Search Results (25,696)

To optimize the oxygen reduction reaction activity and long-term stability of the PrBaFe₂O_6-δ (PBF) cathode for protonic ceramic fuel cell (PCFC), this study employed the sol–gel method to dope Sc at the Fe-site of PBF, preparing a novel PrBaFe_1.8Sc_0.2O_6-δ (PBFS) cathode. The effects of different sintering temperatures on the phase composition, microstructure, and electrochemical performance of the PBFS cathode were systematically studied. Results showed that the PBFS cathode sintered at 1000 °C formed a single cubic perovskite structure, exhibiting excellent chemical compatibility with the electrolyte. Sc doping induced Fe in the cathode to exhibit a mixed valence state of Fe²⁺/Fe³⁺/Fe⁴⁺, thus significantly increasing the oxygen vacancy concentration. The single cell assembled achieved a peak power density of 1.303 W·cm⁻² and a polarization resistance as low as 0.035 Ω·cm² with H₂ as the fuel at 700 °C. Moreover, after 100 h of long-term operation at 650 °C, the power density decayed by only 5.23%, thus demonstrating excellent long-term stability. This study offers an efficient cobalt-free cathode candidate for PCFC. Full article

This research investigates the effects of electrochemical oxidation on surface properties and corrosion performance of the Ti-6Al-4V ELI alloy intended for biomedical applications. Electrochemical anodization is performed in 1 M H₂SO₄ and 1 M H₃PO₄ electrolytes at applied potentials of 200, 250, and 275 V for 1 min. Morphological characteristics and chemical constitution of the oxide films are investigated by SEM-EDS analysis, while surface roughness, wettability, and microhardness are evaluated using profilometry, contact angle measurements, and Vickers microhardness testing. Electrochemical behavior is assessed by monitoring free potential (OCP) and electrochemical impedance spectroscopy in Ringer solution and Ringer solution containing 40 g/L hydrogen peroxide. Among the investigated conditions, anodization at 200 V for 1 min provides the most favorable surface morphology, producing well-defined and uniformly distributed nanopores while maintaining the structural stability of the oxide layer. Oxidation in 1 M H₂SO₄ leads to a more homogeneous nanoporous structure, higher surface roughness, improved hydrophilicity, and increased microhardness compared to 1 M H₃PO₄ treatment. Electrochemical impedance spectroscopy analysis reveals superior corrosion resistance for all oxidized samples in comparison with the untreated alloy. The oxide layers obtained in sulfuric acid exhibit the highest polarization resistance and electrochemical stability in simulated physiological environments. Full article

Quantitatively characterizing the dynamic evolution of fracture swarms under offset well low-frequency distributed acoustic sensing (LF-DAS) monitoring remains a significant challenge. This study proposes a physics-data dual-driven closed-loop inversion framework to address this problem. The framework consists of three core modules: (1) a fluid–solid coupled semi-analytical forward model applicable to variable-rate injection and shut-in conditions; (2) an automatic key feature identification method based on multi-scale scanning and physical polarity constraints; and (3) a dynamic inversion model for fracture swarms based on adaptive particle swarm optimization (APSO). Validation against the classical PKN model confirms that the proposed forward model accurately reproduces the fundamental fracture propagation behavior, with good agreement in fracture half-length and net pressure evolution. In synthetic inversion cases, the method successfully recovers the number of fractures, the dynamic flow rate allocation history, fracture length evolution, and the spatiotemporal strain rate response. A field application further demonstrates that three dominant fractures were generated during stimulation, reaching the vicinity of the monitoring well at 18, 27, and 46 min with corresponding spacings of approximately 21 m and 16 m. The proposed framework provides a new route for advancing LF-DAS monitoring from qualitative interpretation to quantitative dynamic inversion. Full article

