Practical Applications Research Articles

Performance Analysis of Semi-refined Digital Forearm Modeling and Simplified Forearm Model in Electromagnetic Simulation

Objective: The objective of this study is to analyze the performance difference between simplified and digital models based on medical images. Methods: According to the characteristics of human anatomy, the finite element simulation software COMSOL Multiphysics 5.5 was employed to construct a simplified arm model using cylinders and a digital arm model based on Chinese digital human regarding electroacupuncture therapy as an example. A comparative analysis was then performed considering three aspects: mesh number, potential distribution, and resource consumption. Results: Through analysis, the digital arm model based on Chinese digital human requires significantly more mesh cells than the simplified arm model in mesh generation. Meanwhile, because the digital arm model based on the Chinese digital human fully expresses the nonuniformity of the tissue distribution in a real human body, its signal distribution in its interior is also relatively scattered, and the coupling potential slightly differs at the electrode vertex with the smallest change. In addition, the digital arm model has much higher resource consumption and computer hardware resource requirements compared with the simplified arm model. Conclusion: As a result, the digital model based on the Chinese digital human can more fully express the tissue distribution and electrical signal characteristics of a real human body. However, due to its high computational requirements, appropriate simplification can be selected to improve the computational efficiency of the model in practical applications.

Transdermal Drug Delivery System of Linagliptin Sustained-release Microparticle Gels: In vitro Characterization and In vivo Evaluation.

Linagliptin (LNG) exhibits poor bioavailability and numerous side effects, significantly limiting its use. Transdermal drug delivery systems (TDDS) offer a potential solution to overcome the first-pass effect and gastrointestinal reactions associated with oral formulations. The aim of this study was to develop LNG microparticle gels to enhance drug bioavailability and mitigate side effects. Linagliptin hyaluronic acid (LNG-HA) microparticles were prepared by spray drying method and their formulation was optimized via a one-factor method. The solubility and release were investigated using the slurry method. LNG-HA microparticle gels were prepared and optimised using in vitro transdermal permeation assay. The hypoglycaemic effect of the LNG-HA microparticle gel was examined on diabetic mice. The results indicated that the LNG-HA microparticle encapsulation rate was 84.46%. Carbomer was selected as the gel matrix for the microparticle gels. Compared to the oral API, the microparticle gel formulation demonstrated a distinct biphasic release pattern. In the first 30 minutes, only 43.56% of the drug was released, followed by a gradual release. This indicates that the formulation achieved a slow-release effect from a dual reservoir system. Furthermore, pharmacodynamic studies revealed a sustained hypoglycemic effect lasting for 48 hours with the LNG microparticle gel formulation. These findings signify that the LNG microparticle gel holds significant clinical value for providing sustained release and justifies its practical application.

Uncovering hidden prosocial behaviors underlying aggression motivation in mice and young children

BackgroundAnimals exhibit a wide range of social behaviors, including positive actions that promote social cohesion and negative behaviors associated with asserting dominance. While these behaviors are often viewed as opposites, they can also exist independently or coexist in complex ways, necessitating further investigation into their interrelationships.ResultsTo study the interplay between these two types of behaviors, we examined mouse social behaviors using resident-intruder assays and revealed a negative correlation between social aggression and prosocial allogrooming. Suppressing aggressive motivation through various manipulations, including social subordination, olfaction ablation, and inhibition of aggressive neural circuits, led to an increased display of allogrooming behavior. The mouse findings prompted us to further explore the relationship between aggression and prosocial behaviors in preschool children. Similarly, we observed a negative association between aggression and prosocial behaviors, which were potentially influenced by their inhibitory control abilities.ConclusionsThrough this cross-species study, we uncovered the inhibitory impact of aggressive neural circuits on mouse allogrooming and established a link between aggression and prosocial behaviors in children. These insights offer valuable implications for understanding and potentially influencing social interactions in both animal and human contexts, with potential applications in preschool education practices.

