Search Results (202)

Seasonal design floods and operational water levels are critical for high-efficient water resource utilization. In this study, statistical and rational analyses methods were applied to divide the flood season based on seasonal rainfall patterns. The Mann–Kendall test and Theil–Sen analysis were used to detect trend changes in the observed flow series. Both stationary and nonstationary flood frequency analysis methods were conducted to estimate seasonal design floods. The Three Gorges Reservoir (TGR) in the Yangtze River, China, was selected as the case study. Results show that the TGR flood season could be divided into four periods: the reservoir drawdown period (1 May–20 June), the Meiyu flood period (21 June–31 July), the transition period (1 August–10 September), and the Autumn Rain refill period (11 September–31 October). Trend analyses indicate that the flow series at the TGR dam site exhibited a decreasing trend in recent decades. Upstream reservoir regulation has significantly reduced inflow discharges of TGR, and the nonstationary seasonal 1000-year design floods in the transition period are decreased by about 20%, and the flood control water level could rise from 145 m to 157 m, which can generate 2.288 billion kW h more hydropower (16.57% increase) while maintaining unchanged flood prevention standards. This study provides valuable insights into the TGR operational water level in the flood season and highlights the necessity of considering the regulation impact of upstream reservoirs for design floods and reservoir operational water levels. Full article

Background: Shentong Zhuyu Decoction (STZYD) is a traditional Chinese medicine formula that has shown promise in alleviating neuropathic pain (NPP), yet its central mechanisms remain unclear. Methods: We investigated the STZYD effects on NPP using network pharmacology, in vivo assays, and analytical chemistry, focusing on molecular pathways and GABAergic neuronal modulation. Results: Network pharmacology revealed 254 potential STZYD targets enriched in calcium signaling and GABAergic synapse pathways, especially the NMDAR-2B/CaMKII/CREB axis. High-dose STZYD (1.25 g·mL⁻¹) and ifenprodil (6 mg·kg⁻¹) reversed hyperalgesia and anxiety-like behaviors in spared nerve injury (SNI) mice, and microdialysis showed that STZYD and ifenprodil reduced the glutamate, D-serine, aspartate, glycine, and gamma-aminobutyric acid levels in the interpeduncular nucleus (IPN). Immunofluorescence and fiber photometry showed reduced c-Fos expression and suppressed GCaMP signals in IPN GABAergic neurons, with chemogenetic experiments confirming their role in pain modulation. Multimodal molecular biology experiments demonstrated that STZYD and ifenprodil significantly downregulated the GluN2B, p-CaMKII, and p-CREB expressions within the IPN. We identified 145 constituents in STZYD through high-resolution mass spectrometry analysis, among which 40 were absorbed into plasma and 7 were able to cross the blood–brain barrier and accumulate in the IPN. Molecular docking revealed the strong binding of licoricesaponin K2 and senkyunolide F to NMDAR-2B. Conclusions: STZYD exerts dose-dependent antinociceptive effects by modulating IPN GABAergic neuronal activity through the inhibition of the NMDAR-2B-mediated CaMKII/CREB pathway. Full article

Pigeon meat is gaining increasing popularity due to its high nutritional value and desirable sensory qualities. This study aimed to comprehensively evaluate the quality-related components of pigeon meat by analyzing conventional nutritional indicators—including amino acids, fatty acids, and flavor nucleotides—in combination with multi-omics approaches. The results indicated that pigeon meat contains high levels of arginine (Arg), alanine (Ala), linoleic acid, and glycerophospholipids (GPs), which contribute significantly to its flavor profile. Additionally, several lipids, namely, PS (18:0/20:4), PE (16:2; O/2:0), HexCer (9:0;2O/42:11), Hex2Cer (38:1;2O), PS (16:0; O/21:0), and PE (42:9), were identified as potential characteristic markers of pigeon meat. A comparative analysis among three breeds—White King, Shiqi, and Tarim pigeons—revealed breed-specific differences in endogenous compounds, with each breed exhibiting distinct compositional traits. This study provides a comprehensive dataset for quality assessment and offers critical insights for the authenticity verification of pigeon meat. Full article

