Search Results (254)

The primary objective of this study is to bridge the gap between descriptive geometry and mechanistic design by establishing a dual-domain fractal framework to analyze the internal architecture of asphalt mixtures. This research quantitatively assesses the sensitivity of volumetric indicators—namely air voids (VV), voids in mineral aggregate (VMA), and voids filled with asphalt (VFA)—by employing the coarse aggregate fractal dimension (D_c), the fine aggregate fractal dimension (D_f), and the coarse-to-fine ratio (k) through Grey Relational Analysis (GRA). The findings demonstrate that whereas D_f and k substantially influence macro-volumetric parameters, the mesoscopic void fractal dimension (D_V) remains structurally unchanged, indicating that gradation predominantly dictates void volume rather than geometric intricacy. Sensitivity rankings create a prevailing hierarchy: Process Control (Compaction) > Skeleton Regulation (D_c) > Phase Filling (Pb) > Gradation Adjustment (k, D_f). D_c is recognized as the principal regulator of VMA, while binder content (Pb) governs VFA. A “Robust Design” methodology is suggested, emphasizing D_c to stabilize the mineral framework and reduce sensitivity to construction variations. A comparative investigation reveals that the optimized gradation (OG) achieves a more stable volumetric condition and enhanced mechanical performance relative to conventional empirical gradations. Specifically, the OG group demonstrated a substantial 112% enhancement in dynamic stability (2617 times/mm compared to 1230 times/mm) and a 75% increase in average film thickness (AFT), while ensuring consistent moisture and low-temperature resistance. In conclusion, this study transforms asphalt mixture design from empirical trial-and-error to a precision-engineered methodology, providing a robust instrument for optimizing the long-term durability of pavements in extreme cold and arid environments. Full article

Targeted radionuclide therapy (TRT) is an innovative and flexible approach for treating various forms of cancer, enabling selective delivery of cytotoxic radiation to cancerous cells while minimizing damage to healthy tissue. Although TRT has proven to be highly promising for treating even advanced-stage cancers, ensuring a stable supply of the radionuclides essential for its use remains a significant challenge today. This is also true for radionuclides utilized in nuclear imaging procedures, such as Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT). Liquid-fueled molten salt reactors (MSRs) are promising for producing large quantities of highly desirable radionuclides for imaging and therapy, offering the ability to recover these radionuclides online without the need for interruptions to power production. In this study, the production of numerous beta- and alpha-emitting radionuclides for use in TRT and diagnostic procedures was studied in two small, geometrically identical, thermal spectrum MSR models—one operating with LEU fuel, and the other with a mixture of HALEU and thorium—using a novel MSR refueling and waste management concept. For therapeutic alpha emitters such as ²²⁵Ac and ²¹³Bi, the impact of thorium utilization on production yields was significant, facilitating greatly increased production. Full article

Wastewater treatment facilities of a diameter of approximately 15 m or more provide the opportunity to process large volumes of stormwater. The current report investigates the operation of a stormwater radial precipitator, without an impeller, working with particles of various sizes. A distinguishing feature is that the two-phase flow is solely gravity-driven, which leads to reduced energy requirements. This entails the necessity of a facility in which the linear and the local losses are minimized as much as possible. Linear losses can be reduced by decreasing the precipitator’s size. The initially proposed 15 m diameter proved to be ineffective since the sand only reached a certain zone and could not flow further to the outlet due to the insufficient energy. Therefore, it was necessary to reduce the size of the radial precipitator, which resulted in a shorter path for the sand particles and the water, which, in turn, reduced the linear resistance. As for the local losses, it turned out that many areas of the precipitator construction could be geometrically modified to significantly reduce the energy loss of the sand–water mixture. The boundary layer cannot be removed. However, it is possible the size and the number of vortex structures inside the settler to be reduced in order to create an optimal working environment. Full article

A novel unsymmetrical azine, 6-((2-oxoindolin-3-ylidene)hydrazineylidene)indolo[2,1-b]quinazolin-12(6H)-one, was synthesized through a condensation reaction between tryptanthrin-6-hydrazone and isatin in chloroform under reflux conditions. Structural characterization revealed the compound exists as a mixture of geometric isomers with one predominant form. Density functional theory (DFT) calculations identified the E,E configuration as the most stable isomer. The isomerization barriers for both C=N bonds were calculated at approximately 18.5 kcal/mol via nitrogen inversion. Given the established biological activities of tryptanthrin and isatin derivatives, this hybrid azine represents a promising lead compound for developing bifunctional drug candidates. Full article