Overhauser magnetometer (OVM) is a proton precession magnetometer (PM) enhanced by electron resonance, and it is widely used in earthquake prediction, UXO detection, geological exploration, etc. For fast measurement, high cycling rate is necessary for OVM to enhance spatial resolution. Due to the impossibility to receive Larmor signal during the polarization process, traditional intermittent measurement is limited in fast mobile measurement applications owing to the long polarization time. Since it is difficult for proton magnetization to align rapidly for the long longitudinal relaxation time of liquid proton, we combined RF continuous excitation with a series 90° pulse to achieve fast measurement. To achieve the best alignment, a dynamic equation of Larmor precession is constructed and calculated, and the influences such as pulse waveform, pulse strength, and pulse duration on the proton magnetization alignment were investigated. The influence of different waveform pulses on the Larmor signal was studied experimentally, and the experimental results verified that the polarization time can be significantly shortened and fast measurement can be achieved by optimizing the waveform, strength, and duration of the 90° pulse. By using the optimized 90° pulse, the proton magnetization can be saturated within 3 ms, and 0.02 nT sensitivity was observed at 1 Hz cycling rate. Consistency between theory and the experiment indicates that the dynamic equation of Larmor motion can provide theoretical guidance for the investigation of fast measurement. Full article

The dielectric properties of cement-based composites (CBC) are highly sensitive to environmental humidity, which seriously restricts the quantitative interpretation accuracy of ground-penetrating radar (GPR) in the non-destructive testing of cement concrete pavement. In view of the lack of targeted prediction models due to the unclear mechanism of humidity influence in existing research, the core innovations of this study are: (1) the synergistic mechanism of water vapor dipole polarization and adsorbed water multi-layer polarization is clarified, revealing the intrinsic reason for the accelerated growth of permittivity in the high humidity range; (2) the constructed four-component dielectric model of “cement mortar–aggregate–water vapor–adsorbed water” achieves high-precision prediction within the range of 50~100% RH (R² > 0.94, relative error < 5%), and shows good predictive ability within the test scope of this study; (3) a GPR humidity correction protocol based on the model is proposed, which can effectively improve the accuracy of nondestructive testing of cement concrete structures. In this study, CBC samples with water–cement ratios of 0.4~0.6 were prepared using P.O 32.5/P.O 42.5 cement and limestone aggregate. Under the conditions of 20 ± 0.5 °C, relative humidity (RH) of 50~100%, and 2 GHz (common GPR frequency), the permittivity was measured using an Agilent P5001A network analyzer to verify the model. The results show that the permittivity increases monotonically with humidity, and the growth rate in the high humidity range (70~100%) is 2.2 times that of the low humidity range (50~70%); The higher the water–cement ratio, the shorter the age, and the lower the cement strength grade, the stronger the humidity sensitivity of CBC dielectric properties. This model provides a reliable humidity correction tool for GPR detection, and significantly improves the accuracy of nondestructive evaluation of cement concrete structures. Full article

Weak-echo ship target detection in GNSS-based bistatic synthetic aperture radar is severely limited by the coupled effects of burst-type strong windows and polarization mismatch, cross-frequency mis-registration, and long-sequence chain drift in dual-frequency dual-polarization observations. To address these issues, this paper proposes DFDP-QuadDiff, a dual-frequency dual-polarization quad-differential framework for weak-echo ship target detection using B1/B3 × horizontal–horizontal (HH)/vertical–vertical (VV) four-channel complex range-time data. The proposed framework integrates polarization-consistency-driven strong-window suppression, intra-band adaptive polarimetric synthesis, joint delay–Doppler–phase cross-frequency registration, segment-wise Jones drift calibration, and quality-aware final fusion in a unified hierarchical processing chain. In this way, multi-source inconsistencies are progressively constrained and suppressed from the polarization level to the segment level before final accumulation and detection are performed. Experimental results on self-developed four-channel GNSS-S demonstrate that, relative to the best raw single-channel result, the proposed framework increases the median SCR from 6.51 dB to 9.04 dB (+2.53 dB), improves the P10 SCR from −1.76 dB to 3.05 dB (+4.81 dB), and raises the track continuity from 0.85 to 0.97. In addition, the standard deviation of segment-wise delay drift is reduced from 0.97 bin to 0.29 bin, and positive multi-scale accumulation gains are maintained up to the second-long integration range. These results indicate that the proposed framework not only substantially enhances the stability, continuity, and long-time integrability of weak-target responses under low-SNR maritime conditions, but also maintains robust gains under weak-visibility, interference-dominant, and mismatch-sensitive local conditions in the stratified evaluation, thereby establishing a physically interpretable and implementation-ready solution for collaborative weak-target detection in dual-band dual-polarization GNSS-S. Full article

