Search Results (829)

Maple syrup production has the potential to promote sustainable rural economic development in regions with suitable forest and climate conditions. Kentucky emerges as a promising candidate due to its extensive maple tree inventory and favorable seasonal patterns. However, the broader economy-wide implications of developing a maple syrup industry in the state remain underexplored. To fill this knowledge gap, this study employs a customized static single-region computable general equilibrium (CGE) modeling approach for Kentucky under nine scenarios based on production capacities and potential levels. The results consistently show positive impacts on net household income, social welfare (measured by equivalent variation), government revenues, and state GDP across all scenarios. Medium production capacities generate the most balanced and efficient outcomes, while high-potential scenarios, especially under small and large scales produce the largest absolute gains. These results underscore the viability of maple syrup production as an economic development strategy and highlight the role of production scale in maximizing benefits. Furthermore, expanding maple syrup production can enhance rural livelihoods by diversifying forest-based income and promoting long-term stewardship. As a non-timber forest product, maple syrup tapping provides economic incentives to maintain healthy forests, strengthening rural sustainability and resilience. Our findings indicate that developing this industry beyond traditional regions can generate meaningful economic benefits while encouraging sustainable resource use when appropriately scaled and managed. Full article

This study examines the relationship between national open educational resource (OER) policies and Sustainable Development Goal 4 (SDG4) outcomes across 187 countries between 2015 and 2024, with particular attention to the moderating role of artificial intelligence (AI) readiness. Despite widespread optimism about digital technologies as catalysts for universal education, systematic evidence linking formal OER policy frameworks to measurable improvements in educational access and completion remains limited. The analysis employs fixed effects and difference-in-differences estimation strategies using an unbalanced panel dataset comprising 435 country-year observations. The research investigates how OER policies associate with primary completion rates and out-of-school rates while testing whether these relationships depend on countries’ technological and institutional capacity for advanced technology deployment. The findings reveal that AI readiness demonstrates consistent positive associations with educational outcomes, with a ten-point increase in the readiness index corresponding to approximately 0.46 percentage point improvements in primary completion rates and 0.31 percentage point reductions in out-of-school rates across fixed effects specifications. The difference-in-differences analysis indicates that OER-adopting countries experienced completion rate increases averaging 0.52 percentage points relative to non-adopting countries in the post-2020 period, though this estimate remains statistically imprecise (p equals 0.440), preventing definitive causal conclusions. Interaction effects between policies and readiness yield consistently positive coefficients across specifications, but these associations similarly fail to achieve conventional significance thresholds given sample size constraints and limited within-country variation. While the directional patterns align with theoretical expectations that policy effectiveness depends on digital capacity, the evidence should be characterized as suggestive rather than conclusive. These findings represent preliminary assessment of policies in early implementation stages. Most frameworks were adopted between 2019 and 2022, providing observation windows of two to five years before data collection ended in 2024. This timeline proves insufficient for educational system transformations to fully materialize in aggregate indicators, as primary education cycles span six to eight years and implementation processes operate gradually through sequential stages of content development, teacher training, and institutional adaptation. The analysis captures policy impacts during formation rather than at equilibrium, establishing baseline patterns that require extended longitudinal observation for definitive evaluation. High-income countries demonstrate interaction coefficients between policies and readiness that approach marginal statistical significance (p less than 0.10), while low-income subsamples show coefficients near zero with wide confidence intervals. These patterns suggest that OER frameworks function as complementary interventions whose effectiveness depends critically on enabling infrastructure including digital connectivity, governance quality, technical workforce capacity, and innovation ecosystems. The results carry important implications for how countries sequence educational technology reforms and how international development organizations design technical assistance programs. The evidence cautions against uniform policy recommendations across diverse contexts, indicating that countries at different stages of digital development require fundamentally different strategies that coordinate policy adoption with foundational capacity building. However, the modest short-term effects and statistical imprecision observed here should not be interpreted as evidence of policy ineffectiveness, but rather as confirmation that immediate transformation is unlikely given implementation complexities and temporal constraints. The study contributes systematic cross-national evidence on aggregate policy associations while highlighting the conditional nature of educational technology effectiveness and establishing the need for continued longitudinal research as policies mature beyond the early implementation phase captured in this analysis. Full article

