Dynamic Analysis Research Articles

INVESTIGATION OF FRACTIONAL-ORDERED TUMOR-IMMUNE INTERACTION MODEL VIA FRACTIONAL-ORDER DERIVATIVE

Dynamical analysis of system of ordinary differential equations (ODEs) is an interesting topic among researchers and several tools have been discovered since so far to deal with its several other features. There are many built-in functions designed in MATLAB that researchers can use as a tool for the system of ODEs with integer order but in the similar systems have fractional-order derivative is a difficult task. Therefore, the purpose of this work is to use the Caputo fractional-order derivative to qualitatively analyze and then numerically simulate the tumor-immune system interaction model. Moreover, the Schauder fixed point theorem is used to establish the condition for the existence of at least one solution, while the Banach fixed point theorem is utilized to guarantee the existence of a unique solution. Moreover, the stability in the trajectories of considered system achieved with the aid of Ulam–Hyers (UH) stability. In addition, the numerical computations are performed using Variational Iteration Method (VIM) and the visualized results are shown using MATLAB.

Implementing Super-Resolution of Non-Stationary Tides with Wavelets: An Introduction to CWT_Multi

Abstract Tides are often non-stationary due to non-astronomical influences. Investigating variable tidal properties implies a tradeoff between separating adjacent frequencies (using long analysis windows) and resolving their time variations (short windows). Previous continuous wavelet transform (CWT) tidal methods resolved tidal species. Here, we present CWT_Multi, a Matlab code that: a) uses CWT linearity (via the “Response Coefficient Method”) to implement super-resolution (Munk and Hasselman 1964); b) provides a Munk-Hasselman constituent-selection criterion; and c) introduces an objective, time-variable form of inference (“dynamic inference”) based on time-varying data properties. CWT_Multi resolves tidal species on time-scales of days and multiple constituents per species with fortnightly filters. It outputs astronomical phase-lags and admittances, analyzes multiple records, and provides power spectra of the signal(s), residual(s) and reconstruction(s), confidence limits, and signal-to-noise ratios. Artificial data and water-levels from the Lower Columbia River Estuary (LCRE) and San Francisco Bay Delta (SFBD) are used to test CWT_Multi and compare it to harmonic analysis programs NS_Tide and UTide. CWT_Multi provides superior reconstruction, detiding, dynamic analysis utility, and time-resolution of constituents (but with broader confidence limits). Dynamic inference resolves closely spaced constituents (like K1, S1, and P1) on fortnightly time scales, quantifying impacts of diel power-peaking (with a 24-hour period, like S1) on water levels in the LCRE. CWT_Multi also helps quantify impacts of high flows and a salt-barrier closing on tidal properties in the SFBD. On the other hand, CWT_Multi does not excel at prediction, and results depend on analysis details, as for any method applied to non-stationary data.

Sufficiency assessment of intensity measures for natural and spectral-matched ground motion records

AbstractA correct Intensity Measure (IM) selection is essential for Performance-Based Earthquake Engineering (PBEE) applications, as any probabilistic seismic demand model (PSDM) depends significantly on the IM. If a single IM can describe the complexity of the corresponding ground motion record, it can be defined as sufficient in an absolute sense. However, this is unlikely because a single number should be able to inform on the frequency content, the amplitude, the duration, the energy content, etc. For this reason, literature studies have defined sufficiency in a relative sense to investigate whether one IM is more sufficient (i.e., more informative) than another in predicting the structural response. This work explores the relative sufficiency of eight scalar IMs through Nonlinear Response History Analyses (NRHAs) using two sets of 20 pairs of ground motion records. Both sets are spectrum-compatible and consist of unscaled natural and spectral-matched records. Also, both Cloud and Incremental Dynamic Analysis procedures are used. This study demonstrates that Cloud analysis cannot be used in its conventional form to study sufficiency when spectral-matched accelerograms are used. When natural accelerograms are employed, the results clearly indicate the existence of a sufficient IM among those selected. Conversely, it is more difficult to define the relative sufficiency of the IMs for spectral-matched records because the operation of record adjusting leads to similar structural demands. This result could question either the validity of using spectral-matched accelerograms for PBEE due to the lack of aleatory variability in the structural demand or the necessity of having a sufficient IM when a PSDM is fitted in a PBEE analysis using spectral-matched accelerograms.

