Search Results (4,809)

This study presents a carbon footprint assessment of a novel electroslag method for cadmium (Cd) recovery from spent nickel–cadmium (Ni-Cd) batteries in comparison with the carbon footprints of pyrometallurgical and hydrometallurgical cadmium recovery methods. A comparison of CO₂ emissions in three types of technological processes during the recovery of 1 kg of cadmium is carried out. Energy inputs and CO₂ emissions are calculated for the electroslag process and compared to conventional methods, such as pyrometallurgical and hydrometallurgical reduction methods. The electroslag process eliminates cadmium vaporization by using molten KCl–NaCl flux and carbon under electromagnetic stirring. Cadmium reduction occurs under a layer of flux, which prevents the contact of the reduced cadmium with the atmosphere. The electroslag process temperature is limited to 700 °C, which is lower than the boiling point of cadmium (767 °C). The electroslag remelting process uses molten KCl–NaCl flux and carbon as a reductant under electrovortex flow stirring. The pyrometallurgical method for extracting cadmium from nickel–cadmium batteries is based on the reduction of cadmium with carbon at high temperatures. In the pyrometallurgical process, coal (anthracite) is used as the carbonaceous material, which can extract 99.92% of cadmium at 900 °C. Cadmium is separated using a vacuum at temperatures ranging from 800 °C to 950 °C for several hours. Hydrometallurgy is a metal extraction process involving chemical reactions that occur in organic or aqueous solutions at low temperatures. The hydrometallurgical process involves a series of acid or alkaline leaches, followed by separation and purification methods such as absorption, cementation, ion exchange, and solvent extraction to separate and concentrate metals from leach solutions. Full article

The aerodynamic performance of nacelle inlets under crosswind conditions is crucial for engine stability and efficiency. Current parametric investigations are predominantly focused on cruise operations, with minimal consideration given to crosswind conditions. This study employs an iCST-based parametric modeling approach to construct geometric models. A systematic examination of key geometric parameters—including the throat axial location, fan face radius, and leading-edge radii of the inner and outer contours is conducted. The reliability of the numerical methodology was established through a two-step validation process using both the iCST-generated non-axisymmetric model and the DLR-F6 benchmark model, followed by a geometric sensitivity analysis based on parametrically generated axisymmetric models. The results demonstrate that the inner contour leading-edge radius (ROC_I/R_hi) has the most substantial influence on flow separation. When ROC_I/R_hi decreases from 7.84% to 3.46%, the peak maximum circumferential total pressure distortion index (IDCmax) is increased by 86.78% with a 53.85% rearward shift in the complete reattachment mass flow rate. Correspondingly, a similar reduction in the outer contour leading-edge radius (ROC_O/R_hi) from 9.38% to 4.69% results in a 55.50% increase in peak IDCmax and a 33.33% rearward shift. Comparatively, the fan face radius shows minimal impact on flow distortion (increases by 9.72%), but more pronounced effects on total pressure recovery, while rearward movement of the throat axial location (35.00% to 69.00%) causes a 30.03% rise in IDCmax and 43.75% complete flow reattachment delay. It is concluded that the leading-edge optimization is crucial for crosswind resilience, with the inner contour geometry being particularly influential, providing parametric foundations for robust inlet design across a wide range of operating regimes. In addition, it is also found that the effects of Reynolds number (Re) lie in two folds: (1) For a fixed model scale, the aerodynamic performance of the inlet suffers a remarkable degradation with rapidly rising IDCmax as the crosswind velocity-based Re is increased to cause significant flow separations. (2) For a fixed crosswind velocity, the peak IDCmax progressively decreases with the increasing scale based Re, while σ exhibits an overall enhancement as Re rises. Full article

