Search Results (4,614)

This work investigated the potential of different natural fillers, i.e., clay, calcium carbonate, and silica, as sustainable alternatives to glass fibers (GFs) in polyamide 6 (PA6) for Large-Format Additive Manufacturing (LFAM) applications in order to guarantee the chemical recyclability of the produced materials. Specifically, PA6-based composites containing ≤ 10 wt% natural fillers were compared with a conventional system (30 wt% GF-reinforced PA6) from rheological, morphological and thermo-mechanical perspectives. Rheological analysis showed that silica- and clay-filled samples displayed similar rheological response to the GF-filled reference due to their large particle size. Thermal analyses revealed a slight increase in crystallinity (up to 32%) for filled samples, indicating a potential nucleating effect of the natural fillers. Calcium carbonate-filled composites achieved thermal conductivity values comparable to the GF-filled reference (≥0.42 W/mK) indicating a high heat dissipation capability during printing operations. Morphological analysis performed on preliminary LFAM components revealed satisfactory printing quality and good filler dispersion. Flexural tests showed that silica and calcium carbonate could provide a balanced mechanical response, thereby reducing the anisotropy of printed components. These results demonstrated that the addition of suitable natural fillers at limited concentrations (≤10 wt%) can represent a lightweight and eco-sustainable alternative to GF reinforcement in LFAM applications. Full article

This study develops a progressive damage failure criterion to address limitations of traditional instantaneous strength criteria that cannot capture damage evolution or quantify accumulation mechanisms in coalbed methane (CBM) wellbore collapse analysis. A damage variable D defines four evolutionary stages—initiation, propagation, acceleration, and coalescence—coupled with stress redistribution and drilling fluid invasion effects to enable quantitative collapse period prediction. Three-dimensional numerical simulations using FLAC3D 7.0 (Itasca Consulting Group, Minneapolis, MN, USA) reveal that stress anisotropy controls directional damage initiation, while increasing the horizontal stress ratio K substantially reduces the safe collapse period and narrows the safe drilling fluid density window. Horizontal wells exhibit significantly higher collapse pressure requirements than vertical wells, providing a quantitative basis for trajectory optimization. Model predictions show good agreement with published experimental results, with maximum deviations of ≤10% for the collapse period and ≤9% for damage depth. Field applications demonstrated notably fewer wellbore stability incidents and improved drilling efficiency compared to conventional design approaches, validating the practical effectiveness of the proposed methodology for unconventional resource development. Full article

Heat treatment is essential for In625 fabricated by laser powder bed fusion (L-PBF), as it significantly influences microstructural evolution, defect behavior, and mechanical performance. In this study, the effects of different solution heat treatments on L-PBF-fabricated In625 were systematically investigated. Industrial computed tomography was employed to characterize internal defects before and after heat treatment, while optical microscopy, EBSD, TEM, and EDS were used to analyze microstructural evolution. Room-temperature tensile tests evaluated mechanical properties. The results show that heat treatment at 1090 °C reduces porosity from 0.33% to 0.25%, whereas increasing the temperature to 1150 °C results in a further increase in porosity to 0.45%. This non-monotonic behavior is interpreted as the result of competing mechanisms, including partial closure of small pores at 1090 °C and pore coarsening/enlargement at higher temperatures, with the latter possibly involving the growth of sub-resolution pores into the CT-detectable range. Complete grain equiaxiality occurs after heat treatment at 1090 °C or higher, with average grain sizes below 100 μm, although grain coarsening becomes pronounced at higher temperatures. Samples heat-treated at 1150 °C exhibit reduced mechanical anisotropy, achieving tensile strength above 919 MPa and elongation up to 60%. These results clarify the mechanisms by which heat treatment governs microstructure–defect–property relationships in L-PBF In625, guiding its engineering application. Full article

