Search Results (402)

Fiber-reinforced asphalt mixtures improve cracking resistance through fiber bridging, pull-out, and crack-path deflection, but their semi-circular bending (SCB) fracture energy is affected by coupled mixture, testing, and fiber-related variables. This study developed a source-aware and physically interpretable data-driven framework for predicting SCB fracture energy using a literature-derived database containing 261 valid sample-level records from nine source groups. The database was constructed through semantic extraction, unit normalization, rule-based checking, manual verification, and source identifier (SourceID) tracking. Optimum asphalt content, air voids, test temperature, loading rate, fiber dosage, fiber length, diameter, elastic modulus, and tensile strength were used as input variables. Under sample-wise testing, the selected model achieved a coefficient of determination (R²) of 0.89, a root mean square error (RMSE) of 0.0470 kJ/m², and a mean absolute error (MAE) of 0.0247 kJ/m² for the full dataset, while the fiber-containing subset achieved R² = 0.94, RMSE = 0.0194 kJ/m², and MAE = 0.0103 kJ/m². Source-aware validation showed higher prediction errors, indicating that cross-source generalization remains more challenging than internal sample-wise prediction. SHapley Additive exPlanations (SHAP) analysis identified temperature, fiber dosage, and fiber mechanical descriptors as dominant contributors, consistent with temperature-dependent viscoelasticity, fiber bridging, and pull-out mechanisms. The dosage–response analysis was restricted to the observed fiber-dosage range of 0–0.678%, providing a bounded screening tool rather than an extrapolative design equation. Full article

Direction-of-arrival (DOA) estimation in shallow-water underwater acoustics is challenged by coherent multipath and impulsive disturbances, which jointly cause covariance rank deficiency and outlier-driven subspace distortion. This paper proposes an embedded robust covariance-construction mechanism for coherent-plus-impulsive DOA estimation. The mechanism is implemented as mixture-correntropy-weighted simplified spatial smoothing (SS–MCC), in which snapshot reliability is enforced during subarray covariance accumulation rather than after decorrelation. A two-kernel residual-based weighting rule suppresses strongly contaminated snapshots while retaining moderately perturbed but informative snapshots. Under a controlled narrowband uniform linear array benchmark with fully coherent two-arrival multipath and Bernoulli–Gaussian impulsive noise, SS–MCC yields more stable DOA behavior than MUSIC, SS-MUSIC, and FLOM-MUSIC, especially in low-SNR, high-impulsiveness, and near-threshold regimes, although absolute strict recovery remains limited in the hardest cases. All-trial strict correct-two-peak statistics and ablation results show that the gain mainly comes from embedded covariance cleaning rather than post-processing or parameter tuning. A measured-noise-injected benchmark using NOAA–Navy SanctSound FK01 underwater recordings further confirms the same qualitative robustness trend under real noise waveforms, while remaining a semi-realistic noise-injection check rather than measured-array sea-trial validation. A simplified DOA- assisted MVDR benchmark indicates that improved covariance robustness can also support more favorable beamforming-oriented trends. The results provide controlled benchmark evidence that reliability-aware covariance construction can stabilize subspace extraction under joint coherent multipath and impulsive contamination; validation under wideband propagation, model mismatch, partial coherence, and measured array data remains future work. Full article

Ricin and abrin are highly lethal Type II ribosome-inactivating proteins. They depurinate the same site of the 28S rRNA to inhibit protein synthesis. Consequently, standard molecular-level activity assays used to detect the toxic activity of ricin or abrin do not distinguish between the two in mixed samples without prior physical separation or specially designed substrates. This study proposes a novel, cost-effective method to separately and simultaneously quantify the activities of ricin and abrin in mixtures by exploiting their distinct thermal stabilities. Thermal inactivation was used to demonstrate that heating samples at 80 °C for 5 min maximized the difference in their activities; while ricin retained most of its activity, abrin activity dropped to 20% after thermal treatment. This thermal treatment yielded 4 standard curves—ricin or abrin, thermally treated or not treated—in the 0.3 to 50 µg/mL range. By applying Cramer’s rule, the individual concentrations of active ricin and abrin in mixed samples were successfully calculated. However, this method should be used with a method detecting presence of ricin/abrin, to avoid unexpected reactivity due to contaminating RIPs. Full article

