Search Results (526)

To address the imbalance between the shearing–mixing quality and energy efficiency of deepwater drilling mud mixers and breakthrough the limitations of existing independent single-objective analytical perspectives, the Eulerian solid–liquid two-phase numerical simulation was adopted in this study. Combined with a modified shear rate algorithm and a triple energy coupling analysis of shear rate, Lamb vortex energy and Enstrophy, the energy conversion and particle dispersion mechanisms inside the mixer under variable flow rates and solid concentrations were systematically investigated, and the performance differences between the first-generation and optimized mixers were clarified. Structural optimizations including an additional modular stator with a designed shear gap of 2 mm, improved blade profiles and shear angles to 14.2°, and miniaturized radial dimensions of the impeller and volute were implemented to achieve compact structural upgrading. The results demonstrate that high-energy regions are concentrated in the rotor–stator gap. After optimization, the peak shear rate increases from 12,010 s⁻¹ to 17,092 s⁻¹, representing a 42.3% enhancement. The peak Lamb vortex energy and the mean Enstrophy rise by 8.6% and 18.9%, respectively. Shear rate correlates weakly positively with Lamb vortex energy and strongly negatively with Enstrophy, revealing vortex sensitivity to flow velocity and tight coupling of viscous dissipation to particle concentration. The outlet coefficient of variation C_v decreases by 59.6%. Higher flow rates strengthen the coupling of shear and vortex energy, and higher solid concentrations weaken stator shear performance. The optimized mixer achieves synergistic improvements in shear efficiency and mixing quality, with over 50% enhancement in mud dispersion stability and more than 15%. Full article

Spatial confinement strongly affects matter by altering structural stability, relaxation times, and equilibrium properties. Interest in hydrogen storage within carbon nanotube bundles has grown because it addresses practical energy needs while revealing rich confined-fluid physics. Understanding how geometry and defects influence hydrogen structure and dynamics is essential to the development of effective storage materials. Here, we investigate how confinement in single-walled carbon nanotube (SWCNT) bundles with vacancies alters the spatial distribution and phase behavior of physisorbed hydrogen. At low temperature, hydrogen forms solid-like, cylindrical layered structures both inside and outside the tubes. Raising the temperature broadens these layers and produces a liquid-like arrangement within the confined regions. This confined solid-to-liquid crossover controls storage capacity and release behavior and can be tuned by temperature, confinement dimensions, and vacancy defects. Full article

This study examines the relationship between banks’ ESG performance and core risk and balance sheet indicators in the Turkish banking sector. Using an unbalanced panel of eight banks listed on Borsa Istanbul over the period 2008–2023, we estimate bank fixed-effects models with one-year-lagged ESG measures and controls and report Driscoll–Kraay standard errors. Two complementary specifications are employed: one based on the composite ESG score and another based on its environmental (E), social (S), and governance (G) pillars. The findings suggest that the composite ESG score is positively associated with non-performing loans and capital adequacy, while its relationship with liquidity risk and net balance sheet position/equity is less stable across specifications. When the ESG pillars are examined separately, substantial heterogeneity emerges across the E, S, and G dimensions. In particular, the environmental score is negatively associated with capital adequacy, whereas the social score is negatively associated with net balance sheet position/equity. Governance-related results appear weaker and more sensitive to specification choice. Overall, the findings indicate that ESG does not operate through a uniform risk channel in banking and should be interpreted as associational rather than causal. The study contributes evidence from an emerging-market banking system and highlights the importance of disaggregated ESG analysis. Full article

To address the existing challenges in mold slag thickness measurement—such as the susceptibility of contact sensors to high-temperature degradation and the limitation of non-contact methods to detecting only the upper slag surface—this study proposes an integrated approach that fuses millimeter-wave radar and eddy current sensors for measuring mold slag thickness in a continuous casting mold. The method innovatively combines two sensing principles: the millimeter-wave radar employs an improved FFT-CZT² high-precision ranging algorithm to perform high-resolution scanning of the solid slag upper surface, reconstructing its topography (error: $\pm$1 mm), while Mel-frequency cepstral coefficients (MFCC) are applied to extract features from the radar intermediate-frequency signals, combined with an enhanced PSO-BP neural network algorithm to predict the thickness of the solid slag layer (error: $\pm$5 mm). Concurrently, an eddy current sensor monitors the liquid slag–molten steel interface position (error: $\pm$1 mm). Through dual-sensor data fusion, the upper surface topography data and solid slag thickness obtained from the radar are spatially registered in three dimensions with the molten steel level information derived from the eddy current sensor. This integration ultimately enables the non-contact synchronous measurement of three key parameters within the mold: solid slag layer thickness, liquid slag layer thickness inversion, and molten steel level. Furthermore, by reconstructing the upper slag surface morphology, the method successfully resolves practical issues such as uneven material distribution, local material deficiency, or excessive feeding. Preliminary experimental verification confirms that the proposed method maintains stable performance even under high-temperature and complex environmental conditions. It thus provides a real-time, accurate, and full-cross-section monitoring solution for mold slag in continuous casting, offering significant practical value for the development of smart steel plants. Full article