This study presents an analytical framework for evaluating the admissibility of biaxial inclination of rectangular sinking wells. The inclination of the well is interpreted as an eccentric transfer of the vertical load to the concrete plug, which produces a two-dimensional linear stress field beneath the base. Closed-form expressions are derived for the stresses at the four corners of the rectangular base as functions of the eccentricity components associated with the two orthogonal tilt directions. Based on these expressions, the admissibility of inclination is represented by a tilt envelope in the space of the two tilt angles, defining the combinations of tilt components that satisfy the adopted serviceability criterion. The analytical formulation also allows for comparison between the stress-based admissibility limit, the geometric condition corresponding to loss of compressive contact beneath the base, and a simplified indicator of lateral wall-pressure asymmetry acting on the shaft. Parametric analyses show that biaxial inclination leads to stress concentration at the corners of the base and that even relatively small tilt components may combine to produce significant stress amplification. The geometry of the well strongly influences the shape of the admissible tilt envelope, with elongated rectangular wells exhibiting directional anisotropy of the allowable inclination. The proposed analytical approach provides a transparent tool for evaluating inclined wells using basic geometric parameters in engineering practice. Full article

Background/Objectives: Early postnatal nutrition is a modifiable determinant of brain maturation in preterm infants. Exclusive human milk-based diets (EHMD) are associated with improved neurodevelopmental outcomes. The objective of this exploratory ancillary analysis of the NEOVASC randomized controlled trial was to determine whether prolonging an exclusive human milk-based diet, specifically through continued human milk-based fortification until 36 weeks postmenstrual age, is associated with differences in early brain structure and functional motor development compared with earlier introduction of bovine milk-based fortifier or formula at 32 weeks postmenstrual age. Methods: This ancillary study of the NEOVASC trial included preterm infants (<32 gestational weeks and birthweight of 500–1250 g) randomized to either prolonged EHMD until 36 weeks PMA or a diet introducing bovine milk-based fortifier or formula from 32 weeks. Quantitative brain metrics, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) were analyzed at 40 weeks PMA. Functional maturation was assessed repetitively using the General Movement Optimality Score (GMOS) (34, 36, and 40 weeks PMA) and Motor Optimality Score (52 weeks PMA). Results: Fifty-four infants were included. Groups did not differ in brain growth metrics. After adjustment for imbalances in clinical characteristics, no FA or ADC differences remained statistically significant. GMOS at 40 weeks PMA was higher in the intervention group, with no differences at other time points. Conclusions: In this exploratory ancillary analysis of the NEOVASC trial, prolonging an exclusive EHMD until 36 weeks postmenstrual age was not associated with consistent differences in early brain maturation or motor performance. Given the high overall exposure to human milk in both groups, subtle effects may have been attenuated. These findings require confirmation in larger, adequately powered studies with long-term follow-up. Full article

The simultaneous analysis of geometric morphology and thermodynamic states from heterogeneous sensing modalities is essential for high-temperature industrial inspection. While supervoxel segmentation is effective for extracting fine structures, conventional fixed-weighting schemes often struggle with the inherent heterogeneity between spatial sensors and thermal sensors. This paper proposes a segmentation framework for thermo-geometric point clouds based on Pareto-optimal weight learning and gradient anisotropy. A multi-objective evolutionary optimization algorithm is employed for multi-modal Pareto weight learning to adaptively balance geometric and thermal constraints. The developed gradient-anisotropic supervoxel generation algorithm introduces a local saliency factor to achieve fine-grained thermodynamic segmentation. Furthermore, a gradient damping mechanism is implemented to ensure high thermal-boundary adherence even in geometrically planar regions by imposing anisotropic penalty forces. Finally, a region-growing method based on the optimized multi-sensor fusion weights is utilized to merge similar supervoxels. Experimental results demonstrate that our approach outperforms traditional baselines by achieving high-fidelity thermal segmentation and multi-modal boundary preservation, while accepting a modest and necessary compromise in geometric compactness to accommodate spatial–thermal inconsistencies. Full article