While normal fibroblasts suppress tumor growth, during cancer initiation and progression, this capacity can be lost and even switched to tumor-promoting, for reasons that are not understood. In this study, we aimed to determine differences between patient-derived cancer-associated fibroblasts and fibroblasts from healthy breast tissue to identify if and how these changes stimulate Triple-negative breast cancer (TNBC). Two-dimensional and three-dimensional mono and co-cultures of TNBC cells with fibroblasts from healthy breast or TNBC were analyzed for cell contractility, migration, distribution, proliferation, and hyaluronan production by traction force microscopy, live cell imaging, flow cytometry, Western blot, and ELISA. In 3D spheroid co-culture, CAFs migrated into the tumor mass, mixing with tumor cells, whereas normal fibroblasts remained separate. In 2D, CAFs showed increased cell migration and contractile force, and, in both 2D and 3D co-culture, CAFs increased the proliferation of TNBC cells. CAFs showed increased production of hyaluronan, as compared to normal fibroblasts, and loss of hyaluronan synthase 2 reduced CAF-induced stimulation of TNBC proliferation. These findings suggest that increased production of hyaluronan by TNBC CAFs enhances their capacity to mix with and induce the proliferation of cancer cells, and that the production of hyaluronan by CAFs can be a future therapeutic target against TNBC. Full article

Background: The fat-tailed coarse-wooled sheep breeds exhibit excellent reproductive performance, exceptional adaptability to pasture conditions, and high precocity, contributing to enhanced meat, fat, and wool productivity in sheep breeding. Despite the significant role of these sheep breeds in Kazakhstan’s livestock production, their genetics remain poorly studied. This raises concerns about the potential loss of unique, breed-specific traits that could be important for the future development and resilience of Kazakh stan’s sheep farming sector. This study aimed to analyze genome-wide genotyping SNP data of local fat-tailed coarse-wooled sheep breeds (Kazakh fat-tailed coarse-wooled, Edilbay, and Gissar) to reveal their genetic diversity, breed characteristics, and phylogenetic relationships with worldwide domestic sheep breeds and wild sheep. Methods: The OvineSNP50 Genotyping BeadChip was used to obtain genome-wide SNP genotyping data from 160 fat-tailed coarse-wooled sheep from Kazakhstan. Population structure analysis, principal component analysis, phylogenetic and the maximum likelihood tree analysis were performed in comparison with foreign domestic sheep breeds and wild sheep populations. Results: Kazakh breeds exhibited high genetic diversity, with Edilbay showing the greatest allelic richness. PCA and Admixture revealed clear differentiation among the three breeds: Edilbay and Gissar formed homogeneous clusters, while Kazakh fat-tailed coarse-wooled sheep displayed admixture and substructure. Evidence of gene flow from Edilbay into other Kazakh populations supports its role as a genetic source for regional breeds. Phylogenetic analysis placed Kazakhstani sheep close to other Central Asian breeds, while clearly distinct from East Asian and European populations. Wild sheep (Argali and Urial) formed separate clades, with Kerman wild sheep clustering closer to Urial. Conclusions: Our results highlight the value of genotyping data for studying genetic diversity and population structure. Developing genetic resources for Kazakhstan’s native sheep breeds will help preserve their unique diversity and ensure it remains available for future use in breeding and adaptation efforts. Full article

This study developed an automated multistage countercurrent extraction device and applied it to the separation and extraction of phenolic acids—including neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, and isochlorogenic acid C—from an aqueous extract of Lonicera japonica Thunb. The extraction process was optimized by systematically evaluating critical parameters such as liquid–liquid equilibrium pH, internal diameter of the tee connector, phase flow rate ratio, and the number of extraction stages. The apparent partition coefficients of all six phenolic acids increased with decreasing aqueous pH, with fitted pKa values ranging from 3.7 to 4.3. A reduction in tee diameter (0.75 mm) was found to enhance mass transfer efficiency. Increasing the flowrate of both phases (20 mL/min), the organic-to-aqueous phase ratio (4:1), and the number of extraction stages (3 stages) significantly improved both stage efficiency and overall extraction yield. Under optimized conditions, the target chlorogenic acids were efficiently enriched, with their total content increasing from 50.3 mg/g to 70.1 mg/g in the solid residue after three countercurrent stages. The automated multistage countercurrent extraction system demonstrated robust performance, suggesting promising potential for applications in the preparation of traditional Chinese medicine ingredients or as an automated sample pretreatment method in analytical workflows. This study provides a novel and green technological solution for efficient separation of complex TCM systems. Full article