Improving thermal cracking and fatigue cracking performance of hard asphalt binders with bio-renewable additives

Traditional hard asphalt, due to its low cost and excellent mechanical properties, is considered a favorable material for resisting permanent deformation under high-temperature conditions. However, its limited stress relaxation ability at medium and low temperatures significantly impairs its capacity to meet the cracking resistance requirements. To address the limitation, this study synthesized three green and sustainable bio-renewable additives derived from high oleic rapeseed oil. These additives aimed to improve the performance of hard asphalt at medium- and low-temperature conditions, thereby broadening its potential for application in green and low-carbon construction practices. Bending Beam Rheometer (BBR) tests were conducted to determine the critical low-temperature difference (ΔTc) to evaluate the thermal cracking resistance of bio-modified hard asphalt. The effects of the bio-additives on fatigue cracking resistance of hard asphalt were investigated using rheological indices, crossover frequencies, Glover-Rowe (G-R) parameters, and Linear Amplitude Sweep (LAS) tests. The results indicated that bio-additives effectively alleviated the stress in hard asphalt and reduced the asphalt’s susceptibility to thermal cracking by improving the flexibility and stress relaxation of the hard asphalt at low temperatures. Furthermore, the bio-additives substantially improved the ductility and toughness of hard asphalt at intermediate temperatures by lowering its strain sensitivity and increasing its fatigue cracking resistance. Additionally, the high oleic rapeseed oil-based derivatives notably reduced hard asphalt binder’s cracking induced by aging. Among the three bio-additives, acrylated epoxidized high oleic rapeseed oil (AEHORO) and epoxidized high oleic rapeseed oil (EHORO) were noticed to exhibit the most significant improvements in thermal cracking resistance and anti-aging properties, demonstrating superior load-bearing capacity at low temperatures. Overall, the developed bio-additives significantly improved both the thermal cracking and fatigue damage resistance of traditional hard asphalt, thus expanding its applications in pavements for various regions.

Application of Photocatalytic Ozonation for the Remediation of Aquaculture Effluents: A Review

The growing global population and limitations in fish catch production have led to a surge in the demand for aquaculture. Contaminants of emerging concern (CEC) are frequently being detected at low levels in surface water. These CECs, which include previously unidentified or unregulated pollutants, pose potential risks to health and the environment, though their impacts are not yet fully understood. Extensive research studies have been proposed and undertaken to address the issue of aquaculture wastewater, aiming to minimize its impact and implement effective treatment methods. This review provides an analysis of various technologies used for treating aquaculture wastewater using advanced oxidation processes (AOPs) focusing on photocatalysis and ozonation. It examines their advantages and disadvantages, as well as their respective treatment efficacies, and discusses their potential applications in sustainable aquaculture practices complying with the Sustainable Development Goals of 1, 2, and 6 as well as being in line with the Environmental Social and Governance (ESG) framework.

AI-Driven IoT And Blockchain Integration In Industry 5.0 A Systematic Review Of Supply Chain Transformation

The integration of Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain technologies in Industry 5.0 has revolutionized supply chain management, offering unprecedented opportunities for efficiency, transparency, and sustainability. This systematic review, which analyzed 120 peer-reviewed articles published between 2018 and 2024, provides a comprehensive exploration of the transformative potential of these technologies. The findings reveal that the convergence of AI-driven predictive analytics, IoT-enabled real-time monitoring, and Blockchain's decentralized ledger enhances decision-making, streamlines operations, and fosters trust across supply chain networks. Moreover, the study highlights the critical role of these technologies in achieving Environmental, Social, and Governance (ESG) compliance, with applications in sustainable sourcing, ethical practices, and carbon footprint reduction. However, challenges such as scalability, interoperability, and organizational resistance remain significant barriers to adoption, underscoring the need for innovative solutions and interdisciplinary approaches. The review also identifies emerging opportunities, including the integration of quantum computing and digital twins, which promise to address existing limitations and redefine supply chain capabilities. By synthesizing insights from over 120 studies with a cumulative citation count exceeding 30,000, this research provides valuable perspectives on the current state, challenges, and future directions of integrated supply chain technologies in Industry 5.0, offering actionable insights for researchers and practitioners aiming to advance the field.

Particle size is an important factor influencing the effects of biochar return to woodland soils: An evaluation from the perspective of sapling growth and soil microbial carbon processes

