Search Results (13,119)

Soil–steel interface shear governs load transfer and long-term serviceability in piles, retaining systems, and buried infrastructure; yet the large-displacement interface mechanics of fibre-reinforced sands remain poorly resolved, limiting sustainable design. This study couples large-displacement ring-shear testing with physics-guided hybrid AI to quantify and predict the peak and residual resistance of sand–polypropylene fibre mixtures sliding on smooth and rough steel. Two quartz sands with contrasting particle morphology were tested under 25–200 kPa normal stress and 0–1.0% fibre content, producing a design-oriented database that captures post-peak evolution and residual states. The experiments reveal a strongly nonlinear reinforcement law: an optimum fibre range enhances dilation, stabilises the shear band, suppresses post-peak softening, and increases residual strength, whereas excessive fibres disrupt the granular skeleton and reduce mobilisation efficiency. Roughness and confinement act as amplifiers, intensifying fibre-driven dilation and asperity interlock. To translate mechanisms into prediction, three strategies were benchmarked: a deep neural network (DNN), the Physics-Guided Neural Additive Model (PG-NAM++), and the physics-anchored Residual-DNN that learns only the correction to a mechanical baseline. Residual-DNN achieved the tightest agreement and the highest physical consistency for both peak and residual strength, enabling robust parameter selection with reduced uncertainty and overdesign. The combined experimental–AI framework advances the United Nations Sustainable Development Goals (SDGs) by supporting SDG 9 through resilient, innovation-led infrastructure design and contributing to SDG 12 by enabling optimised (rather than maximal) use and reuse of reinforcement materials within circular ground-improvement practice. Full article

Novel porous geopolymer (IGP&SS), possessing mesoporous structure and a compressive strength of 9.40 MPa, was synthesized through alkali activation of double solid wastes such as iron tailings and steel slag. To overcome the high activation energy barrier of oxidants for refractory pollutant treatment, the IGP&SS was designed to efficiently activate peroxymonosulfate (PMS) under visible-light irradiation, generating reactive radicals for the rapid degradation of methylene blue (MB). The system achieved nearly complete removal within 30 min. To enhance MB removal, the effects of key factors including IGP&SS dosage, PMS dosage, initial MB concentration, temperature, and pH on the degradation process were systematically investigated. Quenching experiments revealed that several reactive oxygen species contributed to MB degradation, with the order of contribution being •OH > ¹O₂ > SO₄•⁻ > •O₂⁻. Mechanistic studies indicated that the efficient MB degradation was primarily attributed to the flexible Fe(II)/Fe(III) redox cycling in IGP&SS, which accelerated PMS activation and radical generation. X-ray photoelectron spectroscopy (XPS) analysis of the post-reaction catalyst confirmed its structural robustness, revealing a characteristic binding energy shift in the O 1s peak to 530.8 eV and a quantitative redistribution of iron species (Fe(III) content increasing from 40.4% to 57.0%). Given its outstanding performance, demonstrated stability, and eco-friendly preparation, IGP&SS holds great promise for PMS-based advanced oxidation processes in dye wastewater treatment, offering a sustainable approach for high-value utilization of iron tailings and steel slag while alleviating resource scarcity. Full article

Premature deterioration of reinforced concrete is driven largely by moisture and chloride ingress, which accelerate steel corrosion and shorten service life. This study investigates a dual strategy to enhance durability while supporting circular-economy goals: (i) incorporating coal-fired biomass ash (CBA) as a fine-aggregate replacement (0%, 20%, and 50%) and (ii) applying bio-inspired surface treatments to reduce transport pathways. To capture variability in CBA performance across different environmental and material contexts, two concrete systems—produced in India and the UK—were evaluated, each subjected to a distinct coating approach: a bacterial self-healing treatment or a cinnamaldehyde (CNM) organic barrier. Mechanical, transport, and multi-scale characterization was performed, including compressive strength, capillary absorption, chloride migration (NT Build 492), SEM/EDS, XRF, and XRD. The 20% CBA mixes maintained or slightly improved strength, while higher CBA contents increased porosity but reduced chloride transport in the UK mix. The bacterial coating reduced long-term water absorption by over 80% through CaCO₃ mineralization, offering strong moisture resistance. The CNM coating decreased chloride migration by up to 68% via hydrophobic and ionic-blocking effects. Overall, moderate CBA with self-healing treatment enhances moisture control, whereas higher CBA with CNM provides effective chloride protection, extending the service life of CBA-based concrete. Full article