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

An efficient dynamic reliability method for maglev vehicle-bridge systems and its application in random controller parameters analysis

This article presents an efficient method for analyzing the dynamic reliability of maglev vehicle-bridge coupled systems by combining a theoretical model with an adaptive surrogate model and the probability density evolution method (PDEM). First, a refined theoretical model of a maglev vehicle-bridge coupling system is established. Next, an adaptive surrogate model of the equivalent extreme value of the system dynamic response is established by combining an adaptive sampling method with radial basis functions. Finally, the adaptive surrogate model and PDEM are combined to further improve the efficiency of the dynamic reliability analysis. In the numerical example, the theoretical model of the maglev vehicle-guideway system was first validated by comparing with the measured data from the Shanghai high-speed maglev line. Then, by treating the controller parameters as normally distributed random variables, the accuracy and efficiency of the proposed reliability method were verified through comparison with the Monte Carlo method and the one-stage sampling surrogate model. Additionally, the impact of the randomness of each controller parameter and the coefficient of variation of the controller parameters on the system’s dynamic reliability was discussed.

Dynamical and optimal control analysis of lymphatic filariasis and buruli ulcer co-infection

This study delves into the dynamics of lymphatic filariasis and buruli ulcer coinfection, two overlooked yet impactful tropical diseases. With lymphatic filariasis, commonly referred to as elephantiasis, and buruli ulcer, a chronic affliction caused by mycobacterium ulcerans, both posing significant health challenges, understanding their interaction is crucial. Utilizing a mathematical model, this research aims to analyze the dynamics of this coinfection, elucidating its complexities. The study establishes the local asymptotic stability of the disease-free equilibrium and calculates the basic reproduction number using the next generation matrix. It uncovers transcritical and backward bifurcation phenomena within the model. Additionally, the integration of time-dependent controls enables the exploration of optimal disease management strategies. Numerical simulations highlight the efficacy of employing a comprehensive approach, utilizing all available controls simultaneously, as the most effective strategy for disease control. These findings underscore the importance of integrated interventions in combating lymphatic filariasis and buruli ulcer coinfection, offering valuable insights for public health policymakers and practitioners.

Dynamic Characteristics Analysis of the DI-SO Cylindrical Spur Gear System Based on Meshing Conditions

The dual-input single-output (DI-SO) cylindrical spur gear system possesses advantages such as high load-carrying capacity, precise transmission, and low energy loss. It is increasingly becoming a core component of power transmission systems in maritime vessels, aerospace, marine engineering, and construction machinery. In practical operation, the stability of the DI-SO cylindrical spur gear system is influenced by complex excitations. These excitations lead to nonlinear vibration, meshing instability, and noise, which affect the performance and reliability of the entire equipment. Hence, the dynamic performance of the DI-SO cylindrical spur gear system is thoroughly investigated in this research. The impact of excitations and nonlinear factors on the dynamic characteristics was investigated comprehensively. A comparative analysis of the gear system was conducted by establishing a bending–torsional coupling vibration analysis model under synchronous and asynchronous meshing conditions. Nonlinear factors such as periodic time-varying meshing stiffness, meshing damping, friction coefficient, friction arms, load sharing ratio, comprehensive transmission error, and backlash were considered in the proposed model. Then, the effect laws of excitations and nonlinear factors such as meshing frequency, driving load fluctuation, backlash, and comprehensive transmission error were analyzed. The results indicate that the dynamic characteristics exhibited staged stable and unstable states under different meshing frequencies and meshing conditions. At the medium-frequency meshing stage (0.96 × 104~1.78 × 104 Hz), alternating phenomena of multi-periodic, quasi-periodic, and chaotic motion states were observed. Moreover, the root mean square value (RMS) of the dynamic transmission error (DTE) in the asynchronized gear system was generally higher than that in the synchronized gear system. It was found that selecting the appropriate meshing condition could effectively reduce the amplitude of the DTE. Additionally, the dynamic performance could be significantly improved by adjusting control parameters such as driving load fluctuation (0~179 N), backlash (0.8 × 10−4~0.9 × 10−4 m), and comprehensive transmission error (7.9 × 10−4~9.4 × 10−4 m). The research results provide a theoretical guidance for the design and optimization of the DI-SO cylindrical spur gear system.