Biochar can increase ecosystem carbon sequestration by promoting plant growth and stabilizing soil organic carbon (SOC). Biochar produced from forest waste typically varies in particle size and is frequently applied directly for soil enhancement without pulverization. The effects of different biochar particle sizes on sapling growth, woodland soil properties and microbial carbon processes are unclear. This study used field experiments to compare the effects of different biochar particle sizes on sapling growth and microbial metabolic entropy (qCO2). The impacting mechanisms were explored by examining soil physicochemical properties, enzyme activity, and microbial community structure. The application of forest waste (FW) and small particle biochar (SPBC, particle size<2 mm) did not significantly affect sapling growth. Conversely, middle particle biochar (MPBC, particle size 2–10 mm) and large particle biochar (LPBC, particle size>10 mm) reduced sapling biomass by 20.76% and 38.87%, respectively, compared to SPBC. MPBC and LPBC applications resulted in soil nutrient loss (total nitrogen and available phosphorus), inhibiting sapling growth. After 167 days, qCO2 rankings were as follows: FW (30.37 ± 5.18) (P<0.05)> LPBC (20.91 ± 3.62) > CK (16.21 ± 2.71) > MPBC (15.99 ± 3.54) > SPBC (7.8 ± 0.80) (P < 0.05). The rankings of organic carbon retention rates rankings were as follows: SPBC (85.14%) > LPBC (70.35%) > FW (67.31%) > CK (54.53%) > MPBC (51.96%). SPBC increased biochar-soil-microbe interactions, raised the relative proportion of k/r-strategy bacteria, reduced extracellular cellulase activity thus inhibit qCO2. In conclusion, small particle biochar (<2 mm), compared to larger-particle biochar, improves SOC sequestration without negatively affecting sapling growth. Therefore, particle size should be considered as a management indicator for biochar applications in artificial forest practices.

Biochar-induced changes in soil microbial communities: a comparison of two feedstocks and pyrolysis temperatures

BackgroundThe application of a biochar in agronomical soil offers a dual benefit of improving soil quality and sustainable waste recycling. However, utilizing new organic waste sources requires exploring the biochar’s production conditions and application parameters. Woodchips (W) and bone-meat residues (BM) after mechanical deboning from a poultry slaughterhouse were subjected to pyrolysis at 300 °C and 500 °C and applied to cambisol and luvisol soils at ratios of 2% and 5% (w/w).ResultsInitially, the impact of these biochar amendments on soil prokaryotes was studied over the course of one year. The influence of biochar variants was further studied on prokaryotes and fungi living in the soil, rhizosphere, and roots of Triticum aestivum L., as well as on soil enzymatic activity. Feedstock type, pyrolysis temperature, application dose, and soil type all played significant roles in shaping both soil and endophytic microbial communities. BM treated at a lower pyrolysis temperature of 300 °C increased the relative abundance of Pseudomonadota while causing a substantial decrease in soil microbial diversity. Conversely, BM prepared at 500 °C favored the growth of microbes known for their involvement in various nutrient cycles. The W biochar, especially when pyrolysed at 500 °C, notably affected microbial communities, particularly in acidic cambisol compared to luvisol. In cambisol, biochar treatments had a significant impact on prokaryotic root endophytes of T. aestivum L. Additionally, variations in prokaryotic community structure of the rhizosphere depended on the increasing distance from the root system (2, 4, and 6 mm). The BM biochar enhanced the activity of acid phosphatase, whereas the W biochar increased the activity of enzymes involved in the carbon cycle (β-glucosidase, β-xylosidase, and β-N-acetylglucosaminidase).ConclusionsThese results collectively suggest, that under appropriate production conditions, biochar can exert a positive influence on soil microorganisms, with their response closely tied to the biochar feedstock composition. Such insights are crucial for optimizing biochar application in agricultural practices to enhance soil health.

Self-Distillation for Randomized Neural Networks.

Knowledge distillation (KD) is a conventional method in the field of deep learning that enables the transfer of dark knowledge from a teacher model to a student model, consequently improving the performance of the student model. In randomized neural networks, due to the simple topology of network architecture and the insignificant relationship between model performance and model size, KD is not able to improve model performance. In this work, we propose a self-distillation pipeline for randomized neural networks: the predictions of the network itself are regarded as the additional target, which are mixed with the weighted original target as a distillation target containing dark knowledge to supervise the training of the model. All the predictions during multi-generation self-distillation process can be integrated by a multi-teacher method. By induction, we have additionally arrived at the methods for infinite self-distillation (ISD) of randomized neural networks. We then provide relevant theoretical analysis about the self-distillation method for randomized neural networks. Furthermore, we demonstrated the effectiveness of the proposed method in practical applications on several benchmark datasets.

Iron(III) Monoglycerolate as a New Biocompatible Precursor in the Synthesis of Bioactive Nanocomposite Glycerohydrogels.