Background: This in vitro study evaluated the effects of two different adhesive application approaches (total-etch and self-etch) and gallic acid (GA) pretreatment on the dentin microshear bond strength (μSBS) of a universal adhesive system. Bond strength was assessed both before thermal aging and following aging procedures simulating approximately 1 and 5 years of clinical service. Materials and Methods: One hundred twenty intact human incisors were allocated to experimental groups according to the adhesive strategy, presence or absence of gallic acid (GA) pretreatment, and thermocycling regimen (0, 10,000, or 50,000 cycles). A universal adhesive system (G-Premio BOND) in combination with a nanohybrid composite resin was applied in accordance with the manufacturers’ instructions. Microshear bond strength (µSBS) was determined using a universal testing device. The obtained data were analyzed by three-way ANOVA and subsequently compared using Tukey’s post hoc test at a significance level of 0.05. Results: In the total-etch approach, pretreatment with gallic acid (GA) resulted in significantly greater µSBS values than those observed in the corresponding untreated specimens under all aging conditions (no thermocycling: 18.53 ± 0.99 vs. 11.33 ± 0.81 MPa; 1-year: 19.86 ± 0.82 vs. 11.60 ± 0.58 MPa; 5-year: 19.04 ± 0.62 vs. 10.28 ± 0.83 MPa; p = 0.001). A comparable trend was noted for the self-etch strategy, where GA application significantly enhanced bond strength compared with the non-treated groups (no thermocycling: 21.70 ± 0.98 vs. 14.19 ± 1.17 MPa; 1-year: 22.60 ± 0.50 vs. 14.94 ± 0.85 MPa; 5-year: 22.32 ± 0.59 vs. 12.94 ± 0.84 MPa; p = 0.001). Across all thermocycling conditions, the self-etch mode consistently produced higher bond strength values than the total-etch mode. Thermal aging did not significantly influence µSBS in the GA-treated groups. In contrast, in the absence of GA pretreatment, thermocycling led to a reduction in bond strength, particularly after the 5-year aging protocol. Conclusions: Gallic acid pretreatment significantly improved dentin bond strength and contributed to the preservation of bond durability after thermal aging. The highest µSBS values were obtained when the self-etch approach was combined with gallic acid (GA) pretreatment, suggesting that GA may serve as a beneficial adjunct for improving the durability and long-term performance of resin–dentin bonds. Full article

Hydrogen is an eco-friendly fuel that does not emit greenhouse gases, and demand for it has been gradually increasing. When the hydrogen era arrives, intercontinental high-capacity hydrogen carriers are likely to be required, and for this, the membrane-type LH₂ cargo containment system (CCS) is actively being developed. In the development of liquefied CCS, sloshing pressure is an essential element in structural safety assessment. Currently, there are limitations in directly deriving the sloshing pressures of the LH₂ tank through sloshing model tests. This study proposes a methodology to indirectly predict the sloshing pressure generated in a membrane-type LH₂ cargo tank. Considering the characteristics of hydrogen, high-efficiency insulation materials should be applied to LH₂ CCS, which increases the importance of structural design. To precisely calculate the sloshing capacity of this LH₂ CCS, heat transfer analysis and structural analysis are performed as a series of processes. The stress concentration regions and dynamic effect observed in LH₂ CCS were investigated, and the structural safety of LH₂ CCS is determined by comparing the derived sloshing capacity with estimated design sloshing pressure. This is expected to be used as valuable reference for the detailed development of LH₂ CCS in the future. Full article