Data‐driven dynamical analysis of an age‐structured model: A graph‐theoretic approach

The dynamics of the propagation and outspread of infectious diseases are eminently intricate, mainly due to the heterogeneity of the host individuals. In this paper, an age‐stratified SEIR (susceptible‐exposed‐infected‐recovered) epidemiological model incorporating saturated treatment function and heterogeneous contact rates is developed to study infectious disease transmission dynamics among various age groups. The expression for the basic reproduction number and conditions for the global stability of the system have been derived by a recently developed graph‐theoretic (GT) approach. Digraph reduction creates a GT version of the Gauss elimination method for computing the . The global dynamics results have been formed by constructing the Lyapunov function using a GT approach. The endemic equilibrium exists uniquely if , whereas the disease‐free equilibrium is observed to be globally stable if . The numerical simulations are demonstrated by extracting the daily reported COVID‐19 cases for the second wave in Italy. The age‐dependent contact matrix for the Republic of Italy (data sourced from the POLYMOD study) is computed via paper–diary methodology (PDM) grounded on a population‐prospective survey in European countries. Our numerical findings imply that (i) for the age group (20–49) years and (50–69) years, the number of infected persons is quite double as compared with the exposed cases; (ii) approximately 50% of positive cases lies in (20–69) years age group; (iii) for the (00–19) years age group, only half of the exposed individuals got infected; and (iv) a consistent graph is detected for the age group of (70–99) years in both cases; it shows that almost all the exposed got infected.

An analysis of mastodon adoption dynamics based on instance types

Federated social networks have become an appealing choice as alternatives to mainstream centralized platforms. In the current global context, where the user’s activity on various social networks is monitored, influenced and manipulated, alternative platforms that offer the possibility of owning and controlling one’s own data are of great importance. Mastodon stands out among decentralized alternatives in the fediverse. In this study, we conduct a time-based dynamics analysis of various Mastodon instances, from popular ones to country-specific servers. Moreover, we conducted an analysis of registration account dynamics based on certain topics, such as academic, political and activism in general. Throughout the paper, we reveal the user adoption of Mastodon from multiple instances and metrics. Our results show a growth pattern of instances in terms of accounts in certain periods of time, and due to social events, reinforcing our assumption of it being already trusted as a decentralized platform. Our work holds significance in the wider context of studying and understanding the adoption rates of decentralized networks as ethical alternatives to centrally controlled ones.

Dynamic BIM Adoption Impact on Contract Cost Variance Factors Using PLS-SEM Techniques

This paper investigates the Building Information Modeling (BIM) adoption impact on the factors of Contract Cost Variance (CCV) over time. The study considers qualitative and quantitative data to identify the most common causes of CCV through pre-tendering. A partial least square-structure model (PLS-SEM) procedure was used to develop a causal model and rank CCV factors based on their effect, partially based on prior survey raw data conducted in 2022 and the data from 94 projects. Construction industry experts assessed the prior five-year rate of BIM adoption on construction projects to infer the expected trend in BIM adoption in the future (until 2037). Based on the causal model of CCV factors and the future rates of BIM adoption, the dynamic impact of BIM on CCV factors over time was modeled and analyzed. The analysis shows that BIM reduces CCV over time by improving Estimator Performance (EP), Information Quality (IQ), and contractual procedure (CP). The results showed that the CP, EP, and EF have directly impacted CCV, and the PC and IQ indirectly affect the CCV. This paper considers the temporal aspect, examining how the impact of BIM on CCV factors evolves. This dynamic analysis is crucial for long-term strategic planning in construction management.

The Impact of Dynamic Effects on the Results of Non-Destructive Falling Weight Deflectometer Testing.