In recent years, Transformer-based target tracking algorithms have performed well in ordinary scenarios. However, when applied to satellite video scenarios, the tracking effect of the algorithms is not satisfactory due to the small size of satellite video targets, blurred features, and complex background interference. To address this issue, this paper proposes an algorithm for Enhancing Spatial Perception for Satellite Video Target Tracking (ESPTrack). This algorithm, through the spatial collaborative attention module, integrates local and global spatial information to enhance the multi-level representation of the target’s detailed features and overall structure. Meanwhile, a Gaussian prior cross-attention module is constructed. The Gaussian distribution weighting is utilized to enhance the key context information, improving the model’s ability to perceive the target’s spatial position and reducing the impact of background interference. To verify the effectiveness of the algorithm proposed in this paper, experiments were conducted on the satellite video datasets SatSOT and OOTB. The results show that the proposed algorithm has better performance compared with the existing target tracking algorithms, and it is verified that enhancing spatial perception in complex satellite video scenarios can effectively improve tracking performance. Full article

Environmental policy helps policymakers and researchers understand the process and expected effects of policy before the policies are fully implemented. This study aims to estimate the effects of resource-conserving and environmentally friendly policy implemented in the Wuhan metropolitan area and Changsha–Zhuzhou–Xiangtan urban agglomeration. The synthetic control method is employed as an estimation method. The results show that policy has positive impacts on economic development and SO₂ emission reduction in the pilot regions but cannot improve wastewater treatment. Compared to large cities, medium-sized and small cities are more sensitive to policies since the large cities have transferred a large number of enterprises with high energy consumption and high emissions to the surrounding medium-sized and small cities. The study also finds that the Wuhan metropolitan area reduces pollution emissions through increasing environmental investment and the efficiency of resource allocation. In the Changsha–Zhuzhou–Xiangtan urban agglomeration, policy triggers green technology innovation to improve the environment and boost the economy. Full article

Graph convolutional networks (GCNs) have demonstrated remarkable effectiveness in processing graph-structured data and have been widely adopted across various domains. Existing methods mitigate over-smoothing through selective aggregation strategies such as attention mechanisms, edge dropout, and neighbor sampling. While some approaches incorporate global structural context, they often underexplore category-aware representations and inter-category differences, which are crucial for enhancing node discriminability. To address these limitations, a novel framework, CA-NodeNet, is proposed for semi-supervised node classification. CA-NodeNet comprises three key components: (1) coarse-grained node feature learning, (2) category-decoupled multi-branch attention, and (3) inter-category difference feature learning. Initially, a GCN-based encoder is employed to aggregate neighborhood information and learn coarse-grained representations. Subsequently, the category-decoupled multi-branch attention module employs a hierarchical multi-branch architecture, in which each branch incorporates category-specific attention mechanisms to project coarse-grained features into disentangled semantic subspaces. Furthermore, a layer-wise intermediate supervision strategy is adopted to facilitate the learning of discriminative category-specific features within each branch. To further enhance node feature discriminability, we introduce an inter-category difference feature learning module. This module first encodes pairwise differences between the category-specific features obtained from the previous stage and then integrates complementary information across multiple feature pairs to refine node representations. Finally, we design a dual-component optimization function that synergistically combines intermediate supervision loss with the final classification objective, encouraging the network to learn robust and fine-grained node representations. Extensive experiments on multiple real-world benchmark datasets demonstrate the superior performance of CA-NodeNet over existing state-of-the-art methods. Ablation studies further validate the effectiveness of each module in contributing to overall performance gains. Full article

