Search Results (655)

In order to maximize passenger travel satisfaction and enhance the sustainability of the intercity multimodal transportation system, this paper proposes a two-stage model for intercity multimodal timetable coordination optimization under uncertainty. In the first stage, a robust spatio-temporal graph is built to allocate intermodal passenger flows in order to determine passengers’ route selection results to minimize the total travel cost. At the same time, explicit capacity constraints and transfer behaviors are considered in order to be more realistic. In addition, passengers can take multiple transportation modes (High-speed Rail, Ordinary Rail, EMU, and Coach) in a single trip. The outputs of the first stage are subsequently integrated into the second-stage interval multi-objective timetable optimization model to determine departure times and stopping patterns under uncertain dwell and travel times. It is able to achieve the maximum reduction of passenger travelling time and waiting time within the minimum timetable adjustment, which further improves the integration level of transportation services. To ensure the diversity and convergence of model solving on the basis of retaining uncertain information, we propose an integrated algorithm PSO-IMOEA-MC involving Particle Swarm Optimization algorithm (PSO) and Interval Many-objective Evolutionary Algorithm combined with Monte Carlo (IMOEA-MC). Finally, the effectiveness of the proposed two-stage model and algorithm is validated using three intercity networks: Beijing–Zhangjiakou, Chengdu–Chongqing, and Guangzhou–Qingyuan. The results demonstrate the performance of the method in finding high-level solutions that retain more uncertainty. The findings of this study provide technical support for timetable adjustments under diverse operational scenarios. Full article

Key parameters were estimated separately for the European eel, Anguilla anguilla (Linnaeus, 1758) subpopulations across freshwater and brackish environments within the Eastern Adriatic Eel Management Unit (EMU: EA). Between 2023 and 2024, European eel sampling was carried out at 23 locations along the Croatian coast (N = 678). Ages ranged from 1 to 13 years in freshwater and 1 to 8 years in brackish waters. The population structure was dominated by undifferentiated (42.8%) in freshwater and females (46.3%) in brackish habitats. Eels in freshwater exhibited a significantly higher b-coefficient in their length–weight relationship and better condition. Based on the otolith annuli patterns, age classes 3 to 5 predominated in both groups. A slightly longer asymptotic length and lower growth rate were found for the freshwater group compared to a shorter length and higher growth rate in the brackish habitat. Natural mortality was estimated at 0.174 ± 0.09 year⁻¹ and 0.191 ± 0.133 year⁻¹ for brackish and freshwater habitats, respectively. Total mortality was higher in freshwater (0.86 year⁻¹) in comparison with the brackish (0.83 year⁻¹) habitat. According to obtained results, more than 50% of eels aged three years are under exploitation. The maximum Yield per Recruit (Y/R) was 0.082 g/recruit in brackish at L_c = 44.88 cm, and a current L_c is 19.4 cm in the samples. In freshwater, Y/R peaked at 0.042 g/recruit at L_c = 55.49 and a current L_c 11.1 cm. It is recommended, following a precautionary approach to management, that the current fishing practices change in order to increase the minimum landing size (MLS), at least to 45 cm (above the current official MLS of 35 cm), to increase the fishing yield, and directly enhance population resilience. Findings emphasise the need for sustainable eel management policies considering different subpopulation parameters along the freshwater/brackish gradient at a small spatial scale when proposing and implementing stock management measures. Full article