The enteric nervous system (ENS) constitutes a highly organized and intricate neuronal network comprising two principal plexuses: myenteric and submucosal. These plexuses consist of neurons and enteric glial cells (EGCs). Neurons ensure innervation throughout the intestinal wall, whereas EGCs, distributed within the mucosa, contribute to epithelial barrier integrity and modulation of local inflammatory responses. The ENS orchestrates essential gastrointestinal functions, including motility, secretion, absorption, vascular regulation, and immune interactions with gut microbiota. Under physiological conditions, intestinal homeostasis involves moderate generation of reactive oxygen species (ROS) through endogenous processes such as mitochondrial oxidative phosphorylation. Cellular antioxidant systems maintain redox equilibrium; however, excessive ROS production induces oxidative stress, promoting EGCs activation toward a reactive phenotype characterized by pro-inflammatory cytokine release. This disrupts neuron–glia communication, predisposing to enteric neuroinflammation and neurodegeneration. Obesity, associated with hyperglycemia, hyperlipidemia, and micronutrient deficiencies, enhances ROS generation and inflammatory cascades, thereby impairing ENS integrity. Nevertheless, non-pharmacological strategies—including synthetic and natural antioxidants, bioactive dietary compounds, probiotics, and prebiotics—attenuate oxidative and inflammatory damage. This review summarizes preclinical and clinical evidence elucidating the interplay among the ENS, obesity-induced oxidative stress, inflammation, and the modulatory effects of antioxidant interventions. Full article

The adverse-pressure-gradient (APG) severely disrupts the inherent symmetry of the turbulent boundary layer (TBL). The universal physical behavior and scaling laws observed under zero-pressure-gradient (ZPG) conditions are significantly altered under APG, thereby challenging the predictive accuracy of turbulence models. To address this breakdown, we develop a generalized mixing length model by incorporating APG effects into a baseline ZPG framework. The model is directly constructed using APG-extended wall laws—superposing the log law and the half-power law for the mean velocity—and the logarithmic decay law for the total shear stress. Validated against ten databases spanning the entire APG region, various Reynolds numbers, and both equilibrium and non-equilibrium flows, the model demonstrates accurate predictions for both mixing length and mean velocity profiles. The key achievements are as follows: (i) a significant simplification of model parameters, wherein the inner model can be reduced to a parameterless scaling law, while outer parameters were reduced from five to two; and (ii) the unification of predictions across the entire APG range. This work demonstrates that consistent modeling of APG effects bridges slight and strong APGs, enabling a unified description of the APG region before separation and providing critical insights for turbulence modeling. Full article

Interfaces of rather different natures—as, e.g., bacterial colony or forest fire boundaries, or semiconductor layers grown by different methods (MBE, sputtering, etc.)—are self-affine fractals, and feature scaling with universal exponents (depending on the substrate’s dimensionality d and global topology, as well as on the driving randomness’ spatial and temporal correlations but not on the underlying mechanisms). Adding lateral growth as an essential (non-equilibrium) ingredient to the known equilibrium ones (randomness and interface relaxation), the Kardar–Parisi–Zhang (KPZ) equation succeeded in finding (via the dynamic renormalization group) the correct exponents for flat $d=1$ substrates and (spatially and temporally) uncorrelated randomness. It is this interplay which gives rise to the unique, non-Gaussian scaling properties characteristic of the specific, universal type of non-equilibrium roughening. Later on, the asymptotic statistics of process $h\left(x\right)$ fluctuations in the scaling regime was also analytically found for $d=1$ substrates. For $d>1$ substrates, however, one has to rely on numerical simulations. Here we review a variational approach that allows for analytical progress regardless of substrate dimensionality. After reviewing our previous numerical results in $d=1$, 2, and 3 on the time evolution of one of the functionals—which we call the non-equilibrium potential (NEP)—as well as its scaling behavior with the nonlinearity parameter $\lambda$, we discuss the stochastic thermodynamics of the roughening process and the memory of process $h\left(x\right)$ in KPZ and in the related Golubović–Bruinsma (GB) model, providing numerical evidence for the significant dependence on initial conditions of the NEP’s asymptotic behavior in both models. Finally, we highlight some open questions. Full article