Subsea pipelines, operating in high-pressure and high-salinity conditions, face ongoing risks of leakage. Pipeline leaks can pollute the marine environment and, in severe cases, cause safety incidents, endangering human lives and property. Regular integrity inspections of subsea pipelines are critical to prevent corrosion-related leaks. This study develops a magnetic flux leakage (MFL)-based pig for detecting corrosion in subsea pipelines. Using a three-dimensional finite element model, this study analyzes the effects of defect geometry, lift-off distance, and operating speed on MFL signals. It proposes a defect estimation method based on axial peak-to-valley values and radial peak spacing, with inversion accuracy validated against simulation results. This study establishes a theoretical and practical framework for subsea pipeline integrity management, providing an effective solution for corrosion monitoring. Full article

The commercialization of proton-conducting fuel cells (PCFCs) is hindered by the limited electroactivity and durability of cathodes at intermediate temperatures ranging from 400 to 700 °C, a challenge exacerbated by an insufficient understanding of high-entropy perovskite (HEP) materials for oxygen reduction reaction (ORR) optimization. This study introduces an yttrium-doped HEP to address these limitations. A comparative analysis of Ce_0.2−xY_xBa_0.2Sr_0.2La_0.2Ca_0.2CoO_3−δ (x = 0, 0.2; designated as CBSLCC and YBSLCC) revealed that yttrium doping enhanced the ORR activity, reduced the thermal expansion coefficient (19.9 × 10⁻⁶ K⁻¹, 30–900 °C), and improved the thermomechanical compatibility with the BaZr_0.1Ce_0.7Y_0.1Yb_0.1O_3−δ electrolytes. Electrochemical testing demonstrated a peak power density equal to 586 mW cm⁻² at 700 °C, with a polarization resistance equaling 0.3 Ω cm². Yttrium-induced lattice distortion promotes proton adsorption while suppressing detrimental Co spin-state transitions. These findings advance the development of durable, high-efficiency PCFC cathodes, offering immediate applications in clean energy systems, particularly for distributed power generation. Full article

Currently, quantum steganography schemes utilizing the least significant bit (LSB) approach are primarily optimized for fixed-point data processing, yet they encounter precision limitations when handling extended floating-point data structures owing to quantization error accumulation. To overcome precision constraints in quantum data hiding, the EPlsb-MFQS and MVlsb-MFQS quantum steganography algorithms are constructed based on the LSB approach in this study. The multichannel floating-point quantum representation of digital signals (MFQS) model enhances information hiding by augmenting the number of available channels, thereby increasing the embedding capacity of the LSB approach. Firstly, we analyze the limitations of fixed-point signals steganography schemes and propose the conventional quantum steganography scheme based on the LSB approach for the MFQS model, achieving enhanced embedding capacity. Moreover, the enhanced embedding efficiency of the EPlsb-MFQS algorithm primarily stems from the superposition probability adjustment of the LSB approach. Then, to prevent an unauthorized person easily extracting secret messages, we utilize channel qubits and position qubits as novel carriers during quantum message encoding. The secret message is encoded into the signal’s qubits of the transmission using a particular modulo value rather than through sequential embedding, thereby enhancing the security and reducing the time complexity in the MVlsb-MFQS algorithm. However, this algorithm in the spatial domain has low robustness and security. Therefore, an improved method of transferring the steganographic process to the quantum Fourier transformed domain to further enhance security is also proposed. This scheme establishes the essential building blocks for quantum signal processing, paving the way for advanced quantum algorithms. Compared with available quantum steganography schemes, the proposed steganography schemes achieve significant improvements in embedding efficiency and security. Finally, we theoretically delineate, in detail, the quantum circuit design and operation process. Full article