Interfacial coupling between CoFe₂O₄ (CFO) nanoparticles and oxidatively functionalized multi-walled carbon nanotubes (MWCNTs) enables controlled modulation of structural, optical, and spin dynamic properties in CFO–MWCNT nanocomposites. The solvothermal synthesis promotes nucleation of CFO on –COOH/–OH functional groups, ensuring uniform anchoring along the nanotube surface. X-ray diffraction confirms a cubic spinel phase with lattice expansion from 8.385 Å to 8.410 Å and crystallite growth from 18 nm to 25 nm, reflecting strain transfer and partial nanoparticle coalescence at the carbon interface. The observed bandgap narrowing from 2.72 eV to 2.50 eV, confirmed via Tauc plot analysis, is attributed to localized defect states induced by charge delocalization and orbital hybridization at the interface of the CFO–MWCNT boundary. DC magnetometry reveals a reduction in saturation magnetization from 46 emu/g to 35 emu/g due to diamagnetic dilution and interfacial spin canting, while coercivity decreases from 852 Oe to 841 Oe, indicating modified pinning and domain-wall dynamics associated with exchange-coupled interfaces. Ferromagnetic resonance measurements show a resonance field shift from 3495 G to 3500 G and an increase in the Landé g-factor from 1.97 to 2.00, signifying altered spin–orbit coupling and enhanced local magnetic perturbations. The spin–lattice relaxation time increases from 1.41 ns to 1.59 ns, demonstrating suppressed phonon-mediated relaxation and improved spin coherence across the hybrid network. Spin density rises from 3.72 × 10²² to 4.58 × 10²² spins/g, confirming an increase in unpaired electrons generated by orbital asymmetry at the interface. The anisotropy field and effective magnetocrystalline anisotropy constant exhibit pronounced modulation, evidencing strengthened exchange stiffness and altered Co²⁺/Fe³⁺ superexchange pathways. These results establish CFO-MWCNT nanocomposites as tuneable platforms for spintronic logic elements, high-frequency microwave attenuation, and magneto-optical device architectures. Full article

Background: Manual review of EEG recordings in clinical settings is inherently time-consuming and labor-intensive. These challenges highlight a pressing need for automated EEG analysis tools capable of supporting clinicians by improving efficiency and diagnostic accuracy. Objectives: This study aims to develop and validate an AI-based model for the automated interpretation of adult EEG recordings. Unlike previous approaches that emphasize seizure detection during ictal states, our model targets the early prediction of seizure risk through systematic annotation and recognition of interictal patterns. Methods: The model is designed to accurately distinguish between normal and abnormal EEGs, encompassing both interictal and ictal activity. Abnormal EEGs will be further classified into three clinically relevant categories: (1) non-epileptiform abnormalities such as focal or diffuse slowing, (2) epileptiform discharges, and (3) electrographic seizures. Three AI-based classification algorithms were implemented: Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN). Results: RF demonstrated optimal performance across most tasks, achieving 96.50% accuracy for normal activity identification. This AI-driven system enhances the efficiency, consistency, and accessibility of EEG interpretation. It is particularly valuable in settings with limited access to neurophysiologists and offers an innovative approach to improving diagnostic timelines and clinical decision-making. Conclusions: Ultimately, this tool will support physicians in diagnosing neurological conditions and monitoring patient progress over time. Full article

In this work, four different magnetic Fe₃O₄ nanoparticles are prepared via solvothermal method. According to the morphology, the products can be divided into flower-like Fe₃O₄ (F-Fe₃O₄), solid spherical Fe₃O₄ (S-Fe₃O₄), hollow spherical Fe₃O₄ (HO-Fe₃O₄), and hexahedral Fe₃O₄ (HE-Fe₃O₄). A set of measurements is performed to confirm the structure, composition, and pore properties of the obtained materials. The catalytic activities of the prepared materials are examined and compared. The results prove that the four materials have an intrinsic catalytic property. HO-Fe₃O₄ ranks first in the catalytic activity mainly due to its large surface area and reasonable element composition. The maximum specific saturation magnetization and specific surface area of HO-Fe₃O₄ are 72.94 emu/g and 42.60 m²/g. Fe²⁺/Fe³⁺ in HO-Fe₃O₄ is 51.5%. It is found that HO-Fe₃O₄ possesses fantastic stability and perfect reproducibility as it is used as a catalyst several times without significant loss in its activity. Full article

Accurate reconstruction of train collision accidents is essential for understanding impact conditions, assessing crashworthiness, and supporting safety improvements. This study proposes a surrogate-based optimization framework for reconstructing structural damage in train collisions from post-accident observations. The pre-impact kinematic state, expressed by a six-dimensional vector of relative offsets, rotations, and impact velocity, is formulated as an inverse problem in which a Sum of Squared Relative Deviations (SSRD) between measured and simulated residual deformations serves as the objective function. A reduced two-vehicle finite element (FE) model is developed to capture the dominant impact dynamics, an Optimal Latin Hypercube Design is used to sample the parameter space, and a Kriging surrogate model is constructed to approximate the response. A simulated annealing algorithm is applied to search for the global minimum. The framework is demonstrated on a real high-speed rear-end collision of electric multiple units. The Kriging model achieves a coefficient of determination of about 0.85, and the optimized kinematic state yields FE-predicted residual deformations that agree with field measurements at key locations to within about 5%. The results show that the method can efficiently reconstruct physically plausible collision scenarios and provide insight into parameter sensitivity and identifiability for railway safety analysis. Full article