The free vibration of functionally graded (FG) beams under thermal environments is fundamental to understanding forced vibration, flutter, and thermal buckling in high-temperature structures. However, current research primarily focuses on theoretical modeling and numerical solutions, with limited mechanistic insights into temperature-dependent frequency variations and multi-factor effects. This study presents an analytical investigation coupled with experimental validation to characterize the vibration behavior of FG beams under thermal environments. First, governing equations for thermal vibration of FG beams are derived under uniform, linear, and nonlinear temperature fields based on the power-law assumption, the rule of mixtures, Timoshenko beam theory, and Hamilton’s principle. Subsequently, analytical expressions for natural frequencies and mode shapes are obtained using the state-space method. Then, experimental validation is performed to verify the model’s accuracy. Finally, the combined effects of temperature field, power-law index, slenderness ratio, and boundary conditions on the natural frequencies are systematically analyzed. Full article

Rhizosphere microbiome engineering is a promising approach that can enhance crop resilience and input use efficiency by redirecting plant–microbe–soil interactions toward predictable functions. Here, we review the mechanistic bases underlying rhizosphere assembly and stability, including root exudate-mediated selection, priority effects, keystone taxa, and metabolite-driven signaling, and connect these principles to proposed design rules for microbial inoculants. We present a generalizable Design–Build–Test–Learn (DBTL) framework for engineering synthetic microbial consortia, covering trait-to-module mapping (nutrient acquisition, phytohormone modulation, ACC deaminase activity, stress-protective metabolites, and biocontrol), compatibility screening, minimal yet robust community architectures, and iterative optimization driven by multi-omics and high-throughput phenotyping. Translation to field settings is framed as an engineering challenge defined by formulation and administration limitations, including carrier type, seed coating and encapsulation methods, shelf life, strain invasiveness, and permanence of colonization amid environmental diversity. We also summarize how integrative measurement pipelines (amplicon and shotgun sequencing, transcriptomics, metabolomics, and network or causal analyses) can advance microbiome studies from correlation to actionability. We describe how precision agriculture (sensors, remote sensing, and variable-rate inputs) and AI/ML (split-sample comparisons, transfer learning, and active learning) approaches can accelerate strain discovery, mixture optimization, and adaptive experimentation, driven by the need for stringent controls, metadata-rich reporting, and cross-site comparability. Use cases focus on stress conditions (drought, salinity, thermal extremes, and biotic stress) to demonstrate how microbial functions translate to agronomic outcomes and to highlight critical bottlenecks for reproducible, scalable microbiome products. Full article

Intralayer hybridisation provides a powerful strategy for tailoring the stiffness–strength–ductility balance of fibre-reinforced composites through architecture control. This study investigates the flexural behaviour of carbon/glass intralayer hybrid composites with varying carbon-to-glass (C:G) ratios and degrees of dispersion using a finite element modelling framework supported by experimental validation against published flexural test data. Four hybrid ratios (C:G = 2:1, 1:1, 1:2, and 1:4) and multiple dispersion levels were examined under three-point bending to quantify the effects of intralayer architecture on flexural strength, modulus, and strain to failure. The results show that carbon-rich hybrids retain high flexural stiffness and strength while achieving substantial improvements in failure strain and damage tolerance compared with pure carbon laminates. In these systems, flexural strength is strongly influenced by dispersion, with moderate-to-high dispersion improving strain compatibility, delaying tensile-side carbon fibre fracture, and enhancing strength. In contrast, glass-dominated hybrids exhibit flexural behaviour that is largely insensitive to dispersion, with strength and modulus following near rule-of-mixtures trends and failure governed by progressive glass fibre and matrix damage. Across all hybrid ratios, flexural modulus is controlled primarily by fibre volume fraction, whereas flexural strength and failure strain depend sensitively on intralayer architecture when carbon fibres remain the dominant load-bearing phase. These findings clarify the respective roles of hybrid ratio and dispersion in governing flexural performance and extend recent studies by demonstrating a systematic transition from dispersion-dominated to ratio-dominated behaviour as glass content increases. The results provide mechanistic insight and practical design guidance for optimising intralayer hybrid composites for lightweight, damage-tolerant structural applications. Full article