Nanocomposite glycerohydrogels based on biocompatible elementcontaining glycerolates are of practicular interest for biomedical applications. Using two biocompatible precursors, silicon and iron glycerolates, a new bioactive nanocomposite silicon‒iron glycerolates hydrogel was obtained by sol-gel method. The composition and structural features of the hydrogel were studied using a complex of modern analytical techniques, including TEM, XRD, and AES. On the example of experimental animals hemostatic activity of the hydrogel was studied, as well as primary toxicological studies were carried out. The composition of dispersed phase and dispersion medium of silicon‒iron glycerolates hydrogel was determined. The structural features of hydrogel were revealed and its structure model was proposed. It was shown that silcon-iron glycerolates hydrogel is nontoxic, and exhibits pronounced hemostatic activity. Silicon-iron glycerolates hydrogel is a potential hemostatic agent for topical application in medical and veterinary practice.

Factors related to preoperative anxiety in older patients with sensory impairment: A cross-sectional study.

To identify the factors related to preoperative anxiety in older adults with sensory impairment. Descriptive quantitative research design. Study participants were 120 older adults admitted to a tertiary hospital in Seoul, South Korea to undergo eye or ear surgery. Data were collected from 11 February to 30 April 2023. The collected data were analysed using descriptive statistics, t-tests, ANOVA, and multiple regression analysis using SPSS 28.0. The study was reported following the STROBE checklist. Preoperative anxiety differed significantly according to gender (p = .002), average monthly household income (p < .001), subjective health status (p = .003), subjective vision loss (p = .004), one-sided or both-sided eye discomfort (p = .002), use of glasses (p = .010), subjective hearing loss (p = .022) and anxiety coping mechanisms (p < .001). The results of a multiple regression analysis on the significant variables identified that gender (β = .178, p = .036) and anxiety coping mechanisms (β = .336, p < .001) had the most significant effect on preoperative anxiety, with an explanatory power of 34.5%. The development and practical application of tailored nursing interventions catering to specific genders and anxiety coping mechanisms would contribute to reducing preoperative anxiety and providing efficient nursing care for older adults with sensory impairment.

Camouflaged Object Segmentation Based on Matching-Recognition-Refinement Network.

In the biosphere, camouflaged objects take the advantage of visional wholeness by keeping the color and texture of the objects highly consistent with the background, thereby confusing the visual mechanism of other creatures and achieving a concealed effect. This is also the main reason why the task of camouflaged object detection is challenging. In this article, we break the visual wholeness and see through the camouflage from the perspective of matching the appropriate field of view. We propose a matching-recognition-refinement network (MRR-Net), which consists of two key modules, i.e., the visual field matching and recognition module (VFMRM) and the stepwise refinement module (SWRM). In the VFMRM, various feature receptive fields are used to match candidate areas of camouflaged objects of different sizes and shapes and adaptively activate and recognize the approximate area of the real camouflaged object. The SWRM then uses the features extracted by the backbone to gradually refine the camouflaged region obtained by VFMRM, thus yielding the complete camouflaged object. In addition, a more efficient deep supervision method is exploited, making the features from the backbone input into the SWRM more critical and not redundant. Extensive experimental results demonstrate that our MRR-Net runs in real-time (82.6 frames/s) and significantly outperforms 30 state-of-the-art models on three challenging datasets under three standard metrics. Furthermore, MRR-Net is applied to four downstream tasks of camouflaged object segmentation (COS), and the results validate its practical application value. Our code is publicly available at: https://github.com/XinyuYanTJU/MRR-Net.

PHARMACOGNOSTICAL EVALUATION OF CINNAMOMUM ZEYLANICUM (BLUME.) BARK: A WIDELY USED TRADITIONAL INDIAN MEDICINE WITH PROMISING THERAPEUTIC POTENTIAL

Cinnamomum zeylanicum, commonly known as Dalchini or cinnamon, is a revered botanical species in Indian traditional medicine owing to its diverse therapeutic properties. This study presents a comprehensive botanical and pharmacognostic evaluation of zeylanicum bark aimed at understanding its medicinal potential and ensuring quality control measures. Botanical evaluation involved morphological characterization, including macroscopic and microscopic features, to identify the distinctive traits of zeylanicum bark. Additionally, physicochemical characteristics include total ash and acid-insoluble ash, moisture content, and water-soluble and alcohol-soluble extractive values were determined according to standard procedures. Pharmacognostic evaluation encompassed the determination of phytochemical constituents using various chemical tests. Primary and secondary metabolites, including tannins, alkaloids, flavonoids, phenols, and terpenoids, are present and investigated, providing insights into the chemical composition of zeylanicum bark. The research's conclusions add to establishing quality control parameters for zeylanicum bark, ensuring its authenticity, purity, and efficacy in traditional medicine formulations. Moreover, the detailed pharmacognostic analysis provides valuable information for further exploration of its therapeutic potential and pharmacological applications in modern healthcare practices.