The article investigates the impact of applying a dynamic computational model that considers inertia forces on pavement deflections under rapidly changing loads over time. This study is particularly relevant to the modelling of falling weight deflectometer (FWD) testing. Initially, the article examines the deflection values obtained from computational models under loads with varying frequencies. In this context, considering inertia forces was significant for load durations shorter than 0.04 s. In such cases, the results of static and dynamic analyses differed considerably. One application of FWD measurement results is determining the stiffness moduli of pavement layers using backcalculation. The study explored the impact of incorporating inertia forces into the pavement model on the estimated values of stiffness moduli obtained via backcalculation. The results revealed differences of several percent between the stiffness moduli calculated using dynamic and static numerical models. Subsequently, the key pavement deformations and fatigue life were determined using the obtained moduli. Again, significantly different results were observed between dynamic and static cases. Based on these findings, it can be concluded that dynamic effects should not be ignored when using FWD testing for backcalculation. Additionally, the article addresses the sensitivity of backcalculation results, which is crucial for the accurate interpretation of the obtained data.

Fabrication and thermomechanical property investigations of polypropylene/silica and polypropylene/modified silica composite films

In this study, we fabricated polypropylene/silica (PP/S) and polypropylene/modified silica (PP/MS) composite films using the extrusion technique, and characterized, and investigated their thermomechanical behaviors. The characterization of the neat materials and prepared composites was successfully conducted using some advanced spectroscopic techniques. The thermal stability and thermomechanical behaviors of the composites were investigated through thermogravimetry analysis (TGA) and dynamic mechanical analysis (DMA). The tensile tests revealed that the PP/MS composites exhibited the highest strength values, reaching 22.23 MPa with 1.0 % MS. Higher tensile strength was obtained with PP/MS composites compared to PP/S composites, proving the clear effect of the hexadecyltrimethylammonium bromide (HTAB) binder in the composition of the composites. The highest strength values obtained with the PP/S composites were 20.10 MPa at a ratio of 2.5 %.

A Dynamic Mechanical Analysis on the Compatibilization Effect of Two Different Polymer Waste-Based Compatibilizers in the Fifty/Fifty Polypropylene/Polyamide 6 Blend.

This study aims to examine the 50/50 polypropylene/polyamide 6 (iPP/PA6) system molded under confined flow conditions, both in its original state and after being modified by two different interfacial agents. This study provides two main insights. Firstly, it focuses on a polymer blend close to phase inversion. Secondly, it investigates the impact of using two different types of interfacial agents (derived from polymer waste) to enhance the compatibility between iPP and PA6. Dynamic Mechanical Analysis (DMA) has been employed to achieve these objectives. It is important to note that the investigation of the 50/50 iPP/PA6 system is a crucial focus predicted in previous studies, where a series of mechanical properties were evaluated using Box-Wilson design of experiments (DOEs) over the whole compositional range on the iPP/PA6 binary system. Thus, two interfacial modifiers, namely succinic anhydride (SA)-grafted atactic polypropylene with terminal, side, and bridge SA grafts (aPP-SASA) and succinyl-fluoresceine (SF) with bridge succinic anhydride grafting atactic polypropylene (aPP-SFSA), were employed. The authors obtained and characterized these agents. The quantity of these agents used in the blend was identified as a critical coordinate in prior studies conducted by the authors. The processing method used, compression molding under confined conditions, was chosen to minimize any orientation effect on the emerging morphology. All characterization procedures were performed on samples processed by contour machining to retain the blend morphologies as they emerged from the processing stage. Results from WAXS and SAXS synchrotron tests concluded there were no changes in the crystal morphology of the iPP or the PA6 in the blends nor any co-crystallization process throughout the compositional range. These findings, and the long period fits on the PP crystalline phase for the fifty/fifty blends we are discussing, will support the present DMA study. Finally, the efficiency of these interfacial modifiers has been concluded, even in this unfavorable scenario.

Preparation and Characterization of Biocomposites Based on Fibrous Brucite and Poly (Butylene Succinate)

In our research described in this manuscript, fibrous brucite (FB) was modified with common silane coupling agent (KH-570) and the facile melt blending method was used to fabricate fibrous brucite/poly(butylene succinate) (FB/PBS) composites. To evaluate the influence of surface modification of the FB, scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) showed that the KH-570 reacted with brucite and the treated FB (OFB) could be well dispersed in the polymer matrix. The mechanical properties and dynamic mechanical analysis (DMA) results showed the effect of the surface modification on the tensile strength, impact strength, storage modulus and glass transition temperature (Tg), which were enhanced with the incorporation of the treated FB in the composites. The flame retardancy of the FB/PBS composites was improved significantly, indicating that the FB could be used as an efficient flame retardant. The addition of FB deteriorated the thermal stability of the PBS. However, the loss in thermal stability was exchanged for a considerable increase in the mechanical and flame retardancy properties. The prepared composites demonstrated better mechanical and flame retardancy properties, compared to PP or PP composites, presenting the potential to be widely used in various industrial fields.