To address the problems of unreasonable task allocation and low target search efficiency in the collaborative search of multiple unmanned undersea vehicles (UUVs) in complex marine environments, this paper proposes a search-information-driven collaborative task planning method for multi-UUV systems, and constructs a systematic and integrated multi-UUV collaborative task planning framework. Considering the spatial characteristics of the complex underwater environment and sonar detection rules, an underwater task environment grid model and an active sonar instantaneous detection model are constructed as the environmental and detection foundation of the framework. Within the framework, the Gaussian Mixture Model (GMM) is adopted to realize dynamic division of task regions, and reasonable resource allocation among multiple UUVs is achieved by defining scientific area allocation indicators. A search information map consisting of target probability distribution and environmental uncertainty is established, and a receding horizon planning framework is introduced to balance short-term detection effectiveness and long-term search value. Furthermore, a motion-coded Grey Wolf Optimization (GWO) algorithm is proposed to generate continuous UUV paths, which avoids path discontinuity caused by discrete grids and ensures the convergence efficiency of the algorithm. Simulation results verify that compared with traditional methods, the proposed method improves the total probability benefit by 19.87% and the number of discovered targets by 18.29%, demonstrating better search performance and environmental adaptability. Full article

This study investigates the development of high-strength biofiber cement boards with enhanced thermal insulation properties by utilizing recycled biofibers derived from cement packaging bags, combined with a water-based adhesive to enhance the curing efficiency of Portland cement through a cementation–curing process. This approach reduces waste from cement packaging and other biofiber residues through recycling, thereby promoting environmental sustainability. Moreover, it does not require the use of additional chemicals for the disposal or treatment of fiber waste, nor does it require the incineration of biofiber waste. Recycled biofiber from cement bags, composed primarily of cellulose (60 wt%), lignin (15 wt%), and hemicellulose (10 wt%), serves as a reinforcing phase, while the cement and adhesive mixture functions as a strong binding matrix. The fabrication of composite materials using undamaged cement bag fibers preserves fiber integrity and enables a well-ordered one-dimensional (1D) fiber alignment, which promotes more effective reinforcement than two-dimensional (2D) or three-dimensional (3D) orientations, in accordance with the rule of mixtures. In addition, the incorporation of a water-based PVAc adhesive accelerates the curing rate of the cement phase, promoting the formation of a strong interconnected network structure, and facilitates a more complete curing process. The physical, mechanical, chemical, and thermal properties of the biofiber cement boards were evaluated in accordance with relevant industrial standards, including TISI 878:2023, BS 874, ASTM C1185, ASTM D570, ASTM C518, ISO 8301, and JIS A1412. The results indicate that an optimal cement mortar to water-based adhesive ratio of 1:2, combined with an increased number of biofiber sheet layers, significantly enhances material performance, particularly in Formulas (7)–(9). Among these, Formula (9) exhibits the lowest water absorption (0.0835 ± 0.0102%), the highest tensile strength (19.489 ± 0.670 MPa), the highest flexural strength (20.867 ± 2.505 MPa), the highest Young’s modulus (5735.068 ± 387.032 MPa), and low thermal conductivity (0.152 W/m.K). The resulting boards demonstrate strong bonding ability, enhanced resistance to fire, moisture, and weathering, and a longer service life compared to lower cement-to-adhesive ratios (1:1 and 1:0). These findings demonstrate the potential of recycled biofiber composites, combined with water-based adhesives, as sustainable alternative materials for thermal insulation and structural applications, including ceilings and walls in building construction. Full article