Oral squamous cell carcinoma (OSCC) remains a major global health burden due to aggressive invasion, early metastasis, therapeutic resistance, and poor long-term survival. Beyond tumor-intrinsic genetic and epigenetic alterations, accumulating evidence highlights the critical role of the tumor microenvironment in shaping OSCC progression and clinical outcomes. Cancer-associated fibroblasts (CAFs) and immune cells orchestrate tumor initiation, immune evasion, and recurrence through extracellular matrix remodeling, cytokine signaling, angiogenesis, and metabolic and redox regulation. Key oncogenic pathways, including EGFR/PI3K/AKT/mTOR, TGF-β, Wnt, and Notch, integrate with non-coding RNA networks to reinforce stemness, epithelial–mesenchymal transition, and therapy resistance. Moreover, PD-1/PD-L1-mediated immune escape, CAF-driven biomechanical remodeling, and metabolic reprogramming such as aerobic glycolysis and lipid metabolism contribute to OSCC heterogeneity. This review synthesizes current insights into OSCC across genomic, epigenetic, metabolic, and microenvironmental dimensions, emphasizing CAF biology, immune landscape reprogramming, and non-coding RNA regulation. We further discuss emerging biomarkers, liquid biopsy approaches, and targeted therapeutic strategies, providing a system-level framework for biomarker-guided stratification and precision combination therapies in OSCC. Full article

Underwater micro-bubble detection entails multiple challenges, including diminutive target sizes, sparse pixel information, pronounced specular highlights and water scattering, indistinct bubble boundaries, and adhesion or overlap between instances. To address these issues, we propose HSMD-YOLO, an improved detector tailored for high-resolution micro-bubble detection and built upon YOLOv11. The model incorporates three novel components: the Scale Switch Block (SSB), a scale-transformation module that suppresses artifacts and background noise, thereby stabilizing edges in thin-walled bubble regions and enhancing sensitivity to geometric contours; the Global Local Refine Block (GLRB), which achieves efficient global relationship modeling with an asymptotic linear complexity ($O\left(N\right)$) in spatial dimensions while further refining local features, thereby strengthening boundary perception and improving bubble–background separability; and the Bidirectional Exponential Moving Attention Fusion (BEMAF), which accommodates the multi-scale nature of bubbles by employing a parallel multi-kernel architecture to extract spatial features across scales, coupled with a multi-stage EMA based attention mechanism to enhance detection robustness under weak boundaries and complex backgrounds. Experiments conducted on an Side-Illuminated Light Field Bubble Database (SILB-DB) and a public gas–liquid two-phase flow dataset (GTFD) demonstrate that HSMD-YOLO achieves mAP@50 scores of 0.911 and 0.854, respectively, surpassing mainstream detection methods. Ablation studies indicate that SSB, GLRB, and BEMAF contribute performance gains of 1.3%, 2.0%, and 0.4%, respectively, thereby corroborating the effectiveness of each module for micro-scale object detection. Full article