3D concrete printing (3DCP) is an emerging intelligent construction technology that enables the direct transformation of digital models into physical components, thereby facilitating the precise fabrication of complex geometries. This study investigates the anisotropic mechanical properties and construction applicability of low-carbon 3D printed concrete for reusable formwork systems. Axial compression, flexural, and splitting tensile tests were conducted to examine mechanical anisotropy, and the effects of steel slag and iron tailings replacement levels on mechanical performance were evaluated. Carbon emission analysis was also performed. Using the coefficient-of-variation TOPSIS method, an optimal printable low-carbon mixture was identified, comprising 30% steel slag, 40% iron tailings sand, and 0.3% fibre content, balancing both mechanical performance and environmental benefits. To address the challenges associated with printing large monolithic formwork units, such as excessive weight and demoulding difficulties, three connection strategies for curved wall modular reusable formwork were designed. Finite element analyses were conducted to assess the strength and stiffness of each strategy, and an optimized connection configuration was proposed. The findings demonstrate the feasibility of accurately fabricating complex architectural components using low-carbon 3D printed concrete, providing theoretical and practical support for the industrialized production of large-scale, geometrically complex structures. Full article

Transformers for time series forecasting rely on positional encoding to inject temporal order into the permutation-invariant self-attention mechanism. Classical sinusoidal absolute encodings are fixed and purely geometric; learnable absolute encodings often overfit and fail to extrapolate, while relative or advanced schemes can impose substantial computational overhead without being sufficiently tailored to temporal data. This work introduces a family of window-statistics positional encodings that explicitly incorporate local temporal semantics into the representation of each timestamp. The base variant (WinStat) augments inputs with statistics computed over a sliding window; WinStatLag adds explicit lag-difference features; and hybrid variants (WinStatFlex, WinStatTPE, WinStatSPE) learn soft mixtures of window statistics with absolute, learnable, and semantic positional signals, preserving the simplicity of additive encodings while adapting to local structure and informative lags. We evaluate proposed encodings on four heterogeneous benchmarks against state-of-the-art proposals: Electricity Transformer Temperature (hourly variants), Individual Household Electric Power Consumption, New York City Yellow Taxi Trip Records, and a large-scale industrial time series from heavy machinery. All experiments use a controlled Transformer backbone with full self-attention to isolate the effect of positional information. Across datasets, the proposed methods consistently reduce mean squared error and mean absolute error relative to a strong Transformer baseline with sinusoidal positional encoding and state-of-the-art encodings for time series, with WinStatFlex and WinStatTPE emerging as the most effective variants. Ablation studies that randomly shuffle decoder inputs markedly degrade the proposed methods, supporting the conclusion that their gains arise from learned order-aware locality and semantic structure rather than incidental artifacts. A simple and reproducible heuristic for setting the sliding-window length—roughly one quarter to one third of the input sequence length—provides robust performance without the need for exhaustive tuning. Full article

In this study, one of the main problems related to the development of new foods and the improvement of existing staple foods is examined. The effect of stalk pigweed flour in relation to the main raw material, wheat flour, at levels of 0%, 5%, 10%, and 15% was evaluated with respect to key characteristics of flour mixtures, dough, and biscuits with this additive. A selection of informative features was made, revealing that out of the 39 studied parameters, covering sensory, physicochemical, geometric, colorimetric, and spectral characteristics, only 19 proved to be informative. Principal component analysis showed that the relationship between amaranth green powder (AGP) concentration and the first two principal components explained up to 99% of the variance. The optimal addition level of 7.17% AGP was identified based on the convergence of biscuit characteristics. pH decreased from 6.55 to 6.28, electrical conductivity increased from 1075 to 3759 µS/cm, and sensory scores for aroma and taste peaked near 7% before declining at higher concentrations. It was demonstrated that the relationship between the amount of amaranth in biscuits and the first two principal components can be described with up to 99% accuracy. It was determined that the optimal amount of amaranth flour in biscuits is +7.17%. The results obtained provide a basis for further research into the rapid automated analysis of biscuits with added pigweed flour, which will contribute to the development of new foods with improved characteristics. It is suggested to carry out more research to study the effect of flours from other amaranth types, enhancing different varieties and cultivated in diverse ecological regions. This work also explores the viability of pigweed as a nutritious and sustainable flour alternative while providing a multivariate approach in view of newly developed bakery formulations. Full article

