Search Results (440)

Nineteen monoterpene indole alkaloids, including twelve new ones, were successfully isolated and identified from the stems and leaves of Uncaria hirsuta (Havil.). The planar structures were elucidated by nuclear magnetic resonance (NMR), high-resolution mass (HRMS), and ultraviolet (UV) analyses. The absolute configurations of new compounds were determined using electron circular dichroism calculations in conjunction with NMR calculations. The acetylcholinesterase inhibitory activity of the isolated compounds was evaluated in vitro. In further biological evaluation, the isolated compounds were evaluated for their neuroprotective effects on HT22 neuronal cells. Six compounds demonstrated significant protective activity. Their intracellular reactive oxygen species (ROS) levels were measured using the DCFH-DA fluorescent probe, which markedly attenuated glutamate-induced ROS accumulation. The results not only enrich the knowledge on the structural diversity of monoterpene indole alkaloids but also offer substantial evidence for further pharmacological exploration. Full article

Wireless power transfer (WPT) systems for electric vehicles require reliable foreign object detection (FOD) mechanisms both during and prior to power transfer to ensure operational safety and efficiency. The primary purpose of this study was to develop a foreign object detection system to ensure that no objects are present in the area of magnetic coupling (between primary and secondary coils) prior to initiating power transfer. Conventional FOD techniques based on impedance, visual light, or thermal monitoring provide limited spatial information and are sensitive to coil misalignment. This paper proposes a machine learning-based FOD approach using a planar Magnetic Inductance Tomography (MIT) sensor array that enables spatial electromagnetic sensing for early detection and localisation of conductive foreign objects. A dataset comprising 17,800 measurement frames was collected using a custom STM32-based data acquisition system in the absence of (prior to) power transfer. Likewise, a dataset comprising 300 sets of measurement frames was collected during power transfer, in which each frame contains 120 electromagnetic sensor readings. This capture methodology coincides with the detection requirements of live WPT systems. Four classification models, including Random Forest, Support Vector Machine, XGBoost, and Multi-Layer Perceptron, were evaluated. To enhance robustness against sensor drift and environmental variations, feature-engineering techniques incorporating statistical, temporal, frequency-domain, and derivative-based features were developed. Experimental results demonstrate high detection accuracy under both controlled and real-world conditions. The proposed approach demonstrates the feasibility of integrating machine learning-based MIT sensing into wireless EV charging infrastructure for reliable foreign object detection. Full article

Inhomogeneous magnetic field distributions in high-frequency planar transformers frequently cause severe localized thermal hotspots and elevated leakage inductance. Traditional interleaved winding designs rely heavily on empirical trial-and-error, which becomes computationally prohibitive for multi-layer parallel structures due to the factorial “curse of dimensionality.” To address this bottleneck, this paper proposes a universal, data-driven optimization methodology. First, a quantitative one-dimensional prefix-sum model is established to correlate winding arrangements with spatial magnetomotive force (MMF) distributions, effectively simplifying the electromagnetic evaluation. Subsequently, a customized Genetic Algorithm (GA) framework, featuring physical-constraint-preserving operators such as Order Crossover (OX), is introduced to efficiently navigate the high-dimensional discrete search space. Using an extreme 26-layer complex parallel winding configuration (Np:Ns = 9:2) as a primary case study, the proposed GA method effectively bypasses over 1.5 million permutations, converging to the global optimum within 100 generations. The optimized structure achieves profound peak-shaving, drastically reducing both the peak MMF and total uncoupled magnetic energy area. This methodology provides a systematic, computationally lightweight EDA solution that fundamentally replaces empirical trial-and-error in the design of high-frequency magnetic components. Full article