To address the challenge that unmanned surface vehicles (USVs) struggle to effectively balance tracking accuracy, control smoothness, and system energy efficiency under external disturbances, this paper proposes an anti-disturbance path tracking control method integrating quantum-inspired optimization (QIO) and dynamic game theory (GT). The proposed control method consists of a two-layer optimization architecture: the upper layer employs dynamic game theory to optimize the guidance process, modeling the optimization of the look-ahead distance ($Ld$) and switching radius ($R$) in the LOS guidance algorithm as a non-cooperative game, and achieves adaptive adjustment to path variations and environmental disturbances by solving for the Nash equilibrium. The lower layer, based on a quantum-inspired optimization algorithm, enhances the control process by employing quantum bit probability amplitude encoding for the PID parameter space and utilizing a quantum rotation gate mechanism for efficient global search, thereby achieving online self-tuning of PID parameters under environmental disturbances. Simulation results indicate that, under sea conditions with external disturbances, the proposed method achieves a superior balance among tracking accuracy, control smoothness, and system energy efficiency compared to the traditional fixed-parameter PID-LOS approach, enhancing the comprehensive anti-disturbance robustness of the USV. Full article

A semi-analytical mixed-control model based on the Non-Partitioned Local Equilibrium (NPLE) assumption was developed to simulate the austenite phase transformation kinetics during heating and isothermal processes. The model was validated by comparing the simulation results with experimental data, showing excellent agreement. The effects of various model parameters and process conditions on the phase transformation kinetics was investigated. The results indicate that higher heating rates lead to an increase in the austenite volume fraction at the start of the isothermal hold, accelerating the transformation and resulting in a more complete phase transformation. The transformation during the isothermal stage was found to follow a mixed control mode at all investigated heating rates. Increasing the mobility coefficient enhances interface migration, thereby accelerating the transformation kinetics, while decreasing the grain size promotes nucleation, further accelerating the phase transformation. Modifying the diffusion coefficient had a minor effect on transformation kinetics. Additionally, raising the isothermal temperature increased both the austenite volume fraction at the beginning and end of the isothermal process and the interface migration velocity, suggesting that temperature dominates the phase transformation rather than time. The phase transformation mode under different process conditions was also investigated. For both 5 °C/s and 100 °C/s heating rates, the phase transformation during the isothermal process was predominantly interface-controlled, as indicated by the mixed-mode parameter approaching 1, with a rapid increase followed by a decrease. Full article

Cerrado fruits are rich sources of bioactive compounds with antioxidant and immunomodulatory properties. However, it remains unclear whether the complexes of non-conventional starch with extracts from these fruits can modulate oxidative stress in human cells, under diabetic conditions. This study evaluated the effects of lobeira (Solanum lycocarpum) starch complexed with hydrophilic and lipophilic extracts of mirindiba (Buchenavia tomentosa) on redox parameters in mononuclear cells from normoglycemic and diabetic individuals. The extracts showed high phenolic (1362.70 mg gallic acid equivalent (GAE)/100 g) and carotenoid content (7.07 mg β-carotene/100 g) and strong antioxidant capacity (58.42–140.19 μmol Trolox/g by FRAP and DPPH). Structural analyses (Fourier transform infrared (FTIR), X-ray diffraction (XRD), and Scanning Electron Microscopy (SEM)) confirmed complexation via hydrogen bonding and inclusion-type interactions, which partially modified the crystalline order of starch. The complexes exhibited high biocompatibility (>97% cell viability) and adaptively modulated oxidative and antioxidant responses under different metabolic and infectious conditions. Normoglycemic cells showed enhanced redox balance, with moderate superoxide generation and higher SOD activity, while cells from diabetic individuals displayed elevated oxidative stress and reduced SOD induction upon treatment. Under the E. coli challenge, the complexes modulated redox equilibrium through compensatory antioxidant responses. These findings position lobeira starch–mirindiba extract complexes as promising dietary immunomodulators against oxidative stress in metabolic and infectious contexts. Full article

This study systematically investigates the catalytic effect of histidine (HIS) on CO₂ desorption in amine-based solvents, with a primary focus on 30 wt% N-(2-aminoethylamino)ethanol (AEEA) and its blends with N-methyldiethanolamine (MDEA). Experimental results show that the addition of 0.22 wt% HIS significantly enhances both the equilibrium desorption amount and the maximum desorption rate of CO₂, particularly at elevated temperatures (e.g., 100 °C). Under optimal conditions, HIS increased the maximum desorption rate by 22.1% and reduced the heat duty to 71.7% compared to the non-catalytic benchmark. The catalytic performance was further confirmed in AEEA-MDEA mixed solvents, with the most pronounced effect observed in the 3:2 molar ratio system, where HIS enhanced both the equilibrium desorption amount and the maximum desorption rate by 15.3% and 20.8%, respectively. Through ¹³C NMR analysis and pH-dependent speciation monitoring, we revealed that HIS alters the reaction pathway by suppressing the formation of stable carbamate species (AEEA_(a)COO⁻). The protonated (HIS⁺) and neutral (HIS^±) forms were identified as the active species that promote more direct CO₂ release from carbamate, while the deprotonated (HIS⁻) form facilitates proton transfer and amine regeneration. HIS also exhibited excellent catalytic stability over 10 absorption–desorption cycles. These findings highlight HIS as an efficient and stable organocatalyst for energy-efficient CO₂ desorption processes. Full article