Significant chromite losses to tailings in gravity separation plants arise from both suboptimal separator design and inefficient beneficiation processes, posing major challenges to resource utilization, energy efficiency, and environmental sustainability. These losses are particularly critical because the material, already comminuted to liberation size, is discarded, leading to reduced concentrate yield, wasted energy input, and increased environmental pollution. To address this issue, an industrial-scale custom-designed shaking table was developed and tested to recover marketable-grade chromite concentrate (≥42% Cr₂O₃) from processing plant tailings containing 3.25%–4.25% Cr₂O₃, which had accumulated over years of chromite beneficiation. Experimental results showed that, under optimized operating parameters (320 rpm stroke frequency, 13 mm stroke length, 1° deck slope, 1300 g/L pulp density, 800 kg/h feed rate, and 7 tph wash water flow rate), Cr₂O₃ recovery increased from 8% to 27% for the first and second floor operations and from approximately 17% to 41% for the third and fourth floor operations compared with existing plant performance. The results revealed a strong interdependence between Cr₂O₃ recovery and concentrate grade, both of which are critical indicators of process efficiency. Intermediate particle sizes (−0.250 + 0.150 mm) provided the most favorable balance, yielding high recovery rates without substantially compromising the concentrated grade. Full article

Background/Objectives: Cerebral blood flow (CBF) and cerebral blood volume (CBV) are critical perfusion metrics in diagnosing ischemic stroke. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables the evaluation of these cerebral perfusion metrics; however, accurately assessing them remains challenging. This study aimed to: (1) assess CBF asymmetry by quantifying and comparing it between contralateral hemispheres (right vs. left) within the MCA, ACA, and PCA territories using paired t-tests, and describe pattern of CBV; (2) evaluate overall inter-territorial regional variations in CBF across the different cerebral arterial territories (MCA, ACA, PCA), irrespective of the hemisphere, using ANOVA; (3) determine the correlation between CBF and CBV using both Pearson’s and Spearman’s correlation analyses; and (4) assess the influence of age and gender on CBF using multiple regression analysis. Methods: A cross-sectional study of 55 ischemic stroke patients was conducted. DCE-MRI was used to measure CBF and CBV. Paired t-tests compared contralateral hemispheric CBF in MCA, PCA, and ACA, one-way ANOVA assessed overall inter-territorial CBF variations, correlation analyses (Pearson/Spearman) evaluated the CBF-CBV relationship, and linear regression modeled demographic effects. Results: Significant contralateral asymmetries in CBF were observed for each cerebral pair of cerebral arteries using a paired t-test, with descriptive asymmetries noted in CBV. Separately, ANOVA revealed significant overall variability in CBF between the different cerebral arteries, irrespective of hemisphere. A strong positive correlation was found between CBF and CBV (Pearson r = 0.976; Spearman r = 0.928), with multiple regression analysis identifying age and gender as significant predictors of CBF. Conclusions: This study highlights hemispheric asymmetry and inter-territorial variation, the impact of age, and gender on CBF. DCE-MRI provides perfusion metrics that can guide individualized stroke treatment, offering valuable insights for therapeutic planning, particularly in resource-limited settings. Full article

The uneven distribution of airflow on the blade surface of a yaw wind turbine triggers a complex non-constant flow, resulting in turbine flow field operation disorder, which, in turn, affects the structural field. In view of the different degrees of influence of different blade materials on the structural characteristics of a wind turbine, a numerical simulation of the flow field and structural field of the horizontal-axis wind turbine under different yaw conditions is carried out by using the fluid–solid coupling method to quantitatively analyse the degree of influence of the material on the structural characteristics of the wind turbine. The results show that the average velocity of the wake cross-section shows a trend of decreasing, then increasing, and then stabilising at all yaw angles. The larger the yaw angle, the wider is the vortex structure dispersion. As the wake develops downstream, the turbulence intensity is shown to decrease and then increase, and the yaw perturbation exacerbates the turbulence disorder in the wake flow field. Along the wind turbine blade spreading direction, the blade deformation phenomenon is significant. The yaw angle increases, the wind turbine blade deformation increases, and the maximum blade stress first increases and then decreases. At a 15° yaw angle, the airflow on the blade surface is more easily separated, and vortices are formed in the vicinity, which impede the airflow in the boundary layer and lead to a reduction in the velocity in the boundary layer in this region. The minimum deformation and maximum stress of the three materials under a 15° yaw angle indicate that the blades are more capable of resisting external deformation under this condition, so 15° yaw is the best operating condition for the wind turbine. This paper employs different materials to quantitatively analyse the extent to which structural characteristics influence wind turbine performance. The findings from this research can provide valuable insights for optimising wind turbine designs. Full article