Electrified roads with embedded wireless power transfer (WPT) systems provide a promising strategy for dynamic charging of electric vehicles, but pavement materials strongly influence transmission efficiency. This study examines the effect of replacing conventional filler with magnetite powder in AC-16 asphalt mixtures. Specimens were prepared with five magnetite substitution levels (0–100%) and three bitumen contents (4.1%, 4.6%, and 5.1%) and were tested under different temperatures (10, 20, and 40 °C), moisture conditions (dry and saturated), and specimen thicknesses. Power transmission was measured with a resonant inductive system at 85 kHz, and both received power variation (RPV) and relative efficiency (RE) were computed. Results showed that magnetite systematically improved electromagnetic performance: RPV increased by up to 13% under dry conditions at 20 °C with 100% magnetite, while RE exhibited smaller variations (−1% to +2%). Moisture reduced RPV, and high temperature (40 °C) caused additional losses, whereas RE remained largely stable. Bitumen contributed indirectly, adding modest RPV gains. Thickness was the dominant geometric factor, with magnetite content particularly effective in mitigating losses at greater depths. Random forest analysis confirmed thickness and magnetite as the most influential variables. These findings demonstrate the potential of magnetite-modified asphalt to enhance the design of WPT-enabled pavements, providing a robust experimental basis for future full-scale applications. Full article

Variability in reclaimed asphalt pavement (RAP) properties, such as aggregate gradation, asphalt content, and moisture content, poses a significant challenge to producing consistent and reliable recycled asphalt mixtures. This study systematically evaluated processing techniques for mitigating variability through a comparative analysis of four fractionation strategies, i.e., unfractionated, two-fraction, four-fraction, and six-fraction processing. Corresponding to the four approaches, four distinct reference RAP mixtures were fabricated by proportionally recombining the obtained RAP fractions towards a target gradation. The gray relational analysis (GRA) was employed to quantify geometric similarity between the gradation curve of reclaimed aggregates from each fraction and the target gradation curve, thereby facilitating efficient determination of blending proportions without resorting to complex optimization algorithms. Statistical variability indicators, including range, standard deviation, and coefficient of variation (COV), were used to assess the effectiveness of each fractionation and recombining method. The results demonstrated that refined fractionation processing significantly reduced variability, particularly in gradation properties. Compared with the COV values from the commonly used two-fraction processing, those from the refined four-fraction and six-fraction processing methods decreased by up to 51.5% and 73.5%, respectively. While increasing the number of fractions generally enhanced homogeneity, the four-fraction approach emerged as the most technically reliable and economically viable strategy, achieving a desirable balance between processing effort and variability control. Furthermore, the GRA proved to be a practical and efficient tool for blend proportioning, reducing reliance on complex numerical methods. These findings reveal the importance of refined fractionated RAP processing in enabling the production of high-RAP recycled mixtures with improved uniformity and performance. Full article

The Free Water Knock Out (FWKO) vessel is a critical device in the oil sands treatment process, responsible for separating water, oil, and gas. This study investigates the gas–oil interface within the FWKO and analyzes the flow characteristics of the unresolved mixture near the interface. To enhance the separation efficiency by increasing the residence time of the mixture, a concave-shaped weir was introduced. Numerical simulations were conducted using ANSYS Fluent 2023 R1, applying the Volume of Fluid (VOF) model to capture the multiphase flow behavior. Optimization was performed using a genetic algorithm, and the optimal weir curvature with a minor radius of 0.017333 m and a major radius of 0.19032 m yielded the highest separation efficiency. The model incorporating the optimized weir demonstrated a 1.26% improvement in separation efficiency compared to the reference model, and a 2.13% improvement over the baseline model without curvature. These findings confirm that applying curvature to the traditionally flat weir can achieve higher separation efficiency. Moreover, improving separation efficiency through such a simple geometric modification demonstrates significant economic effectiveness. Full article

The compressive, tensile, and shear strength properties of two cement-stabilized soils (CSS) treated with 2% to 4% of cement are investigated for several different curing times at several densities. The measured Mohr–Coulomb (MC) shear strength features, cohesion (c), and friction angle (φ) are compared with values reported in the literature for similar materials and are subject to debate depending on the estimation methods used. In addition, an alternative geometric criterion based on indirect tensile strength (ITS) and unconfined compressive strength (UCS) is evaluated. The results show that the value of c determined using the alternative criterion is slightly higher than the value of c measured using the direct shear (DS) test. A relationship between mixture variables and c is established and validated by combining numerical and experimental approaches. The friction angle appears to be constant, independent of mixture parameters. This parameter is underestimated using the geometric approach. Full article

