valuable insights into the dynamic interplay between trophoblasts and maternal vasculature. Collectively, our findings highlight the importance of MMP-mediated arterial remodeling in placental development and underscore the potential of our platform to study pregnancy-related complications and evaluate therapeutic interventions. Full article

Due to their advantages of good stability, adaptability, and flexibility, multi-legged robots are increasingly important in fields such as rescue, military, and healthcare. This study focuses on the millipede, a multi-segmented organism, and designs a novel multi-segment biomimetic robot based on an in-depth investigation of the millipede’s biological characteristics and locomotion mechanisms. Key leg joints of millipede locomotion are targeted, and a mathematical model of the biomimetic robot’s leg joint structure is established for kinematic analysis. Furthermore, a central pattern generator (CPG) control strategy is studied for multi-jointed biomimetic millipede robots. Inspired by the millipede’s neural system, a simplified single-loop CPG network model is constructed, reducing the number of oscillators from 48 to 16. Experimental trials are conducted using a prototype to test walking in a wave-like gait, walking with a leg removed, and walking on complex terrain. The results demonstrate that under CPG waveform input conditions, the robot can walk stably, and the impact of a leg failure on overall locomotion is acceptable, with minimal speed loss observed when walking on complex terrain. The research on the structure and motion control algorithms of multi-jointed biomimetic robots lays a technical foundation, expanding their potential applications in exploring unknown environments, rescue missions, agriculture, and other fields. Full article

In this paper, we describe a sheet-shaped throwable transforming robot. Sheet-type robots can change their shape to perform tasks according to the situation. Therefore, they are expected to be useful in places with many restrictions, such as disaster sites. However, most of them can only move slowly on the ground. Therefore, in order to actually deliver the robot to the disaster site, it must be carried manually. To solve this problem, we are developing a sheet-shaped robot that can be thrown from the sky. Previously developed prototypes could only move in the forward direction, and the transition from falling to walking was complicated and uncertain. In this paper, we report on a new prototype that improves on these shortcomings. Full article

Silk and silk derivatives have emerged as a possible alternative in surgical device development, offering mechanical strength, biocompatibility, and environmental sustainability. Through a systematic review following PRISMA guidelines, this study evaluated silk fibroin’s application across pre-clinical and clinical settings, focusing on its role as screws and plates for osteofixation. A comprehensive search yielded 245 studies, with 33 subjected to full-text review and 15 ultimately included for qualitative analysis. The findings underscore silk fibroin’s superior properties, including its tunable degradation rates and ability to be functionalized with therapeutic agents. In vivo and in vitro studies demonstrated its efficacy in enhancing bone healing, offering improved outcomes in osteofixation, particularly for craniofacial defects. Silk fibroin’s remarkable attributes in biodegradation and drug release capabilities underscore its potential to enhance patient care. Ultimately, silk fibroin’s integration into surgical practices promises a revolution in patient outcomes and environmental sustainability. Its versatility, coupled with the continuous progress in fabrication techniques, signals a promising horizon for its widespread acceptance in the medical field, potentially establishing a new benchmark in surgical treatment. Further research is expected to solidify the transition of silk products from basic science to patient care, paving the way for widespread use in various surgical applications. Full article

Triply periodic minimal surfaces (TPMSs) are found in many natural objects including butterfly wings, sea urchins, and biological membranes. They simultaneously have zero mean curvature at every point and a crystallographic group symmetry. A metamaterial can be created from such periodic surfaces or used as a reinforcement of a composite material. While a TPMS as a mathematical object has been known since 1865, only novel additive manufacturing (AM) technology made it possible to fabricate cellular materials with complex TPMS shapes. Cellular TPMS-based metamaterials have remarkable properties related to wetting/liquid penetration, shock absorption, and the absence of stress concentrators. Recent studies showed that TPMSs are also found in natural crystals when electron surfaces are considered. Artificial crystal-inspired metamaterials mimic such crystals including zeolites and schwarzites. These metamaterials are used for shock, acoustic waves, and vibration absorption, and as structural materials, heat exchangers, and for other applications. The choice of the crystalline cell of a material, as well as its microstructure, plays a decisive role in its properties. The new area of crystal-inspired materials has many common features with traditional biomimetics with models being borrowed from nature and adjusted for engineering applications. Full article