Accurate and efficient CFD simulations are essential for a wide range of engineering and scientific applications, from resilient structural design to environmental analysis. Traditional methods such as RANS simulations often face challenges in capturing complex flow phenomena like separation, while high-fidelity approaches including Large Eddy Simulations and Direct Numerical Simulations demand significant computational resources, thereby limiting their practical applicability. This paper provides an in-depth synthesis of recent advancements in integrating artificial intelligence and machine learning techniques with CFD to enhance simulation accuracy, computational efficiency, and modeling capabilities, including data-driven surrogate models, physics-informed methods, and ML-assisted numerical solvers. This integration marks a crucial paradigm shift, transcending incremental improvements to fundamentally redefine the possibilities of fluid dynamics research and engineering design. Key themes discussed include data-driven surrogate models, physics-informed methods, ML-assisted numerical solvers, inverse design, and advanced turbulence modeling. Practical applications, such as wind load design for solar panels and deep learning approaches for eddy viscosity prediction in bluff body flows, illustrate the substantial impact of ML integration. The findings demonstrate that ML techniques can accelerate simulations by up to 10,000 times in certain cases while maintaining or improving the accuracy, particularly in challenging flow regimes. For instance, models employing learned interpolation can achieve 40- to 80-fold computational speedups while matching the accuracy of baseline solvers with a resolution 8 to 10 times finer. Other approaches, like Fourier Neural Operators, can achieve inference times three orders of magnitude faster than conventional PDE solvers for the Navier–Stokes equations. Such advancements not only accelerate critical engineering workflows but also open unprecedented avenues for scientific discovery in complex, nonlinear systems that were previously intractable with traditional computational methods. Furthermore, ML enables unprecedented advances in turbulence modeling, improving predictions within complex separated flow zones. This integration is reshaping fluid mechanics, offering pathways toward more reliable, efficient, and resilient engineering solutions necessary for addressing contemporary challenges. Full article

Accurate traffic flow prediction is pivotal for intelligent transportation systems; yet, existing spatial-temporal graph neural networks (STGNNs) struggle to jointly capture the long-term structural stability, short-term dynamics, and multi-scale temporal patterns of road networks. To address these shortcomings, we propose FISTGCN, a Frequency-Aware Interactive Spatial-Temporal Graph Convolutional Network. FISTGCN enriches raw traffic flow features with learnable spatial and temporal embeddings, thereby providing comprehensive spatial-temporal representations for subsequent modeling. Specifically, it utilizes an interactive dynamic graph convolutional block that generates a time-evolving fused adjacency matrix by combining adaptive and dynamic adjacency matrices. It then applies dual sparse graph convolutions with cross-scale interactions to capture multi-scale spatial dependencies. The gated spectral block projects the input features into the frequency domain and adaptively separates low- and high-frequency components using a learnable threshold. It then employs learnable filters to extract features from different frequency bands and adopts a gating mechanism to adaptively fuse low- and high-frequency information, thereby dynamically highlighting short-term fluctuations or long-term trends. Extensive experiments on four benchmark datasets demonstrate that FISTGCN delivers state-of-the-art predictive accuracy while maintaining competitive computational efficiency. Full article

The paper describes an installation and procedure for evaluating the velocity profile for the airflow produced by the fan of the cleaning unit of a New Holland wheat combine harvester. The velocity profile is based on measurements taken at 52 points spread over the entire surface of the top and bottom sieves, for different speeds of the fan, different positions of the wind boards and different opening positions of the sieves. The experimental data obtained were graphically represented using the Radial Basis Function (RBF) interpolation model and highlighted that the airflow generated by the fan at the upper screen level, in the longitudinal plane and, especially, in the transverse plane, is distributed unevenly, and depends on the fan rotor speed, the opening of the louvers of the two screens and the arrangement of the two deflectors. The correct adjustment of the cleaning unit and correct evaluation of the air velocity profile over the sieves result in the reduction in grain losses from the upper sieve due to grain flotation, reduction in the content of broken grains in the grain tank due to the reduction in the material flow from the tailing auger as well as reduction in the impurities content of the grain tank due to better separation of the material over the surface of the lower sieve. Full article