Euler deconvolution is widely used to estimate the three-dimensional locations of geological sources from magnetic anomaly data. However, traditional Euler deconvolution is commonly performed on planar gridded data, whereas magnetic surveys in mountainous and hilly areas are often acquired over undulating terrain. Reducing such data to a horizontal plane before derivative calculation can introduce transformation errors, and derivative calculation by the conventional FFT-based (wavenumber-domain) method becomes less suitable under variable topographic conditions. To address these limitations, this study proposes an equivalent source method based on correlation imaging for calculating the spatial derivatives required by Euler deconvolution directly from magnetic anomaly data acquired over undulating terrain. An improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is further introduced to suppress spurious Euler solutions and retain valid source location estimates. Synthetic model experiments show that the proposed equivalent source method yields more accurate derivatives than the conventional FFT-based method under undulating terrain conditions. The improved DBSCAN algorithm effectively removes spurious solutions while preserving clustered solutions associated with geological sources. The proposed workflow was further applied to magnetic data from a coal fire zone in Shenmu, Shaanxi Province, China, to estimate the 3D locations of underground magnetic sources related to underground coal fires. The interpreted source locations are consistent with surface validation evidence, demonstrating the applicability of the proposed method for magnetic anomaly interpretation in complex topographic settings. Full article

Ion-acoustic waves in dense quantum plasmas are strongly influenced by Fermi degeneracy, Landau quantization, and finite-temperature effects, and in many relevant environments, they also experience memory and nonlocal transport processes that cannot be captured within the planar integer Korteweg-de Vries (KdV) paradigm. In the present work, we revisit this problem by considering a two-fluid, partially degenerate electron-ion plasma in which electron trapping in the presence of a quantizing field and finite temperature is taken into account. Starting from the normalized fluid-Poisson system appropriate for such magnetized quantum plasmas, the reductive perturbation technique is used to derive the planar integer KdV equation for weakly nonlinear ion-acoustic disturbances. Within this integer-order KdV framework, we recast the evolution equation as a planar dynamical system, construct the associated Hamiltonian and effective Sagdeev-like potential, and demonstrate the existence of compressive solitary waves and nonlinear periodic modes via homoclinic and periodic phase-space orbits. Exact multi-soliton solutions and interaction states are then obtained by combining Hirota’s direct bilinear method with generalized Wronskian representations, allowing us to describe not only standard one-, two-, and three-soliton profiles but also positon-negaton interactions relevant to magnetized, partially degenerate plasmas. To incorporate hereditary and history-dependent effects that arise from anomalous transport and nonlocal temporal response in dense environments, we extend the model by introducing a Caputo time-fractional derivative, thereby obtaining a time-fractional KdV (FKdV) equation that continuously connects the classical KdV limit to fractional dynamics. The FKdV equation is analyzed using the Tantawy technique. This semi-analytical iterative scheme yields rapidly convergent series approximations for the fractional ion-acoustic soliton and provides explicit control of the approximation error. The fractional solutions show that varying the order of the Caputo derivative modifies the amplitude, width, and temporal relaxation of the solitary structures and can even split the pulse into two distinct lobes, in contrast with the nearly rigid propagation predicted by the integer-order KdV equation. Taken together, these results clarify how Landau quantization, finite electron temperature, and fractional-order memory jointly shape the morphology, robustness, and interaction properties of ion-acoustic structures in strongly magnetized quantum plasmas of astrophysical and high-energy-density laboratory interest. Full article

Syrian hamsters (SHs) are widely used in research and as pets. However, their head anatomy has not yet been evaluated using sectional anatomy and imaging despite their unique features, which are important for studying ischemia–reperfusion injury, cancer, oral tumors, and common stomatognathic and ocular conditions. This study was conducted to correlate the planar anatomy of the heads of eight healthy male and female SHs with micro-CT and MRI images to establish a descriptive, imaging-based anatomical reference. Clinically important head structures observed in transverse, dorsal, and sagittal anatomical sections were correspondingly identified on micro-CT and/or MRI images. In SHs, head micro-CT was shown to be particularly effective for visualizing mineralized structures (e.g., dental and osseous tissues) and air-filled cavities (e.g., the ear canal and tympanic bulla), whereas MRI was demonstrated to provide superior assessment of soft tissues, including the brain, vertebral canal and spinal cord, musculature, intervertebral disks, major salivary glands, eye, and harderian and extraorbital lacrimal glands. The present investigation provides a descriptive and imaging-based anatomical reference of the SH head by integrating anatomical sections, in situ topographical anatomy, and dry-skull photographs with micro-CT and MRI datasets, thereby serving as a foundational resource for the interpretation of cross-sectional imaging in both research and clinical contexts. Full article

