Search Results (2,678)

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability. Full article

We investigate the affine term structure models (ATSMs) with unspanned stochastic volatility (USV). Our aim is to test their ability to generate accurate cross-sectional behavior and time-series dynamics of bond yields. Comparing the restricted models and those with USV, we test whether they produce both reasonable estimates for the short rate variance and cross-sectional fit. Essentially, a joint approach from both time series and options data for estimating risk-neutral dynamics in ATSMs should be followed. Due to the scarcity of derivative data in emerging markets, we estimate the model using only time-series of bond yields. A Bayesian estimation approach combining Markov Chain Monte Carlo (MCMC) and the Kalman filter is employed to recover the model parameters and filter out latent state variables. We further incorporate macro-economic indicators and GARCH-based volatility as external validation of the filtered latent volatility process. The $A_1\left(4\right)$USV performs better both in and out of sample, even though the issue of a tension between time series and cross-section remains unresolved. Our findings suggest that even without derivative instruments, it is possible to identify and interpret risk-neutral dynamics and volatility risk using observable time-series data. Full article

In this study, a new fibre combination for an interlayer hybrid fibre-reinforced polymer laminate was investigated to achieve pseudo-ductile behaviour in tensile tests. The chosen high-strain fibre for this purpose was S-Glass, and the low-strain fibre was flax. These materials were chosen because of their relatively low environmental impact compared to carbon/carbon and carbon/glass hybrids. An analytical model was used to find an ideal combination of the two materials. With that model, the expected stress–strain relation could also be predicted analytically. The modelling was based on preliminary tensile tests of the two basic components investigated in this research: unidirectional laminates reinforced with either flax fibres or S-Glass fibres. Hybrid specimens were then designed, produced in a heat-assisted pressing process, and subjected to tensile tests. The strain measurement was performed using distributed fibre optic sensing. Ultimately, it was possible to obtain repeatable pseudo-ductile stress–strain behaviour with the chosen hybrid when the specimens were subjected to quasi-static uniaxial tension in the direction of the fibres. The intended damage-mode, consisting of a controlled delamination at the flax-fibre/glass-fibre interface after the flax fibres failed, followed by a load transfer to the glass fibre layers, was successfully achieved. The pseudo-ductile strain averaged 0.52% with a standard deviation of 0.09%, and the average load reserve after delamination was 145.5 MPa with a standard deviation of 48.5 MPa. The integrated fibre optic sensors allowed us to monitor and verify the damage process with increasing strain and load. Finally, the analytical model was compared to the measurements and was partially modified by neglecting the Weibull strength distribution of the high-strain material. Full article

A maximum entropy (ME) methodology was used to infer the Hubble constant from the temperature anisotropies in cosmic microwave background (CMB) measurements, as measured by the Planck satellite. A simple cosmological model provided physical insight and afforded robust statistical sampling of a parameter space. The parameter space included the spectral tilt and amplitude of adiabatic density fluctuations of the early universe and the present-day ratios of dark energy, matter, and baryonic matter density. A statistical temperature was estimated by applying the equipartition theorem, which uniquely specifies a posterior probability distribution. The ME analysis inferred the mean value of the Hubble constant to be about 67 km/sec/Mpc with a conservative standard deviation of approximately 4.4 km/sec/Mpc. Unlike standard Bayesian analyses that incorporate specific noise models, the ME approach treats the model error generically, thereby producing broader, but less assumption-dependent, uncertainty bounds. The inferred ME value lies within 1σ of both early-universe estimates (Planck, Dark Energy Signal Instrument (DESI)) and late-universe measurements (e.g., the Chicago Carnegie Hubble Program (CCHP)) using redshift data collected from the James Webb Space Telescope (JWST). Thus, the ME analysis does not appear to support the existence of the Hubble tension. Full article