Alginate aerogels are attractive candidates for biomedical scaffolds because they combine high mesoporosity with biocompatibility and can be processed into open, interconnected macroporous networks suitable for tissue engineering. Here, we systematically investigate how CO₂-induced foaming parameters govern the hierarchical pore structure of alginate aerogels produced by subsequent supercritical CO₂ drying. Sodium alginate–CaCO₃ suspensions are foamed in a CO₂ atmosphere at 50 or 100 bar, depressurization rates of 50 or 0.05 bar·s⁻¹, temperatures of 5 or 25 °C, and, optionally, under pulsed pressure or with Pluronic F-68 as a surfactant. The resulting gels are dried using supercritical CO₂ and characterized by micro-computed tomography and N₂ sorption. High pressure combined with slow depressurization (100 bar, 0.05 bar·s⁻¹) yields a homogeneous macroporous network with pores predominantly in the 200–500 µm range and a mesoporous texture with 15–35 nm pores, whereas fast depressurization promotes bubble coalescence and the appearance of large (>2100 µm) macropores and a broader mesopore distribution. Lowering the temperature, applying pulsed pressure, and adding surfactant enable further tuning of macropore size and connectivity with a limited impact on mesoporosity. Interpretation in terms of Peclet and Deborah numbers links processing conditions to non-equilibrium mass transfer and gel viscoelasticity, providing a physically grounded map for designing hierarchically porous alginate aerogel scaffolds for biomedical applications. Full article

It has been shown for the first time that in the case of a pressure flow of a Newtonian fluid in a circular pipeline, the influence of forces of rheological origin, ion electrostatic and Van der Waals nature on the radius of the undeformed flow core is described by a third-degree polynomial with respect to the thickness of the layer, where the suspension structure is destroyed and its shear flow occurs. In this polynomial, the contributions of rheological forces and the influence of the hydraulic size of the solid-phase particles in the suspension enter as linear terms; ionic electrostatic and Van der Waals forces enter as quadratic and constant terms, respectively. For conditions typical of water–coal fuel, we demonstrate that the hydraulic (size) term is several orders of magnitude smaller than the leading terms and may be neglected, and that the quadratic term is negligible compared with the constant (free) term, so that the limiting value of the undeformed core radius is obtained as the real root of a cubic equation containing cubic, linear and constant terms. At DLVO equilibrium, the constant term vanishes, and the limiting relative core radius reduces to the rheological–hydraulic expression; away from equilibrium, the constant term becomes positive or negative, thereby altering the admissible interval of the relative core radius. Using Cardan’s method, we show analytically that (i) when the cubic discriminant is positive, a single real root exists and physically admissible solutions occur only for a negative constant term; (ii) when the discriminant is negative, three real roots exist and the maximum relative radius at which the suspension structure is preserved shifts above or below the rheological-only radius depending on the sign of the constant term. Numerical evaluation of the proposed lyophobicity model for proportionality coefficients k₁ in the range 1–10 yields a lyophobicity function varying approximately from 0.67 to 1.06, confirming the modest but non-negligible role of interparticle interaction energy in modifying the undeformed core size under water–coal fuel conditions. These results quantify the competing roles of rheology and interparticle forces in determining the stability and extent of the undeformed core in pipeline transport of structured suspensions. Full article