We study the planar dynamics of a charged particle subjected to a radially repulsive inverted harmonic potential and a perpendicular uniform magnetic field, a configuration that is relevant to nanoscale-charged transport and confinement in low-dimensional systems. The competition between the destabilizing central repulsion and magnetic field-induced rotational motion gives rise to rich trajectory behavior, including spiraling, unbounded escape, and parameter-dependent quasi-confined motion. The governing coupled differential equations of motion are solved analytically. The resulting trajectories are classified as functions of system parameters. The proposed framework provides insight into charge carrier dynamics in nanostructured environments such as quantum wells, 2D materials, and plasma-like nanosystems, where effective repulsive potentials may arise from external gating or collective interactions. In addition, the model offers a classical analogue for interpreting features associated with magnetic confinement in non-equilibrium or unstable regimes. These results contribute to the theoretical foundation for designing and controlling charged particle motion in emerging nanomaterials and devices. Full article

Background: Cardiac magnetic resonance (MRI) images often exhibit low contrast, anatomical variability, and indistinct boundaries, particularly in the myocardium (MYO) and right ventricle (RV). These challenges can reduce the reliability of both manual and automated segmentation, highlighting the need for more robust and boundary-aware approaches. Methods: In this study, an Aspect-Aware Boundary-Resilient UNet3D (ABR-UNet3D) architecture is proposed for cardiac MRI segmentation. The model incorporates an Aspect-Aware Complementary Attention (AAC) module that combines multi-planar contextual information with a complementary gating mechanism to enhance boundary representation. The method was evaluated on the ACDC dataset under consistent training conditions. In addition to Dice Similarity Coefficient (DSC) and Intersection over Union (IoU), boundary-based metrics, including the 95th percentile Hausdorff Distance (HD95), Average Surface Distance (ASD), and Surface Dice, were employed. Furthermore, a five-fold cross-validation protocol and detailed ablation studies were conducted to assess robustness and analyze the contribution of individual AAC components. Results: The proposed method achieved a mean DSC of 0.9603 in single-run experiments on the ACDC dataset and showed consistent performance in anatomically challenging regions, particularly for RV and MYO segmentation. In addition, five-fold cross-validation experiments resulted in an average DSC of 0.952 ± 0.009 and IoU of 0.908 ± 0.012, indicating stable performance across different data splits within the evaluated dataset. Boundary-based metrics also showed improved surface agreement and lower boundary errors compared with the evaluated baseline models. Ablation studies further indicated that the combined use of multi-planar contextual information and complementary gating contributes more effectively to segmentation performance than the individual components used separately. Conclusions: The results suggest that the proposed ABR-UNet3D architecture provides a stable and competitive segmentation framework for cardiac MRI images within the scope of the ACDC dataset. By jointly modeling contextual information and boundary refinement, the method improves segmentation reliability in challenging regions while maintaining competitive and consistent performance with respect to existing approaches. Full article

In this paper, we investigate the absolute stability of several Translationally Invariant Configurations (TICs) observed in cholesteric liquid crystal samples. The bounding plates of the samples may impose homeotropic anchoring (case 1), slightly tilted anchoring when the plates are also rubbed in either the same (case 2) or opposite (case 3) directions, or hybrid anchoring with planar on one plate and homeotropic on the other. In each case, the stability is examined as a function of the confinement ratio—defined as the ratio of the sample thickness to the cholesteric pitch—and of the applied field (electric and/or magnetic). Full article