The problem of student’s responsibility in the context of digitalization of education

Introduction. The article discusses some socio-psychological problems related to the change in the subjectivity of the student as the main actor of educational practices.Purpose setting. The purpose of this article is to discuss the acute problems of a student’s responsibility in the context of the emerging non-traditional nature of educational communications.Methodology and methods of the study. The discussion is conducted within the framework of the methodological principles of cognitivism and social constructionism, which today determine the vector of research related to the impact of digitalization on educational practices.Results. The thesis is updated that the change in the subjectivity of an individual (as a learning subject) in the context of convergence of AI applications in educational practices occurs in two main planes. The first of them is associated with the deformation (decrease) of student’s level of responsibility for performing educational practices «as specific learning actions». The second is that the determination of reducing responsibility is largely determined by the «moving»of the driver into the «comfort zone». In this zone, there is a «delegation»of choice and decision-making from the individual (subject, student) by AI application.Conclusion. Against the background of issues related to the «reliability of solutions»offered by AI and the lack of «digital literacy», the possibility of self-identification of the student and the level of his responsibility (as a real subject of educational practices) can be clearly questioned and requires methodological and methodical reflection.

Religion, secularism, and postsecularism in Chinese internet literature

Abstract Internet literature emerged in China in the 1990s and became commercialized in the early 2000s, with readers paying an access fee, which is split between literary platforms and their contracted writers, to access popular novels. While the most popular genre is fantasy, a type of imaginative literature devoted to invoking magic beyond the limits of empirical reality and scientific rationality, the primary source of magic for Chinese fantasy is traditional Chinese cosmology and its concrete applications in everyday practices. These ideas and practices, the onto-epistemic-practical foundation of Chinese religion before the twentieth century, were considered superstitious and targeted for elimination in modernizing and secularization processes. However, they have not only survived but taken up a new life in fantasy novels, which depict them as the antecedents of, alternatives to, or more advanced forms than modern scientific endeavors at engineering natural environments and enhancing human bodies. This is why I see online fantasy literature as a palimpsest bearing the traces of Chinese religion, Chinese secularism, and the social conditions of contemporary China. In bearing such traces, this literature exemplifies the postsecular.

Chitosan nanoparticles (CSNPs) conferred salinity tolerance in maize by upregulating E3 ubiquitin-protein ligase, P5CS1, HKT1, NHX1, and PMP3 genes.

This study explored the transcriptional behaviors of several candidate genes in response to the application of CSNPs (50 and 100 mgl-1) in maize seedlings grown under two salinity levels (NaCl of 0.07 and 0.14 gkg-1soil). Employing CSNPs at both concentrations mitigated the inhibitory role of salinity on the leaf and root fresh weights. The application of CSNPs enhanced the transcription of the E3 ubiquitin-protein ligase gene by an average of threefold, contrasted with the salinity controls. The Δ1-pyrroline-5-carboxylate synthetase (P5CS1) gene was upregulated in response to both individual and mixed treatments of CSNPs and salinity. The transcription of the high-affinity K+ transporter (HKT1) gene displayed an upward trend in response to the CSNPs and salinity treatments. The Na+/H+ exchangers (NHX1) gene exhibited a similar trend to that of the HKT1 gene. The utilization of CSNPs was accompanied by an upregulation in the plasma membrane proteolipid 3 (PMP3) gene, contrasted with the salinity controls. The phenylalanine ammonia-lyase (PAL) activity displayed an upward trend in response to the foliar application of CSNPs. The CSNPs at the 100 mgl-1 concentration were more capable of inducing the ascorbate peroxidase enzyme under both salinity conditions than the 50 mgl-1 dose. The simultaneous exposure of maize seedlings to CSNPs and salinity resulted in the drastic upregulation of the catalase activities. This study provides novel insights into the major mechanisms underlying the stress-mitigating effects of CSNPs, thereby providing a suitable platform for their application in sustainable agricultural practices.

Discrimination and precision of Continuous Glucose Monitoring in staging children with presymptomatic type 1 diabetes.