Weak alternating electric fields are widely used in neuromodulation techniques such as transcranial alternating current stimulation (tACS), yet the precise biophysical mechanisms underlying neuronal responses remain incompletely understood. Current computational models often neglect the electrical properties of the extracellular microenvironment, limiting their predictive accuracy. Motivated by experimentally observed frequency-dependent modulation of neuronal activity, we developed a two-compartment model of hippocampal CA3 pyramidal neurons in which extracellular resistance is explicitly parameterized and systematically examined as a key factor influencing neuronal response properties under external electric fields. Within a dual-compartment Hodgkin–Huxley framework, the neuron is divided into a “soma–basal dendrite unit” and an “apical dendrite unit,” accounting for voltage polarization induced by external fields. Using phase-locking ratio curves and three-dimensional parameter response surface, we systematically characterized neuronal sensitivity to field parameters and examined how potassium equilibrium potential ($V_K$) and extracellular resistance ($R_{\mathrm{out}}$) modulate these responses. Our results demonstrate that increasing $R_{\mathrm{out}}$ enhances neuronal responsiveness to external fields, while $V_K$ variations primarily regulate intrinsic excitability. These findings provide mechanistic insights into the frequency-dependent modulation of neuronal responses under weak electric fields, consistent with phenomena observed in biological neural systems, and provide a mechanistic and theoretical framework for understanding the joint effects of electric field amplitude and frequency on neuronal sensitivity to weak electric fields, which may help inform future neuromodulation strategies. Full article

Synthetic Aperture Radar (SAR) ship classification plays a critical role in maritime surveillance, addressing challenges such as the similarity between ship categories, as well as scarcity of annotated datasets and data imbalance. In this paper, a lightweight and real-time dual-branch architecture is proposed to effectively address the SAR ship classification task. The proposed approach integrates dual-polarization data within a hybrid convolution-transformer framework to improve classification performance. The model fuses dual-polarization modes, combining convolutional layers for local feature extraction with transformer blocks for global contextual understanding. Evaluations on the OpenSARShip 2.0 dataset show that the proposed model achieves 97.50% accuracy in the 3-class configuration and 93.28% in the 6-class configuration. For the FUSAR-Ship dataset, which does not provide dual-polarization data for the same ship target, the single branch model achieved an accuracy of 94.92% for the 7-class configuration. Despite its dual-branch design, the model maintains computational efficiency, making it suitable for real-time maritime monitoring applications. The results demonstrate the effectiveness of polarization-aware hybrid models for scalable and robust SAR ship classification. Full article

Coherent optical communication serves as the backbone of long-haul, high-capacity optical networks, where polarization-insensitive 90° optical hybrids (OHs) are crucial for system simplification and robustness. This work presents a polarization-insensitive 90° OH based on asymmetric double-strip silicon nitride waveguides, designed for dual-polarization quadrature phase-shift keying (DP-QPSK) systems. The device consists of a cascaded polarization-insensitive structure incorporating one 1 × 2 and three 2 × 2 multimode interference (MMI) couplers, interconnected by four 90° bent waveguides. Optimized via 3D finite-difference time-domain (FDTD) simulations, the 1 × 2 MMI coupler exhibits insertion losses below 0.06 dB (TE) and 0.09 dB (TM), while each 2 × 2 MMI coupler shows insertion losses under 0.2/0.4 dB, amplitude imbalance below 0.05/0.18 dB, and phase error within ±0.5°/±1.5° for the TE/TM modes, respectively. Based on these components, the full device achieves polarization-insensitive operation across a 100 nm bandwidth (1500–1600 nm), with a phase error within ±1°, insertion loss below 0.3 dB (TE) and 0.5 dB (TM), and common-mode rejection ratio better than −40 dB (TE) and −30 dB (TM). Furthermore, the design demonstrates high fabrication tolerance, maintaining performance under manufacturing deviations of ±2 μm in MMI length and ±20 nm in waveguide spacing. This work provides a promising polarization-insensitive OH design and a viable route toward cost-effective mass production of next-generation high-speed coherent systems. Full article