In this study, the two-dimensional aligned steel fiber-reinforced micro-expansive concrete (2D) was prepared, aiming to address the inherent vulnerabilities of concrete, such as early-age shrinkage cracking and low tensile ductility. For this purpose, the steel fibers and expansive agent were utilized. Furthermore, the planar rotating magnetic field was used to randomly distribute the steel fibers in a two-dimensional plane. In order to verify its superior mechanical and shrinkage properties, the compressive, fracture and drying shrinkage tests were carried out. The results demonstrate that the 2D alignment method enhances the fiber utilization efficiency. Compared with fiber-free groups, the compressive strength and fracture parameters of specimens incorporating steel fibers were improved. Furthermore, compared with randomly distributed steel fiber-reinforced micro-expansive concrete (RD), the 2D alignment method made the cubic compressive strength and fracture energy improve 8–14.2% and 19.4–110%, respectively. Additionally, the advantage of the fiber 2D alignment method was also reflected in the inhibition of drying shrinkage. Compared with normal concrete, the 180-day shrinkage strain of the 2D1.2 group was reduced to 200 με (only 19.5% of that of normal concrete, or 30.6% of that of micro-expansive concrete). Mechanistically, these superior performances are fundamentally governed by a coupling effect: chemical shrinkage compensation and physical alignment constraint. Full article

High-frequency, high-power-density planar transformers represent a key development direction for magnetic components in power converters, with winding loss optimization being a critical design issue. Under low-voltage, high-current operating conditions, the optimization potential of conventional parameters—such as operating frequency, copper thickness, and insulation thickness—is severely constrained by circuit topology and fabrication process limitations. As the number of paralleled PCB layer increases, the possible interlayer connection arrangements grow exponentially. Existing methods largely rely on enumerating and comparing predefined structures, lacking a systematic optimization approach and making it difficult to balance computational efficiency with global optimality. To address this problem, this paper proposes a systematic optimization method for the connection arrangement of parallel windings in planar transformers based on an impedance matrix and mathematical programming. First, an impedance-matrix-based loss model is established that uses the connection arrangement as an explicit variable, reducing the per-evaluation time to approximately 1% and eliminating the cumbersome need to rebuild the model for each candidate as in conventional approaches. The connection arrangement optimization problem is then transformed into a standard mathematical programming problem, enabling fast global solution for the optimal connections. The validity of the proposed model and optimization method is verified through impedance measurements and comparative simulations. This work provides a systematic solution for the interlayer connection design of high-frequency, high-current planar transformers. Full article

Flexible textile membranes were prepared by impregnating woven cotton fabrics with silicone oil (SO)-based suspensions containing carbonyl iron (CI) microparticles and iron oxide microfibers ($\mu$Fe). The microfibers were obtained by a microwave-assisted microplasma process and then co-dispersed with CI in SO. In the final membranes, the CI content was kept constant at ${\mathrm{\Phi }}_{\mathrm{CI}}=10$ vol.%, whereas the microfiber fraction was 0, 10 and 20 vol.%. The resulting membranes were used as dielectric layers in planar capacitors and examined at 1 kHz under a static magnetic field of up to 150 mT and compressive pressure up to 10 kPa. In every composition, the capacitance rose with increasing magnetic flux density, but both the zero-field capacitance and the field-induced capacitance change became smaller as the microfiber content increased. A monotonic, nearly linear increase in capacitance was also observed under compression over the tested pressure range. Within a simplified parallel-plate and magnetic-stress analysis, the capacitance data were further used to estimate the apparent relative permittivity, together with capacitance-derived indicators of deformation and stiffness. These estimates suggest field-induced stiffening of the membranes and a higher apparent low-field stiffness at higher microfiber loading. The obtained hybrid CI/$\mu$Fe-based textile membranes can serve as composition-tunable dielectric layers whose electrical response is influenced by both magnetic field and compressive loading, making them relevant for flexible capacitor-based elements. Full article