Facial beauty prediction (FBP) is a cutting-edge task in deep learning that aims to equip machines with the ability to assess facial attractiveness in a human-like manner. In human perception, facial beauty is strongly associated with facial symmetry, where balanced structures often reflect aesthetic appeal. Leveraging symmetry provides an interpretable prior for FBP and offers geometric constraints that enhance feature learning. However, existing multi-task FBP models still face challenges such as limited annotated data, insufficient frequency–temporal modeling, and feature conflicts from task heterogeneity. The Mamba model excels in feature extraction and long-range dependency modeling but encounters difficulties in parameter sharing and computational efficiency in multi-task settings. In contrast, mixture-of-experts (MoE) enables adaptive expert selection, reducing redundancy while enhancing task specialization. This paper proposes MoMamba, a multi-task decoder combining Mamba’s state-space modeling with MoE’s dynamic routing to improve multi-scale feature fusion and adaptability. A detail enhancement module fuses high- and low-frequency components from discrete cosine transform with temporal features from Mamba, and a state-aware MoE module incorporates low-rank expert modeling and task-specific decoding. Experiments on SCUT-FBP and SCUT-FBP5500 demonstrate superior performance in both classification and regression, particularly in symmetry-related perception modeling. Full article

Unmanned aerial vehicle (UAV)-based light detection and ranging (LiDAR) technology enables the acquisition of high-precision three-dimensional point clouds of the Earth’s surface. These data serve as a fundamental input for applications such as digital terrain model (DTM) construction and terrain analysis. Nevertheless, accurately extracting ground points in densely vegetated areas remains challenging. This study proposes a point cloud filtering method for the separation of ground points by integrating elevation frequency histograms and a multi-feature Gaussian mixture model (GMM). Firstly, local elevation frequency histograms are employed to estimate the elevation range for the coarse identification of ground points. Then, GMM is applied to refine the ground segmentation by integrating geometric features, intensity, and spectral information represented by the green leaf index (GLI). Finally, Mahalanobis distance is introduced to optimize the segmentation result, thereby improving the overall stability and robustness of the method in complex terrain and vegetated environments. The proposed method was validated on three study areas with different vegetation cover and terrain conditions, achieving an average $OA$ of 94.14%, $IoUg$ of 88.45%, $IoUng$ of 88.35%, and F1-score of 93.85%. Compared to existing ground filtering algorithms (e.g., CSF, SBF, and PMF), the proposed method performs well in all study areas, highlighting its robustness and effectiveness in complex environments, especially in areas densely covered by low vegetation. Full article

This review paper deals with Triply Periodic Minimal Surfaces (TPMS) and lattice structures as a new generation of heat exchangers. Especially, their manufacturing is becoming feasible with technological progress. While some intricate structures are fabricated, challenges persist concerning manufacturing limitations, cost-effectiveness, and performance under transient operating conditions. Studies reported that these complex geometries, such as diamond, gyroid, and hexagonal lattices, outperform traditional finned and porous materials in thermal management, particularly under forced and turbulent convection regimes. However, TPMS necessitates the optimization of geometric parameters such as cell size, porosity, and topology stretching. The complex geometries enhance uniform heat exchange and reduce thermal boundary layers. Moreover, the integration of high thermal conductivity materials (e.g., aluminum and silver) and advanced coolants (including nanofluids and ethylene glycol mixtures) further improves performance. However, the drawback of complex geometries, confirmed by both numerical and experimental investigations, is the critical trade-off between heat transfer performance and pressure drop. The potential of TPMS-based heatsinks transpires as a trend for next-generation thermal management systems, besides identifying key directions for future research, including design optimization, Multiphysics modeling, and practical implementation. Full article

Compact nuclear reactor systems usually use helium–xenon (He-Xe) mixtures as coolants. Tight-lattice rod-bundled channels, serving as primary core configurations in compact nuclear reactor designs, exhibit quasi-triangular cross-sections where fluid dynamics substantially deviate from circular tube behavior. This study evaluates the applicability of turbulence models and turbulent Prandtl number (Pr_t) models in quasi-triangular channels through systematic numerical simulations. The results demonstrate that the Transition SST model accurately resolves flow dynamics and turbulence development in helium–xenon mixtures, while implementing Pr_t models significantly enhances temperature prediction accuracy. Among the evaluated models, the Weigand model achieves optimal performance by dynamically adapting Pr_t values across flow regimes. Further refinements targeting parameters governing near-wall Pr_t distribution are identified as critical pathways for improving numerical simulation precision of low-Prandtl-number fluids in geometrically complex nuclear systems. Full article