The stability of deep water-saturated rock masses under dynamic disturbance is crucial for the efficient development of deep geothermal resources. This study focuses on granite as the research object, using the Split Hopkinson Pressure Bar (SHPB) system to investigate the dynamic mechanical properties, energy dissipation, and failure characteristics of dry and saturated granite under impact loading, and to analyze the influence of water on the dynamic mechanical properties of granite. The results show that granite exhibits a Type II stress–strain curve (rebound phenomenon) at low strain rates, while at high strain rates, it exhibits a Type I stress–strain curve. The dynamic mechanical parameters of granite exhibit significant strain rate dependence, with water-saturated granite showing a stronger strain rate sensitivity. The dissipated energy and dissipation coefficient of the granite samples increase linearly and logarithmically, respectively, with the increase in incident energy. The dissipated energy of water-saturated granite is higher than that of dry granite. As the strain rate increases, the failure mode of the granite specimens transitions from splitting to fragmentation, with a more pronounced ductile fracture mode. The degree of fragmentation of water-saturated specimens is greater than that of dry specimens. As the strain rate increases, the difference in fractal dimensions between dry and water-saturated specimens decreases. At high strain rates, the free water within the rock generates inertial effects, meniscus effects, and viscous effects. When the strain rate reaches 124.22 s⁻¹, the strength of the water-saturated specimen matches that of the dry specimen. The research findings provide theoretical support for the safe and efficient development of deep geothermal resources. Full article

Polystyrene (PS) is widely used yet highly flammable, and developing halogen-free flame retardants that ensure both high fire safety and mechanical performance remains a challenge. A green intumescent system comprising ammonium dihydrogen phosphate (ADP) and phytic acid–triethylenetetramine (PA–TETA) was incorporated into PS powder via sequential solution grinding and hot pressing. The optimal formulation, PS/10ADP/15PA–TETA, achieved a limiting oxygen index of 28.5% with a UL-94 V-0 rating, and reduced the peak heat release rate and total heat release by 73.8% and 46.2%, respectively, while retaining 78.4% of the tensile strength of neat PS. The ADP/PA–TETA system operates via a cooperative condensed-phase charring and gas-phase dilution mechanism, achieving superior flame retardancy in PS composites. This work provides an effective and eco-friendly strategy for fabricating high-performance PS composites with balanced flame retardancy and mechanical properties. Full article

Accurate prediction of the indoor temperature in pig housing facilities is vital for the optimization of environmental control and to ensure animal welfare. However, existing models struggle to capture the complex temporal data patterns in pig farm buildings. To overcome this challenge, a novel type of hybrid model is proposed, which combines the strengths of the Prophet, Transformer, and XGBoost models. The proposed framework integrates an adaptive time-delay attention block into the Transformer encoder that automatically extracts and assigns the optimal weight to the lag features. The Prophet component makes use of multiplicative seasonal decomposition in order to capture trend, seasonal, and cyclical patterns. The XGBoost component is the final predictor which makes use of its gradient boosting capabilities to train the nonlinear feature interactions. The performance of the proposed hybrid model is compared to another six machine learning models to assess its effectiveness. Experimental validation on a real-world dataset demonstrates its superior performance, achieving the R² value of 0.97, a mean absolute error of 0.584, and a root mean squared error of 0.797. It can effectively guide the process of maximizing energy efficiency of modern livestock farms and contributes to cleaner and sustainable pig production systems. Full article

Red mud, a major solid waste from the alumina industry, suffers from an extremely low utilization rate due to its high alkalinity, complex chemistry, and particularly low cementitious activity, which drives the need for novel activation strategies. This study presents a new method for red mud activation through electrochemical treatment, which simultaneously enables iron recovery as a valuable by-product. The electrochemical activation was systematically investigated by performing experiments in alkaline, neutral, and acidic electrolytes. The alkaline system showed a pronounced enhancing effect on the electrochemical process. Under alkaline conditions, the average Faradaic efficiency exceeded 80%. The electrochemical treatment modified the microstructure of red mud particles and transformed iron oxides into magnetic species, which could be effectively separated via magnetic separation. More importantly, this activation process significantly enhanced the cementitious activity of the treated red mud by removing iron oxide that encapsulates reactive aluminosilicate phases and increasing surface reactivity. When used as a supplementary cementitious material with ordinary Portland cement and gypsum, the electrochemically activated red mud demonstrated remarkably improved mechanical properties, with 28-day compressive strength reaching up to 69 MPa. Characterization analysis revealed that the electrochemical activation promoted the formation of key hydration products, including C-S-H gel (formed through both OPC hydration and pozzolanic reactions between activated red mud and portlandite), ettringite, and portlandite. This work provides a green and low-carbon pathway for the stepwise utilization of red mud through activation and resource recovery. Full article