Background: The occlusal angle (OA), influenced by pillow height, may affect muscle tension in the head and neck. However, its optimal range for minimizing muscle activation has not been clearly defined. Objective: This study aimed to investigate the effects of OA on the resting muscle activity of masticatory and cervical muscles and to identify an optimal OA range using cluster analysis and linear mixed-effects modeling. Methods: The resting muscle activities of the masseter (MAS), temporalis (TEM), sternocleidomastoid (SCM), and posterior vertebral muscles (PVM) were measured at OA conditions modulated by pillow heights of 0, 5, and 10 cm at 0, 1, and 5 min in the supine position. Intraclass correlation coefficients (ICCs) assessed measurement reliability. Statistical analyses included ANOVA, ROC curve analysis, k-means clustering, and linear mixed-effects models. Results: MAS and TEM resting muscle activity ratio (RMR) significantly increased with larger OA values (p < 0.001), while SCM showed decreased activation (p = 0.001). An OA range of 105°–111° was identified as the center of a low-activity cluster, and an upper cut-off of 138° was associated with potential muscular overload. ICC values for MAS and SCM ranged from 0.82 to 0.89, indicating excellent test–retest reliability. Conclusions: OA modulated by pillow height is a modifiable factor that influences muscle activity. An OA of 105°–111° may serve as a practical comfort zone, especially for individuals at risk of TMDs. Full article

To address the issue of the low compression–tension ratio in the traditional parallel bond model (PBM), this study proposes an improved PBM incorporating a random distribution strategy of strong–weak contact groups. An L₂₇(3¹²) orthogonal experimental design was employed to construct 27 sets of numerical simulation schemes. Combined with Pearson correlation coefficient analysis and multivariate regression, the influence of twelve microscopic parameters on seven of the macroscopic mechanical properties of sandstone was systematically investigated, including elastic modulus (E), Poisson’s ratio (v), uniaxial compressive strength (σ_c), internal friction angle (φ), cohesion (c), crack damage stress ratio (σ_cd/σ_c), and compressive–tensile strength ratio (σ_c/σ_t). Based on these analyses, a quantitative relationship model between the macro and micro parameters was established and validated through numerical simulation and experimental comparison. The proposed method provides a theoretical foundation for the mechanical modeling of sandstone and the inversion of microscopic parameters. Full article

Background/Objectives: Although technology has progressed and novel dosage forms have been developed, tablets are still the most used form of medication. However, the present manufacturing methods of these oral solid dosage forms offer limited capacity for personalized treatment and adaptable dosing. Personalized therapy, with a few exceptions, is not yet a part of routine clinical practice. Drug printing could be a possible approach to increase the use of personalized therapy. The aim of this work was to investigate the role of surface tension and the viscosity of inks in the formation of the printing pattern and to investigate how the porosity of substrate tablets influences the behavior of inks on the surface. Methods: Spray-dried mannitol served as a binder and filler, while magnesium stearate functioned as a lubricant in the preparation of substrate tablets. Brilliant Blue dye was a model “drug”. The ink formulation was applied to the substrates in three varying quantities. Results: Increasing the viscosity enhanced the drug content, potentially improving printing speed and pattern accuracy. However, it negatively impacted the dosing accuracy due to nozzle clogging and prolonged drying time. Viscosity had a significantly higher impact on the ink behavior than surface tension. Lowering the surface tension improved the dosing accuracy and reduced the drying time but resulted in smaller drop sizes and decreases in pattern accuracy. Reducing the substrate porosity led to longer drying times and diminished pattern accuracy. Conclusions: A target surface tension of around 30 mN/m is suggested for inkjet printing. It is necessary to further investigate the applicability of the technology with solutions of inks with high viscosity and low surface tension, including the API. Full article

Deployable thin-film antennas deliver large aperture gains and high stowage efficiency for spaceborne phased arrays but suffer wrinkling-induced planarity loss and radiation distortion. To bridge the lack of electromechanical coupling models for tensioned thin-film patch antennas, we present a unified framework combining structural deformation and electromagnetic simulation. We derive a coupling model capturing the increased bending stiffness of stepped-thickness membranes, formulate a wrinkling analysis algorithm to compute tension-induced displacements, and fit representative unit-cell deformations to a dual-domain displacement model. Parametric studies across stiffness ratios confirm the framework’s ability to predict shifts in pattern, gain, and impedance due to wrinkling. This tool supports the optimized design of wrinkle-resistant thin-film phased arrays for reliable, high-performance space communications. Full article