The accumulation of heavy metals in fish tissues is widely recognized as an indicator of aquatic environmental pollution, and the analysis of their content provides a basis for assessing ecological risk and the safety of aquatic food. The European eel (Anguilla anguilla) is a species frequently used as a bioindicator in environmental studies due to its wide geographic distribution, long life cycle, and high capacity for bioaccumulation of heavy metals in various tissues. The aim of this study was to assess the variation in the accumulation of heavy metals, i.e., mercury (Hg), lead (Pb), arsenic (As), and cadmium (Cd), in the tissues (muscle, liver, gonads, and gills) of European eels caught in two locations in Polish inland waters. The obtained results showed significant differences both in the concentration levels of individual elements and in their co-occurrence in the examined tissues. The statistical methods used, including correlation analysis, heat maps, and principal component analysis (PCA), allowed for a comprehensive assessment of the relationships between metals and the identification of factors differentiating the studied populations. The obtained results clearly indicate that fish residing in similar environments for long periods exhibit significant differences in heavy metal content in various fish tissues. Fish obtained from environments with potentially higher levels of heavy metal inputs, such as the Oder River EMU compared with the Vistula River EMU, showed higher levels of heavy metal accumulation in tissues. This study also found that the concentration of heavy metals tested did not exceed the safe standards for human fish consumption. Full article

The increasing discharge of recalcitrant organic dyes from the textile industry necessitates the development of efficient and sustainable wastewater treatment technologies. This study reports the successful eco-friendly fabrication of magnetically separable cerium–manganese ferrite (Ce-MnFe₂O₄) nanocatalysts via a one-pot green synthesis route, utilizing an aqueous extract of Brachychiton populneus leaves. The structural, morphological, magnetic, and optical properties of the synthesized nanocatalysts were systematically investigated. X-ray diffraction (XRD) analysis confirmed the formation of a phase-pure cubic spinel structure, with evidence of Ce³⁺ ion incorporation leading to lattice expansion and the formation of beneficial oxygen vacancies. The composite material exhibited superparamagnetic behavior with a high saturation magnetization of 38.7 emu/g, which facilitates efficient magnetic separation and recovery. Optical studies revealed a direct bandgap of 2.33 eV, enabling significant photocatalytic activity under visible light irradiation. The Ce-MnFe₂O₄ nanocatalyst demonstrated superior performance, achieving degradation efficiencies of 96% for methylene blue and 98% for Congo Red within 90 min. Furthermore, the catalyst demonstrated good operational stability, maintaining 62% of its initial degradation efficiency for CR and 51% for MB after five consecutive reuse cycles. These results underscore the potential of this green-synthesized, magnetically recoverable nanocatalyst as a highly effective and sustainable solution for the remediation of dye-contaminated industrial effluents. Full article

Soft magnetic materials are critical for efficient electromagnetic energy conversion, with their development evolving from traditional alloys like ferrites to amorphous/nanocrystalline materials and advanced multi-component alloys. While multi-component alloys address key limitations of prior materials (e.g., low resistivity, poor thermal stability), gaps remain in understanding how preparation parameters regulate the microstructure and properties. This study systematically investigates the effects of sputtering power and substrate temperature on the microstructural evolution and soft magnetic properties of an FeGaYCo film. First, the sputtering power increases from 70 W to 160 W. This adjustment refines grains, promotes crystallization, and drives coercivity (H_C) and saturation magnetization (M_S) to first decrease then increase —with optimal soft magnetic properties (H_C = 5.7 Oe, M_S = 1164.3 emu/cm³) being achieved at 100 W. For substrate temperature, increasing the temperature from 25 °C to 100 °C enhances atomic migration (leading to larger grains) but exerts limited influence on the overall number of grains per unit volume; the lowest H_C (3.8 Oe) and highest M_S (1321.2 emu/cm³) occur at 75 °C. These findings provide theoretical and experimental support for developing a high-performance next-generation soft magnetic film. Full article