Hydrogel-based products are used in many areas of biomedicine and healthcare. Recently, the incorporation of cellulose nanocrystals (CNC), a renewable and functional nanomaterial, into hydrogels has enhanced their functionality, particularly by imparting mechanical strength and structural integrity. This scoping review aims to appraise the types of biomedical models and assays that have been utilised to investigate the effects of CNC incorporation into hydrogels in tissue engineering, wound healing, medical implantation and drug delivery applications, and reports on the rationale for including these models and assays. A structured literature search was undertaken in major scientific databases (PubMed Central, PubMed, BioMed Central, ScienceDirect, Wiley and EBSCOhost), focusing on identifying primary research published between 2016 and 2024. From this process, fifteen studies providing biomedical analyses met the inclusion criteria. Most of these investigations employed in vitro cell-line models (n = 12), with a smaller number utilising in vivo experimental systems (n = 5). Across the included studies, CNC incorporation typically yielded measurable performance gains: reported compressive or storage modulus improvements of 20–40% over hydrogel-only controls, consistently high cell viability (>85%) across multiple human and murine cell types for up to 21 days, and sustained drug release profiles (days–weeks) in stent and antitumour contexts. Where quantified, functional outcomes in vivo included preserved graft volume (autologous fat grafts) and reduced intimal hyperplasia signals in vascular graft models. Critical gaps included heterogeneous CNC sources and surface chemistries, inconsistent reporting of CNC concentration and hydrogel formulation parameters, the limited duration and scope of biocompatibility testing, and minimal alignment with standard evaluation protocols, constraining reproducibility and cross-study comparability. To date, there are no human clinical trials of CNC-hydrogels. Translational readiness will require standardised ISO-compliant biocompatibility evaluations. Large-animal studies under relevant mechanical and physiological conditions, and rigorous long-term degradation and immunogenicity assessments to de-risk progression to human trials. We recommend standardised CNC sources and surface functionalisation reporting, concentration (wt%) ranges, hydrogel rheological characterisation (G′, G″, swelling), and consistent biological endpoints (viability, differentiation, inflammation panels) to enable robust meta-analyses and translational benchmarking. Distinct from prior nanocellulose reviews that emphasise material synthesis and properties, this analysis centres on the biomedical models and assays applied to CNC-incorporated hydrogels, identifying the methodological convergence and divergence that directly impact translational pathways. Full article

The low activity and expansion risk of steel slag limit its large-scale utilization in cementitious systems. This study developed an alkali-sulfate synergistic activation method to prepare binder with steel slag content exceeding 50 wt%. The effects of alkali activator dosage, modulus, steel slag and flue gas desulfurization gypsum content on the mechanical properties and workability were systematically investigated. With a mix of 60% steel slag, 30% fly ash, 10% desulfurization gypsum and activated by additional 20% alkali activator with modulus 1.0, the 28-day compressive strength reached 12.85 MPa, along with excellent volume stability. Microstructural characterization revealed that the main hydration products are C-A-S-H and ettringite, which jointly form a dense microstructure. When used to solidify lead–zinc tailings for backfill, the binder yielded satisfactory strength and effectively immobilized heavy metals (Pb, As, Cd, Zn), with leaching concentrations meeting environmental standards and immobilization efficiencies > 80%. Heavy metals were primarily immobilized through physical encapsulation, ion exchange, and co-precipitation. This study elucidates the hydration and mechanisms of high-content steel slag systems under alkali-sulfate synergistic activation, providing a sustainable technical framework for large-scale utilization of steel slag and tailings management. Full article