This study presents a comprehensive analysis of the microphysical structures of Meiyu heavy rainfall (near-surface rainfall intensity > 8 mm/h) across different life stages in the Yangtze-Huaihe River Valley (YHRV). We classified the heavy rainfall events into three life stages of developing, mature, and dissipating using ERA5 reanalysis and IMERG precipitation estimates, and examined vertical microphysical structures using Dual-frequency Precipitation Radar (DPR) data from the Global Precipitation Measurement (GPM) satellite during the Meiyu period from 2014 to 2023. The results showed that convective heavy rainfall during the mature stage exhibits peak radar reflectivity and surface rainfall rates, with the largest near-surface mass weighted diameter (D_m ≈ 1.8 mm) and the smallest droplet concentration (dBN_w ≈ 38). Downdrafts in the dissipating stage preferentially remove large ice particles, whereas sustained moisture influx stabilizes droplet concentrations. Stratiform heavy rainfall, characterized by weak updrafts, displays narrower particle size distributions. During dissipation, particle breakups dominate, reducing D_m while increasing dBN_w. The analysis of the relationship between microphysical parameters and rainfall rate revealed that convective heavy rainfall shows synchronized growth of D_m and dBN_w during the developing stage, with D_m peaking at about 2.1 mm near 70 mm/h before stabilizing in the mature stage, followed by small-particle dominance in the dissipating stage. In contrast, stratiform rainfall exhibits a “small size, high concentration” regime, where the rainfall rate correlates primarily with increasing dBN_w. Additionally, convective heavy rainfall demonstrates about 22% higher precipitation efficiency than stratiform systems, while stratiform rainfall shows a 25% efficiency surge during the dissipation stage compared to other stages. Full article

This study examines a Mei-Yu rainfall event using rain gauges (RG) and OTT Parsivel disdrometers to observe precipitation characteristics and raindrop size distributions (RSD), with comparisons made against Weather Research and Forecasting (WRF) model simulations. Results show that Parsivel-derived rain rates (RR) are slightly underestimated relative to RG measurements. Both observations and simulations identify 1–3 mm raindrops as the dominant precipitation contributors, though the model overestimates small and large drop contributions. At low RR, decreased small-drop and increased large-drop concentrations cause corresponding leftward and rightward RSD shifts with decreasing altitude—a pattern well captured by simulations. However, at elevated rainfall rates, the simulated concentration of large raindrops shows no significant increase, resulting in negligible rightward shifting of RSD in the model outputs. Autoconversion from cloud droplets to raindrops (ATcr), collision and breakup between raindrops (AGrr), ice melting (MLir), and evaporation of raindrops (VDrv) contribute more to the number density of raindrops. At 0.1 < RR < 1 mm·h⁻¹, ATcr dominates, while VDrv peaks in this intensity range before decreasing. At higher intensities (RR > 20 mm·h⁻¹), AGrr contributes most, followed by MLir. When the RR is high enough, the breakup of raindrops plays a more important role than collision, leading to a decrease in the number density of raindrops. The overestimation of raindrop breakup from the numerical parameterization may be one of the reasons why the RSD does not shift significantly to the right toward the surface under the heavy RR grade. The RSD near the surface varies with the RR and characterizes surface precipitation well. Toward the surface, ATcr and VDrv, but not AGrr, become similar when precipitation approaches. Full article

Meiyu is a critical component of the summer rainy season over the Yangtze–Huaihe River Basin (YHRB) in China, and the Meiyu onset date (MOD), serving as a key indicator of Meiyu, has garnered substantial attention. This article demonstrates an in-phase relationship between MOD and the preceding spring Barents–Kara Seas ice concentration (BKSIC) during 1979–2023. Specifically, the loss of spring BKSIC promotes an earlier MOD. Further analysis indicates that decreased spring BKSIC reduces the reflection of shortwave radiation, thereby enhancing oceanic solar radiation absorption and warming sea surface temperature (SST) in spring. The warming SST persists into summer and induces significant deep warming in the BKS through enhanced upward longwave radiation. The BKS deep warming triggers a wave train propagating southeastward to the East Asia–Northwest Pacific region, leading to a strengthened East Asian Subtropical Jet and an intensified Western North Pacific Subtropical High in summer. Under these conditions, the transport of warm and humid airflows into the YHRB is enhanced, promoting convective instability through increased low-level warming and humidity, combined with enhanced wind shear, which jointly contribute to an earlier MOD. These results may advance the understanding of MOD variability and provide valuable information for disaster prevention and mitigation. Full article