Addressing the thermal management challenges of prismatic aluminum shell lithium battery modules in electric vehicles under high-rate charge–discharge conditions, this study proposes a multi-objective optimization design method for integrated biomimetic liquid cooling plates. By integrating various highly efficient heat transfer structures from nature, including fractal-tree-like networks, leaf vein branching systems, and spider web radial distribution, a novel biomimetic liquid cooling plate topology was constructed. A multi-physics coupled numerical model considering electrochemical heat generation, thermal conduction, convective heat transfer, and thermal stress deformation was established. The NSGA-II algorithm was employed to globally optimize 12 design variables including channel geometric parameters, operating conditions, and structural dimensions, achieving collaborative optimization objectives of maximum temperature minimization, temperature uniformity maximization, pressure drop minimization, and structural lightweighting. The weight coefficients for the four optimization objectives were determined through the Analytic Hierarchy Process (AHP) with verified consistency (CR = 0.02 < 0.10), ensuring rational priority allocation aligned with automotive safety standards. The optimization results demonstrated that compared to the initial design, the optimal solution reduced the maximum temperature under 3C discharge conditions by 9.9% to 34.7 °C, decreased the temperature difference by 31.3% to 3.3 °C, lowered the pressure drop by 24.6% to 2150 Pa, reduced structural mass by 4.0%, and decreased maximum stress by 16.7%. Quantitative comparison with single biomimetic structures under identical boundary conditions showed that the integrated design achieved a 3.3% lower maximum temperature and 25.7% better flow uniformity than the best-performing single structure, demonstrating the synergistic advantages of multi-biomimetic integration. These synergistic performance improvements can be attributed to the hierarchical multi-scale architecture where fractal networks provide macro-scale flow distribution, leaf vein branches ensure meso-scale coverage, and spider web radials achieve micro-scale thermal matching. Long-term cycling tests conducted at 1C/1C rate with 25 ± 1 °C ambient temperature showed that the optimized design maintained a capacity retention rate of 92.3% after 1000 charge–discharge cycles, demonstrating excellent durability. The complex biomimetic channel structure can be fabricated using selective laser melting technology with minimum feature sizes below 0.3 mm, indicating promising manufacturing feasibility. The research findings provide theoretical guidance and technical support for the engineering design of high-performance battery thermal management systems. Full article

In the context of a deep structural adjustment of China’s real estate sector and heightened macroeconomic uncertainty, quantitatively assessing the resilience of listed real estate enterprises is crucial for preventing systemic risk and promoting sustainable development. This paper proposes a multidimensional resilience evaluation framework for 37 Chinese A-share listed real estate firms using panel data from 2017–2024. An index system covering four dimensions—solvency and liquidity, profitability and cash flow, operational efficiency and asset structure, and growth and value—is constructed on the basis of financial ratios. The entropy-weighted TOPSIS method is employed to derive a composite resilience index, while principal component analysis (PCA) provides a complementary robustness check of the rankings. The empirical results indicate that (1) operational efficiency and asset structure receive the highest objective weight, followed by solvency and liquidity, whereas the weights of profitability, cash flow, and growth–value dimensions are relatively lower; at the indicator level, accounts receivable turnover, inventory turnover and the cash-to-short-term-debt ratio play a leading role, underscoring the central importance of liquidity safety and asset turnover under the “three red lines” regulatory regime. (2) Firms such as Shahe Co., Shenzhen, China, Huafa Co., Zhuhai, China and Wantong Development, Beijing, China exhibit persistently higher resilience scores, characterized by lower leverage, stronger cash buffers and faster operating turnover, whereas firms such as Yunnan Metropolitan Investment, Kunming, China, Greenland Holdings, Shanghai, China, Bright Real Estate, Shanghai, China and Rongsheng Development, Langfang, China remain at the lower tail of the resilience distribution with high leverage, tight liquidity and volatile profitability. (3) The resilience rankings obtained from entropy-weighted TOPSIS and PCA are positively and significantly correlated at the 1% level, suggesting a moderate level of consistency between distance-based and variance-based evaluation schemes. Building on these findings, this paper proposes resilience-oriented policy recommendations for regulators and managers in terms of differentiated prudential regulation, capital-structure and debt-maturity optimization, operational efficiency enhancement, and the integration of digital transformation and ESG governance. Full article