A 2D multiphase-flow coupling simulation model for preparing nanocrystalline ribbons using planar-flow casting (PFC) with a cooling roller was established. The influence of roller speed on molten pool characteristics, cooling-roller heat transfer, and ribbon thickness was analyzed. The effect of ribbon thickness on the total loss and permeability of the magnetic cores was investigated. The results indicate that the molten pool size decreased as the roller speed increased. At t = 5 ms, the maximum heat-transfer coefficient of the roller surface increased from 2.09 × 10⁶ W·m⁻²·K⁻¹ at 15 m/s to 2.6 × 10⁶ W·m⁻²·K⁻¹ at 24 m/s. The ribbon thickness decreased from 39.96 μm to 20.02 μm (a 49.9% reduction) as the roller speed increased from 18 m/s to 30 m/s. The total loss of the nanocrystalline magnetic cores increased with ribbon thickness, whereas their permeability increased as ribbon thickness decreased. At 100 kHz, the nanocrystalline magnetic core made of 10–12 μm ribbons exhibited a high permeability of 59,507. Full article

This study examines the design, manufacturing, and testing of planar PCB inductors (spiral and toroid), including multilayer PCB toroid configurations. These inductors are intended for environments with strong magnetic fields, such as high-energy physics experiments and medical applications, where traditional inductors with ferromagnetic cores are unsuitable. Twelve inductor samples were manufactured and tested. The focus was on maximizing inductance and evaluating performance in a high-frequency DC-DC step-down converter. Key parameters measured included inductance, resistance, thermal performance, electromagnetic interference (EMI), and frequency-dependent behavior in multilayer PCB implementations. The results showed that planar spiral inductors handled higher currents and achieved better efficiency, reaching up to 74.86%. Planar toroid inductors were more tolerant of added shielding, maintaining their inductance, while multilayer toroid designs exhibited reduced DC resistance but increased frequency dependence and sensitivity to parasitic effects. Overall, planar inductors were found to be viable for applications where ferromagnetic cores are unsuitable. Further optimization of geometry, layer configuration, and manufacturing processes could enhance their performance. Full article

Nitronyl nitroxides (NNs) are widely employed in chemistry, physics, and materials science due to their inherently high stability and magnetic properties. However, the synthesis of C(2)-organoelement derivatives remains a challenging task. This paper reports on the efficient synthesis and characterization of an unusual organosilver complex consisting of the [Ag–(IPr)₂]⁺ cation and the [Ag–(NN)₂]⁻ anion. The salt [Ag–(IPr)₂][Ag–(NN)₂] was prepared in high yields (88–96%) by two synthetic routes: by reacting the carbene ligand precursor IPr·HCl with Ag₂O and nitronyl nitroxide NN–H, or by addition of NN–H/^tBuONa to a THF solution of IPrAgCl (generated in situ from IPr·HCl and Ag₂O) under microwave irradiation. Electrochemical analysis of [Ag–(IPr)₂][Ag–(NN)₂] revealed a reversible one-electron oxidation peak at E_1/2 = −0.258 V and an irreversible reduction peak at E_p = −2.169 V, which is likely related to the electrochemical transformation of the nitronyl nitroxide moieties. Crystallization from an acetone/benzene solution yielded crystals of [Ag–(IPr)₂][Ag–(NN)₂]·2H₂O solvate, in which the diradical anion [Ag–(NN)₂]⁻ is bound to two water molecules by hydrogen bonds. These hydrogen bonds stabilize a planar conformation of the [Ag–(NN)₂]⁻ anion, in which both NN fragments lie in the same plane and, according to DFT calculations, are linked by fairly strong antiferromagnetic interaction. DFT calculations also predict the dissociation of the complex with water in toluene solution and a conformational change leading to the appearance of about 90° between NN fragments and a significant decrease in exchange interaction. Full article