The Temane gas field, the first producing natural gas field in Mozambique, remains a key supplier to southern Mozambique and the South African market. In recent years, however, the field has experienced an accelerated production decline, raising concerns regarding its long-term supply sustainability. Between 2020 and 2024, gas production decreased by approximately 25%, motivating a comprehensive reserve assessment to quantify the remaining potential and support informed reservoir management. This study applied three modern rate transient analysis (RTA) methods (Blasingame, normalized rate–cumulative, and flowing material balance) to twenty years of daily production data from thirteen producing wells across three reservoirs (G-9A, G-9B, and TEast) on a per-well basis. The RTA methods yielded consistent estimates, indicating an original gas-in-place value of 1576.38 Bscf, a remaining gas-in-place value of 503.37 Bscf, an estimated ultimate recovery of 1405.25 Bscf, and a field-average recovery factor of 76.35%. Reservoir-level recovery factors are estimated at 79% for G-9A, 74.92% for G-9B, and 58.01% for TEast. Despite the high depletion level, the magnitude of the observed production decline is not fully explained by reservoir exhaustion alone, suggesting that the field retains significant remaining recovery potential. Full article

In this paper, we take the longitudinal two-stage and two-yard EMU (Electric Multiple Unit) depot as an example and discusses the optimization challenges of the first-level maintenance shunting operation plan under the background of limited maintenance capacity. A multi-objective programming is constructed, which adopts the lexicographic ordering method and aims to minimize the occupancy time of key line areas and the number of train storage times. In order to enhance the flexibility and solution efficiency of the shunting operation plan, we design an efficient three-stage strategy algorithm. Specifically, in the first stage, the genetic and mutation rules are integrated, and the fast iterative advantage of the genetic algorithm is utilized to solve the time decision variables in the optimization problem. In the second stage, the allocation of track occupancy variables is further solved. The third stage focuses on the optimized allocation of maintenance team variables to ensure the scientific scheduling of maintenance resources. Finally, a validation experiment was conducted using the maintenance tasks of 19 EMU sets as the test scenario. The results indicate that when the number of maintenance teams is set to 4, an optimal balance between maintenance efficiency and operational cost is achieved, the occupancy duration of key line zones reaches 3034 min (the theoretical optimum), the number of maintenance teams is reduced by 33.33% compared to the initial 6 teams, and the number of storage operations is optimized to 27 times. Additionally, the algorithm’s solution time remains under 50 s, demonstrating significantly improved computational efficiency. Comparative experiments with baseline algorithms show that the proposed method reduces the occupancy duration of key line zones by up to 0.49%, decreases the number of storage operations by 14 times, and advances the maximum completion time by 20 min. In summary, the proposed method provides solid theoretical support for the formulation of maintenance plans and shunting schedules in EMU depots. Particularly in complex scenarios with limited maintenance capacity, it offers innovative and robust decision-making foundations, demonstrating significant practical guidance value. Full article

In this paper, a series of iron thin films were prepared using the direct current magnetron sputtering method at different deposition times. By means of characterization techniques such as X-ray diffraction (XRD), transmission electron microscopy (TEM), atomic force microscopy (AFM), and vibrating sample magnetometer (VSM), the structure, surface morphology, and magnetic properties of the iron thin films prepared at different deposition times were systematically investigated. The XRD results indicate that all the iron thin films exhibit a polycrystalline body-centered cubic structure, with an obvious preferred orientation in the (110) direction. As the deposition time increases, the average grain size of the iron thin films gradually increases. This is mainly because the post-sputtered atoms can provide the energy required for the formation, movement, and growth of the already deposited grains or clusters. When the deposition time is too long, factors such as elastic effects and size constraints will limit the growth of grains and clusters. Therefore, for the thin films deposited after 120 s, the average grain size gradually stabilizes. When the deposition time is short, the thin films usually grow in the form of island-like accumulation. Grains and clusters of uneven sizes accumulate on the substrate, so the roughness gradually increases. This also implies an increase in the density of defects such as internal stress and vacancies within the thin film. As the deposition time increases, the thin films gradually transform to grow in a layered and flat manner, and the grain size gradually stabilizes and becomes relatively uniform. Therefore, the roughness of the thin film samples decreases and tends to be stable. The magnetic property test results show that all the iron thin films exhibit ferromagnetism. The iron thin film prepared at a deposition time of 120 s has the best comprehensive performance, with a saturation magnetization M_s of 1567 emu/cm³, a coercivity of 92 Oe, and a remanence ratio of 0.86. Full article