Reflection removal from a single image is an ill-posed problem due to the inherent ambiguity in separating transmission and reflection components from a single composite observation. In this paper, we address this challenge by introducing a reversible feature encoding strategy combined with a simplified dual-stream decoding structure. In particular, the reversible NAFNet encoder enables us to retain all feature information throughout the encoding process while avoiding memory overhead, an aspect that is crucial for separating overlapping structures. In place of complex gated mechanisms, the proposed dual-stream decoder leverages shared encoder features and skip connections, thus enabling implicit bidirectional information flow between transmission and reflection streams. Although our model adopts a lightweight structure and omits attention modules, it achieves competitive results on standard reflection removal benchmarks, indicating that efficient and interpretable designs can match or surpass more complex counterparts. Full article

Modern military aircraft integrate a large number of high-power-density electronic devices, which leads to a rapid increase in thermal load and poses significant challenges for heat dissipation. A promising thermal management approach is to intake ram air through a fuselage-mounted S-duct inlet and utilize it as a heat sink for the downstream heat exchanger. However, the S-duct’s geometry can induce significant flow separation and total pressure distortion, thereby limiting the mass flow rate. To address these challenges, this study investigates three flow-control strategies—vortex generators (VGs), Coanda injectors, and their combination—using high-fidelity three-dimensional numerical simulations validated against experimental data. The results indicate that VGs effectively suppress local separation and improve flow uniformity, although additional losses limit pressure recovery. The Coanda injector enhances boundary-layer momentum, substantially increasing mass flow throughput and pressure recovery. The combined VGs and Coanda injector approach achieves a lower distortion coefficient and provides a favorable balance between pressure recovery and flow uniformity. These findings demonstrate the potential of hybrid passive–active flow control in improving inlet aerodynamic quality and supporting integrated thermal management systems for future aircraft. Full article

In this study, a mathematical model was proposed for a continuous, multistage, industrial-scale alcoholic fermentation process, comprising four vats in series with volumes equal to 600 m³, with separation, acid treatment, and cell recycling from the fourth to the first vat. The system was operated daily under variable volumetric flow rates and substrate concentrations in the feed stream, i.e., F₀ = 93–127 m³/h and S₀ = 210–238 g/L. The mathematical model consisted of mass balance equations for cells, substrate, and product in the vats, the separator, and the acid treatment unit. An unsegregated and unstructured approach was used to describe the microbial population, with the kinetics of cell growth, substrate consumption, and product formation represented by equations generally adopted for alcoholic fermentation. The model parameters were estimated by nonlinear regression, providing typical values for alcoholic fermentation. Model predictions agreed well with both the experimental data used in the parameter estimation step and those used in the model validation step. Full article

The radius-to-width ratio has an obvious impact on the flow structure within curved channels, which most natural rivers possess, but there are currently few studies on the influence of the radius-to-width ratio of a tributary (R/B) on the hydrodynamic characteristics of a confluent channel. In order to contribute to this field of research, this study employed the RNG k-ε turbulence model, which has good applicability and accuracy for confluence, to investigate the effects of the R/B and flow ratios (q*) on the hydraulic characteristics of confluence. The results reveal that the numerical model can effectively simulate the velocity distribution in the confluence. The values of the key errors are all relatively small (e.g., the value of Mean RMSE is 0.05), and the flow patterns near the bed and water surfaces are different. The maximum velocity zone (MVZ) and the scale of the separation zone (SZ) increase as R/B increases; conversely, the MVZ and the scale of the SZ decrease as the q* increases. Upstream of the confluence, turbulent kinetic energy (TKE) increases and decreases as R/B and q* increase, respectively, while TKE downstream of the confluence hardly changes. Furthermore, the size of the SF decreases as R/B increases. The value of $\overline{S_w}$ peaks downstream of the confluence, increases with the increase in the R/B, and decreases with the increase in the q*. The results of this study will contribute to a better understanding of the hydrodynamic characteristics of confluence and provide valuable insights for the management and ecological restoration of confluent channels. Full article