Asphalt pavements are essential to modern transport infrastructure but remain highly dependent on virgin aggregates and petroleum-based binders, resulting in high energy demand and significant greenhouse gas emissions. In response, research has advanced recycled-material solutions and low-temperature asphalt technologies. However, sustainability is still often inferred from isolated environmental indicators, without consistent consideration of mechanical durability or economic feasibility throughout the life cycle. This review provides an integrated synthesis of sustainable asphalt mixtures by jointly examining recycling strategies, temperature-reduction processes (warm-mix, half-warm-mix, and cold-mix asphalt technologies), and their combined applications through an integrated performance–cost–environment perspective. The literature reveals substantial methodological fragmentation, with limited harmonisation of functional units, system boundaries, and allocation rules, which constrains cross-study comparability. Evidence indicates that reclaimed asphalt, recycled concrete aggregates, and steel slag can maintain or improve rutting resistance, stiffness, and moisture durability while enabling material cost savings of approximately 5–68%. Temperature-reduction technologies further achieve significant energy and GHG reductions in the production phase (20–70%), with integrated recycling–temperature-reduction systems showing the most consistent combined benefits. Overall, this review demonstrates that asphalt sustainability cannot be established through single-dimensional assessments but requires harmonised life-cycle frameworks that explicitly link environmental gains to mechanical performance, durability, and economic viability. Full article

Docker systems are gaining widespread use due to their consistency, scalability, and ease of application portability, which addresses specific security challenges. Traditional monitoring and intrusion detection systems based on predefined rules often struggle with advanced attack patterns due to a lack of the capability to correlate incoming log messages. This paper proposes a correlation-aware log analysis approach based on a Mixture-of-Experts (MoE) large language models, enabling detection of malicious activity by analyzing both individual log entries and their contextual relationships within sequences of logs. The system processes each log in the context of 50 preceding messages, allowing identification of attack patterns that are not observable from isolated logs. To evaluate the approach, we generated a comprehensive dataset based on OWASP Top 10 attack scenarios, enriched with zero-day attacks such as Log4j and React2Shell, deployed in a distributed Docker Swarm environment. Multiple LLMs were evaluated under identical hardware conditions to ensure fair comparison. Experimental results demonstrate that while most models achieve comparable performance on single-log detection, significant differences emerge in contextual analysis. The proposed MoE-based approach demonstrates superior effectiveness, achieving an F1 score from 0.993 to 0.998 for contextual-log analysis. The contribution of this research is the novel use of MoE LLMs for log analysis, the distinct novel attack log dataset, and the unique framework based on offline technology that conserves hardware resources and data privacy. Full article

This study investigated mechanical properties of composite materials consisting of an isotactic polypropylene (iPP) matrix reinforced with whisker-like fillers: carbon nanofibers (CBNF) and wollastonite (WN). We strove to develop mechanical models specifically for predicting yield stress and fracture toughness. Experimentally obtained results validated findings obtained using the proposed models. Regarding the elastic modulus, data suggest that conventional rules of mixture, typically used for glass fiber-reinforced polymers, remain applicable, indicating that filler addition enhances stiffness in a predictable manner. However, yield stress and fracture toughness exhibited distinct behaviors. Results revealed that these properties are governed predominantly by shear yielding of the iPP matrix rather than reinforcement effect of the fillers. Despite the presence of whiskers, the overall yield and fracture mechanisms depend heavily on the matrix’s plastic deformation and energy dissipation. The constructed models consistently explain these findings, supporting quantitative evaluation of the matrix’s contribution. These results emphasize that developing high-performance iPP composites requires knowledge of the intrinsic ductile properties of the matrix alongside filler selection and dispersion. Full article