The purpose of this study was to evaluate the repair process in rat calvaria filled with synthetic biphasic bioceramics (Plenum^® Osshp-70:30, HA:βTCP) or autogenous bone, covered with a polydioxanone membrane (PDO). A total of 48 rats were divided into two groups (n = 24): particulate autogenous bone + Plenum^® Guide (AUTOPT+PG) or Plenum^® Osshp + Plenum^® Guide (PO+PG). A defect was created in the calvaria, filled with the grafts, and covered with a PDO membrane, and euthanasia took place at 7, 30, and 60 days. Micro-CT showed no statistical difference between the groups, but there was an increase in bone volume (56.26%), the number of trabeculae (2.76 mm), and intersection surface (26.76 mm²) and a decrease in total porosity (43.79%) in the PO+PG group, as well as higher values for the daily mineral apposition rate (7.16 µm/day). Histometric analysis presented material replacement and increased bone formation at 30 days compared to 7 days in both groups. Immunostaining showed a similar pattern between the groups, with an increase in proteins related to bone remodeling and formation. In conclusion, Plenum^® Osshp + Plenum^® Guide showed similar and sometimes superior results when compared to autogenous bone, making it a competent option as a bone substitute. Full article

The set-covering problem aims to find the smallest possible set of subsets that cover all the elements of a larger set. The difficulty of solving the set-covering problem increases as the number of elements and sets grows, making it a complex problem for which traditional integer programming solutions may become inefficient in real-life instances. Given this complexity, various metaheuristics have been successfully applied to solve the set-covering problem and related issues. This study introduces, implements, and analyzes a novel metaheuristic inspired by the well-established Growth Optimizer algorithm. Drawing insights from human behavioral patterns, this approach has shown promise in optimizing complex problems in continuous domains, where experimental results demonstrate the effectiveness and competitiveness of the metaheuristic compared to other strategies. The Growth Optimizer algorithm is modified and adapted to the realm of binary optimization for solving the set-covering problem, resulting in the creation of the Binary Growth Optimizer algorithm. Upon the implementation and analysis of its outcomes, the findings illustrate its capability to achieve competitive and efficient solutions in terms of resolution time and result quality. Full article

Previous studies on the clap–fling mechanism have predominantly focused on the initial downward and forward phases of flight in miniature insects, either during hovering or forward flight. However, this study presents the first comprehensive kinematic data of Coccinella septempunctata during climbing flight. It reveals, for the first time, that a clap-and-fling mechanism occurs during the initial upward and backward phase of the hind wings’ motion. This discovery addresses the previously limited understanding of the clap-and-fling mechanism by demonstrating that, during the clap motion, the leading edges of beetle’s wings come into proximity to form a figure-eight shape before rotating around their trailing edge to open into a “V” shape. By employing numerical solutions to solve Navier–Stokes (N-S) equations, we simulated both single hind wings’ and double hind wings’ aerodynamic conditions. Our findings demonstrate that this fling mechanism not only significantly enhances the lift coefficient by approximately 9.65% but also reduces the drag coefficient by about 1.7%, indicating an extension of the applicability range of this clap-and-fling mechanism beyond minute insect flight. Consequently, these insights into insect flight mechanics deepen our understanding of their biological characteristics and inspire advancements in robotics and biomimetics. Full article

Mechanical stimulation is prevalent within organisms, and appropriate regulation of such stimulation can significantly enhance cellular functions. Consequently, the in vitro construction and simulation of mechanical stimulation have emerged as a research hotspot in biomechanics. In recent years, a class of artificial muscles named electroactive polymers (EAPs), especially ionic EAPs, have shown promising applications in biomechanics. While several techniques utilizing ionic EAPs for cell mechanical stimulation have been reported, further research is needed to advance and enhance their practical applications. Here, we prepared a microactuator array based on ionic EAP artificial muscles for cell mechanical stimulation. As a preliminary effort, we created a 5 × 5 microactuator array on a supporting membrane by employing laser cutting. We evaluated the electro-actuation performance of the microactuators through experimental testing and numerical simulations, affirming the potential use of the microactuator array for cell mechanical stimulation. The devised approach could inspire innovative design concepts in the development of miniaturized intelligent electronic devices, not only in biomechanics and biomimetics but also in other related fields. Full article