Parkinson’s disease (PD) may benefit from non-pharmacological motor–cognitive rehabilitation, but sensitive neuroimaging markers of training-related brain changes remain limited. This study investigated whether 4 weeks of daily Quadrato Motor Training (QMT) modulate resting-state functional connectivity (FC) in PD and secondarily explored whether whole-brain radiomic features derived from T1-weighted and fractional anisotropy (FA) images could detect pre–post differences over this short intervention interval. Fifty patients with idiopathic PD were randomized to QMT or a SHAM repetitive stepping condition, and 48 completed the protocol (25 SHAM, 23 QMT). MRI was acquired at baseline and after 4 weeks and included resting-state fMRI, 3D T1-weighted imaging, and diffusion-derived FA maps. Resting-state fMRI was analyzed using independent component analysis and dual regression, whereas an IBSI-compliant radiomics workflow and machine-learning models were used for exploratory scan-level classification. Compared with baseline, the SHAM group showed reduced synchronization across several resting-state networks, whereas the QMT group showed increased synchronization in the right sensorimotor and frontoparietal networks and no significant reductions. Between-group analyses showed lower delta-FC in SHAM than QMT in the cerebellar and sensorimotor networks. In contrast, radiomics showed limited discrimination between pre- and post-QMT scans; the best model achieved a ROC-AUC of 0.65 with near-chance accuracy, and no selected predictor remained significant after multiple-comparison correction. These findings suggest that QMT may support short-term functional network stability or task-relevant reorganization in PD relative to the SHAM condition, whereas whole-brain structural radiomics appears less sensitive for detecting early training-related effects in this setting. Full article

Triaxial induction logging is particularly outstanding in identifying reservoir parameters including anisotropic strata, inclined boreholes and horizontal wells. However, the coplanar systems follow the traditional induction method of using a shielding coil to offset the direct coupling. This method results in severe horns in the coplanar coil response, which makes it more difficult to evaluate the water (oil) saturation of the reservoir. In this study, we used an analytic method to derive the magnetic field in a finite-thickness anisotropic medium by applying tangential continuity of the electric and magnetic field strengths, introducing the magnetic vector potential and Bessel functions. The response model influenced by different parameters was established. Under the same environmental parameters, the measurement range of the vertical and horizontal conductivities was larger than that of the traditional coplanar system. The apparent conductivity of the target layer was closer to the true value of the vertical conductivity in the layered strata, with an accuracy improvement of 78.9%. Furthermore, the improved coplanar system mechanism was revealed by analyzing the spatial distributions of eddy currents and the magnitudes of the magnetic fields generated. Finally, we designed an experimental device for a coplanar sensing system. Under the same parameters, the received signals of the improved coplanar system were greater than those of the traditional coplanar system in the air, which laid a foundation for the quantitative evaluation of stratigraphic anisotropy response characterization and inversion. Full article

The surface quality of granite cut by diamond wire saw significantly impacts the cost of subsequent processes such as grinding and polishing. Traditional evaluation parameters like surface roughness (Ra) or peak-to-valley value (PV) face challenges in characterizing the surface morphology. This study introduces fractal dimension (FD) as a potential auxiliary parameter for evaluating the surface quality of sawn granite. Cutting experiments were conducted on Shanxi Black granite using varying wire speeds, feed speeds, and workpiece sizes. The box-counting method was employed to extract the three-dimensional fractal dimension (3D FD) of the granite surface, which characterizes the overall surface complexity, as well as the distribution of two-dimensional fractal dimensions (2D FD) for granite surface cross-sectional profiles at different angles. The results indicate that the granite-sawn surface exhibits complex micro-morphology featuring brittle micro-pits and wavelike saw marks along the feed direction. A strong negative correlation exists between the 3D FD and both surface roughness Ra and PV value, suggesting that 3D FD can serve as an indicator of granite surface quality, with higher FD values corresponding to better surface quality. Moreover, compared to the PV value constrained by material heterogeneity, 3D FD more effectively represents the true surface quality of the granite. Additionally, the distribution characteristics of 2D FD at different angles effectively reveal surface anisotropy and damage. The results suggest that a more symmetrical 2D FD distribution is associated with consistent surface integrity in the evaluated samples. This suggests that FD has the potential to serve as a meaningful auxiliary parameter for characterizing granite surface quality. The findings hold significant importance for the accurate evaluation of diamond wire-saw-cut granite surfaces and provide a basis for the formulation of subsequent grinding process. Full article