The Zeta-Minimizer Theorem establishes that the Riemann zeta function $\zeta \left(s\right)$ and the primes arise variationally as unique minimizers of a phase functional defined on a symmetric measure space $\left(X,\mu ,G\right)$ equipped with helical operators. Three fundamental axioms—strict concave entropy maximization (Axiom 1), spectral Gibbs minima with non-vanishing ground states (Axiom 2), and irreducible bounded oscillations with flux conservation (Axiom 3)—allow for the selection of the non-proper Archimedean conical helix as the sole topology satisfying all constraints. Primes emerge as indivisible minimal cycles in the associated representation graph $\Gamma$ (via Hilbert irreducibility and Maschke’s theorem), while the Euler product is recovered through the spectral Dirichlet mapping of the helical eigenvalues. The partial zeta product, $Z\left(s\right)=\prod _j{\displaystyle \frac{1}{1-p_j^{-s}}},s\in \mathbb{R}\left\{0\right\},$ constitutes the exact grand partition function of any finite subsystem. Numerical inversion of this product directly recovers the mixture frequency $s$ from any experimental compressibility factor $Z_{\mathrm{m}\mathrm{i}\mathrm{x}}$. Mole fractions $x_i\left(s\right)$, interaction parameters $\Delta \left(x_i\right)$, and the Lyapunov spectrum $\lambda \left(x_i\right)$ then follow deductively via the helical transfer matrix and the closed-form linear ODE for $\Delta$. Occupation numbers $N\left(x_i\right)$ attain sharp maxima precisely at Fibonacci ratios $F_r/F_{r+1}$, leading to the molecular prime-ID rule. For twelve representative purely binary (irreducible) systems spanning atomic noble gases, simple diatomics, polar molecules, and an aromatic ring, the residuals satisfy $|Z\left(s\right)-Z_{\mathrm{m}\mathrm{i}\mathrm{x}}|<1.5\times {10}^{-8}$. The resulting $\lambda \left(x_i\right)$ curves accurately reproduce critical points, liquid ranges, and thermodynamic anomalies with zero adjustable parameters. The Riemann Hypothesis follows rigorously as a theorem: the unique fixed point of the duality functor $s\mapsto 1-s$ that preserves the orthogonality condition $\sum {\mathrm{c}\mathrm{o}\mathrm{s}}^2{\theta }^k=1$ is $\mathrm{R}\mathrm{e}\left(s\right)=1/2$, enforced by Axiom 1 concavity and Axiom 3 irreducibility. The framework is fully deductive and parameter-free and extends naturally to arbitrary mixtures and multiplicities through the helical representation graph. It provides a variational unification of analytic number theory, spectral geometry, thermodynamic phase behavior, and the Riemann Hypothesis from first principles. Full article

To address the challenges of winter pavement icing and the disposal of organic waste, this study developed a sustained-release deicing filler utilizing biochar derived from spent coffee grounds (SCGs). The material was synthesized through high-temperature carbonization, followed by physical adsorption of chloride salts and surface hydrophobic modification to control release rates. The study made asphalt mixtures and replaced normal mineral filler with the SCG material by volume at ratios of 0%, 50%, 75%, and 100% to test road and deicing performance. Wheel-tracking tests showed that the additive improved high-temperature stability and dynamic stability went up by 27.04% at the 75% replacement level. Salt dissolving created voids and slightly lowered water stability at high dosages, but all performance numbers still met the current engineering rules. Rutting slab tests at −5 °C showed the 100% replacement mix cut snow coverage to 11.43% in 60 min and proved it works for deicing. Pull-out tests measure the bond strength between ice and pavement at −5 °C, −7 °C, and −9 °C. The SCG deicing material weakens ice sticking and the bond strength for the 100% group at −5 °C was 0.35 kN, which is about 57.8% lower than the control asphalt. The bond strength of the deicing mix at −9 °C was still lower than the normal mix at −5 °C. This big drop in stickiness means the pavement stops ice from packing hard and makes mechanical removal easier. This study shows that the prepared deicing materials exhibit excellent sustained-release performance and snow-melting efficiency while ensuring satisfactory road performance. SCG deicing materials can effectively reduce snow accumulation on road surfaces in winter, lower the difficulty of ice-layer removal, and realize the sustainable utilization of SCGs. Full article