Inefficient inland repositioning of empty containers between depots remains a persistent challenge in container logistics, contributing significantly to unnecessary truck movements, elevated operational costs, and increased CO₂ emissions. Acknowledging the importance of this problem, a large amount of relevant literature has appeared. The objective of this paper is to track the empty container flow between ports, empty depots, inland terminals, and customer premises. Additionally, it aims to simulate and assess CO₂ emissions, capturing the dynamic interactions between different agents. In this study, agent-based modeling (ABM) was proposed to simulate the empty container movements with an emphasis on inland transportation. ABM is an emerging approach that is increasingly used to simulate complex economic systems and artificial market behaviours. NetLogo was used to incorporate real-world geographic data and quantify CO₂ emissions based on truckload status and to evaluate the other operational aspects. Behavior Space was also utilized to systematically conduct multiple simulation experiments, varying parameters to analyze different scenarios. The results of the study show that customer demand frequency plays a crucial role in system efficiency, affecting container availability and logistical tension. Full article

During operation, dynamic cables endure coupled thermo-mechanical loads (mechanical: tension/bending; thermal: power transmission) that degrade stiffness, amplifying extreme responses and impairing configuration optimization. To address this, this study pioneers a multi-objective optimization framework integrating stiffness characteristics from mechanical/thermo-mechanical analyses, with objectives to minimize dynamic extreme tension and curvature under constraints of global configuration variables and safety thresholds. The framework employs a Radial Basis Function (RBF) surrogate model coupled with NSGA-II algorithm, yielding validated Pareto solutions (≤6.15% max error vs. simulations). Results demonstrate universal reduction in extreme responses across optimized configurations, with the thermo-mechanically optimized solution achieving 20.24% fatigue life enhancement. This work establishes the first methodology quantifying thermo-mechanical coupling effects on offshore cable safety and fatigue performance. This configuration design scheme exhibits better safety during actual service conditions. Full article

A novel approach to estimating the absorbed energy (toughness) in a uniaxial tensile test with only knowledge of the microstructure is presented. The flow behavior of each Dual-Phase (DP) steel grade is predicted using idealized Representative Volume Elements (RVEs) up to uniform elongation. To estimate the flow behavior beyond uniform elongation, the stress-modified fracture strain in a non-local damage model was implemented in Abaqus. Damage parameters were calibrated using Finite Element (FE) simulations of purely ferritic tensile specimens. The damage parameters remained unchanged, except for the coefficient of triaxiality. This coefficient was adjusted based on the average triaxiality of ferrite elements at the instability point of the uniaxially loaded RVEs for each DP steel grade. The proposed approach comprises two steps: micron-sized RVEs to predict the flow behavior up to the point of uniform elongation and the average triaxiality and full-scale tensile-test simulations to predict the rest of the curves. The results show that the damage parameters calibrated for high-strain ferrite effectively estimate the absorbed energy during failure in tension tests. This approach is also geometry-independent; varying the geometry of the tensile specimen, including miniature or notched specimens, still yields predicted absorbed energies that are in good agreement with the experimental results. Full article

To establish a theoretical foundation for assessing the dynamic performance of high-speed train catenary systems in wind-prone regions, this study develops a coupled pantograph–catenary model using ANSYS(2022R1) APDL. The dynamic responses of conventional high-speed pantographs traversing both mainline and transition sections are analyzed under varying operational conditions. The key findings reveal that an elevated rated tension in the contact wire and messenger wire reduces the pantograph lift in wind areas with no crosswind compared to non-wind areas, with an average lift reduction of 8.52% and diminished standard deviation, indicating enhanced system stability. Under a 20 m/s crosswind, both tested pantograph designs maintain contact force and dynamic lift within permissible thresholds, while significant catenary undulations predominantly occur at mid-span locations. Active control strategies preserve the static lift force but induce pantograph flattening under compression, reducing aerodynamic drag and resulting in smaller contact force fluctuations relative to normal-speed sections. In contrast, passive control increases static lift, thereby causing greater fluctuations in contact force compared to baseline conditions. The superior performance of active control is attributed to its avoidance of static lift amplification, which dominates the dynamic response in passive systems. Full article