The sand cat swarm optimization algorithm (SCSO) is a novel metaheuristic algorithm that has been proposed in recent years. The algorithm optimizes the search ability of individuals by mimicking the hunting behavior of sand cat groups in nature, thereby achieving robust optimization performance. It is characterized by few control parameters and simple operation. However, due to the lack of population diversity, SCSO is less efficient in solving complex problems and is prone to fall into local optimization. To address these shortcomings and refine the algorithm’s efficacy, an improved multi-strategy sand cat optimization algorithm (IMSCSO) is proposed in this paper. In IMSCSO, a roulette fitness–distance balancing strategy is used to select codes to replace random agents in the exploration phase and enhance the convergence performance of the algorithm. To bolster population diversity, a novel population perturbation strategy is introduced, aiming to facilitate the algorithm’s escape from local optima. Finally, a best–worst perturbation strategy is developed. The approach not only maintains diversity throughout the optimization process but also enhances the algorithm’s exploitation capabilities. To evaluate the performance of the proposed IMSCSO, we conducted experiments in the CEC 2017 test suite and compared IMSCSO with seven other algorithms. The results show that the IMSCSO proposed in this paper has better optimization performance. Full article

Biomimetic materials have become a promising alternative in the field of tissue engineering and regenerative medicine to address critical challenges in wound healing and skin regeneration. Skin-mimetic materials have enormous potential to improve wound healing outcomes and enable innovative diagnostic and sensor applications. Human skin, with its complex structure and diverse functions, serves as an excellent model for designing biomaterials. Creating effective wound coverings requires mimicking the unique extracellular matrix composition, mechanical properties, and biochemical cues. Additionally, integrating electronic functionality into these materials presents exciting possibilities for real-time monitoring, diagnostics, and personalized healthcare. This review examines biomimetic skin materials and their role in regenerative wound healing, as well as their integration with electronic skin technologies. It discusses recent advances, challenges, and future directions in this rapidly evolving field. Full article

This paper presents an improved pelican optimization algorithm (IPOA) to solve the economic load dispatch problem. The vertical crossover operator in the crisscross optimization algorithm is integrated to expand the diversity of the population in the local search phase. The optimal individual is also introduced to enhance its ability to guide the whole population and add disturbance factors to enhance its ability to jump out of the local optimal. The dimensional variation strategy is adopted to improve the optimal individual and speed up the algorithm’s convergence. The results of the IPOA showed that coal consumption was reduced by 0.0292%, 2.7273%, and 3.6739%, respectively, when tested on 10, 40, and 80-dimensional thermal power plant units compared to POA. The IPOA can significantly reduce the fuel cost of power plants. Full article

This pilot study aimed to evaluate the level of implant success after transcrestal sinus floor elevation (tSFE) using the osseodensification technique (OD) combined with beta-tricalcium phosphate (β-TCP) by analyzing clinical and radiographic results. Moreover, the increase in bone height was analyzed immediately after surgery, 3 months after, and before loading by taking standardized radiographic measurements. Thirteen patients, four males and nine females, with a mean age of 54.69 ± 5.86 years, requiring the placement of one implant in the upper posterior maxilla, with a residual bone height of <8 mm and a minimum bone width of 5 mm, participated in the study. The bone gain data was obtained using cone-beam computed tomography (CBCT) immediately after surgery and twelve months after the placement. The correlation between initial and final bone height with implant stability was also assessed. The results were analyzed using SPSS 23 software (p < 0.05). The results of the study indicated a 100% implant success rate after a follow-up period of twelve months. Preoperative main bone height was 5.70 ± 0.95 mm. The osseodensification technique allowed a significant increase of 6.65 ± 1.06 mm immediately after surgery. After a twelve-month follow-up, a graft material contraction of 0.90 ± 0.49 mm was observed. No correlation was observed between the bone height at the different times of the study and the primary stability of the implant. Considering the limitations of the size sample of this study, the osseodensification technique used for transcrestal sinus lift with the additional bone graft material (β-TCP) may provide a predictable elevation of the maxillary sinus floor, allowing simultaneous implant insertion with adequate stability irrespective of bone height limitations. Full article

Chronic wounds such as diabetic ulcers are a major complication in diabetes caused by hyperglycemia, prolonged inflammation, high oxidative stress, and bacterial bioburden. Bioactive biopolymers have been found to have a biological response in wound tissue microenvironments and are used for developing advanced tissue engineering strategies to enhance wound healing. These biopolymers possess innate bioactivity and are biodegradable, with favourable mechanical properties. However, their bioactivity is highly dependent on their structural properties, which need to be carefully considered while developing wound healing strategies. Biopolymers such as alginate, chitosan, hyaluronic acid, and collagen have previously been used in wound healing solutions but the modulation of structural/physico-chemical properties for differential bioactivity have not been the prime focus. Factors such as molecular weight, degree of polymerization, amino acid sequences, and hierarchical structures can have a spectrum of immunomodulatory, anti-bacterial, and anti-oxidant properties that could determine the fate of the wound. The current narrative review addresses the structure–function relationship in bioactive biopolymers for promoting healing in chronic wounds with emphasis on diabetic ulcers. This review highlights the need for characterization of the biopolymers under research while designing biomaterials to maximize the inherent bioactive potency for better tissue regeneration outcomes, especially in the context of diabetic ulcers. Full article