The theory underlying non-linear dynamical systems remains essential for understanding complex behaviors in science and engineering. In this study, we propose a new chaotic dynamical system that exhibits a butterfly-shaped attractor without any equilibrium point. Despite its compact structure comprising only five terms, the system demonstrates rich chaotic behavior distinct from conventional oscillator models. Detailed modeling and dynamical analyses are conducted to confirm the presence of chaos and to characterize the system’s sensitivity to initial conditions. Furthermore, synchronization of the proposed dynamical system is investigated using both identical and non-identical control algorithms. In the identical case, the activation function of the neural network is governed by the butterfly oscillator dynamics, whereas in the non-identical case, a sigmoidal activation function is employed. The proposed synchronization algorithms enable faster convergence by pinning a subset of nodes in the network. Finally, a practical implementation of the conceived dynamical system in an encryption framework is presented, with the aim to demonstrate its feasibility and potential application in secure communication systems. The results highlight the effectiveness of the proposed approach for both theoretical exploration and engineering applications involving chaotic dynamical systems. Full article

Cryogenic Energy Storage (CES) has emerged as a promising solution for large-scale and long-duration energy storage, offering high energy density, zero local emissions, and compatibility with intermittent renewable energy sources. This systematic review critically examines recent advances in the numerical modeling of CES systems, with the objective of identifying prevailing methodologies, emerging trends, and existing research gaps. The studies analyzed are classified into three main categories: global thermodynamic modeling, simulation of specific components, and transient dynamic modeling. The findings highlight the continued use of thermodynamic models due to their simplicity and computational efficiency, alongside a growing reliance on high-fidelity CFD and transient models for more realistic operational analyses. A clear trend is also observed toward hybrid approaches, which integrate deterministic modeling with machine learning techniques and response surface methodologies to enhance predictive accuracy and computational performance. Nevertheless, significant challenges persist, including the absence of multiscale integrative models, the scarcity of high-resolution experimental data under transient conditions, and the limited consideration of operational uncertainties and material degradation. It is concluded that the development of integrated numerical frameworks will be critical to advancing the technological maturity of CES systems and ensuring their robust deployment in real-world energy transition scenarios. Additionally, the review also discusses local thermal non-equilibrium (LTNE) conditions, the influence of geometric and operational parameters, and the role of multidimensional and multi-region modeling in predicting thermal and exergy performance of packed-bed TES within LAES cycles. Full article

This study explores the spread of malware within a digital framework by introducing a unique fractional-order model that employs the Atangana–Baleanu–Caputo (ABC) derivative. As cyber threats grow increasingly sophisticated and widespread, traditional models using classical differential equations often prove inadequate, particularly in capturing long-term memory effects and historical dependencies inherent in real-world systems. To address these challenges, the proposed approach utilizes the non-local characteristics of fractional calculus, offering a more comprehensive framework for understanding malware behavior. The model includes the derivation of the basic reproduction number, ${\Re }_0$, to evaluate conditions for malware persistence or elimination, sensitivity analysis and examines equilibrium states to assess overall system stability. Theoretical analysis ensures the existence and uniqueness of solutions through fixed-point techniques. Through numerical simulations, the theoretical results are validated, emphasizing the significant impact of antidotal and recovery measures in controlling malware spread. These findings provide essential guidance for enhancing the protection and robustness of sophisticated cyber-physical and humanoid infrastructures. Full article

Efficient resource allocation is a central challenge in multi-tenant cloud, fog, and edge environments, where heterogeneous tenants compete for shared resources under dynamic and uncertain workloads. Static or purely heuristic methods often fail to capture strategic tenant behavior, whereas many existing game-theoretic approaches overlook stochastic demand variability, fairness, or scalability. This paper proposes a Dynamic and Stochastic Game-Theoretic Allocation (DSGTA) model that jointly models non-cooperative tenant interactions, repeated strategy adaptation, and random workload fluctuations. The framework combines a Nash-like dynamic equilibrium, achieved via a lightweight best-response update rule, with an approximate Shapley-value-based fairness mechanism that remains tractable for large tenant populations. The model is evaluated on synthetic scenarios, with a trace-driven setup built from the Google 2019 Cluster dataset, and a scalability study is conducted with up to $K=500$ heterogeneous tenants. Using a consistent set of core metrics (tenant utility, resource cost, fairness index, and SLA satisfaction rate), DSGTA is compared against a static game-theoretic allocation (SGTA) and a dynamic pricing-based allocation (DPBA). The results, supported by statistical significance tests, show that DSGTA achieves higher utility, lower average cost, improved fairness and competitive utilization across diverse strategy profiles and stochastic conditions, thereby demonstrating its practical relevance for scalable, fair, and economically efficient resource allocation in realistic multi-tenant cloud environments. Full article