The accurate description of plasticity and fracture behavior is essential in numerically investigating the mechanical responses of high-strength bolts under tension, shear and coupling loads. However, based on the von Mises criterion, inputting the constitutive relation and damage model from the tensile coupon test into the finite element method cannot properly predict the shear behavior of high-strength bolts. Cylindrical tensile coupons and shear specimens of common and weathering high-strength bolts are tested to obtain the complete tensile and shear responses. The combined S-V model and the modified shear constitutive model are collaboratively used to calibrate and describe the tensile and shear constitutive relations of high-strength bolts, and then the Bao–Wierzbicki model is used to predict the tensile and shear fracture behaviors. Furthermore, the collaborating method is used to discuss the applicable range of tensile and shear constitutive models for high-strength bolts under a tensile–shear coupling load, based on numerical analysis against available experimental data in the literature. The loading angle of 30° along the bolt rod is defined as the cut-off to differentiate high-strength bolts under a tensile- or shear-dominated state, and the corresponding mechanical responses of high-strength bolts can be predicted well based on the tensile and shear constitutive models, respectively. Full article

Water within coal reservoirs exerts dual effects on methane adsorption–desorption by competing for adsorption sites and reducing permeability. The bound water effect, caused by coal wettability, significantly constrains coalbed methane (CBM) production, rendering investigations into coal wettability crucial for efficient CBM development. Compared with other geological formations, coals are characterized by a highly developed microporous structure, making the CO₂ sequestration mechanism in coal seams closely linked to the microscale interactions among gas, water, and coal matrixes. However, the intrinsic mechanisms remain poorly understood. In this study, molecular dynamics simulations are employed to investigate the wettability behaviors of CO₂, CH₄, and water on different coal matrix surfaces under varying temperature and pressure conditions, for coal macromolecules representative of four coal ranks. The study reveals the evolution of water wettability in response to CO₂ and CH₄ injection, identifies wettability differences among coal ranks, and analyzes the microscopic mechanisms governing wettability. The results show the following: (1) The contact angle increases with gas pressure, and the variation in wettability is more pronounced in CO₂ environments than in CH₄. As pressure increases, the number of hydrogen bonds decreases, while the peak gas density of CH₄ and CO₂ increases, leading to larger contact angles. (2) Simulations under different temperatures for the four coal ranks indicate that temperature has minimal influence on low-rank Hegu coal, whereas for higher-rank coals, gas adsorption on the coal surface increases, resulting in reduced wettability. Interfacial tension analysis further suggests that higher temperatures reduce water surface tension, cause dispersion of water molecules, and consequently improve wettability. Understanding the wettability variations among different coal ranks under variable pressure–temperature conditions provides a fundamental model and theoretical basis for investigating deep coal seam gas–water interactions and CO₂ geological sequestration mechanisms. These findings have significant implications for the advancement of CO₂-ECBM technology. Full article

This study investigates the shear bearing capacity of aluminum alloy–concrete composite beams to address the limitations caused by the low elastic modulus of aluminum alloys. A finite element model was developed using the Concrete Damaged Plasticity (CDP) model for concrete and validated through parametric analysis. Key factors such as concrete strength, stirrup spacing, and cross-sectional dimensions were examined. An improved shear capacity formula was derived based on the tension–compression bar model and the superposition method. The proposed formula achieved an average ratio of 1.018 to finite element results, with a standard deviation of 0.151, and the proposed formula was validated against 22 FEA models, demonstrating excellent agreement with numerical results and confirming its reliability for practical engineering applications. This work provides a practical analytical approach for the shear design of aluminum–concrete composite structures. Full article