To elucidate the stability mechanisms of grid-forming (GFM) inverters governed by dispatchable virtual oscillator control (dVOC), this paper develops a comprehensive sequence-impedance modeling and stability analysis framework for dVOC-based GFM inverters with different inner-loop control structures. Three representative configurations are investigated: open-loop dVOC control, dVOC with dual-loop voltage–current control (DLC), and dVOC with virtual admittance control (VAC). For each configuration, unified positive-sequence impedance models are derived and analytically validated. Based on these models, the stability characteristics are first analyzed in a single-inverter grid-connected system under different grid strengths. The analysis is then extended to a mixed inverter system consisting of grid-forming and grid-following (GFL) inverters. Particular attention is paid to the impedance interaction between GFM impedance shaping and the capacitive negative damping introduced by GFL inverters under weak-grid conditions. Quantitative analyses reveal that the dVOC–DLC configuration significantly enhances oscillation damping in mixed systems. Under benchmark scenarios, stable operation can be ensured with approximately a 25% GFM capacity penetration. In contrast, the open-loop and VAC configurations require around 50% and 75% capacities, respectively, to maintain stability. These findings indicate that the DLC-based inner-loop design offers superior stability margins while substantially reducing the required GFM capacity, thereby improving economic efficiency. This study establishes a quantitative impedance-based criterion for inner-loop control selection and provides practical design guidelines for deploying dVOC-based GFM inverters in future converter-dominated power systems. Full article

Bribery remains prevalent across African countries, yet little is known about how fear of retaliation for reporting corruption interacts with national institutional contexts to shape bribery behaviour. Using Round 9 Afrobarometer data from 42,655 respondents across 39 African states, this study examines how perceptions of reporting risk combine with macro-level conditions of state capture and symbolic law to influence the likelihood of paying bribes. Hierarchical logistic regression results show that individuals who fear retaliation are significantly more likely to engage in bribery, but this relationship is conditioned by institutional strength. High levels of state capture and weak rule-of-law systems intensify the effect of retaliation risk, whereas judicial independence mitigates it. Aspects of symbolic law—judicial accountability, access to justice, and enforcement—further shape how fear translates into corrupt exchanges. The findings demonstrate that reducing bribery requires credible, protective, and functional institutions, not simply increased anti-corruption awareness. The study advances corruption research by integrating behavioural risk perceptions with multi-dimensional measures of institutional weakness, offering a cross-national explanation for when fear becomes behaviourally consequential. Full article

Atmospheric turbulence is a critical factor limiting the imaging resolution of ground-based solar telescopes. This study presents a systematic investigation of the intensity and vertical distribution of daytime atmospheric turbulence during winter at the Fuxian Solar Observatory, using data acquired from the 1-meter New Vacuum Solar Telescope (NVST) with its Ground Layer Adaptive Optics (GLAO) system and a custom-developed wide-field Shack–Hartmann wavefront sensor. Statistical results reveal a median Fried parameter ($r_0$) of 8.25 cm at 500 nm, indicating generally favorable daytime observing conditions. A distinct diurnal variation in $r_0$ was observed: values were higher in the morning and afternoon but decreased significantly around noon due to enhanced ground-layer heating. Vertical turbulence profiling showed that approximately 52.8% of the total turbulence strength originates from the ground layer, and 93.1% is confined below 4 km, with only weak turbulence detected at higher altitudes. This study establishes the first statistical turbulence profile model for the Fuxian Solar Observatory site during winter daytime, providing crucial insights for optimizing high-resolution solar observations and the design of multi-conjugate adaptive optics systems. Full article

Chest X-ray (CXR) imaging remains the most widely used radiological modality for assessing pulmonary and cardiothoracic disease, yet its interpretation is inherently constrained by tissue superposition, subtle radiographic findings and marked inter-observer variability. Recent advances in artificial intelligence (AI) have driven significant progress in automated CXR analysis, supported by large public datasets, evolving annotation strategies and increasingly expressive deep learning architectures. This review presents a comprehensive synthesis of approaches for pulmonary abnormality detection, encompassing convolutional neural networks, transformers, multimodal and vision–language models and self-supervised representation learning. We critically discuss their strengths, limitations and vulnerability to label noise, domain shift and shortcut learning. In parallel, we examine dataset properties, annotation practices, robustness challenges, explainability methods and the heterogeneity of evaluation protocols that hinder fair comparison and clinical translation. Building on these observations, the review identifies key future directions, including foundation models, multimodal integration, federated and domain-generalized training, longitudinal modeling, synthetic data generation and standardized clinical evaluation frameworks. By integrating methodological and clinical perspectives, this work offers an up-to-date reference for researchers and clinicians and outlines a roadmap toward reliable, interpretable and clinically deployable AI systems for chest radiography. Full article