Dynamics analysis and FPGA implementation of discrete memristive cellular neural network with heterogeneous activation functions

The activation function, as an important component of artificial neural networks, endows neural networks with rich dynamical phenomena by virtue of its nonlinear properties. However, especially for cellular neural networks (CNNs), the exploration of neural networks consisting of heterogeneous activation functions has not been sufficient. In this article, we introduce heterogeneous activation functions in discrete cellular neural network (DCNN) for the first time. In order to enhance the dynamics of the original DCNN, we propose our discrete memristive cellular neural network (DMCNN) based on a memristor with a sinusoidal function. Using various methods of dynamical characterization, such as Lyapunov exponential analysis, bifurcation diagrams and spectral entropy, the rich dynamical behaviour of the proposed model is comprehensively investigated, including hyperchaos, transient chaos, high spectral entropy and multiple types of coexisting attractors in the proposed model. Last but not least, the hardware platform of the proposed model is implemented by field programmable gate array (FPGA), and the dynamics of the proposed model is verified by a combination of software simulation and hardware experiments. The new exploration of DMCNN with heterogeneous activation functions in this article lays the foundation for further research into neural networks with complex dynamical behaviour.

The dynamic reconfiguration of the functional network during episodic memory task predicts the memory performance

Episodic memory is essential for forming and retaining personal experiences, representing a fundamental aspect of human cognition. Traditional studies of episodic memory have typically used static analysis methods, viewing the brain as an unchanging entity and overlooking its dynamic properties over time. In this study, we utilized dynamic functional connectivity analysis on fMRI data from healthy adults performing an episodic memory task. We quantified integration and recruitment metrics and examined their correlation with memory performance using Pearson correlation. During encoding, integration across the entire brain, especially within the frontoparietal subnetwork, was significantly correlated with memory performance. During retrieval, recruitment becomes significantly associated with memory performance in visual subnetwork, somatomotor subnetwork, and ventral attention subnetwork. At the nodal level, a significant negative correlation was observed between memory scores and integration of the anterior cingulate gyrus, precentral gyrus, and inferior frontal gyrus within the frontoparietal network during encoding task. During retrieval task, a significant negative correlation was found between memory scores and recruitment in the left progranular cortex and right transverse gyral ventral, whereas positive correlations were seen in the right posterior inferior temporal, left middle temporal, right frontal operculum, and left operculum nodes. Moreover, the dynamic reconfiguration of the functional network was predictive of predict memory performance, as demonstrated by a significant correlation between actual and predicted memory scores. These findings advance our understanding network mechanisms underlying memory processes and developing intervention approaches for memory-related disorders as they shed light on critical factors involved in cognitive processes and provide a deeper understanding of the underlying mechanisms driving cognitive function.

Seismic response and damage evolution process of a bedded slope‒tunnel system via the continuum‒discontinuum element method

To investigate the failure evolution process and failure mechanism of the bedded slope‒tunnel system under earthquakes, this work examines a specific layered slope at a tunnel portal in southeast China and conducts a 2D dynamic analysis with the continuum‒discontinuum element method (CDEM). It investigates the slope's dynamic behavior and potential for instability by evaluating the wave patterns, acceleration, displacement, Hilbert‒Huang transform (HHT) spectral analysis, and equivalent crack ratio. The research results indicate that the analysis of acceleration and displacement over time provides insights into wave propagation within a slope. During minor earthquakes (< 0.3 g), the slope experiences dynamic amplification at the surface and elevation-dependent effects, which are less evident during stronger seismic events. This work also revealed a positive correlation between the tunnel's dynamic amplification and elevation. A method leveraging HHT energy analysis, in conjunction with the slope's equivalent fracture ratio, is introduced to trace the progression of seismic damage across temporal and spatial dimensions. The progression of seismic intensity is characterized by stages of local failure initiation, expansion, and eventual holistic failure. Similarly, the temporal dynamics of instability are categorized into phases of initial instability, acceleration, and eventual sliding. Furthermore, this work explores the impact of tunnels on slope stability by comparing the equivalent fracture ratios and dynamic displacement patterns of slopes both with and without tunnels, revealing the evolution process of seismic damage to slope‒tunnel systems. This work provides a reference for the seismic design of complex slope‒tunnel systems.