Ultrafine hematite particles (<10 μm), commonly generated in beneficiation circuits, exhibit poor flocculation and slow settling, posing challenges for solid–liquid separation. This study investigates the influence of the anionic polyacrylamide (APAM) molecular weight on ultrafine hematite flocculation under controlled laboratory conditions, combining macroscopic experiments with molecular dynamics simulations (MDSs). Sedimentation tests show that the APAM molecular weight strongly affects settling kinetics, supernatant clarity, and floc structure, with the settling rate, flocculation-stage reaction time, supernatant turbidity, and underflow concentration exhibiting a non-monotonic trend and optimal performance at seven million. Under this condition, particles aggregate most efficiently, achieving a turbidity of 182 NTU, an underflow concentration of 51.5%, and the largest compact flocs, averaging 379.8 μm with a fractal dimension of 1.71. Higher molecular weights (≥9 million) induce chain coiling, reduce floc compactness, increase water retention, and impair settling. MDS indicates that polymer–surface interactions improve with an increasing polymerisation degree only up to an intermediate chain length; a polymerisation degree of 30 exhibits the most favourable extended–flexible conformation, maximal surface enrichment, strongest coordination between carboxyl groups and surface Fe atoms, lowest adsorption energy, and fastest adsorption kinetics. The functional-group distribution and hydrogen-bond analyses show that –NH₂ and –COO^– groups dominate interfacial interactions, with a polymerisation degree of 30 yielding the highest density of interfacial hydrogen bonds. By correlating macroscopic experiments with molecular-scale observations, this work provides mechanistic insight into how the APAM chain length governs ultrafine hematite flocculation, highlighting the role of polymer conformation and multipoint adsorption in controlling the settling performance. Full article

Effective electrochemical CO₂ reduction to liquid fuels requires that the local catalytic environment facilitates the desired reactivity, yet a microscopic understanding of this environment is difficult to achieve from experiment alone. In this work, a 3D reaction-diffusion model was developed to explore the effects of electrode surface area and local geometry on the performance of a heterogeneous catalyst that performs a two-step CO₂ reduction cascade reaction to CO and then CH₃OH under aqueous conditions. Kinetic parameters for the model were inspired by experimental results using a cobalt phthalocyanine (CoPc) catalyst. Three-dimensional architectures composed of arrays of square pillars with varying dimensions and either smooth or periodically modulated surfaces were tested, revealing the extent to which geometry modulates the performance of the cascade reactions. Although structural variations modulate local concentration gradients, we find that electrochemically active surface area predominantly governs the overall cascade reaction. Moreover, the results suggest that supersaturation of CO, with concentrations up to ten-fold higher than the equilibrium solubility limit, might be critical for more efficient conversion to CH₃OH. For any given geometry, the spatially averaged ratio of [CO] to [CO₂] is dictated by the electrochemically active surface area and determines the yield of CH₃OH. For a fixed surface area, geometries that spatially confine the electrolyte yield moderate local [CO] to [CO₂] ratios within small volumes. In contrast, less confining geometries result in a broader distribution of local ratios spread over larger volumes, with both configurations yielding the same spatially averaged [CO] to [CO₂] ratio. These insights provide valuable design principles—highlighting the critical importance of surface area and possibly CO supersaturation—for engineering advanced electrode architectures that leverage intermediate trapping and CO supersaturation to enhance overall performance in tandem CO₂ reduction systems. Full article

The olive oil sector is one of the most important agri-food chains, but it is also characterised by the production of large volumes of solid and liquid by-products which, if improperly managed, have a significant environmental impact. In this context, circular economy approaches have been increasingly proposed to improve sustainability through the valorisation of by-products. This study investigates whether it is possible to conceptualise a circular business model for the olive oil supply chain by integrating by-products into the production system itself. The research adopts a systematic review of the literature supported by bibliometric techniques. The results show that current studies focus mainly on the technological and environmental aspects of by-product valorisation, particularly chemical extraction processes and environmental impact assessment, while the organisational, supply chain and governance dimensions remain fragmented. Based on these findings, the study develops an emerging conceptual framework that integrates by-product valorisation, supply chain configuration and enabling conditions, such as partnerships and political support, into a circular business model perspective. The study concludes that a circular business model for the olive oil supply chain is conceptually and technically feasible, but its implementation requires a systemic and integrated approach at the supply chain level rather than isolated technological solutions. Full article

Coal seam water injection is a widely used technique for dust suppression in coal mining. However, its effectiveness is often limited in low-permeability coal seams with poor wettability, primarily due to an unclear understanding of the wetting mechanism. To address this issue, a spontaneous imbibition model of a curved capillary bundle incorporating surface roughness elements was established based on the Hagen–Poiseuille equation. The accuracy of the proposed model was validated through experimental measurements, and the effects of different structural parameters on liquid imbibition behavior were systematically investigated. The results indicate that an increase in pore area fractal dimension significantly enhances the spontaneous imbibition capacity of water within coal pores. Moreover, the relative roughness inside pores increases with the minimum pore diameter, leading to a higher imbibition height. This suggests that increased relative roughness strengthens capillary attraction and promotes water migration in the pore structure. The proposed model provides a theoretical description applicable to the wetting stage of coal seam water injection and offers valuable insights for improving dust suppression efficiency in low-permeability coal seams. Full article