The clinical utility of the anticancer drug camptothecin (CPT) is limited by its poor aqueous solubility and instability in the bloodstream, hindering bioavailability and efficacy. This study explores the complexation of CPT with carboxymethyl-beta-cyclodextrin (cmβCD) to overcome these limitations. Fluorescence spectroscopy and molecular modeling demonstrated 1:1 inclusion complexes, with stability constants governed by electrostatic interactions that were inversely correlated with pH. To validate this effect, a cationic amino-beta-cyclodextrin (amβCD) was used as a mechanistic control, revealing that Coulombic forces significantly modulate binding strength and stoichiometry. Crucially, cmβCD enhanced CPT solubility by up to 11-fold at 14 × 10⁻³ moldm⁻³, enabling a 385-fold increase in drug loading into liposomal carriers compared to the cyclodextrin-free system. Fluorescence-based release studies indicated high liposomal stability at physiological pH and partial CPT release under acidic conditions. Furthermore, CPT-loaded liposomes demonstrated cytotoxicity against cancer cell lines, particularly BT-474, with IC₅₀ values generally comparable to or slightly higher than those of free CPT and the CPT:cmβCD complex, likely due to the distinct lysosomal cellular uptake pathway. This work highlights cmβCD complexation as a promising strategy to enhance CPT solubility and liposomal loading for improved drug delivery. Full article

Liquid nitrogen (LN₂) fracturing is a highly promising stimulation technology for unconventional reservoirs. Understanding its in situ fracture network formation mechanism is essential for engineering practice. This study investigates coal rock fracturing driven by the synergistic effect of thermal stress and fluid pressure during LN₂ injection. A coupled thermal–hydraulic–mechanical–damage (THMD) numerical model is developed, incorporating in situ stress conditions and LN₂ phase change behavior. Through true triaxial LN₂ fracturing simulations validated against physical experiments, the multi-field dynamic coupling behavior is systematically analyzed, revealing the synergistic mechanism of fracture propagation and permeability enhancement under cryogenic conditions. The results show the following: (1) The proposed model effectively reproduces the true triaxial LN₂ fracturing process, with simulation results in good agreement with physical experiments. (2) LN₂ fracturing exhibits distinct stage-wise characteristics: cryogenic temperatures induce thermal stress that triggers micro-crack initiation; the self-enhancing effects of damage and permeability significantly promote fracture propagation; fluid pressure then becomes the dominant driving force. (3) Coal rock damage follows a four-stage evolution—wellbore crack initiation, stable propagation, unstable propagation, and through-going failure—ultimately forming a complex spatial fracture network. (4) The horizontal stress ratio is a key factor controlling fracture morphology: a single dominant fracture forms under a high stress difference, whereas a multi-directional complex network develops under equal confining pressure. Fractal analysis reveals significant anisotropy and a non-monotonic stress response in the fracture complexity, reflecting structural evolution from multi-directional propagation to main channel connection. This study provides theoretical support for understanding LN₂ fracturing mechanisms and optimizing field treatment parameters. Full article

Permeability anisotropy, which is widely present in natural soil deposits, plays an important role in controlling groundwater flow patterns and ground deformation during deep excavation dewatering. However, isotropic assumptions are still commonly adopted in engineering practice, making it difficult to accurately capture realistic subsurface hydraulic conditions. In this study, a deep foundation pit of a metro station in Jinan, China, is taken as a case study. A three-dimensional excavation–dewatering model incorporating permeability anisotropy is established using PLAXIS 3D to systematically investigate the influence of the permeability ratio (Kx/Kz) ranging from 0.1 to 10 on the seepage field evolution, dewatering influence radius, ground surface settlement, and consolidation time history. The results indicate that increasing permeability anisotropy promotes a fundamental transition of the seepage regime from vertically concentrated recharge to laterally dominated radial flow. Correspondingly, the dewatering influence radius exhibits a pronounced non-monotonic response to Kx/Kz, decreasing significantly with increasing permeability ratio and reaching a minimum at approximately Kx/Kz ≈ 5, followed by a slight rebound. Meanwhile, surface settlement profiles evolve from a localized concentration pattern to a widely distributed form as permeability anisotropy increases, accompanied by a remarkable outward expansion of the settlement influence zone. Both the magnitude and spatial distribution of settlement show high sensitivity to variations in permeability anisotropy. Based on these findings, a three-stage conceptual seepage structure model accounting for permeability anisotropy is proposed, characterized by vertically dominated flow, a transitional competition regime, and horizontally dominated flow. The staged evolution of seepage structures is shown to govern the non-monotonic variation in the dewatering influence radius and the spatial–temporal response of ground settlement. The results indicate a dual-scale influence mechanism of permeability anisotropy on dewatering-induced hydro-mechanical behavior, providing a theoretical basis for refined dewatering design and environmental impact assessment in deep excavation projects. Full article