Staging and monitoring of pre-symptomatic type 1 diabetes includes the assessment for dysglycemia. To assess the ability of Continuous Glucose Monitoring (CGM) to differentiate between islet autoantibody-negative controls and early-stage type 1 diabetes and explore whether CGM classifiers predict progression to clinical diabetes. Children and adolescents participating in public health screening for islet autoantibodies in Bavaria, Germany were invited to undergo CGM with Dexcom G6. In total, 118 participated and valid data was obtained from 97 (57 female; median age 10 [range 3-17] years), including 46 with stage 1, 18 with stage 2, and 33 with no islet autoantibodies. Mean glucose during CGM in islet autoantibody-negative controls was high (median, 115.3 mg/dl) and varied substantially (IQR, 106.8-124.4). Eleven (33%) of the controls had more than 10% of glucose values above 140 mg/dl (TA140). Using thresholds corresponding to 100% specificity in controls, differences between controls and stage 1 and stage 2 were obtained for glucose standard deviation, TA140, TA160 and TA180. Elevations in any two of these parameters identified 12 (67%) with stage 2 and 9 (82%) of 11 participants who developed clinical diabetes within one year. However, there was marked variation within groups for all parameters and poor consistency observed in a second CGM performed in 18 participants. This study demonstrated the potential of integrating CGM into staging and monitoring of early-stage type 1 diabetes. However, substantial improvement in the precision of CGM is required for its application in routine monitoring practices.

Методика перетворення кодових послідовностей у відповідності до системи координат модуляційного диска

An analysis of current approaches used in the design of optical recording systems for modulation disks has been conducted. By adapting mathematical models, software algo-rithms were developed to transform code sequences represented in polar, homogeneous, and parametric coordinate systems, and the unique characteristics of each approach in de-veloping a universal method for ensuring accurate and efficient modulation pattern trans-formation were established. It was noted that the polar coordinate system is the most suit-able for practical applications in code sequence transformations. Its ability to effectively represent circular and symmetrical structures, as well as the convenient representation of objects with radial symmetry, provides advantages in the creation of modulation disks. As a result of the study, effective software solutions for automating data processing in the formation of modulation patterns were identified. The implementation of the developed software algorithms for the presented approach involves adapting the code sequence to the current metric within the design of an optical system based on modulation disks. The pre-sented methodology ensures the ability to transform code sequences regardless of the cho-sen coordinate system, which significantly enhances its flexibility and versatility for prac-tical applications.

Genotype-specific responses to in vitro drought stress in myrtle (Myrtus communis L.): integrating machine learning techniques.

Myrtle (Myrtus communis L.), native to the Mediterranean region of Türkiye, is a valuable plant with applications in traditional medicine, pharmaceuticals, and culinary practices. Understanding how myrtle responds to water stress is essential for sustainable cultivation as climate change exacerbates drought conditions. This study investigated the performance of selected myrtle genotypes under in vitro drought stress by employing tissue culture techniques, rooting trials, and acclimatization processes. Genotypes were tested under varying polyethylene glycol (PEG) concentrations (1%, 2%, 4%, and 6%). Machine learning (ML) algorithms, including Gaussian process (GP), support vector machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), were utilized to model and predict micropropagation and rooting efficiency. The research revealed a genotype-dependent response to drought stress. Black-fruited genotypes exhibited higher micropropagation rates compared to white-fruited ones under stress conditions. The application of ML models successfully predicted micropropagation and rooting efficiency, providing insights into genotype performance. The findings suggest that selecting drought-tolerant genotypes is crucial for enhancing myrtle cultivation. The results underscore the importance of genotype selection and optimization of cultivation practices to address climate change impacts. Future research should explore the molecular mechanisms of stress responses to refine breeding strategies and improve resilience in myrtle and similar economically important crops.

Robust adaptive dynamic control of electromagnetically actuated soft-tethered robots for medical intervention

Electromagnetically actuated soft-tethered robots (EASTRs) exhibit significant potential for medical intervention applications due to their compact size and minimal invasiveness. However, their inherent nonlinear behavior and susceptibility to unexpected disturbances present challenges for achieving robust control performance. To address this issue, in this paper, a dynamic model for EASTRs is first established, which encompasses the actuation model of the magnetic tip and the dynamic model of the soft tether. Subsequently, a robust adaptive dynamic controller is designed to compensate for the inaccuracy of the established dynamic model, thus ensuring robust control performance. The proposed approach integrates adaptive laws based on the Lyapunov method to effectively handle time-varying parameters and disturbances. Experimental results present an excellent control accuracy of the proposed scheme in trajectory tracking tasks, showcasing its superior performance compared to passive schemes and classical proportional–derivative control. This research contributes valuable insights into advancing the control capabilities of EASTRs for diverse applications in medical practices.