Marine-derived natural products are increasingly recognized for their therapeutic potential in cancer and other chronic diseases. Despite significant advances, current cancer treatments remain challenged by toxicity, drug resistance, and limited survival benefits. Natural compounds offer promising alternatives due to their multi-target mechanisms and favorable safety profiles. Among them, Spirulina, a filamentous cyanobacterium, stands out for its rich composition and diverse biological activities. Its anticancer effects involve apoptosis induction via intrinsic and extrinsic pathways, cell cycle arrest at G1/S or G2/M phases, inhibition of angiogenesis through the VEGF/VEGFR2 axis, and suppression of epithelial–mesenchymal transition. These activities are mainly attributed to C-phycocyanin, allophycocyanin, phenolic compounds, and immunomodulatory polysaccharides. Spirulina also exhibits potent immunomodulatory effects by enhancing natural killer cell activity, promoting M1 macrophage polarization, and regulating Th1 and Th17 cytokine responses, highlighting its potential as both an immunotherapeutic and chemoprotective agent. Moreover, preclinical findings suggest it may reduce chemotherapy-associated side effects. However, translation into clinical therapy remains limited by low bioavailability, lack of standardized extracts, and scarce clinical evidence. This review summarizes current mechanistic and immunological insights and highlights the need for optimized formulations, defined dosing strategies, and well-designed clinical trials to validate Spirulina’s potential in cancer treatment. Full article

Cordierite-based ceramics (Mg₂Al₄Si₅O₁₈) were successfully synthesized and comprehensively characterized to evaluate their structural and dielectric behavior for high-temperature electronic applications. Morphological, microstructural and vibrational analyses confirm the high phase purity and structural integrity of the synthesized material. Dielectric measurements reveal high real permittivity (ε′) values at low frequencies and elevated temperatures, mainly attributed to interfacial polarization arising from Schottky-type barriers at grain–grain and surface–volume interfaces, underscoring the crucial influence of heterogeneous interfaces on the dielectric response. The electrical conductivity follows a thermally activated hopping mechanism involving both intra-grain and grain-boundary charge transport. Analysis of the electric modulus formalism provides further insight into relaxation dynamics: the real (M′) and imaginary (M″) components highlight pronounced space-charge effects, with M″ exhibiting a distinct relaxation peak (M″) associated with grain contributions. The systematic shift of this peak toward higher frequencies with increasing temperature indicates enhanced charge-carrier mobility and a strongly thermally activated relaxation process. The frequency-dependent conductivity displays two regimes: a low-frequency plateau corresponding to dc conductivity and a high-frequency dispersive region following a power-law behavior characteristic of hopping conduction, with power-law exponents (α₁ and α₂) markedly lower than unity, confirming the non-Debye character of the relaxation processes. The hopping frequency (ω) increases with temperature, further supporting the thermally activated nature of charge transport. Activation energies extracted from Arrhenius plots of dc conductivity are 0.88 eV for grain boundaries and 0.83 eV for grains, demonstrating that both microstructural regions significantly contribute to the overall conduction process. Full article

Recent advances in metasurface-based research have enabled significant reductions in the size and weight of optical devices. By employing metallic nanostructures with subwavelength dimensions, color filtering can be achieved through phenomena such as extraordinary optical transmission (EOT), which allows specific bands of visible light to pass through. However, conventional EOT-based color filters often suffer from strong side peaks outside the desired transmission band, degrading color purity and hindering accurate color reproduction. In this study, we propose an ultrathin, polarization-independent color filter based on a nanohole array that utilizes the EOT effect while effectively suppressing unwanted side peaks. To achieve this, we introduce a modified design in which additional metallic triangular edges are placed around a hole in a conventional hole array. This configuration suppresses higher-order diffraction modes and enables selective transmission at RGB wavelengths, thereby improving spectral selectivity and overall color performance. Full article