This study presents a calibrated analytical micromechanical framework for predicting the linear elastic behavior of unidirectional glass fiber/epoxy and carbon fiber/epoxy composites over a wide range of fiber volume fractions. The approach combines the classical rule of mixtures for the longitudinal Young’s modulus with the semi empirical Halpin–Tsai equations to estimate the transverse Young’s modulus and the in-plane shear modulus. The framework is specifically formulated to support durability-oriented composite design through rapid and physically consistent estimation of elastic properties governing load transfer and stress distribution. Material parameters, including fiber and matrix Young’s moduli (Ef, Em), shear moduli (Gf, Gm), Poisson’s ratios (νf, νm), and fiber volume fraction (Vf up to 0.80), are taken from established material property databases and implemented within a literature-informed modeling scheme. To preserve physical realism at high fiber contents, a shear correction factor is introduced for Vf > 0.50 to account for microstructural interaction and fiber clustering effects. The predicted effective elastic constants (E₁, E₂, G₁₂, ν₁₂) exhibit consistent and physically meaningful trends across the full fiber volume fraction range. The model predictions were evaluated against trends widely reported in the composite micromechanics literature, and the results showed overall agreement in the nonlinear reduction in stiffness gains at elevated fiber volume fractions. Comparative results indicate that carbon fiber/epoxy composites achieve up to approximately 30% higher stiffness than glass fiber/epoxy systems at equivalent fiber contents, reflecting the influence of stiffness contrast on composite response. The analysis further indicates that stiffness saturation begins approximately in the Vf = 0.60–0.70 range, where the incremental gains in E2 and G12 become noticeably smaller for both composite systems. This behavior provides design-relevant guidance by showing that, beyond this range, further increases in fiber content may offer limited stiffness improvement relative to the associated manufacturing complexity. Overall, the calibrated Halpin–Tsai methodology offers a practical and computationally efficient tool for preliminary evaluation and design-stage optimization of the elastic performance of high-performance composite structures. Full article

Saxony was ruled by two cousins in 1544: John Frederick I (Elector of Saxony) and his cousin Maurice (Duke of Saxony). Both rulers’ names appear on each side of the quarter thalers produced in this year. They were enemies involved in religious wars, although they were both Protestants. Two types of quarter thalers from 1544 occur: a pierced random find from Transylvania (Romania) with four shields on the reverse, heavily worn, and another one with three shields on the obverse side, found in the Głogów Hoard (Poland), which is well preserved. Why did they issue two types in the same year? Was it a matter of silver title or other historical factors? Nondestructive investigation methods were used: XRD revealed the phases within the alloy and patina layer; SEM-EDS revealed the morphological aspects and their elemental compositions, which were correlated with XRF results. The results show that both coins have closer silver amounts, from 91 to 96 wt.%. The EDS results were in good agreement with the XRF results. Lead traces indicated a difference between them: the four-shielded coin is lead-free, while the three-shielded coin has a moderate amount of lead, about 0.5 wt.%. The archeological data evidence that the four-shielded coin issued in 1544 is rarer than the three-shielded one because it was issued during specific historical conditions. Black patina is formed by a mixture rich in copper oxides mixed with silver oxides and Ag₂S. The presence of silver sulfide in the patina layer confirms that the pierced coin was in prolonged contact with the skin surface. Also, the finest traces of minerals embedded in the patina layer (e.g., quartz, kaolinite, and calcite) suggest that they were embedded in the patina via prolonged exposure to particulate matter. The mineral inclusions in the patina would have been more numerous if they were formed underground. Thus, the pierced four-shielded coin was probably worn as jewelry by nomads, while the three-shielded coin was most likely treasured in a well-preserved hoard. Full article