Flow lines in aluminum alloy forgings are not merely post-deformation metallographic features; they are integrated indicators of material transport, microstructural evolution, defect susceptibility, and service performance. This review critically examines the mechanisms controlling flow-line evolution, with emphasis on constitutive flow behavior, dynamic recovery and recrystallization, second-phase redistribution, friction, thermal gradients, and die/preform design. It then evaluates how abnormal flow paths promote key defects, including folding/laps, flow-through discontinuities, vortex-like instability, and exposed flow lines, and distinguishes well-established mechanisms from topics that still rely on indirect evidence. Particular attention is given to the effects of flow-line morphology on anisotropy, notch sensitivity, corrosion-assisted damage, and fatigue life in forged aluminum alloys. Current control strategies, including preform optimization, FE-based backward tracing, multiphysics defect indices, frictional heat management, and isothermal forging, are also assessed. The available literature shows that stable contour-following flow lines are essential for the simultaneous control of defect formation, microstructural homogeneity, and durability, while major research needs remain in in situ validation, quantitative defect criteria, and digitally closed-loop process control. This review is therefore framed as a critical narrative synthesis rather than a formal systematic review; emphasis is placed on forging-centered studies that directly relate flow-path evolution to defect formation, anisotropy, fatigue, and process optimization, while evidence transferred from adjacent processes is treated as mechanistic support rather than equivalent proof. Full article

3D Concrete Printing (3DCP) is increasingly explored as a digital fabrication technology offering design freedom, automation, and material efficiency. Nevertheless, its application in reinforced and long-life structures remains limited by insufficient understanding and poor comparability of durability performance, as previous reviews have not systematically linked methodologies to transport-related results. This study presents a systematic and critical review of carbonation and chloride ingress in 3DCP cementitious materials, conducted in accordance with the PRISMA methodology. Following a structured database search and two-stage screening process, the selected studies are subjected to qualitative analysis. Experimental methodologies, specimen typologies, exposure conditions, and attack directions are compiled and qualitatively compared. The review highlights pronounced methodological heterogeneity and frequent under-reporting of key parameters, particularly attack direction, sealing conditions, CO₂ concentration, and indicator methods, limiting cross-study comparison. Despite these limitations, consistent qualitative trends are identified. Printed specimens generally exhibit inferior durability performance than cast specimens, while cold joints are associated with increased penetration depth and result dispersion. Directional effects are non-negligible, although they are systematically addressed in only a limited number of studies. Overall, the findings emphasise the critical role of process-induced features and the need for harmonised testing methods to enable reliable durability assessment. Full article

Accurate identification of cultivated land planting types is essential for agricultural resource management and national food security. Traditional optical remote sensing approaches are susceptible to weather interference in cloudy regions, making continuous crop growth monitoring challenging to achieve. To address this limitation, this study proposes a crop classification framework based on time-series Sentinel-1A SAR imagery combined with Recurrent Neural Networks (RNN), using Chongming Island, Shanghai as the experimental area. The framework integrates backscattering coefficients (VV, VH, VV/VH ratio) with polarimetric decomposition parameters (entropy H, scattering angle alpha, anisotropy A) as multi-dimensional temporal input features, and employs decision-level voting to obtain plot-level classification results. Experiments on three classification tasks (Rice versus Non-Rice, Wheat versus Non-Wheat, and multi-class rotation patterns) demonstrate that the proposed method achieves pixel-level accuracies of 99.72%, 99.60%, and 98.39% respectively using the six-dimensional BSPD model, with plot-level F1 scores exceeding 0.990 across all tasks. The fusion of polarimetric decomposition features reduces classification errors by up to 70% compared with backscattering-only features, particularly improving discrimination of phenologically overlapping crop categories. These results confirm that multi-dimensional temporal features extracted from dense time-series SAR imagery significantly enhance crop classification accuracy in all-weather conditions. Full article