Tornado is a localized, small-scale severe convective weather phenomenon characterized by extreme destructiveness. Tornado detecting and warning mainly rely on Doppler weather radar, which identifies and tracks tornadoes by recognizing the tornado vortex signature and supercells in radar data. Artificial intelligence technology has been applied to tornado recognition in recent years. However, existing monitoring methods, especially those using unsupervised learning algorithms, still have limited recognition accuracy and timely warning, and usually struggle to strike a balance between detection accuracy and false alarm rate. A novel tornado detection algorithm TDA-DARKNet has been proposed to address the aforementioned issues. The algorithm integrates a dual attention mechanism, dense residual connections, and Kolmogorov–Arnold network (KAN). A tornado dataset suitable for deep learning has been formed, which utilizes features including radial velocity, reflectivity, velocity spectrum width, differential reflectivity, and correlation coefficient in radar data. The TDA-DARKNet algorithm was trained and tested using the tornado dataset, and evaluated in tornado cases. The experimental results show that TDA-DARKNet improves the detection probability and extends the lead time to a maximum of 42 min in strong tornado situations, while achieving 97.11% accuracy, 95.08% precision, indicating strong overall identification performance. In addition, by directly leveraging radar-based data for tornado identification, the algorithm eliminates the need for manual feature engineering, simplifies data processing, reduces complexity, and further enhances detection effectiveness. Full article

The development of planar structures such as wings or leaves is a common feature among organisms and serves as a mechanism to increase surface to volume ratios. We wished to explore whether the recurrent and independent development of similar adaptive planar morphologies is the result of an activation of common genetic modules or toolkits. To test this, we focused on the developmental gene networks that are proposed to define leaf polarity in eudicots in phylloclades, leaf-like organs derived from branch primordia, in the monocot Ruscus aculeatus. Since branch primordia normally have a radial shape, this approach allowed us to examine the genetic changes required for the transformation from a round to a planar (flat) form. In our transcriptome analysis of phylloclade and stem tissue, we detected 76,085 annotated ORFs of which 87.2% were identified as complete out of 2026 BUSCO groups. Expression patterns clearly identify differentiation between phylloclade and stem tissues consistent with an enhanced photosynthetic function in the phylloclades. However, except for the AS1/AS2 and possibly STM module, we see little evidence that canonical leaf adaxial and abaxial modules are activated in the sampled phylloclades compared with the stems. Our results show that the unifacial nature of phylloclades is consistent with the observed lack of strong adaxial/abaxial molecular signatures. We propose that in R. aculeatus and plants with similar unifacial laminar leaves, adaxial/abaxial molecular identity may not be required for planar growth, and that lateral expansion of organ primordia and acropetal and intercalary cell division may be sufficient to generate planar versus radial organ shapes. Full article

The practical application of inorganic ferroelectric fillers in flexible piezoelectric composites is critically constrained by low polarization efficiency and severe interfacial incompatibility with polymer matrices. Herein, we report a multi-level in situ surface modification strategy that simultaneously addresses both limitations. High-purity one-dimensional tetragonal barium titanate nanofibers (BTO NFs) are first synthesized via sol–gel electrospinning combined with a two-step gradient annealing process, which precisely controls phase evolution and preserves structural continuity. To overcome the detrimental acid-induced degradation of BTO NFs during functionalization, a polydopamine (PDA) buffer layer is first conformally coated, followed by the liquid-phase deposition of a conductive polypyrrole (PPy) shell, forming a robust core–shell PPy@PBT NFs architecture. Incorporating only 4 wt% of these multifunctional fillers into a poly(vinylidene fluoride) (PVDF) matrix yields a dramatic enhancement in electromechanical performance. The resulting flexible piezoelectric energy harvesters achieve a piezoelectric coefficient (d₃₃) of 28.7 pC/N, an output voltage of 13 V, and an output current of 0.7 μA, representing substantial improvements over unmodified filler systems. This synergistic enhancement originates from the PDA-mediated interfacial stress transfer and the PPy-induced Maxwell–Wagner polarization intensification, establishing a robust and generalizable paradigm for high-performance flexible piezoelectric composites in self-powered wearable electronics. Full article