High vertical jumping motion, which enables a humanoid robot to leap over obstacles, is a direct reflection of its extreme motion capabilities. This article proposes a single sequential kino-dynamic trajectory optimization method to solve the whole-body motion trajectory for high vertical jumping motion. The trajectory optimization process is decomposed into two sequential optimization parts: optimization computation of centroidal dynamics and coherent whole-body kinematics. Both optimization problems converge on the common variables (the center of mass, momentum, and foot position) using cost functions while allowing for some tolerance in the consistency of the foot position. Additionally, complementarity conditions and a pre-defined contact sequence are implemented to constrain the contact force and foot position during the launching and flight phases. The whole-body trajectory, including the launching and flight phases, can be efficiently solved by a single sequential optimization, which is an efficient solution for the vertical jumping motion. Finally, the whole-body trajectory generated by the proposed optimized method is demonstrated on a real humanoid robot platform, and a vertical jumping motion of 0.5 m in height (foot lifting distance) is achieved. Full article

Recent advancements in biomimetics have spurred significant innovations in prosthetic limb development by leveraging the intricate designs and mechanisms found in nature. Biomimetics, also known as “nature-inspired engineering”, involves studying and emulating biological systems to address complex human challenges. This comprehensive review provides insights into the latest trends in biomimetic prosthetics, focusing on leveraging knowledge from natural biomechanics, sensory feedback mechanisms, and control systems to closely mimic biological appendages. Highlighted breakthroughs include the integration of cutting-edge materials and manufacturing techniques such as 3D printing, facilitating seamless anatomical integration of prosthetic limbs. Additionally, the incorporation of neural interfaces and sensory feedback systems enhances control and movement, while technologies like 3D scanning enable personalized customization, optimizing comfort and functionality for individual users. Ongoing research efforts in biomimetics hold promise for further advancements, offering enhanced mobility and integration for individuals with limb loss or impairment. This review illuminates the dynamic landscape of biomimetic prosthetic technology, emphasizing its transformative potential in rehabilitation and assistive technologies. It envisions a future where prosthetic solutions seamlessly integrate with the human body, augmenting both mobility and quality of life. Full article

To inhibit the deep conversion of partial oxidation products (POX-products) in C-H bonds’ functionalization utilizing O₂, 5-(4-(chloromethyl)phenyl)-10,15,20-tris(perfluorophenyl)porphyrin cobalt(II) and 5-(4-(chloromethyl)phenyl)-10,15,20-tris(perfluorophenyl)porphyrin copper(II) were immobilized on the surface of hybrid silica to conduct relay catalysis on the surface. Fluorocarbons with low polarity and heterogeneous catalysis were devised to decrease the convenient accessibility of polar POX-products to catalytic centers on the lower polar surface. Relay catalysis between Co and Cu was designed to utilize the oxidation intermediates alkyl hydroperoxides to transform more C-H bonds. Systematic characterizations were conducted to investigate the structure of catalytic materials and confirm their successful syntheses. Applied to C-H bond oxidation, not only deep conversion of POX-products was inhibited but also substrate conversion and POX-product selectivity were improved simultaneously. For cyclohexane oxidation, conversion was improved from 3.87% to 5.27% with selectivity from 84.8% to 92.3%, which was mainly attributed to the relay catalysis on the surface excluding products. The effects of the catalytic materials, product exclusion, relay catalysis, kinetic study, substrate scope, and reaction mechanism were also investigated. To our knowledge, a practical and novel strategy was presented to inhibit the deep conversion of POX-products and to achieve efficient and accurate oxidative functionalization of hydrocarbons. Also, a valuable protocol was provided to avoid over-reaction in other chemical transformations requiring high selectivity. Full article