Catastrophic floods in monsoon-driven river systems pose significant challenges to flood resilience. In July 2020, China’s Huai River Basin (HRB) encountered an unprecedented basin-wide flood event characterized by anomalous southward displacement of the rain belt. This event established a new historical record with the three typical hydrological stations (Wangjiaba, Runheji, and Lutaizi sections) along the mainstem of the Huai River exceeded their guaranteed water levels within 11 h and synchronously reached peak flood levels within a 9-h window, whereas the inter-station lag times during the 2003 and 2007 floods ranged from 24 to 48 h, causing a critical emergency in the flood defense. By integrating operational hydrological data, meteorological reports, and empirical rainfall-runoff model schemes for the Meiyu periods of 2003, 2007, and 2020, this research systematically dissects the 2020 flood’s spatial composition patterns. Comparative analyses across spatiotemporal rainfall distribution, intensity metrics, and flood peak response dynamics reveal distinct characteristics of southward-shifted torrential rain and flood variability. The findings provide critical technical guidance for defending against extreme weather events and unprecedented hydrological disasters, directly supporting revisions to flood control planning in the Huai River Ecological and Economic Zone. Full article

In sheep production, due to the limitations of breeding conditions, the uteri of ewes are often infected with bacteria, resulting in the failure of embryo implantation or loss, causing huge losses to the sheep industry. Therefore, in this study, by using RT-qPCR, Western blot, and immunofluorescence, we investigated the effects of LPS infusion on the immune microenvironment and endometrial receptivity, which play an important role in the process of embryo implantation in ruminants, during the three critical periods of embryo implantation in sheep. The results showed that LPS infusion at day 12, day 16, and day 20 significantly increased the expression of Th1 cytokines (TNF-α, IL-1β, IL-8, IL-6), while significantly decreasing the expression of Th2 cytokines (IL-4 and IL-10) and disrupting the expression of implantation factors, such as ITGB3, ITGB5, VEGF, and LIF, in the endometrial tissues of sheep. Additionally, the protein expression level of TLR4 and the phosphorylation level of ERK were significantly elevated at day 12, day 16, and day 20 after LPS infusion, suggesting that LPS may impair endometrial receptivity through the TLR4/ERK pathway. Validation was conducted in a receptive model of sEECs using TLR4 and ERK phosphorylation inhibitors. Compared with the LPS group, TLR4 and ERK phosphorylation inhibitors significantly reduced the expression of TLR4 and p-ERK, down-regulated Th1 cytokines, up-regulated Th2 cytokines, and alleviated the disruption of genes for attachment. Treatment with 50 μM PTE can significantly alleviate the abnormal expression of implantation genes caused by LPS, and its mechanism may be related to the regulation of the ERK signaling pathway. Full article

To expand the operating frequency bands of the Doherty power amplifier (DPA), this paper proposes a dual-mode multi-band DPA design method employing impedance-and-phase constrained optimization based on reciprocal gate bias. By introducing the concept of reciprocal gate bias, the operating mode is switched by swapping the gate biases of the carrier and peaking amplifiers of the DPA, which effectively extend the operating frequency band without modifying the load modulation network. Furthermore, multiple impedance constraint circles are used to cover the optimum load impedance region obtained from the load-pull simulation. And, the phases required for impedance transformation network (ITN) across the multi-band are determined based on the impedance transformation requirements when the DPA operates in power back-off (PBO) state and saturation state. Then, the ITNs that satisfy the impedance and phase constraints can be optimized and designed. For verification, a dual-mode multi-band DPA, operating in Mode I at 1.96–2.10 GHz and 2.75–2.86 GHz, and in Mode II at 2.49–2.61 GHz and 3.20–3.36 GHz, is designed and fabricated. Measured results show that the output power of the DPA exceeds 43 dBm with corresponding saturated drain efficiencies (DEs) higher than 50% in both modes. For 6 dB PBO, the DEs are 49.4–55.7% and 49.8–51.7% in Mode I, whereas in Mode II, they range from 51.2% to 52.4% and from 50.4% to 53.5%. Moreover, good linearity can be achieved after linearization for 20 MHz modulated signals. Full article