9th Ishihara lecture: Effects of subsurface heterogeneity on liquefaction-induced ground deformation during earthquakes

The effects of subsurface heterogeneity on liquefaction phenomena during earthquakes are discussed using case histories and nonlinear dynamic analyses with different subsurface modeling approaches. The importance of geologic and anthropogenic controls and the effects of stratigraphic heterogeneity, lithological heterogeneity, and inherent soil variability at the project site scale are discussed. The results of these studies reinforce lessons regarding the importance of subsurface characterization and its representation in analyses for evaluating liquefaction-induced ground deformations and their impacts on civil infrastructure.

Free and forced vibration analysis of piezolaminated plates via an isogeometric layerwise finite element

Isogeometric layerwise finite element (L-IGA) formulation is a recent state-of-the-art approach integrating Non-Uniform Rational B-spline (NURBS) basis functions into the quasi-static solution process of piezolaminated composite plates. This study extends the application of the L-IGA framework to encompass free, forced vibration, and displacement control analyses of laminated composite plates with straight/curvilinear fibers and piezoelectric layers. To this end, the NURBS basis functions, utilized in geometry definition, are employed to solve electromechanically coupled differential equations following Hamilton’s variational principle. The adoption of high-order continuous NURBS shape functions throughout the IGA discretization span both in-plane and through-thickness laminate dimensions. This effectively facilitates precise geometry representation directly from Computer-Aided Design (CAD). Besides, such a discretization accelerates the convergence of displacement and electric potential solution fields toward exact results. Various benchmark problems have been solved to verify the robustness and high accuracy of the proposed dynamic L-IGA method. These include comparative analyses between L-IGA dynamic solutions (i.e. employing the Newmark-Beta method), analytical solutions, and ANSYS-Solid 226 finite element results. All the results are compared across various span-to-thickness ratios, mechanical-potential loading scenarios, and fiber orientation angles. Remarkably, the L-IGA method attains almost excellently accurate time response of various fields (displacement, stress, electric potential) and modal results, with considerably fewer mesh elements than Solid 226 solutions. Overall, such an outcome reveals the high potential and practical merits of the proposed L-IGA formulation as a proficient finite element approach for the dynamic analysis of piezolaminated plates.

Epicatechin and β-Glucan from Whole Highland Barley Grain Synergistic Benefit on Attenuating Hyperglycemia via Improving Hepatic Glucose Metabolism in Diabetic C57BL/6J Mice.

Our previous study proved that epicatechin (EC) and β-glucan (BG) from whole-grain highland barley synergistically modulate glucose metabolism in insulin-resistant HepG2 cells. However, the main target and the mechanism underlying the modulation of glucose metabolism in vivo remain largely unknown. In this study, cell transfection assay and microscale thermophoresis analysis revealed that EC and BG could directly bind to the insulin receptor (IR) and mammalian receptor for rapamycin (mTOR), respectively. Molecular dynamic analysis indicated that the key amino acids of binding sites were Asp, Met, Val, Lys, Ser, and Tys. EC supplementation upregulated the IRS-1/PI3K/Akt pathway, while BG upregulated the mTOR/Akt pathway. Notably, supplementation with EC + BG significantly increased Akt and glucose transporter type 4 (GLUT4) protein expressions, while decreasing glycogen synthase kinase 3β (GSK-3β) expression in liver cells as compared to the individual effects of EC and BG, indicating their synergistic effect on improving hepatic glucose uptake and glycogen synthesis. Consistently, supplementation with EC + BG significantly decreased blood glucose levels and improved oral glucose tolerance compared to EC and BG. Therefore, combined supplementation with EC and BG may bind to corresponding receptors, targeting synergistic activation of Akt expression, leading to the improvement of hepatic glucose metabolism and thereby ameliorating hyperglycemia in vivo.