The Dung beetle optimization (DBO) algorithm, devised by Jiankai Xue in 2022, is known for its strong optimization capabilities and fast convergence. However, it does have certain limitations, including insufficiently random population initialization, slow search speed, and inadequate global search capabilities. Drawing inspiration from the mathematical properties of the Sinh and Cosh functions, we proposed a new metaheuristic algorithm, Sinh–Cosh Dung Beetle Optimization (SCDBO). By leveraging the Sinh and Cosh functions to disrupt the initial distribution of DBO and balance the development of rollerball dung beetles, SCDBO enhances the search efficiency and global exploration capabilities of DBO through nonlinear enhancements. These improvements collectively enhance the performance of the dung beetle optimization algorithm, making it more adept at solving complex real-world problems. To evaluate the performance of the SCDBO algorithm, we compared it with seven typical algorithms using the CEC2017 test functions. Additionally, by successfully applying it to three engineering problems, robot arm design, pressure vessel problem, and unmanned aerial vehicle (UAV) path planning, we further demonstrate the superiority of the SCDBO algorithm. Full article

The traditional golden jackal optimization algorithm (GJO) has slow convergence speed, insufficient accuracy, and weakened optimization ability in the process of finding the optimal solution. At the same time, it is easy to fall into local extremes and other limitations. In this paper, a novel golden jackal optimization algorithm (SCMGJO) combining sine–cosine and Cauchy mutation is proposed. On one hand, tent mapping reverse learning is introduced in population initialization, and sine and cosine strategies are introduced in the update of prey positions, which enhances the global exploration ability of the algorithm. On the other hand, the introduction of Cauchy mutation for perturbation and update of the optimal solution effectively improves the algorithm’s ability to obtain the optimal solution. Through the optimization experiment of 23 benchmark test functions, the results show that the SCMGJO algorithm performs well in convergence speed and accuracy. In addition, the stretching/compression spring design problem, three-bar truss design problem, and unmanned aerial vehicle path planning problem are introduced for verification. The experimental results prove that the SCMGJO algorithm has superior performance compared with other intelligent optimization algorithms and verify its application ability in engineering applications. Full article

Preclinical testing of medical devices is an essential step in the product life cycle, whereas testing of cardiovascular implants requires specialised testbeds or numerical simulations using computer software Ansys 2016. Existing test setups used to evaluate physiological scenarios and test cardiac implants such as mock circulatory systems or isolated beating heart platforms are driven by sophisticated hardware which comes at a high cost or raises ethical concerns. On the other hand, computational methods used to simulate blood flow in the cardiovascular system may be simplified or computationally expensive. Therefore, there is a need for low-cost, relatively simple and efficient test beds that can provide realistic conditions to simulate physiological scenarios and evaluate cardiovascular devices. In this study, the concept design of a novel left ventricular simulator made of latex rubber and actuated by pneumatic artificial muscles is presented. The designed left ventricular simulator is geometrically similar to a native left ventricle, whereas the basal diameter and long axis length are within an anatomical range. Finite element simulations evaluating left ventricular twisting and shortening predicted that the designed left ventricular simulator rotates approximately 17 degrees at the apex and the long axis shortens around 11 mm. Experimental results showed that the twist angle is 18 degrees and the left ventricular simulator shortens 5 mm. Twist angles and long axis shortening as in a native left ventricle show it is capable of functioning like a native left ventricle and simulating a variety of scenarios, and therefore has the potential to be used as a test platform. Full article

Poly lactic acid (PLA) is one of the most commonly used bio-derived thermoplastic polymers in 3D and 4D printing applications. The determination of PLA surface properties is of capital importance in 3D/4D printing technology. The surface thermodynamic properties of PLA polymers were determined using the inverse gas chromatography (IGC) technique at infinite dilution. The determination of the retention volume of polar and non-polar molecules adsorbed on the PLA particles filling the column allowed us to obtain the dispersive, polar, and Lewis’s acid–base surface properties at different temperatures from 40 °C to 100 °C. The applied surface method was based on our recent model that used the London dispersion equation, the new chromatographic parameter function of the deformation polarizability, and the harmonic mean of the ionization energies of the PLA polymer and organic molecules. The application of this new method led to the determination of the dispersive and polar free surface energy of the adsorption of molecules on the polymeric material, as well as the glass transition and the Lewis acid–base constants. Four interval temperatures were distinguished, showing four zones of variations in the surface properties of PLA as a function of the temperature before and after the glass transition. The acid–base parameters of PLA strongly depend on the temperature. The accurate determination of the dispersive and polar surface physicochemical properties of PLA led to the work of adhesion of the polar organic solvents adsorbed on PLA. These results can be very useful for achieving reliable and functional 3D and 4D printed components. Full article