This study investigates the fatigue strength of a motor hanger used in high-speed electric multiple units (EMUs). Finite element analysis and field measurements revealed that reduced weld penetration significantly increases stresses in welded regions. Line tests demonstrated that a 100 Hz torque ripple induces elastic vibration of the hanger, serving as the primary driver of stress propagation, with stress and acceleration levels increasing proportionally with the torque ripple amplitude. This 100 Hz excitation lies close to the hanger’s constrained modal frequency of about 109 Hz, creating a near-resonance condition that amplifies dynamic deformation at the welded joints and accelerates fatigue crack initiation. Hangers with lower in situ modal frequencies exhibited higher equivalent stresses. Joint dynamic simulation further showed that increasing motor mass reduces the longitudinal acceleration of the hanger, while enhancing the radial stiffness of rubber nodes markedly decreases both longitudinal and vertical vibration accelerations as well as stress responses. Based on these insights, a structural improvement scheme was developed. Strength analysis and on-track tests confirmed substantial reductions in overall and weld stresses after modification. Fatigue bench tests indicated that the critical welds of the improved hanger achieved a service life of 15 million km, more than twice that of the original structure (7.08 million km), thereby satisfying operational safety requirements. Full article

This work demonstrates the synthesis of ferromagnetic metallic cobalt nanoparticles embedded in a graphene framework through a graphene-assisted carbothermal reduction process. Cobalt oxide (Co₃O₄) was employed as the starting material, with graphene nanopowder functioning simultaneously as the reducing medium and structural scaffold. Thermal treatment at 850 °C under an argon atmosphere triggered the phase transformation. X-ray diffraction (XRD) confirmed the successful conversion of cobalt oxide into face-centered cubic (FCC) metallic cobalt. The graphene network not only accelerated the reduction reaction but also ensured the homogeneous distribution of cobalt nanoparticles within the matrix. Magnetic measurements using vibrating sample magnetometry (VSM) revealed a substantial improvement in ferromagnetic behavior: the graphene-mediated samples reached a saturation magnetization (M_s) of approximately 130 emu/g, compared to the nearly non-magnetic response of cobalt oxide annealed under the same conditions without graphene. Collectively, the structural, compositional, and magnetic results highlight graphene’s critical role in driving the formation of metallic cobalt nanoparticles with enhanced ferromagnetism, emphasizing their promise for use in magnetic storage, sensing, and spintronic applications. We anticipate that this study will inspire further research into the dual functionality of graphene, serving as both a reductive agent for metal oxides and a supportive matrix for nanoparticles, toward enhancing the structural integrity and functional properties of graphene-based metal nanocomposite materials. Full article

Magneto-photoluminescent hybrid materials (MPHMs) were prepared by incorporating cobalt ferrite nanoparticles (CFNs) into the fluorescent polymer poly(terephthalaldehyde-undecan-2-one) (PT2U). The CFNs, with a mean size of 3.95 nm, formed aggregates within the PT2U matrix (650–1042 nm) due to surface and interfacial interactions, modulating aggregate morphology and interparticle coupling. Magnetization studies revealed non-monotonic variations in saturation magnetization (30.3–16.2 emu/g), mean blocking temperature (39.3–43.1 K) and effective magnetic anisotropy energy density (2.14 × 10⁶–1.31 × 10⁶ erg/cm³) with increasing CFN content, consistent with the presence of canted surface spins and enhanced magnetizing interparticle interactions. Photoluminescence exhibited progressive quenching, dominated by collisional mechanisms at low CFN content and by interfacial CFN–PT2U interactions at higher loadings. Under a magnetic field (800 Oe), additional quenching occurred, attributed to magnetically induced polymer-chain rearrangements that disrupted the molecular stacking required for efficient aggregation-induced emission. These results demonstrate tunable magneto-photoluminescent coupling in MPHMs governed by surface and interfacial phenomena, providing insights for the design of functional and responsive hybrid materials. Full article