The exceptional mechanical strength and toughness of collagen arise from its well-defined hierarchical architecture. Conventional methods for obtaining collagen aggregates (CAs), such as direct extraction from native tissues or acid swelling followed by mechanical processing, offer limited control over dimensional uniformity and provide little insight into the underlying exfoliation mechanisms. To overcome these challenges, this study introduces a novel strategy that leverages insights into the hierarchical interactions within collagen. We employ the ionic liquid 1-allyl-3-methylimidazolium chloride ([AMIM]Cl) as an exfoliating agent to successfully isolate fibrous CAs from native bovine tendon. By precisely modulating temperature and processing time, we achieve CAs with tunable mesoscale dimensions (diameter 0.9–1.1 μm, length > 160 μm). Molecular dynamics simulations reveal that [AMIM]Cl disrupts the intramolecular hydrogen-bonding network within collagen, thereby facilitating controlled exfoliation. These exfoliated aggregates serve as fundamental building blocks for fabricating collagen films. The resulting materials exhibit robust mechanical integrity, high transparency, reversible pH-responsive behavior, and excellent biocompatibility as verified by cytotoxicity assays, which together underscore their potential as versatile biomaterial platforms. Furthermore, the integration of single-walled carbon nanotubes yields conductive composites with confirmed electrical functionality. This study thus presents an innovative pathway for the precision processing of collagen and advances the design of high-performance collagen-based biomaterials. Full article

Linalyl acetate is a key bioactive component of essential oils with notable calming and sedative effects; however, its high volatility severely limits stability and practical application. Herein, bimodal mesoporous silica (BMMs) was employed as an efficient carrier to encapsulate linalyl acetate using liquid- and gas-phase loading strategies, enabling high loading capacity and sustained release. Under optimized gas-phase conditions (600 mg·mL⁻¹, 85 °C, 2 h), a maximum loading capacity of 80.13% was achieved. The X-ray diffraction (XRD) and small-angle X-ray scattering (SAXS) patterns, scanning electron microscopy (SEM) images, N₂ adsorption–desorption isotherms, Fourier transform infrared (FT-IR) spectra, and thermogravimetric (TG) performances confirmed the successful confinement of linalyl acetate within the bimodal mesoporous channels. Particularly, the SAXS patterns revealed the pronounced fractal characteristics, whereas the increased mass-fractal dimension (D_m) values indicated the enhanced structural compactness, and higher surface-fractal dimension (D_s) values reflected increased surface roughness upon loading. Release experiments conducted in an open environment demonstrated an excellent sustained-release performance, with only 22.41% of linalyl acetate released from BMMs over 30 days, compared with 94.41% for the free compound. Molecular dynamics simulations further elucidated that the interactions between linalyl acetate molecules and surface silanol groups dominated the adsorption process and governed diffusion within the mesoporous channels. These findings suggested that BMMs provide a robust platform for stabilizing volatile fragrance compounds and achieving long-term controlled release. Full article

Self-sustained oscillatory systems enable autonomous motion through continuous interaction with ambient energy sources, positioning them as promising candidates for soft robotic actuation, energy conversion, and biomedical applications. However, their utility is often limited by inherent vibrations and frictional losses, which can lead to impaired efficiency and generate noise. To overcome these limitations, a continuously rotating disc mechanism is proposed, which exploits the photothermal response of liquid crystal elastomers (LCEs) under uniform illumination. The resulting temperature field within the material is obtained via photothermal modeling of the LCE. The rotational actuation torque is generated through mass displacement resulting from light-induced LCE contraction. Based on the above conditions, we establish the equilibrium conditions and critical thresholds for continuous motion and reveal a synergy between the thermal field and torque. Through the interplay of the temperature field and the actuating rotating moment, the system ultimately attains steady self-rotation. Therefore, the absorbed energy offsets damping losses. Numerical simulations reveal that the steady-state self-spinning and translational velocity are influenced by multiple parameters including incident heat flux, gravitational field strength, material contraction coefficient, LCE element dimensions, illumination geometry, and resistive torque. The proposed LCE disc configuration exhibits exceptional operational stability and minimal damping, which has potential for implementation in advanced soft robotic systems and mechanical energy conversion applications. Full article